From andrea.brovelli at univ-amu.fr Mon Feb 4 09:22:17 2013 From: andrea.brovelli at univ-amu.fr (andrea brovelli) Date: Mon, 04 Feb 2013 09:22:17 +0100 Subject: [FieldTrip] Error in prepare_freq_matrices.m ? In-Reply-To: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> References: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> Message-ID: <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> Dear all, I have an error while running ft_sourceanalysis. I am analysing a data set over a frequency range which includes 100 frequencies and 60 trials. I get an error due to the definition of the variable Ntrials, which as far as I understand, it is done in prepare_freq_matrices.m at lines 76 -> 85: ------------------------------------------------- % the time-frequency latency has already been squeezed away (see above) if strcmp(freq.dimord, 'chan_freq') Ntrials = 1; elseif strcmp(freq.dimord, 'rpt_chan_freq') Ntrials = length(freq.cumtapcnt); elseif strcmp(freq.dimord, 'rpttap_chan_freq') Ntrials = length(freq.cumtapcnt); else error('unrecognized dimord for frequency data'); end ------------------------------------------------- If the number of trials is less than the number of frequencies, Ntrials = length(freq.cumtapcnt) should be replaced by Ntrials = size(freq.cumtapcnt,1); It is the case ? Thanks a lot Andrea From jan.schoffelen at donders.ru.nl Mon Feb 4 12:01:11 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Mon, 4 Feb 2013 12:01:11 +0100 Subject: [FieldTrip] Error in prepare_freq_matrices.m ? In-Reply-To: <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> References: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> Message-ID: <7C99534A-440F-4B53-BFCC-F0968FF0BB9D@donders.ru.nl> Hi Andrea, This could very well be. Sorry for not getting back to you earlier. Could you create an account on our bugzilla server and file this as a bug? We will then look into it (and fix it) as soon as possible. For the time being, could you work around it by just changing your code locally? Thanks and best wishes, Jan-Mathijs On Feb 4, 2013, at 9:22 AM, andrea brovelli wrote: > > Dear all, > > I have an error while running ft_sourceanalysis. I am analysing a data set over a frequency range which includes 100 frequencies and 60 trials. I get an error due to the definition of the variable Ntrials, which as far as I understand, it is done in prepare_freq_matrices.m at lines 76 -> 85: > > ------------------------------------------------- > % the time-frequency latency has already been squeezed away (see above) > if strcmp(freq.dimord, 'chan_freq') > Ntrials = 1; > elseif strcmp(freq.dimord, 'rpt_chan_freq') > Ntrials = length(freq.cumtapcnt); > elseif strcmp(freq.dimord, 'rpttap_chan_freq') > Ntrials = length(freq.cumtapcnt); > else > error('unrecognized dimord for frequency data'); > end > ------------------------------------------------- > > If the number of trials is less than the number of frequencies, Ntrials = length(freq.cumtapcnt) should be replaced by Ntrials = size(freq.cumtapcnt,1); > > It is the case ? > > Thanks a lot > > Andrea > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Tue Feb 5 22:40:56 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Tue, 5 Feb 2013 21:40:56 +0000 Subject: [FieldTrip] localspheres Message-ID: Hello, I have what is possibly a naïve question, but I can't seem to find anything on the tutorial pages. I'm trying to create a headmodel using the localspheres method, using the output of a segmented MRI. There is a tutorial page for using different types of headmodels, but it references ft_prepare_localspheres - which works, but it appears to have been deprecated. When I try this: hdr=ft_read_header('mydata.ds'); cfg=[]; cfg.method='localspheres'; cfg.grad=hdr.grad; cfg.vol=segmented_mri; vol=ft_prepare_headmodel(cfg, segmentedmri); I get an error at ft_getopt(cfg,'tissue'); Although the documentation for ft_prepare_headmodel states that the only additional field needed by localspheres is "cfg.grad" it seems that cfg.tissue may also be required? If so, how do I set this - I can't find any documentation that explains. I should note that I've run ft_prepare_headmodel successfully using a singleshell method. Thanks, Allison Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Wed Feb 6 09:53:15 2013 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Wed, 6 Feb 2013 09:53:15 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Dear Allison, Thank you for your question. There have been some changes to ft_prepare_headmodel recently (partly implemented by me) and my apologies that the documentation for these changes was not made thoroughly. I assume that you are refering to a very recent FT version. :-) The way that you call ft_prepare_headmodel looks almost correct, except that cfg.vol is not needed. If you have already a 'vol' or 'bnd' , then that can be used as the second input argument to ft_prepare_headmodel, and the 'segmentedmri' is not needed. If you don't already have a 'vol' or 'bnd', then that will be created on the fly within ft_prepare_headmodel from the segmentedmri that you include as second input. However, what are the fields within 'segmentedmri' that you use? If 'brain' or 'scalp' already exist, then those will be found and used by default, and therefore a cfg.tissue is not needed. However, if you have other fields with different names, etc then cfg.tissue should point to the name of the subfield of segmentedmri that you wish to use as the headshape. Please see ft_volumesegment for more details on which tissue types or segmentation types can be computed as output and which can then be used in subsequent functions. Perhaps simply recompute the segmentedmri with the newest version of ft_volumesegment and then it will work? In the meantime, I will update the documentation to make all this more clear. However, one more question. I'm not sure what you mean by the error you get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it will return a default empty variable, and there should not be an error. Can you say exactly what line of what function gives the error, and what the error exactly is? And finally, when you successfully ran singleshell method, was that with the segmentedmri (which would surprise me), or rather with a cfg.headshape option? Cheers, Johanna 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] > Hello, **** > > ** ** > > I have what is possibly a naïve question, but I can’t seem to find > anything on the tutorial pages.**** > > ** ** > > I’m trying to create a headmodel using the localspheres method, using the > output of a segmented MRI.**** > > ** ** > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres – which works, but it appears to have > been deprecated. When I try this:**** > > ** ** > > hdr=ft_read_header(‘mydata.ds’);**** > > cfg=[];**** > > cfg.method=’localspheres’;**** > > cfg.grad=hdr.grad;**** > > cfg.vol=segmented_mri;**** > > vol=ft_prepare_headmodel(cfg, segmentedmri);**** > > ** ** > > I get an error at ft_getopt(cfg,’tissue’);**** > > ** ** > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is “cfg.grad” it seems that > cfg.tissue may also be required? If so, how do I set this – I can’t find > any documentation that explains.**** > > ** ** > > I should note that I’ve run ft_prepare_headmodel successfully using a > singleshell method.**** > > ** ** > > Thanks,**** > > ** ** > > Allison**** > > ** ** > > Allison Nugent, PhD**** > > MRI Physicist**** > > Experimental Therapeutics and Pathophysiology Branch**** > > NIMH/NIH/DHHS**** > > Ph. 301-451-8863**** > > nugenta at mail.nih.gov**** > > ** ** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Wed Feb 6 09:56:29 2013 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Wed, 6 Feb 2013 09:56:29 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Sorry, I meant if you have a 'bnd'. Of course you won't have the 'vol', that is the purpose of calling ft_prepare_headmodel! Johanna 2013/2/6 Johanna Zumer > Dear Allison, > > Thank you for your question. There have been some changes to > ft_prepare_headmodel recently (partly implemented by me) and my apologies > that the documentation for these changes was not made thoroughly. I > assume that you are refering to a very recent FT version. :-) > > The way that you call ft_prepare_headmodel looks almost correct, except > that cfg.vol is not needed. > > If you have already a 'vol' or 'bnd' , then that can be used as the second > input argument to ft_prepare_headmodel, and the 'segmentedmri' is not > needed. > > If you don't already have a 'vol' or 'bnd', then that will be created on > the fly within ft_prepare_headmodel from the segmentedmri that you include > as second input. However, what are the fields within 'segmentedmri' that > you use? If 'brain' or 'scalp' already exist, then those will be found > and used by default, and therefore a cfg.tissue is not needed. However, if > you have other fields with different names, etc then cfg.tissue should > point to the name of the subfield of segmentedmri that you wish to use as > the headshape. Please see ft_volumesegment for more details on which > tissue types or segmentation types can be computed as output and which can > then be used in subsequent functions. Perhaps simply recompute the > segmentedmri with the newest version of ft_volumesegment and then it will > work? > > In the meantime, I will update the documentation to make all this more > clear. > > However, one more question. I'm not sure what you mean by the error you > get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it will > return a default empty variable, and there should not be an error. Can > you say exactly what line of what function gives the error, and what the > error exactly is? > > And finally, when you successfully ran singleshell method, was that with > the segmentedmri (which would surprise me), or rather with a cfg.headshape > option? > > Cheers, > Johanna > > > > > > > > > 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] > >> Hello, **** >> >> ** ** >> >> I have what is possibly a naïve question, but I can’t seem to find >> anything on the tutorial pages.**** >> >> ** ** >> >> I’m trying to create a headmodel using the localspheres method, using the >> output of a segmented MRI.**** >> >> ** ** >> >> There is a tutorial page for using different types of headmodels, but it >> references ft_prepare_localspheres – which works, but it appears to have >> been deprecated. When I try this:**** >> >> ** ** >> >> hdr=ft_read_header(‘mydata.ds’);**** >> >> cfg=[];**** >> >> cfg.method=’localspheres’;**** >> >> cfg.grad=hdr.grad;**** >> >> cfg.vol=segmented_mri;**** >> >> vol=ft_prepare_headmodel(cfg, segmentedmri);**** >> >> ** ** >> >> I get an error at ft_getopt(cfg,’tissue’);**** >> >> ** ** >> >> Although the documentation for ft_prepare_headmodel states that the only >> additional field needed by localspheres is “cfg.grad” it seems that >> cfg.tissue may also be required? If so, how do I set this – I can’t find >> any documentation that explains.**** >> >> ** ** >> >> I should note that I’ve run ft_prepare_headmodel successfully using a >> singleshell method.**** >> >> ** ** >> >> Thanks,**** >> >> ** ** >> >> Allison**** >> >> ** ** >> >> Allison Nugent, PhD**** >> >> MRI Physicist**** >> >> Experimental Therapeutics and Pathophysiology Branch**** >> >> NIMH/NIH/DHHS**** >> >> Ph. 301-451-8863**** >> >> nugenta at mail.nih.gov**** >> >> ** ** >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Lilla.Magyari at mpi.nl Wed Feb 6 10:32:15 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 10:32:15 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> hi Allison, this was a small a bug in FieldTrip a few weeks ago. It has been fixed since then already, so I think if you download the latest version, you can run ft_prepare_headmodel with method 'localspheres' without the specification of tissue-type. In this case, the geometry of the 'brain' tissue will be used for the headmodel by default. Therefore, it will work only if your segmentation contains a binary mask of the brain (i.e. your segmentation should have a 'brain' field with binary values) or if your segmentation contains the probability tissue maps of 'gray','white','csf' tissue. In this later case, the brain mask will be created from gray, white and csf by the function. But actually, if you want to run ft_prepare_headmodel with your version, you can just specify the name of the tissue that is in your segmentation. Best, Lilla > Hello, > > I have what is possibly a naïve question, but I can't seem to find > anything on the tutorial pages. > > I'm trying to create a headmodel using the localspheres method, using the > output of a segmented MRI. > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres - which works, but it appears to have > been deprecated. When I try this: > > hdr=ft_read_header('mydata.ds'); > cfg=[]; > cfg.method='localspheres'; > cfg.grad=hdr.grad; > cfg.vol=segmented_mri; > vol=ft_prepare_headmodel(cfg, segmentedmri); > > I get an error at ft_getopt(cfg,'tissue'); > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is "cfg.grad" it seems that > cfg.tissue may also be required? If so, how do I set this - I can't find > any documentation that explains. > > I should note that I've run ft_prepare_headmodel successfully using a > singleshell method. > > Thanks, > > Allison > > Allison Nugent, PhD > MRI Physicist > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph. 301-451-8863 > nugenta at mail.nih.gov > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From smoratti at psi.ucm.es Wed Feb 6 10:34:23 2013 From: smoratti at psi.ucm.es (STEPHAN MORATTI) Date: Wed, 6 Feb 2013 10:34:23 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: I guess you would need headshape points for the local spheres. Not sure if ft automatically creates a head surface from the segmented MRI. Best Stephan El 05/02/2013 23:25, "Nugent, Allison C. (NIH/NIMH) [E]" < nugenta at mail.nih.gov> escribió: > Hello, **** > > ** ** > > I have what is possibly a naïve question, but I can’t seem to find > anything on the tutorial pages.**** > > ** ** > > I’m trying to create a headmodel using the localspheres method, using the > output of a segmented MRI.**** > > ** ** > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres – which works, but it appears to have > been deprecated. When I try this:**** > > ** ** > > hdr=ft_read_header(‘mydata.ds’);**** > > cfg=[];**** > > cfg.method=’localspheres’;**** > > cfg.grad=hdr.grad;**** > > cfg.vol=segmented_mri;**** > > vol=ft_prepare_headmodel(cfg, segmentedmri);**** > > ** ** > > I get an error at ft_getopt(cfg,’tissue’);**** > > ** ** > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is “cfg.grad” it seems that > cfg.tissue may also be required? If so, how do I set this – I can’t find > any documentation that explains.**** > > ** ** > > I should note that I’ve run ft_prepare_headmodel successfully using a > singleshell method.**** > > ** ** > > Thanks,**** > > ** ** > > Allison**** > > ** ** > > Allison Nugent, PhD**** > > MRI Physicist**** > > Experimental Therapeutics and Pathophysiology Branch**** > > NIMH/NIH/DHHS**** > > Ph. 301-451-8863**** > > nugenta at mail.nih.gov**** > > ** ** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Lilla.Magyari at mpi.nl Wed Feb 6 10:43:38 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 10:43:38 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: <49445.131.174.45.70.1360143818.squirrel@131.174.45.70> hi Johanna and Allison, I think there was a small bug in ft_prepare_headmodel http://bugzilla.fcdonders.nl/show_bug.cgi?id=1679 a few weeks ago which caused this error. It has been fixed already, so if the newest version of FT is used, ft_prepare_headmodel should run now with cfg.method 'localspheres' without cfg.tissue specified. But this depends on the tissues in the segmentation as Johanna wrote. But besides 'brain' and 'scalp', it is also fine if the segmentation contains the probability tissue maps of the cerebro-spinal fluid, the gray and white matter. In this case, brain binary mask will be created by the function from csf,w hite and gray and the geometry of the brain tissue will be used for the head-model. I hope this helps too. Best, Lilla > Sorry, I meant if you have a 'bnd'. Of course you won't have the 'vol', > that is the purpose of calling ft_prepare_headmodel! > > Johanna > > > 2013/2/6 Johanna Zumer > >> Dear Allison, >> >> Thank you for your question. There have been some changes to >> ft_prepare_headmodel recently (partly implemented by me) and my >> apologies >> that the documentation for these changes was not made thoroughly. I >> assume that you are refering to a very recent FT version. :-) >> >> The way that you call ft_prepare_headmodel looks almost correct, except >> that cfg.vol is not needed. >> >> If you have already a 'vol' or 'bnd' , then that can be used as the >> second >> input argument to ft_prepare_headmodel, and the 'segmentedmri' is not >> needed. >> >> If you don't already have a 'vol' or 'bnd', then that will be created on >> the fly within ft_prepare_headmodel from the segmentedmri that you >> include >> as second input. However, what are the fields within 'segmentedmri' >> that >> you use? If 'brain' or 'scalp' already exist, then those will be found >> and used by default, and therefore a cfg.tissue is not needed. However, >> if >> you have other fields with different names, etc then cfg.tissue should >> point to the name of the subfield of segmentedmri that you wish to use >> as >> the headshape. Please see ft_volumesegment for more details on which >> tissue types or segmentation types can be computed as output and which >> can >> then be used in subsequent functions. Perhaps simply recompute the >> segmentedmri with the newest version of ft_volumesegment and then it >> will >> work? >> >> In the meantime, I will update the documentation to make all this more >> clear. >> >> However, one more question. I'm not sure what you mean by the error you >> get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it >> will >> return a default empty variable, and there should not be an error. >> Can >> you say exactly what line of what function gives the error, and what the >> error exactly is? >> >> And finally, when you successfully ran singleshell method, was that with >> the segmentedmri (which would surprise me), or rather with a >> cfg.headshape >> option? >> >> Cheers, >> Johanna >> >> >> >> >> >> >> >> >> 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] >> >>> Hello, **** >>> >>> ** ** >>> >>> I have what is possibly a naïve question, but I can’t seem to find >>> anything on the tutorial pages.**** >>> >>> ** ** >>> >>> I’m trying to create a headmodel using the localspheres method, using >>> the >>> output of a segmented MRI.**** >>> >>> ** ** >>> >>> There is a tutorial page for using different types of headmodels, but >>> it >>> references ft_prepare_localspheres – which works, but it appears to >>> have >>> been deprecated. When I try this:**** >>> >>> ** ** >>> >>> hdr=ft_read_header(‘mydata.ds’);**** >>> >>> cfg=[];**** >>> >>> cfg.method=’localspheres’;**** >>> >>> cfg.grad=hdr.grad;**** >>> >>> cfg.vol=segmented_mri;**** >>> >>> vol=ft_prepare_headmodel(cfg, segmentedmri);**** >>> >>> ** ** >>> >>> I get an error at ft_getopt(cfg,’tissue’);**** >>> >>> ** ** >>> >>> Although the documentation for ft_prepare_headmodel states that the >>> only >>> additional field needed by localspheres is “cfg.grad” it seems that >>> cfg.tissue may also be required? If so, how do I set this – I can’t >>> find >>> any documentation that explains.**** >>> >>> ** ** >>> >>> I should note that I’ve run ft_prepare_headmodel successfully using a >>> singleshell method.**** >>> >>> ** ** >>> >>> Thanks,**** >>> >>> ** ** >>> >>> Allison**** >>> >>> ** ** >>> >>> Allison Nugent, PhD**** >>> >>> MRI Physicist**** >>> >>> Experimental Therapeutics and Pathophysiology Branch**** >>> >>> NIMH/NIH/DHHS**** >>> >>> Ph. 301-451-8863**** >>> >>> nugenta at mail.nih.gov**** >>> >>> ** ** >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From Lilla.Magyari at mpi.nl Wed Feb 6 11:19:31 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 11:19:31 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> References: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> Message-ID: <49498.131.174.45.70.1360145971.squirrel@131.174.45.70> dear all, sorry for the multiply posting. My email browser is not working properly. Lilla > hi Allison, > > this was a small a bug in FieldTrip a few weeks ago. It has been fixed > since then already, so I think if you download the latest version, you can > run ft_prepare_headmodel with method 'localspheres' without the > specification of tissue-type. In this case, the geometry of the 'brain' > tissue will be used for the headmodel by default. Therefore, it will work > only if your segmentation contains a binary mask of the brain (i.e. your > segmentation should have a 'brain' field with binary values) or if your > segmentation contains the probability tissue maps of 'gray','white','csf' > tissue. In this later case, the brain mask will be created from gray, > white and csf by the function. > > But actually, if you want to run ft_prepare_headmodel with your version, > you can just specify the name of the tissue that is in your segmentation. > > Best, > Lilla > > >> Hello, >> >> I have what is possibly a naïve question, but I can't seem to find >> anything on the tutorial pages. >> >> I'm trying to create a headmodel using the localspheres method, using >> the >> output of a segmented MRI. >> >> There is a tutorial page for using different types of headmodels, but it >> references ft_prepare_localspheres - which works, but it appears to have >> been deprecated. When I try this: >> >> hdr=ft_read_header('mydata.ds'); >> cfg=[]; >> cfg.method='localspheres'; >> cfg.grad=hdr.grad; >> cfg.vol=segmented_mri; >> vol=ft_prepare_headmodel(cfg, segmentedmri); >> >> I get an error at ft_getopt(cfg,'tissue'); >> >> Although the documentation for ft_prepare_headmodel states that the only >> additional field needed by localspheres is "cfg.grad" it seems that >> cfg.tissue may also be required? If so, how do I set this - I can't >> find >> any documentation that explains. >> >> I should note that I've run ft_prepare_headmodel successfully using a >> singleshell method. >> >> Thanks, >> >> Allison >> >> Allison Nugent, PhD >> MRI Physicist >> Experimental Therapeutics and Pathophysiology Branch >> NIMH/NIH/DHHS >> Ph. 301-451-8863 >> nugenta at mail.nih.gov >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > From robince at gmail.com Wed Feb 6 12:54:01 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 11:54:01 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca Message-ID: Hi all, I am a new fieldtrip user getting started preprocessing a large MEG data set (I am in Glasgow and the data was collected at CCNi). I think I am slowly getting to grips with all the steps necessary, but I have a question about the artifact rejection. My undersanding is that the denoise procedure helps correct external sources of noise, so having the signal cleaned in this way should help detect the biological artifacts which are valid magnetic signal at the scalp. But I can't see an easy way to do this since the ft_artifact_* functions want to load the raw continuous data from disk. I can get them to act on the in memory trials data if I set the padding options to 0, but then I get an unacceptable amount of rejections (I guess because of the filter artifacts the padding usually prevents). Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the denoised signal from ft_denoise_pca and if so how? At the moment I am performing the following steps: Load each run Detect jumps with ft_artifact_jump. Concatenate the jump-free trials from all runs together for this block. Visually inspect the reference channels and remove high variance trials (across the whole block). Compute denoise PCA weights using only good reference data (and no MEG jump) trials across the whole block. I would now like to apply the denoise PCA weights, perform other automatic artifact removal on the cleaned data, before further visual inspection and the next steps of ICA etc. Is there any problems with this strategy? Thanks in advance for any advice, Robin From jm.horschig at donders.ru.nl Wed Feb 6 15:02:03 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Wed, 06 Feb 2013 15:02:03 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: Message-ID: <5112625B.9090504@donders.ru.nl> Hi Robin, I think the steps you suggested sound reasonable, but I do not see how you are avoiding the filter artifact issue there, you just postpone it to a later stage. Instead it might be a smart way to 'pad' your trials when defining them with 1s pre- and post (so cut out more than you need); that way all filter artifacts will be in that 1s that you are not interested in anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I understand your question correctly, that solves your problem, doesn't it? Best, Jörn On 2/6/2013 12:54 PM, Robin wrote: > Hi all, > > I am a new fieldtrip user getting started preprocessing a large MEG > data set (I am in Glasgow and the data was collected at CCNi). > > I think I am slowly getting to grips with all the steps necessary, but > I have a question about the artifact rejection. > > My undersanding is that the denoise procedure helps correct external > sources of noise, so having the signal cleaned in this way should help > detect the biological artifacts which are valid magnetic signal at the > scalp. But I can't see an easy way to do this since the ft_artifact_* > functions want to load the raw continuous data from disk. I can get > them to act on the in memory trials data if I set the padding options > to 0, but then I get an unacceptable amount of rejections (I guess > because of the filter artifacts the padding usually prevents). > > Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the > denoised signal from ft_denoise_pca and if so how? > > At the moment I am performing the following steps: > > Load each run > Detect jumps with ft_artifact_jump. > Concatenate the jump-free trials from all runs together for this block. > > Visually inspect the reference channels and remove high variance > trials (across the whole block). > Compute denoise PCA weights using only good reference data (and no MEG > jump) trials across the whole block. > > I would now like to apply the denoise PCA weights, perform other > automatic artifact removal on the cleaned data, before further visual > inspection and the next steps of ICA etc. > > Is there any problems with this strategy? > > Thanks in advance for any advice, > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands From robince at gmail.com Wed Feb 6 15:07:30 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 14:07:30 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: <5112625B.9090504@donders.ru.nl> References: <5112625B.9090504@donders.ru.nl> Message-ID: Hi Jörn, Thanks very much. Yes I think that will solve the problem - I hadn't realised I could use negative trial padding values. What I had just got working was as similar approach extracting larger trials at first and then manually making a new trl defintion: % artifact detection tmpcfg = []; tmpcfg.continuous = 'no'; % some trials are excluded tmpcfg.trl = run_clean.sampleinfo; tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + round(filterpad*run_clean.fsample); tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - round(filterpad*run_clean.fsample); [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); which seemed to work but the trlpadding option definitely looks cleaner! Thanks, Robin On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" wrote: > Hi Robin, > > I think the steps you suggested sound reasonable, but I do not see how you > are avoiding the filter artifact issue there, you just postpone it to a > later stage. Instead it might be a smart way to 'pad' your trials when > defining them with 1s pre- and post (so cut out more than you need); that > way all filter artifacts will be in that 1s that you are not interested in > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > understand your question correctly, that solves your problem, doesn't it? > > Best, > Jörn > > > > On 2/6/2013 12:54 PM, Robin wrote: >> >> Hi all, >> >> I am a new fieldtrip user getting started preprocessing a large MEG >> data set (I am in Glasgow and the data was collected at CCNi). >> >> I think I am slowly getting to grips with all the steps necessary, but >> I have a question about the artifact rejection. >> >> My undersanding is that the denoise procedure helps correct external >> sources of noise, so having the signal cleaned in this way should help >> detect the biological artifacts which are valid magnetic signal at the >> scalp. But I can't see an easy way to do this since the ft_artifact_* >> functions want to load the raw continuous data from disk. I can get >> them to act on the in memory trials data if I set the padding options >> to 0, but then I get an unacceptable amount of rejections (I guess >> because of the filter artifacts the padding usually prevents). >> >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the >> denoised signal from ft_denoise_pca and if so how? >> >> At the moment I am performing the following steps: >> >> Load each run >> Detect jumps with ft_artifact_jump. >> Concatenate the jump-free trials from all runs together for this block. >> >> Visually inspect the reference channels and remove high variance >> trials (across the whole block). >> Compute denoise PCA weights using only good reference data (and no MEG >> jump) trials across the whole block. >> >> I would now like to apply the denoise PCA weights, perform other >> automatic artifact removal on the cleaned data, before further visual >> inspection and the next steps of ICA etc. >> >> Is there any problems with this strategy? >> >> Thanks in advance for any advice, >> >> Robin >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > -- > Jörn M. Horschig > PhD Student > Donders Institute for Brain, Cognition and Behaviour > Centre for Cognitive Neuroimaging > Radboud University Nijmegen > Neuronal Oscillations Group > FieldTrip Development Team > > P.O. Box 9101 > NL-6500 HB Nijmegen > The Netherlands > > Contact: > E-Mail: jm.horschig at donders.ru.nl > Tel: +31-(0)24-36-68493 > Web: http://www.ru.nl/donders > > Visiting address: > Trigon, room 2.30 > Kapittelweg 29 > NL-6525 EN Nijmegen > The Netherlands > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From stephen.whitmarsh at gmail.com Wed Feb 6 15:17:39 2013 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Wed, 6 Feb 2013 15:17:39 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: Dear Robin, Please allow me to refer you to the excellent documentation on (negative) padding and artifact rejection in this gorgeous didactical masterpiece, a joy to behold: ***** http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection***** ;-) Stephen On 6 February 2013 15:07, Robin wrote: > Hi Jörn, > > Thanks very much. Yes I think that will solve the problem - I hadn't > realised I could use negative trial padding values. > What I had just got working was as similar approach extracting larger > trials at first and then manually making a new trl defintion: > > % artifact detection > tmpcfg = []; > tmpcfg.continuous = 'no'; % some trials are excluded > tmpcfg.trl = run_clean.sampleinfo; > tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + round(filterpad*run_clean.fsample); > tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - round(filterpad*run_clean.fsample); > > [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); > > which seemed to work but the trlpadding option definitely looks cleaner! > > Thanks, > > Robin > > On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" > wrote: > > Hi Robin, > > > > I think the steps you suggested sound reasonable, but I do not see how > you > > are avoiding the filter artifact issue there, you just postpone it to a > > later stage. Instead it might be a smart way to 'pad' your trials when > > defining them with 1s pre- and post (so cut out more than you need); that > > way all filter artifacts will be in that 1s that you are not interested > in > > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > > understand your question correctly, that solves your problem, doesn't it? > > > > Best, > > Jörn > > > > > > > > On 2/6/2013 12:54 PM, Robin wrote: > >> > >> Hi all, > >> > >> I am a new fieldtrip user getting started preprocessing a large MEG > >> data set (I am in Glasgow and the data was collected at CCNi). > >> > >> I think I am slowly getting to grips with all the steps necessary, but > >> I have a question about the artifact rejection. > >> > >> My undersanding is that the denoise procedure helps correct external > >> sources of noise, so having the signal cleaned in this way should help > >> detect the biological artifacts which are valid magnetic signal at the > >> scalp. But I can't see an easy way to do this since the ft_artifact_* > >> functions want to load the raw continuous data from disk. I can get > >> them to act on the in memory trials data if I set the padding options > >> to 0, but then I get an unacceptable amount of rejections (I guess > >> because of the filter artifacts the padding usually prevents). > >> > >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the > >> denoised signal from ft_denoise_pca and if so how? > >> > >> At the moment I am performing the following steps: > >> > >> Load each run > >> Detect jumps with ft_artifact_jump. > >> Concatenate the jump-free trials from all runs together for this block. > >> > >> Visually inspect the reference channels and remove high variance > >> trials (across the whole block). > >> Compute denoise PCA weights using only good reference data (and no MEG > >> jump) trials across the whole block. > >> > >> I would now like to apply the denoise PCA weights, perform other > >> automatic artifact removal on the cleaned data, before further visual > >> inspection and the next steps of ICA etc. > >> > >> Is there any problems with this strategy? > >> > >> Thanks in advance for any advice, > >> > >> Robin > >> _______________________________________________ > >> fieldtrip mailing list > >> fieldtrip at donders.ru.nl > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > > > > -- > > Jörn M. Horschig > > PhD Student > > Donders Institute for Brain, Cognition and Behaviour > > Centre for Cognitive Neuroimaging > > Radboud University Nijmegen > > Neuronal Oscillations Group > > FieldTrip Development Team > > > > P.O. Box 9101 > > NL-6500 HB Nijmegen > > The Netherlands > > > > Contact: > > E-Mail: jm.horschig at donders.ru.nl > > Tel: +31-(0)24-36-68493 > > Web: http://www.ru.nl/donders > > > > Visiting address: > > Trigon, room 2.30 > > Kapittelweg 29 > > NL-6525 EN Nijmegen > > The Netherlands > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From robince at gmail.com Wed Feb 6 15:26:01 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 14:26:01 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: Hi Stephen, Thanks very much - I think I get it now. Combined with a f_redefinetrial at the end to cut back just the bit I want it seems to work well. In fact it is working so well that almost all my trials are rejected :) but I think that is another problem! Cheers Robin On Wed, Feb 6, 2013 at 2:17 PM, Stephen Whitmarsh wrote: > Dear Robin, > > Please allow me to refer you to the excellent documentation on (negative) > padding and artifact rejection in this gorgeous didactical masterpiece, a > joy to behold: > ***** http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection > ***** > > ;-) > Stephen > > > On 6 February 2013 15:07, Robin wrote: >> >> Hi Jörn, >> >> Thanks very much. Yes I think that will solve the problem - I hadn't >> realised I could use negative trial padding values. >> What I had just got working was as similar approach extracting larger >> trials at first and then manually making a new trl defintion: >> >> % artifact detection >> tmpcfg = []; >> tmpcfg.continuous = 'no'; % some trials are excluded >> tmpcfg.trl = run_clean.sampleinfo; >> tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + >> round(filterpad*run_clean.fsample); >> tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - >> round(filterpad*run_clean.fsample); >> >> [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); >> >> which seemed to work but the trlpadding option definitely looks cleaner! >> >> Thanks, >> >> Robin >> >> On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" >> wrote: >> > Hi Robin, >> > >> > I think the steps you suggested sound reasonable, but I do not see how >> > you >> > are avoiding the filter artifact issue there, you just postpone it to a >> > later stage. Instead it might be a smart way to 'pad' your trials when >> > defining them with 1s pre- and post (so cut out more than you need); >> > that >> > way all filter artifacts will be in that 1s that you are not interested >> > in >> > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling >> > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I >> > understand your question correctly, that solves your problem, doesn't >> > it? >> > >> > Best, >> > Jörn >> > >> > >> > >> > On 2/6/2013 12:54 PM, Robin wrote: >> >> >> >> Hi all, >> >> >> >> I am a new fieldtrip user getting started preprocessing a large MEG >> >> data set (I am in Glasgow and the data was collected at CCNi). >> >> >> >> I think I am slowly getting to grips with all the steps necessary, but >> >> I have a question about the artifact rejection. >> >> >> >> My undersanding is that the denoise procedure helps correct external >> >> sources of noise, so having the signal cleaned in this way should help >> >> detect the biological artifacts which are valid magnetic signal at the >> >> scalp. But I can't see an easy way to do this since the ft_artifact_* >> >> functions want to load the raw continuous data from disk. I can get >> >> them to act on the in memory trials data if I set the padding options >> >> to 0, but then I get an unacceptable amount of rejections (I guess >> >> because of the filter artifacts the padding usually prevents). >> >> >> >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the >> >> denoised signal from ft_denoise_pca and if so how? >> >> >> >> At the moment I am performing the following steps: >> >> >> >> Load each run >> >> Detect jumps with ft_artifact_jump. >> >> Concatenate the jump-free trials from all runs together for this block. >> >> >> >> Visually inspect the reference channels and remove high variance >> >> trials (across the whole block). >> >> Compute denoise PCA weights using only good reference data (and no MEG >> >> jump) trials across the whole block. >> >> >> >> I would now like to apply the denoise PCA weights, perform other >> >> automatic artifact removal on the cleaned data, before further visual >> >> inspection and the next steps of ICA etc. >> >> >> >> Is there any problems with this strategy? >> >> >> >> Thanks in advance for any advice, >> >> >> >> Robin >> >> _______________________________________________ >> >> fieldtrip mailing list >> >> fieldtrip at donders.ru.nl >> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > >> > >> > >> > -- >> > Jörn M. Horschig >> > PhD Student >> > Donders Institute for Brain, Cognition and Behaviour >> > Centre for Cognitive Neuroimaging >> > Radboud University Nijmegen >> > Neuronal Oscillations Group >> > FieldTrip Development Team >> > >> > P.O. Box 9101 >> > NL-6500 HB Nijmegen >> > The Netherlands >> > >> > Contact: >> > E-Mail: jm.horschig at donders.ru.nl >> > Tel: +31-(0)24-36-68493 >> > Web: http://www.ru.nl/donders >> > >> > Visiting address: >> > Trigon, room 2.30 >> > Kapittelweg 29 >> > NL-6525 EN Nijmegen >> > The Netherlands >> > >> > _______________________________________________ >> > fieldtrip mailing list >> > fieldtrip at donders.ru.nl >> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From jm.horschig at donders.ru.nl Wed Feb 6 15:38:59 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Wed, 06 Feb 2013 15:38:59 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: <51126B03.3030106@donders.ru.nl> only a brilliant mind might have created such a guide - chapeau ^^ On 2/6/2013 3:17 PM, Stephen Whitmarsh wrote: > Dear Robin, > > Please allow me to refer you to the excellent documentation on > (negative) padding and artifact rejection in this gorgeous didactical > masterpiece, a joy to behold: > ***** > http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection ***** > > ;-) > Stephen > > On 6 February 2013 15:07, Robin > wrote: > > Hi Jörn, > > Thanks very much. Yes I think that will solve the problem - I hadn't > realised I could use negative trial padding values. > What I had just got working was as similar approach extracting larger > trials at first and then manually making a new trl defintion: > > % artifact detection > tmpcfg = []; > tmpcfg.continuous = 'no'; % some trials are excluded > tmpcfg.trl = run_clean.sampleinfo; > tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + > round(filterpad*run_clean.fsample); > tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - > round(filterpad*run_clean.fsample); > > [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); > > which seemed to work but the trlpadding option definitely looks > cleaner! > > Thanks, > > Robin > > On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" > > wrote: > > Hi Robin, > > > > I think the steps you suggested sound reasonable, but I do not > see how you > > are avoiding the filter artifact issue there, you just postpone > it to a > > later stage. Instead it might be a smart way to 'pad' your > trials when > > defining them with 1s pre- and post (so cut out more than you > need); that > > way all filter artifacts will be in that 1s that you are not > interested in > > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > > understand your question correctly, that solves your problem, > doesn't it? > > > > Best, > > Jörn > > > > > > > > On 2/6/2013 12:54 PM, Robin wrote: > >> > >> Hi all, > >> > >> I am a new fieldtrip user getting started preprocessing a large MEG > >> data set (I am in Glasgow and the data was collected at CCNi). > >> > >> I think I am slowly getting to grips with all the steps > necessary, but > >> I have a question about the artifact rejection. > >> > >> My undersanding is that the denoise procedure helps correct > external > >> sources of noise, so having the signal cleaned in this way > should help > >> detect the biological artifacts which are valid magnetic signal > at the > >> scalp. But I can't see an easy way to do this since the > ft_artifact_* > >> functions want to load the raw continuous data from disk. I can get > >> them to act on the in memory trials data if I set the padding > options > >> to 0, but then I get an unacceptable amount of rejections (I guess > >> because of the filter artifacts the padding usually prevents). > >> > >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. > on the > >> denoised signal from ft_denoise_pca and if so how? > >> > >> At the moment I am performing the following steps: > >> > >> Load each run > >> Detect jumps with ft_artifact_jump. > >> Concatenate the jump-free trials from all runs together for > this block. > >> > >> Visually inspect the reference channels and remove high variance > >> trials (across the whole block). > >> Compute denoise PCA weights using only good reference data (and > no MEG > >> jump) trials across the whole block. > >> > >> I would now like to apply the denoise PCA weights, perform other > >> automatic artifact removal on the cleaned data, before further > visual > >> inspection and the next steps of ICA etc. > >> > >> Is there any problems with this strategy? > >> > >> Thanks in advance for any advice, > >> > >> Robin > >> _______________________________________________ > >> fieldtrip mailing list > >> fieldtrip at donders.ru.nl > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > > > > -- > > Jörn M. Horschig > > PhD Student > > Donders Institute for Brain, Cognition and Behaviour > > Centre for Cognitive Neuroimaging > > Radboud University Nijmegen > > Neuronal Oscillations Group > > FieldTrip Development Team > > > > P.O. Box 9101 > > NL-6500 HB Nijmegen > > The Netherlands > > > > Contact: > > E-Mail: jm.horschig at donders.ru.nl > > Tel: +31-(0)24-36-68493 > > Web: http://www.ru.nl/donders > > > > Visiting address: > > Trigon, room 2.30 > > Kapittelweg 29 > > NL-6525 EN Nijmegen > > The Netherlands > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Wed Feb 6 21:59:16 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Wed, 6 Feb 2013 20:59:16 +0000 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Thank you so much - I downloaded the newest version of FieldTrip, and it works as expected. I was using one from early in January. To answer some of your questions... When I ran ft_prepare_headmodel with a singleshell method, I used the process described here: http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg?s[]=singleshell cfg=[];cfg.method='singleshell'; vol=ft_prepare_headmodel(cfg,segmentedmri); I have one follow-up question - - I'd like to visualize the results. According to the fieldtrip faq: http://fieldtrip.fcdonders.nl/faq/how_can_i_visualize_the_different_geometrical_objects_that_are_needed_for_forward_and_inverse_computations "The low level plotting functions do not support the multisphere volume conductor models." But the deprecated function doesn't seem to work... I have some other questions regarding coercing my nifti format MRI into the correct coordinate system, but I'll save those for another post. Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From evaladez at psych.udel.edu Wed Feb 6 23:38:06 2013 From: evaladez at psych.udel.edu (Emilio Valadez) Date: Wed, 6 Feb 2013 17:38:06 -0500 Subject: [FieldTrip] Reading events from an EDF file Message-ID: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> Dear FieldTrip users, I am trying to define trials from a continuous EEG data set that was exported from BESA to .edf format, but I'm having trouble reading the events with FieldTrip. The events are located in a separate channel that was appended to the EEG data. After running ft_definetrial with cfg.trialdef.eventtype set to '?' (in order to see the event types and event values in the data), I received the following output: the following events were found in the datafile event type: 'trial' with event values: no trials have been defined yet, see FT_DEFINETRIAL for further help found 720 events created 0 trials the call to "ft_definetrial" took 1 seconds It seems that ft_definetrial is not reading any events except for trials, which should not be present in the data. As a comparison, I opened the data set with eeglab, which did read the events properly, leading me to believe that the event information is in fact part of the file. How can I get ft_definetrial to correctly read the events? Thanks in advance for your help. Emilio -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 7 00:33:42 2013 From: frank.ye.mei at gmail.com (Frank Mei) Date: Wed, 6 Feb 2013 18:33:42 -0500 Subject: [FieldTrip] need example code - activity of condition 1 contrasted with condition 2. Message-ID: Hi All, The tutorial here (http://fieldtrip.fcdonders.nl/tutorial/beamformer) provides example of activity contrasted with baseline, but not activity of condition 1 contrasted with condition 2. Could someone kindly give some example code that contrasts two activities, for example left vs right button pressing? I am thinking about modifying the example code in the tutorial, by turn the code ------- sourceDiff = sourcePost_con; sourceDiff.avg.pow = (sourcePost_con.avg.pow - sourcePre_con.avg.pow) ./ sourcePre_con.avg.pow; -------- into A: -------- sourceDiff = sourceLeft_con; sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) ./ sourceRight_con.avg.pow; -------- or into B: -------- sourceDiff = sourceRight_con; sourceDiff.avg.pow = (sourceRight_con.avg.pow - sourceLeft_con.avg.pow) ./ sourceLeft_con.avg.pow; -------- Not sure if I should use "A" or "B", or something else. thanks, Frank -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at donders.ru.nl Thu Feb 7 08:35:30 2013 From: johanna.zumer at donders.ru.nl (Johanna Zumer) Date: Thu, 7 Feb 2013 08:35:30 +0100 Subject: [FieldTrip] need example code - activity of condition 1 contrasted with condition 2. In-Reply-To: References: Message-ID: Dear Frank, You're on the right way of thinking. I think the answer partially depends on your hypothesis. In the tutorial situation of a Post and Pre, there is the hypothesis that nothing of interest is going on in Pre, and that the experimental manipulation is causing something to occur in Post, and the researcher is asking how Post differs from Pre. In your case of Left and Right, if you are assuming that these are equally interesting experimental manipulations (i.e. neither is the 'baseline' condition), then often the denominator is formed by the average of the two conditions: sourceDiff = sourceLeft_con; % or sourceRight_con, does not matter sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) ./ (0.5* sourceLeft_con.avg.pow +0.5* sourceRight_con.avg.pow); Cheers, Johanna 2013/2/7 Frank Mei > Hi All, > > The tutorial here (http://fieldtrip.fcdonders.nl/tutorial/beamformer) > provides example of activity contrasted with baseline, but not activity of > condition 1 contrasted with condition 2. > > Could someone kindly give some example code that contrasts two activities, > for example left vs right button pressing? > > I am thinking about modifying the example code in the tutorial, by turn > the code > ------- > sourceDiff = sourcePost_con; > sourceDiff.avg.pow = (sourcePost_con.avg.pow - sourcePre_con.avg.pow) ./ > sourcePre_con.avg.pow; > -------- > into A: > -------- > sourceDiff = sourceLeft_con; > sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) > ./ sourceRight_con.avg.pow; > -------- > > or into B: > -------- > sourceDiff = sourceRight_con; > sourceDiff.avg.pow = (sourceRight_con.avg.pow - sourceLeft_con.avg.pow) > ./ sourceLeft_con.avg.pow; > -------- > > Not sure if I should use "A" or "B", or something else. > > thanks, > Frank > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From patrick.jung at esi-frankfurt.de Fri Feb 8 12:06:07 2013 From: patrick.jung at esi-frankfurt.de (Jung, Patrick) Date: Fri, 8 Feb 2013 11:06:07 +0000 Subject: [FieldTrip] ft_freqgrandaverage Message-ID: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> Hi Fieldtrippers, To get a feeling of my data I want to visually inspect the data and look where are differences between the conditions by plotting the grand-averages of TFRs. By using ft_freqgrandaverage I noticed that it gives back NaN if freq entries for one time bin are missing for one subject (n=28). [cid:image003.jpg at 01CE05F4.DAF32510] 1. sSTOP, 2. cAC, 3. diff In my data with variable trial lengths, the shortest poststim time point is around 0.06 s in one condition (cAC) and in one subject but I expect my effects around 0.1-0.35 s. How can I overcome this problem? Is there a more appropriate fieldtrip function or do I have to write a special self-made Matlab code? Here is an excerpt of my code: GA_sSTOP = ft_freqgrandaverage(cfg, AllSubjMat_sSTOP{1,:}); % where AllSubjMat_sSTOP contains TFRs of all subjects in a <1x28 cell> GA_cAC = ft_freqgrandaverage(cfg, AllSubjMat_cAC{1,:}); GA_diff.powspctrm = (GA_sSTOP.powspctrm - GA_cAC.powspctrm) ./ (0.5*GA_sSTOP.powspctrm + 0.5*GA_cAC.powspctrm); Many thanks for your help! Cheers, Patrick -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image003.jpg Type: image/jpeg Size: 11890 bytes Desc: image003.jpg URL: From jm.horschig at donders.ru.nl Fri Feb 8 12:37:58 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 08 Feb 2013 12:37:58 +0100 Subject: [FieldTrip] ft_freqgrandaverage In-Reply-To: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> References: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> Message-ID: <5114E396.5050605@donders.ru.nl> Hi Patrick, I think you have to write this yourself. I never tried though, so maybe there is a way. It's a tricky thing to what you want, so I guess that's why it is not implemented. If you average for some time bins over less repetitions than for others, you get a weaker noise estimate, thereby any effects found or not found could be attributed to plain noise. Put in another way, depending on what analysis you are doing, you might get into trouble with your statistics because of different degrees of freedom per time bin. Also note that for frequency data, power has only positive values with a lower bound of zero, thus noise can only increase the power estimate and not cancel out (so more noise = more power), thus a difference in a later time bin between conditions might be explained by having lower df (fewer observations, more noise) in one condition than in the other, especially if power is greater in the condition with fewer observation. I would strongly suggest to throw out trials which do not reach your time of interest and process only these (i.e. throw out that one subject) unless you really know what you are doing. On the other hand as already mentioned, I never tried and never did this, so maybe there is some neat way to achieve what you want (you'd be probably notice, cause people would reply to this response rather fast). Best, Jörn On 2/8/2013 12:06 PM, Jung, Patrick wrote: > > Hi Fieldtrippers, > > To get a feeling of my data I want to visually inspect the data and > look where are differences between the conditions > > by plotting the grand-averages of TFRs. > > By using *ft_freqgrandaverage*I noticed that it gives back *NaN* > > if freq entries for one time bin are missing for one subject (n=28). > > 1.sSTOP, 2. cAC, 3. diff > > In my data with variable trial lengths, the shortest poststim time > point is around 0.06 s in one condition (cAC) and in one subject > > but I expect my effects around 0.1-0.35 s. > > How can I overcome this problem? Is there a more appropriate fieldtrip > function or do I have to write a special self-made Matlab code? > > Here is an excerpt of my code: > > GA_sSTOP = ft_freqgrandaverage(cfg, AllSubjMat_sSTOP{1,:}); > > % where AllSubjMat_sSTOP contains TFRs of all subjects in a <1x28 cell> > > GA_cAC = ft_freqgrandaverage(cfg, AllSubjMat_cAC{1,:}); > > GA_diff.powspctrm = (GA_sSTOP.powspctrm - GA_cAC.powspctrm) ./ > (0.5*GA_sSTOP.powspctrm + 0.5*GA_cAC.powspctrm); > > Many thanks for your help! > > Cheers, > > Patrick > > ** > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: image/jpeg Size: 11890 bytes Desc: not available URL: From robince at gmail.com Fri Feb 8 12:52:09 2013 From: robince at gmail.com (Robin) Date: Fri, 8 Feb 2013 11:52:09 +0000 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? Message-ID: Hello, Having got through the preprocessing I am now investigating source reconstruction. The information on the web site is very useful. This tutorial page: http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed Spatio-temporal EEG/MEG Inverse Solver which looks interesting but I wondered if this method was actually implemented in fieldtrip (or elsewhere). When I look in minimumnormestimate.m this reference is not listed as one of the methods implemented. Is it available as a different named method? Thanks for any help. Robin From Andrew.Dykstra at med.uni-heidelberg.de Fri Feb 8 13:32:42 2013 From: Andrew.Dykstra at med.uni-heidelberg.de (Andrew R. Dykstra) Date: Fri, 8 Feb 2013 13:32:42 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: Message-ID: Hi Robin, The MNE Python package implements mixed L1/L2 norm solutions. Not sure if something similar exists in Fieldtrip. Cheers, Andy On Feb 8, 2013 1:12 PM, "Robin" wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 13:51:31 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 13:51:31 +0100 Subject: [FieldTrip] Reading events from an EDF file In-Reply-To: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> References: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> Message-ID: <43B67570-A429-4C0B-B936-FCE3B96CF778@donders.ru.nl> Dear Emilio EDF is a fileformat that is widely supported, but that does not have a standard way of storing events in the file. Hence FieldTrip cannot find them. The later EDF+ extension to the fileformat describes how to store annotations (like events) in the file, but this "annotation channel" is not used by many software packages as it is rather clumsy for storing trigger information. Consequently, most software packages have their own ways of storing events. Usually it is dealt with in a very similar manner by adding a binary channel with the same sampling rate and with 0 if there is no, and another value if there is a trigger. The EDF format is written in (short) segments, those are the trials you see in the event structure. If there is a trigger, status, or event channel, you'll have to detect that yourself (e.f. using ft_databrowser). Subsequently you can make a custom "trial function", i.e. a function that reads that channel and defines the data segments to your requirements. Have a look at http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition and http://fieldtrip.fcdonders.nl/tag/trialfun?do=showtag&tag=trialfun best regards, Robert On 6 Feb 2013, at 23:38, Emilio Valadez wrote: > Dear FieldTrip users, > > I am trying to define trials from a continuous EEG data set that was exported from BESA to .edf format, but I’m having trouble reading the events with FieldTrip. The events are located in a separate channel that was appended to the EEG data. > > After running ft_definetrial with cfg.trialdef.eventtype set to ‘?’ (in order to see the event types and event values in the data), I received the following output: > > the following events were found in the datafile > event type: 'trial' with event values: > no trials have been defined yet, see FT_DEFINETRIAL for further help > found 720 events > created 0 trials > the call to "ft_definetrial" took 1 seconds > > It seems that ft_definetrial is not reading any events except for trials, which should not be present in the data. As a comparison, I opened the data set with eeglab, which did read the events properly, leading me to believe that the event information is in fact part of the file. How can I get ft_definetrial to correctly read the events? > > Thanks in advance for your help. > > Emilio > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 13:53:37 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 13:53:37 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: Message-ID: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Hi Robin, The FieldTrip cfg.method='mne' in FT_SOURCEANALYSIS implements an L2 solver, but not an L1 solver. The actual code with more details is in fieldtrip/inverse/minimumnormestimate., best regards, Robert On 8 Feb 2013, at 13:32, Andrew R. Dykstra wrote: > Hi Robin, > > The MNE Python package implements mixed L1/L2 norm solutions. Not sure if something similar exists in Fieldtrip. > > Cheers, > Andy > > On Feb 8, 2013 1:12 PM, "Robin" wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 14:04:07 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 14:04:07 +0100 Subject: [FieldTrip] GE MRI platform 12.0 scans don't import into CTF MRIViewer In-Reply-To: References: Message-ID: <182EAA41-16F5-448D-BFDF-9252C99A6443@donders.ru.nl> Hi Inna, You could try ft_read_mri with as input one of the files that comprises the volume. I never tested it with GE, but for Siemens it is able to figure out the other file names and put the slices in the correct order. The ft_read_mri uses the MATLAB dicom reader for each slice and puts them in a volume. Subsequently you would do ft_volumerealign to assign the head coordinate system, potentially followed by ft_volumereslice. See http://fieldtrip.fcdonders.nl/faq/how_can_i_convert_an_anatomical_mri_from_dicom_into_ctf_format http://fieldtrip.fcdonders.nl/faq/why_does_my_anatomical_mri_show_upside-down_when_plotting_it_with_ft_sourceplot http://fieldtrip.fcdonders.nl/tag/coordinate?do=showtag&tag=coordinate best Robert On 28 Jan 2013, at 17:55, McGowin, Inna wrote: > Hello, > > We have an MRI research scan, GE MRI platform 12.0, that produces scans with some DICOM header fields missing. > These fields are required in order to import the scan into CTF MRIViewer or DICOM_Viewer or some other software. > Does anybody know if these missing fields can be somehow added to the DICOM header? Maybe in Matlab or through some conversion method? > > Thanks! > -- > Inna > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From r.oostenveld at donders.ru.nl Fri Feb 8 14:36:53 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 14:36:53 +0100 Subject: [FieldTrip] Combined EEG and MEG source reconstruction In-Reply-To: References: Message-ID: <8FB714F5-02E8-4B44-96C3-E8472120AD4F@donders.ru.nl> Dear Mushfa In principle it can be made to work, but you'll have to do a little bit of work outside fieldtrip. You would start with 1) ft_prepare_headmodel and ft_prepare_leadfield for the MEG part 2) ft_prepare_headmodel and ft_prepare_leadfield for the EEG part Subsequently you would (manually) concatenate the leadfields of the MEG and EEG. Here you have to make sure that the channel order is consistent with that in your combined data. The resulting structure with combined leadfields can be passed into ft_sourceanalysis as cfg.grid. However, I foresee a problem with the scaling. At this moment FieldTrip is not (yet) very precise in maintaining the correct units throughout. Consequently you might get different units for the EEG and MEG contribution to each dipole, causing weird cancelation effects. You'll just have to check carefully that the leadfield units and the data units consistently scaled between megmag, megplanar and eeg. This brings me to another known problem for the combined vectorview magnetometer and planar gradiometer channels: at this moment the forward computation computes both in T (or fT), whereas the data is represented as T for the magnetometers and T/m for the gradiometers. So the gradiometer leadfields are off by a factor "1/baseline", which is approximately 1/70 if I recall correctly. Many neuromag users use only the planar channels, and therefore don't notice. We are working on fixing the neuromag channel/gradiometer units. That is not as simple as it appears, because conversions of the geometrical dimensions from m to cm or mm also affect the gradiometer baseline. So converting the data from m to mm should result in the planar channel data getting 1000 times smaller, whereas the magnetometer channels shoudl stay the same. See http://bugzilla.fcdonders.nl/show_bug.cgi?id=963 and http://bugzilla.fcdonders.nl/show_bug.cgi?id=963 if you want to follow this. best regards Robert On 28 Jan 2013, at 20:20, Mushfa Yousuf wrote: > Hello Fieldtrippers, > > I am currently doing source analysis using beamformer method in fieldtrip. > The data i work on is a simultaneous measurement of MEG (306) with EEG > (128) on PD patients. > > I was successful in calculating the sources for both the modalities alone. > > I tried according the tutorial "Combined EEG and MEG source reconstruction" and was successful till the estimation > of the lead field. But, then when i want to use the created vol for the > source analysis i have two structures one for EEG and the second one for > MEG. Now, i can only define only one to estimate the sources. How to use > this for both the modalities? Any help would be appreciated. > > With regards > Mushfa > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From alexandre.gramfort at inria.fr Fri Feb 8 14:42:14 2013 From: alexandre.gramfort at inria.fr (Alexandre Gramfort) Date: Fri, 8 Feb 2013 14:42:14 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> References: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Message-ID: Hi Robin, the solver for inverse problem with L1/L2 prior as described in: A Distributed Spatio-temporal EEG/MEG Inverse Solver is not really tractable on real data. My recent work [1] explains how to solve it more efficiently in a few seconds. [1] http://www.ncbi.nlm.nih.gov/pubmed/22421459 This is what I implemented in mne-python: http://martinos.org/mne/auto_examples/inverse/plot_mixed_norm_L21_inverse.html#example-inverse-plot-mixed-norm-l21-inverse-py I have matlab code too but it's less optimized in terms of speed. If you feel like porting it into Fieldtrip that would be much appreciated. See this page that deserves some updates: http://embal.gforge.inria.fr/ If you're into these methods I invite you to have a look at the next improvement using Time-Frequency transforms: http://www.ncbi.nlm.nih.gov/pubmed/23291276 with demo code: http://martinos.org/mne/auto_examples/inverse/plot_time_frequency_mixed_norm_inverse.html#example-inverse-plot-time-frequency-mixed-norm-inverse-py This contribution explains how to correct for amplitude bias and take care of loose orientation constraints when working with cortical source spaces. Best, Alex PS : sorry Robert for advertising mne on the fieldtrip mailing list ... -- Alexandre Gramfort, PhD Assistant Professor, TSI, Telecom ParisTech, CNRS LTCI 37-39 Rue Dareau, 75014 Paris, France http://alexandre.gramfort.net alexandre.gramfort at telecom-paristech.fr On Fri, Feb 8, 2013 at 12:52 PM, Robin wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the e-mail > contains patient information, please contact the Partners Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in error > but does not contain patient information, please contact the sender and properly > dispose of the e-mail. > From nugenta at mail.nih.gov Fri Feb 8 17:35:59 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 8 Feb 2013 16:35:59 +0000 Subject: [FieldTrip] headmodels Message-ID: Hello, I have more simple questions, this time about headmodels. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 22:37:47 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 22:37:47 +0100 Subject: [FieldTrip] MEG toolkit course in Nijmegen - registration is open Message-ID: On April 8-11, 2013 we will host the "Toolkit of Cognitive Neuroscience: advanced data analysis and source modelling of EEG and MEG data" at the Donders Institute in Nijmegen. This 4-day toolkit course will teach you advanced MEG and EEG data analysis skills. Preprocessing, frequency analysis, source reconstruction and various statistical methods will be covered. The toolkit will consist of a number of lectures, followed by hands-on sessions in which you will be tutored through the complete analysis of a MEG data set using the FieldTrip toolbox. There will be time to ask questions and discuss analysis methods pertaining to your reseach questions. In the last hands-on session you will get started with the analysis on the data that you will bring yourself The registration for this toolkit course is now open and can be found on http://www.ru.nl/donders/course-information/2013courses/toolkit-cognitive-4/ The fee for senior participants is € 400. The (PhD) student fee is € 200. Registration fee includes coffee/tea, Dutch sandwich lunches and one dinner. Please note that in the past years the course was oversubscribed and we expect that as well for this year. We will be able to host approximately 40 participants and consequently we are likely to be required to make a selection that is based on the information that you provide on the registration form. Note that neither being a very novice or a very expert in EEG/MEG automatically disqualifies you from participating. We select the participants on basis of their motivation, research background and skills, and whether we expect the course to pay off for the participant (i.e. whether there is a match between course content and the expectations and requirements for fruitfull use of the analysis methods that we'll cover). Furthermore, we try to make a nice group of participants with a homogenous level and with sufficient broad coverage of research interests. The deadline for the initial registration is March 1, 2013. You can have a look at our Facebook page on http://www.facebook.com/fieldtriptoolbox to get an impression from the previous "MEG/EEG toolkit course" in May 2012. Best regards, Robert Oostenveld and Jan-Mathijs Schoffelen From robince at gmail.com Mon Feb 11 12:37:30 2013 From: robince at gmail.com (Robin) Date: Mon, 11 Feb 2013 11:37:30 +0000 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Message-ID: Hi Alexander, Thanks very much for the pointers. I am completely new to the area and was looking at that paper only because it was linked in the Fieldtrip tutorial which I thought would be a good place to start! I will definitely check out all the other useful information you provided. Thanks again, Robin On Fri, Feb 8, 2013 at 1:42 PM, Alexandre Gramfort wrote: > Hi Robin, > > the solver for inverse problem with L1/L2 prior as described in: > > A Distributed Spatio-temporal EEG/MEG Inverse Solver > > is not really tractable on real data. My recent work [1] > explains how to solve it more efficiently in a few seconds. > > [1] http://www.ncbi.nlm.nih.gov/pubmed/22421459 > > This is what I implemented in mne-python: > > http://martinos.org/mne/auto_examples/inverse/plot_mixed_norm_L21_inverse.html#example-inverse-plot-mixed-norm-l21-inverse-py > > I have matlab code too but it's less optimized in terms of speed. If > you feel like porting > it into Fieldtrip that would be much appreciated. See this page that > deserves some updates: > > http://embal.gforge.inria.fr/ > > If you're into these methods I invite you to have a look at the next > improvement using Time-Frequency transforms: > > http://www.ncbi.nlm.nih.gov/pubmed/23291276 > > with demo code: > > http://martinos.org/mne/auto_examples/inverse/plot_time_frequency_mixed_norm_inverse.html#example-inverse-plot-time-frequency-mixed-norm-inverse-py > > This contribution explains how to correct for amplitude bias and take > care of loose orientation constraints when working with cortical > source spaces. > > Best, > Alex > > PS : sorry Robert for advertising mne on the fieldtrip mailing list ... > > -- > Alexandre Gramfort, PhD > Assistant Professor, > TSI, Telecom ParisTech, CNRS LTCI > 37-39 Rue Dareau, 75014 Paris, France > http://alexandre.gramfort.net > alexandre.gramfort at telecom-paristech.fr > > > > > On Fri, Feb 8, 2013 at 12:52 PM, Robin wrote: >> Hello, >> >> Having got through the preprocessing I am now investigating source >> reconstruction. >> >> The information on the web site is very useful. This tutorial page: >> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate >> >> Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed >> Spatio-temporal EEG/MEG Inverse Solver >> >> which looks interesting but I wondered if this method was actually >> implemented in fieldtrip (or elsewhere). When I look in >> minimumnormestimate.m this reference is not listed as one of the >> methods implemented. Is it available as a different named method? >> >> Thanks for any help. >> >> Robin >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> >> >> The information in this e-mail is intended only for the person to whom it is >> addressed. If you believe this e-mail was sent to you in error and the e-mail >> contains patient information, please contact the Partners Compliance HelpLine at >> http://www.partners.org/complianceline . If the e-mail was sent to you in error >> but does not contain patient information, please contact the sender and properly >> dispose of the e-mail. >> > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From polomacnenad at gmail.com Mon Feb 11 17:14:00 2013 From: polomacnenad at gmail.com (Nenad Polomac) Date: Mon, 11 Feb 2013 17:14:00 +0100 Subject: [FieldTrip] problem with ft_singleplotTFR Message-ID: Dear fieldtrip users, I have problem with ft_singleplotTFR. Please have a look on attached image. Has anybody had similar problem? Thank you in advance! Nenad -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: ft_singlplotTFR.jpg Type: image/jpeg Size: 759989 bytes Desc: not available URL: From sophiechen33 at gmail.com Tue Feb 12 11:46:36 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Tue, 12 Feb 2013 11:46:36 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases Message-ID: Dear Fieldtripers I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: *with fieldtrip fieldtrip-20111024 * cfg = []; cfg.name = 'ctf'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path the input is volume data with dimensions [256 256 256] Converting the coordinate system from ctf to spm performing the segmentation on the specified volume segmentedmri = dim: [256 256 256] transform: [4x4 double] coordsys: 'ctf' unit: 'mm' gray: [256x256x256 double] white: [256x256x256 double] csf: [256x256x256 double] cfg: [1x1 struct] *with fieldtrip 'fieldtrip-20121203' * >> cfg = []; cfg.name = 'ctf'; cfg.write = 'no'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 > In ft_defaults at 60 In ft_volumesegment at 130 the input is volume data with dimensions [256 256 256] Converting the coordinate system from ctf to spm Rescaling NIFTI: slope = 0.00342945, intercept = 0 Smoothing by 0 & 8mm.. Coarse Affine Registration.. Fine Affine Registration.. Error using ft_write_mri (line 128) unsupported data format Error in ft_volumesegment (line 274) Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); * and 'fieldtrip-20130210*' cfg = []; cfg.name = 'ctf'; cfg.write = 'no'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); the input is volume data with dimensions [256 256 256] Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path Converting the coordinate system from ctf to spm Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path Rescaling NIFTI: slope = 0.00342945, intercept = 0 Smoothing by 0 & 8mm.. Coarse Affine Registration.. Fine Affine Registration.. Warning: could not open ctf.img > In fileio\private\warning_once at 116 In fileio\private\filetype_check_header at 54 In ft_filetype at 338 In ft_write_mri at 54 In ft_volumesegment at 282 Error using ft_write_mri (line 128) unsupported data format Error in ft_volumesegment (line 282) Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); Please help... :-) it's not convenient to switch fieldtrip version while running scripts... Thanks a lot! cheers Sophie -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 12 12:07:08 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 12 Feb 2013 12:07:08 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases In-Reply-To: References: Message-ID: <3E0FF981-1B4D-46DF-A999-C64AFCB4AE89@donders.ru.nl> Dear Sophie, What happens if you don't specify cfg.name? It seems that you don't need the output to be written to a file anyway (since you also specify cfg.write = 'no'); Best, Jan-Mathijs On Feb 12, 2013, at 11:46 AM, sophie chen wrote: > Dear Fieldtripers > > I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: > with fieldtrip fieldtrip-20111024 > > cfg = []; > cfg.name = 'ctf'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path > > the input is volume data with dimensions [256 256 256] > Converting the coordinate system from ctf to spm > performing the segmentation on the specified volume > segmentedmri = > dim: [256 256 256] > transform: [4x4 double] > coordsys: 'ctf' > unit: 'mm' > gray: [256x256x256 double] > white: [256x256x256 double] > csf: [256x256x256 double] > cfg: [1x1 struct] > > with fieldtrip 'fieldtrip-20121203' > > >> cfg = []; > cfg.name = 'ctf'; > cfg.write = 'no'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 > > In ft_defaults at 60 > In ft_volumesegment at 130 > the input is volume data with dimensions [256 256 256] > Converting the coordinate system from ctf to spm > Rescaling NIFTI: slope = 0.00342945, intercept = 0 > Smoothing by 0 & 8mm.. > Coarse Affine Registration.. > Fine Affine Registration.. > Error using ft_write_mri (line 128) > unsupported data format > Error in ft_volumesegment (line 274) > Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); > > > and 'fieldtrip-20130210' > > cfg = []; > cfg.name = 'ctf'; > cfg.write = 'no'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > the input is volume data with dimensions [256 256 256] > > Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path > > Converting the coordinate system from ctf to spm > > Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path > > Rescaling NIFTI: slope = 0.00342945, intercept = 0 > Smoothing by 0 & 8mm.. > Coarse Affine Registration.. > Fine Affine Registration.. > Warning: could not open ctf.img > > In fileio\private\warning_once at 116 > In fileio\private\filetype_check_header at 54 > In ft_filetype at 338 > In ft_write_mri at 54 > In ft_volumesegment at 282 > Error using ft_write_mri (line 128) > unsupported data format > Error in ft_volumesegment (line 282) > Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); > > Please help... :-) it's not convenient to switch fieldtrip version while running scripts... > Thanks a lot! > > cheers > Sophie > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophiechen33 at gmail.com Tue Feb 12 15:42:48 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Tue, 12 Feb 2013 15:42:48 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases In-Reply-To: References: Message-ID: Hi Jan-Mathijs Thanks for you reply, I just figure out where the problem is coming from (and you are totally right about the * cfg.name = 'ctf' :-) *, completely no sens what I wrote... ) So the problem I had (and I also had some problems while using ft_prepare_headmodel) is coming from the ft_defaults.m, the one from more recent release which is not working for me.... (I always run ft_defaults before executing my programs) So I used the one from the 20111024 release Now, everything is working! I also talk to another Fieldtrip user in our lab, and he couldn't run the fieldtrip functions, unless 'adding fieldtrip directory in path with subfolders' which created conflicts with eeglab toolbox... Is there actually a problem with the ft_defaults.m file itself or is it coming from our Matlab version (2012b)? What should we use instead? Thanks! Cheers, Sophie Dear Sophie, What happens if you don't specify cfg.name? It seems that you don't need the output to be written to a file anyway (since you also specify cfg.write = 'no'); Best, Jan-Mathijs On Feb 12, 2013, at 11:46 AM, sophie chen wrote: >* Dear Fieldtripers*>* *>* I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: *>* with fieldtrip fieldtrip-20111024 *>* *>* cfg = [];*>* cfg.name = 'ctf';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path *>* *>* the input is volume data with dimensions [256 256 256]*>* Converting the coordinate system from ctf to spm*>* performing the segmentation on the specified volume*>* segmentedmri = *>* dim: [256 256 256]*>* transform: [4x4 double]*>* coordsys: 'ctf'*>* unit: 'mm'*>* gray: [256x256x256 double]*>* white: [256x256x256 double]*>* csf: [256x256x256 double]*>* cfg: [1x1 struct]*>* *>* with fieldtrip 'fieldtrip-20121203' *>* *>* >> cfg = [];*>* cfg.name = 'ctf';*>* cfg.write = 'no';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 *>* > In ft_defaults at 60*>* In ft_volumesegment at 130 *>* the input is volume data with dimensions [256 256 256]*>* Converting the coordinate system from ctf to spm*>* Rescaling NIFTI: slope = 0.00342945, intercept = 0*>* Smoothing by 0 & 8mm..*>* Coarse Affine Registration..*>* Fine Affine Registration..*>* Error using ft_write_mri (line 128)*>* unsupported data format*>* Error in ft_volumesegment (line 274)*>* Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); *>* *>* *>* and 'fieldtrip-20130210'*>* *>* cfg = [];*>* cfg.name = 'ctf';*>* cfg.write = 'no';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* the input is volume data with dimensions [256 256 256]*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path *>* *>* Converting the coordinate system from ctf to spm*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path *>* *>* Rescaling NIFTI: slope = 0.00342945, intercept = 0*>* Smoothing by 0 & 8mm..*>* Coarse Affine Registration..*>* Fine Affine Registration..*>* Warning: could not open ctf.img *>* > In fileio\private\warning_once at 116*>* In fileio\private\filetype_check_header at 54*>* In ft_filetype at 338*>* In ft_write_mri at 54*>* In ft_volumesegment at 282 *>* Error using ft_write_mri (line 128)*>* unsupported data format*>* Error in ft_volumesegment (line 282)*>* Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); *>* *>* Please help... :-) it's not convenient to switch fieldtrip version while running scripts...*>* Thanks a lot!*>* *>* cheers*>* Sophie*>* _______________________________________________*>* fieldtrip mailing list*>* fieldtrip at donders.ru.nl *>* http://mailman.science.ru.nl/mailman/listinfo/fieldtrip* Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at gmail.com Wed Feb 13 15:05:39 2013 From: cmuehl at gmail.com (Christian Muehl) Date: Wed, 13 Feb 2013 15:05:39 +0100 Subject: [FieldTrip] Call for Papers: 3rd Workshop on Affective Brain-Computer Interfaces at ACII 2013 Message-ID: ** First Call for Papers ** 3rd Workshop on Affective Brain-Computer Interfaces (aBCI) Workshop at ACII 2013 (September 2-5), Geneva, Switzerland, September 2, 2013 http://hmi.ewi.utwente.nl/abci2013 (coming soon) http://www.acii2013.org During the last decade, brain computer interface (BCI) research has developed into a major research field establishing methodological frameworks, guidelines and a core community of established researchers. Besides proving valuable as a communication channel that bypasses impeded muscular pathways, the novel technology also spurred the investigation of applications for able-bodied users, foremost in the fields of entertainment, health and lifestyle. Affective BCI systems allowing users to control computer games, support relaxation training, or trigger your alarm clock during a shallow sleep stage have been proposed, implemented, and sold. Moreover, the affordable hardware and software tools also encouraged artists to play with the idea of a direct access to people’s most private information: their affective and cognitive states. From these explorations followed a number of interesting installations, suggesting novel ways of human-computer as well as human-human interaction: neurotechnology-based systems that encourage affective self-reflection, the synchronization and empathizing between or the competition of different minds, and the collaborative creation and manipulation of digital multimodal content. The third workshop on affective brain-computer interfaces will explore the advantages and limitations of using neuro-physiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in applications for domains like health, arts, and entertainment. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress and their visions, and thus to spur the development of guidelines and frameworks for affective BCI. Topics of interest include, but are not limited to: • emotion elicitation and data collection for affective BCI • detection of affect and mental state via BCI and other modalities • innovative concepts for adaptive interfaces and affective BCI • demos of aBCI systems and artworks Submission Instructions: * The papers should feature original empirical work, theoretical work, or a well defendable but arguable position of the authors. * Papers will be published in the proceedings of ACII 2013 by IEEE. Papers should be limited to 6 + max 2 additional pages (to be charged €100 per page) * Further details about the submission instructions and format will appear on the ACII 2013 website soon. Important Dates: April 20, 2013: Submission of manuscripts May 20, 2013: Acceptance/Rejection notification June 17, 2013: Submission of camera-ready papers and presenting author’s registration September 2, 2013: Date of the Workshop Programme Chairs: * Brendan Allison, University of California, San Diego, USA * Guilliaume Chanel, Swiss Center for Affective Sciences, Geneva, Switzerland, * Christian Mühl, INRIA Bordeaux - Sud-Ouest, France * Anton Nijholt, Universiteit Twente, the Netherlands Programme Committee: * Egon L. van den Broek, TNO Technical Sciences, Delft, the Netherlands * Anne-Marie Brouwer, TNO Perceptual and Cognitive Systems, Soesterberg, the Netherlands * Stephen Fairclough, John Moores University, Liverpool, UK * Didier Grandjean, Swiss Center for Affective Sciences, Geneva, Switzerland * Hayrettin Gürkök, University of Twente, Enschede, the Netherlands * Jonghwa Kim, University of Augsburg, Germany * Brent Lance, Army Research Laboratory/TNB, Aberdeen Proving Ground, USA, * Fabien Lotte, INRIA Bordeaux - Sud-Ouest, France * Winfried Menninghaus, Freie Universität Berlin, Germany * Gary Garcia Molina, Philips Research North America, Briarcliff, USA * Christopher Honey, Princeton University, USA * Olga Sourina, NanYang Technological University, Singapore * Ioannis Patras, Queen Mary University, London, UK * Mannes Poel, University of Twente, Enschede, the Netherlands * Thorsten Zander, Technische Universität Berlin, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: From brungio at gmail.com Wed Feb 13 20:47:36 2013 From: brungio at gmail.com (Bruno L. Giordano) Date: Wed, 13 Feb 2013 19:47:36 +0000 Subject: [FieldTrip] Job: research assistant/associate, University of Glasgow: Lifelong changes in the cerebral processing of social signals Message-ID: <511BEDD8.9030005@gmail.com> Dear list, apologies for cross-postings. RESEARCH ASSISTANT/ASSOCIATE - Ref: 003341 - University of Glasgow - College of Medical, Veterinary and Life Sciences - Institute of Neuroscience and Psychology. Salary: Grade 6 £26,264-£29,541 or Grade 7 £32,267 - £36,298. To contribute to a MRC-funded project entitled “Lifelong changes in the cerebral processing of social signals”. Specifically, the job requires a review of current literature in relevant fields, development of auditory and visual stimuli and experimental procedures, contributing to the design and programming of the behavioral, fMRI and EEG experiments, recruiting and running the participants, assisting in analyzing the results, and participating in the writing up of the results. This post has funding available until 25 March 2014. Apply online at http://www.glasgow.ac.uk/jobs For informal inquiries, please contact Dr Guillaume Rousselet, guillaume.rousselet at glasgow.ac.uk. The University is committed to equality of opportunity in employment. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Bruno L. Giordano, PhD Institute of Neuroscience and Psychology 58 Hillhead Street, University of Glasgow Glasgow, G12 8QB, Scotland T +44 (0) 141 330 5484 Www: http://www.brunolgiordano.net From marek-b at wp.pl Thu Feb 14 14:14:51 2013 From: marek-b at wp.pl (marek) Date: Thu, 14 Feb 2013 14:14:51 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? Message-ID: Dear all, Is it possible to use ft_topoplotER to draw selected frequency peaks over scalp after FFT analysis? I did frequency analysis of EEG signal in the range 3-42 Hz with the following settings: cfg = []; cfg.output = 'pow'; cfg.channel = 'all'; cfg.method = 'mtmfft'; cfg.taper = 'hanning'; cfg.trials = 'all'; cfg.keeptrials = 'no'; cfg.foilim = [3 42]; fft1 = ft_freqanalysis(cfg, avg1); I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. (I've got _only_ frequency domain data). Is it possible to do it with with the ft_topoplotER function? What settings are needed? I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem to be related to the parameter (the frequency selection) I try to manipulate. Any help will be greatly appreciated! Best, Marek Psychophysiology Laboratory, Jagiellonian University, Krakow (PL) From ploner at lrz.tu-muenchen.de Thu Feb 14 14:26:50 2013 From: ploner at lrz.tu-muenchen.de (Markus Ploner) Date: Thu, 14 Feb 2013 14:26:50 +0100 Subject: [FieldTrip] PhD Student in systems neuroscience/pain research in Munich, Germany Message-ID: Applications are invited for a PhD Student position at the Department of Neurology, Technische Universität München, to work on the cerebral representation of pain by using EEG. The project will focus on theneurophysiological correlates of ongoing pain in healthy human subjects andpatients suffering from chronic pain disorders. Major experimental methods include EEG time-frequency analysis, source analysis and connectivity analysis. The candidate will join a research group dedicated to the multimodal investigation of the cerebral representation of pain (http://www.neurokopfzentrum.med.tum.de/neurologie/426.html) which is part of the TUM-Neuroimaging Center (http://www.tumnic.mri.tum.de ). Applicants should have a background in neuroscience, medicine, psychology, physics, engineering, or other relevantdisciplines. Prior experience in EEG experimental design, data acquisition and analysis as well as time series analysis and MATLAB programming are highly desirable. The position is funded by the Deutsche Forschungsgemeinschaft. Salary will be commensurate with the German TVöD salary scale (EG13, 50%). The position is available for three years. Applications will be considered until the position is filled. Candidates may contact Dr. Markus Ploner for more detailed information or directly e-mail their application (ploner at lrz.tum.de). PD Dr. Markus Ploner Department of Neurology Technische Universität München Munich, Germany ploner at lrz.tum.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From ploner at lrz.tu-muenchen.de Thu Feb 14 14:27:49 2013 From: ploner at lrz.tu-muenchen.de (Markus Ploner) Date: Thu, 14 Feb 2013 14:27:49 +0100 Subject: [FieldTrip] Postdoc in systems neuroscience/pain research in Munich, Germany Message-ID: Applications are invited for a postdoctoral position at the Department of Neurology, Technische Universität München, to work on the cerebral representation of pain by using EEG. The project will focus on theneurophysiological correlates of ongoing pain in healthy human subjects andpatients suffering from chronic pain disorders. Major experimental methods include EEG time-frequency analysis, source analysis and connectivity analysis. The candidate will join a research group dedicated to the multimodal investigation of the cerebral representation of pain (http://www.neurokopfzentrum.med.tum.de/neurologie/426.html) which is part of the TUM-Neuroimaging Center (http://www.tumnic.mri.tum.de ). Applicants should have a PhD or comparable background in neuroscience, medicine, psychology, physics, engineering, or other relevant disciplines. Prior experience in EEG experimental design,data acquisition and analysis is necessary. Advanced skills for time seriesanalysis and MATLAB programming are highly desirable. The position is funded by the Deutsche Forschungsgemeinschaft. Salary will be commensurate with the German TVöD salary scale (EG13). The position is initially available for two years, the secondyear contingent on satisfactory progress. Extension beyond two years may bepossible. Applications will be considered until the position is filled. Candidates may contact Dr. Markus Ploner for more detailed information or directly e-mail their application (ploner at lrz.tum.de). PD Dr. Markus Ploner Department of Neurology Technische Universität München Munich, Germany ploner at lrz.tum.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Thu Feb 14 14:59:03 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Thu, 14 Feb 2013 14:59:03 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? In-Reply-To: References: Message-ID: <511CEDA7.5020000@donders.ru.nl> Hi Marek, it should work like this: /cfg = []; cfg.layout = 'XXX.lay'; cfg.xlim = [18 22]; cfg.zlim = 'maxabs'; figure; ft_topoplotER(cfg, fft1);/ Note that /cfg.xlim /needs to be a vector with two elements. Best, Jörn On 2/14/2013 2:14 PM, marek wrote: > Dear all, > > Is it possible to use ft_topoplotER to draw selected frequency peaks > over scalp after FFT analysis? > > I did frequency analysis of EEG signal in the range 3-42 Hz with the > following settings: > cfg = []; > cfg.output = 'pow'; > cfg.channel = 'all'; > cfg.method = 'mtmfft'; > cfg.taper = 'hanning'; > cfg.trials = 'all'; > cfg.keeptrials = 'no'; > cfg.foilim = [3 42]; > fft1 = ft_freqanalysis(cfg, avg1); > > I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. > (I've got _only_ frequency domain data). > > Is it possible to do it with with the ft_topoplotER function? What > settings are needed? > I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem > to be related to the parameter (the frequency selection) I try to > manipulate. > > Any help will be greatly appreciated! > > Best, > Marek > > Psychophysiology Laboratory, > Jagiellonian University, Krakow (PL) > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From cornabel at googlemail.com Thu Feb 14 15:42:14 2013 From: cornabel at googlemail.com (cornelius abel) Date: Thu, 14 Feb 2013 15:42:14 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? In-Reply-To: <511CEDA7.5020000@donders.ru.nl> References: <511CEDA7.5020000@donders.ru.nl> Message-ID: <511CF7C6.8000605@googlemail.com> If it is not working you might also need to define the parameter as: cfg.parameter='powspctrm' Greetings, Cornelius Am 14.02.2013 14:59, schrieb "Jörn M. Horschig": > Hi Marek, > > it should work like this: > > /cfg = []; > cfg.layout = 'XXX.lay'; > cfg.xlim = [18 22]; > cfg.zlim = 'maxabs'; > figure; > ft_topoplotER(cfg, fft1); / > > Note that /cfg.xlim /needs to be a vector with two elements. > > Best, > Jörn > > > On 2/14/2013 2:14 PM, marek wrote: >> Dear all, >> >> Is it possible to use ft_topoplotER to draw selected frequency peaks >> over scalp after FFT analysis? >> >> I did frequency analysis of EEG signal in the range 3-42 Hz with the >> following settings: >> cfg = []; >> cfg.output = 'pow'; >> cfg.channel = 'all'; >> cfg.method = 'mtmfft'; >> cfg.taper = 'hanning'; >> cfg.trials = 'all'; >> cfg.keeptrials = 'no'; >> cfg.foilim = [3 42]; >> fft1 = ft_freqanalysis(cfg, avg1); >> >> I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. >> (I've got _only_ frequency domain data). >> >> Is it possible to do it with with the ft_topoplotER function? What >> settings are needed? >> I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem >> to be related to the parameter (the frequency selection) I try to >> manipulate. >> >> Any help will be greatly appreciated! >> >> Best, >> Marek >> >> Psychophysiology Laboratory, >> Jagiellonian University, Krakow (PL) >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > -- > Jörn M. Horschig > PhD Student > Donders Institute for Brain, Cognition and Behaviour > Centre for Cognitive Neuroimaging > Radboud University Nijmegen > Neuronal Oscillations Group > FieldTrip Development Team > > P.O. Box 9101 > NL-6500 HB Nijmegen > The Netherlands > > Contact: > E-Mail:jm.horschig at donders.ru.nl > Tel: +31-(0)24-36-68493 > Web:http://www.ru.nl/donders > > Visiting address: > Trigon, room 2.30 > Kapittelweg 29 > NL-6525 EN Nijmegen > The Netherlands > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From ricardoojm at gmail.com Thu Feb 14 16:12:54 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Thu, 14 Feb 2013 16:12:54 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution Message-ID: Dear all, I am very new to fieldtrip and I am experiencing a problem when reading brainvision data. I searched in the mailinglist archives but I didn't find anything that could help me. In case there is information about it somewhere else, I would appreciate if someone can send me a reference. The problem is the following. I am tring to read continuous data from the brainvision analyzer (already preprocessed), but I always have an error which seems to be due to a problem with the identification of the channels resolution. I exported the data from brainvision in ".dat" vectorized format, and I am loading it first with the ft_preprocessing command. Here is the command I am running to load it: cfg = []; cfg.dataset = 'Raw Data Inspection.dat'; eegData = ft_preprocessing(cfg) Then the following warning message is returned, for each of the 56 channels I have in the data: Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > In fileio\private\read_brainvision_vhdr at 50 In ft_read_header at 381 In ft_preprocessing at 394 And at the end, I have the following error: ??? Index exceeds matrix dimensions. Error in ==> read_brainvision_eeg at 150 dat(chan,:) = tmp(begsample:endsample); Error in ==> ft_read_data at 400 dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, chanindx); Error in ==> ft_preprocessing at 573 dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', rawindx, 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', cfg.dataformat) Interestingly, when I read the header file with the "hdr = ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 samples in the data. When checking the header file with the notepad, it says that there are actualy 797740 data points. So, am I realling doing it right? Thank you very much in advance, and best wishes, Ricardo -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at gmail.com Thu Feb 14 17:32:38 2013 From: cmuehl at gmail.com (Christian Muehl) Date: Thu, 14 Feb 2013 17:32:38 +0100 Subject: [FieldTrip] Call for Papers: 3rd Workshop on Affective Brain-Computer Interfaces at ACII 2013 Message-ID: ** Call for Papers ** 3rd Workshop on Affective Brain-Computer Interfaces (aBCI) Workshop at ACII 2013 (September 2-5), Geneva, Switzerland, September 2, 2013 http://hmi.ewi.utwente.nl/abci2013 http://www.acii2013.org During the last decade, brain computer interface (BCI) research has developed into a major research field establishing methodological frameworks, guidelines and a core community of established researchers. Besides proving valuable as a communication channel that bypasses impeded muscular pathways, the novel technology also spurred the investigation of applications for able-bodied users, foremost in the fields of entertainment, health and lifestyle. Affective BCI systems allowing users to control computer games, support relaxation training, or trigger your alarm clock during a shallow sleep stage have been proposed, implemented, and sold. Moreover, the affordable hardware and software tools also encouraged artists to play with the idea of a direct access to people’s most private information: their affective and cognitive states. From these explorations followed a number of interesting installations, suggesting novel ways of human-computer as well as human-human interaction: neurotechnology-based systems that encourage affective self-reflection, the synchronization and empathizing between or the competition of different minds, and the collaborative creation and manipulation of digital multimodal content. The third workshop on affective brain-computer interfaces will explore the advantages and limitations of using neuro-physiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in applications for domains like health, arts, and entertainment. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress and their visions, and thus to spur the development of guidelines and frameworks for affective BCI. Topics of interest include, but are not limited to: • emotion elicitation and data collection for affective BCI • detection of affect and mental state via BCI and other modalities • innovative concepts for adaptive interfaces and affective BCI • demos of aBCI systems and artworks Submission Instructions: * The papers should feature original empirical work, theoretical work, or a well defendable but arguable position of the authors. * Papers will be published in the proceedings of ACII 2013 by IEEE. Papers should be limited to 6 pages. * Further details about the submission instructions and format can be found on the website of ACII 2013. * For further information, contact abci at cs.utwente.nl Important Dates: April 20, 2013: Submission of manuscripts May 20, 2013: Acceptance/Rejection notification June 17, 2013: Submission of camera-ready papers and presenting author’s registration September 2, 2013: Date of the Workshop Programme Chairs: * Brendan Allison, University of California, San Diego, USA * Guilliaume Chanel, Swiss Center for Affective Sciences, Geneva, Switzerland, * Christian Mühl, INRIA Bordeaux - Sud-Ouest, France * Anton Nijholt, Universiteit Twente, the Netherlands Programme Committee: * Egon L. van den Broek, TNO Technical Sciences, Delft, the Netherlands * Anne-Marie Brouwer, TNO Perceptual and Cognitive Systems, Soesterberg, the Netherlands * Stephen Fairclough, John Moores University, Liverpool, UK * Didier Grandjean, Swiss Center for Affective Sciences, Geneva, Switzerland * Hayrettin Gürkök, University of Twente, Enschede, the Netherlands * Jonghwa Kim, University of Augsburg, Germany * Brent Lance, Army Research Laboratory/TNB, Aberdeen Proving Ground, USA, * Fabien Lotte, INRIA Bordeaux - Sud-Ouest, France * Winfried Menninghaus, Freie Universität Berlin, Germany * Gary Garcia Molina, Philips Research North America, Briarcliff, USA * Christopher Honey, Princeton University, USA * Olga Sourina, NanYang Technological University, Singapore * Ioannis Patras, Queen Mary University, London, UK * Mannes Poel, University of Twente, Enschede, the Netherlands * Ed Tan, Universiteit van Amsterdam, the Netherlands * Thorsten Zander, Technische Universität Berlin, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: From Alan.Leggitt at ucsf.edu Fri Feb 15 01:58:32 2013 From: Alan.Leggitt at ucsf.edu (Leggitt, Alan) Date: Fri, 15 Feb 2013 00:58:32 +0000 Subject: [FieldTrip] Support Vector Machine (SVM) for classification of EEG data Message-ID: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> Hello, I'm new to field trip and I am interested in using a support vector machine to classify EEG data. I see that field trip has svm code through the DLMT toolbox. Has anyone had any experience with this and would be willing to share their code for adapting EEG data to use as inputs to the svm class? My current understanding is that others use ICA to extract features to use in the svm. Are there other techniques for feature extraction? Thanks very much. Regards, Alan -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Fri Feb 15 08:04:38 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 15 Feb 2013 08:04:38 +0100 Subject: [FieldTrip] Support Vector Machine (SVM) for classification of EEG data In-Reply-To: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> References: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> Message-ID: <511DDE06.70101@donders.ru.nl> Dear Alan, you should probably start off with going through our tutorials: http://fieldtrip.fcdonders.nl/tutorial/ And for you especially http://fieldtrip.fcdonders.nl/tutorial/multivariateanalysis There are lots of different approaches for feature extraction or reduce feature space, but what works wors best for your data is something you have to test yourself. When you've read the tutorials you probably got a pretty got overview of what is possible in FieldTrip and that you can easily test what you asked for yourself without having others send you their code (you just have to replace a few keywords from the tutorial to test a different method). If you have more specific questions, feel free to ask again. Best, Jörn On 2/15/2013 1:58 AM, Leggitt, Alan wrote: > Hello, > > I'm new to field trip and I am interested in using a support vector > machine to classify EEG data. I see that field trip has svm code > through the DLMT toolbox. Has anyone had any experience with this and > would be willing to share their code for adapting EEG data to use as > inputs to the svm class? My current understanding is that others use > ICA to extract features to use in the svm. Are there other techniques > for feature extraction? > > Thanks very much. > > Regards, > Alan > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 15 08:50:46 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Fri, 15 Feb 2013 08:50:46 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: <94F3F43D-320E-4E49-9BE2-97B7859C1241@donders.ru.nl> Hi Ricardo, It looks as if there's a discrepancy between what FieldTrip extracts from the header, and what is actually in the data file. Did you try another data file to see whether your problem occurs just in this single example or not? I read brainvision data all the time, and haven't encountered issues so far. If your data file is sufficiently small, you could try to .zip it (both data/header/marker files) and upload it to our bugzilla.fcdonders.nl website. You have to create an account, and then you can 'file a bug', describing the problem (basically just copy and paste what you wrote in your original e-mail), and upload the data. Our team than can have a look at it. Best wishes, Jan-Mathijs On Feb 14, 2013, at 4:12 PM, Ricardo Moura wrote: > Dear all, > > I am very new to fieldtrip and I am experiencing a problem when reading brainvision data. I searched in the mailinglist archives but I didn't find anything that could help me. In case there is information about it somewhere else, I would appreciate if someone can send me a reference. > > The problem is the following. I am tring to read continuous data from the brainvision analyzer (already preprocessed), but I always have an error which seems to be due to a problem with the identification of the channels resolution. I exported the data from brainvision in ".dat" vectorized format, and I am loading it first with the ft_preprocessing command. > > Here is the command I am running to load it: > cfg = []; > cfg.dataset = 'Raw Data Inspection.dat'; > eegData = ft_preprocessing(cfg) > > > Then the following warning message is returned, for each of the 56 channels I have in the data: > Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > > In fileio\private\read_brainvision_vhdr at 50 > In ft_read_header at 381 > In ft_preprocessing at 394 > > > And at the end, I have the following error: > ??? Index exceeds matrix dimensions. > > Error in ==> read_brainvision_eeg at 150 > dat(chan,:) = tmp(begsample:endsample); > > Error in ==> ft_read_data at 400 > dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, chanindx); > > Error in ==> ft_preprocessing at 573 > dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', rawindx, > 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', cfg.dataformat) > > > Interestingly, when I read the header file with the "hdr = ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 samples in the data. When checking the header file with the notepad, it says that there are actualy 797740 data points. > > So, am I realling doing it right? > Thank you very much in advance, and best wishes, > Ricardo > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ricardoojm at gmail.com Fri Feb 15 11:52:32 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Fri, 15 Feb 2013 11:52:32 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: Hi Jan-Mathijs, Thank you very much for your reply. I found a mistake of mine in the data export. I didn't export it as ".dat" binary file. I was exporting it as text file. Now, the same script I sent in the first email is working in the sense that the program is properly recognizing the samples in the data (the 797740 sampling points, instead of only 80). Nevertheless, I still have a problem with the channel's resolution. I saw that when exporting the binary files as ieee 32-bit floating, the resolution of the channels is not recorded in the header. So I changed it to the "32-bit signed integer" format, and now I have the resolution (in the header, it appears as "Ch1=AF3,NewRef,4.1322874E-08,µV", under "Channel Infos"), but then, another error message is returned: ??? Error using ==> read_brainvision_eeg at 155 unsupported sub-fileformat I tried to export the data in different ways, but the error persists. I am afraid there is something else wrong in the way I am exporting the data. Could you tell me how I must export the data, or just show me where I can find more detailed specifications about it? I searched through the site and mailing list, and haven't find further information about it. Thanks again, Best wishes, Ricardo On 14 February 2013 16:12, Ricardo Moura wrote: > Dear all, > > I am very new to fieldtrip and I am experiencing a problem when reading > brainvision data. I searched in the mailinglist archives but I didn't find > anything that could help me. In case there is information about it > somewhere else, I would appreciate if someone can send me a reference. > > The problem is the following. I am tring to read continuous data from the > brainvision analyzer (already preprocessed), but I always have an error > which seems to be due to a problem with the identification of the channels > resolution. I exported the data from brainvision in ".dat" vectorized > format, and I am loading it first with the ft_preprocessing command. > > Here is the command I am running to load it: > cfg = []; > cfg.dataset = 'Raw Data Inspection.dat'; > eegData = ft_preprocessing(cfg) > > > Then the following warning message is returned, for each of the 56 > channels I have in the data: > Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > > In fileio\private\read_brainvision_vhdr at 50 > In ft_read_header at 381 > In ft_preprocessing at 394 > > > And at the end, I have the following error: > ??? Index exceeds matrix dimensions. > > Error in ==> read_brainvision_eeg at 150 > dat(chan,:) = tmp(begsample:endsample); > > Error in ==> ft_read_data at 400 > dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, > chanindx); > > Error in ==> ft_preprocessing at 573 > dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', > begsample, 'endsample', endsample, 'chanindx', rawindx, > 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', > cfg.dataformat) > > > Interestingly, when I read the header file with the "hdr = > ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 > samples in the data. When checking the header file with the notepad, it > says that there are actualy 797740 data points. > > So, am I realling doing it right? > Thank you very much in advance, and best wishes, > Ricardo > -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Fri Feb 15 15:51:52 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 15 Feb 2013 14:51:52 +0000 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: Hello, I'm very sorry to repost this, but I'm hoping that someone might be able to give me advice. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI that looks fine. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 15 16:16:52 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Fri, 15 Feb 2013 16:16:52 +0100 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: <13AAF5AE-0977-4C63-B6F8-AE5ED6E6FA7A@donders.ru.nl> Hi Allison, The warning you get is inconsequential and will be fixed soon. Regarding the scale of the data objects, you can use ft_convert_units to get them all in the same scale: hdr.grad = ft_convert_units(hdr.grad); % tries to add a unit field if it does not exist vol = ft_convert_units(vol, hdr.grad.unit); Then you can proceed with the plotting. Best Jan_Mathijs On Feb 15, 2013, at 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: > Hello, I’m very sorry to repost this, but I’m hoping that someone might be able to give me advice. > > I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I’ve scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. > > I’ve imported the MRI like so: > > mri=ft_read_mri(‘ABC_ortho_anat.nii’); > mri=ft_determine_coordsys(mri) > > I re-label the coordinate axes, and set the origin – when it’s done, it has “Neuromag” as the coordsys, although that’s not how it was created. Next: > > cfg=[]; cfg.method=’interactive’ > mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points > cfg=[]; > [segmentedmri]=ft_volumesegment(cfg, mri_realigned) > > During execution I get this warning: > Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img > Even though the file appears to exist – and the program completes and produces a segmented MRI that looks fine. Finally: > > hdr=ft_read_header(‘ACN.ds’); > cfg=[]; cfg.method=’singleshell’; > vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); > figure > ft_plot_vol(vol_realistic);hold on > ft_plot_sens(hdr.grad) > > The plot has the sensor array and the headmodel on different scales – like it didn’t properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I’d ultimately also like to be able to use the localspheres model, and compare results, but since I can’t figure out how to plot that headmodel to check it, I thought I’d start with one that I can plot. > > Thank you! > > Allison Nugent, PhD > MRI Physicist > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph. 301-451-8863 > nugenta at mail.nih.gov > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Fri Feb 15 17:55:51 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 15 Feb 2013 17:55:51 +0100 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: <511E6897.1060101@donders.ru.nl> Dear Allison, I was encountering similar issues the last two days and hope to have fixed some unit conversion bugs. Thus it might be that with the newest FT version, you don't need to manually convert the units anymore as JM suggested. Could you give it a try for me and see whether it works without JMs manual approach in the newest FT version? Best, Jörn On 2/15/2013 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: > > Hello, I'm very sorry to repost this, but I'm hoping that someone > might be able to give me advice. > > I have an MRI in nifti format. It has already been re-aligned with > the fiducial markers. I've scoured the tutorials, but most seem to > deal with MRIs that are already in the ctf coordinate system. > > I've imported the MRI like so: > > mri=ft_read_mri('ABC_ortho_anat.nii'); > > mri=ft_determine_coordsys(mri) > > I re-label the coordinate axes, and set the origin -- when it's done, > it has "Neuromag" as the coordsys, although that's not how it was > created. Next: > > cfg=[]; cfg.method='interactive' > > mri_realigned=ft_volumerealign(cfg,mri) % > to set the fiducial points > > cfg=[]; > > [segmentedmri]=ft_volumesegment(cfg, mri_realigned) > > During execution I get this warning: > > Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img > > Even though the file appears to exist -- and the program completes and > produces a segmented MRIthat looks fine. Finally: > > hdr=ft_read_header('ACN.ds'); > > cfg=[]; cfg.method='singleshell'; > > vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); > > figure > > ft_plot_vol(vol_realistic);hold on > > ft_plot_sens(hdr.grad) > > The plot has the sensor array and the headmodel on different scales -- > like it didn't properly adjust for the difference in mm and cm, even > though the units are specified in the data structures. I'd > ultimately also like to be able to use the localspheres model, and > compare results, but since I can't figure out how to plot that > headmodel to check it, I thought I'd start with one that I can plot. > > Thank you! > > Allison Nugent, PhD > > MRI Physicist > > Experimental Therapeutics and Pathophysiology Branch > > NIMH/NIH/DHHS > > Ph. 301-451-8863 > > nugenta at mail.nih.gov > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From markus.siegel at uni-tuebingen.de Fri Feb 15 18:17:04 2013 From: markus.siegel at uni-tuebingen.de (Markus Siegel) Date: Fri, 15 Feb 2013 18:17:04 +0100 Subject: [FieldTrip] PhD Position - Centre for Integrative Neuroscience (CIN), Tuebingen, Germany Message-ID: <7E2BFDC3-6406-4067-8E66-915714698B52@uni-tuebingen.de> PhD Position - Centre for Integrative Neuroscience (CIN), Tuebingen The laboratory of Markus Siegel at the Centre for Integrative Neuroscience (CIN), Tuebingen (http://www.cin.uni-tuebingen.de/research/siegel.php) is seeking candidates for a PhD position to study large-scale neuronal interactions in humans. The project will focus on ongoing and task-related neuronal oscillations and interactions in the healthy and diseased human brain. Experimental methods include, MEG, psychophysics, spectral analysis, source-reconstruction techniques, and novel connectivity analyses. The candidate will join a stimulating interdisciplinary team that employs a broad spectrum of neurophysiological techniques in animals and humans. The ideal candidate is highly motivated with a strong interest in interdisciplinary research. Candidates must have an MA (or equivalent) in neuroscience, physics, mathematics, psychology, or related fields. Fluency in Matlab is required. Experience in electrophysiology, spectral analysis and/or M/EEG is highly valued. Applications should include a detailed CV, statement of research interests, and names of at least two referees. The position is available for three years. Applications will be considered until the position is filled. Please send applications or informal inquiries to Markus Siegel (markus.siegel at uni-tuebingen.de). -- Dr. Markus Siegel Principal Investigator, Centre for Integrative Neuroscience (CIN), Tübingen From nugenta at mail.nih.gov Fri Feb 15 18:34:44 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 15 Feb 2013 17:34:44 +0000 Subject: [FieldTrip] headmodels In-Reply-To: <511E6897.1060101@donders.ru.nl> References: <511E6897.1060101@donders.ru.nl> Message-ID: It certainly works with the unit conversions in the version I'm currently using, which is from 2/5/2013 - - thanks so much!! As soon as I have a chance, I'll download the latest version to test. Thanks again! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov From: "Jörn M. Horschig" [mailto:jm.horschig at donders.ru.nl] Sent: Friday, February 15, 2013 11:56 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] headmodels Dear Allison, I was encountering similar issues the last two days and hope to have fixed some unit conversion bugs. Thus it might be that with the newest FT version, you don't need to manually convert the units anymore as JM suggested. Could you give it a try for me and see whether it works without JMs manual approach in the newest FT version? Best, Jörn On 2/15/2013 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: Hello, I'm very sorry to repost this, but I'm hoping that someone might be able to give me advice. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI that looks fine. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From ricardoojm at gmail.com Sun Feb 17 19:23:05 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Sun, 17 Feb 2013 19:23:05 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: Hi, I solved this problem already. But as I have seen, the marks for the bad intervals that were defined in the brainvision analyzer are not automatically imported. Is it really right? And how could I use these already defined bad intervals, instead of doing the whole artifact correction again (is there a function in fieldtrip that does it, or do I have to write one myself)? Thank you very much once again, Best regards Ricardo On 15 February 2013 11:52, Ricardo Moura wrote: > Hi Jan-Mathijs, > Thank you very much for your reply. > > I found a mistake of mine in the data export. I didn't export it as ".dat" > binary file. I was exporting it as text file. Now, the same script I sent > in the first email is working in the sense that the program is properly > recognizing the samples in the data (the 797740 sampling points, instead of > only 80). Nevertheless, I still have a problem with the channel's > resolution. > > I saw that when exporting the binary files as ieee 32-bit floating, the > resolution of the channels is not recorded in the header. So I changed it > to the "32-bit signed integer" format, and now I have the resolution (in > the header, it appears as "Ch1=AF3,NewRef,4.1322874E-08,µV", under "Channel > Infos"), but then, another error message is returned: > > ??? Error using ==> read_brainvision_eeg at 155 > unsupported sub-fileformat > > I tried to export the data in different ways, but the error persists. > > I am afraid there is something else wrong in the way I am exporting the > data. Could you tell me how I must export the data, or just show me where I > can find more detailed specifications about it? I searched through the site > and mailing list, and haven't find further information about it. > > Thanks again, > Best wishes, > Ricardo > > > > > > On 14 February 2013 16:12, Ricardo Moura wrote: > >> Dear all, >> >> I am very new to fieldtrip and I am experiencing a problem when reading >> brainvision data. I searched in the mailinglist archives but I didn't find >> anything that could help me. In case there is information about it >> somewhere else, I would appreciate if someone can send me a reference. >> >> The problem is the following. I am tring to read continuous data from the >> brainvision analyzer (already preprocessed), but I always have an error >> which seems to be due to a problem with the identification of the channels >> resolution. I exported the data from brainvision in ".dat" vectorized >> format, and I am loading it first with the ft_preprocessing command. >> >> Here is the command I am running to load it: >> cfg = []; >> cfg.dataset = 'Raw Data Inspection.dat'; >> eegData = ft_preprocessing(cfg) >> >> >> Then the following warning message is returned, for each of the 56 >> channels I have in the data: >> Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! >> > In fileio\private\read_brainvision_vhdr at 50 >> In ft_read_header at 381 >> In ft_preprocessing at 394 >> >> >> And at the end, I have the following error: >> ??? Index exceeds matrix dimensions. >> >> Error in ==> read_brainvision_eeg at 150 >> dat(chan,:) = tmp(begsample:endsample); >> >> Error in ==> ft_read_data at 400 >> dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, >> chanindx); >> >> Error in ==> ft_preprocessing at 573 >> dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', >> begsample, 'endsample', endsample, 'chanindx', rawindx, >> 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', >> cfg.dataformat) >> >> >> Interestingly, when I read the header file with the "hdr = >> ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 >> samples in the data. When checking the header file with the notepad, it >> says that there are actualy 797740 data points. >> >> So, am I realling doing it right? >> Thank you very much in advance, and best wishes, >> Ricardo >> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stidimitriadis at gmail.com Tue Feb 19 10:33:53 2013 From: stidimitriadis at gmail.com (Stavros Dimitriadis) Date: Tue, 19 Feb 2013 11:33:53 +0200 Subject: [FieldTrip] from axial to planar gradiometers Message-ID: Hello to everybody ! I am facing a problem with the transformation of data from axial to planar gradiometers ! I manipulate data recorded from 248- channel BTi (4D Neuroimaging) axial gradiometer system ! I am using cfg.planarmethod='sincos'; The basic problem is the output of ft_megplanar where labels sections have 2x248 labels (vertical & horizontal) but only 248 channels in avg section of the struct. I cannot understand the problem! Can anyone have any idea ? Best regards Dimitriadis Stavros users.auth.gr/~stdimitr/index.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From sammler at cbs.mpg.de Tue Feb 19 13:33:55 2013 From: sammler at cbs.mpg.de (Daniela Sammler) Date: Tue, 19 Feb 2013 13:33:55 +0100 (CET) Subject: [FieldTrip] PhD position on "Intonation in speech" at MPI-CBS in Leipzig, Germany In-Reply-To: <291809232.3656.1361277182103.JavaMail.root@zimbra> Message-ID: <1757739675.3682.1361277235866.JavaMail.root@zimbra> The Max Planck Institute for Human Cognitive and Brain Sciences (MPI-CBS) in Leipzig and its newly established Otto Hahn Group on the "Neural Bases of Intonation in Speech", led by Daniela Sammler, are now offering a PhD position for 3 years in a research project on social aspects of prosody perception in speech using fMRI, MEG and/or TMS. There is much more to human communication than the (de)coding of the explicit, propositional meaning of a vocal speech signal. Between the lines, the vocal output reveals a lot about the speakers’ believes, attitudes (e.g., sympathy, dominance), and communicative intentions (e.g., to warn, to request, to command, to tease). Much of such implicit, illocutionary meaning is conveyed by the “manner of saying”, i.e. the speech prosody, and the interpretation of those subtleties involves a lot of pragmatic inference. There is growing evidence that this latter faculty is distinct from our language abilities such as phonology, syntax and semantics, making it reasonable to assume the involvement of brain areas beyond the well-known fronto-temporal language network in human vocal communication. The goal of the PhD project is to investigate the neural bases of decoding communicative intentions conveyed by prosody (i.e. HOW something is said) in contrast to and in interaction with the decoding of propositional meaning (i.e. WHAT is said). Applicants must have a master degree (or equivalent) in psychology, cognitive sciences, neuroscience, medicine, linguistics, or a related field. Proficiency in oral and written English is necessary. A solid methods background (statistics and programming) as well as prior experience with either fMRI or EEG/MEG are highly desirable. Most importantly, the successful applicant will share our enthusiasm in research questions on prosody and the social brain in vocal communication. Preferable starting date is July 2013. Salary is dependent on experience and based on MPI stipends or equivalent salary according to German Public service regulations. The research will be conducted at the MPI-CBS in Leipzig, Germany, an internationally leading center for cognitive and imaging neuroscience equipped with a 7T MRI scanner, three 3T MRI scanners, a 306 channels MEG system, a TMS system and several EEG suites. All facilities are supported by experienced IT and physicist staff. Our institute (just 190 km or 70 minutes by train, south of Berlin) offers a very international environment, with English and German being the languages spoken in the laboratory. It offers a friendly and generous environment of researchers with diverse backgrounds and with an excellent infrastructure. In order to increase the proportion of female staff members, applications from female scientists are particularly encouraged. Preference will be given to disabled persons with the same qualification. Applications should be sent to the email below as a single, appropriately named pdf email attachment. It should enclose a cover letter (max. 2 pages) that also specifies your future research interests; a CV; up to three representative reprints; and contact details of two personal references. This call remains open until the position is filled. The application should be kindly sent to personal at cbs.mpg.de using the code "PhD 3/13" in the subject. For further details please contact Dr Daniela Sammler, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, sammler at cbs.mpg.de -- Daniela SAMMLER, Ph.D. Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1a 04103 Leipzig phone: +49 341 9940 2679 fax: +49 341 9940 2260 From r.oostenveld at donders.ru.nl Tue Feb 19 14:30:47 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Tue, 19 Feb 2013 14:30:47 +0100 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 References: <002201ce0e9a$e18ab740$a4a025c0$@stijns@fcdonders.ru.nl> Message-ID: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> NIHC-BrainGain Tutorial Day: Tools and novelties in neurotechnology research We invite PhD students, post-docs and senior researchers working in the fields of brain-computer interfacing (BCI), neurofeedback, cognitive neuroscience, neuroinformatics, neurosurgery and related topics to our Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen. The day marks the end of the BrainGain consortium, a six-year joint-effort project on Brain-Computer Interfacing and related technologies. More information on BrainGain can be found here. The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. The 'tools' track is intended to provide both newcomers to the field and experienced researchers with an overview of the tools needed to integrate cognitive neuroscience and advanced invasive and non-invasive technology. Topics range from data streaming to modelling and statistics, and from online fMRI decoding to a crash course in neuroethics., You will also receive some helpful insights for a future career, in case you are interested in applying for a grant in the near future or considering setting up your own company. The 'novelties' track covers a wide range of topics indicating some of the possible topics to be further explored in BCI and neurotechnology research, including genetics, robotics and intracranial recordings. There is no need to stick to one of the two tracks the whole day: you are free to switch between tracks any time. In parallel to the lectures, there will be several interesting demonstrations. The full programme and registration form can be found on the NIHC website (https://www.hersenenencognitie.nl). Please register before 1 March 2013. Participation is free. Lunch and drinks will be provided. We hope to welcome you on March 21st in Nijmegen! Susanna Bicknell Radboud University Nijmegen ____________________________________________________________________ Faculty of Science | Finance and Economic Affairs | Project Management | LC-IMPACT Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | Project Manager T +31 24 3653300 | HG00.616 (Monday, Thursday) Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, Wednesday) Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands Visiting and courier service address: Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From mcgoiv0 at wfu.edu Tue Feb 19 18:47:39 2013 From: mcgoiv0 at wfu.edu (McGowin, Inna) Date: Tue, 19 Feb 2013 12:47:39 -0500 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 In-Reply-To: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> References: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> Message-ID: Hello Susanna, Thanks for the information. Is the tutorial day a local event or it can be accessed through a webinar? Thanks, Inna On Tue, Feb 19, 2013 at 8:30 AM, Robert Oostenveld < r.oostenveld at donders.ru.nl> wrote: > > *NIHC-BrainGain Tutorial Day:* > *Tools and novelties in neurotechnology research * > ** ** > We invite PhD students, post-docs and senior researchers working in the > fields of brain-computer interfacing (BCI), neurofeedback, cognitive > neuroscience, neuroinformatics, neurosurgery and related topics to our > Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen.**** > The day marks the end of the BrainGain consortium, a six-year joint-effort > project on Brain-Computer Interfacing and related technologies. More > information on BrainGain can be found here .**** > ** ** > The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. > The 'tools' track is intended to provide both newcomers to the field and > experienced researchers with an overview of the tools needed to integrate > cognitive neuroscience and advanced invasive and non-invasive technology. > Topics range from data streaming to modelling and statistics, and from > online fMRI decoding to a crash course in neuroethics., You will also > receive some helpful insights for a future career, in case you are > interested in applying for a grant in the near future or considering > setting up your own company.**** > The 'novelties' track covers a wide range of topics indicating some of the > possible topics to be further explored in BCI and neurotechnology research, > including genetics, robotics and intracranial recordings. **** > There is no need to stick to one of the two tracks the whole day: you are > free to switch between tracks any time.**** > ** ** > In parallel to the lectures, there will be several interesting > demonstrations. **** > ** ** > The full programme and registration form can be found on the NIHC website > (https://www.hersenenencognitie.nl)*. *Please register before 1 March > 2013. Participation is free. Lunch and drinks will be provided. **** > ** ** > We hope to welcome you on March 21st in Nijmegen!**** > ** ** > Susanna Bicknell**** > Radboud University Nijmegen**** > ____________________________________________________________________**** > Faculty of Science | Finance and Economic Affairs | Project Management | > LC-IMPACT**** > Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | > Project Manager**** > T +31 24 3653300 | HG00.616 (Monday, Thursday)**** > Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, > Wednesday)**** > Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands**** > Visiting and courier service address: Heyendaalseweg 135, 6525 AJ > Nijmegen, The Netherlands > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -- Inna McGowin -------------- next part -------------- An HTML attachment was scrubbed... URL: From inieuwenhuis at berkeley.edu Wed Feb 20 00:59:13 2013 From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis) Date: Tue, 19 Feb 2013 15:59:13 -0800 Subject: [FieldTrip] cluster analysis correlation Message-ID: <512411D1.6040901@berkeley.edu> Hi all, I've computer correlations (kendall's tau) between EEG power and a behavioral measure over participants (made my own statfun using corr). Now I'd like to use the cluster randomization framework to correct for multiple comparisons. I think it would be valid to shuffle the assignment of EEG power to behavioral measure (which is specified in cfg.design for correlation), make a distribution and test my correlations against that. So shuffle the data so that say EEG power of subect1 get's linked to behavioral measure of subject3, subject2 to subject6 etc, etc, just as we do with t-values shuffling who belongs to which condition. Questions: 1) is this implemented in FieldTrip? How would I do this? Cause the design needs to be shuffled now, this is different from how it would work for a t-test no? 2) If 1== false, Anyone done this, got some tips? 3) Is the above approach I suggest statistically valid? I think testing the tau against zero is not valid (seeing if it is significantly different from zero by making some dummy stat with zeros), but what I suggest is, anyone any thoughts? Thanks!! Ingrid -- Ingrid Nieuwenhuis PhD Postdoctoral Fellow Sleep and Neuroimaging Laboratory Department of Psychology University of California, Berkeley California 94720-1650 Tolman Hall, room 5305 From simonjameslittle at gmail.com Thu Feb 21 14:17:17 2013 From: simonjameslittle at gmail.com (Simon Little) Date: Thu, 21 Feb 2013 13:17:17 +0000 Subject: [FieldTrip] LAYOUT PAIN! Message-ID: Hi, I would be really very grateful for some help regarding setting layout for EEG. Im analysing (or trying to!) some clinical EEG 10-20 data on epilepsy patients and am struggling to get the layout working using the standardised layout files. My channel names concur with those of standard EEG 10 -20 systems (see below) (http://en.wikipedia.org/wiki/10-20_system_(EEG)) Number of questions - 1. The EEG 10-20 standard layout does not seem to match what I thought of (and have checked online) as the standard 10-20 format. Specifically - it includes channels Fpz and Oz for example which aren't on the standard layoutand excludes T3 T4 T5 T6 ( http://en.wikipedia.org/wiki/10-20_system_(EEG)) 2. When I check what my layout should be - >> [type]=ft_senstype(datast_A.label) type = ext1020 Yep there is no layout file for ext1020 in the standard layout templates that seem to come with fieldtrip to use with ft_prepare_layout. Given that all the channels are I need are in the EEG1010 file, I hoped that I could use that instead but then I end up with a layout has 80 odd channels when I only need 21. I'd be so grateful for any help with this! I'm very sorry if its something very simple but I have been looking at it for many many hours without any luck! Many thanks Simon Little My channel names - 'Fp1' 'Fp2' 'F3' 'F4' 'C3' 'C4' 'P3' 'P4' 'O1' 'O2' 'F7' 'F8' 'T3' 'T4' 'T5' 'T6' 'A1' 'A2' 'Fz' 'Cz' 'Pz' EEG1020 - channel names from lay file. 1 -0.485328 1.493835 0.393101 0.294826 Fp1 2 0.000000 1.570696 0.393101 0.294826 Fpz 3 0.485501 1.493884 0.393101 0.294826 Fp2 4 -1.270781 0.923319 0.393101 0.294826 F7 5 -0.652084 0.812357 0.393101 0.294826 F3 6 0.000000 0.785398 0.393101 0.294826 Fz 7 0.652084 0.812357 0.393101 0.294826 F4 8 1.270781 0.923319 0.393101 0.294826 F8 9 -1.570796 0.000000 0.393101 0.294826 T7 10 -0.785398 0.000111 0.393101 0.294826 C3 11 0.000000 0.000200 0.393101 0.294826 Cz 12 0.785398 0.000111 0.393101 0.294826 C4 13 1.570796 -0.000000 0.393101 0.294826 T8 14 -1.270862 -0.923378 0.393101 0.294826 P7 15 -0.652231 -0.811998 0.393101 0.294826 P3 16 -0.000000 -0.785257 0.393101 0.294826 Pz 17 0.652231 -0.811998 0.393101 0.294826 P4 18 1.270862 -0.923378 0.393101 0.294826 P8 19 -0.485359 -1.493930 0.393101 0.294826 O1 20 -0.000000 -1.570796 0.393101 0.294826 Oz 21 0.485359 -1.493930 0.393101 0.294826 O2 22 -1.570796 1.570696 0.393101 0.294826 COMNT 23 1.570796 1.570696 0.393101 0.294826 SCALE -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.herring at fcdonders.ru.nl Thu Feb 21 16:34:31 2013 From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim)) Date: Thu, 21 Feb 2013 16:34:31 +0100 (CET) Subject: [FieldTrip] Notification for users with different channel ordering between participants Message-ID: <004701ce1048$f16daeb0$d4490c10$@herring@fcdonders.ru.nl> Dear Fieldtrip users, It has come to our attention by Philip Ruhnau that when averaging across participants using ft_XXXgrandaverage, due to a bug, no care was taken when the channel-order was different between participants (see http://bugzilla.fcdonders.nl/show_bug.cgi?id=1986). This could occur, for example, when after interpolating channels, the interpolated channels are added to the end of the data and thus changing the channel ordering. Particularly for EEG data this bug could be a problem because often different channels are interpolated for different subjects. No problems should have occurred when merely removing channels. For MEG data, the same problem occurred when using ft_combineplanar after interpolating, for example, vertical or horizontal channels separately. In this instance the wrong channel pairs were combined. However, if channels were interpolated after using ft_combineplanar, or if pairs of horizontal and vertical channels were removed you should have no problems given that the same channels were affected across all participants. The bug has been fixed as of rev. 7519. We strongly advise users that have data containing different channel ordering between participants to download the newest version of Fieldtrip and re-check grand averaged data. Best, Jim -------------- next part -------------- An HTML attachment was scrubbed... URL: From skelly2 at ccny.cuny.edu Mon Feb 25 03:16:15 2013 From: skelly2 at ccny.cuny.edu (Simon Kelly) Date: Sun, 24 Feb 2013 21:16:15 -0500 (EST) Subject: [FieldTrip] Postdoc position in systems/cognitive neuroscience (New York) Message-ID: <201302250216.020279@pelican.admin.ccny.cuny.edu> Applications are invited for a Postdoctoral position in the Neural Systems Lab of Simon Kelly in The City College of New York. The position is funded by the Endeavor Scientists Program of the Child Mind Institute (CMI; http://www.childmind.org/en/endeavor-scientists/) and will be jointly supervised by Simon Kelly (http://bme.ccny.cuny.edu/people/faculty/skelly) and Michael Milham (http://www.childmind.org/en/directory/clinicians/mmilham). The goal of the collaboration is to develop novel paradigms for the study of perception, attention and decision making in humans using EEG and/or fMRI, and to deploy these paradigms in clinical studies of child and adolescent populations in CMI as well as in basic research studies in the Kelly Lab. Any innovative analytic tools and paradigms developed in the course of this position will be made publicly available. Applicants must have a Ph.D. in neuroscience or a related field and have experience and strong interest in cognitive neuroscience. The candidate must have strong analytic skills, be proficient in programming (especially Matlab), and have experience in psychophysics and EEG recording and analysis. Experience with fMRI is a strong plus. The ideal candidate will be reliable, highly motivated and productive, and enjoy working collaboratively. Applicants should send a curriculum vitae, contact information for 2-3 references, and a cover letter with a brief description of past research accomplishments as well as future research interests and career goals to Simon Kelly: skelly2 at ccny.cuny.edu. From paul.sowman at mq.edu.au Mon Feb 25 07:20:55 2013 From: paul.sowman at mq.edu.au (Paul Sowman) Date: Mon, 25 Feb 2013 17:20:55 +1100 Subject: [FieldTrip] FT_CONNECTIVITYANALYIS Message-ID: Hi, which is the appropriate option in FT_CONNECTIVITYANALYIS to implement connectivity analysis via the imaginary part of coherency? The 2011 Computational Intelligence and Neuroscience paper says that the method from the Nolte paper is implemented but I'm not sure which is the right option to do this from the list: coh', coherence, support for freq, freqmvar and source data. For partial coherence also specify cfg.partchannel 'csd', cross-spectral density matrix, can also calculate partial csds - if cfg.partchannel is specified, support for freq and freqmvar data 'plv', phase-locking value, support for freq and freqmvar data 'powcorr', power correlation, support for freq and source data 'amplcorr', amplitude correlation, support for freq and source data 'granger', granger causality, support for freq and freqmvar data 'dtf', directed transfer function, support for freq and freqmvar data 'pdc', partial directed coherence, support for freq and freqmvar data 'psi', phaseslope index, support for freq and freqmvar data 'wpli', weighted phase lag index (signed one, still have to take absolute value to get indication of strength of interaction. Note: measure has positive bias. Use wpli_debiased to avoid this. 'wpli_debiased' debiased weighted phase lag index (estimates squared wpli) 'ppc' pairwise phase consistency 'wppc' weighted pairwise phase consistency G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. -- Paul F Sowman NHMRC Postdoctoral Training Fellow ARC Centre of Excellence for Cognition and its Disorders (CCD) MACQUARIE UNIVERSITY NSW 2109 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Feb 25 09:35:21 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Mon, 25 Feb 2013 09:35:21 +0100 Subject: [FieldTrip] FT_CONNECTIVITYANALYIS In-Reply-To: References: Message-ID: <05D58012-4719-4188-94AF-237EE1D58007@donders.ru.nl> Hi Paul, You should specify cfg.method = 'coh' in conjunction with cfg.complex = 'imag'; I'll update the documentation. Best, Jan-Mathijs On Feb 25, 2013, at 7:20 AM, Paul Sowman wrote: > Hi, which is the appropriate option in FT_CONNECTIVITYANALYIS to implement connectivity analysis via the imaginary part of coherency? The 2011 Computational Intelligence and Neuroscience paper says that the method from the Nolte paper is implemented but I'm not sure which is the right option to do this from the list: > coh', coherence, support for freq, freqmvar and > source data. For partial coherence also > specify cfg.partchannel > 'csd', cross-spectral density matrix, can also > calculate partial csds - > if cfg.partchannel is specified, support for freq and > freqmvar data > 'plv', phase-locking value, support for freq and freqmvar data > 'powcorr', power correlation, support for freq and source data > 'amplcorr', amplitude correlation, support for freq and source data > 'granger', granger causality, support for freq and freqmvar data > 'dtf', directed transfer function, support for freq and freqmvar data > 'pdc', partial directed coherence, support for freq and freqmvar data > 'psi', phaseslope index, support for freq and freqmvar data > 'wpli', weighted phase lag index (signed one, > still have to take absolute value to get indication of > strength of interaction. Note: measure has > positive bias. Use wpli_debiased to avoid > this. > 'wpli_debiased' debiased weighted phase lag index > (estimates squared wpli) > 'ppc' pairwise phase consistency > 'wppc' weighted pairwise phase consistency > > G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. > > -- > Paul F Sowman > NHMRC Postdoctoral Training Fellow > ARC Centre of Excellence for Cognition and its Disorders (CCD) > MACQUARIE UNIVERSITY NSW 2109 > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From polomacnenad at gmail.com Mon Feb 25 10:27:44 2013 From: polomacnenad at gmail.com (Nenad Polomac) Date: Mon, 25 Feb 2013 10:27:44 +0100 Subject: [FieldTrip] loreta in ft_sourceanalysis Message-ID: Dear Fieldtrip users, I would like to ask you which version of loreta is implemented in ft_sourceanalysis. Is it eloreta or sloreta? Thank you in advance! Kind regards! Nenad -------------- next part -------------- An HTML attachment was scrubbed... URL: From pd25588 at berkeley.edu Mon Feb 25 21:23:28 2013 From: pd25588 at berkeley.edu (Pascasie L. Dombert) Date: Mon, 25 Feb 2013 12:23:28 -0800 Subject: [FieldTrip] problem using ft_artifact_muscle Message-ID: Hi all, I am a fieldtrip starter working on an EEG data set. I have a question concerning the muscle artifact detection function and I was hoping that you could help me with this. I am calling the function [cfg,artifact_muscle] = ft_artifact_muscle(cfg,ref_data) as explained in the manual (settings suggested) and get the following error message (see code + error): ________________________________________________________________________________________________ > %detect the MUSCLE artifacts > cfg = []; > cfg.continuous = 'yes'; > % define trial first > cfg.dataset = 'xx’; > cfg.trialfun ='trialfun_general'; > cfg.trialdef.triallength =1; % creates 1-second data segments > cfg.trialdef.ntrials = inf; % i.e. the complete file > cfg = ft_definetrial(cfg); > > % cutoff > cfg.artfctdef.muscle.channel = 'all'; > cfg.artfctdef.muscle.cutoff = 4; > > % algorithmic parameters > cfg.artfctdef.muscle.bpfilter = 'yes'; > cfg.artfctdef.muscle.bpfreq = [110 140]; > cfg.artfctdef.muscle.bpfiltord = 9; > cfg.artfctdef.muscle.bpfilttype = 'but'; > cfg.artfctdef.muscle.hilbert = 'yes'; > cfg.artfctdef.muscle.boxcar = 0.2; > > % feedback > %cfg.artfctdef.muscle.interactive = 'yes'; % to adjust cutoff zvalue if needed > > [cfg, artifact_muscle] = ft_artifact_muscle(cfg,ref_data); > > > > > ERROR: > Subscript indices must either be real positive integers or logicals. > > Error in ft_fetch_data (line 123) > count = count(begsample:endsample); > > Error in ft_artifact_zvalue (line 195) > dat{trlop} = ft_fetch_data(data, 'header', hdr, 'begsample', trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding, 'chanindx', > sgnind, 'checkboundary', strcmp(cfg.continuous,' > Error in ft_artifact_muscle (line 156) > [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data); > _______________________________________________________ However, I only get the error message with the default/suggested values. When I use: cfg.artfctdef.muscle.bpfreq = [110 120]; and cfg.artfctdef.muscle.bpfiltord = 7; I don't get the error message and the script runs properly. Does anyone happen to know what could have let to this problem? Thanks a lot in advance! Best, Leonie -------------- next part -------------- An HTML attachment was scrubbed... URL: From eeguser at hotmail.com Mon Feb 25 22:52:49 2013 From: eeguser at hotmail.com (Subramaniam Iyer) Date: Tue, 26 Feb 2013 00:52:49 +0300 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order Message-ID: Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable : http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance.Subbu -------------- next part -------------- An HTML attachment was scrubbed... URL: From k.kouroupaki at med.uoc.gr Tue Feb 26 13:27:07 2013 From: k.kouroupaki at med.uoc.gr (k.kouroupaki at med.uoc.gr) Date: Tue, 26 Feb 2013 14:27:07 +0200 Subject: [FieldTrip] cfg.latency Message-ID: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> HI everyone! I am a new field trip user and have been using it for EEG SOURCE LOCALIZATION. I have a problem though. When I run the ft_sourceanalysis as: source = ft_sourceanalysis(cfg, freq) I get the following error: ??? Reference to non-existent field 'latency'. Error in ==> prepare_freq_matrices at 55 tbin = nearest(freq.time, cfg.latency); Error in ==> ft_sourceanalysis at 458 [Cf, Cr, Pr, Ntrials, cfg] = prepare_freq_matrices(cfg, data); Could you please help me to localize where the problem is and solve it? Thank you in advance, Kleo ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. From evaladez at psych.udel.edu Tue Feb 26 21:26:30 2013 From: evaladez at psych.udel.edu (Emilio Valadez) Date: Tue, 26 Feb 2013 15:26:30 -0500 Subject: [FieldTrip] Performing time-frequency statistical tests on regional source data Message-ID: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> Dear FieldTrip users, I have an EEG dataset that was reduced to 8 regional sources with BESA and then exported for FieldTrip analysis. I want to perform a statistical test on the regional sources' time-frequency data, comparing two experimental conditions, but I don't know whether it would be appropriate to use ft_freqstatistics (because I have regional sources instead of a complete sensor layout - making cluster formation problematic) or ft_sourcestatistics. Can you suggest a method for performing a statistical test in this situation? Thanks in advance for your help. Best, Emilio Valadez From jan.schoffelen at donders.ru.nl Tue Feb 26 21:36:28 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:36:28 +0100 Subject: [FieldTrip] Performing time-frequency statistical tests on regional source data In-Reply-To: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> References: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> Message-ID: <1ECC8F93-0E0D-4646-B407-96F3E5F13631@donders.ru.nl> Hi Emilio, Using ft_freqstatistics is very possible. Indeed you will not be able to use clustering for multiple comparison correction. In fact, having reduced the number of comparisons to 8 already almost gets rid of the multiple comparison problem. You can use a nonparametric permutation test without a cluster-based test statistic, and do a bonferroni correction on the p-values. Best, Jan-Mathijs On Feb 26, 2013, at 9:26 PM, Emilio Valadez wrote: > Dear FieldTrip users, > > I have an EEG dataset that was reduced to 8 regional sources with BESA and then exported for FieldTrip analysis. I want to perform a statistical test on the regional sources' time-frequency data, comparing two experimental conditions, but I don't know whether it would be appropriate to use ft_freqstatistics (because I have regional sources instead of a complete sensor layout - making cluster formation problematic) or ft_sourcestatistics. Can you suggest a method for performing a statistical test in this situation? Thanks in advance for your help. > > Best, > Emilio Valadez > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 21:44:21 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:44:21 +0100 Subject: [FieldTrip] cfg.latency In-Reply-To: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> References: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> Message-ID: <2C7B27EF-6A82-4781-B57D-5E2918DF8FEF@donders.ru.nl> Hi Kleo, Did you try following the suggestion that is in the error message, and specified a cfg.latency prior to calling ft_sourceanalysis? Best wishes, Jan-Mathijs On Feb 26, 2013, at 1:27 PM, k.kouroupaki at med.uoc.gr wrote: > HI everyone! > > I am a new field trip user and have been using it for EEG SOURCE LOCALIZATION. > I have a problem though. When I run the ft_sourceanalysis as: source = ft_sourceanalysis(cfg, freq) I get the following error: > > ??? Reference to non-existent field 'latency'. > > Error in ==> prepare_freq_matrices at 55 > tbin = nearest(freq.time, cfg.latency); > > Error in ==> ft_sourceanalysis at 458 > [Cf, Cr, Pr, Ntrials, cfg] = prepare_freq_matrices(cfg, data); > > Could you please help me to localize where the problem is and solve it? > Thank you in advance, > Kleo > > ---------------------------------------------------------------- > This message was sent using IMP, the Internet Messaging Program. > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 21:52:37 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:52:37 +0100 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: References: Message-ID: <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote: > Dear FieldTrip users > > I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. > > 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? > 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? > 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? > > Thanks in advance. > Subbu > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 22:03:23 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 22:03:23 +0100 Subject: [FieldTrip] problem using ft_artifact_muscle In-Reply-To: References: Message-ID: <2AD4BB54-F01D-40C7-89F2-20982BBBFD1F@donders.ru.nl> Hi Leonie, > > ERROR: > > > Subscript indices must either be real positive integers or logicals. > > > > > > Error in ft_fetch_data (line 123) > > > count = count(begsample:endsample); > > > > The error message indicates that either begsample or endsample are badly behaved. I put my money on begsample, in that its value <= 0 in the case of a bandpassfilter-order of 9. My guess is that ft_fetch_data tries to get some data that is not there. Did you check the cfg.artfctdef.muscle.fltpadding? In general, when supplying data in the input to ft_artifact_muscle, the value of this parameter should be set to 0. Best, Jan-Mathijs On Feb 25, 2013, at 9:23 PM, Pascasie L. Dombert wrote: > Hi all, > > > I am a fieldtrip starter working on an EEG data set. I have a question concerning the muscle artifact detection function and I was hoping that you could help me with this. > > I am calling the function > > [cfg,artifact_muscle] = ft_artifact_muscle(cfg,ref_data) as explained in the manual (settings suggested) and get the following error message (see code + error): > > ________________________________________________________________________________________________ > > > %detect the MUSCLE artifacts > > > cfg = []; > > > cfg.continuous = 'yes'; > > > % define trial first > > > cfg.dataset = 'xx’; > > > cfg.trialfun ='trialfun_general'; > > > cfg.trialdef.triallength =1; % creates 1-second data segments > > > cfg.trialdef.ntrials = inf; > > % i.e. the complete file > > > cfg = ft_definetrial(cfg); > > > > > > % cutoff > > > cfg.artfctdef.muscle.channel = 'all'; > > > cfg.artfctdef.muscle.cutoff = 4; > > > > > > % algorithmic parameters > > > cfg.artfctdef.muscle.bpfilter = 'yes'; > > > cfg.artfctdef.muscle.bpfreq = [110 140]; > > > cfg.artfctdef.muscle.bpfiltord = 9; > > > cfg.artfctdef.muscle.bpfilttype = 'but'; > > > cfg.artfctdef.muscle.hilbert = 'yes'; > > > cfg.artfctdef.muscle.boxcar = 0.2; > > > > > > % feedback > > > %cfg.artfctdef.muscle.interactive = 'yes'; % to adjust cutoff zvalue if needed > > > > > > [cfg, artifact_muscle] = ft_artifact_muscle(cfg,ref_data); > > > > > > > > > > > > > > > ERROR: > > > Subscript indices must either be real positive integers or logicals. > > > > > > Error in ft_fetch_data (line 123) > > > count = count(begsample:endsample); > > > > > > Error in ft_artifact_zvalue (line 195) > > > dat{trlop} = ft_fetch_data(data, 'header', hdr, 'begsample', trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding, 'chanindx', > > > sgnind, 'checkboundary', strcmp(cfg.continuous,' > > > Error in ft_artifact_muscle (line 156) > > > [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data); > > > _______________________________________________________ > > > > However, I only get the error message with the default/suggested values. > > When I use: > > cfg.artfctdef.muscle.bpfreq = [110 120]; and cfg.artfctdef.muscle.bpfiltord = 7; > > I don't get the error message and the script runs properly. Does anyone happen to know what could have let to this problem? > > > Thanks a lot in advance! > > Best, Leonie > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From eeguser at hotmail.com Wed Feb 27 00:07:00 2013 From: eeguser at hotmail.com (Subramaniam Iyer) Date: Wed, 27 Feb 2013 02:07:00 +0300 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> References: , <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> Message-ID: Dear Jan-Mathjis Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first.I have never done source localization before, but I will try it by going through the extensive FT documentation. However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ? RegardsSubbu From: jan.schoffelen at donders.ru.nl Date: Tue, 26 Feb 2013 21:52:37 +0100 To: fieldtrip at science.ru.nl Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote:Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance.Subbu_______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics,Nijmegen, The Netherlands J.Schoffelen at donders.ru.nlTelephone: +31-24-3614793 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From carlo.huber at uk-koeln.de Wed Feb 27 10:21:27 2013 From: carlo.huber at uk-koeln.de (Carlo Huber) Date: Wed, 27 Feb 2013 09:21:27 +0000 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: References: , <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl>, Message-ID: <877B32852B5C3A40978EA1F48A10B5022C9854B7@UKK087.ADS.UK-KOELN.DE> Dear Subbu, PDC seems to be influenced by filtering, see http://www.ncbi.nlm.nih.gov/pubmed/20026279 by Florin et al., 2010, Neuroimage. I would not recommend therefore applying PDC to source data. Other views are much welcome. Best, Carlo ________________________________ Von: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]" im Auftrag von "Subramaniam Iyer [eeguser at hotmail.com] Gesendet: Mittwoch, 27. Februar 2013 00:07 An: FieldTrip Betreff: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Jan-Mathjis Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first. I have never done source localization before, but I will try it by going through the extensive FT documentation. However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ? Regards Subbu ________________________________ From: jan.schoffelen at donders.ru.nl Date: Tue, 26 Feb 2013 21:52:37 +0100 To: fieldtrip at science.ru.nl Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote: Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance. Subbu _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophiechen33 at gmail.com Wed Feb 27 13:51:27 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Wed, 27 Feb 2013 13:51:27 +0100 Subject: [FieldTrip] troubles while reading 4D MEG files in getting the MEG channels In-Reply-To: <1538559706.484002.1361969272444.JavaMail.root@bureau-frontal1> References: <1538559706.484002.1361969272444.JavaMail.root@bureau-frontal1> Message-ID: Dear all, I am trying to read MEG 4D files with Fieldtrip version 20130226 using ft_preprocessing file with a preselection of MEG channels ( 'MEG' or a cell array of channel names, here is MEG_LABEL) but the output data contains only 152 channels while I have 248 channels... I tried the same code with Fieldtrip version 20121015, and I get everything properly (i.e. 248 channels) Following the script I am running and the corresponding results in matlab. *cfg = []; cfg.dataset = 'c,rfDC'; cfg.trialdef.eventtype = 'TRIGGER'; cfg.trialdef.eventvalue = 2; cfg.trialdef.prestim = 1; cfg.trialdef.poststim = 2; [cfg] = ft_definetrial(cfg); % cfg.channel = 'MEG'; cfg.channel = MEG_LABEL; cfg.continous = 'yes'; data_2 = ft_preprocessing (cfg)* *I get this >>* Warning: no trialfun was specified, using ft_trialfun_general > In ft_definetrial at 123 evaluating trialfunction 'ft_trialfun_general' applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_trialfun_general at 71 In ft_definetrial at 162 undoing the Supine balancing reading the events from 'c,rfDC' applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_read_event at 174 In ft_trialfun_general at 80 In ft_definetrial at 162 found 677 events created 249 trials the call to "ft_definetrial" took 5 seconds applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_preprocessing at 394 processing channel { 'A2' 'A104' 'A241' 'A138' 'A71' 'A125' 'A20' 'A65' 'A9' 'A114' 'A175' 'A228' 'A35' 'A191' 'A37' 'A170' 'A207' 'A224' 'A82' 'A238' 'A28' 'A239' 'A13' 'A165' 'A204' 'A25' 'A70' 'A11' 'A47' 'A64' 'A177' 'A127' 'A247' 'A194' 'A5' 'A242' 'A168' 'A31' 'A245' 'A219' 'A105' 'A222' 'A76' 'A188' 'A215' 'A235' 'A181' 'A38' 'A230' 'A91' 'A212' 'A24' 'A96' 'A57' 'A86' 'A116' 'A141' 'A120' 'A80' 'A210' 'A113' 'A27' 'A135' 'A167' 'A206' 'A100' 'A43' 'A200' 'A102' 'A132' 'A122' 'A62' 'A21' 'A229' 'A55' 'A32' 'A85' 'A58' 'A60' 'A88' 'A79' 'A203' 'A145' 'A139' 'A156' 'A68' 'A159' 'A236' 'A161' 'A6' 'A126' 'A94' 'A15' 'A193' 'A150' 'A36' 'A225' 'A195' 'A172' 'A108' 'A81' 'A171' 'A218' 'A173' 'A201' 'A74' 'A29' 'A164' 'A232' 'A69' 'A157' 'A97' 'A124' 'A40' 'A178' 'A179' 'A33' 'A147' 'A148' 'A89' 'A119' 'A52' 'A190' 'A73' 'A136' 'A184' 'A51' 'A77' 'A129' 'A197' 'A182' 'A46' 'A92' 'A41' 'A90' 'A23' 'A154' 'A18' 'A248' 'A149' 'A118' 'A152' 'A140' 'A110' 'A185' 'A162' 'A106' 'A187' 'A221' 'A133' 'A158' 'A216' } reading and preprocessing reading and preprocessing trial 249 from 249 the call to "ft_preprocessing" took 20 seconds data_2 = hdr: [1x1 struct] label: {152x1 cell} time: {1x249 cell} trial: {1x249 cell} fsample: 2.0345e+03 sampleinfo: [249x2 double] trialinfo: [249x1 double] grad: [1x1 struct] cfg: [1x1 struct] *This is what I get with Fieldtrip 20121015:* Warning: no trialfun was specified, using ft_trialfun_general > In ft_definetrial at 123 evaluating trialfunction 'ft_trialfun_general' applying digital weights in the gradiometer balancing matrix undoing the Supine balancing reading the events from 'c,rfDC' applying digital weights in the gradiometer balancing matrix undoing the Supine balancing found 677 events created 249 trials the call to "ft_definetrial" took 7 seconds applying digital weights in the gradiometer balancing matrix undoing the Supine balancing processing channel { 'A22' 'A2' 'A104' 'A241' 'A138' 'A214' 'A71' 'A26' 'A93' 'A39' 'A125' 'A20' 'A65' 'A9' 'A8' 'A95' 'A114' 'A175' 'A16' 'A228' 'A35' 'A191' 'A37' 'A170' 'A207' 'A112' 'A224' 'A82' 'A238' 'A202' 'A220' 'A28' 'A239' 'A13' 'A165' 'A204' 'A233' 'A98' 'A25' 'A70' 'A72' 'A11' 'A47' 'A160' 'A64' 'A3' 'A177' 'A63' 'A155' 'A10' 'A127' 'A67' 'A115' 'A247' 'A174' 'A194' 'A5' 'A242' 'A176' 'A78' 'A168' 'A31' 'A223' 'A245' 'A219' 'A12' 'A186' 'A105' 'A222' 'A76' 'A50' 'A188' 'A231' 'A45' 'A180' 'A99' 'A234' 'A215' 'A235' 'A181' 'A38' 'A230' 'A91' 'A212' 'A24' 'A66' 'A42' 'A96' 'A57' 'A86' 'A56' 'A116' 'A151' 'A141' 'A120' 'A189' 'A80' 'A210' 'A143' 'A113' 'A27' 'A137' 'A135' 'A167' 'A75' 'A240' 'A206' 'A107' 'A130' 'A100' 'A43' 'A200' 'A102' 'A132' 'A183' 'A199' 'A122' 'A19' 'A62' 'A21' 'A229' 'A84' 'A213' 'A55' 'A32' 'A85' 'A146' 'A58' 'A60' 'A88' 'A79' 'A169' 'A54' 'A203' 'A145' 'A103' 'A163' 'A139' 'A49' 'A166' 'A156' 'A128' 'A68' 'A159' 'A236' 'A161' 'A121' 'A4' 'A61' 'A6' 'A126' 'A14' 'A94' 'A15' 'A193' 'A150' 'A227' 'A59' 'A36' 'A225' 'A195' 'A30' 'A109' 'A172' 'A108' 'A81' 'A171' 'A218' 'A173' 'A201' 'A74' 'A29' 'A164' 'A205' 'A232' 'A69' 'A157' 'A97' 'A217' 'A101' 'A124' 'A40' 'A123' 'A153' 'A178' 'A1' 'A179' 'A33' 'A147' 'A117' 'A148' 'A87' 'A89' 'A243' 'A119' 'A52' 'A142' 'A211' 'A190' 'A53' 'A192' 'A73' 'A226' 'A136' 'A184' 'A51' 'A237' 'A77' 'A129' 'A131' 'A198' 'A197' 'A182' 'A46' 'A92' 'A41' 'A90' 'A7' 'A23' 'A83' 'A154' 'A34' 'A17' 'A18' 'A248' 'A149' 'A118' 'A208' 'A152' 'A140' 'A144' 'A209' 'A110' 'A111' 'A244' 'A185' 'A246' 'A162' 'A106' 'A187' 'A48' 'A221' 'A196' 'A133' 'A158' 'A44' 'A134' 'A216' } reading and preprocessing reading and preprocessing trial 249 from 249 the call to "ft_preprocessing" took 24 seconds data_2 = hdr: [1x1 struct] label: {248x1 cell} time: {1x249 cell} trial: {1x249 cell} fsample: 2.0345e+03 sampleinfo: [249x2 double] trialinfo: [249x1 double] grad: [1x1 struct] cfg: [1x1 struct] I hope this helps to find out where the problem is coming from... Thanks in advance for your help Cheers, Sophie Chen -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 28 17:38:21 2013 From: frank.ye.mei at gmail.com (Ye Mei) Date: Thu, 28 Feb 2013 11:38:21 -0500 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well Message-ID: <512F87FD.80500@gmail.com> Hello FieldtripList, After segmentation and alignment using 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented brain seems rotated forward in the sensor helmet(brain.png) and the cerebellum part seems to be segmented out. However, his head MRI seems fitting the sensor helmet well(head.jpg). My another subject's brain seem to be correctly segmented without missing the cerebellum part. And the brain is not rotated forward. Could might be the problem? thanks ahead, Ye -------------- next part -------------- A non-text attachment was scrubbed... Name: brain.png Type: image/png Size: 15197 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: head.jpg Type: image/jpeg Size: 50294 bytes Desc: not available URL: From r.oostenveld at donders.ru.nl Thu Feb 28 17:46:39 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Thu, 28 Feb 2013 17:46:39 +0100 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 In-Reply-To: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> References: <002201ce0e9a$e18ab740$a4a025c0$@stijns@fcdonders.ru.nl> <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> Message-ID: <9741C083-F00A-4BC9-86EF-FB99715576A7@donders.ru.nl> Dear FieldTrip users, The NIHC-BrainGain Tutorial Day marks the end of the BrainGain project. For the last 6 years, the development and continued support of FieldTrip for normal/offline and realtime/online analysis has received support from the BrainGain project. There is now more information available online on this tutorial day, please see https://www.hersenenencognitie.nl/contents/1876 https://www.hersenenencognitie.nl/contents/1915 If you happen to be close to Nijmegen, you might also want to come to the "Breinfest" on Tuesday evening 19 March in the city centre with talks by international speakers and BCI demo's for the general public. Personally, I will be demonstrating how real-time data streaming and processing can be done using the FieldTrip buffer to various platforms (OS X, WIndows, Linux), to the Raspberry Pi and even to an Arduino (yes, fieldtrip runs on an arduino! ... well, a small part of it runs on an arduino). See http://www.ru.nl/breinfest for details on the evening. best regards, Robert On 19 Feb 2013, at 14:30, Robert Oostenveld wrote: > > NIHC-BrainGain Tutorial Day: > Tools and novelties in neurotechnology research > > We invite PhD students, post-docs and senior researchers working in the fields of brain-computer interfacing (BCI), neurofeedback, cognitive neuroscience, neuroinformatics, neurosurgery and related topics to our Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen. > The day marks the end of the BrainGain consortium, a six-year joint-effort project on Brain-Computer Interfacing and related technologies. More information on BrainGain can be found here. > > The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. The 'tools' track is intended to provide both newcomers to the field and experienced researchers with an overview of the tools needed to integrate cognitive neuroscience and advanced invasive and non-invasive technology. Topics range from data streaming to modelling and statistics, and from online fMRI decoding to a crash course in neuroethics., You will also receive some helpful insights for a future career, in case you are interested in applying for a grant in the near future or considering setting up your own company. > The 'novelties' track covers a wide range of topics indicating some of the possible topics to be further explored in BCI and neurotechnology research, including genetics, robotics and intracranial recordings. > There is no need to stick to one of the two tracks the whole day: you are free to switch between tracks any time. > > In parallel to the lectures, there will be several interesting demonstrations. > > The full programme and registration form can be found on the NIHC website (https://www.hersenenencognitie.nl). Please register before 1 March 2013. Participation is free. Lunch and drinks will be provided. > > We hope to welcome you on March 21st in Nijmegen! > > Susanna Bicknell > Radboud University Nijmegen > ____________________________________________________________________ > Faculty of Science | Finance and Economic Affairs | Project Management | LC-IMPACT > Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | Project Manager > T +31 24 3653300 | HG00.616 (Monday, Thursday) > Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, Wednesday) > Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands > Visiting and courier service address: Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From jan.schoffelen at donders.ru.nl Thu Feb 28 18:54:14 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Thu, 28 Feb 2013 18:54:14 +0100 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well In-Reply-To: <512F87FD.80500@gmail.com> References: <512F87FD.80500@gmail.com> Message-ID: Hi Ye, Looks like a coregistration problem to me. In other words, something went wrong in ft_volumesegment, because the images were not sufficiently aligned. You need to investigate the input and output of ft_volumesegment. Do you use ft_volumerealign after calling ft_volumesegment? This should be the other way around. Best, Jan-Mathijs On Feb 28, 2013, at 5:38 PM, Ye Mei wrote: > Hello FieldtripList, > > After segmentation and alignment using > 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented > brain seems rotated forward in the sensor helmet(brain.png) and the > cerebellum part seems to be segmented out. However, his head MRI seems > fitting the sensor helmet well(head.jpg). My another subject's brain > seem to be correctly segmented without missing the cerebellum part. And > the brain is not rotated forward. > > Could might be the problem? > > thanks ahead, > Ye > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 28 23:09:57 2013 From: frank.ye.mei at gmail.com (Ye Mei) Date: Thu, 28 Feb 2013 17:09:57 -0500 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well In-Reply-To: References: Message-ID: <512FD5B5.8080700@gmail.com> Hello All, I found the problem I mentioned in the previous email was caused by using "mri_sliced = ft_volumereslice([], mri);" before using ft_volumesegment. After erasing the line "mri_sliced = ft_volumereslice([], mri);", the segmented brain seems to be normal and fits the sensor helmet well now, as show in the attached figure(notvolumnsliced.jpg). For another of my subject, if the "ft_volumereslice" is included, the brain looks sliced on the top(subject2vs.jpg). If no "ft_volumreslice" it looks normal(subject2.jpg). I notice in the fieldtrip headmodel tutorial (http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg), "ft_volumereslice" is not used. but in the field trip beamformer tutorial(http://fieldtrip.fcdonders.nl/tutorial/beamformer), it is used. I am wondering if I should include "ft_volumereslice" in my source localization code. Can anyone give me some suggestions? thanks ahead, Ye On 13-02-28 11:45 AM, fieldtrip-request at science.ru.nl wrote: > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > or, via email, send a message with subject or body 'help' to > fieldtrip-request at science.ru.nl > > You can reach the person managing the list at > fieldtrip-owner at science.ru.nl > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of fieldtrip digest..." > > > Today's Topics: > > 1. segmented brain seems not fitting the sensor helmet well (Ye Mei) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Thu, 28 Feb 2013 11:38:21 -0500 > From: Ye Mei > To: fieldtrip at science.ru.nl > Subject: [FieldTrip] segmented brain seems not fitting the sensor > helmet well > Message-ID: <512F87FD.80500 at gmail.com> > Content-Type: text/plain; charset="iso-8859-1"; Format="flowed" > > Hello FieldtripList, > > After segmentation and alignment using > 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented > brain seems rotated forward in the sensor helmet(brain.png) and the > cerebellum part seems to be segmented out. However, his head MRI seems > fitting the sensor helmet well(head.jpg). My another subject's brain > seem to be correctly segmented without missing the cerebellum part. And > the brain is not rotated forward. > > Could might be the problem? > > thanks ahead, > Ye > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: brain.png > Type: image/png > Size: 15197 bytes > Desc: not available > URL: > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: head.jpg > Type: image/jpeg > Size: 50294 bytes > Desc: not available > URL: > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 27, Issue 31 > ***************************************** -------------- next part -------------- A non-text attachment was scrubbed... Name: notvolumnsliced.jpg Type: image/jpeg Size: 28621 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: subject2.jpg Type: image/jpeg Size: 27415 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: subject2vc.jpg Type: image/jpeg Size: 27788 bytes Desc: not available URL: From andrea.brovelli at univ-amu.fr Mon Feb 4 09:22:17 2013 From: andrea.brovelli at univ-amu.fr (andrea brovelli) Date: Mon, 04 Feb 2013 09:22:17 +0100 Subject: [FieldTrip] Error in prepare_freq_matrices.m ? In-Reply-To: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> References: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> Message-ID: <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> Dear all, I have an error while running ft_sourceanalysis. I am analysing a data set over a frequency range which includes 100 frequencies and 60 trials. I get an error due to the definition of the variable Ntrials, which as far as I understand, it is done in prepare_freq_matrices.m at lines 76 -> 85: ------------------------------------------------- % the time-frequency latency has already been squeezed away (see above) if strcmp(freq.dimord, 'chan_freq') Ntrials = 1; elseif strcmp(freq.dimord, 'rpt_chan_freq') Ntrials = length(freq.cumtapcnt); elseif strcmp(freq.dimord, 'rpttap_chan_freq') Ntrials = length(freq.cumtapcnt); else error('unrecognized dimord for frequency data'); end ------------------------------------------------- If the number of trials is less than the number of frequencies, Ntrials = length(freq.cumtapcnt) should be replaced by Ntrials = size(freq.cumtapcnt,1); It is the case ? Thanks a lot Andrea From jan.schoffelen at donders.ru.nl Mon Feb 4 12:01:11 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Mon, 4 Feb 2013 12:01:11 +0100 Subject: [FieldTrip] Error in prepare_freq_matrices.m ? In-Reply-To: <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> References: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> Message-ID: <7C99534A-440F-4B53-BFCC-F0968FF0BB9D@donders.ru.nl> Hi Andrea, This could very well be. Sorry for not getting back to you earlier. Could you create an account on our bugzilla server and file this as a bug? We will then look into it (and fix it) as soon as possible. For the time being, could you work around it by just changing your code locally? Thanks and best wishes, Jan-Mathijs On Feb 4, 2013, at 9:22 AM, andrea brovelli wrote: > > Dear all, > > I have an error while running ft_sourceanalysis. I am analysing a data set over a frequency range which includes 100 frequencies and 60 trials. I get an error due to the definition of the variable Ntrials, which as far as I understand, it is done in prepare_freq_matrices.m at lines 76 -> 85: > > ------------------------------------------------- > % the time-frequency latency has already been squeezed away (see above) > if strcmp(freq.dimord, 'chan_freq') > Ntrials = 1; > elseif strcmp(freq.dimord, 'rpt_chan_freq') > Ntrials = length(freq.cumtapcnt); > elseif strcmp(freq.dimord, 'rpttap_chan_freq') > Ntrials = length(freq.cumtapcnt); > else > error('unrecognized dimord for frequency data'); > end > ------------------------------------------------- > > If the number of trials is less than the number of frequencies, Ntrials = length(freq.cumtapcnt) should be replaced by Ntrials = size(freq.cumtapcnt,1); > > It is the case ? > > Thanks a lot > > Andrea > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Tue Feb 5 22:40:56 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Tue, 5 Feb 2013 21:40:56 +0000 Subject: [FieldTrip] localspheres Message-ID: Hello, I have what is possibly a naïve question, but I can't seem to find anything on the tutorial pages. I'm trying to create a headmodel using the localspheres method, using the output of a segmented MRI. There is a tutorial page for using different types of headmodels, but it references ft_prepare_localspheres - which works, but it appears to have been deprecated. When I try this: hdr=ft_read_header('mydata.ds'); cfg=[]; cfg.method='localspheres'; cfg.grad=hdr.grad; cfg.vol=segmented_mri; vol=ft_prepare_headmodel(cfg, segmentedmri); I get an error at ft_getopt(cfg,'tissue'); Although the documentation for ft_prepare_headmodel states that the only additional field needed by localspheres is "cfg.grad" it seems that cfg.tissue may also be required? If so, how do I set this - I can't find any documentation that explains. I should note that I've run ft_prepare_headmodel successfully using a singleshell method. Thanks, Allison Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Wed Feb 6 09:53:15 2013 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Wed, 6 Feb 2013 09:53:15 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Dear Allison, Thank you for your question. There have been some changes to ft_prepare_headmodel recently (partly implemented by me) and my apologies that the documentation for these changes was not made thoroughly. I assume that you are refering to a very recent FT version. :-) The way that you call ft_prepare_headmodel looks almost correct, except that cfg.vol is not needed. If you have already a 'vol' or 'bnd' , then that can be used as the second input argument to ft_prepare_headmodel, and the 'segmentedmri' is not needed. If you don't already have a 'vol' or 'bnd', then that will be created on the fly within ft_prepare_headmodel from the segmentedmri that you include as second input. However, what are the fields within 'segmentedmri' that you use? If 'brain' or 'scalp' already exist, then those will be found and used by default, and therefore a cfg.tissue is not needed. However, if you have other fields with different names, etc then cfg.tissue should point to the name of the subfield of segmentedmri that you wish to use as the headshape. Please see ft_volumesegment for more details on which tissue types or segmentation types can be computed as output and which can then be used in subsequent functions. Perhaps simply recompute the segmentedmri with the newest version of ft_volumesegment and then it will work? In the meantime, I will update the documentation to make all this more clear. However, one more question. I'm not sure what you mean by the error you get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it will return a default empty variable, and there should not be an error. Can you say exactly what line of what function gives the error, and what the error exactly is? And finally, when you successfully ran singleshell method, was that with the segmentedmri (which would surprise me), or rather with a cfg.headshape option? Cheers, Johanna 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] > Hello, **** > > ** ** > > I have what is possibly a naïve question, but I can’t seem to find > anything on the tutorial pages.**** > > ** ** > > I’m trying to create a headmodel using the localspheres method, using the > output of a segmented MRI.**** > > ** ** > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres – which works, but it appears to have > been deprecated. When I try this:**** > > ** ** > > hdr=ft_read_header(‘mydata.ds’);**** > > cfg=[];**** > > cfg.method=’localspheres’;**** > > cfg.grad=hdr.grad;**** > > cfg.vol=segmented_mri;**** > > vol=ft_prepare_headmodel(cfg, segmentedmri);**** > > ** ** > > I get an error at ft_getopt(cfg,’tissue’);**** > > ** ** > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is “cfg.grad” it seems that > cfg.tissue may also be required? If so, how do I set this – I can’t find > any documentation that explains.**** > > ** ** > > I should note that I’ve run ft_prepare_headmodel successfully using a > singleshell method.**** > > ** ** > > Thanks,**** > > ** ** > > Allison**** > > ** ** > > Allison Nugent, PhD**** > > MRI Physicist**** > > Experimental Therapeutics and Pathophysiology Branch**** > > NIMH/NIH/DHHS**** > > Ph. 301-451-8863**** > > nugenta at mail.nih.gov**** > > ** ** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Wed Feb 6 09:56:29 2013 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Wed, 6 Feb 2013 09:56:29 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Sorry, I meant if you have a 'bnd'. Of course you won't have the 'vol', that is the purpose of calling ft_prepare_headmodel! Johanna 2013/2/6 Johanna Zumer > Dear Allison, > > Thank you for your question. There have been some changes to > ft_prepare_headmodel recently (partly implemented by me) and my apologies > that the documentation for these changes was not made thoroughly. I > assume that you are refering to a very recent FT version. :-) > > The way that you call ft_prepare_headmodel looks almost correct, except > that cfg.vol is not needed. > > If you have already a 'vol' or 'bnd' , then that can be used as the second > input argument to ft_prepare_headmodel, and the 'segmentedmri' is not > needed. > > If you don't already have a 'vol' or 'bnd', then that will be created on > the fly within ft_prepare_headmodel from the segmentedmri that you include > as second input. However, what are the fields within 'segmentedmri' that > you use? If 'brain' or 'scalp' already exist, then those will be found > and used by default, and therefore a cfg.tissue is not needed. However, if > you have other fields with different names, etc then cfg.tissue should > point to the name of the subfield of segmentedmri that you wish to use as > the headshape. Please see ft_volumesegment for more details on which > tissue types or segmentation types can be computed as output and which can > then be used in subsequent functions. Perhaps simply recompute the > segmentedmri with the newest version of ft_volumesegment and then it will > work? > > In the meantime, I will update the documentation to make all this more > clear. > > However, one more question. I'm not sure what you mean by the error you > get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it will > return a default empty variable, and there should not be an error. Can > you say exactly what line of what function gives the error, and what the > error exactly is? > > And finally, when you successfully ran singleshell method, was that with > the segmentedmri (which would surprise me), or rather with a cfg.headshape > option? > > Cheers, > Johanna > > > > > > > > > 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] > >> Hello, **** >> >> ** ** >> >> I have what is possibly a naïve question, but I can’t seem to find >> anything on the tutorial pages.**** >> >> ** ** >> >> I’m trying to create a headmodel using the localspheres method, using the >> output of a segmented MRI.**** >> >> ** ** >> >> There is a tutorial page for using different types of headmodels, but it >> references ft_prepare_localspheres – which works, but it appears to have >> been deprecated. When I try this:**** >> >> ** ** >> >> hdr=ft_read_header(‘mydata.ds’);**** >> >> cfg=[];**** >> >> cfg.method=’localspheres’;**** >> >> cfg.grad=hdr.grad;**** >> >> cfg.vol=segmented_mri;**** >> >> vol=ft_prepare_headmodel(cfg, segmentedmri);**** >> >> ** ** >> >> I get an error at ft_getopt(cfg,’tissue’);**** >> >> ** ** >> >> Although the documentation for ft_prepare_headmodel states that the only >> additional field needed by localspheres is “cfg.grad” it seems that >> cfg.tissue may also be required? If so, how do I set this – I can’t find >> any documentation that explains.**** >> >> ** ** >> >> I should note that I’ve run ft_prepare_headmodel successfully using a >> singleshell method.**** >> >> ** ** >> >> Thanks,**** >> >> ** ** >> >> Allison**** >> >> ** ** >> >> Allison Nugent, PhD**** >> >> MRI Physicist**** >> >> Experimental Therapeutics and Pathophysiology Branch**** >> >> NIMH/NIH/DHHS**** >> >> Ph. 301-451-8863**** >> >> nugenta at mail.nih.gov**** >> >> ** ** >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Lilla.Magyari at mpi.nl Wed Feb 6 10:32:15 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 10:32:15 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> hi Allison, this was a small a bug in FieldTrip a few weeks ago. It has been fixed since then already, so I think if you download the latest version, you can run ft_prepare_headmodel with method 'localspheres' without the specification of tissue-type. In this case, the geometry of the 'brain' tissue will be used for the headmodel by default. Therefore, it will work only if your segmentation contains a binary mask of the brain (i.e. your segmentation should have a 'brain' field with binary values) or if your segmentation contains the probability tissue maps of 'gray','white','csf' tissue. In this later case, the brain mask will be created from gray, white and csf by the function. But actually, if you want to run ft_prepare_headmodel with your version, you can just specify the name of the tissue that is in your segmentation. Best, Lilla > Hello, > > I have what is possibly a naïve question, but I can't seem to find > anything on the tutorial pages. > > I'm trying to create a headmodel using the localspheres method, using the > output of a segmented MRI. > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres - which works, but it appears to have > been deprecated. When I try this: > > hdr=ft_read_header('mydata.ds'); > cfg=[]; > cfg.method='localspheres'; > cfg.grad=hdr.grad; > cfg.vol=segmented_mri; > vol=ft_prepare_headmodel(cfg, segmentedmri); > > I get an error at ft_getopt(cfg,'tissue'); > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is "cfg.grad" it seems that > cfg.tissue may also be required? If so, how do I set this - I can't find > any documentation that explains. > > I should note that I've run ft_prepare_headmodel successfully using a > singleshell method. > > Thanks, > > Allison > > Allison Nugent, PhD > MRI Physicist > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph. 301-451-8863 > nugenta at mail.nih.gov > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From smoratti at psi.ucm.es Wed Feb 6 10:34:23 2013 From: smoratti at psi.ucm.es (STEPHAN MORATTI) Date: Wed, 6 Feb 2013 10:34:23 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: I guess you would need headshape points for the local spheres. Not sure if ft automatically creates a head surface from the segmented MRI. Best Stephan El 05/02/2013 23:25, "Nugent, Allison C. (NIH/NIMH) [E]" < nugenta at mail.nih.gov> escribió: > Hello, **** > > ** ** > > I have what is possibly a naïve question, but I can’t seem to find > anything on the tutorial pages.**** > > ** ** > > I’m trying to create a headmodel using the localspheres method, using the > output of a segmented MRI.**** > > ** ** > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres – which works, but it appears to have > been deprecated. When I try this:**** > > ** ** > > hdr=ft_read_header(‘mydata.ds’);**** > > cfg=[];**** > > cfg.method=’localspheres’;**** > > cfg.grad=hdr.grad;**** > > cfg.vol=segmented_mri;**** > > vol=ft_prepare_headmodel(cfg, segmentedmri);**** > > ** ** > > I get an error at ft_getopt(cfg,’tissue’);**** > > ** ** > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is “cfg.grad” it seems that > cfg.tissue may also be required? If so, how do I set this – I can’t find > any documentation that explains.**** > > ** ** > > I should note that I’ve run ft_prepare_headmodel successfully using a > singleshell method.**** > > ** ** > > Thanks,**** > > ** ** > > Allison**** > > ** ** > > Allison Nugent, PhD**** > > MRI Physicist**** > > Experimental Therapeutics and Pathophysiology Branch**** > > NIMH/NIH/DHHS**** > > Ph. 301-451-8863**** > > nugenta at mail.nih.gov**** > > ** ** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Lilla.Magyari at mpi.nl Wed Feb 6 10:43:38 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 10:43:38 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: <49445.131.174.45.70.1360143818.squirrel@131.174.45.70> hi Johanna and Allison, I think there was a small bug in ft_prepare_headmodel http://bugzilla.fcdonders.nl/show_bug.cgi?id=1679 a few weeks ago which caused this error. It has been fixed already, so if the newest version of FT is used, ft_prepare_headmodel should run now with cfg.method 'localspheres' without cfg.tissue specified. But this depends on the tissues in the segmentation as Johanna wrote. But besides 'brain' and 'scalp', it is also fine if the segmentation contains the probability tissue maps of the cerebro-spinal fluid, the gray and white matter. In this case, brain binary mask will be created by the function from csf,w hite and gray and the geometry of the brain tissue will be used for the head-model. I hope this helps too. Best, Lilla > Sorry, I meant if you have a 'bnd'. Of course you won't have the 'vol', > that is the purpose of calling ft_prepare_headmodel! > > Johanna > > > 2013/2/6 Johanna Zumer > >> Dear Allison, >> >> Thank you for your question. There have been some changes to >> ft_prepare_headmodel recently (partly implemented by me) and my >> apologies >> that the documentation for these changes was not made thoroughly. I >> assume that you are refering to a very recent FT version. :-) >> >> The way that you call ft_prepare_headmodel looks almost correct, except >> that cfg.vol is not needed. >> >> If you have already a 'vol' or 'bnd' , then that can be used as the >> second >> input argument to ft_prepare_headmodel, and the 'segmentedmri' is not >> needed. >> >> If you don't already have a 'vol' or 'bnd', then that will be created on >> the fly within ft_prepare_headmodel from the segmentedmri that you >> include >> as second input. However, what are the fields within 'segmentedmri' >> that >> you use? If 'brain' or 'scalp' already exist, then those will be found >> and used by default, and therefore a cfg.tissue is not needed. However, >> if >> you have other fields with different names, etc then cfg.tissue should >> point to the name of the subfield of segmentedmri that you wish to use >> as >> the headshape. Please see ft_volumesegment for more details on which >> tissue types or segmentation types can be computed as output and which >> can >> then be used in subsequent functions. Perhaps simply recompute the >> segmentedmri with the newest version of ft_volumesegment and then it >> will >> work? >> >> In the meantime, I will update the documentation to make all this more >> clear. >> >> However, one more question. I'm not sure what you mean by the error you >> get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it >> will >> return a default empty variable, and there should not be an error. >> Can >> you say exactly what line of what function gives the error, and what the >> error exactly is? >> >> And finally, when you successfully ran singleshell method, was that with >> the segmentedmri (which would surprise me), or rather with a >> cfg.headshape >> option? >> >> Cheers, >> Johanna >> >> >> >> >> >> >> >> >> 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] >> >>> Hello, **** >>> >>> ** ** >>> >>> I have what is possibly a naïve question, but I can’t seem to find >>> anything on the tutorial pages.**** >>> >>> ** ** >>> >>> I’m trying to create a headmodel using the localspheres method, using >>> the >>> output of a segmented MRI.**** >>> >>> ** ** >>> >>> There is a tutorial page for using different types of headmodels, but >>> it >>> references ft_prepare_localspheres – which works, but it appears to >>> have >>> been deprecated. When I try this:**** >>> >>> ** ** >>> >>> hdr=ft_read_header(‘mydata.ds’);**** >>> >>> cfg=[];**** >>> >>> cfg.method=’localspheres’;**** >>> >>> cfg.grad=hdr.grad;**** >>> >>> cfg.vol=segmented_mri;**** >>> >>> vol=ft_prepare_headmodel(cfg, segmentedmri);**** >>> >>> ** ** >>> >>> I get an error at ft_getopt(cfg,’tissue’);**** >>> >>> ** ** >>> >>> Although the documentation for ft_prepare_headmodel states that the >>> only >>> additional field needed by localspheres is “cfg.grad” it seems that >>> cfg.tissue may also be required? If so, how do I set this – I can’t >>> find >>> any documentation that explains.**** >>> >>> ** ** >>> >>> I should note that I’ve run ft_prepare_headmodel successfully using a >>> singleshell method.**** >>> >>> ** ** >>> >>> Thanks,**** >>> >>> ** ** >>> >>> Allison**** >>> >>> ** ** >>> >>> Allison Nugent, PhD**** >>> >>> MRI Physicist**** >>> >>> Experimental Therapeutics and Pathophysiology Branch**** >>> >>> NIMH/NIH/DHHS**** >>> >>> Ph. 301-451-8863**** >>> >>> nugenta at mail.nih.gov**** >>> >>> ** ** >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From Lilla.Magyari at mpi.nl Wed Feb 6 11:19:31 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 11:19:31 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> References: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> Message-ID: <49498.131.174.45.70.1360145971.squirrel@131.174.45.70> dear all, sorry for the multiply posting. My email browser is not working properly. Lilla > hi Allison, > > this was a small a bug in FieldTrip a few weeks ago. It has been fixed > since then already, so I think if you download the latest version, you can > run ft_prepare_headmodel with method 'localspheres' without the > specification of tissue-type. In this case, the geometry of the 'brain' > tissue will be used for the headmodel by default. Therefore, it will work > only if your segmentation contains a binary mask of the brain (i.e. your > segmentation should have a 'brain' field with binary values) or if your > segmentation contains the probability tissue maps of 'gray','white','csf' > tissue. In this later case, the brain mask will be created from gray, > white and csf by the function. > > But actually, if you want to run ft_prepare_headmodel with your version, > you can just specify the name of the tissue that is in your segmentation. > > Best, > Lilla > > >> Hello, >> >> I have what is possibly a naïve question, but I can't seem to find >> anything on the tutorial pages. >> >> I'm trying to create a headmodel using the localspheres method, using >> the >> output of a segmented MRI. >> >> There is a tutorial page for using different types of headmodels, but it >> references ft_prepare_localspheres - which works, but it appears to have >> been deprecated. When I try this: >> >> hdr=ft_read_header('mydata.ds'); >> cfg=[]; >> cfg.method='localspheres'; >> cfg.grad=hdr.grad; >> cfg.vol=segmented_mri; >> vol=ft_prepare_headmodel(cfg, segmentedmri); >> >> I get an error at ft_getopt(cfg,'tissue'); >> >> Although the documentation for ft_prepare_headmodel states that the only >> additional field needed by localspheres is "cfg.grad" it seems that >> cfg.tissue may also be required? If so, how do I set this - I can't >> find >> any documentation that explains. >> >> I should note that I've run ft_prepare_headmodel successfully using a >> singleshell method. >> >> Thanks, >> >> Allison >> >> Allison Nugent, PhD >> MRI Physicist >> Experimental Therapeutics and Pathophysiology Branch >> NIMH/NIH/DHHS >> Ph. 301-451-8863 >> nugenta at mail.nih.gov >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > From robince at gmail.com Wed Feb 6 12:54:01 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 11:54:01 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca Message-ID: Hi all, I am a new fieldtrip user getting started preprocessing a large MEG data set (I am in Glasgow and the data was collected at CCNi). I think I am slowly getting to grips with all the steps necessary, but I have a question about the artifact rejection. My undersanding is that the denoise procedure helps correct external sources of noise, so having the signal cleaned in this way should help detect the biological artifacts which are valid magnetic signal at the scalp. But I can't see an easy way to do this since the ft_artifact_* functions want to load the raw continuous data from disk. I can get them to act on the in memory trials data if I set the padding options to 0, but then I get an unacceptable amount of rejections (I guess because of the filter artifacts the padding usually prevents). Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the denoised signal from ft_denoise_pca and if so how? At the moment I am performing the following steps: Load each run Detect jumps with ft_artifact_jump. Concatenate the jump-free trials from all runs together for this block. Visually inspect the reference channels and remove high variance trials (across the whole block). Compute denoise PCA weights using only good reference data (and no MEG jump) trials across the whole block. I would now like to apply the denoise PCA weights, perform other automatic artifact removal on the cleaned data, before further visual inspection and the next steps of ICA etc. Is there any problems with this strategy? Thanks in advance for any advice, Robin From jm.horschig at donders.ru.nl Wed Feb 6 15:02:03 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Wed, 06 Feb 2013 15:02:03 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: Message-ID: <5112625B.9090504@donders.ru.nl> Hi Robin, I think the steps you suggested sound reasonable, but I do not see how you are avoiding the filter artifact issue there, you just postpone it to a later stage. Instead it might be a smart way to 'pad' your trials when defining them with 1s pre- and post (so cut out more than you need); that way all filter artifacts will be in that 1s that you are not interested in anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I understand your question correctly, that solves your problem, doesn't it? Best, Jörn On 2/6/2013 12:54 PM, Robin wrote: > Hi all, > > I am a new fieldtrip user getting started preprocessing a large MEG > data set (I am in Glasgow and the data was collected at CCNi). > > I think I am slowly getting to grips with all the steps necessary, but > I have a question about the artifact rejection. > > My undersanding is that the denoise procedure helps correct external > sources of noise, so having the signal cleaned in this way should help > detect the biological artifacts which are valid magnetic signal at the > scalp. But I can't see an easy way to do this since the ft_artifact_* > functions want to load the raw continuous data from disk. I can get > them to act on the in memory trials data if I set the padding options > to 0, but then I get an unacceptable amount of rejections (I guess > because of the filter artifacts the padding usually prevents). > > Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the > denoised signal from ft_denoise_pca and if so how? > > At the moment I am performing the following steps: > > Load each run > Detect jumps with ft_artifact_jump. > Concatenate the jump-free trials from all runs together for this block. > > Visually inspect the reference channels and remove high variance > trials (across the whole block). > Compute denoise PCA weights using only good reference data (and no MEG > jump) trials across the whole block. > > I would now like to apply the denoise PCA weights, perform other > automatic artifact removal on the cleaned data, before further visual > inspection and the next steps of ICA etc. > > Is there any problems with this strategy? > > Thanks in advance for any advice, > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands From robince at gmail.com Wed Feb 6 15:07:30 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 14:07:30 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: <5112625B.9090504@donders.ru.nl> References: <5112625B.9090504@donders.ru.nl> Message-ID: Hi Jörn, Thanks very much. Yes I think that will solve the problem - I hadn't realised I could use negative trial padding values. What I had just got working was as similar approach extracting larger trials at first and then manually making a new trl defintion: % artifact detection tmpcfg = []; tmpcfg.continuous = 'no'; % some trials are excluded tmpcfg.trl = run_clean.sampleinfo; tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + round(filterpad*run_clean.fsample); tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - round(filterpad*run_clean.fsample); [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); which seemed to work but the trlpadding option definitely looks cleaner! Thanks, Robin On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" wrote: > Hi Robin, > > I think the steps you suggested sound reasonable, but I do not see how you > are avoiding the filter artifact issue there, you just postpone it to a > later stage. Instead it might be a smart way to 'pad' your trials when > defining them with 1s pre- and post (so cut out more than you need); that > way all filter artifacts will be in that 1s that you are not interested in > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > understand your question correctly, that solves your problem, doesn't it? > > Best, > Jörn > > > > On 2/6/2013 12:54 PM, Robin wrote: >> >> Hi all, >> >> I am a new fieldtrip user getting started preprocessing a large MEG >> data set (I am in Glasgow and the data was collected at CCNi). >> >> I think I am slowly getting to grips with all the steps necessary, but >> I have a question about the artifact rejection. >> >> My undersanding is that the denoise procedure helps correct external >> sources of noise, so having the signal cleaned in this way should help >> detect the biological artifacts which are valid magnetic signal at the >> scalp. But I can't see an easy way to do this since the ft_artifact_* >> functions want to load the raw continuous data from disk. I can get >> them to act on the in memory trials data if I set the padding options >> to 0, but then I get an unacceptable amount of rejections (I guess >> because of the filter artifacts the padding usually prevents). >> >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the >> denoised signal from ft_denoise_pca and if so how? >> >> At the moment I am performing the following steps: >> >> Load each run >> Detect jumps with ft_artifact_jump. >> Concatenate the jump-free trials from all runs together for this block. >> >> Visually inspect the reference channels and remove high variance >> trials (across the whole block). >> Compute denoise PCA weights using only good reference data (and no MEG >> jump) trials across the whole block. >> >> I would now like to apply the denoise PCA weights, perform other >> automatic artifact removal on the cleaned data, before further visual >> inspection and the next steps of ICA etc. >> >> Is there any problems with this strategy? >> >> Thanks in advance for any advice, >> >> Robin >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > -- > Jörn M. Horschig > PhD Student > Donders Institute for Brain, Cognition and Behaviour > Centre for Cognitive Neuroimaging > Radboud University Nijmegen > Neuronal Oscillations Group > FieldTrip Development Team > > P.O. Box 9101 > NL-6500 HB Nijmegen > The Netherlands > > Contact: > E-Mail: jm.horschig at donders.ru.nl > Tel: +31-(0)24-36-68493 > Web: http://www.ru.nl/donders > > Visiting address: > Trigon, room 2.30 > Kapittelweg 29 > NL-6525 EN Nijmegen > The Netherlands > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From stephen.whitmarsh at gmail.com Wed Feb 6 15:17:39 2013 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Wed, 6 Feb 2013 15:17:39 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: Dear Robin, Please allow me to refer you to the excellent documentation on (negative) padding and artifact rejection in this gorgeous didactical masterpiece, a joy to behold: ***** http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection***** ;-) Stephen On 6 February 2013 15:07, Robin wrote: > Hi Jörn, > > Thanks very much. Yes I think that will solve the problem - I hadn't > realised I could use negative trial padding values. > What I had just got working was as similar approach extracting larger > trials at first and then manually making a new trl defintion: > > % artifact detection > tmpcfg = []; > tmpcfg.continuous = 'no'; % some trials are excluded > tmpcfg.trl = run_clean.sampleinfo; > tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + round(filterpad*run_clean.fsample); > tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - round(filterpad*run_clean.fsample); > > [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); > > which seemed to work but the trlpadding option definitely looks cleaner! > > Thanks, > > Robin > > On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" > wrote: > > Hi Robin, > > > > I think the steps you suggested sound reasonable, but I do not see how > you > > are avoiding the filter artifact issue there, you just postpone it to a > > later stage. Instead it might be a smart way to 'pad' your trials when > > defining them with 1s pre- and post (so cut out more than you need); that > > way all filter artifacts will be in that 1s that you are not interested > in > > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > > understand your question correctly, that solves your problem, doesn't it? > > > > Best, > > Jörn > > > > > > > > On 2/6/2013 12:54 PM, Robin wrote: > >> > >> Hi all, > >> > >> I am a new fieldtrip user getting started preprocessing a large MEG > >> data set (I am in Glasgow and the data was collected at CCNi). > >> > >> I think I am slowly getting to grips with all the steps necessary, but > >> I have a question about the artifact rejection. > >> > >> My undersanding is that the denoise procedure helps correct external > >> sources of noise, so having the signal cleaned in this way should help > >> detect the biological artifacts which are valid magnetic signal at the > >> scalp. But I can't see an easy way to do this since the ft_artifact_* > >> functions want to load the raw continuous data from disk. I can get > >> them to act on the in memory trials data if I set the padding options > >> to 0, but then I get an unacceptable amount of rejections (I guess > >> because of the filter artifacts the padding usually prevents). > >> > >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the > >> denoised signal from ft_denoise_pca and if so how? > >> > >> At the moment I am performing the following steps: > >> > >> Load each run > >> Detect jumps with ft_artifact_jump. > >> Concatenate the jump-free trials from all runs together for this block. > >> > >> Visually inspect the reference channels and remove high variance > >> trials (across the whole block). > >> Compute denoise PCA weights using only good reference data (and no MEG > >> jump) trials across the whole block. > >> > >> I would now like to apply the denoise PCA weights, perform other > >> automatic artifact removal on the cleaned data, before further visual > >> inspection and the next steps of ICA etc. > >> > >> Is there any problems with this strategy? > >> > >> Thanks in advance for any advice, > >> > >> Robin > >> _______________________________________________ > >> fieldtrip mailing list > >> fieldtrip at donders.ru.nl > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > > > > -- > > Jörn M. Horschig > > PhD Student > > Donders Institute for Brain, Cognition and Behaviour > > Centre for Cognitive Neuroimaging > > Radboud University Nijmegen > > Neuronal Oscillations Group > > FieldTrip Development Team > > > > P.O. Box 9101 > > NL-6500 HB Nijmegen > > The Netherlands > > > > Contact: > > E-Mail: jm.horschig at donders.ru.nl > > Tel: +31-(0)24-36-68493 > > Web: http://www.ru.nl/donders > > > > Visiting address: > > Trigon, room 2.30 > > Kapittelweg 29 > > NL-6525 EN Nijmegen > > The Netherlands > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From robince at gmail.com Wed Feb 6 15:26:01 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 14:26:01 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: Hi Stephen, Thanks very much - I think I get it now. Combined with a f_redefinetrial at the end to cut back just the bit I want it seems to work well. In fact it is working so well that almost all my trials are rejected :) but I think that is another problem! Cheers Robin On Wed, Feb 6, 2013 at 2:17 PM, Stephen Whitmarsh wrote: > Dear Robin, > > Please allow me to refer you to the excellent documentation on (negative) > padding and artifact rejection in this gorgeous didactical masterpiece, a > joy to behold: > ***** http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection > ***** > > ;-) > Stephen > > > On 6 February 2013 15:07, Robin wrote: >> >> Hi Jörn, >> >> Thanks very much. Yes I think that will solve the problem - I hadn't >> realised I could use negative trial padding values. >> What I had just got working was as similar approach extracting larger >> trials at first and then manually making a new trl defintion: >> >> % artifact detection >> tmpcfg = []; >> tmpcfg.continuous = 'no'; % some trials are excluded >> tmpcfg.trl = run_clean.sampleinfo; >> tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + >> round(filterpad*run_clean.fsample); >> tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - >> round(filterpad*run_clean.fsample); >> >> [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); >> >> which seemed to work but the trlpadding option definitely looks cleaner! >> >> Thanks, >> >> Robin >> >> On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" >> wrote: >> > Hi Robin, >> > >> > I think the steps you suggested sound reasonable, but I do not see how >> > you >> > are avoiding the filter artifact issue there, you just postpone it to a >> > later stage. Instead it might be a smart way to 'pad' your trials when >> > defining them with 1s pre- and post (so cut out more than you need); >> > that >> > way all filter artifacts will be in that 1s that you are not interested >> > in >> > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling >> > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I >> > understand your question correctly, that solves your problem, doesn't >> > it? >> > >> > Best, >> > Jörn >> > >> > >> > >> > On 2/6/2013 12:54 PM, Robin wrote: >> >> >> >> Hi all, >> >> >> >> I am a new fieldtrip user getting started preprocessing a large MEG >> >> data set (I am in Glasgow and the data was collected at CCNi). >> >> >> >> I think I am slowly getting to grips with all the steps necessary, but >> >> I have a question about the artifact rejection. >> >> >> >> My undersanding is that the denoise procedure helps correct external >> >> sources of noise, so having the signal cleaned in this way should help >> >> detect the biological artifacts which are valid magnetic signal at the >> >> scalp. But I can't see an easy way to do this since the ft_artifact_* >> >> functions want to load the raw continuous data from disk. I can get >> >> them to act on the in memory trials data if I set the padding options >> >> to 0, but then I get an unacceptable amount of rejections (I guess >> >> because of the filter artifacts the padding usually prevents). >> >> >> >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the >> >> denoised signal from ft_denoise_pca and if so how? >> >> >> >> At the moment I am performing the following steps: >> >> >> >> Load each run >> >> Detect jumps with ft_artifact_jump. >> >> Concatenate the jump-free trials from all runs together for this block. >> >> >> >> Visually inspect the reference channels and remove high variance >> >> trials (across the whole block). >> >> Compute denoise PCA weights using only good reference data (and no MEG >> >> jump) trials across the whole block. >> >> >> >> I would now like to apply the denoise PCA weights, perform other >> >> automatic artifact removal on the cleaned data, before further visual >> >> inspection and the next steps of ICA etc. >> >> >> >> Is there any problems with this strategy? >> >> >> >> Thanks in advance for any advice, >> >> >> >> Robin >> >> _______________________________________________ >> >> fieldtrip mailing list >> >> fieldtrip at donders.ru.nl >> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > >> > >> > >> > -- >> > Jörn M. Horschig >> > PhD Student >> > Donders Institute for Brain, Cognition and Behaviour >> > Centre for Cognitive Neuroimaging >> > Radboud University Nijmegen >> > Neuronal Oscillations Group >> > FieldTrip Development Team >> > >> > P.O. Box 9101 >> > NL-6500 HB Nijmegen >> > The Netherlands >> > >> > Contact: >> > E-Mail: jm.horschig at donders.ru.nl >> > Tel: +31-(0)24-36-68493 >> > Web: http://www.ru.nl/donders >> > >> > Visiting address: >> > Trigon, room 2.30 >> > Kapittelweg 29 >> > NL-6525 EN Nijmegen >> > The Netherlands >> > >> > _______________________________________________ >> > fieldtrip mailing list >> > fieldtrip at donders.ru.nl >> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From jm.horschig at donders.ru.nl Wed Feb 6 15:38:59 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Wed, 06 Feb 2013 15:38:59 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: <51126B03.3030106@donders.ru.nl> only a brilliant mind might have created such a guide - chapeau ^^ On 2/6/2013 3:17 PM, Stephen Whitmarsh wrote: > Dear Robin, > > Please allow me to refer you to the excellent documentation on > (negative) padding and artifact rejection in this gorgeous didactical > masterpiece, a joy to behold: > ***** > http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection ***** > > ;-) > Stephen > > On 6 February 2013 15:07, Robin > wrote: > > Hi Jörn, > > Thanks very much. Yes I think that will solve the problem - I hadn't > realised I could use negative trial padding values. > What I had just got working was as similar approach extracting larger > trials at first and then manually making a new trl defintion: > > % artifact detection > tmpcfg = []; > tmpcfg.continuous = 'no'; % some trials are excluded > tmpcfg.trl = run_clean.sampleinfo; > tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + > round(filterpad*run_clean.fsample); > tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - > round(filterpad*run_clean.fsample); > > [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); > > which seemed to work but the trlpadding option definitely looks > cleaner! > > Thanks, > > Robin > > On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" > > wrote: > > Hi Robin, > > > > I think the steps you suggested sound reasonable, but I do not > see how you > > are avoiding the filter artifact issue there, you just postpone > it to a > > later stage. Instead it might be a smart way to 'pad' your > trials when > > defining them with 1s pre- and post (so cut out more than you > need); that > > way all filter artifacts will be in that 1s that you are not > interested in > > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > > understand your question correctly, that solves your problem, > doesn't it? > > > > Best, > > Jörn > > > > > > > > On 2/6/2013 12:54 PM, Robin wrote: > >> > >> Hi all, > >> > >> I am a new fieldtrip user getting started preprocessing a large MEG > >> data set (I am in Glasgow and the data was collected at CCNi). > >> > >> I think I am slowly getting to grips with all the steps > necessary, but > >> I have a question about the artifact rejection. > >> > >> My undersanding is that the denoise procedure helps correct > external > >> sources of noise, so having the signal cleaned in this way > should help > >> detect the biological artifacts which are valid magnetic signal > at the > >> scalp. But I can't see an easy way to do this since the > ft_artifact_* > >> functions want to load the raw continuous data from disk. I can get > >> them to act on the in memory trials data if I set the padding > options > >> to 0, but then I get an unacceptable amount of rejections (I guess > >> because of the filter artifacts the padding usually prevents). > >> > >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. > on the > >> denoised signal from ft_denoise_pca and if so how? > >> > >> At the moment I am performing the following steps: > >> > >> Load each run > >> Detect jumps with ft_artifact_jump. > >> Concatenate the jump-free trials from all runs together for > this block. > >> > >> Visually inspect the reference channels and remove high variance > >> trials (across the whole block). > >> Compute denoise PCA weights using only good reference data (and > no MEG > >> jump) trials across the whole block. > >> > >> I would now like to apply the denoise PCA weights, perform other > >> automatic artifact removal on the cleaned data, before further > visual > >> inspection and the next steps of ICA etc. > >> > >> Is there any problems with this strategy? > >> > >> Thanks in advance for any advice, > >> > >> Robin > >> _______________________________________________ > >> fieldtrip mailing list > >> fieldtrip at donders.ru.nl > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > > > > -- > > Jörn M. Horschig > > PhD Student > > Donders Institute for Brain, Cognition and Behaviour > > Centre for Cognitive Neuroimaging > > Radboud University Nijmegen > > Neuronal Oscillations Group > > FieldTrip Development Team > > > > P.O. Box 9101 > > NL-6500 HB Nijmegen > > The Netherlands > > > > Contact: > > E-Mail: jm.horschig at donders.ru.nl > > Tel: +31-(0)24-36-68493 > > Web: http://www.ru.nl/donders > > > > Visiting address: > > Trigon, room 2.30 > > Kapittelweg 29 > > NL-6525 EN Nijmegen > > The Netherlands > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Wed Feb 6 21:59:16 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Wed, 6 Feb 2013 20:59:16 +0000 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Thank you so much - I downloaded the newest version of FieldTrip, and it works as expected. I was using one from early in January. To answer some of your questions... When I ran ft_prepare_headmodel with a singleshell method, I used the process described here: http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg?s[]=singleshell cfg=[];cfg.method='singleshell'; vol=ft_prepare_headmodel(cfg,segmentedmri); I have one follow-up question - - I'd like to visualize the results. According to the fieldtrip faq: http://fieldtrip.fcdonders.nl/faq/how_can_i_visualize_the_different_geometrical_objects_that_are_needed_for_forward_and_inverse_computations "The low level plotting functions do not support the multisphere volume conductor models." But the deprecated function doesn't seem to work... I have some other questions regarding coercing my nifti format MRI into the correct coordinate system, but I'll save those for another post. Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From evaladez at psych.udel.edu Wed Feb 6 23:38:06 2013 From: evaladez at psych.udel.edu (Emilio Valadez) Date: Wed, 6 Feb 2013 17:38:06 -0500 Subject: [FieldTrip] Reading events from an EDF file Message-ID: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> Dear FieldTrip users, I am trying to define trials from a continuous EEG data set that was exported from BESA to .edf format, but I'm having trouble reading the events with FieldTrip. The events are located in a separate channel that was appended to the EEG data. After running ft_definetrial with cfg.trialdef.eventtype set to '?' (in order to see the event types and event values in the data), I received the following output: the following events were found in the datafile event type: 'trial' with event values: no trials have been defined yet, see FT_DEFINETRIAL for further help found 720 events created 0 trials the call to "ft_definetrial" took 1 seconds It seems that ft_definetrial is not reading any events except for trials, which should not be present in the data. As a comparison, I opened the data set with eeglab, which did read the events properly, leading me to believe that the event information is in fact part of the file. How can I get ft_definetrial to correctly read the events? Thanks in advance for your help. Emilio -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 7 00:33:42 2013 From: frank.ye.mei at gmail.com (Frank Mei) Date: Wed, 6 Feb 2013 18:33:42 -0500 Subject: [FieldTrip] need example code - activity of condition 1 contrasted with condition 2. Message-ID: Hi All, The tutorial here (http://fieldtrip.fcdonders.nl/tutorial/beamformer) provides example of activity contrasted with baseline, but not activity of condition 1 contrasted with condition 2. Could someone kindly give some example code that contrasts two activities, for example left vs right button pressing? I am thinking about modifying the example code in the tutorial, by turn the code ------- sourceDiff = sourcePost_con; sourceDiff.avg.pow = (sourcePost_con.avg.pow - sourcePre_con.avg.pow) ./ sourcePre_con.avg.pow; -------- into A: -------- sourceDiff = sourceLeft_con; sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) ./ sourceRight_con.avg.pow; -------- or into B: -------- sourceDiff = sourceRight_con; sourceDiff.avg.pow = (sourceRight_con.avg.pow - sourceLeft_con.avg.pow) ./ sourceLeft_con.avg.pow; -------- Not sure if I should use "A" or "B", or something else. thanks, Frank -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at donders.ru.nl Thu Feb 7 08:35:30 2013 From: johanna.zumer at donders.ru.nl (Johanna Zumer) Date: Thu, 7 Feb 2013 08:35:30 +0100 Subject: [FieldTrip] need example code - activity of condition 1 contrasted with condition 2. In-Reply-To: References: Message-ID: Dear Frank, You're on the right way of thinking. I think the answer partially depends on your hypothesis. In the tutorial situation of a Post and Pre, there is the hypothesis that nothing of interest is going on in Pre, and that the experimental manipulation is causing something to occur in Post, and the researcher is asking how Post differs from Pre. In your case of Left and Right, if you are assuming that these are equally interesting experimental manipulations (i.e. neither is the 'baseline' condition), then often the denominator is formed by the average of the two conditions: sourceDiff = sourceLeft_con; % or sourceRight_con, does not matter sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) ./ (0.5* sourceLeft_con.avg.pow +0.5* sourceRight_con.avg.pow); Cheers, Johanna 2013/2/7 Frank Mei > Hi All, > > The tutorial here (http://fieldtrip.fcdonders.nl/tutorial/beamformer) > provides example of activity contrasted with baseline, but not activity of > condition 1 contrasted with condition 2. > > Could someone kindly give some example code that contrasts two activities, > for example left vs right button pressing? > > I am thinking about modifying the example code in the tutorial, by turn > the code > ------- > sourceDiff = sourcePost_con; > sourceDiff.avg.pow = (sourcePost_con.avg.pow - sourcePre_con.avg.pow) ./ > sourcePre_con.avg.pow; > -------- > into A: > -------- > sourceDiff = sourceLeft_con; > sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) > ./ sourceRight_con.avg.pow; > -------- > > or into B: > -------- > sourceDiff = sourceRight_con; > sourceDiff.avg.pow = (sourceRight_con.avg.pow - sourceLeft_con.avg.pow) > ./ sourceLeft_con.avg.pow; > -------- > > Not sure if I should use "A" or "B", or something else. > > thanks, > Frank > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From patrick.jung at esi-frankfurt.de Fri Feb 8 12:06:07 2013 From: patrick.jung at esi-frankfurt.de (Jung, Patrick) Date: Fri, 8 Feb 2013 11:06:07 +0000 Subject: [FieldTrip] ft_freqgrandaverage Message-ID: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> Hi Fieldtrippers, To get a feeling of my data I want to visually inspect the data and look where are differences between the conditions by plotting the grand-averages of TFRs. By using ft_freqgrandaverage I noticed that it gives back NaN if freq entries for one time bin are missing for one subject (n=28). [cid:image003.jpg at 01CE05F4.DAF32510] 1. sSTOP, 2. cAC, 3. diff In my data with variable trial lengths, the shortest poststim time point is around 0.06 s in one condition (cAC) and in one subject but I expect my effects around 0.1-0.35 s. How can I overcome this problem? Is there a more appropriate fieldtrip function or do I have to write a special self-made Matlab code? Here is an excerpt of my code: GA_sSTOP = ft_freqgrandaverage(cfg, AllSubjMat_sSTOP{1,:}); % where AllSubjMat_sSTOP contains TFRs of all subjects in a <1x28 cell> GA_cAC = ft_freqgrandaverage(cfg, AllSubjMat_cAC{1,:}); GA_diff.powspctrm = (GA_sSTOP.powspctrm - GA_cAC.powspctrm) ./ (0.5*GA_sSTOP.powspctrm + 0.5*GA_cAC.powspctrm); Many thanks for your help! Cheers, Patrick -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image003.jpg Type: image/jpeg Size: 11890 bytes Desc: image003.jpg URL: From jm.horschig at donders.ru.nl Fri Feb 8 12:37:58 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 08 Feb 2013 12:37:58 +0100 Subject: [FieldTrip] ft_freqgrandaverage In-Reply-To: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> References: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> Message-ID: <5114E396.5050605@donders.ru.nl> Hi Patrick, I think you have to write this yourself. I never tried though, so maybe there is a way. It's a tricky thing to what you want, so I guess that's why it is not implemented. If you average for some time bins over less repetitions than for others, you get a weaker noise estimate, thereby any effects found or not found could be attributed to plain noise. Put in another way, depending on what analysis you are doing, you might get into trouble with your statistics because of different degrees of freedom per time bin. Also note that for frequency data, power has only positive values with a lower bound of zero, thus noise can only increase the power estimate and not cancel out (so more noise = more power), thus a difference in a later time bin between conditions might be explained by having lower df (fewer observations, more noise) in one condition than in the other, especially if power is greater in the condition with fewer observation. I would strongly suggest to throw out trials which do not reach your time of interest and process only these (i.e. throw out that one subject) unless you really know what you are doing. On the other hand as already mentioned, I never tried and never did this, so maybe there is some neat way to achieve what you want (you'd be probably notice, cause people would reply to this response rather fast). Best, Jörn On 2/8/2013 12:06 PM, Jung, Patrick wrote: > > Hi Fieldtrippers, > > To get a feeling of my data I want to visually inspect the data and > look where are differences between the conditions > > by plotting the grand-averages of TFRs. > > By using *ft_freqgrandaverage*I noticed that it gives back *NaN* > > if freq entries for one time bin are missing for one subject (n=28). > > 1.sSTOP, 2. cAC, 3. diff > > In my data with variable trial lengths, the shortest poststim time > point is around 0.06 s in one condition (cAC) and in one subject > > but I expect my effects around 0.1-0.35 s. > > How can I overcome this problem? Is there a more appropriate fieldtrip > function or do I have to write a special self-made Matlab code? > > Here is an excerpt of my code: > > GA_sSTOP = ft_freqgrandaverage(cfg, AllSubjMat_sSTOP{1,:}); > > % where AllSubjMat_sSTOP contains TFRs of all subjects in a <1x28 cell> > > GA_cAC = ft_freqgrandaverage(cfg, AllSubjMat_cAC{1,:}); > > GA_diff.powspctrm = (GA_sSTOP.powspctrm - GA_cAC.powspctrm) ./ > (0.5*GA_sSTOP.powspctrm + 0.5*GA_cAC.powspctrm); > > Many thanks for your help! > > Cheers, > > Patrick > > ** > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: image/jpeg Size: 11890 bytes Desc: not available URL: From robince at gmail.com Fri Feb 8 12:52:09 2013 From: robince at gmail.com (Robin) Date: Fri, 8 Feb 2013 11:52:09 +0000 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? Message-ID: Hello, Having got through the preprocessing I am now investigating source reconstruction. The information on the web site is very useful. This tutorial page: http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed Spatio-temporal EEG/MEG Inverse Solver which looks interesting but I wondered if this method was actually implemented in fieldtrip (or elsewhere). When I look in minimumnormestimate.m this reference is not listed as one of the methods implemented. Is it available as a different named method? Thanks for any help. Robin From Andrew.Dykstra at med.uni-heidelberg.de Fri Feb 8 13:32:42 2013 From: Andrew.Dykstra at med.uni-heidelberg.de (Andrew R. Dykstra) Date: Fri, 8 Feb 2013 13:32:42 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: Message-ID: Hi Robin, The MNE Python package implements mixed L1/L2 norm solutions. Not sure if something similar exists in Fieldtrip. Cheers, Andy On Feb 8, 2013 1:12 PM, "Robin" wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 13:51:31 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 13:51:31 +0100 Subject: [FieldTrip] Reading events from an EDF file In-Reply-To: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> References: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> Message-ID: <43B67570-A429-4C0B-B936-FCE3B96CF778@donders.ru.nl> Dear Emilio EDF is a fileformat that is widely supported, but that does not have a standard way of storing events in the file. Hence FieldTrip cannot find them. The later EDF+ extension to the fileformat describes how to store annotations (like events) in the file, but this "annotation channel" is not used by many software packages as it is rather clumsy for storing trigger information. Consequently, most software packages have their own ways of storing events. Usually it is dealt with in a very similar manner by adding a binary channel with the same sampling rate and with 0 if there is no, and another value if there is a trigger. The EDF format is written in (short) segments, those are the trials you see in the event structure. If there is a trigger, status, or event channel, you'll have to detect that yourself (e.f. using ft_databrowser). Subsequently you can make a custom "trial function", i.e. a function that reads that channel and defines the data segments to your requirements. Have a look at http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition and http://fieldtrip.fcdonders.nl/tag/trialfun?do=showtag&tag=trialfun best regards, Robert On 6 Feb 2013, at 23:38, Emilio Valadez wrote: > Dear FieldTrip users, > > I am trying to define trials from a continuous EEG data set that was exported from BESA to .edf format, but I’m having trouble reading the events with FieldTrip. The events are located in a separate channel that was appended to the EEG data. > > After running ft_definetrial with cfg.trialdef.eventtype set to ‘?’ (in order to see the event types and event values in the data), I received the following output: > > the following events were found in the datafile > event type: 'trial' with event values: > no trials have been defined yet, see FT_DEFINETRIAL for further help > found 720 events > created 0 trials > the call to "ft_definetrial" took 1 seconds > > It seems that ft_definetrial is not reading any events except for trials, which should not be present in the data. As a comparison, I opened the data set with eeglab, which did read the events properly, leading me to believe that the event information is in fact part of the file. How can I get ft_definetrial to correctly read the events? > > Thanks in advance for your help. > > Emilio > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 13:53:37 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 13:53:37 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: Message-ID: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Hi Robin, The FieldTrip cfg.method='mne' in FT_SOURCEANALYSIS implements an L2 solver, but not an L1 solver. The actual code with more details is in fieldtrip/inverse/minimumnormestimate., best regards, Robert On 8 Feb 2013, at 13:32, Andrew R. Dykstra wrote: > Hi Robin, > > The MNE Python package implements mixed L1/L2 norm solutions. Not sure if something similar exists in Fieldtrip. > > Cheers, > Andy > > On Feb 8, 2013 1:12 PM, "Robin" wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 14:04:07 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 14:04:07 +0100 Subject: [FieldTrip] GE MRI platform 12.0 scans don't import into CTF MRIViewer In-Reply-To: References: Message-ID: <182EAA41-16F5-448D-BFDF-9252C99A6443@donders.ru.nl> Hi Inna, You could try ft_read_mri with as input one of the files that comprises the volume. I never tested it with GE, but for Siemens it is able to figure out the other file names and put the slices in the correct order. The ft_read_mri uses the MATLAB dicom reader for each slice and puts them in a volume. Subsequently you would do ft_volumerealign to assign the head coordinate system, potentially followed by ft_volumereslice. See http://fieldtrip.fcdonders.nl/faq/how_can_i_convert_an_anatomical_mri_from_dicom_into_ctf_format http://fieldtrip.fcdonders.nl/faq/why_does_my_anatomical_mri_show_upside-down_when_plotting_it_with_ft_sourceplot http://fieldtrip.fcdonders.nl/tag/coordinate?do=showtag&tag=coordinate best Robert On 28 Jan 2013, at 17:55, McGowin, Inna wrote: > Hello, > > We have an MRI research scan, GE MRI platform 12.0, that produces scans with some DICOM header fields missing. > These fields are required in order to import the scan into CTF MRIViewer or DICOM_Viewer or some other software. > Does anybody know if these missing fields can be somehow added to the DICOM header? Maybe in Matlab or through some conversion method? > > Thanks! > -- > Inna > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From r.oostenveld at donders.ru.nl Fri Feb 8 14:36:53 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 14:36:53 +0100 Subject: [FieldTrip] Combined EEG and MEG source reconstruction In-Reply-To: References: Message-ID: <8FB714F5-02E8-4B44-96C3-E8472120AD4F@donders.ru.nl> Dear Mushfa In principle it can be made to work, but you'll have to do a little bit of work outside fieldtrip. You would start with 1) ft_prepare_headmodel and ft_prepare_leadfield for the MEG part 2) ft_prepare_headmodel and ft_prepare_leadfield for the EEG part Subsequently you would (manually) concatenate the leadfields of the MEG and EEG. Here you have to make sure that the channel order is consistent with that in your combined data. The resulting structure with combined leadfields can be passed into ft_sourceanalysis as cfg.grid. However, I foresee a problem with the scaling. At this moment FieldTrip is not (yet) very precise in maintaining the correct units throughout. Consequently you might get different units for the EEG and MEG contribution to each dipole, causing weird cancelation effects. You'll just have to check carefully that the leadfield units and the data units consistently scaled between megmag, megplanar and eeg. This brings me to another known problem for the combined vectorview magnetometer and planar gradiometer channels: at this moment the forward computation computes both in T (or fT), whereas the data is represented as T for the magnetometers and T/m for the gradiometers. So the gradiometer leadfields are off by a factor "1/baseline", which is approximately 1/70 if I recall correctly. Many neuromag users use only the planar channels, and therefore don't notice. We are working on fixing the neuromag channel/gradiometer units. That is not as simple as it appears, because conversions of the geometrical dimensions from m to cm or mm also affect the gradiometer baseline. So converting the data from m to mm should result in the planar channel data getting 1000 times smaller, whereas the magnetometer channels shoudl stay the same. See http://bugzilla.fcdonders.nl/show_bug.cgi?id=963 and http://bugzilla.fcdonders.nl/show_bug.cgi?id=963 if you want to follow this. best regards Robert On 28 Jan 2013, at 20:20, Mushfa Yousuf wrote: > Hello Fieldtrippers, > > I am currently doing source analysis using beamformer method in fieldtrip. > The data i work on is a simultaneous measurement of MEG (306) with EEG > (128) on PD patients. > > I was successful in calculating the sources for both the modalities alone. > > I tried according the tutorial "Combined EEG and MEG source reconstruction" and was successful till the estimation > of the lead field. But, then when i want to use the created vol for the > source analysis i have two structures one for EEG and the second one for > MEG. Now, i can only define only one to estimate the sources. How to use > this for both the modalities? Any help would be appreciated. > > With regards > Mushfa > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From alexandre.gramfort at inria.fr Fri Feb 8 14:42:14 2013 From: alexandre.gramfort at inria.fr (Alexandre Gramfort) Date: Fri, 8 Feb 2013 14:42:14 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> References: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Message-ID: Hi Robin, the solver for inverse problem with L1/L2 prior as described in: A Distributed Spatio-temporal EEG/MEG Inverse Solver is not really tractable on real data. My recent work [1] explains how to solve it more efficiently in a few seconds. [1] http://www.ncbi.nlm.nih.gov/pubmed/22421459 This is what I implemented in mne-python: http://martinos.org/mne/auto_examples/inverse/plot_mixed_norm_L21_inverse.html#example-inverse-plot-mixed-norm-l21-inverse-py I have matlab code too but it's less optimized in terms of speed. If you feel like porting it into Fieldtrip that would be much appreciated. See this page that deserves some updates: http://embal.gforge.inria.fr/ If you're into these methods I invite you to have a look at the next improvement using Time-Frequency transforms: http://www.ncbi.nlm.nih.gov/pubmed/23291276 with demo code: http://martinos.org/mne/auto_examples/inverse/plot_time_frequency_mixed_norm_inverse.html#example-inverse-plot-time-frequency-mixed-norm-inverse-py This contribution explains how to correct for amplitude bias and take care of loose orientation constraints when working with cortical source spaces. Best, Alex PS : sorry Robert for advertising mne on the fieldtrip mailing list ... -- Alexandre Gramfort, PhD Assistant Professor, TSI, Telecom ParisTech, CNRS LTCI 37-39 Rue Dareau, 75014 Paris, France http://alexandre.gramfort.net alexandre.gramfort at telecom-paristech.fr On Fri, Feb 8, 2013 at 12:52 PM, Robin wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the e-mail > contains patient information, please contact the Partners Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in error > but does not contain patient information, please contact the sender and properly > dispose of the e-mail. > From nugenta at mail.nih.gov Fri Feb 8 17:35:59 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 8 Feb 2013 16:35:59 +0000 Subject: [FieldTrip] headmodels Message-ID: Hello, I have more simple questions, this time about headmodels. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 22:37:47 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 22:37:47 +0100 Subject: [FieldTrip] MEG toolkit course in Nijmegen - registration is open Message-ID: On April 8-11, 2013 we will host the "Toolkit of Cognitive Neuroscience: advanced data analysis and source modelling of EEG and MEG data" at the Donders Institute in Nijmegen. This 4-day toolkit course will teach you advanced MEG and EEG data analysis skills. Preprocessing, frequency analysis, source reconstruction and various statistical methods will be covered. The toolkit will consist of a number of lectures, followed by hands-on sessions in which you will be tutored through the complete analysis of a MEG data set using the FieldTrip toolbox. There will be time to ask questions and discuss analysis methods pertaining to your reseach questions. In the last hands-on session you will get started with the analysis on the data that you will bring yourself The registration for this toolkit course is now open and can be found on http://www.ru.nl/donders/course-information/2013courses/toolkit-cognitive-4/ The fee for senior participants is € 400. The (PhD) student fee is € 200. Registration fee includes coffee/tea, Dutch sandwich lunches and one dinner. Please note that in the past years the course was oversubscribed and we expect that as well for this year. We will be able to host approximately 40 participants and consequently we are likely to be required to make a selection that is based on the information that you provide on the registration form. Note that neither being a very novice or a very expert in EEG/MEG automatically disqualifies you from participating. We select the participants on basis of their motivation, research background and skills, and whether we expect the course to pay off for the participant (i.e. whether there is a match between course content and the expectations and requirements for fruitfull use of the analysis methods that we'll cover). Furthermore, we try to make a nice group of participants with a homogenous level and with sufficient broad coverage of research interests. The deadline for the initial registration is March 1, 2013. You can have a look at our Facebook page on http://www.facebook.com/fieldtriptoolbox to get an impression from the previous "MEG/EEG toolkit course" in May 2012. Best regards, Robert Oostenveld and Jan-Mathijs Schoffelen From robince at gmail.com Mon Feb 11 12:37:30 2013 From: robince at gmail.com (Robin) Date: Mon, 11 Feb 2013 11:37:30 +0000 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Message-ID: Hi Alexander, Thanks very much for the pointers. I am completely new to the area and was looking at that paper only because it was linked in the Fieldtrip tutorial which I thought would be a good place to start! I will definitely check out all the other useful information you provided. Thanks again, Robin On Fri, Feb 8, 2013 at 1:42 PM, Alexandre Gramfort wrote: > Hi Robin, > > the solver for inverse problem with L1/L2 prior as described in: > > A Distributed Spatio-temporal EEG/MEG Inverse Solver > > is not really tractable on real data. My recent work [1] > explains how to solve it more efficiently in a few seconds. > > [1] http://www.ncbi.nlm.nih.gov/pubmed/22421459 > > This is what I implemented in mne-python: > > http://martinos.org/mne/auto_examples/inverse/plot_mixed_norm_L21_inverse.html#example-inverse-plot-mixed-norm-l21-inverse-py > > I have matlab code too but it's less optimized in terms of speed. If > you feel like porting > it into Fieldtrip that would be much appreciated. See this page that > deserves some updates: > > http://embal.gforge.inria.fr/ > > If you're into these methods I invite you to have a look at the next > improvement using Time-Frequency transforms: > > http://www.ncbi.nlm.nih.gov/pubmed/23291276 > > with demo code: > > http://martinos.org/mne/auto_examples/inverse/plot_time_frequency_mixed_norm_inverse.html#example-inverse-plot-time-frequency-mixed-norm-inverse-py > > This contribution explains how to correct for amplitude bias and take > care of loose orientation constraints when working with cortical > source spaces. > > Best, > Alex > > PS : sorry Robert for advertising mne on the fieldtrip mailing list ... > > -- > Alexandre Gramfort, PhD > Assistant Professor, > TSI, Telecom ParisTech, CNRS LTCI > 37-39 Rue Dareau, 75014 Paris, France > http://alexandre.gramfort.net > alexandre.gramfort at telecom-paristech.fr > > > > > On Fri, Feb 8, 2013 at 12:52 PM, Robin wrote: >> Hello, >> >> Having got through the preprocessing I am now investigating source >> reconstruction. >> >> The information on the web site is very useful. This tutorial page: >> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate >> >> Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed >> Spatio-temporal EEG/MEG Inverse Solver >> >> which looks interesting but I wondered if this method was actually >> implemented in fieldtrip (or elsewhere). When I look in >> minimumnormestimate.m this reference is not listed as one of the >> methods implemented. Is it available as a different named method? >> >> Thanks for any help. >> >> Robin >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> >> >> The information in this e-mail is intended only for the person to whom it is >> addressed. If you believe this e-mail was sent to you in error and the e-mail >> contains patient information, please contact the Partners Compliance HelpLine at >> http://www.partners.org/complianceline . If the e-mail was sent to you in error >> but does not contain patient information, please contact the sender and properly >> dispose of the e-mail. >> > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From polomacnenad at gmail.com Mon Feb 11 17:14:00 2013 From: polomacnenad at gmail.com (Nenad Polomac) Date: Mon, 11 Feb 2013 17:14:00 +0100 Subject: [FieldTrip] problem with ft_singleplotTFR Message-ID: Dear fieldtrip users, I have problem with ft_singleplotTFR. Please have a look on attached image. Has anybody had similar problem? Thank you in advance! Nenad -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: ft_singlplotTFR.jpg Type: image/jpeg Size: 759989 bytes Desc: not available URL: From sophiechen33 at gmail.com Tue Feb 12 11:46:36 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Tue, 12 Feb 2013 11:46:36 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases Message-ID: Dear Fieldtripers I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: *with fieldtrip fieldtrip-20111024 * cfg = []; cfg.name = 'ctf'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path the input is volume data with dimensions [256 256 256] Converting the coordinate system from ctf to spm performing the segmentation on the specified volume segmentedmri = dim: [256 256 256] transform: [4x4 double] coordsys: 'ctf' unit: 'mm' gray: [256x256x256 double] white: [256x256x256 double] csf: [256x256x256 double] cfg: [1x1 struct] *with fieldtrip 'fieldtrip-20121203' * >> cfg = []; cfg.name = 'ctf'; cfg.write = 'no'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 > In ft_defaults at 60 In ft_volumesegment at 130 the input is volume data with dimensions [256 256 256] Converting the coordinate system from ctf to spm Rescaling NIFTI: slope = 0.00342945, intercept = 0 Smoothing by 0 & 8mm.. Coarse Affine Registration.. Fine Affine Registration.. Error using ft_write_mri (line 128) unsupported data format Error in ft_volumesegment (line 274) Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); * and 'fieldtrip-20130210*' cfg = []; cfg.name = 'ctf'; cfg.write = 'no'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); the input is volume data with dimensions [256 256 256] Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path Converting the coordinate system from ctf to spm Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path Rescaling NIFTI: slope = 0.00342945, intercept = 0 Smoothing by 0 & 8mm.. Coarse Affine Registration.. Fine Affine Registration.. Warning: could not open ctf.img > In fileio\private\warning_once at 116 In fileio\private\filetype_check_header at 54 In ft_filetype at 338 In ft_write_mri at 54 In ft_volumesegment at 282 Error using ft_write_mri (line 128) unsupported data format Error in ft_volumesegment (line 282) Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); Please help... :-) it's not convenient to switch fieldtrip version while running scripts... Thanks a lot! cheers Sophie -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 12 12:07:08 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 12 Feb 2013 12:07:08 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases In-Reply-To: References: Message-ID: <3E0FF981-1B4D-46DF-A999-C64AFCB4AE89@donders.ru.nl> Dear Sophie, What happens if you don't specify cfg.name? It seems that you don't need the output to be written to a file anyway (since you also specify cfg.write = 'no'); Best, Jan-Mathijs On Feb 12, 2013, at 11:46 AM, sophie chen wrote: > Dear Fieldtripers > > I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: > with fieldtrip fieldtrip-20111024 > > cfg = []; > cfg.name = 'ctf'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path > > the input is volume data with dimensions [256 256 256] > Converting the coordinate system from ctf to spm > performing the segmentation on the specified volume > segmentedmri = > dim: [256 256 256] > transform: [4x4 double] > coordsys: 'ctf' > unit: 'mm' > gray: [256x256x256 double] > white: [256x256x256 double] > csf: [256x256x256 double] > cfg: [1x1 struct] > > with fieldtrip 'fieldtrip-20121203' > > >> cfg = []; > cfg.name = 'ctf'; > cfg.write = 'no'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 > > In ft_defaults at 60 > In ft_volumesegment at 130 > the input is volume data with dimensions [256 256 256] > Converting the coordinate system from ctf to spm > Rescaling NIFTI: slope = 0.00342945, intercept = 0 > Smoothing by 0 & 8mm.. > Coarse Affine Registration.. > Fine Affine Registration.. > Error using ft_write_mri (line 128) > unsupported data format > Error in ft_volumesegment (line 274) > Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); > > > and 'fieldtrip-20130210' > > cfg = []; > cfg.name = 'ctf'; > cfg.write = 'no'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > the input is volume data with dimensions [256 256 256] > > Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path > > Converting the coordinate system from ctf to spm > > Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path > > Rescaling NIFTI: slope = 0.00342945, intercept = 0 > Smoothing by 0 & 8mm.. > Coarse Affine Registration.. > Fine Affine Registration.. > Warning: could not open ctf.img > > In fileio\private\warning_once at 116 > In fileio\private\filetype_check_header at 54 > In ft_filetype at 338 > In ft_write_mri at 54 > In ft_volumesegment at 282 > Error using ft_write_mri (line 128) > unsupported data format > Error in ft_volumesegment (line 282) > Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); > > Please help... :-) it's not convenient to switch fieldtrip version while running scripts... > Thanks a lot! > > cheers > Sophie > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophiechen33 at gmail.com Tue Feb 12 15:42:48 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Tue, 12 Feb 2013 15:42:48 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases In-Reply-To: References: Message-ID: Hi Jan-Mathijs Thanks for you reply, I just figure out where the problem is coming from (and you are totally right about the * cfg.name = 'ctf' :-) *, completely no sens what I wrote... ) So the problem I had (and I also had some problems while using ft_prepare_headmodel) is coming from the ft_defaults.m, the one from more recent release which is not working for me.... (I always run ft_defaults before executing my programs) So I used the one from the 20111024 release Now, everything is working! I also talk to another Fieldtrip user in our lab, and he couldn't run the fieldtrip functions, unless 'adding fieldtrip directory in path with subfolders' which created conflicts with eeglab toolbox... Is there actually a problem with the ft_defaults.m file itself or is it coming from our Matlab version (2012b)? What should we use instead? Thanks! Cheers, Sophie Dear Sophie, What happens if you don't specify cfg.name? It seems that you don't need the output to be written to a file anyway (since you also specify cfg.write = 'no'); Best, Jan-Mathijs On Feb 12, 2013, at 11:46 AM, sophie chen wrote: >* Dear Fieldtripers*>* *>* I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: *>* with fieldtrip fieldtrip-20111024 *>* *>* cfg = [];*>* cfg.name = 'ctf';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path *>* *>* the input is volume data with dimensions [256 256 256]*>* Converting the coordinate system from ctf to spm*>* performing the segmentation on the specified volume*>* segmentedmri = *>* dim: [256 256 256]*>* transform: [4x4 double]*>* coordsys: 'ctf'*>* unit: 'mm'*>* gray: [256x256x256 double]*>* white: [256x256x256 double]*>* csf: [256x256x256 double]*>* cfg: [1x1 struct]*>* *>* with fieldtrip 'fieldtrip-20121203' *>* *>* >> cfg = [];*>* cfg.name = 'ctf';*>* cfg.write = 'no';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 *>* > In ft_defaults at 60*>* In ft_volumesegment at 130 *>* the input is volume data with dimensions [256 256 256]*>* Converting the coordinate system from ctf to spm*>* Rescaling NIFTI: slope = 0.00342945, intercept = 0*>* Smoothing by 0 & 8mm..*>* Coarse Affine Registration..*>* Fine Affine Registration..*>* Error using ft_write_mri (line 128)*>* unsupported data format*>* Error in ft_volumesegment (line 274)*>* Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); *>* *>* *>* and 'fieldtrip-20130210'*>* *>* cfg = [];*>* cfg.name = 'ctf';*>* cfg.write = 'no';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* the input is volume data with dimensions [256 256 256]*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path *>* *>* Converting the coordinate system from ctf to spm*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path *>* *>* Rescaling NIFTI: slope = 0.00342945, intercept = 0*>* Smoothing by 0 & 8mm..*>* Coarse Affine Registration..*>* Fine Affine Registration..*>* Warning: could not open ctf.img *>* > In fileio\private\warning_once at 116*>* In fileio\private\filetype_check_header at 54*>* In ft_filetype at 338*>* In ft_write_mri at 54*>* In ft_volumesegment at 282 *>* Error using ft_write_mri (line 128)*>* unsupported data format*>* Error in ft_volumesegment (line 282)*>* Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); *>* *>* Please help... :-) it's not convenient to switch fieldtrip version while running scripts...*>* Thanks a lot!*>* *>* cheers*>* Sophie*>* _______________________________________________*>* fieldtrip mailing list*>* fieldtrip at donders.ru.nl *>* http://mailman.science.ru.nl/mailman/listinfo/fieldtrip* Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at gmail.com Wed Feb 13 15:05:39 2013 From: cmuehl at gmail.com (Christian Muehl) Date: Wed, 13 Feb 2013 15:05:39 +0100 Subject: [FieldTrip] Call for Papers: 3rd Workshop on Affective Brain-Computer Interfaces at ACII 2013 Message-ID: ** First Call for Papers ** 3rd Workshop on Affective Brain-Computer Interfaces (aBCI) Workshop at ACII 2013 (September 2-5), Geneva, Switzerland, September 2, 2013 http://hmi.ewi.utwente.nl/abci2013 (coming soon) http://www.acii2013.org During the last decade, brain computer interface (BCI) research has developed into a major research field establishing methodological frameworks, guidelines and a core community of established researchers. Besides proving valuable as a communication channel that bypasses impeded muscular pathways, the novel technology also spurred the investigation of applications for able-bodied users, foremost in the fields of entertainment, health and lifestyle. Affective BCI systems allowing users to control computer games, support relaxation training, or trigger your alarm clock during a shallow sleep stage have been proposed, implemented, and sold. Moreover, the affordable hardware and software tools also encouraged artists to play with the idea of a direct access to people’s most private information: their affective and cognitive states. From these explorations followed a number of interesting installations, suggesting novel ways of human-computer as well as human-human interaction: neurotechnology-based systems that encourage affective self-reflection, the synchronization and empathizing between or the competition of different minds, and the collaborative creation and manipulation of digital multimodal content. The third workshop on affective brain-computer interfaces will explore the advantages and limitations of using neuro-physiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in applications for domains like health, arts, and entertainment. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress and their visions, and thus to spur the development of guidelines and frameworks for affective BCI. Topics of interest include, but are not limited to: • emotion elicitation and data collection for affective BCI • detection of affect and mental state via BCI and other modalities • innovative concepts for adaptive interfaces and affective BCI • demos of aBCI systems and artworks Submission Instructions: * The papers should feature original empirical work, theoretical work, or a well defendable but arguable position of the authors. * Papers will be published in the proceedings of ACII 2013 by IEEE. Papers should be limited to 6 + max 2 additional pages (to be charged €100 per page) * Further details about the submission instructions and format will appear on the ACII 2013 website soon. Important Dates: April 20, 2013: Submission of manuscripts May 20, 2013: Acceptance/Rejection notification June 17, 2013: Submission of camera-ready papers and presenting author’s registration September 2, 2013: Date of the Workshop Programme Chairs: * Brendan Allison, University of California, San Diego, USA * Guilliaume Chanel, Swiss Center for Affective Sciences, Geneva, Switzerland, * Christian Mühl, INRIA Bordeaux - Sud-Ouest, France * Anton Nijholt, Universiteit Twente, the Netherlands Programme Committee: * Egon L. van den Broek, TNO Technical Sciences, Delft, the Netherlands * Anne-Marie Brouwer, TNO Perceptual and Cognitive Systems, Soesterberg, the Netherlands * Stephen Fairclough, John Moores University, Liverpool, UK * Didier Grandjean, Swiss Center for Affective Sciences, Geneva, Switzerland * Hayrettin Gürkök, University of Twente, Enschede, the Netherlands * Jonghwa Kim, University of Augsburg, Germany * Brent Lance, Army Research Laboratory/TNB, Aberdeen Proving Ground, USA, * Fabien Lotte, INRIA Bordeaux - Sud-Ouest, France * Winfried Menninghaus, Freie Universität Berlin, Germany * Gary Garcia Molina, Philips Research North America, Briarcliff, USA * Christopher Honey, Princeton University, USA * Olga Sourina, NanYang Technological University, Singapore * Ioannis Patras, Queen Mary University, London, UK * Mannes Poel, University of Twente, Enschede, the Netherlands * Thorsten Zander, Technische Universität Berlin, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: From brungio at gmail.com Wed Feb 13 20:47:36 2013 From: brungio at gmail.com (Bruno L. Giordano) Date: Wed, 13 Feb 2013 19:47:36 +0000 Subject: [FieldTrip] Job: research assistant/associate, University of Glasgow: Lifelong changes in the cerebral processing of social signals Message-ID: <511BEDD8.9030005@gmail.com> Dear list, apologies for cross-postings. RESEARCH ASSISTANT/ASSOCIATE - Ref: 003341 - University of Glasgow - College of Medical, Veterinary and Life Sciences - Institute of Neuroscience and Psychology. Salary: Grade 6 £26,264-£29,541 or Grade 7 £32,267 - £36,298. To contribute to a MRC-funded project entitled “Lifelong changes in the cerebral processing of social signals”. Specifically, the job requires a review of current literature in relevant fields, development of auditory and visual stimuli and experimental procedures, contributing to the design and programming of the behavioral, fMRI and EEG experiments, recruiting and running the participants, assisting in analyzing the results, and participating in the writing up of the results. This post has funding available until 25 March 2014. Apply online at http://www.glasgow.ac.uk/jobs For informal inquiries, please contact Dr Guillaume Rousselet, guillaume.rousselet at glasgow.ac.uk. The University is committed to equality of opportunity in employment. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Bruno L. Giordano, PhD Institute of Neuroscience and Psychology 58 Hillhead Street, University of Glasgow Glasgow, G12 8QB, Scotland T +44 (0) 141 330 5484 Www: http://www.brunolgiordano.net From marek-b at wp.pl Thu Feb 14 14:14:51 2013 From: marek-b at wp.pl (marek) Date: Thu, 14 Feb 2013 14:14:51 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? Message-ID: Dear all, Is it possible to use ft_topoplotER to draw selected frequency peaks over scalp after FFT analysis? I did frequency analysis of EEG signal in the range 3-42 Hz with the following settings: cfg = []; cfg.output = 'pow'; cfg.channel = 'all'; cfg.method = 'mtmfft'; cfg.taper = 'hanning'; cfg.trials = 'all'; cfg.keeptrials = 'no'; cfg.foilim = [3 42]; fft1 = ft_freqanalysis(cfg, avg1); I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. (I've got _only_ frequency domain data). Is it possible to do it with with the ft_topoplotER function? What settings are needed? I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem to be related to the parameter (the frequency selection) I try to manipulate. Any help will be greatly appreciated! Best, Marek Psychophysiology Laboratory, Jagiellonian University, Krakow (PL) From ploner at lrz.tu-muenchen.de Thu Feb 14 14:26:50 2013 From: ploner at lrz.tu-muenchen.de (Markus Ploner) Date: Thu, 14 Feb 2013 14:26:50 +0100 Subject: [FieldTrip] PhD Student in systems neuroscience/pain research in Munich, Germany Message-ID: Applications are invited for a PhD Student position at the Department of Neurology, Technische Universität München, to work on the cerebral representation of pain by using EEG. The project will focus on theneurophysiological correlates of ongoing pain in healthy human subjects andpatients suffering from chronic pain disorders. Major experimental methods include EEG time-frequency analysis, source analysis and connectivity analysis. The candidate will join a research group dedicated to the multimodal investigation of the cerebral representation of pain (http://www.neurokopfzentrum.med.tum.de/neurologie/426.html) which is part of the TUM-Neuroimaging Center (http://www.tumnic.mri.tum.de ). Applicants should have a background in neuroscience, medicine, psychology, physics, engineering, or other relevantdisciplines. Prior experience in EEG experimental design, data acquisition and analysis as well as time series analysis and MATLAB programming are highly desirable. The position is funded by the Deutsche Forschungsgemeinschaft. Salary will be commensurate with the German TVöD salary scale (EG13, 50%). The position is available for three years. Applications will be considered until the position is filled. Candidates may contact Dr. Markus Ploner for more detailed information or directly e-mail their application (ploner at lrz.tum.de). PD Dr. Markus Ploner Department of Neurology Technische Universität München Munich, Germany ploner at lrz.tum.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From ploner at lrz.tu-muenchen.de Thu Feb 14 14:27:49 2013 From: ploner at lrz.tu-muenchen.de (Markus Ploner) Date: Thu, 14 Feb 2013 14:27:49 +0100 Subject: [FieldTrip] Postdoc in systems neuroscience/pain research in Munich, Germany Message-ID: Applications are invited for a postdoctoral position at the Department of Neurology, Technische Universität München, to work on the cerebral representation of pain by using EEG. The project will focus on theneurophysiological correlates of ongoing pain in healthy human subjects andpatients suffering from chronic pain disorders. Major experimental methods include EEG time-frequency analysis, source analysis and connectivity analysis. The candidate will join a research group dedicated to the multimodal investigation of the cerebral representation of pain (http://www.neurokopfzentrum.med.tum.de/neurologie/426.html) which is part of the TUM-Neuroimaging Center (http://www.tumnic.mri.tum.de ). Applicants should have a PhD or comparable background in neuroscience, medicine, psychology, physics, engineering, or other relevant disciplines. Prior experience in EEG experimental design,data acquisition and analysis is necessary. Advanced skills for time seriesanalysis and MATLAB programming are highly desirable. The position is funded by the Deutsche Forschungsgemeinschaft. Salary will be commensurate with the German TVöD salary scale (EG13). The position is initially available for two years, the secondyear contingent on satisfactory progress. Extension beyond two years may bepossible. Applications will be considered until the position is filled. Candidates may contact Dr. Markus Ploner for more detailed information or directly e-mail their application (ploner at lrz.tum.de). PD Dr. Markus Ploner Department of Neurology Technische Universität München Munich, Germany ploner at lrz.tum.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Thu Feb 14 14:59:03 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Thu, 14 Feb 2013 14:59:03 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? In-Reply-To: References: Message-ID: <511CEDA7.5020000@donders.ru.nl> Hi Marek, it should work like this: /cfg = []; cfg.layout = 'XXX.lay'; cfg.xlim = [18 22]; cfg.zlim = 'maxabs'; figure; ft_topoplotER(cfg, fft1);/ Note that /cfg.xlim /needs to be a vector with two elements. Best, Jörn On 2/14/2013 2:14 PM, marek wrote: > Dear all, > > Is it possible to use ft_topoplotER to draw selected frequency peaks > over scalp after FFT analysis? > > I did frequency analysis of EEG signal in the range 3-42 Hz with the > following settings: > cfg = []; > cfg.output = 'pow'; > cfg.channel = 'all'; > cfg.method = 'mtmfft'; > cfg.taper = 'hanning'; > cfg.trials = 'all'; > cfg.keeptrials = 'no'; > cfg.foilim = [3 42]; > fft1 = ft_freqanalysis(cfg, avg1); > > I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. > (I've got _only_ frequency domain data). > > Is it possible to do it with with the ft_topoplotER function? What > settings are needed? > I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem > to be related to the parameter (the frequency selection) I try to > manipulate. > > Any help will be greatly appreciated! > > Best, > Marek > > Psychophysiology Laboratory, > Jagiellonian University, Krakow (PL) > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From cornabel at googlemail.com Thu Feb 14 15:42:14 2013 From: cornabel at googlemail.com (cornelius abel) Date: Thu, 14 Feb 2013 15:42:14 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? In-Reply-To: <511CEDA7.5020000@donders.ru.nl> References: <511CEDA7.5020000@donders.ru.nl> Message-ID: <511CF7C6.8000605@googlemail.com> If it is not working you might also need to define the parameter as: cfg.parameter='powspctrm' Greetings, Cornelius Am 14.02.2013 14:59, schrieb "Jörn M. Horschig": > Hi Marek, > > it should work like this: > > /cfg = []; > cfg.layout = 'XXX.lay'; > cfg.xlim = [18 22]; > cfg.zlim = 'maxabs'; > figure; > ft_topoplotER(cfg, fft1); / > > Note that /cfg.xlim /needs to be a vector with two elements. > > Best, > Jörn > > > On 2/14/2013 2:14 PM, marek wrote: >> Dear all, >> >> Is it possible to use ft_topoplotER to draw selected frequency peaks >> over scalp after FFT analysis? >> >> I did frequency analysis of EEG signal in the range 3-42 Hz with the >> following settings: >> cfg = []; >> cfg.output = 'pow'; >> cfg.channel = 'all'; >> cfg.method = 'mtmfft'; >> cfg.taper = 'hanning'; >> cfg.trials = 'all'; >> cfg.keeptrials = 'no'; >> cfg.foilim = [3 42]; >> fft1 = ft_freqanalysis(cfg, avg1); >> >> I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. >> (I've got _only_ frequency domain data). >> >> Is it possible to do it with with the ft_topoplotER function? What >> settings are needed? >> I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem >> to be related to the parameter (the frequency selection) I try to >> manipulate. >> >> Any help will be greatly appreciated! >> >> Best, >> Marek >> >> Psychophysiology Laboratory, >> Jagiellonian University, Krakow (PL) >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > -- > Jörn M. Horschig > PhD Student > Donders Institute for Brain, Cognition and Behaviour > Centre for Cognitive Neuroimaging > Radboud University Nijmegen > Neuronal Oscillations Group > FieldTrip Development Team > > P.O. Box 9101 > NL-6500 HB Nijmegen > The Netherlands > > Contact: > E-Mail:jm.horschig at donders.ru.nl > Tel: +31-(0)24-36-68493 > Web:http://www.ru.nl/donders > > Visiting address: > Trigon, room 2.30 > Kapittelweg 29 > NL-6525 EN Nijmegen > The Netherlands > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From ricardoojm at gmail.com Thu Feb 14 16:12:54 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Thu, 14 Feb 2013 16:12:54 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution Message-ID: Dear all, I am very new to fieldtrip and I am experiencing a problem when reading brainvision data. I searched in the mailinglist archives but I didn't find anything that could help me. In case there is information about it somewhere else, I would appreciate if someone can send me a reference. The problem is the following. I am tring to read continuous data from the brainvision analyzer (already preprocessed), but I always have an error which seems to be due to a problem with the identification of the channels resolution. I exported the data from brainvision in ".dat" vectorized format, and I am loading it first with the ft_preprocessing command. Here is the command I am running to load it: cfg = []; cfg.dataset = 'Raw Data Inspection.dat'; eegData = ft_preprocessing(cfg) Then the following warning message is returned, for each of the 56 channels I have in the data: Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > In fileio\private\read_brainvision_vhdr at 50 In ft_read_header at 381 In ft_preprocessing at 394 And at the end, I have the following error: ??? Index exceeds matrix dimensions. Error in ==> read_brainvision_eeg at 150 dat(chan,:) = tmp(begsample:endsample); Error in ==> ft_read_data at 400 dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, chanindx); Error in ==> ft_preprocessing at 573 dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', rawindx, 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', cfg.dataformat) Interestingly, when I read the header file with the "hdr = ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 samples in the data. When checking the header file with the notepad, it says that there are actualy 797740 data points. So, am I realling doing it right? Thank you very much in advance, and best wishes, Ricardo -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at gmail.com Thu Feb 14 17:32:38 2013 From: cmuehl at gmail.com (Christian Muehl) Date: Thu, 14 Feb 2013 17:32:38 +0100 Subject: [FieldTrip] Call for Papers: 3rd Workshop on Affective Brain-Computer Interfaces at ACII 2013 Message-ID: ** Call for Papers ** 3rd Workshop on Affective Brain-Computer Interfaces (aBCI) Workshop at ACII 2013 (September 2-5), Geneva, Switzerland, September 2, 2013 http://hmi.ewi.utwente.nl/abci2013 http://www.acii2013.org During the last decade, brain computer interface (BCI) research has developed into a major research field establishing methodological frameworks, guidelines and a core community of established researchers. Besides proving valuable as a communication channel that bypasses impeded muscular pathways, the novel technology also spurred the investigation of applications for able-bodied users, foremost in the fields of entertainment, health and lifestyle. Affective BCI systems allowing users to control computer games, support relaxation training, or trigger your alarm clock during a shallow sleep stage have been proposed, implemented, and sold. Moreover, the affordable hardware and software tools also encouraged artists to play with the idea of a direct access to people’s most private information: their affective and cognitive states. From these explorations followed a number of interesting installations, suggesting novel ways of human-computer as well as human-human interaction: neurotechnology-based systems that encourage affective self-reflection, the synchronization and empathizing between or the competition of different minds, and the collaborative creation and manipulation of digital multimodal content. The third workshop on affective brain-computer interfaces will explore the advantages and limitations of using neuro-physiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in applications for domains like health, arts, and entertainment. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress and their visions, and thus to spur the development of guidelines and frameworks for affective BCI. Topics of interest include, but are not limited to: • emotion elicitation and data collection for affective BCI • detection of affect and mental state via BCI and other modalities • innovative concepts for adaptive interfaces and affective BCI • demos of aBCI systems and artworks Submission Instructions: * The papers should feature original empirical work, theoretical work, or a well defendable but arguable position of the authors. * Papers will be published in the proceedings of ACII 2013 by IEEE. Papers should be limited to 6 pages. * Further details about the submission instructions and format can be found on the website of ACII 2013. * For further information, contact abci at cs.utwente.nl Important Dates: April 20, 2013: Submission of manuscripts May 20, 2013: Acceptance/Rejection notification June 17, 2013: Submission of camera-ready papers and presenting author’s registration September 2, 2013: Date of the Workshop Programme Chairs: * Brendan Allison, University of California, San Diego, USA * Guilliaume Chanel, Swiss Center for Affective Sciences, Geneva, Switzerland, * Christian Mühl, INRIA Bordeaux - Sud-Ouest, France * Anton Nijholt, Universiteit Twente, the Netherlands Programme Committee: * Egon L. van den Broek, TNO Technical Sciences, Delft, the Netherlands * Anne-Marie Brouwer, TNO Perceptual and Cognitive Systems, Soesterberg, the Netherlands * Stephen Fairclough, John Moores University, Liverpool, UK * Didier Grandjean, Swiss Center for Affective Sciences, Geneva, Switzerland * Hayrettin Gürkök, University of Twente, Enschede, the Netherlands * Jonghwa Kim, University of Augsburg, Germany * Brent Lance, Army Research Laboratory/TNB, Aberdeen Proving Ground, USA, * Fabien Lotte, INRIA Bordeaux - Sud-Ouest, France * Winfried Menninghaus, Freie Universität Berlin, Germany * Gary Garcia Molina, Philips Research North America, Briarcliff, USA * Christopher Honey, Princeton University, USA * Olga Sourina, NanYang Technological University, Singapore * Ioannis Patras, Queen Mary University, London, UK * Mannes Poel, University of Twente, Enschede, the Netherlands * Ed Tan, Universiteit van Amsterdam, the Netherlands * Thorsten Zander, Technische Universität Berlin, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: From Alan.Leggitt at ucsf.edu Fri Feb 15 01:58:32 2013 From: Alan.Leggitt at ucsf.edu (Leggitt, Alan) Date: Fri, 15 Feb 2013 00:58:32 +0000 Subject: [FieldTrip] Support Vector Machine (SVM) for classification of EEG data Message-ID: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> Hello, I'm new to field trip and I am interested in using a support vector machine to classify EEG data. I see that field trip has svm code through the DLMT toolbox. Has anyone had any experience with this and would be willing to share their code for adapting EEG data to use as inputs to the svm class? My current understanding is that others use ICA to extract features to use in the svm. Are there other techniques for feature extraction? Thanks very much. Regards, Alan -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Fri Feb 15 08:04:38 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 15 Feb 2013 08:04:38 +0100 Subject: [FieldTrip] Support Vector Machine (SVM) for classification of EEG data In-Reply-To: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> References: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> Message-ID: <511DDE06.70101@donders.ru.nl> Dear Alan, you should probably start off with going through our tutorials: http://fieldtrip.fcdonders.nl/tutorial/ And for you especially http://fieldtrip.fcdonders.nl/tutorial/multivariateanalysis There are lots of different approaches for feature extraction or reduce feature space, but what works wors best for your data is something you have to test yourself. When you've read the tutorials you probably got a pretty got overview of what is possible in FieldTrip and that you can easily test what you asked for yourself without having others send you their code (you just have to replace a few keywords from the tutorial to test a different method). If you have more specific questions, feel free to ask again. Best, Jörn On 2/15/2013 1:58 AM, Leggitt, Alan wrote: > Hello, > > I'm new to field trip and I am interested in using a support vector > machine to classify EEG data. I see that field trip has svm code > through the DLMT toolbox. Has anyone had any experience with this and > would be willing to share their code for adapting EEG data to use as > inputs to the svm class? My current understanding is that others use > ICA to extract features to use in the svm. Are there other techniques > for feature extraction? > > Thanks very much. > > Regards, > Alan > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 15 08:50:46 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Fri, 15 Feb 2013 08:50:46 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: <94F3F43D-320E-4E49-9BE2-97B7859C1241@donders.ru.nl> Hi Ricardo, It looks as if there's a discrepancy between what FieldTrip extracts from the header, and what is actually in the data file. Did you try another data file to see whether your problem occurs just in this single example or not? I read brainvision data all the time, and haven't encountered issues so far. If your data file is sufficiently small, you could try to .zip it (both data/header/marker files) and upload it to our bugzilla.fcdonders.nl website. You have to create an account, and then you can 'file a bug', describing the problem (basically just copy and paste what you wrote in your original e-mail), and upload the data. Our team than can have a look at it. Best wishes, Jan-Mathijs On Feb 14, 2013, at 4:12 PM, Ricardo Moura wrote: > Dear all, > > I am very new to fieldtrip and I am experiencing a problem when reading brainvision data. I searched in the mailinglist archives but I didn't find anything that could help me. In case there is information about it somewhere else, I would appreciate if someone can send me a reference. > > The problem is the following. I am tring to read continuous data from the brainvision analyzer (already preprocessed), but I always have an error which seems to be due to a problem with the identification of the channels resolution. I exported the data from brainvision in ".dat" vectorized format, and I am loading it first with the ft_preprocessing command. > > Here is the command I am running to load it: > cfg = []; > cfg.dataset = 'Raw Data Inspection.dat'; > eegData = ft_preprocessing(cfg) > > > Then the following warning message is returned, for each of the 56 channels I have in the data: > Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > > In fileio\private\read_brainvision_vhdr at 50 > In ft_read_header at 381 > In ft_preprocessing at 394 > > > And at the end, I have the following error: > ??? Index exceeds matrix dimensions. > > Error in ==> read_brainvision_eeg at 150 > dat(chan,:) = tmp(begsample:endsample); > > Error in ==> ft_read_data at 400 > dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, chanindx); > > Error in ==> ft_preprocessing at 573 > dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', rawindx, > 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', cfg.dataformat) > > > Interestingly, when I read the header file with the "hdr = ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 samples in the data. When checking the header file with the notepad, it says that there are actualy 797740 data points. > > So, am I realling doing it right? > Thank you very much in advance, and best wishes, > Ricardo > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ricardoojm at gmail.com Fri Feb 15 11:52:32 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Fri, 15 Feb 2013 11:52:32 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: Hi Jan-Mathijs, Thank you very much for your reply. I found a mistake of mine in the data export. I didn't export it as ".dat" binary file. I was exporting it as text file. Now, the same script I sent in the first email is working in the sense that the program is properly recognizing the samples in the data (the 797740 sampling points, instead of only 80). Nevertheless, I still have a problem with the channel's resolution. I saw that when exporting the binary files as ieee 32-bit floating, the resolution of the channels is not recorded in the header. So I changed it to the "32-bit signed integer" format, and now I have the resolution (in the header, it appears as "Ch1=AF3,NewRef,4.1322874E-08,µV", under "Channel Infos"), but then, another error message is returned: ??? Error using ==> read_brainvision_eeg at 155 unsupported sub-fileformat I tried to export the data in different ways, but the error persists. I am afraid there is something else wrong in the way I am exporting the data. Could you tell me how I must export the data, or just show me where I can find more detailed specifications about it? I searched through the site and mailing list, and haven't find further information about it. Thanks again, Best wishes, Ricardo On 14 February 2013 16:12, Ricardo Moura wrote: > Dear all, > > I am very new to fieldtrip and I am experiencing a problem when reading > brainvision data. I searched in the mailinglist archives but I didn't find > anything that could help me. In case there is information about it > somewhere else, I would appreciate if someone can send me a reference. > > The problem is the following. I am tring to read continuous data from the > brainvision analyzer (already preprocessed), but I always have an error > which seems to be due to a problem with the identification of the channels > resolution. I exported the data from brainvision in ".dat" vectorized > format, and I am loading it first with the ft_preprocessing command. > > Here is the command I am running to load it: > cfg = []; > cfg.dataset = 'Raw Data Inspection.dat'; > eegData = ft_preprocessing(cfg) > > > Then the following warning message is returned, for each of the 56 > channels I have in the data: > Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > > In fileio\private\read_brainvision_vhdr at 50 > In ft_read_header at 381 > In ft_preprocessing at 394 > > > And at the end, I have the following error: > ??? Index exceeds matrix dimensions. > > Error in ==> read_brainvision_eeg at 150 > dat(chan,:) = tmp(begsample:endsample); > > Error in ==> ft_read_data at 400 > dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, > chanindx); > > Error in ==> ft_preprocessing at 573 > dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', > begsample, 'endsample', endsample, 'chanindx', rawindx, > 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', > cfg.dataformat) > > > Interestingly, when I read the header file with the "hdr = > ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 > samples in the data. When checking the header file with the notepad, it > says that there are actualy 797740 data points. > > So, am I realling doing it right? > Thank you very much in advance, and best wishes, > Ricardo > -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Fri Feb 15 15:51:52 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 15 Feb 2013 14:51:52 +0000 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: Hello, I'm very sorry to repost this, but I'm hoping that someone might be able to give me advice. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI that looks fine. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 15 16:16:52 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Fri, 15 Feb 2013 16:16:52 +0100 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: <13AAF5AE-0977-4C63-B6F8-AE5ED6E6FA7A@donders.ru.nl> Hi Allison, The warning you get is inconsequential and will be fixed soon. Regarding the scale of the data objects, you can use ft_convert_units to get them all in the same scale: hdr.grad = ft_convert_units(hdr.grad); % tries to add a unit field if it does not exist vol = ft_convert_units(vol, hdr.grad.unit); Then you can proceed with the plotting. Best Jan_Mathijs On Feb 15, 2013, at 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: > Hello, I’m very sorry to repost this, but I’m hoping that someone might be able to give me advice. > > I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I’ve scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. > > I’ve imported the MRI like so: > > mri=ft_read_mri(‘ABC_ortho_anat.nii’); > mri=ft_determine_coordsys(mri) > > I re-label the coordinate axes, and set the origin – when it’s done, it has “Neuromag” as the coordsys, although that’s not how it was created. Next: > > cfg=[]; cfg.method=’interactive’ > mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points > cfg=[]; > [segmentedmri]=ft_volumesegment(cfg, mri_realigned) > > During execution I get this warning: > Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img > Even though the file appears to exist – and the program completes and produces a segmented MRI that looks fine. Finally: > > hdr=ft_read_header(‘ACN.ds’); > cfg=[]; cfg.method=’singleshell’; > vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); > figure > ft_plot_vol(vol_realistic);hold on > ft_plot_sens(hdr.grad) > > The plot has the sensor array and the headmodel on different scales – like it didn’t properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I’d ultimately also like to be able to use the localspheres model, and compare results, but since I can’t figure out how to plot that headmodel to check it, I thought I’d start with one that I can plot. > > Thank you! > > Allison Nugent, PhD > MRI Physicist > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph. 301-451-8863 > nugenta at mail.nih.gov > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Fri Feb 15 17:55:51 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 15 Feb 2013 17:55:51 +0100 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: <511E6897.1060101@donders.ru.nl> Dear Allison, I was encountering similar issues the last two days and hope to have fixed some unit conversion bugs. Thus it might be that with the newest FT version, you don't need to manually convert the units anymore as JM suggested. Could you give it a try for me and see whether it works without JMs manual approach in the newest FT version? Best, Jörn On 2/15/2013 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: > > Hello, I'm very sorry to repost this, but I'm hoping that someone > might be able to give me advice. > > I have an MRI in nifti format. It has already been re-aligned with > the fiducial markers. I've scoured the tutorials, but most seem to > deal with MRIs that are already in the ctf coordinate system. > > I've imported the MRI like so: > > mri=ft_read_mri('ABC_ortho_anat.nii'); > > mri=ft_determine_coordsys(mri) > > I re-label the coordinate axes, and set the origin -- when it's done, > it has "Neuromag" as the coordsys, although that's not how it was > created. Next: > > cfg=[]; cfg.method='interactive' > > mri_realigned=ft_volumerealign(cfg,mri) % > to set the fiducial points > > cfg=[]; > > [segmentedmri]=ft_volumesegment(cfg, mri_realigned) > > During execution I get this warning: > > Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img > > Even though the file appears to exist -- and the program completes and > produces a segmented MRIthat looks fine. Finally: > > hdr=ft_read_header('ACN.ds'); > > cfg=[]; cfg.method='singleshell'; > > vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); > > figure > > ft_plot_vol(vol_realistic);hold on > > ft_plot_sens(hdr.grad) > > The plot has the sensor array and the headmodel on different scales -- > like it didn't properly adjust for the difference in mm and cm, even > though the units are specified in the data structures. I'd > ultimately also like to be able to use the localspheres model, and > compare results, but since I can't figure out how to plot that > headmodel to check it, I thought I'd start with one that I can plot. > > Thank you! > > Allison Nugent, PhD > > MRI Physicist > > Experimental Therapeutics and Pathophysiology Branch > > NIMH/NIH/DHHS > > Ph. 301-451-8863 > > nugenta at mail.nih.gov > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From markus.siegel at uni-tuebingen.de Fri Feb 15 18:17:04 2013 From: markus.siegel at uni-tuebingen.de (Markus Siegel) Date: Fri, 15 Feb 2013 18:17:04 +0100 Subject: [FieldTrip] PhD Position - Centre for Integrative Neuroscience (CIN), Tuebingen, Germany Message-ID: <7E2BFDC3-6406-4067-8E66-915714698B52@uni-tuebingen.de> PhD Position - Centre for Integrative Neuroscience (CIN), Tuebingen The laboratory of Markus Siegel at the Centre for Integrative Neuroscience (CIN), Tuebingen (http://www.cin.uni-tuebingen.de/research/siegel.php) is seeking candidates for a PhD position to study large-scale neuronal interactions in humans. The project will focus on ongoing and task-related neuronal oscillations and interactions in the healthy and diseased human brain. Experimental methods include, MEG, psychophysics, spectral analysis, source-reconstruction techniques, and novel connectivity analyses. The candidate will join a stimulating interdisciplinary team that employs a broad spectrum of neurophysiological techniques in animals and humans. The ideal candidate is highly motivated with a strong interest in interdisciplinary research. Candidates must have an MA (or equivalent) in neuroscience, physics, mathematics, psychology, or related fields. Fluency in Matlab is required. Experience in electrophysiology, spectral analysis and/or M/EEG is highly valued. Applications should include a detailed CV, statement of research interests, and names of at least two referees. The position is available for three years. Applications will be considered until the position is filled. Please send applications or informal inquiries to Markus Siegel (markus.siegel at uni-tuebingen.de). -- Dr. Markus Siegel Principal Investigator, Centre for Integrative Neuroscience (CIN), Tübingen From nugenta at mail.nih.gov Fri Feb 15 18:34:44 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 15 Feb 2013 17:34:44 +0000 Subject: [FieldTrip] headmodels In-Reply-To: <511E6897.1060101@donders.ru.nl> References: <511E6897.1060101@donders.ru.nl> Message-ID: It certainly works with the unit conversions in the version I'm currently using, which is from 2/5/2013 - - thanks so much!! As soon as I have a chance, I'll download the latest version to test. Thanks again! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov From: "Jörn M. Horschig" [mailto:jm.horschig at donders.ru.nl] Sent: Friday, February 15, 2013 11:56 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] headmodels Dear Allison, I was encountering similar issues the last two days and hope to have fixed some unit conversion bugs. Thus it might be that with the newest FT version, you don't need to manually convert the units anymore as JM suggested. Could you give it a try for me and see whether it works without JMs manual approach in the newest FT version? Best, Jörn On 2/15/2013 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: Hello, I'm very sorry to repost this, but I'm hoping that someone might be able to give me advice. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI that looks fine. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From ricardoojm at gmail.com Sun Feb 17 19:23:05 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Sun, 17 Feb 2013 19:23:05 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: Hi, I solved this problem already. But as I have seen, the marks for the bad intervals that were defined in the brainvision analyzer are not automatically imported. Is it really right? And how could I use these already defined bad intervals, instead of doing the whole artifact correction again (is there a function in fieldtrip that does it, or do I have to write one myself)? Thank you very much once again, Best regards Ricardo On 15 February 2013 11:52, Ricardo Moura wrote: > Hi Jan-Mathijs, > Thank you very much for your reply. > > I found a mistake of mine in the data export. I didn't export it as ".dat" > binary file. I was exporting it as text file. Now, the same script I sent > in the first email is working in the sense that the program is properly > recognizing the samples in the data (the 797740 sampling points, instead of > only 80). Nevertheless, I still have a problem with the channel's > resolution. > > I saw that when exporting the binary files as ieee 32-bit floating, the > resolution of the channels is not recorded in the header. So I changed it > to the "32-bit signed integer" format, and now I have the resolution (in > the header, it appears as "Ch1=AF3,NewRef,4.1322874E-08,µV", under "Channel > Infos"), but then, another error message is returned: > > ??? Error using ==> read_brainvision_eeg at 155 > unsupported sub-fileformat > > I tried to export the data in different ways, but the error persists. > > I am afraid there is something else wrong in the way I am exporting the > data. Could you tell me how I must export the data, or just show me where I > can find more detailed specifications about it? I searched through the site > and mailing list, and haven't find further information about it. > > Thanks again, > Best wishes, > Ricardo > > > > > > On 14 February 2013 16:12, Ricardo Moura wrote: > >> Dear all, >> >> I am very new to fieldtrip and I am experiencing a problem when reading >> brainvision data. I searched in the mailinglist archives but I didn't find >> anything that could help me. In case there is information about it >> somewhere else, I would appreciate if someone can send me a reference. >> >> The problem is the following. I am tring to read continuous data from the >> brainvision analyzer (already preprocessed), but I always have an error >> which seems to be due to a problem with the identification of the channels >> resolution. I exported the data from brainvision in ".dat" vectorized >> format, and I am loading it first with the ft_preprocessing command. >> >> Here is the command I am running to load it: >> cfg = []; >> cfg.dataset = 'Raw Data Inspection.dat'; >> eegData = ft_preprocessing(cfg) >> >> >> Then the following warning message is returned, for each of the 56 >> channels I have in the data: >> Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! >> > In fileio\private\read_brainvision_vhdr at 50 >> In ft_read_header at 381 >> In ft_preprocessing at 394 >> >> >> And at the end, I have the following error: >> ??? Index exceeds matrix dimensions. >> >> Error in ==> read_brainvision_eeg at 150 >> dat(chan,:) = tmp(begsample:endsample); >> >> Error in ==> ft_read_data at 400 >> dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, >> chanindx); >> >> Error in ==> ft_preprocessing at 573 >> dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', >> begsample, 'endsample', endsample, 'chanindx', rawindx, >> 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', >> cfg.dataformat) >> >> >> Interestingly, when I read the header file with the "hdr = >> ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 >> samples in the data. When checking the header file with the notepad, it >> says that there are actualy 797740 data points. >> >> So, am I realling doing it right? >> Thank you very much in advance, and best wishes, >> Ricardo >> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stidimitriadis at gmail.com Tue Feb 19 10:33:53 2013 From: stidimitriadis at gmail.com (Stavros Dimitriadis) Date: Tue, 19 Feb 2013 11:33:53 +0200 Subject: [FieldTrip] from axial to planar gradiometers Message-ID: Hello to everybody ! I am facing a problem with the transformation of data from axial to planar gradiometers ! I manipulate data recorded from 248- channel BTi (4D Neuroimaging) axial gradiometer system ! I am using cfg.planarmethod='sincos'; The basic problem is the output of ft_megplanar where labels sections have 2x248 labels (vertical & horizontal) but only 248 channels in avg section of the struct. I cannot understand the problem! Can anyone have any idea ? Best regards Dimitriadis Stavros users.auth.gr/~stdimitr/index.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From sammler at cbs.mpg.de Tue Feb 19 13:33:55 2013 From: sammler at cbs.mpg.de (Daniela Sammler) Date: Tue, 19 Feb 2013 13:33:55 +0100 (CET) Subject: [FieldTrip] PhD position on "Intonation in speech" at MPI-CBS in Leipzig, Germany In-Reply-To: <291809232.3656.1361277182103.JavaMail.root@zimbra> Message-ID: <1757739675.3682.1361277235866.JavaMail.root@zimbra> The Max Planck Institute for Human Cognitive and Brain Sciences (MPI-CBS) in Leipzig and its newly established Otto Hahn Group on the "Neural Bases of Intonation in Speech", led by Daniela Sammler, are now offering a PhD position for 3 years in a research project on social aspects of prosody perception in speech using fMRI, MEG and/or TMS. There is much more to human communication than the (de)coding of the explicit, propositional meaning of a vocal speech signal. Between the lines, the vocal output reveals a lot about the speakers’ believes, attitudes (e.g., sympathy, dominance), and communicative intentions (e.g., to warn, to request, to command, to tease). Much of such implicit, illocutionary meaning is conveyed by the “manner of saying”, i.e. the speech prosody, and the interpretation of those subtleties involves a lot of pragmatic inference. There is growing evidence that this latter faculty is distinct from our language abilities such as phonology, syntax and semantics, making it reasonable to assume the involvement of brain areas beyond the well-known fronto-temporal language network in human vocal communication. The goal of the PhD project is to investigate the neural bases of decoding communicative intentions conveyed by prosody (i.e. HOW something is said) in contrast to and in interaction with the decoding of propositional meaning (i.e. WHAT is said). Applicants must have a master degree (or equivalent) in psychology, cognitive sciences, neuroscience, medicine, linguistics, or a related field. Proficiency in oral and written English is necessary. A solid methods background (statistics and programming) as well as prior experience with either fMRI or EEG/MEG are highly desirable. Most importantly, the successful applicant will share our enthusiasm in research questions on prosody and the social brain in vocal communication. Preferable starting date is July 2013. Salary is dependent on experience and based on MPI stipends or equivalent salary according to German Public service regulations. The research will be conducted at the MPI-CBS in Leipzig, Germany, an internationally leading center for cognitive and imaging neuroscience equipped with a 7T MRI scanner, three 3T MRI scanners, a 306 channels MEG system, a TMS system and several EEG suites. All facilities are supported by experienced IT and physicist staff. Our institute (just 190 km or 70 minutes by train, south of Berlin) offers a very international environment, with English and German being the languages spoken in the laboratory. It offers a friendly and generous environment of researchers with diverse backgrounds and with an excellent infrastructure. In order to increase the proportion of female staff members, applications from female scientists are particularly encouraged. Preference will be given to disabled persons with the same qualification. Applications should be sent to the email below as a single, appropriately named pdf email attachment. It should enclose a cover letter (max. 2 pages) that also specifies your future research interests; a CV; up to three representative reprints; and contact details of two personal references. This call remains open until the position is filled. The application should be kindly sent to personal at cbs.mpg.de using the code "PhD 3/13" in the subject. For further details please contact Dr Daniela Sammler, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, sammler at cbs.mpg.de -- Daniela SAMMLER, Ph.D. Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1a 04103 Leipzig phone: +49 341 9940 2679 fax: +49 341 9940 2260 From r.oostenveld at donders.ru.nl Tue Feb 19 14:30:47 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Tue, 19 Feb 2013 14:30:47 +0100 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 References: <002201ce0e9a$e18ab740$a4a025c0$@stijns@fcdonders.ru.nl> Message-ID: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> NIHC-BrainGain Tutorial Day: Tools and novelties in neurotechnology research We invite PhD students, post-docs and senior researchers working in the fields of brain-computer interfacing (BCI), neurofeedback, cognitive neuroscience, neuroinformatics, neurosurgery and related topics to our Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen. The day marks the end of the BrainGain consortium, a six-year joint-effort project on Brain-Computer Interfacing and related technologies. More information on BrainGain can be found here. The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. The 'tools' track is intended to provide both newcomers to the field and experienced researchers with an overview of the tools needed to integrate cognitive neuroscience and advanced invasive and non-invasive technology. Topics range from data streaming to modelling and statistics, and from online fMRI decoding to a crash course in neuroethics., You will also receive some helpful insights for a future career, in case you are interested in applying for a grant in the near future or considering setting up your own company. The 'novelties' track covers a wide range of topics indicating some of the possible topics to be further explored in BCI and neurotechnology research, including genetics, robotics and intracranial recordings. There is no need to stick to one of the two tracks the whole day: you are free to switch between tracks any time. In parallel to the lectures, there will be several interesting demonstrations. The full programme and registration form can be found on the NIHC website (https://www.hersenenencognitie.nl). Please register before 1 March 2013. Participation is free. Lunch and drinks will be provided. We hope to welcome you on March 21st in Nijmegen! Susanna Bicknell Radboud University Nijmegen ____________________________________________________________________ Faculty of Science | Finance and Economic Affairs | Project Management | LC-IMPACT Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | Project Manager T +31 24 3653300 | HG00.616 (Monday, Thursday) Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, Wednesday) Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands Visiting and courier service address: Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From mcgoiv0 at wfu.edu Tue Feb 19 18:47:39 2013 From: mcgoiv0 at wfu.edu (McGowin, Inna) Date: Tue, 19 Feb 2013 12:47:39 -0500 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 In-Reply-To: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> References: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> Message-ID: Hello Susanna, Thanks for the information. Is the tutorial day a local event or it can be accessed through a webinar? Thanks, Inna On Tue, Feb 19, 2013 at 8:30 AM, Robert Oostenveld < r.oostenveld at donders.ru.nl> wrote: > > *NIHC-BrainGain Tutorial Day:* > *Tools and novelties in neurotechnology research * > ** ** > We invite PhD students, post-docs and senior researchers working in the > fields of brain-computer interfacing (BCI), neurofeedback, cognitive > neuroscience, neuroinformatics, neurosurgery and related topics to our > Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen.**** > The day marks the end of the BrainGain consortium, a six-year joint-effort > project on Brain-Computer Interfacing and related technologies. More > information on BrainGain can be found here .**** > ** ** > The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. > The 'tools' track is intended to provide both newcomers to the field and > experienced researchers with an overview of the tools needed to integrate > cognitive neuroscience and advanced invasive and non-invasive technology. > Topics range from data streaming to modelling and statistics, and from > online fMRI decoding to a crash course in neuroethics., You will also > receive some helpful insights for a future career, in case you are > interested in applying for a grant in the near future or considering > setting up your own company.**** > The 'novelties' track covers a wide range of topics indicating some of the > possible topics to be further explored in BCI and neurotechnology research, > including genetics, robotics and intracranial recordings. **** > There is no need to stick to one of the two tracks the whole day: you are > free to switch between tracks any time.**** > ** ** > In parallel to the lectures, there will be several interesting > demonstrations. **** > ** ** > The full programme and registration form can be found on the NIHC website > (https://www.hersenenencognitie.nl)*. *Please register before 1 March > 2013. Participation is free. Lunch and drinks will be provided. **** > ** ** > We hope to welcome you on March 21st in Nijmegen!**** > ** ** > Susanna Bicknell**** > Radboud University Nijmegen**** > ____________________________________________________________________**** > Faculty of Science | Finance and Economic Affairs | Project Management | > LC-IMPACT**** > Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | > Project Manager**** > T +31 24 3653300 | HG00.616 (Monday, Thursday)**** > Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, > Wednesday)**** > Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands**** > Visiting and courier service address: Heyendaalseweg 135, 6525 AJ > Nijmegen, The Netherlands > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -- Inna McGowin -------------- next part -------------- An HTML attachment was scrubbed... URL: From inieuwenhuis at berkeley.edu Wed Feb 20 00:59:13 2013 From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis) Date: Tue, 19 Feb 2013 15:59:13 -0800 Subject: [FieldTrip] cluster analysis correlation Message-ID: <512411D1.6040901@berkeley.edu> Hi all, I've computer correlations (kendall's tau) between EEG power and a behavioral measure over participants (made my own statfun using corr). Now I'd like to use the cluster randomization framework to correct for multiple comparisons. I think it would be valid to shuffle the assignment of EEG power to behavioral measure (which is specified in cfg.design for correlation), make a distribution and test my correlations against that. So shuffle the data so that say EEG power of subect1 get's linked to behavioral measure of subject3, subject2 to subject6 etc, etc, just as we do with t-values shuffling who belongs to which condition. Questions: 1) is this implemented in FieldTrip? How would I do this? Cause the design needs to be shuffled now, this is different from how it would work for a t-test no? 2) If 1== false, Anyone done this, got some tips? 3) Is the above approach I suggest statistically valid? I think testing the tau against zero is not valid (seeing if it is significantly different from zero by making some dummy stat with zeros), but what I suggest is, anyone any thoughts? Thanks!! Ingrid -- Ingrid Nieuwenhuis PhD Postdoctoral Fellow Sleep and Neuroimaging Laboratory Department of Psychology University of California, Berkeley California 94720-1650 Tolman Hall, room 5305 From simonjameslittle at gmail.com Thu Feb 21 14:17:17 2013 From: simonjameslittle at gmail.com (Simon Little) Date: Thu, 21 Feb 2013 13:17:17 +0000 Subject: [FieldTrip] LAYOUT PAIN! Message-ID: Hi, I would be really very grateful for some help regarding setting layout for EEG. Im analysing (or trying to!) some clinical EEG 10-20 data on epilepsy patients and am struggling to get the layout working using the standardised layout files. My channel names concur with those of standard EEG 10 -20 systems (see below) (http://en.wikipedia.org/wiki/10-20_system_(EEG)) Number of questions - 1. The EEG 10-20 standard layout does not seem to match what I thought of (and have checked online) as the standard 10-20 format. Specifically - it includes channels Fpz and Oz for example which aren't on the standard layoutand excludes T3 T4 T5 T6 ( http://en.wikipedia.org/wiki/10-20_system_(EEG)) 2. When I check what my layout should be - >> [type]=ft_senstype(datast_A.label) type = ext1020 Yep there is no layout file for ext1020 in the standard layout templates that seem to come with fieldtrip to use with ft_prepare_layout. Given that all the channels are I need are in the EEG1010 file, I hoped that I could use that instead but then I end up with a layout has 80 odd channels when I only need 21. I'd be so grateful for any help with this! I'm very sorry if its something very simple but I have been looking at it for many many hours without any luck! Many thanks Simon Little My channel names - 'Fp1' 'Fp2' 'F3' 'F4' 'C3' 'C4' 'P3' 'P4' 'O1' 'O2' 'F7' 'F8' 'T3' 'T4' 'T5' 'T6' 'A1' 'A2' 'Fz' 'Cz' 'Pz' EEG1020 - channel names from lay file. 1 -0.485328 1.493835 0.393101 0.294826 Fp1 2 0.000000 1.570696 0.393101 0.294826 Fpz 3 0.485501 1.493884 0.393101 0.294826 Fp2 4 -1.270781 0.923319 0.393101 0.294826 F7 5 -0.652084 0.812357 0.393101 0.294826 F3 6 0.000000 0.785398 0.393101 0.294826 Fz 7 0.652084 0.812357 0.393101 0.294826 F4 8 1.270781 0.923319 0.393101 0.294826 F8 9 -1.570796 0.000000 0.393101 0.294826 T7 10 -0.785398 0.000111 0.393101 0.294826 C3 11 0.000000 0.000200 0.393101 0.294826 Cz 12 0.785398 0.000111 0.393101 0.294826 C4 13 1.570796 -0.000000 0.393101 0.294826 T8 14 -1.270862 -0.923378 0.393101 0.294826 P7 15 -0.652231 -0.811998 0.393101 0.294826 P3 16 -0.000000 -0.785257 0.393101 0.294826 Pz 17 0.652231 -0.811998 0.393101 0.294826 P4 18 1.270862 -0.923378 0.393101 0.294826 P8 19 -0.485359 -1.493930 0.393101 0.294826 O1 20 -0.000000 -1.570796 0.393101 0.294826 Oz 21 0.485359 -1.493930 0.393101 0.294826 O2 22 -1.570796 1.570696 0.393101 0.294826 COMNT 23 1.570796 1.570696 0.393101 0.294826 SCALE -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.herring at fcdonders.ru.nl Thu Feb 21 16:34:31 2013 From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim)) Date: Thu, 21 Feb 2013 16:34:31 +0100 (CET) Subject: [FieldTrip] Notification for users with different channel ordering between participants Message-ID: <004701ce1048$f16daeb0$d4490c10$@herring@fcdonders.ru.nl> Dear Fieldtrip users, It has come to our attention by Philip Ruhnau that when averaging across participants using ft_XXXgrandaverage, due to a bug, no care was taken when the channel-order was different between participants (see http://bugzilla.fcdonders.nl/show_bug.cgi?id=1986). This could occur, for example, when after interpolating channels, the interpolated channels are added to the end of the data and thus changing the channel ordering. Particularly for EEG data this bug could be a problem because often different channels are interpolated for different subjects. No problems should have occurred when merely removing channels. For MEG data, the same problem occurred when using ft_combineplanar after interpolating, for example, vertical or horizontal channels separately. In this instance the wrong channel pairs were combined. However, if channels were interpolated after using ft_combineplanar, or if pairs of horizontal and vertical channels were removed you should have no problems given that the same channels were affected across all participants. The bug has been fixed as of rev. 7519. We strongly advise users that have data containing different channel ordering between participants to download the newest version of Fieldtrip and re-check grand averaged data. Best, Jim -------------- next part -------------- An HTML attachment was scrubbed... URL: From skelly2 at ccny.cuny.edu Mon Feb 25 03:16:15 2013 From: skelly2 at ccny.cuny.edu (Simon Kelly) Date: Sun, 24 Feb 2013 21:16:15 -0500 (EST) Subject: [FieldTrip] Postdoc position in systems/cognitive neuroscience (New York) Message-ID: <201302250216.020279@pelican.admin.ccny.cuny.edu> Applications are invited for a Postdoctoral position in the Neural Systems Lab of Simon Kelly in The City College of New York. The position is funded by the Endeavor Scientists Program of the Child Mind Institute (CMI; http://www.childmind.org/en/endeavor-scientists/) and will be jointly supervised by Simon Kelly (http://bme.ccny.cuny.edu/people/faculty/skelly) and Michael Milham (http://www.childmind.org/en/directory/clinicians/mmilham). The goal of the collaboration is to develop novel paradigms for the study of perception, attention and decision making in humans using EEG and/or fMRI, and to deploy these paradigms in clinical studies of child and adolescent populations in CMI as well as in basic research studies in the Kelly Lab. Any innovative analytic tools and paradigms developed in the course of this position will be made publicly available. Applicants must have a Ph.D. in neuroscience or a related field and have experience and strong interest in cognitive neuroscience. The candidate must have strong analytic skills, be proficient in programming (especially Matlab), and have experience in psychophysics and EEG recording and analysis. Experience with fMRI is a strong plus. The ideal candidate will be reliable, highly motivated and productive, and enjoy working collaboratively. Applicants should send a curriculum vitae, contact information for 2-3 references, and a cover letter with a brief description of past research accomplishments as well as future research interests and career goals to Simon Kelly: skelly2 at ccny.cuny.edu. From paul.sowman at mq.edu.au Mon Feb 25 07:20:55 2013 From: paul.sowman at mq.edu.au (Paul Sowman) Date: Mon, 25 Feb 2013 17:20:55 +1100 Subject: [FieldTrip] FT_CONNECTIVITYANALYIS Message-ID: Hi, which is the appropriate option in FT_CONNECTIVITYANALYIS to implement connectivity analysis via the imaginary part of coherency? The 2011 Computational Intelligence and Neuroscience paper says that the method from the Nolte paper is implemented but I'm not sure which is the right option to do this from the list: coh', coherence, support for freq, freqmvar and source data. For partial coherence also specify cfg.partchannel 'csd', cross-spectral density matrix, can also calculate partial csds - if cfg.partchannel is specified, support for freq and freqmvar data 'plv', phase-locking value, support for freq and freqmvar data 'powcorr', power correlation, support for freq and source data 'amplcorr', amplitude correlation, support for freq and source data 'granger', granger causality, support for freq and freqmvar data 'dtf', directed transfer function, support for freq and freqmvar data 'pdc', partial directed coherence, support for freq and freqmvar data 'psi', phaseslope index, support for freq and freqmvar data 'wpli', weighted phase lag index (signed one, still have to take absolute value to get indication of strength of interaction. Note: measure has positive bias. Use wpli_debiased to avoid this. 'wpli_debiased' debiased weighted phase lag index (estimates squared wpli) 'ppc' pairwise phase consistency 'wppc' weighted pairwise phase consistency G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. -- Paul F Sowman NHMRC Postdoctoral Training Fellow ARC Centre of Excellence for Cognition and its Disorders (CCD) MACQUARIE UNIVERSITY NSW 2109 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Feb 25 09:35:21 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Mon, 25 Feb 2013 09:35:21 +0100 Subject: [FieldTrip] FT_CONNECTIVITYANALYIS In-Reply-To: References: Message-ID: <05D58012-4719-4188-94AF-237EE1D58007@donders.ru.nl> Hi Paul, You should specify cfg.method = 'coh' in conjunction with cfg.complex = 'imag'; I'll update the documentation. Best, Jan-Mathijs On Feb 25, 2013, at 7:20 AM, Paul Sowman wrote: > Hi, which is the appropriate option in FT_CONNECTIVITYANALYIS to implement connectivity analysis via the imaginary part of coherency? The 2011 Computational Intelligence and Neuroscience paper says that the method from the Nolte paper is implemented but I'm not sure which is the right option to do this from the list: > coh', coherence, support for freq, freqmvar and > source data. For partial coherence also > specify cfg.partchannel > 'csd', cross-spectral density matrix, can also > calculate partial csds - > if cfg.partchannel is specified, support for freq and > freqmvar data > 'plv', phase-locking value, support for freq and freqmvar data > 'powcorr', power correlation, support for freq and source data > 'amplcorr', amplitude correlation, support for freq and source data > 'granger', granger causality, support for freq and freqmvar data > 'dtf', directed transfer function, support for freq and freqmvar data > 'pdc', partial directed coherence, support for freq and freqmvar data > 'psi', phaseslope index, support for freq and freqmvar data > 'wpli', weighted phase lag index (signed one, > still have to take absolute value to get indication of > strength of interaction. Note: measure has > positive bias. Use wpli_debiased to avoid > this. > 'wpli_debiased' debiased weighted phase lag index > (estimates squared wpli) > 'ppc' pairwise phase consistency > 'wppc' weighted pairwise phase consistency > > G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. > > -- > Paul F Sowman > NHMRC Postdoctoral Training Fellow > ARC Centre of Excellence for Cognition and its Disorders (CCD) > MACQUARIE UNIVERSITY NSW 2109 > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From polomacnenad at gmail.com Mon Feb 25 10:27:44 2013 From: polomacnenad at gmail.com (Nenad Polomac) Date: Mon, 25 Feb 2013 10:27:44 +0100 Subject: [FieldTrip] loreta in ft_sourceanalysis Message-ID: Dear Fieldtrip users, I would like to ask you which version of loreta is implemented in ft_sourceanalysis. Is it eloreta or sloreta? Thank you in advance! Kind regards! Nenad -------------- next part -------------- An HTML attachment was scrubbed... URL: From pd25588 at berkeley.edu Mon Feb 25 21:23:28 2013 From: pd25588 at berkeley.edu (Pascasie L. Dombert) Date: Mon, 25 Feb 2013 12:23:28 -0800 Subject: [FieldTrip] problem using ft_artifact_muscle Message-ID: Hi all, I am a fieldtrip starter working on an EEG data set. I have a question concerning the muscle artifact detection function and I was hoping that you could help me with this. I am calling the function [cfg,artifact_muscle] = ft_artifact_muscle(cfg,ref_data) as explained in the manual (settings suggested) and get the following error message (see code + error): ________________________________________________________________________________________________ > %detect the MUSCLE artifacts > cfg = []; > cfg.continuous = 'yes'; > % define trial first > cfg.dataset = 'xx’; > cfg.trialfun ='trialfun_general'; > cfg.trialdef.triallength =1; % creates 1-second data segments > cfg.trialdef.ntrials = inf; % i.e. the complete file > cfg = ft_definetrial(cfg); > > % cutoff > cfg.artfctdef.muscle.channel = 'all'; > cfg.artfctdef.muscle.cutoff = 4; > > % algorithmic parameters > cfg.artfctdef.muscle.bpfilter = 'yes'; > cfg.artfctdef.muscle.bpfreq = [110 140]; > cfg.artfctdef.muscle.bpfiltord = 9; > cfg.artfctdef.muscle.bpfilttype = 'but'; > cfg.artfctdef.muscle.hilbert = 'yes'; > cfg.artfctdef.muscle.boxcar = 0.2; > > % feedback > %cfg.artfctdef.muscle.interactive = 'yes'; % to adjust cutoff zvalue if needed > > [cfg, artifact_muscle] = ft_artifact_muscle(cfg,ref_data); > > > > > ERROR: > Subscript indices must either be real positive integers or logicals. > > Error in ft_fetch_data (line 123) > count = count(begsample:endsample); > > Error in ft_artifact_zvalue (line 195) > dat{trlop} = ft_fetch_data(data, 'header', hdr, 'begsample', trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding, 'chanindx', > sgnind, 'checkboundary', strcmp(cfg.continuous,' > Error in ft_artifact_muscle (line 156) > [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data); > _______________________________________________________ However, I only get the error message with the default/suggested values. When I use: cfg.artfctdef.muscle.bpfreq = [110 120]; and cfg.artfctdef.muscle.bpfiltord = 7; I don't get the error message and the script runs properly. Does anyone happen to know what could have let to this problem? Thanks a lot in advance! Best, Leonie -------------- next part -------------- An HTML attachment was scrubbed... URL: From eeguser at hotmail.com Mon Feb 25 22:52:49 2013 From: eeguser at hotmail.com (Subramaniam Iyer) Date: Tue, 26 Feb 2013 00:52:49 +0300 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order Message-ID: Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable : http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance.Subbu -------------- next part -------------- An HTML attachment was scrubbed... URL: From k.kouroupaki at med.uoc.gr Tue Feb 26 13:27:07 2013 From: k.kouroupaki at med.uoc.gr (k.kouroupaki at med.uoc.gr) Date: Tue, 26 Feb 2013 14:27:07 +0200 Subject: [FieldTrip] cfg.latency Message-ID: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> HI everyone! I am a new field trip user and have been using it for EEG SOURCE LOCALIZATION. I have a problem though. When I run the ft_sourceanalysis as: source = ft_sourceanalysis(cfg, freq) I get the following error: ??? Reference to non-existent field 'latency'. Error in ==> prepare_freq_matrices at 55 tbin = nearest(freq.time, cfg.latency); Error in ==> ft_sourceanalysis at 458 [Cf, Cr, Pr, Ntrials, cfg] = prepare_freq_matrices(cfg, data); Could you please help me to localize where the problem is and solve it? Thank you in advance, Kleo ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. From evaladez at psych.udel.edu Tue Feb 26 21:26:30 2013 From: evaladez at psych.udel.edu (Emilio Valadez) Date: Tue, 26 Feb 2013 15:26:30 -0500 Subject: [FieldTrip] Performing time-frequency statistical tests on regional source data Message-ID: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> Dear FieldTrip users, I have an EEG dataset that was reduced to 8 regional sources with BESA and then exported for FieldTrip analysis. I want to perform a statistical test on the regional sources' time-frequency data, comparing two experimental conditions, but I don't know whether it would be appropriate to use ft_freqstatistics (because I have regional sources instead of a complete sensor layout - making cluster formation problematic) or ft_sourcestatistics. Can you suggest a method for performing a statistical test in this situation? Thanks in advance for your help. Best, Emilio Valadez From jan.schoffelen at donders.ru.nl Tue Feb 26 21:36:28 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:36:28 +0100 Subject: [FieldTrip] Performing time-frequency statistical tests on regional source data In-Reply-To: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> References: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> Message-ID: <1ECC8F93-0E0D-4646-B407-96F3E5F13631@donders.ru.nl> Hi Emilio, Using ft_freqstatistics is very possible. Indeed you will not be able to use clustering for multiple comparison correction. In fact, having reduced the number of comparisons to 8 already almost gets rid of the multiple comparison problem. You can use a nonparametric permutation test without a cluster-based test statistic, and do a bonferroni correction on the p-values. Best, Jan-Mathijs On Feb 26, 2013, at 9:26 PM, Emilio Valadez wrote: > Dear FieldTrip users, > > I have an EEG dataset that was reduced to 8 regional sources with BESA and then exported for FieldTrip analysis. I want to perform a statistical test on the regional sources' time-frequency data, comparing two experimental conditions, but I don't know whether it would be appropriate to use ft_freqstatistics (because I have regional sources instead of a complete sensor layout - making cluster formation problematic) or ft_sourcestatistics. Can you suggest a method for performing a statistical test in this situation? Thanks in advance for your help. > > Best, > Emilio Valadez > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 21:44:21 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:44:21 +0100 Subject: [FieldTrip] cfg.latency In-Reply-To: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> References: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> Message-ID: <2C7B27EF-6A82-4781-B57D-5E2918DF8FEF@donders.ru.nl> Hi Kleo, Did you try following the suggestion that is in the error message, and specified a cfg.latency prior to calling ft_sourceanalysis? Best wishes, Jan-Mathijs On Feb 26, 2013, at 1:27 PM, k.kouroupaki at med.uoc.gr wrote: > HI everyone! > > I am a new field trip user and have been using it for EEG SOURCE LOCALIZATION. > I have a problem though. When I run the ft_sourceanalysis as: source = ft_sourceanalysis(cfg, freq) I get the following error: > > ??? Reference to non-existent field 'latency'. > > Error in ==> prepare_freq_matrices at 55 > tbin = nearest(freq.time, cfg.latency); > > Error in ==> ft_sourceanalysis at 458 > [Cf, Cr, Pr, Ntrials, cfg] = prepare_freq_matrices(cfg, data); > > Could you please help me to localize where the problem is and solve it? > Thank you in advance, > Kleo > > ---------------------------------------------------------------- > This message was sent using IMP, the Internet Messaging Program. > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 21:52:37 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:52:37 +0100 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: References: Message-ID: <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote: > Dear FieldTrip users > > I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. > > 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? > 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? > 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? > > Thanks in advance. > Subbu > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 22:03:23 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 22:03:23 +0100 Subject: [FieldTrip] problem using ft_artifact_muscle In-Reply-To: References: Message-ID: <2AD4BB54-F01D-40C7-89F2-20982BBBFD1F@donders.ru.nl> Hi Leonie, > > ERROR: > > > Subscript indices must either be real positive integers or logicals. > > > > > > Error in ft_fetch_data (line 123) > > > count = count(begsample:endsample); > > > > The error message indicates that either begsample or endsample are badly behaved. I put my money on begsample, in that its value <= 0 in the case of a bandpassfilter-order of 9. My guess is that ft_fetch_data tries to get some data that is not there. Did you check the cfg.artfctdef.muscle.fltpadding? In general, when supplying data in the input to ft_artifact_muscle, the value of this parameter should be set to 0. Best, Jan-Mathijs On Feb 25, 2013, at 9:23 PM, Pascasie L. Dombert wrote: > Hi all, > > > I am a fieldtrip starter working on an EEG data set. I have a question concerning the muscle artifact detection function and I was hoping that you could help me with this. > > I am calling the function > > [cfg,artifact_muscle] = ft_artifact_muscle(cfg,ref_data) as explained in the manual (settings suggested) and get the following error message (see code + error): > > ________________________________________________________________________________________________ > > > %detect the MUSCLE artifacts > > > cfg = []; > > > cfg.continuous = 'yes'; > > > % define trial first > > > cfg.dataset = 'xx’; > > > cfg.trialfun ='trialfun_general'; > > > cfg.trialdef.triallength =1; % creates 1-second data segments > > > cfg.trialdef.ntrials = inf; > > % i.e. the complete file > > > cfg = ft_definetrial(cfg); > > > > > > % cutoff > > > cfg.artfctdef.muscle.channel = 'all'; > > > cfg.artfctdef.muscle.cutoff = 4; > > > > > > % algorithmic parameters > > > cfg.artfctdef.muscle.bpfilter = 'yes'; > > > cfg.artfctdef.muscle.bpfreq = [110 140]; > > > cfg.artfctdef.muscle.bpfiltord = 9; > > > cfg.artfctdef.muscle.bpfilttype = 'but'; > > > cfg.artfctdef.muscle.hilbert = 'yes'; > > > cfg.artfctdef.muscle.boxcar = 0.2; > > > > > > % feedback > > > %cfg.artfctdef.muscle.interactive = 'yes'; % to adjust cutoff zvalue if needed > > > > > > [cfg, artifact_muscle] = ft_artifact_muscle(cfg,ref_data); > > > > > > > > > > > > > > > ERROR: > > > Subscript indices must either be real positive integers or logicals. > > > > > > Error in ft_fetch_data (line 123) > > > count = count(begsample:endsample); > > > > > > Error in ft_artifact_zvalue (line 195) > > > dat{trlop} = ft_fetch_data(data, 'header', hdr, 'begsample', trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding, 'chanindx', > > > sgnind, 'checkboundary', strcmp(cfg.continuous,' > > > Error in ft_artifact_muscle (line 156) > > > [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data); > > > _______________________________________________________ > > > > However, I only get the error message with the default/suggested values. > > When I use: > > cfg.artfctdef.muscle.bpfreq = [110 120]; and cfg.artfctdef.muscle.bpfiltord = 7; > > I don't get the error message and the script runs properly. Does anyone happen to know what could have let to this problem? > > > Thanks a lot in advance! > > Best, Leonie > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From eeguser at hotmail.com Wed Feb 27 00:07:00 2013 From: eeguser at hotmail.com (Subramaniam Iyer) Date: Wed, 27 Feb 2013 02:07:00 +0300 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> References: , <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> Message-ID: Dear Jan-Mathjis Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first.I have never done source localization before, but I will try it by going through the extensive FT documentation. However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ? RegardsSubbu From: jan.schoffelen at donders.ru.nl Date: Tue, 26 Feb 2013 21:52:37 +0100 To: fieldtrip at science.ru.nl Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote:Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance.Subbu_______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics,Nijmegen, The Netherlands J.Schoffelen at donders.ru.nlTelephone: +31-24-3614793 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From carlo.huber at uk-koeln.de Wed Feb 27 10:21:27 2013 From: carlo.huber at uk-koeln.de (Carlo Huber) Date: Wed, 27 Feb 2013 09:21:27 +0000 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: References: , <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl>, Message-ID: <877B32852B5C3A40978EA1F48A10B5022C9854B7@UKK087.ADS.UK-KOELN.DE> Dear Subbu, PDC seems to be influenced by filtering, see http://www.ncbi.nlm.nih.gov/pubmed/20026279 by Florin et al., 2010, Neuroimage. I would not recommend therefore applying PDC to source data. Other views are much welcome. Best, Carlo ________________________________ Von: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]" im Auftrag von "Subramaniam Iyer [eeguser at hotmail.com] Gesendet: Mittwoch, 27. Februar 2013 00:07 An: FieldTrip Betreff: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Jan-Mathjis Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first. I have never done source localization before, but I will try it by going through the extensive FT documentation. However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ? Regards Subbu ________________________________ From: jan.schoffelen at donders.ru.nl Date: Tue, 26 Feb 2013 21:52:37 +0100 To: fieldtrip at science.ru.nl Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote: Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance. Subbu _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophiechen33 at gmail.com Wed Feb 27 13:51:27 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Wed, 27 Feb 2013 13:51:27 +0100 Subject: [FieldTrip] troubles while reading 4D MEG files in getting the MEG channels In-Reply-To: <1538559706.484002.1361969272444.JavaMail.root@bureau-frontal1> References: <1538559706.484002.1361969272444.JavaMail.root@bureau-frontal1> Message-ID: Dear all, I am trying to read MEG 4D files with Fieldtrip version 20130226 using ft_preprocessing file with a preselection of MEG channels ( 'MEG' or a cell array of channel names, here is MEG_LABEL) but the output data contains only 152 channels while I have 248 channels... I tried the same code with Fieldtrip version 20121015, and I get everything properly (i.e. 248 channels) Following the script I am running and the corresponding results in matlab. *cfg = []; cfg.dataset = 'c,rfDC'; cfg.trialdef.eventtype = 'TRIGGER'; cfg.trialdef.eventvalue = 2; cfg.trialdef.prestim = 1; cfg.trialdef.poststim = 2; [cfg] = ft_definetrial(cfg); % cfg.channel = 'MEG'; cfg.channel = MEG_LABEL; cfg.continous = 'yes'; data_2 = ft_preprocessing (cfg)* *I get this >>* Warning: no trialfun was specified, using ft_trialfun_general > In ft_definetrial at 123 evaluating trialfunction 'ft_trialfun_general' applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_trialfun_general at 71 In ft_definetrial at 162 undoing the Supine balancing reading the events from 'c,rfDC' applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_read_event at 174 In ft_trialfun_general at 80 In ft_definetrial at 162 found 677 events created 249 trials the call to "ft_definetrial" took 5 seconds applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_preprocessing at 394 processing channel { 'A2' 'A104' 'A241' 'A138' 'A71' 'A125' 'A20' 'A65' 'A9' 'A114' 'A175' 'A228' 'A35' 'A191' 'A37' 'A170' 'A207' 'A224' 'A82' 'A238' 'A28' 'A239' 'A13' 'A165' 'A204' 'A25' 'A70' 'A11' 'A47' 'A64' 'A177' 'A127' 'A247' 'A194' 'A5' 'A242' 'A168' 'A31' 'A245' 'A219' 'A105' 'A222' 'A76' 'A188' 'A215' 'A235' 'A181' 'A38' 'A230' 'A91' 'A212' 'A24' 'A96' 'A57' 'A86' 'A116' 'A141' 'A120' 'A80' 'A210' 'A113' 'A27' 'A135' 'A167' 'A206' 'A100' 'A43' 'A200' 'A102' 'A132' 'A122' 'A62' 'A21' 'A229' 'A55' 'A32' 'A85' 'A58' 'A60' 'A88' 'A79' 'A203' 'A145' 'A139' 'A156' 'A68' 'A159' 'A236' 'A161' 'A6' 'A126' 'A94' 'A15' 'A193' 'A150' 'A36' 'A225' 'A195' 'A172' 'A108' 'A81' 'A171' 'A218' 'A173' 'A201' 'A74' 'A29' 'A164' 'A232' 'A69' 'A157' 'A97' 'A124' 'A40' 'A178' 'A179' 'A33' 'A147' 'A148' 'A89' 'A119' 'A52' 'A190' 'A73' 'A136' 'A184' 'A51' 'A77' 'A129' 'A197' 'A182' 'A46' 'A92' 'A41' 'A90' 'A23' 'A154' 'A18' 'A248' 'A149' 'A118' 'A152' 'A140' 'A110' 'A185' 'A162' 'A106' 'A187' 'A221' 'A133' 'A158' 'A216' } reading and preprocessing reading and preprocessing trial 249 from 249 the call to "ft_preprocessing" took 20 seconds data_2 = hdr: [1x1 struct] label: {152x1 cell} time: {1x249 cell} trial: {1x249 cell} fsample: 2.0345e+03 sampleinfo: [249x2 double] trialinfo: [249x1 double] grad: [1x1 struct] cfg: [1x1 struct] *This is what I get with Fieldtrip 20121015:* Warning: no trialfun was specified, using ft_trialfun_general > In ft_definetrial at 123 evaluating trialfunction 'ft_trialfun_general' applying digital weights in the gradiometer balancing matrix undoing the Supine balancing reading the events from 'c,rfDC' applying digital weights in the gradiometer balancing matrix undoing the Supine balancing found 677 events created 249 trials the call to "ft_definetrial" took 7 seconds applying digital weights in the gradiometer balancing matrix undoing the Supine balancing processing channel { 'A22' 'A2' 'A104' 'A241' 'A138' 'A214' 'A71' 'A26' 'A93' 'A39' 'A125' 'A20' 'A65' 'A9' 'A8' 'A95' 'A114' 'A175' 'A16' 'A228' 'A35' 'A191' 'A37' 'A170' 'A207' 'A112' 'A224' 'A82' 'A238' 'A202' 'A220' 'A28' 'A239' 'A13' 'A165' 'A204' 'A233' 'A98' 'A25' 'A70' 'A72' 'A11' 'A47' 'A160' 'A64' 'A3' 'A177' 'A63' 'A155' 'A10' 'A127' 'A67' 'A115' 'A247' 'A174' 'A194' 'A5' 'A242' 'A176' 'A78' 'A168' 'A31' 'A223' 'A245' 'A219' 'A12' 'A186' 'A105' 'A222' 'A76' 'A50' 'A188' 'A231' 'A45' 'A180' 'A99' 'A234' 'A215' 'A235' 'A181' 'A38' 'A230' 'A91' 'A212' 'A24' 'A66' 'A42' 'A96' 'A57' 'A86' 'A56' 'A116' 'A151' 'A141' 'A120' 'A189' 'A80' 'A210' 'A143' 'A113' 'A27' 'A137' 'A135' 'A167' 'A75' 'A240' 'A206' 'A107' 'A130' 'A100' 'A43' 'A200' 'A102' 'A132' 'A183' 'A199' 'A122' 'A19' 'A62' 'A21' 'A229' 'A84' 'A213' 'A55' 'A32' 'A85' 'A146' 'A58' 'A60' 'A88' 'A79' 'A169' 'A54' 'A203' 'A145' 'A103' 'A163' 'A139' 'A49' 'A166' 'A156' 'A128' 'A68' 'A159' 'A236' 'A161' 'A121' 'A4' 'A61' 'A6' 'A126' 'A14' 'A94' 'A15' 'A193' 'A150' 'A227' 'A59' 'A36' 'A225' 'A195' 'A30' 'A109' 'A172' 'A108' 'A81' 'A171' 'A218' 'A173' 'A201' 'A74' 'A29' 'A164' 'A205' 'A232' 'A69' 'A157' 'A97' 'A217' 'A101' 'A124' 'A40' 'A123' 'A153' 'A178' 'A1' 'A179' 'A33' 'A147' 'A117' 'A148' 'A87' 'A89' 'A243' 'A119' 'A52' 'A142' 'A211' 'A190' 'A53' 'A192' 'A73' 'A226' 'A136' 'A184' 'A51' 'A237' 'A77' 'A129' 'A131' 'A198' 'A197' 'A182' 'A46' 'A92' 'A41' 'A90' 'A7' 'A23' 'A83' 'A154' 'A34' 'A17' 'A18' 'A248' 'A149' 'A118' 'A208' 'A152' 'A140' 'A144' 'A209' 'A110' 'A111' 'A244' 'A185' 'A246' 'A162' 'A106' 'A187' 'A48' 'A221' 'A196' 'A133' 'A158' 'A44' 'A134' 'A216' } reading and preprocessing reading and preprocessing trial 249 from 249 the call to "ft_preprocessing" took 24 seconds data_2 = hdr: [1x1 struct] label: {248x1 cell} time: {1x249 cell} trial: {1x249 cell} fsample: 2.0345e+03 sampleinfo: [249x2 double] trialinfo: [249x1 double] grad: [1x1 struct] cfg: [1x1 struct] I hope this helps to find out where the problem is coming from... Thanks in advance for your help Cheers, Sophie Chen -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 28 17:38:21 2013 From: frank.ye.mei at gmail.com (Ye Mei) Date: Thu, 28 Feb 2013 11:38:21 -0500 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well Message-ID: <512F87FD.80500@gmail.com> Hello FieldtripList, After segmentation and alignment using 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented brain seems rotated forward in the sensor helmet(brain.png) and the cerebellum part seems to be segmented out. However, his head MRI seems fitting the sensor helmet well(head.jpg). My another subject's brain seem to be correctly segmented without missing the cerebellum part. And the brain is not rotated forward. Could might be the problem? thanks ahead, Ye -------------- next part -------------- A non-text attachment was scrubbed... Name: brain.png Type: image/png Size: 15197 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: head.jpg Type: image/jpeg Size: 50294 bytes Desc: not available URL: From r.oostenveld at donders.ru.nl Thu Feb 28 17:46:39 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Thu, 28 Feb 2013 17:46:39 +0100 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 In-Reply-To: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> References: <002201ce0e9a$e18ab740$a4a025c0$@stijns@fcdonders.ru.nl> <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> Message-ID: <9741C083-F00A-4BC9-86EF-FB99715576A7@donders.ru.nl> Dear FieldTrip users, The NIHC-BrainGain Tutorial Day marks the end of the BrainGain project. For the last 6 years, the development and continued support of FieldTrip for normal/offline and realtime/online analysis has received support from the BrainGain project. There is now more information available online on this tutorial day, please see https://www.hersenenencognitie.nl/contents/1876 https://www.hersenenencognitie.nl/contents/1915 If you happen to be close to Nijmegen, you might also want to come to the "Breinfest" on Tuesday evening 19 March in the city centre with talks by international speakers and BCI demo's for the general public. Personally, I will be demonstrating how real-time data streaming and processing can be done using the FieldTrip buffer to various platforms (OS X, WIndows, Linux), to the Raspberry Pi and even to an Arduino (yes, fieldtrip runs on an arduino! ... well, a small part of it runs on an arduino). See http://www.ru.nl/breinfest for details on the evening. best regards, Robert On 19 Feb 2013, at 14:30, Robert Oostenveld wrote: > > NIHC-BrainGain Tutorial Day: > Tools and novelties in neurotechnology research > > We invite PhD students, post-docs and senior researchers working in the fields of brain-computer interfacing (BCI), neurofeedback, cognitive neuroscience, neuroinformatics, neurosurgery and related topics to our Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen. > The day marks the end of the BrainGain consortium, a six-year joint-effort project on Brain-Computer Interfacing and related technologies. More information on BrainGain can be found here. > > The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. The 'tools' track is intended to provide both newcomers to the field and experienced researchers with an overview of the tools needed to integrate cognitive neuroscience and advanced invasive and non-invasive technology. Topics range from data streaming to modelling and statistics, and from online fMRI decoding to a crash course in neuroethics., You will also receive some helpful insights for a future career, in case you are interested in applying for a grant in the near future or considering setting up your own company. > The 'novelties' track covers a wide range of topics indicating some of the possible topics to be further explored in BCI and neurotechnology research, including genetics, robotics and intracranial recordings. > There is no need to stick to one of the two tracks the whole day: you are free to switch between tracks any time. > > In parallel to the lectures, there will be several interesting demonstrations. > > The full programme and registration form can be found on the NIHC website (https://www.hersenenencognitie.nl). Please register before 1 March 2013. Participation is free. Lunch and drinks will be provided. > > We hope to welcome you on March 21st in Nijmegen! > > Susanna Bicknell > Radboud University Nijmegen > ____________________________________________________________________ > Faculty of Science | Finance and Economic Affairs | Project Management | LC-IMPACT > Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | Project Manager > T +31 24 3653300 | HG00.616 (Monday, Thursday) > Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, Wednesday) > Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands > Visiting and courier service address: Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From jan.schoffelen at donders.ru.nl Thu Feb 28 18:54:14 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Thu, 28 Feb 2013 18:54:14 +0100 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well In-Reply-To: <512F87FD.80500@gmail.com> References: <512F87FD.80500@gmail.com> Message-ID: Hi Ye, Looks like a coregistration problem to me. In other words, something went wrong in ft_volumesegment, because the images were not sufficiently aligned. You need to investigate the input and output of ft_volumesegment. Do you use ft_volumerealign after calling ft_volumesegment? This should be the other way around. Best, Jan-Mathijs On Feb 28, 2013, at 5:38 PM, Ye Mei wrote: > Hello FieldtripList, > > After segmentation and alignment using > 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented > brain seems rotated forward in the sensor helmet(brain.png) and the > cerebellum part seems to be segmented out. However, his head MRI seems > fitting the sensor helmet well(head.jpg). My another subject's brain > seem to be correctly segmented without missing the cerebellum part. And > the brain is not rotated forward. > > Could might be the problem? > > thanks ahead, > Ye > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 28 23:09:57 2013 From: frank.ye.mei at gmail.com (Ye Mei) Date: Thu, 28 Feb 2013 17:09:57 -0500 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well In-Reply-To: References: Message-ID: <512FD5B5.8080700@gmail.com> Hello All, I found the problem I mentioned in the previous email was caused by using "mri_sliced = ft_volumereslice([], mri);" before using ft_volumesegment. After erasing the line "mri_sliced = ft_volumereslice([], mri);", the segmented brain seems to be normal and fits the sensor helmet well now, as show in the attached figure(notvolumnsliced.jpg). For another of my subject, if the "ft_volumereslice" is included, the brain looks sliced on the top(subject2vs.jpg). If no "ft_volumreslice" it looks normal(subject2.jpg). I notice in the fieldtrip headmodel tutorial (http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg), "ft_volumereslice" is not used. but in the field trip beamformer tutorial(http://fieldtrip.fcdonders.nl/tutorial/beamformer), it is used. I am wondering if I should include "ft_volumereslice" in my source localization code. Can anyone give me some suggestions? thanks ahead, Ye On 13-02-28 11:45 AM, fieldtrip-request at science.ru.nl wrote: > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > or, via email, send a message with subject or body 'help' to > fieldtrip-request at science.ru.nl > > You can reach the person managing the list at > fieldtrip-owner at science.ru.nl > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of fieldtrip digest..." > > > Today's Topics: > > 1. segmented brain seems not fitting the sensor helmet well (Ye Mei) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Thu, 28 Feb 2013 11:38:21 -0500 > From: Ye Mei > To: fieldtrip at science.ru.nl > Subject: [FieldTrip] segmented brain seems not fitting the sensor > helmet well > Message-ID: <512F87FD.80500 at gmail.com> > Content-Type: text/plain; charset="iso-8859-1"; Format="flowed" > > Hello FieldtripList, > > After segmentation and alignment using > 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented > brain seems rotated forward in the sensor helmet(brain.png) and the > cerebellum part seems to be segmented out. However, his head MRI seems > fitting the sensor helmet well(head.jpg). My another subject's brain > seem to be correctly segmented without missing the cerebellum part. And > the brain is not rotated forward. > > Could might be the problem? > > thanks ahead, > Ye > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: brain.png > Type: image/png > Size: 15197 bytes > Desc: not available > URL: > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: head.jpg > Type: image/jpeg > Size: 50294 bytes > Desc: not available > URL: > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 27, Issue 31 > ***************************************** -------------- next part -------------- A non-text attachment was scrubbed... Name: notvolumnsliced.jpg Type: image/jpeg Size: 28621 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: subject2.jpg Type: image/jpeg Size: 27415 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: subject2vc.jpg Type: image/jpeg Size: 27788 bytes Desc: not available URL: From andrea.brovelli at univ-amu.fr Mon Feb 4 09:22:17 2013 From: andrea.brovelli at univ-amu.fr (andrea brovelli) Date: Mon, 04 Feb 2013 09:22:17 +0100 Subject: [FieldTrip] Error in prepare_freq_matrices.m ? In-Reply-To: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> References: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> Message-ID: <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> Dear all, I have an error while running ft_sourceanalysis. I am analysing a data set over a frequency range which includes 100 frequencies and 60 trials. I get an error due to the definition of the variable Ntrials, which as far as I understand, it is done in prepare_freq_matrices.m at lines 76 -> 85: ------------------------------------------------- % the time-frequency latency has already been squeezed away (see above) if strcmp(freq.dimord, 'chan_freq') Ntrials = 1; elseif strcmp(freq.dimord, 'rpt_chan_freq') Ntrials = length(freq.cumtapcnt); elseif strcmp(freq.dimord, 'rpttap_chan_freq') Ntrials = length(freq.cumtapcnt); else error('unrecognized dimord for frequency data'); end ------------------------------------------------- If the number of trials is less than the number of frequencies, Ntrials = length(freq.cumtapcnt) should be replaced by Ntrials = size(freq.cumtapcnt,1); It is the case ? Thanks a lot Andrea From jan.schoffelen at donders.ru.nl Mon Feb 4 12:01:11 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Mon, 4 Feb 2013 12:01:11 +0100 Subject: [FieldTrip] Error in prepare_freq_matrices.m ? In-Reply-To: <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> References: <20130129171605.176164iln90u72f4@wmelperso1.univmed.fr> <20130204092217.951517otbyl27feo@wmelperso1.univmed.fr> Message-ID: <7C99534A-440F-4B53-BFCC-F0968FF0BB9D@donders.ru.nl> Hi Andrea, This could very well be. Sorry for not getting back to you earlier. Could you create an account on our bugzilla server and file this as a bug? We will then look into it (and fix it) as soon as possible. For the time being, could you work around it by just changing your code locally? Thanks and best wishes, Jan-Mathijs On Feb 4, 2013, at 9:22 AM, andrea brovelli wrote: > > Dear all, > > I have an error while running ft_sourceanalysis. I am analysing a data set over a frequency range which includes 100 frequencies and 60 trials. I get an error due to the definition of the variable Ntrials, which as far as I understand, it is done in prepare_freq_matrices.m at lines 76 -> 85: > > ------------------------------------------------- > % the time-frequency latency has already been squeezed away (see above) > if strcmp(freq.dimord, 'chan_freq') > Ntrials = 1; > elseif strcmp(freq.dimord, 'rpt_chan_freq') > Ntrials = length(freq.cumtapcnt); > elseif strcmp(freq.dimord, 'rpttap_chan_freq') > Ntrials = length(freq.cumtapcnt); > else > error('unrecognized dimord for frequency data'); > end > ------------------------------------------------- > > If the number of trials is less than the number of frequencies, Ntrials = length(freq.cumtapcnt) should be replaced by Ntrials = size(freq.cumtapcnt,1); > > It is the case ? > > Thanks a lot > > Andrea > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Tue Feb 5 22:40:56 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Tue, 5 Feb 2013 21:40:56 +0000 Subject: [FieldTrip] localspheres Message-ID: Hello, I have what is possibly a naïve question, but I can't seem to find anything on the tutorial pages. I'm trying to create a headmodel using the localspheres method, using the output of a segmented MRI. There is a tutorial page for using different types of headmodels, but it references ft_prepare_localspheres - which works, but it appears to have been deprecated. When I try this: hdr=ft_read_header('mydata.ds'); cfg=[]; cfg.method='localspheres'; cfg.grad=hdr.grad; cfg.vol=segmented_mri; vol=ft_prepare_headmodel(cfg, segmentedmri); I get an error at ft_getopt(cfg,'tissue'); Although the documentation for ft_prepare_headmodel states that the only additional field needed by localspheres is "cfg.grad" it seems that cfg.tissue may also be required? If so, how do I set this - I can't find any documentation that explains. I should note that I've run ft_prepare_headmodel successfully using a singleshell method. Thanks, Allison Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Wed Feb 6 09:53:15 2013 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Wed, 6 Feb 2013 09:53:15 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Dear Allison, Thank you for your question. There have been some changes to ft_prepare_headmodel recently (partly implemented by me) and my apologies that the documentation for these changes was not made thoroughly. I assume that you are refering to a very recent FT version. :-) The way that you call ft_prepare_headmodel looks almost correct, except that cfg.vol is not needed. If you have already a 'vol' or 'bnd' , then that can be used as the second input argument to ft_prepare_headmodel, and the 'segmentedmri' is not needed. If you don't already have a 'vol' or 'bnd', then that will be created on the fly within ft_prepare_headmodel from the segmentedmri that you include as second input. However, what are the fields within 'segmentedmri' that you use? If 'brain' or 'scalp' already exist, then those will be found and used by default, and therefore a cfg.tissue is not needed. However, if you have other fields with different names, etc then cfg.tissue should point to the name of the subfield of segmentedmri that you wish to use as the headshape. Please see ft_volumesegment for more details on which tissue types or segmentation types can be computed as output and which can then be used in subsequent functions. Perhaps simply recompute the segmentedmri with the newest version of ft_volumesegment and then it will work? In the meantime, I will update the documentation to make all this more clear. However, one more question. I'm not sure what you mean by the error you get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it will return a default empty variable, and there should not be an error. Can you say exactly what line of what function gives the error, and what the error exactly is? And finally, when you successfully ran singleshell method, was that with the segmentedmri (which would surprise me), or rather with a cfg.headshape option? Cheers, Johanna 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] > Hello, **** > > ** ** > > I have what is possibly a naïve question, but I can’t seem to find > anything on the tutorial pages.**** > > ** ** > > I’m trying to create a headmodel using the localspheres method, using the > output of a segmented MRI.**** > > ** ** > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres – which works, but it appears to have > been deprecated. When I try this:**** > > ** ** > > hdr=ft_read_header(‘mydata.ds’);**** > > cfg=[];**** > > cfg.method=’localspheres’;**** > > cfg.grad=hdr.grad;**** > > cfg.vol=segmented_mri;**** > > vol=ft_prepare_headmodel(cfg, segmentedmri);**** > > ** ** > > I get an error at ft_getopt(cfg,’tissue’);**** > > ** ** > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is “cfg.grad” it seems that > cfg.tissue may also be required? If so, how do I set this – I can’t find > any documentation that explains.**** > > ** ** > > I should note that I’ve run ft_prepare_headmodel successfully using a > singleshell method.**** > > ** ** > > Thanks,**** > > ** ** > > Allison**** > > ** ** > > Allison Nugent, PhD**** > > MRI Physicist**** > > Experimental Therapeutics and Pathophysiology Branch**** > > NIMH/NIH/DHHS**** > > Ph. 301-451-8863**** > > nugenta at mail.nih.gov**** > > ** ** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Wed Feb 6 09:56:29 2013 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Wed, 6 Feb 2013 09:56:29 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Sorry, I meant if you have a 'bnd'. Of course you won't have the 'vol', that is the purpose of calling ft_prepare_headmodel! Johanna 2013/2/6 Johanna Zumer > Dear Allison, > > Thank you for your question. There have been some changes to > ft_prepare_headmodel recently (partly implemented by me) and my apologies > that the documentation for these changes was not made thoroughly. I > assume that you are refering to a very recent FT version. :-) > > The way that you call ft_prepare_headmodel looks almost correct, except > that cfg.vol is not needed. > > If you have already a 'vol' or 'bnd' , then that can be used as the second > input argument to ft_prepare_headmodel, and the 'segmentedmri' is not > needed. > > If you don't already have a 'vol' or 'bnd', then that will be created on > the fly within ft_prepare_headmodel from the segmentedmri that you include > as second input. However, what are the fields within 'segmentedmri' that > you use? If 'brain' or 'scalp' already exist, then those will be found > and used by default, and therefore a cfg.tissue is not needed. However, if > you have other fields with different names, etc then cfg.tissue should > point to the name of the subfield of segmentedmri that you wish to use as > the headshape. Please see ft_volumesegment for more details on which > tissue types or segmentation types can be computed as output and which can > then be used in subsequent functions. Perhaps simply recompute the > segmentedmri with the newest version of ft_volumesegment and then it will > work? > > In the meantime, I will update the documentation to make all this more > clear. > > However, one more question. I'm not sure what you mean by the error you > get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it will > return a default empty variable, and there should not be an error. Can > you say exactly what line of what function gives the error, and what the > error exactly is? > > And finally, when you successfully ran singleshell method, was that with > the segmentedmri (which would surprise me), or rather with a cfg.headshape > option? > > Cheers, > Johanna > > > > > > > > > 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] > >> Hello, **** >> >> ** ** >> >> I have what is possibly a naïve question, but I can’t seem to find >> anything on the tutorial pages.**** >> >> ** ** >> >> I’m trying to create a headmodel using the localspheres method, using the >> output of a segmented MRI.**** >> >> ** ** >> >> There is a tutorial page for using different types of headmodels, but it >> references ft_prepare_localspheres – which works, but it appears to have >> been deprecated. When I try this:**** >> >> ** ** >> >> hdr=ft_read_header(‘mydata.ds’);**** >> >> cfg=[];**** >> >> cfg.method=’localspheres’;**** >> >> cfg.grad=hdr.grad;**** >> >> cfg.vol=segmented_mri;**** >> >> vol=ft_prepare_headmodel(cfg, segmentedmri);**** >> >> ** ** >> >> I get an error at ft_getopt(cfg,’tissue’);**** >> >> ** ** >> >> Although the documentation for ft_prepare_headmodel states that the only >> additional field needed by localspheres is “cfg.grad” it seems that >> cfg.tissue may also be required? If so, how do I set this – I can’t find >> any documentation that explains.**** >> >> ** ** >> >> I should note that I’ve run ft_prepare_headmodel successfully using a >> singleshell method.**** >> >> ** ** >> >> Thanks,**** >> >> ** ** >> >> Allison**** >> >> ** ** >> >> Allison Nugent, PhD**** >> >> MRI Physicist**** >> >> Experimental Therapeutics and Pathophysiology Branch**** >> >> NIMH/NIH/DHHS**** >> >> Ph. 301-451-8863**** >> >> nugenta at mail.nih.gov**** >> >> ** ** >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Lilla.Magyari at mpi.nl Wed Feb 6 10:32:15 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 10:32:15 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> hi Allison, this was a small a bug in FieldTrip a few weeks ago. It has been fixed since then already, so I think if you download the latest version, you can run ft_prepare_headmodel with method 'localspheres' without the specification of tissue-type. In this case, the geometry of the 'brain' tissue will be used for the headmodel by default. Therefore, it will work only if your segmentation contains a binary mask of the brain (i.e. your segmentation should have a 'brain' field with binary values) or if your segmentation contains the probability tissue maps of 'gray','white','csf' tissue. In this later case, the brain mask will be created from gray, white and csf by the function. But actually, if you want to run ft_prepare_headmodel with your version, you can just specify the name of the tissue that is in your segmentation. Best, Lilla > Hello, > > I have what is possibly a naïve question, but I can't seem to find > anything on the tutorial pages. > > I'm trying to create a headmodel using the localspheres method, using the > output of a segmented MRI. > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres - which works, but it appears to have > been deprecated. When I try this: > > hdr=ft_read_header('mydata.ds'); > cfg=[]; > cfg.method='localspheres'; > cfg.grad=hdr.grad; > cfg.vol=segmented_mri; > vol=ft_prepare_headmodel(cfg, segmentedmri); > > I get an error at ft_getopt(cfg,'tissue'); > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is "cfg.grad" it seems that > cfg.tissue may also be required? If so, how do I set this - I can't find > any documentation that explains. > > I should note that I've run ft_prepare_headmodel successfully using a > singleshell method. > > Thanks, > > Allison > > Allison Nugent, PhD > MRI Physicist > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph. 301-451-8863 > nugenta at mail.nih.gov > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From smoratti at psi.ucm.es Wed Feb 6 10:34:23 2013 From: smoratti at psi.ucm.es (STEPHAN MORATTI) Date: Wed, 6 Feb 2013 10:34:23 +0100 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: I guess you would need headshape points for the local spheres. Not sure if ft automatically creates a head surface from the segmented MRI. Best Stephan El 05/02/2013 23:25, "Nugent, Allison C. (NIH/NIMH) [E]" < nugenta at mail.nih.gov> escribió: > Hello, **** > > ** ** > > I have what is possibly a naïve question, but I can’t seem to find > anything on the tutorial pages.**** > > ** ** > > I’m trying to create a headmodel using the localspheres method, using the > output of a segmented MRI.**** > > ** ** > > There is a tutorial page for using different types of headmodels, but it > references ft_prepare_localspheres – which works, but it appears to have > been deprecated. When I try this:**** > > ** ** > > hdr=ft_read_header(‘mydata.ds’);**** > > cfg=[];**** > > cfg.method=’localspheres’;**** > > cfg.grad=hdr.grad;**** > > cfg.vol=segmented_mri;**** > > vol=ft_prepare_headmodel(cfg, segmentedmri);**** > > ** ** > > I get an error at ft_getopt(cfg,’tissue’);**** > > ** ** > > Although the documentation for ft_prepare_headmodel states that the only > additional field needed by localspheres is “cfg.grad” it seems that > cfg.tissue may also be required? If so, how do I set this – I can’t find > any documentation that explains.**** > > ** ** > > I should note that I’ve run ft_prepare_headmodel successfully using a > singleshell method.**** > > ** ** > > Thanks,**** > > ** ** > > Allison**** > > ** ** > > Allison Nugent, PhD**** > > MRI Physicist**** > > Experimental Therapeutics and Pathophysiology Branch**** > > NIMH/NIH/DHHS**** > > Ph. 301-451-8863**** > > nugenta at mail.nih.gov**** > > ** ** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Lilla.Magyari at mpi.nl Wed Feb 6 10:43:38 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 10:43:38 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: <49445.131.174.45.70.1360143818.squirrel@131.174.45.70> hi Johanna and Allison, I think there was a small bug in ft_prepare_headmodel http://bugzilla.fcdonders.nl/show_bug.cgi?id=1679 a few weeks ago which caused this error. It has been fixed already, so if the newest version of FT is used, ft_prepare_headmodel should run now with cfg.method 'localspheres' without cfg.tissue specified. But this depends on the tissues in the segmentation as Johanna wrote. But besides 'brain' and 'scalp', it is also fine if the segmentation contains the probability tissue maps of the cerebro-spinal fluid, the gray and white matter. In this case, brain binary mask will be created by the function from csf,w hite and gray and the geometry of the brain tissue will be used for the head-model. I hope this helps too. Best, Lilla > Sorry, I meant if you have a 'bnd'. Of course you won't have the 'vol', > that is the purpose of calling ft_prepare_headmodel! > > Johanna > > > 2013/2/6 Johanna Zumer > >> Dear Allison, >> >> Thank you for your question. There have been some changes to >> ft_prepare_headmodel recently (partly implemented by me) and my >> apologies >> that the documentation for these changes was not made thoroughly. I >> assume that you are refering to a very recent FT version. :-) >> >> The way that you call ft_prepare_headmodel looks almost correct, except >> that cfg.vol is not needed. >> >> If you have already a 'vol' or 'bnd' , then that can be used as the >> second >> input argument to ft_prepare_headmodel, and the 'segmentedmri' is not >> needed. >> >> If you don't already have a 'vol' or 'bnd', then that will be created on >> the fly within ft_prepare_headmodel from the segmentedmri that you >> include >> as second input. However, what are the fields within 'segmentedmri' >> that >> you use? If 'brain' or 'scalp' already exist, then those will be found >> and used by default, and therefore a cfg.tissue is not needed. However, >> if >> you have other fields with different names, etc then cfg.tissue should >> point to the name of the subfield of segmentedmri that you wish to use >> as >> the headshape. Please see ft_volumesegment for more details on which >> tissue types or segmentation types can be computed as output and which >> can >> then be used in subsequent functions. Perhaps simply recompute the >> segmentedmri with the newest version of ft_volumesegment and then it >> will >> work? >> >> In the meantime, I will update the documentation to make all this more >> clear. >> >> However, one more question. I'm not sure what you mean by the error you >> get with ft_getopt(cfg,'tissue'). If 'tissue' is not in cfg, then it >> will >> return a default empty variable, and there should not be an error. >> Can >> you say exactly what line of what function gives the error, and what the >> error exactly is? >> >> And finally, when you successfully ran singleshell method, was that with >> the segmentedmri (which would surprise me), or rather with a >> cfg.headshape >> option? >> >> Cheers, >> Johanna >> >> >> >> >> >> >> >> >> 2013/2/5 Nugent, Allison C. (NIH/NIMH) [E] >> >>> Hello, **** >>> >>> ** ** >>> >>> I have what is possibly a naïve question, but I can’t seem to find >>> anything on the tutorial pages.**** >>> >>> ** ** >>> >>> I’m trying to create a headmodel using the localspheres method, using >>> the >>> output of a segmented MRI.**** >>> >>> ** ** >>> >>> There is a tutorial page for using different types of headmodels, but >>> it >>> references ft_prepare_localspheres – which works, but it appears to >>> have >>> been deprecated. When I try this:**** >>> >>> ** ** >>> >>> hdr=ft_read_header(‘mydata.ds’);**** >>> >>> cfg=[];**** >>> >>> cfg.method=’localspheres’;**** >>> >>> cfg.grad=hdr.grad;**** >>> >>> cfg.vol=segmented_mri;**** >>> >>> vol=ft_prepare_headmodel(cfg, segmentedmri);**** >>> >>> ** ** >>> >>> I get an error at ft_getopt(cfg,’tissue’);**** >>> >>> ** ** >>> >>> Although the documentation for ft_prepare_headmodel states that the >>> only >>> additional field needed by localspheres is “cfg.grad” it seems that >>> cfg.tissue may also be required? If so, how do I set this – I can’t >>> find >>> any documentation that explains.**** >>> >>> ** ** >>> >>> I should note that I’ve run ft_prepare_headmodel successfully using a >>> singleshell method.**** >>> >>> ** ** >>> >>> Thanks,**** >>> >>> ** ** >>> >>> Allison**** >>> >>> ** ** >>> >>> Allison Nugent, PhD**** >>> >>> MRI Physicist**** >>> >>> Experimental Therapeutics and Pathophysiology Branch**** >>> >>> NIMH/NIH/DHHS**** >>> >>> Ph. 301-451-8863**** >>> >>> nugenta at mail.nih.gov**** >>> >>> ** ** >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From Lilla.Magyari at mpi.nl Wed Feb 6 11:19:31 2013 From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl) Date: Wed, 6 Feb 2013 11:19:31 +0100 (CET) Subject: [FieldTrip] localspheres In-Reply-To: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> References: <49433.131.174.45.70.1360143135.squirrel@131.174.45.70> Message-ID: <49498.131.174.45.70.1360145971.squirrel@131.174.45.70> dear all, sorry for the multiply posting. My email browser is not working properly. Lilla > hi Allison, > > this was a small a bug in FieldTrip a few weeks ago. It has been fixed > since then already, so I think if you download the latest version, you can > run ft_prepare_headmodel with method 'localspheres' without the > specification of tissue-type. In this case, the geometry of the 'brain' > tissue will be used for the headmodel by default. Therefore, it will work > only if your segmentation contains a binary mask of the brain (i.e. your > segmentation should have a 'brain' field with binary values) or if your > segmentation contains the probability tissue maps of 'gray','white','csf' > tissue. In this later case, the brain mask will be created from gray, > white and csf by the function. > > But actually, if you want to run ft_prepare_headmodel with your version, > you can just specify the name of the tissue that is in your segmentation. > > Best, > Lilla > > >> Hello, >> >> I have what is possibly a naïve question, but I can't seem to find >> anything on the tutorial pages. >> >> I'm trying to create a headmodel using the localspheres method, using >> the >> output of a segmented MRI. >> >> There is a tutorial page for using different types of headmodels, but it >> references ft_prepare_localspheres - which works, but it appears to have >> been deprecated. When I try this: >> >> hdr=ft_read_header('mydata.ds'); >> cfg=[]; >> cfg.method='localspheres'; >> cfg.grad=hdr.grad; >> cfg.vol=segmented_mri; >> vol=ft_prepare_headmodel(cfg, segmentedmri); >> >> I get an error at ft_getopt(cfg,'tissue'); >> >> Although the documentation for ft_prepare_headmodel states that the only >> additional field needed by localspheres is "cfg.grad" it seems that >> cfg.tissue may also be required? If so, how do I set this - I can't >> find >> any documentation that explains. >> >> I should note that I've run ft_prepare_headmodel successfully using a >> singleshell method. >> >> Thanks, >> >> Allison >> >> Allison Nugent, PhD >> MRI Physicist >> Experimental Therapeutics and Pathophysiology Branch >> NIMH/NIH/DHHS >> Ph. 301-451-8863 >> nugenta at mail.nih.gov >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > From robince at gmail.com Wed Feb 6 12:54:01 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 11:54:01 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca Message-ID: Hi all, I am a new fieldtrip user getting started preprocessing a large MEG data set (I am in Glasgow and the data was collected at CCNi). I think I am slowly getting to grips with all the steps necessary, but I have a question about the artifact rejection. My undersanding is that the denoise procedure helps correct external sources of noise, so having the signal cleaned in this way should help detect the biological artifacts which are valid magnetic signal at the scalp. But I can't see an easy way to do this since the ft_artifact_* functions want to load the raw continuous data from disk. I can get them to act on the in memory trials data if I set the padding options to 0, but then I get an unacceptable amount of rejections (I guess because of the filter artifacts the padding usually prevents). Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the denoised signal from ft_denoise_pca and if so how? At the moment I am performing the following steps: Load each run Detect jumps with ft_artifact_jump. Concatenate the jump-free trials from all runs together for this block. Visually inspect the reference channels and remove high variance trials (across the whole block). Compute denoise PCA weights using only good reference data (and no MEG jump) trials across the whole block. I would now like to apply the denoise PCA weights, perform other automatic artifact removal on the cleaned data, before further visual inspection and the next steps of ICA etc. Is there any problems with this strategy? Thanks in advance for any advice, Robin From jm.horschig at donders.ru.nl Wed Feb 6 15:02:03 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Wed, 06 Feb 2013 15:02:03 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: Message-ID: <5112625B.9090504@donders.ru.nl> Hi Robin, I think the steps you suggested sound reasonable, but I do not see how you are avoiding the filter artifact issue there, you just postpone it to a later stage. Instead it might be a smart way to 'pad' your trials when defining them with 1s pre- and post (so cut out more than you need); that way all filter artifacts will be in that 1s that you are not interested in anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I understand your question correctly, that solves your problem, doesn't it? Best, Jörn On 2/6/2013 12:54 PM, Robin wrote: > Hi all, > > I am a new fieldtrip user getting started preprocessing a large MEG > data set (I am in Glasgow and the data was collected at CCNi). > > I think I am slowly getting to grips with all the steps necessary, but > I have a question about the artifact rejection. > > My undersanding is that the denoise procedure helps correct external > sources of noise, so having the signal cleaned in this way should help > detect the biological artifacts which are valid magnetic signal at the > scalp. But I can't see an easy way to do this since the ft_artifact_* > functions want to load the raw continuous data from disk. I can get > them to act on the in memory trials data if I set the padding options > to 0, but then I get an unacceptable amount of rejections (I guess > because of the filter artifacts the padding usually prevents). > > Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the > denoised signal from ft_denoise_pca and if so how? > > At the moment I am performing the following steps: > > Load each run > Detect jumps with ft_artifact_jump. > Concatenate the jump-free trials from all runs together for this block. > > Visually inspect the reference channels and remove high variance > trials (across the whole block). > Compute denoise PCA weights using only good reference data (and no MEG > jump) trials across the whole block. > > I would now like to apply the denoise PCA weights, perform other > automatic artifact removal on the cleaned data, before further visual > inspection and the next steps of ICA etc. > > Is there any problems with this strategy? > > Thanks in advance for any advice, > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands From robince at gmail.com Wed Feb 6 15:07:30 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 14:07:30 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: <5112625B.9090504@donders.ru.nl> References: <5112625B.9090504@donders.ru.nl> Message-ID: Hi Jörn, Thanks very much. Yes I think that will solve the problem - I hadn't realised I could use negative trial padding values. What I had just got working was as similar approach extracting larger trials at first and then manually making a new trl defintion: % artifact detection tmpcfg = []; tmpcfg.continuous = 'no'; % some trials are excluded tmpcfg.trl = run_clean.sampleinfo; tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + round(filterpad*run_clean.fsample); tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - round(filterpad*run_clean.fsample); [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); which seemed to work but the trlpadding option definitely looks cleaner! Thanks, Robin On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" wrote: > Hi Robin, > > I think the steps you suggested sound reasonable, but I do not see how you > are avoiding the filter artifact issue there, you just postpone it to a > later stage. Instead it might be a smart way to 'pad' your trials when > defining them with 1s pre- and post (so cut out more than you need); that > way all filter artifacts will be in that 1s that you are not interested in > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > understand your question correctly, that solves your problem, doesn't it? > > Best, > Jörn > > > > On 2/6/2013 12:54 PM, Robin wrote: >> >> Hi all, >> >> I am a new fieldtrip user getting started preprocessing a large MEG >> data set (I am in Glasgow and the data was collected at CCNi). >> >> I think I am slowly getting to grips with all the steps necessary, but >> I have a question about the artifact rejection. >> >> My undersanding is that the denoise procedure helps correct external >> sources of noise, so having the signal cleaned in this way should help >> detect the biological artifacts which are valid magnetic signal at the >> scalp. But I can't see an easy way to do this since the ft_artifact_* >> functions want to load the raw continuous data from disk. I can get >> them to act on the in memory trials data if I set the padding options >> to 0, but then I get an unacceptable amount of rejections (I guess >> because of the filter artifacts the padding usually prevents). >> >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the >> denoised signal from ft_denoise_pca and if so how? >> >> At the moment I am performing the following steps: >> >> Load each run >> Detect jumps with ft_artifact_jump. >> Concatenate the jump-free trials from all runs together for this block. >> >> Visually inspect the reference channels and remove high variance >> trials (across the whole block). >> Compute denoise PCA weights using only good reference data (and no MEG >> jump) trials across the whole block. >> >> I would now like to apply the denoise PCA weights, perform other >> automatic artifact removal on the cleaned data, before further visual >> inspection and the next steps of ICA etc. >> >> Is there any problems with this strategy? >> >> Thanks in advance for any advice, >> >> Robin >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > -- > Jörn M. Horschig > PhD Student > Donders Institute for Brain, Cognition and Behaviour > Centre for Cognitive Neuroimaging > Radboud University Nijmegen > Neuronal Oscillations Group > FieldTrip Development Team > > P.O. Box 9101 > NL-6500 HB Nijmegen > The Netherlands > > Contact: > E-Mail: jm.horschig at donders.ru.nl > Tel: +31-(0)24-36-68493 > Web: http://www.ru.nl/donders > > Visiting address: > Trigon, room 2.30 > Kapittelweg 29 > NL-6525 EN Nijmegen > The Netherlands > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From stephen.whitmarsh at gmail.com Wed Feb 6 15:17:39 2013 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Wed, 6 Feb 2013 15:17:39 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: Dear Robin, Please allow me to refer you to the excellent documentation on (negative) padding and artifact rejection in this gorgeous didactical masterpiece, a joy to behold: ***** http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection***** ;-) Stephen On 6 February 2013 15:07, Robin wrote: > Hi Jörn, > > Thanks very much. Yes I think that will solve the problem - I hadn't > realised I could use negative trial padding values. > What I had just got working was as similar approach extracting larger > trials at first and then manually making a new trl defintion: > > % artifact detection > tmpcfg = []; > tmpcfg.continuous = 'no'; % some trials are excluded > tmpcfg.trl = run_clean.sampleinfo; > tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + round(filterpad*run_clean.fsample); > tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - round(filterpad*run_clean.fsample); > > [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); > > which seemed to work but the trlpadding option definitely looks cleaner! > > Thanks, > > Robin > > On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" > wrote: > > Hi Robin, > > > > I think the steps you suggested sound reasonable, but I do not see how > you > > are avoiding the filter artifact issue there, you just postpone it to a > > later stage. Instead it might be a smart way to 'pad' your trials when > > defining them with 1s pre- and post (so cut out more than you need); that > > way all filter artifacts will be in that 1s that you are not interested > in > > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > > understand your question correctly, that solves your problem, doesn't it? > > > > Best, > > Jörn > > > > > > > > On 2/6/2013 12:54 PM, Robin wrote: > >> > >> Hi all, > >> > >> I am a new fieldtrip user getting started preprocessing a large MEG > >> data set (I am in Glasgow and the data was collected at CCNi). > >> > >> I think I am slowly getting to grips with all the steps necessary, but > >> I have a question about the artifact rejection. > >> > >> My undersanding is that the denoise procedure helps correct external > >> sources of noise, so having the signal cleaned in this way should help > >> detect the biological artifacts which are valid magnetic signal at the > >> scalp. But I can't see an easy way to do this since the ft_artifact_* > >> functions want to load the raw continuous data from disk. I can get > >> them to act on the in memory trials data if I set the padding options > >> to 0, but then I get an unacceptable amount of rejections (I guess > >> because of the filter artifacts the padding usually prevents). > >> > >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the > >> denoised signal from ft_denoise_pca and if so how? > >> > >> At the moment I am performing the following steps: > >> > >> Load each run > >> Detect jumps with ft_artifact_jump. > >> Concatenate the jump-free trials from all runs together for this block. > >> > >> Visually inspect the reference channels and remove high variance > >> trials (across the whole block). > >> Compute denoise PCA weights using only good reference data (and no MEG > >> jump) trials across the whole block. > >> > >> I would now like to apply the denoise PCA weights, perform other > >> automatic artifact removal on the cleaned data, before further visual > >> inspection and the next steps of ICA etc. > >> > >> Is there any problems with this strategy? > >> > >> Thanks in advance for any advice, > >> > >> Robin > >> _______________________________________________ > >> fieldtrip mailing list > >> fieldtrip at donders.ru.nl > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > > > > -- > > Jörn M. Horschig > > PhD Student > > Donders Institute for Brain, Cognition and Behaviour > > Centre for Cognitive Neuroimaging > > Radboud University Nijmegen > > Neuronal Oscillations Group > > FieldTrip Development Team > > > > P.O. Box 9101 > > NL-6500 HB Nijmegen > > The Netherlands > > > > Contact: > > E-Mail: jm.horschig at donders.ru.nl > > Tel: +31-(0)24-36-68493 > > Web: http://www.ru.nl/donders > > > > Visiting address: > > Trigon, room 2.30 > > Kapittelweg 29 > > NL-6525 EN Nijmegen > > The Netherlands > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From robince at gmail.com Wed Feb 6 15:26:01 2013 From: robince at gmail.com (Robin) Date: Wed, 6 Feb 2013 14:26:01 +0000 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: Hi Stephen, Thanks very much - I think I get it now. Combined with a f_redefinetrial at the end to cut back just the bit I want it seems to work well. In fact it is working so well that almost all my trials are rejected :) but I think that is another problem! Cheers Robin On Wed, Feb 6, 2013 at 2:17 PM, Stephen Whitmarsh wrote: > Dear Robin, > > Please allow me to refer you to the excellent documentation on (negative) > padding and artifact rejection in this gorgeous didactical masterpiece, a > joy to behold: > ***** http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection > ***** > > ;-) > Stephen > > > On 6 February 2013 15:07, Robin wrote: >> >> Hi Jörn, >> >> Thanks very much. Yes I think that will solve the problem - I hadn't >> realised I could use negative trial padding values. >> What I had just got working was as similar approach extracting larger >> trials at first and then manually making a new trl defintion: >> >> % artifact detection >> tmpcfg = []; >> tmpcfg.continuous = 'no'; % some trials are excluded >> tmpcfg.trl = run_clean.sampleinfo; >> tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + >> round(filterpad*run_clean.fsample); >> tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - >> round(filterpad*run_clean.fsample); >> >> [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); >> >> which seemed to work but the trlpadding option definitely looks cleaner! >> >> Thanks, >> >> Robin >> >> On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" >> wrote: >> > Hi Robin, >> > >> > I think the steps you suggested sound reasonable, but I do not see how >> > you >> > are avoiding the filter artifact issue there, you just postpone it to a >> > later stage. Instead it might be a smart way to 'pad' your trials when >> > defining them with 1s pre- and post (so cut out more than you need); >> > that >> > way all filter artifacts will be in that 1s that you are not interested >> > in >> > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling >> > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I >> > understand your question correctly, that solves your problem, doesn't >> > it? >> > >> > Best, >> > Jörn >> > >> > >> > >> > On 2/6/2013 12:54 PM, Robin wrote: >> >> >> >> Hi all, >> >> >> >> I am a new fieldtrip user getting started preprocessing a large MEG >> >> data set (I am in Glasgow and the data was collected at CCNi). >> >> >> >> I think I am slowly getting to grips with all the steps necessary, but >> >> I have a question about the artifact rejection. >> >> >> >> My undersanding is that the denoise procedure helps correct external >> >> sources of noise, so having the signal cleaned in this way should help >> >> detect the biological artifacts which are valid magnetic signal at the >> >> scalp. But I can't see an easy way to do this since the ft_artifact_* >> >> functions want to load the raw continuous data from disk. I can get >> >> them to act on the in memory trials data if I set the padding options >> >> to 0, but then I get an unacceptable amount of rejections (I guess >> >> because of the filter artifacts the padding usually prevents). >> >> >> >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. on the >> >> denoised signal from ft_denoise_pca and if so how? >> >> >> >> At the moment I am performing the following steps: >> >> >> >> Load each run >> >> Detect jumps with ft_artifact_jump. >> >> Concatenate the jump-free trials from all runs together for this block. >> >> >> >> Visually inspect the reference channels and remove high variance >> >> trials (across the whole block). >> >> Compute denoise PCA weights using only good reference data (and no MEG >> >> jump) trials across the whole block. >> >> >> >> I would now like to apply the denoise PCA weights, perform other >> >> automatic artifact removal on the cleaned data, before further visual >> >> inspection and the next steps of ICA etc. >> >> >> >> Is there any problems with this strategy? >> >> >> >> Thanks in advance for any advice, >> >> >> >> Robin >> >> _______________________________________________ >> >> fieldtrip mailing list >> >> fieldtrip at donders.ru.nl >> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > >> > >> > >> > -- >> > Jörn M. Horschig >> > PhD Student >> > Donders Institute for Brain, Cognition and Behaviour >> > Centre for Cognitive Neuroimaging >> > Radboud University Nijmegen >> > Neuronal Oscillations Group >> > FieldTrip Development Team >> > >> > P.O. Box 9101 >> > NL-6500 HB Nijmegen >> > The Netherlands >> > >> > Contact: >> > E-Mail: jm.horschig at donders.ru.nl >> > Tel: +31-(0)24-36-68493 >> > Web: http://www.ru.nl/donders >> > >> > Visiting address: >> > Trigon, room 2.30 >> > Kapittelweg 29 >> > NL-6525 EN Nijmegen >> > The Netherlands >> > >> > _______________________________________________ >> > fieldtrip mailing list >> > fieldtrip at donders.ru.nl >> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From jm.horschig at donders.ru.nl Wed Feb 6 15:38:59 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Wed, 06 Feb 2013 15:38:59 +0100 Subject: [FieldTrip] automatic artifact detection and ft_denoise_pca In-Reply-To: References: <5112625B.9090504@donders.ru.nl> Message-ID: <51126B03.3030106@donders.ru.nl> only a brilliant mind might have created such a guide - chapeau ^^ On 2/6/2013 3:17 PM, Stephen Whitmarsh wrote: > Dear Robin, > > Please allow me to refer you to the excellent documentation on > (negative) padding and artifact rejection in this gorgeous didactical > masterpiece, a joy to behold: > ***** > http://fieldtrip.fcdonders.nl/tutorial/automatic_artifact_rejection ***** > > ;-) > Stephen > > On 6 February 2013 15:07, Robin > wrote: > > Hi Jörn, > > Thanks very much. Yes I think that will solve the problem - I hadn't > realised I could use negative trial padding values. > What I had just got working was as similar approach extracting larger > trials at first and then manually making a new trl defintion: > > % artifact detection > tmpcfg = []; > tmpcfg.continuous = 'no'; % some trials are excluded > tmpcfg.trl = run_clean.sampleinfo; > tmpcfg.trl(:,1) = tmpcfg.trl(:,1) + > round(filterpad*run_clean.fsample); > tmpcfg.trl(:,2) = tmpcfg.trl(:,2) - > round(filterpad*run_clean.fsample); > > [tmpcfg, artifact] = ft_artifact_muscle(tmpcfg, run_clean); > > which seemed to work but the trlpadding option definitely looks > cleaner! > > Thanks, > > Robin > > On Wed, Feb 6, 2013 at 2:02 PM, "Jörn M. Horschig" > > wrote: > > Hi Robin, > > > > I think the steps you suggested sound reasonable, but I do not > see how you > > are avoiding the filter artifact issue there, you just postpone > it to a > > later stage. Instead it might be a smart way to 'pad' your > trials when > > defining them with 1s pre- and post (so cut out more than you > need); that > > way all filter artifacts will be in that 1s that you are not > interested in > > anyway. Then, you can define cfg.xxx.trlpadding =-1 prior to calling > > ft_artifact_xxx (thereby ignoring that 1s of 'padded' data). If I > > understand your question correctly, that solves your problem, > doesn't it? > > > > Best, > > Jörn > > > > > > > > On 2/6/2013 12:54 PM, Robin wrote: > >> > >> Hi all, > >> > >> I am a new fieldtrip user getting started preprocessing a large MEG > >> data set (I am in Glasgow and the data was collected at CCNi). > >> > >> I think I am slowly getting to grips with all the steps > necessary, but > >> I have a question about the artifact rejection. > >> > >> My undersanding is that the denoise procedure helps correct > external > >> sources of noise, so having the signal cleaned in this way > should help > >> detect the biological artifacts which are valid magnetic signal > at the > >> scalp. But I can't see an easy way to do this since the > ft_artifact_* > >> functions want to load the raw continuous data from disk. I can get > >> them to act on the in memory trials data if I set the padding > options > >> to 0, but then I get an unacceptable amount of rejections (I guess > >> because of the filter artifacts the padding usually prevents). > >> > >> Is it possible to run ft_artifact_muscle, ft_artifact_eog etc. > on the > >> denoised signal from ft_denoise_pca and if so how? > >> > >> At the moment I am performing the following steps: > >> > >> Load each run > >> Detect jumps with ft_artifact_jump. > >> Concatenate the jump-free trials from all runs together for > this block. > >> > >> Visually inspect the reference channels and remove high variance > >> trials (across the whole block). > >> Compute denoise PCA weights using only good reference data (and > no MEG > >> jump) trials across the whole block. > >> > >> I would now like to apply the denoise PCA weights, perform other > >> automatic artifact removal on the cleaned data, before further > visual > >> inspection and the next steps of ICA etc. > >> > >> Is there any problems with this strategy? > >> > >> Thanks in advance for any advice, > >> > >> Robin > >> _______________________________________________ > >> fieldtrip mailing list > >> fieldtrip at donders.ru.nl > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > > > > -- > > Jörn M. Horschig > > PhD Student > > Donders Institute for Brain, Cognition and Behaviour > > Centre for Cognitive Neuroimaging > > Radboud University Nijmegen > > Neuronal Oscillations Group > > FieldTrip Development Team > > > > P.O. Box 9101 > > NL-6500 HB Nijmegen > > The Netherlands > > > > Contact: > > E-Mail: jm.horschig at donders.ru.nl > > Tel: +31-(0)24-36-68493 > > Web: http://www.ru.nl/donders > > > > Visiting address: > > Trigon, room 2.30 > > Kapittelweg 29 > > NL-6525 EN Nijmegen > > The Netherlands > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Wed Feb 6 21:59:16 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Wed, 6 Feb 2013 20:59:16 +0000 Subject: [FieldTrip] localspheres In-Reply-To: References: Message-ID: Thank you so much - I downloaded the newest version of FieldTrip, and it works as expected. I was using one from early in January. To answer some of your questions... When I ran ft_prepare_headmodel with a singleshell method, I used the process described here: http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg?s[]=singleshell cfg=[];cfg.method='singleshell'; vol=ft_prepare_headmodel(cfg,segmentedmri); I have one follow-up question - - I'd like to visualize the results. According to the fieldtrip faq: http://fieldtrip.fcdonders.nl/faq/how_can_i_visualize_the_different_geometrical_objects_that_are_needed_for_forward_and_inverse_computations "The low level plotting functions do not support the multisphere volume conductor models." But the deprecated function doesn't seem to work... I have some other questions regarding coercing my nifti format MRI into the correct coordinate system, but I'll save those for another post. Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From evaladez at psych.udel.edu Wed Feb 6 23:38:06 2013 From: evaladez at psych.udel.edu (Emilio Valadez) Date: Wed, 6 Feb 2013 17:38:06 -0500 Subject: [FieldTrip] Reading events from an EDF file Message-ID: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> Dear FieldTrip users, I am trying to define trials from a continuous EEG data set that was exported from BESA to .edf format, but I'm having trouble reading the events with FieldTrip. The events are located in a separate channel that was appended to the EEG data. After running ft_definetrial with cfg.trialdef.eventtype set to '?' (in order to see the event types and event values in the data), I received the following output: the following events were found in the datafile event type: 'trial' with event values: no trials have been defined yet, see FT_DEFINETRIAL for further help found 720 events created 0 trials the call to "ft_definetrial" took 1 seconds It seems that ft_definetrial is not reading any events except for trials, which should not be present in the data. As a comparison, I opened the data set with eeglab, which did read the events properly, leading me to believe that the event information is in fact part of the file. How can I get ft_definetrial to correctly read the events? Thanks in advance for your help. Emilio -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 7 00:33:42 2013 From: frank.ye.mei at gmail.com (Frank Mei) Date: Wed, 6 Feb 2013 18:33:42 -0500 Subject: [FieldTrip] need example code - activity of condition 1 contrasted with condition 2. Message-ID: Hi All, The tutorial here (http://fieldtrip.fcdonders.nl/tutorial/beamformer) provides example of activity contrasted with baseline, but not activity of condition 1 contrasted with condition 2. Could someone kindly give some example code that contrasts two activities, for example left vs right button pressing? I am thinking about modifying the example code in the tutorial, by turn the code ------- sourceDiff = sourcePost_con; sourceDiff.avg.pow = (sourcePost_con.avg.pow - sourcePre_con.avg.pow) ./ sourcePre_con.avg.pow; -------- into A: -------- sourceDiff = sourceLeft_con; sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) ./ sourceRight_con.avg.pow; -------- or into B: -------- sourceDiff = sourceRight_con; sourceDiff.avg.pow = (sourceRight_con.avg.pow - sourceLeft_con.avg.pow) ./ sourceLeft_con.avg.pow; -------- Not sure if I should use "A" or "B", or something else. thanks, Frank -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at donders.ru.nl Thu Feb 7 08:35:30 2013 From: johanna.zumer at donders.ru.nl (Johanna Zumer) Date: Thu, 7 Feb 2013 08:35:30 +0100 Subject: [FieldTrip] need example code - activity of condition 1 contrasted with condition 2. In-Reply-To: References: Message-ID: Dear Frank, You're on the right way of thinking. I think the answer partially depends on your hypothesis. In the tutorial situation of a Post and Pre, there is the hypothesis that nothing of interest is going on in Pre, and that the experimental manipulation is causing something to occur in Post, and the researcher is asking how Post differs from Pre. In your case of Left and Right, if you are assuming that these are equally interesting experimental manipulations (i.e. neither is the 'baseline' condition), then often the denominator is formed by the average of the two conditions: sourceDiff = sourceLeft_con; % or sourceRight_con, does not matter sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) ./ (0.5* sourceLeft_con.avg.pow +0.5* sourceRight_con.avg.pow); Cheers, Johanna 2013/2/7 Frank Mei > Hi All, > > The tutorial here (http://fieldtrip.fcdonders.nl/tutorial/beamformer) > provides example of activity contrasted with baseline, but not activity of > condition 1 contrasted with condition 2. > > Could someone kindly give some example code that contrasts two activities, > for example left vs right button pressing? > > I am thinking about modifying the example code in the tutorial, by turn > the code > ------- > sourceDiff = sourcePost_con; > sourceDiff.avg.pow = (sourcePost_con.avg.pow - sourcePre_con.avg.pow) ./ > sourcePre_con.avg.pow; > -------- > into A: > -------- > sourceDiff = sourceLeft_con; > sourceDiff.avg.pow = (sourceLeft_con.avg.pow - sourceRight_con.avg.pow) > ./ sourceRight_con.avg.pow; > -------- > > or into B: > -------- > sourceDiff = sourceRight_con; > sourceDiff.avg.pow = (sourceRight_con.avg.pow - sourceLeft_con.avg.pow) > ./ sourceLeft_con.avg.pow; > -------- > > Not sure if I should use "A" or "B", or something else. > > thanks, > Frank > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From patrick.jung at esi-frankfurt.de Fri Feb 8 12:06:07 2013 From: patrick.jung at esi-frankfurt.de (Jung, Patrick) Date: Fri, 8 Feb 2013 11:06:07 +0000 Subject: [FieldTrip] ft_freqgrandaverage Message-ID: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> Hi Fieldtrippers, To get a feeling of my data I want to visually inspect the data and look where are differences between the conditions by plotting the grand-averages of TFRs. By using ft_freqgrandaverage I noticed that it gives back NaN if freq entries for one time bin are missing for one subject (n=28). [cid:image003.jpg at 01CE05F4.DAF32510] 1. sSTOP, 2. cAC, 3. diff In my data with variable trial lengths, the shortest poststim time point is around 0.06 s in one condition (cAC) and in one subject but I expect my effects around 0.1-0.35 s. How can I overcome this problem? Is there a more appropriate fieldtrip function or do I have to write a special self-made Matlab code? Here is an excerpt of my code: GA_sSTOP = ft_freqgrandaverage(cfg, AllSubjMat_sSTOP{1,:}); % where AllSubjMat_sSTOP contains TFRs of all subjects in a <1x28 cell> GA_cAC = ft_freqgrandaverage(cfg, AllSubjMat_cAC{1,:}); GA_diff.powspctrm = (GA_sSTOP.powspctrm - GA_cAC.powspctrm) ./ (0.5*GA_sSTOP.powspctrm + 0.5*GA_cAC.powspctrm); Many thanks for your help! Cheers, Patrick -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image003.jpg Type: image/jpeg Size: 11890 bytes Desc: image003.jpg URL: From jm.horschig at donders.ru.nl Fri Feb 8 12:37:58 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 08 Feb 2013 12:37:58 +0100 Subject: [FieldTrip] ft_freqgrandaverage In-Reply-To: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> References: <36E953F5321EB743AC6B338995A56D6304A9C84C@UM-EXCDAG-A01.um.gwdg.de> Message-ID: <5114E396.5050605@donders.ru.nl> Hi Patrick, I think you have to write this yourself. I never tried though, so maybe there is a way. It's a tricky thing to what you want, so I guess that's why it is not implemented. If you average for some time bins over less repetitions than for others, you get a weaker noise estimate, thereby any effects found or not found could be attributed to plain noise. Put in another way, depending on what analysis you are doing, you might get into trouble with your statistics because of different degrees of freedom per time bin. Also note that for frequency data, power has only positive values with a lower bound of zero, thus noise can only increase the power estimate and not cancel out (so more noise = more power), thus a difference in a later time bin between conditions might be explained by having lower df (fewer observations, more noise) in one condition than in the other, especially if power is greater in the condition with fewer observation. I would strongly suggest to throw out trials which do not reach your time of interest and process only these (i.e. throw out that one subject) unless you really know what you are doing. On the other hand as already mentioned, I never tried and never did this, so maybe there is some neat way to achieve what you want (you'd be probably notice, cause people would reply to this response rather fast). Best, Jörn On 2/8/2013 12:06 PM, Jung, Patrick wrote: > > Hi Fieldtrippers, > > To get a feeling of my data I want to visually inspect the data and > look where are differences between the conditions > > by plotting the grand-averages of TFRs. > > By using *ft_freqgrandaverage*I noticed that it gives back *NaN* > > if freq entries for one time bin are missing for one subject (n=28). > > 1.sSTOP, 2. cAC, 3. diff > > In my data with variable trial lengths, the shortest poststim time > point is around 0.06 s in one condition (cAC) and in one subject > > but I expect my effects around 0.1-0.35 s. > > How can I overcome this problem? Is there a more appropriate fieldtrip > function or do I have to write a special self-made Matlab code? > > Here is an excerpt of my code: > > GA_sSTOP = ft_freqgrandaverage(cfg, AllSubjMat_sSTOP{1,:}); > > % where AllSubjMat_sSTOP contains TFRs of all subjects in a <1x28 cell> > > GA_cAC = ft_freqgrandaverage(cfg, AllSubjMat_cAC{1,:}); > > GA_diff.powspctrm = (GA_sSTOP.powspctrm - GA_cAC.powspctrm) ./ > (0.5*GA_sSTOP.powspctrm + 0.5*GA_cAC.powspctrm); > > Many thanks for your help! > > Cheers, > > Patrick > > ** > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: not available Type: image/jpeg Size: 11890 bytes Desc: not available URL: From robince at gmail.com Fri Feb 8 12:52:09 2013 From: robince at gmail.com (Robin) Date: Fri, 8 Feb 2013 11:52:09 +0000 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? Message-ID: Hello, Having got through the preprocessing I am now investigating source reconstruction. The information on the web site is very useful. This tutorial page: http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed Spatio-temporal EEG/MEG Inverse Solver which looks interesting but I wondered if this method was actually implemented in fieldtrip (or elsewhere). When I look in minimumnormestimate.m this reference is not listed as one of the methods implemented. Is it available as a different named method? Thanks for any help. Robin From Andrew.Dykstra at med.uni-heidelberg.de Fri Feb 8 13:32:42 2013 From: Andrew.Dykstra at med.uni-heidelberg.de (Andrew R. Dykstra) Date: Fri, 8 Feb 2013 13:32:42 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: Message-ID: Hi Robin, The MNE Python package implements mixed L1/L2 norm solutions. Not sure if something similar exists in Fieldtrip. Cheers, Andy On Feb 8, 2013 1:12 PM, "Robin" wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 13:51:31 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 13:51:31 +0100 Subject: [FieldTrip] Reading events from an EDF file In-Reply-To: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> References: <10DBEA48DAE8BB4F8F588B1254C0D92E01428C23AD57@razor.psych.udel.edu> Message-ID: <43B67570-A429-4C0B-B936-FCE3B96CF778@donders.ru.nl> Dear Emilio EDF is a fileformat that is widely supported, but that does not have a standard way of storing events in the file. Hence FieldTrip cannot find them. The later EDF+ extension to the fileformat describes how to store annotations (like events) in the file, but this "annotation channel" is not used by many software packages as it is rather clumsy for storing trigger information. Consequently, most software packages have their own ways of storing events. Usually it is dealt with in a very similar manner by adding a binary channel with the same sampling rate and with 0 if there is no, and another value if there is a trigger. The EDF format is written in (short) segments, those are the trials you see in the event structure. If there is a trigger, status, or event channel, you'll have to detect that yourself (e.f. using ft_databrowser). Subsequently you can make a custom "trial function", i.e. a function that reads that channel and defines the data segments to your requirements. Have a look at http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition and http://fieldtrip.fcdonders.nl/tag/trialfun?do=showtag&tag=trialfun best regards, Robert On 6 Feb 2013, at 23:38, Emilio Valadez wrote: > Dear FieldTrip users, > > I am trying to define trials from a continuous EEG data set that was exported from BESA to .edf format, but I’m having trouble reading the events with FieldTrip. The events are located in a separate channel that was appended to the EEG data. > > After running ft_definetrial with cfg.trialdef.eventtype set to ‘?’ (in order to see the event types and event values in the data), I received the following output: > > the following events were found in the datafile > event type: 'trial' with event values: > no trials have been defined yet, see FT_DEFINETRIAL for further help > found 720 events > created 0 trials > the call to "ft_definetrial" took 1 seconds > > It seems that ft_definetrial is not reading any events except for trials, which should not be present in the data. As a comparison, I opened the data set with eeglab, which did read the events properly, leading me to believe that the event information is in fact part of the file. How can I get ft_definetrial to correctly read the events? > > Thanks in advance for your help. > > Emilio > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 13:53:37 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 13:53:37 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: Message-ID: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Hi Robin, The FieldTrip cfg.method='mne' in FT_SOURCEANALYSIS implements an L2 solver, but not an L1 solver. The actual code with more details is in fieldtrip/inverse/minimumnormestimate., best regards, Robert On 8 Feb 2013, at 13:32, Andrew R. Dykstra wrote: > Hi Robin, > > The MNE Python package implements mixed L1/L2 norm solutions. Not sure if something similar exists in Fieldtrip. > > Cheers, > Andy > > On Feb 8, 2013 1:12 PM, "Robin" wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 14:04:07 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 14:04:07 +0100 Subject: [FieldTrip] GE MRI platform 12.0 scans don't import into CTF MRIViewer In-Reply-To: References: Message-ID: <182EAA41-16F5-448D-BFDF-9252C99A6443@donders.ru.nl> Hi Inna, You could try ft_read_mri with as input one of the files that comprises the volume. I never tested it with GE, but for Siemens it is able to figure out the other file names and put the slices in the correct order. The ft_read_mri uses the MATLAB dicom reader for each slice and puts them in a volume. Subsequently you would do ft_volumerealign to assign the head coordinate system, potentially followed by ft_volumereslice. See http://fieldtrip.fcdonders.nl/faq/how_can_i_convert_an_anatomical_mri_from_dicom_into_ctf_format http://fieldtrip.fcdonders.nl/faq/why_does_my_anatomical_mri_show_upside-down_when_plotting_it_with_ft_sourceplot http://fieldtrip.fcdonders.nl/tag/coordinate?do=showtag&tag=coordinate best Robert On 28 Jan 2013, at 17:55, McGowin, Inna wrote: > Hello, > > We have an MRI research scan, GE MRI platform 12.0, that produces scans with some DICOM header fields missing. > These fields are required in order to import the scan into CTF MRIViewer or DICOM_Viewer or some other software. > Does anybody know if these missing fields can be somehow added to the DICOM header? Maybe in Matlab or through some conversion method? > > Thanks! > -- > Inna > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From r.oostenveld at donders.ru.nl Fri Feb 8 14:36:53 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 14:36:53 +0100 Subject: [FieldTrip] Combined EEG and MEG source reconstruction In-Reply-To: References: Message-ID: <8FB714F5-02E8-4B44-96C3-E8472120AD4F@donders.ru.nl> Dear Mushfa In principle it can be made to work, but you'll have to do a little bit of work outside fieldtrip. You would start with 1) ft_prepare_headmodel and ft_prepare_leadfield for the MEG part 2) ft_prepare_headmodel and ft_prepare_leadfield for the EEG part Subsequently you would (manually) concatenate the leadfields of the MEG and EEG. Here you have to make sure that the channel order is consistent with that in your combined data. The resulting structure with combined leadfields can be passed into ft_sourceanalysis as cfg.grid. However, I foresee a problem with the scaling. At this moment FieldTrip is not (yet) very precise in maintaining the correct units throughout. Consequently you might get different units for the EEG and MEG contribution to each dipole, causing weird cancelation effects. You'll just have to check carefully that the leadfield units and the data units consistently scaled between megmag, megplanar and eeg. This brings me to another known problem for the combined vectorview magnetometer and planar gradiometer channels: at this moment the forward computation computes both in T (or fT), whereas the data is represented as T for the magnetometers and T/m for the gradiometers. So the gradiometer leadfields are off by a factor "1/baseline", which is approximately 1/70 if I recall correctly. Many neuromag users use only the planar channels, and therefore don't notice. We are working on fixing the neuromag channel/gradiometer units. That is not as simple as it appears, because conversions of the geometrical dimensions from m to cm or mm also affect the gradiometer baseline. So converting the data from m to mm should result in the planar channel data getting 1000 times smaller, whereas the magnetometer channels shoudl stay the same. See http://bugzilla.fcdonders.nl/show_bug.cgi?id=963 and http://bugzilla.fcdonders.nl/show_bug.cgi?id=963 if you want to follow this. best regards Robert On 28 Jan 2013, at 20:20, Mushfa Yousuf wrote: > Hello Fieldtrippers, > > I am currently doing source analysis using beamformer method in fieldtrip. > The data i work on is a simultaneous measurement of MEG (306) with EEG > (128) on PD patients. > > I was successful in calculating the sources for both the modalities alone. > > I tried according the tutorial "Combined EEG and MEG source reconstruction" and was successful till the estimation > of the lead field. But, then when i want to use the created vol for the > source analysis i have two structures one for EEG and the second one for > MEG. Now, i can only define only one to estimate the sources. How to use > this for both the modalities? Any help would be appreciated. > > With regards > Mushfa > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From alexandre.gramfort at inria.fr Fri Feb 8 14:42:14 2013 From: alexandre.gramfort at inria.fr (Alexandre Gramfort) Date: Fri, 8 Feb 2013 14:42:14 +0100 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> References: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Message-ID: Hi Robin, the solver for inverse problem with L1/L2 prior as described in: A Distributed Spatio-temporal EEG/MEG Inverse Solver is not really tractable on real data. My recent work [1] explains how to solve it more efficiently in a few seconds. [1] http://www.ncbi.nlm.nih.gov/pubmed/22421459 This is what I implemented in mne-python: http://martinos.org/mne/auto_examples/inverse/plot_mixed_norm_L21_inverse.html#example-inverse-plot-mixed-norm-l21-inverse-py I have matlab code too but it's less optimized in terms of speed. If you feel like porting it into Fieldtrip that would be much appreciated. See this page that deserves some updates: http://embal.gforge.inria.fr/ If you're into these methods I invite you to have a look at the next improvement using Time-Frequency transforms: http://www.ncbi.nlm.nih.gov/pubmed/23291276 with demo code: http://martinos.org/mne/auto_examples/inverse/plot_time_frequency_mixed_norm_inverse.html#example-inverse-plot-time-frequency-mixed-norm-inverse-py This contribution explains how to correct for amplitude bias and take care of loose orientation constraints when working with cortical source spaces. Best, Alex PS : sorry Robert for advertising mne on the fieldtrip mailing list ... -- Alexandre Gramfort, PhD Assistant Professor, TSI, Telecom ParisTech, CNRS LTCI 37-39 Rue Dareau, 75014 Paris, France http://alexandre.gramfort.net alexandre.gramfort at telecom-paristech.fr On Fri, Feb 8, 2013 at 12:52 PM, Robin wrote: > Hello, > > Having got through the preprocessing I am now investigating source > reconstruction. > > The information on the web site is very useful. This tutorial page: > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate > > Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed > Spatio-temporal EEG/MEG Inverse Solver > > which looks interesting but I wondered if this method was actually > implemented in fieldtrip (or elsewhere). When I look in > minimumnormestimate.m this reference is not listed as one of the > methods implemented. Is it available as a different named method? > > Thanks for any help. > > Robin > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the e-mail > contains patient information, please contact the Partners Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in error > but does not contain patient information, please contact the sender and properly > dispose of the e-mail. > From nugenta at mail.nih.gov Fri Feb 8 17:35:59 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 8 Feb 2013 16:35:59 +0000 Subject: [FieldTrip] headmodels Message-ID: Hello, I have more simple questions, this time about headmodels. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Fri Feb 8 22:37:47 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 8 Feb 2013 22:37:47 +0100 Subject: [FieldTrip] MEG toolkit course in Nijmegen - registration is open Message-ID: On April 8-11, 2013 we will host the "Toolkit of Cognitive Neuroscience: advanced data analysis and source modelling of EEG and MEG data" at the Donders Institute in Nijmegen. This 4-day toolkit course will teach you advanced MEG and EEG data analysis skills. Preprocessing, frequency analysis, source reconstruction and various statistical methods will be covered. The toolkit will consist of a number of lectures, followed by hands-on sessions in which you will be tutored through the complete analysis of a MEG data set using the FieldTrip toolbox. There will be time to ask questions and discuss analysis methods pertaining to your reseach questions. In the last hands-on session you will get started with the analysis on the data that you will bring yourself The registration for this toolkit course is now open and can be found on http://www.ru.nl/donders/course-information/2013courses/toolkit-cognitive-4/ The fee for senior participants is € 400. The (PhD) student fee is € 200. Registration fee includes coffee/tea, Dutch sandwich lunches and one dinner. Please note that in the past years the course was oversubscribed and we expect that as well for this year. We will be able to host approximately 40 participants and consequently we are likely to be required to make a selection that is based on the information that you provide on the registration form. Note that neither being a very novice or a very expert in EEG/MEG automatically disqualifies you from participating. We select the participants on basis of their motivation, research background and skills, and whether we expect the course to pay off for the participant (i.e. whether there is a match between course content and the expectations and requirements for fruitfull use of the analysis methods that we'll cover). Furthermore, we try to make a nice group of participants with a homogenous level and with sufficient broad coverage of research interests. The deadline for the initial registration is March 1, 2013. You can have a look at our Facebook page on http://www.facebook.com/fieldtriptoolbox to get an impression from the previous "MEG/EEG toolkit course" in May 2012. Best regards, Robert Oostenveld and Jan-Mathijs Schoffelen From robince at gmail.com Mon Feb 11 12:37:30 2013 From: robince at gmail.com (Robin) Date: Mon, 11 Feb 2013 11:37:30 +0000 Subject: [FieldTrip] l1l2 norm inverse solver in fieldtrip? In-Reply-To: References: <914E8D0A-69C9-42B7-AE9C-9B2A2EC4E927@donders.ru.nl> Message-ID: Hi Alexander, Thanks very much for the pointers. I am completely new to the area and was looking at that paper only because it was linked in the Fieldtrip tutorial which I thought would be a good place to start! I will definitely check out all the other useful information you provided. Thanks again, Robin On Fri, Feb 8, 2013 at 1:42 PM, Alexandre Gramfort wrote: > Hi Robin, > > the solver for inverse problem with L1/L2 prior as described in: > > A Distributed Spatio-temporal EEG/MEG Inverse Solver > > is not really tractable on real data. My recent work [1] > explains how to solve it more efficiently in a few seconds. > > [1] http://www.ncbi.nlm.nih.gov/pubmed/22421459 > > This is what I implemented in mne-python: > > http://martinos.org/mne/auto_examples/inverse/plot_mixed_norm_L21_inverse.html#example-inverse-plot-mixed-norm-l21-inverse-py > > I have matlab code too but it's less optimized in terms of speed. If > you feel like porting > it into Fieldtrip that would be much appreciated. See this page that > deserves some updates: > > http://embal.gforge.inria.fr/ > > If you're into these methods I invite you to have a look at the next > improvement using Time-Frequency transforms: > > http://www.ncbi.nlm.nih.gov/pubmed/23291276 > > with demo code: > > http://martinos.org/mne/auto_examples/inverse/plot_time_frequency_mixed_norm_inverse.html#example-inverse-plot-time-frequency-mixed-norm-inverse-py > > This contribution explains how to correct for amplitude bias and take > care of loose orientation constraints when working with cortical > source spaces. > > Best, > Alex > > PS : sorry Robert for advertising mne on the fieldtrip mailing list ... > > -- > Alexandre Gramfort, PhD > Assistant Professor, > TSI, Telecom ParisTech, CNRS LTCI > 37-39 Rue Dareau, 75014 Paris, France > http://alexandre.gramfort.net > alexandre.gramfort at telecom-paristech.fr > > > > > On Fri, Feb 8, 2013 at 12:52 PM, Robin wrote: >> Hello, >> >> Having got through the preprocessing I am now investigating source >> reconstruction. >> >> The information on the web site is very useful. This tutorial page: >> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate >> >> Refers to Ou, W., Hamalainen, M., Golland, P., 2008, A Distributed >> Spatio-temporal EEG/MEG Inverse Solver >> >> which looks interesting but I wondered if this method was actually >> implemented in fieldtrip (or elsewhere). When I look in >> minimumnormestimate.m this reference is not listed as one of the >> methods implemented. Is it available as a different named method? >> >> Thanks for any help. >> >> Robin >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> >> >> The information in this e-mail is intended only for the person to whom it is >> addressed. If you believe this e-mail was sent to you in error and the e-mail >> contains patient information, please contact the Partners Compliance HelpLine at >> http://www.partners.org/complianceline . If the e-mail was sent to you in error >> but does not contain patient information, please contact the sender and properly >> dispose of the e-mail. >> > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From polomacnenad at gmail.com Mon Feb 11 17:14:00 2013 From: polomacnenad at gmail.com (Nenad Polomac) Date: Mon, 11 Feb 2013 17:14:00 +0100 Subject: [FieldTrip] problem with ft_singleplotTFR Message-ID: Dear fieldtrip users, I have problem with ft_singleplotTFR. Please have a look on attached image. Has anybody had similar problem? Thank you in advance! Nenad -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: ft_singlplotTFR.jpg Type: image/jpeg Size: 759989 bytes Desc: not available URL: From sophiechen33 at gmail.com Tue Feb 12 11:46:36 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Tue, 12 Feb 2013 11:46:36 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases Message-ID: Dear Fieldtripers I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: *with fieldtrip fieldtrip-20111024 * cfg = []; cfg.name = 'ctf'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path the input is volume data with dimensions [256 256 256] Converting the coordinate system from ctf to spm performing the segmentation on the specified volume segmentedmri = dim: [256 256 256] transform: [4x4 double] coordsys: 'ctf' unit: 'mm' gray: [256x256x256 double] white: [256x256x256 double] csf: [256x256x256 double] cfg: [1x1 struct] *with fieldtrip 'fieldtrip-20121203' * >> cfg = []; cfg.name = 'ctf'; cfg.write = 'no'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 > In ft_defaults at 60 In ft_volumesegment at 130 the input is volume data with dimensions [256 256 256] Converting the coordinate system from ctf to spm Rescaling NIFTI: slope = 0.00342945, intercept = 0 Smoothing by 0 & 8mm.. Coarse Affine Registration.. Fine Affine Registration.. Error using ft_write_mri (line 128) unsupported data format Error in ft_volumesegment (line 274) Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); * and 'fieldtrip-20130210*' cfg = []; cfg.name = 'ctf'; cfg.write = 'no'; cfg.output= { 'tpm' }; segmentedmri = ft_volumesegment(cfg, mri); the input is volume data with dimensions [256 256 256] Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path Converting the coordinate system from ctf to spm Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path Rescaling NIFTI: slope = 0.00342945, intercept = 0 Smoothing by 0 & 8mm.. Coarse Affine Registration.. Fine Affine Registration.. Warning: could not open ctf.img > In fileio\private\warning_once at 116 In fileio\private\filetype_check_header at 54 In ft_filetype at 338 In ft_write_mri at 54 In ft_volumesegment at 282 Error using ft_write_mri (line 128) unsupported data format Error in ft_volumesegment (line 282) Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); Please help... :-) it's not convenient to switch fieldtrip version while running scripts... Thanks a lot! cheers Sophie -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 12 12:07:08 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 12 Feb 2013 12:07:08 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases In-Reply-To: References: Message-ID: <3E0FF981-1B4D-46DF-A999-C64AFCB4AE89@donders.ru.nl> Dear Sophie, What happens if you don't specify cfg.name? It seems that you don't need the output to be written to a file anyway (since you also specify cfg.write = 'no'); Best, Jan-Mathijs On Feb 12, 2013, at 11:46 AM, sophie chen wrote: > Dear Fieldtripers > > I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: > with fieldtrip fieldtrip-20111024 > > cfg = []; > cfg.name = 'ctf'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path > > the input is volume data with dimensions [256 256 256] > Converting the coordinate system from ctf to spm > performing the segmentation on the specified volume > segmentedmri = > dim: [256 256 256] > transform: [4x4 double] > coordsys: 'ctf' > unit: 'mm' > gray: [256x256x256 double] > white: [256x256x256 double] > csf: [256x256x256 double] > cfg: [1x1 struct] > > with fieldtrip 'fieldtrip-20121203' > > >> cfg = []; > cfg.name = 'ctf'; > cfg.write = 'no'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 > > In ft_defaults at 60 > In ft_volumesegment at 130 > the input is volume data with dimensions [256 256 256] > Converting the coordinate system from ctf to spm > Rescaling NIFTI: slope = 0.00342945, intercept = 0 > Smoothing by 0 & 8mm.. > Coarse Affine Registration.. > Fine Affine Registration.. > Error using ft_write_mri (line 128) > unsupported data format > Error in ft_volumesegment (line 274) > Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); > > > and 'fieldtrip-20130210' > > cfg = []; > cfg.name = 'ctf'; > cfg.write = 'no'; > cfg.output= { 'tpm' }; > segmentedmri = ft_volumesegment(cfg, mri); > > the input is volume data with dimensions [256 256 256] > > Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path > > Converting the coordinate system from ctf to spm > > Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path > > Rescaling NIFTI: slope = 0.00342945, intercept = 0 > Smoothing by 0 & 8mm.. > Coarse Affine Registration.. > Fine Affine Registration.. > Warning: could not open ctf.img > > In fileio\private\warning_once at 116 > In fileio\private\filetype_check_header at 54 > In ft_filetype at 338 > In ft_write_mri at 54 > In ft_volumesegment at 282 > Error using ft_write_mri (line 128) > unsupported data format > Error in ft_volumesegment (line 282) > Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); > > Please help... :-) it's not convenient to switch fieldtrip version while running scripts... > Thanks a lot! > > cheers > Sophie > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophiechen33 at gmail.com Tue Feb 12 15:42:48 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Tue, 12 Feb 2013 15:42:48 +0100 Subject: [FieldTrip] reporting errors while calling ft_volumesegment with recent fieldtrip releases In-Reply-To: References: Message-ID: Hi Jan-Mathijs Thanks for you reply, I just figure out where the problem is coming from (and you are totally right about the * cfg.name = 'ctf' :-) *, completely no sens what I wrote... ) So the problem I had (and I also had some problems while using ft_prepare_headmodel) is coming from the ft_defaults.m, the one from more recent release which is not working for me.... (I always run ft_defaults before executing my programs) So I used the one from the 20111024 release Now, everything is working! I also talk to another Fieldtrip user in our lab, and he couldn't run the fieldtrip functions, unless 'adding fieldtrip directory in path with subfolders' which created conflicts with eeglab toolbox... Is there actually a problem with the ft_defaults.m file itself or is it coming from our Matlab version (2012b)? What should we use instead? Thanks! Cheers, Sophie Dear Sophie, What happens if you don't specify cfg.name? It seems that you don't need the output to be written to a file anyway (since you also specify cfg.write = 'no'); Best, Jan-Mathijs On Feb 12, 2013, at 11:46 AM, sophie chen wrote: >* Dear Fieldtripers*>* *>* I am having some errors when running recent fieldtrip releases while calling ft_volumesegment that I don't have with former fieldtrip version, following what I get: *>* with fieldtrip fieldtrip-20111024 *>* *>* cfg = [];*>* cfg.name = 'ctf';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20111024\external\spm8 toolbox to your Matlab path *>* *>* the input is volume data with dimensions [256 256 256]*>* Converting the coordinate system from ctf to spm*>* performing the segmentation on the specified volume*>* segmentedmri = *>* dim: [256 256 256]*>* transform: [4x4 double]*>* coordsys: 'ctf'*>* unit: 'mm'*>* gray: [256x256x256 double]*>* white: [256x256x256 double]*>* csf: [256x256x256 double]*>* cfg: [1x1 struct]*>* *>* with fieldtrip 'fieldtrip-20121203' *>* *>* >> cfg = [];*>* cfg.name = 'ctf';*>* cfg.write = 'no';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* Warning: FieldTrip is not yet on your MATLAB path, adding D:\\SOPHIE\\Software\\fieldtrip-20121203(1)\\fieldtrip-20121203 *>* > In ft_defaults at 60*>* In ft_volumesegment at 130 *>* the input is volume data with dimensions [256 256 256]*>* Converting the coordinate system from ctf to spm*>* Rescaling NIFTI: slope = 0.00342945, intercept = 0*>* Smoothing by 0 & 8mm..*>* Coarse Affine Registration..*>* Fine Affine Registration..*>* Error using ft_write_mri (line 128)*>* unsupported data format*>* Error in ft_volumesegment (line 274)*>* Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); *>* *>* *>* and 'fieldtrip-20130210'*>* *>* cfg = [];*>* cfg.name = 'ctf';*>* cfg.write = 'no';*>* cfg.output= { 'tpm' }; *>* segmentedmri = ft_volumesegment(cfg, mri);*>* *>* the input is volume data with dimensions [256 256 256]*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\spm8 toolbox to your Matlab path *>* *>* Converting the coordinate system from ctf to spm*>* *>* Warning: adding D:\SOPHIE\Software\fieldtrip-20130210\fieldtrip-20130210\external\freesurfer toolbox to your Matlab path *>* *>* Rescaling NIFTI: slope = 0.00342945, intercept = 0*>* Smoothing by 0 & 8mm..*>* Coarse Affine Registration..*>* Fine Affine Registration..*>* Warning: could not open ctf.img *>* > In fileio\private\warning_once at 116*>* In fileio\private\filetype_check_header at 54*>* In ft_filetype at 338*>* In ft_write_mri at 54*>* In ft_volumesegment at 282 *>* Error using ft_write_mri (line 128)*>* unsupported data format*>* Error in ft_volumesegment (line 282)*>* Va = ft_write_mri([cfg.name,'.img'], mri.anatomy, 'transform', mri.transform, 'spmversion', cfg.spmversion); *>* *>* Please help... :-) it's not convenient to switch fieldtrip version while running scripts...*>* Thanks a lot!*>* *>* cheers*>* Sophie*>* _______________________________________________*>* fieldtrip mailing list*>* fieldtrip at donders.ru.nl *>* http://mailman.science.ru.nl/mailman/listinfo/fieldtrip* Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at gmail.com Wed Feb 13 15:05:39 2013 From: cmuehl at gmail.com (Christian Muehl) Date: Wed, 13 Feb 2013 15:05:39 +0100 Subject: [FieldTrip] Call for Papers: 3rd Workshop on Affective Brain-Computer Interfaces at ACII 2013 Message-ID: ** First Call for Papers ** 3rd Workshop on Affective Brain-Computer Interfaces (aBCI) Workshop at ACII 2013 (September 2-5), Geneva, Switzerland, September 2, 2013 http://hmi.ewi.utwente.nl/abci2013 (coming soon) http://www.acii2013.org During the last decade, brain computer interface (BCI) research has developed into a major research field establishing methodological frameworks, guidelines and a core community of established researchers. Besides proving valuable as a communication channel that bypasses impeded muscular pathways, the novel technology also spurred the investigation of applications for able-bodied users, foremost in the fields of entertainment, health and lifestyle. Affective BCI systems allowing users to control computer games, support relaxation training, or trigger your alarm clock during a shallow sleep stage have been proposed, implemented, and sold. Moreover, the affordable hardware and software tools also encouraged artists to play with the idea of a direct access to people’s most private information: their affective and cognitive states. From these explorations followed a number of interesting installations, suggesting novel ways of human-computer as well as human-human interaction: neurotechnology-based systems that encourage affective self-reflection, the synchronization and empathizing between or the competition of different minds, and the collaborative creation and manipulation of digital multimodal content. The third workshop on affective brain-computer interfaces will explore the advantages and limitations of using neuro-physiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in applications for domains like health, arts, and entertainment. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress and their visions, and thus to spur the development of guidelines and frameworks for affective BCI. Topics of interest include, but are not limited to: • emotion elicitation and data collection for affective BCI • detection of affect and mental state via BCI and other modalities • innovative concepts for adaptive interfaces and affective BCI • demos of aBCI systems and artworks Submission Instructions: * The papers should feature original empirical work, theoretical work, or a well defendable but arguable position of the authors. * Papers will be published in the proceedings of ACII 2013 by IEEE. Papers should be limited to 6 + max 2 additional pages (to be charged €100 per page) * Further details about the submission instructions and format will appear on the ACII 2013 website soon. Important Dates: April 20, 2013: Submission of manuscripts May 20, 2013: Acceptance/Rejection notification June 17, 2013: Submission of camera-ready papers and presenting author’s registration September 2, 2013: Date of the Workshop Programme Chairs: * Brendan Allison, University of California, San Diego, USA * Guilliaume Chanel, Swiss Center for Affective Sciences, Geneva, Switzerland, * Christian Mühl, INRIA Bordeaux - Sud-Ouest, France * Anton Nijholt, Universiteit Twente, the Netherlands Programme Committee: * Egon L. van den Broek, TNO Technical Sciences, Delft, the Netherlands * Anne-Marie Brouwer, TNO Perceptual and Cognitive Systems, Soesterberg, the Netherlands * Stephen Fairclough, John Moores University, Liverpool, UK * Didier Grandjean, Swiss Center for Affective Sciences, Geneva, Switzerland * Hayrettin Gürkök, University of Twente, Enschede, the Netherlands * Jonghwa Kim, University of Augsburg, Germany * Brent Lance, Army Research Laboratory/TNB, Aberdeen Proving Ground, USA, * Fabien Lotte, INRIA Bordeaux - Sud-Ouest, France * Winfried Menninghaus, Freie Universität Berlin, Germany * Gary Garcia Molina, Philips Research North America, Briarcliff, USA * Christopher Honey, Princeton University, USA * Olga Sourina, NanYang Technological University, Singapore * Ioannis Patras, Queen Mary University, London, UK * Mannes Poel, University of Twente, Enschede, the Netherlands * Thorsten Zander, Technische Universität Berlin, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: From brungio at gmail.com Wed Feb 13 20:47:36 2013 From: brungio at gmail.com (Bruno L. Giordano) Date: Wed, 13 Feb 2013 19:47:36 +0000 Subject: [FieldTrip] Job: research assistant/associate, University of Glasgow: Lifelong changes in the cerebral processing of social signals Message-ID: <511BEDD8.9030005@gmail.com> Dear list, apologies for cross-postings. RESEARCH ASSISTANT/ASSOCIATE - Ref: 003341 - University of Glasgow - College of Medical, Veterinary and Life Sciences - Institute of Neuroscience and Psychology. Salary: Grade 6 £26,264-£29,541 or Grade 7 £32,267 - £36,298. To contribute to a MRC-funded project entitled “Lifelong changes in the cerebral processing of social signals”. Specifically, the job requires a review of current literature in relevant fields, development of auditory and visual stimuli and experimental procedures, contributing to the design and programming of the behavioral, fMRI and EEG experiments, recruiting and running the participants, assisting in analyzing the results, and participating in the writing up of the results. This post has funding available until 25 March 2014. Apply online at http://www.glasgow.ac.uk/jobs For informal inquiries, please contact Dr Guillaume Rousselet, guillaume.rousselet at glasgow.ac.uk. The University is committed to equality of opportunity in employment. ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Bruno L. Giordano, PhD Institute of Neuroscience and Psychology 58 Hillhead Street, University of Glasgow Glasgow, G12 8QB, Scotland T +44 (0) 141 330 5484 Www: http://www.brunolgiordano.net From marek-b at wp.pl Thu Feb 14 14:14:51 2013 From: marek-b at wp.pl (marek) Date: Thu, 14 Feb 2013 14:14:51 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? Message-ID: Dear all, Is it possible to use ft_topoplotER to draw selected frequency peaks over scalp after FFT analysis? I did frequency analysis of EEG signal in the range 3-42 Hz with the following settings: cfg = []; cfg.output = 'pow'; cfg.channel = 'all'; cfg.method = 'mtmfft'; cfg.taper = 'hanning'; cfg.trials = 'all'; cfg.keeptrials = 'no'; cfg.foilim = [3 42]; fft1 = ft_freqanalysis(cfg, avg1); I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. (I've got _only_ frequency domain data). Is it possible to do it with with the ft_topoplotER function? What settings are needed? I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem to be related to the parameter (the frequency selection) I try to manipulate. Any help will be greatly appreciated! Best, Marek Psychophysiology Laboratory, Jagiellonian University, Krakow (PL) From ploner at lrz.tu-muenchen.de Thu Feb 14 14:26:50 2013 From: ploner at lrz.tu-muenchen.de (Markus Ploner) Date: Thu, 14 Feb 2013 14:26:50 +0100 Subject: [FieldTrip] PhD Student in systems neuroscience/pain research in Munich, Germany Message-ID: Applications are invited for a PhD Student position at the Department of Neurology, Technische Universität München, to work on the cerebral representation of pain by using EEG. The project will focus on theneurophysiological correlates of ongoing pain in healthy human subjects andpatients suffering from chronic pain disorders. Major experimental methods include EEG time-frequency analysis, source analysis and connectivity analysis. The candidate will join a research group dedicated to the multimodal investigation of the cerebral representation of pain (http://www.neurokopfzentrum.med.tum.de/neurologie/426.html) which is part of the TUM-Neuroimaging Center (http://www.tumnic.mri.tum.de ). Applicants should have a background in neuroscience, medicine, psychology, physics, engineering, or other relevantdisciplines. Prior experience in EEG experimental design, data acquisition and analysis as well as time series analysis and MATLAB programming are highly desirable. The position is funded by the Deutsche Forschungsgemeinschaft. Salary will be commensurate with the German TVöD salary scale (EG13, 50%). The position is available for three years. Applications will be considered until the position is filled. Candidates may contact Dr. Markus Ploner for more detailed information or directly e-mail their application (ploner at lrz.tum.de). PD Dr. Markus Ploner Department of Neurology Technische Universität München Munich, Germany ploner at lrz.tum.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From ploner at lrz.tu-muenchen.de Thu Feb 14 14:27:49 2013 From: ploner at lrz.tu-muenchen.de (Markus Ploner) Date: Thu, 14 Feb 2013 14:27:49 +0100 Subject: [FieldTrip] Postdoc in systems neuroscience/pain research in Munich, Germany Message-ID: Applications are invited for a postdoctoral position at the Department of Neurology, Technische Universität München, to work on the cerebral representation of pain by using EEG. The project will focus on theneurophysiological correlates of ongoing pain in healthy human subjects andpatients suffering from chronic pain disorders. Major experimental methods include EEG time-frequency analysis, source analysis and connectivity analysis. The candidate will join a research group dedicated to the multimodal investigation of the cerebral representation of pain (http://www.neurokopfzentrum.med.tum.de/neurologie/426.html) which is part of the TUM-Neuroimaging Center (http://www.tumnic.mri.tum.de ). Applicants should have a PhD or comparable background in neuroscience, medicine, psychology, physics, engineering, or other relevant disciplines. Prior experience in EEG experimental design,data acquisition and analysis is necessary. Advanced skills for time seriesanalysis and MATLAB programming are highly desirable. The position is funded by the Deutsche Forschungsgemeinschaft. Salary will be commensurate with the German TVöD salary scale (EG13). The position is initially available for two years, the secondyear contingent on satisfactory progress. Extension beyond two years may bepossible. Applications will be considered until the position is filled. Candidates may contact Dr. Markus Ploner for more detailed information or directly e-mail their application (ploner at lrz.tum.de). PD Dr. Markus Ploner Department of Neurology Technische Universität München Munich, Germany ploner at lrz.tum.de -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Thu Feb 14 14:59:03 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Thu, 14 Feb 2013 14:59:03 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? In-Reply-To: References: Message-ID: <511CEDA7.5020000@donders.ru.nl> Hi Marek, it should work like this: /cfg = []; cfg.layout = 'XXX.lay'; cfg.xlim = [18 22]; cfg.zlim = 'maxabs'; figure; ft_topoplotER(cfg, fft1);/ Note that /cfg.xlim /needs to be a vector with two elements. Best, Jörn On 2/14/2013 2:14 PM, marek wrote: > Dear all, > > Is it possible to use ft_topoplotER to draw selected frequency peaks > over scalp after FFT analysis? > > I did frequency analysis of EEG signal in the range 3-42 Hz with the > following settings: > cfg = []; > cfg.output = 'pow'; > cfg.channel = 'all'; > cfg.method = 'mtmfft'; > cfg.taper = 'hanning'; > cfg.trials = 'all'; > cfg.keeptrials = 'no'; > cfg.foilim = [3 42]; > fft1 = ft_freqanalysis(cfg, avg1); > > I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. > (I've got _only_ frequency domain data). > > Is it possible to do it with with the ft_topoplotER function? What > settings are needed? > I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem > to be related to the parameter (the frequency selection) I try to > manipulate. > > Any help will be greatly appreciated! > > Best, > Marek > > Psychophysiology Laboratory, > Jagiellonian University, Krakow (PL) > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From cornabel at googlemail.com Thu Feb 14 15:42:14 2013 From: cornabel at googlemail.com (cornelius abel) Date: Thu, 14 Feb 2013 15:42:14 +0100 Subject: [FieldTrip] using ft_topoplotER to plot selected FFT peak amplitudes over scalp? In-Reply-To: <511CEDA7.5020000@donders.ru.nl> References: <511CEDA7.5020000@donders.ru.nl> Message-ID: <511CF7C6.8000605@googlemail.com> If it is not working you might also need to define the parameter as: cfg.parameter='powspctrm' Greetings, Cornelius Am 14.02.2013 14:59, schrieb "Jörn M. Horschig": > Hi Marek, > > it should work like this: > > /cfg = []; > cfg.layout = 'XXX.lay'; > cfg.xlim = [18 22]; > cfg.zlim = 'maxabs'; > figure; > ft_topoplotER(cfg, fft1); / > > Note that /cfg.xlim /needs to be a vector with two elements. > > Best, > Jörn > > > On 2/14/2013 2:14 PM, marek wrote: >> Dear all, >> >> Is it possible to use ft_topoplotER to draw selected frequency peaks >> over scalp after FFT analysis? >> >> I did frequency analysis of EEG signal in the range 3-42 Hz with the >> following settings: >> cfg = []; >> cfg.output = 'pow'; >> cfg.channel = 'all'; >> cfg.method = 'mtmfft'; >> cfg.taper = 'hanning'; >> cfg.trials = 'all'; >> cfg.keeptrials = 'no'; >> cfg.foilim = [3 42]; >> fft1 = ft_freqanalysis(cfg, avg1); >> >> I would like to draw a scalp distribution of FFT peaks for, say 20 Hz. >> (I've got _only_ frequency domain data). >> >> Is it possible to do it with with the ft_topoplotER function? What >> settings are needed? >> I tried it using cfg.ylim nor cfg.xlim parameters but they do not seem >> to be related to the parameter (the frequency selection) I try to >> manipulate. >> >> Any help will be greatly appreciated! >> >> Best, >> Marek >> >> Psychophysiology Laboratory, >> Jagiellonian University, Krakow (PL) >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > -- > Jörn M. Horschig > PhD Student > Donders Institute for Brain, Cognition and Behaviour > Centre for Cognitive Neuroimaging > Radboud University Nijmegen > Neuronal Oscillations Group > FieldTrip Development Team > > P.O. Box 9101 > NL-6500 HB Nijmegen > The Netherlands > > Contact: > E-Mail:jm.horschig at donders.ru.nl > Tel: +31-(0)24-36-68493 > Web:http://www.ru.nl/donders > > Visiting address: > Trigon, room 2.30 > Kapittelweg 29 > NL-6525 EN Nijmegen > The Netherlands > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From ricardoojm at gmail.com Thu Feb 14 16:12:54 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Thu, 14 Feb 2013 16:12:54 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution Message-ID: Dear all, I am very new to fieldtrip and I am experiencing a problem when reading brainvision data. I searched in the mailinglist archives but I didn't find anything that could help me. In case there is information about it somewhere else, I would appreciate if someone can send me a reference. The problem is the following. I am tring to read continuous data from the brainvision analyzer (already preprocessed), but I always have an error which seems to be due to a problem with the identification of the channels resolution. I exported the data from brainvision in ".dat" vectorized format, and I am loading it first with the ft_preprocessing command. Here is the command I am running to load it: cfg = []; cfg.dataset = 'Raw Data Inspection.dat'; eegData = ft_preprocessing(cfg) Then the following warning message is returned, for each of the 56 channels I have in the data: Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > In fileio\private\read_brainvision_vhdr at 50 In ft_read_header at 381 In ft_preprocessing at 394 And at the end, I have the following error: ??? Index exceeds matrix dimensions. Error in ==> read_brainvision_eeg at 150 dat(chan,:) = tmp(begsample:endsample); Error in ==> ft_read_data at 400 dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, chanindx); Error in ==> ft_preprocessing at 573 dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', rawindx, 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', cfg.dataformat) Interestingly, when I read the header file with the "hdr = ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 samples in the data. When checking the header file with the notepad, it says that there are actualy 797740 data points. So, am I realling doing it right? Thank you very much in advance, and best wishes, Ricardo -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at gmail.com Thu Feb 14 17:32:38 2013 From: cmuehl at gmail.com (Christian Muehl) Date: Thu, 14 Feb 2013 17:32:38 +0100 Subject: [FieldTrip] Call for Papers: 3rd Workshop on Affective Brain-Computer Interfaces at ACII 2013 Message-ID: ** Call for Papers ** 3rd Workshop on Affective Brain-Computer Interfaces (aBCI) Workshop at ACII 2013 (September 2-5), Geneva, Switzerland, September 2, 2013 http://hmi.ewi.utwente.nl/abci2013 http://www.acii2013.org During the last decade, brain computer interface (BCI) research has developed into a major research field establishing methodological frameworks, guidelines and a core community of established researchers. Besides proving valuable as a communication channel that bypasses impeded muscular pathways, the novel technology also spurred the investigation of applications for able-bodied users, foremost in the fields of entertainment, health and lifestyle. Affective BCI systems allowing users to control computer games, support relaxation training, or trigger your alarm clock during a shallow sleep stage have been proposed, implemented, and sold. Moreover, the affordable hardware and software tools also encouraged artists to play with the idea of a direct access to people’s most private information: their affective and cognitive states. From these explorations followed a number of interesting installations, suggesting novel ways of human-computer as well as human-human interaction: neurotechnology-based systems that encourage affective self-reflection, the synchronization and empathizing between or the competition of different minds, and the collaborative creation and manipulation of digital multimodal content. The third workshop on affective brain-computer interfaces will explore the advantages and limitations of using neuro-physiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in applications for domains like health, arts, and entertainment. The goal is to bring researchers, artists, and practitioners together to present state-of-the-art progress and their visions, and thus to spur the development of guidelines and frameworks for affective BCI. Topics of interest include, but are not limited to: • emotion elicitation and data collection for affective BCI • detection of affect and mental state via BCI and other modalities • innovative concepts for adaptive interfaces and affective BCI • demos of aBCI systems and artworks Submission Instructions: * The papers should feature original empirical work, theoretical work, or a well defendable but arguable position of the authors. * Papers will be published in the proceedings of ACII 2013 by IEEE. Papers should be limited to 6 pages. * Further details about the submission instructions and format can be found on the website of ACII 2013. * For further information, contact abci at cs.utwente.nl Important Dates: April 20, 2013: Submission of manuscripts May 20, 2013: Acceptance/Rejection notification June 17, 2013: Submission of camera-ready papers and presenting author’s registration September 2, 2013: Date of the Workshop Programme Chairs: * Brendan Allison, University of California, San Diego, USA * Guilliaume Chanel, Swiss Center for Affective Sciences, Geneva, Switzerland, * Christian Mühl, INRIA Bordeaux - Sud-Ouest, France * Anton Nijholt, Universiteit Twente, the Netherlands Programme Committee: * Egon L. van den Broek, TNO Technical Sciences, Delft, the Netherlands * Anne-Marie Brouwer, TNO Perceptual and Cognitive Systems, Soesterberg, the Netherlands * Stephen Fairclough, John Moores University, Liverpool, UK * Didier Grandjean, Swiss Center for Affective Sciences, Geneva, Switzerland * Hayrettin Gürkök, University of Twente, Enschede, the Netherlands * Jonghwa Kim, University of Augsburg, Germany * Brent Lance, Army Research Laboratory/TNB, Aberdeen Proving Ground, USA, * Fabien Lotte, INRIA Bordeaux - Sud-Ouest, France * Winfried Menninghaus, Freie Universität Berlin, Germany * Gary Garcia Molina, Philips Research North America, Briarcliff, USA * Christopher Honey, Princeton University, USA * Olga Sourina, NanYang Technological University, Singapore * Ioannis Patras, Queen Mary University, London, UK * Mannes Poel, University of Twente, Enschede, the Netherlands * Ed Tan, Universiteit van Amsterdam, the Netherlands * Thorsten Zander, Technische Universität Berlin, Germany -------------- next part -------------- An HTML attachment was scrubbed... URL: From Alan.Leggitt at ucsf.edu Fri Feb 15 01:58:32 2013 From: Alan.Leggitt at ucsf.edu (Leggitt, Alan) Date: Fri, 15 Feb 2013 00:58:32 +0000 Subject: [FieldTrip] Support Vector Machine (SVM) for classification of EEG data Message-ID: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> Hello, I'm new to field trip and I am interested in using a support vector machine to classify EEG data. I see that field trip has svm code through the DLMT toolbox. Has anyone had any experience with this and would be willing to share their code for adapting EEG data to use as inputs to the svm class? My current understanding is that others use ICA to extract features to use in the svm. Are there other techniques for feature extraction? Thanks very much. Regards, Alan -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Fri Feb 15 08:04:38 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 15 Feb 2013 08:04:38 +0100 Subject: [FieldTrip] Support Vector Machine (SVM) for classification of EEG data In-Reply-To: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> References: <77E38B660FBC4E4A83CDF1668885F501323AABAF@ex05.net.ucsf.edu> Message-ID: <511DDE06.70101@donders.ru.nl> Dear Alan, you should probably start off with going through our tutorials: http://fieldtrip.fcdonders.nl/tutorial/ And for you especially http://fieldtrip.fcdonders.nl/tutorial/multivariateanalysis There are lots of different approaches for feature extraction or reduce feature space, but what works wors best for your data is something you have to test yourself. When you've read the tutorials you probably got a pretty got overview of what is possible in FieldTrip and that you can easily test what you asked for yourself without having others send you their code (you just have to replace a few keywords from the tutorial to test a different method). If you have more specific questions, feel free to ask again. Best, Jörn On 2/15/2013 1:58 AM, Leggitt, Alan wrote: > Hello, > > I'm new to field trip and I am interested in using a support vector > machine to classify EEG data. I see that field trip has svm code > through the DLMT toolbox. Has anyone had any experience with this and > would be willing to share their code for adapting EEG data to use as > inputs to the svm class? My current understanding is that others use > ICA to extract features to use in the svm. Are there other techniques > for feature extraction? > > Thanks very much. > > Regards, > Alan > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 15 08:50:46 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Fri, 15 Feb 2013 08:50:46 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: <94F3F43D-320E-4E49-9BE2-97B7859C1241@donders.ru.nl> Hi Ricardo, It looks as if there's a discrepancy between what FieldTrip extracts from the header, and what is actually in the data file. Did you try another data file to see whether your problem occurs just in this single example or not? I read brainvision data all the time, and haven't encountered issues so far. If your data file is sufficiently small, you could try to .zip it (both data/header/marker files) and upload it to our bugzilla.fcdonders.nl website. You have to create an account, and then you can 'file a bug', describing the problem (basically just copy and paste what you wrote in your original e-mail), and upload the data. Our team than can have a look at it. Best wishes, Jan-Mathijs On Feb 14, 2013, at 4:12 PM, Ricardo Moura wrote: > Dear all, > > I am very new to fieldtrip and I am experiencing a problem when reading brainvision data. I searched in the mailinglist archives but I didn't find anything that could help me. In case there is information about it somewhere else, I would appreciate if someone can send me a reference. > > The problem is the following. I am tring to read continuous data from the brainvision analyzer (already preprocessed), but I always have an error which seems to be due to a problem with the identification of the channels resolution. I exported the data from brainvision in ".dat" vectorized format, and I am loading it first with the ft_preprocessing command. > > Here is the command I am running to load it: > cfg = []; > cfg.dataset = 'Raw Data Inspection.dat'; > eegData = ft_preprocessing(cfg) > > > Then the following warning message is returned, for each of the 56 channels I have in the data: > Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > > In fileio\private\read_brainvision_vhdr at 50 > In ft_read_header at 381 > In ft_preprocessing at 394 > > > And at the end, I have the following error: > ??? Index exceeds matrix dimensions. > > Error in ==> read_brainvision_eeg at 150 > dat(chan,:) = tmp(begsample:endsample); > > Error in ==> ft_read_data at 400 > dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, chanindx); > > Error in ==> ft_preprocessing at 573 > dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', begsample, 'endsample', endsample, 'chanindx', rawindx, > 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', cfg.dataformat) > > > Interestingly, when I read the header file with the "hdr = ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 samples in the data. When checking the header file with the notepad, it says that there are actualy 797740 data points. > > So, am I realling doing it right? > Thank you very much in advance, and best wishes, > Ricardo > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From ricardoojm at gmail.com Fri Feb 15 11:52:32 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Fri, 15 Feb 2013 11:52:32 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: Hi Jan-Mathijs, Thank you very much for your reply. I found a mistake of mine in the data export. I didn't export it as ".dat" binary file. I was exporting it as text file. Now, the same script I sent in the first email is working in the sense that the program is properly recognizing the samples in the data (the 797740 sampling points, instead of only 80). Nevertheless, I still have a problem with the channel's resolution. I saw that when exporting the binary files as ieee 32-bit floating, the resolution of the channels is not recorded in the header. So I changed it to the "32-bit signed integer" format, and now I have the resolution (in the header, it appears as "Ch1=AF3,NewRef,4.1322874E-08,µV", under "Channel Infos"), but then, another error message is returned: ??? Error using ==> read_brainvision_eeg at 155 unsupported sub-fileformat I tried to export the data in different ways, but the error persists. I am afraid there is something else wrong in the way I am exporting the data. Could you tell me how I must export the data, or just show me where I can find more detailed specifications about it? I searched through the site and mailing list, and haven't find further information about it. Thanks again, Best wishes, Ricardo On 14 February 2013 16:12, Ricardo Moura wrote: > Dear all, > > I am very new to fieldtrip and I am experiencing a problem when reading > brainvision data. I searched in the mailinglist archives but I didn't find > anything that could help me. In case there is information about it > somewhere else, I would appreciate if someone can send me a reference. > > The problem is the following. I am tring to read continuous data from the > brainvision analyzer (already preprocessed), but I always have an error > which seems to be due to a problem with the identification of the channels > resolution. I exported the data from brainvision in ".dat" vectorized > format, and I am loading it first with the ft_preprocessing command. > > Here is the command I am running to load it: > cfg = []; > cfg.dataset = 'Raw Data Inspection.dat'; > eegData = ft_preprocessing(cfg) > > > Then the following warning message is returned, for each of the 56 > channels I have in the data: > Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! > > In fileio\private\read_brainvision_vhdr at 50 > In ft_read_header at 381 > In ft_preprocessing at 394 > > > And at the end, I have the following error: > ??? Index exceeds matrix dimensions. > > Error in ==> read_brainvision_eeg at 150 > dat(chan,:) = tmp(begsample:endsample); > > Error in ==> ft_read_data at 400 > dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, > chanindx); > > Error in ==> ft_preprocessing at 573 > dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', > begsample, 'endsample', endsample, 'chanindx', rawindx, > 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', > cfg.dataformat) > > > Interestingly, when I read the header file with the "hdr = > ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 > samples in the data. When checking the header file with the notepad, it > says that there are actualy 797740 data points. > > So, am I realling doing it right? > Thank you very much in advance, and best wishes, > Ricardo > -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Fri Feb 15 15:51:52 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 15 Feb 2013 14:51:52 +0000 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: Hello, I'm very sorry to repost this, but I'm hoping that someone might be able to give me advice. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI that looks fine. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 15 16:16:52 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Fri, 15 Feb 2013 16:16:52 +0100 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: <13AAF5AE-0977-4C63-B6F8-AE5ED6E6FA7A@donders.ru.nl> Hi Allison, The warning you get is inconsequential and will be fixed soon. Regarding the scale of the data objects, you can use ft_convert_units to get them all in the same scale: hdr.grad = ft_convert_units(hdr.grad); % tries to add a unit field if it does not exist vol = ft_convert_units(vol, hdr.grad.unit); Then you can proceed with the plotting. Best Jan_Mathijs On Feb 15, 2013, at 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: > Hello, I’m very sorry to repost this, but I’m hoping that someone might be able to give me advice. > > I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I’ve scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. > > I’ve imported the MRI like so: > > mri=ft_read_mri(‘ABC_ortho_anat.nii’); > mri=ft_determine_coordsys(mri) > > I re-label the coordinate axes, and set the origin – when it’s done, it has “Neuromag” as the coordsys, although that’s not how it was created. Next: > > cfg=[]; cfg.method=’interactive’ > mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points > cfg=[]; > [segmentedmri]=ft_volumesegment(cfg, mri_realigned) > > During execution I get this warning: > Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img > Even though the file appears to exist – and the program completes and produces a segmented MRI that looks fine. Finally: > > hdr=ft_read_header(‘ACN.ds’); > cfg=[]; cfg.method=’singleshell’; > vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); > figure > ft_plot_vol(vol_realistic);hold on > ft_plot_sens(hdr.grad) > > The plot has the sensor array and the headmodel on different scales – like it didn’t properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I’d ultimately also like to be able to use the localspheres model, and compare results, but since I can’t figure out how to plot that headmodel to check it, I thought I’d start with one that I can plot. > > Thank you! > > Allison Nugent, PhD > MRI Physicist > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph. 301-451-8863 > nugenta at mail.nih.gov > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jm.horschig at donders.ru.nl Fri Feb 15 17:55:51 2013 From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=) Date: Fri, 15 Feb 2013 17:55:51 +0100 Subject: [FieldTrip] headmodels In-Reply-To: References: Message-ID: <511E6897.1060101@donders.ru.nl> Dear Allison, I was encountering similar issues the last two days and hope to have fixed some unit conversion bugs. Thus it might be that with the newest FT version, you don't need to manually convert the units anymore as JM suggested. Could you give it a try for me and see whether it works without JMs manual approach in the newest FT version? Best, Jörn On 2/15/2013 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: > > Hello, I'm very sorry to repost this, but I'm hoping that someone > might be able to give me advice. > > I have an MRI in nifti format. It has already been re-aligned with > the fiducial markers. I've scoured the tutorials, but most seem to > deal with MRIs that are already in the ctf coordinate system. > > I've imported the MRI like so: > > mri=ft_read_mri('ABC_ortho_anat.nii'); > > mri=ft_determine_coordsys(mri) > > I re-label the coordinate axes, and set the origin -- when it's done, > it has "Neuromag" as the coordsys, although that's not how it was > created. Next: > > cfg=[]; cfg.method='interactive' > > mri_realigned=ft_volumerealign(cfg,mri) % > to set the fiducial points > > cfg=[]; > > [segmentedmri]=ft_volumesegment(cfg, mri_realigned) > > During execution I get this warning: > > Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img > > Even though the file appears to exist -- and the program completes and > produces a segmented MRIthat looks fine. Finally: > > hdr=ft_read_header('ACN.ds'); > > cfg=[]; cfg.method='singleshell'; > > vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); > > figure > > ft_plot_vol(vol_realistic);hold on > > ft_plot_sens(hdr.grad) > > The plot has the sensor array and the headmodel on different scales -- > like it didn't properly adjust for the difference in mm and cm, even > though the units are specified in the data structures. I'd > ultimately also like to be able to use the localspheres model, and > compare results, but since I can't figure out how to plot that > headmodel to check it, I thought I'd start with one that I can plot. > > Thank you! > > Allison Nugent, PhD > > MRI Physicist > > Experimental Therapeutics and Pathophysiology Branch > > NIMH/NIH/DHHS > > Ph. 301-451-8863 > > nugenta at mail.nih.gov > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From markus.siegel at uni-tuebingen.de Fri Feb 15 18:17:04 2013 From: markus.siegel at uni-tuebingen.de (Markus Siegel) Date: Fri, 15 Feb 2013 18:17:04 +0100 Subject: [FieldTrip] PhD Position - Centre for Integrative Neuroscience (CIN), Tuebingen, Germany Message-ID: <7E2BFDC3-6406-4067-8E66-915714698B52@uni-tuebingen.de> PhD Position - Centre for Integrative Neuroscience (CIN), Tuebingen The laboratory of Markus Siegel at the Centre for Integrative Neuroscience (CIN), Tuebingen (http://www.cin.uni-tuebingen.de/research/siegel.php) is seeking candidates for a PhD position to study large-scale neuronal interactions in humans. The project will focus on ongoing and task-related neuronal oscillations and interactions in the healthy and diseased human brain. Experimental methods include, MEG, psychophysics, spectral analysis, source-reconstruction techniques, and novel connectivity analyses. The candidate will join a stimulating interdisciplinary team that employs a broad spectrum of neurophysiological techniques in animals and humans. The ideal candidate is highly motivated with a strong interest in interdisciplinary research. Candidates must have an MA (or equivalent) in neuroscience, physics, mathematics, psychology, or related fields. Fluency in Matlab is required. Experience in electrophysiology, spectral analysis and/or M/EEG is highly valued. Applications should include a detailed CV, statement of research interests, and names of at least two referees. The position is available for three years. Applications will be considered until the position is filled. Please send applications or informal inquiries to Markus Siegel (markus.siegel at uni-tuebingen.de). -- Dr. Markus Siegel Principal Investigator, Centre for Integrative Neuroscience (CIN), Tübingen From nugenta at mail.nih.gov Fri Feb 15 18:34:44 2013 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 15 Feb 2013 17:34:44 +0000 Subject: [FieldTrip] headmodels In-Reply-To: <511E6897.1060101@donders.ru.nl> References: <511E6897.1060101@donders.ru.nl> Message-ID: It certainly works with the unit conversions in the version I'm currently using, which is from 2/5/2013 - - thanks so much!! As soon as I have a chance, I'll download the latest version to test. Thanks again! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov From: "Jörn M. Horschig" [mailto:jm.horschig at donders.ru.nl] Sent: Friday, February 15, 2013 11:56 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] headmodels Dear Allison, I was encountering similar issues the last two days and hope to have fixed some unit conversion bugs. Thus it might be that with the newest FT version, you don't need to manually convert the units anymore as JM suggested. Could you give it a try for me and see whether it works without JMs manual approach in the newest FT version? Best, Jörn On 2/15/2013 3:51 PM, Nugent, Allison C. (NIH/NIMH) [E] wrote: Hello, I'm very sorry to repost this, but I'm hoping that someone might be able to give me advice. I have an MRI in nifti format. It has already been re-aligned with the fiducial markers. I've scoured the tutorials, but most seem to deal with MRIs that are already in the ctf coordinate system. I've imported the MRI like so: mri=ft_read_mri('ABC_ortho_anat.nii'); mri=ft_determine_coordsys(mri) I re-label the coordinate axes, and set the origin - when it's done, it has "Neuromag" as the coordsys, although that's not how it was created. Next: cfg=[]; cfg.method='interactive' mri_realigned=ft_volumerealign(cfg,mri) % to set the fiducial points cfg=[]; [segmentedmri]=ft_volumesegment(cfg, mri_realigned) During execution I get this warning: Warning: could not open /tmp/tpe3eb8b07_40e0_49bf_88d2_e0c227c3d7af.img Even though the file appears to exist - and the program completes and produces a segmented MRI that looks fine. Finally: hdr=ft_read_header('ACN.ds'); cfg=[]; cfg.method='singleshell'; vol_realistic=ft_prepare_headmodel(cfg,segmentedmri); figure ft_plot_vol(vol_realistic);hold on ft_plot_sens(hdr.grad) The plot has the sensor array and the headmodel on different scales - like it didn't properly adjust for the difference in mm and cm, even though the units are specified in the data structures. I'd ultimately also like to be able to use the localspheres model, and compare results, but since I can't figure out how to plot that headmodel to check it, I thought I'd start with one that I can plot. Thank you! Allison Nugent, PhD MRI Physicist Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph. 301-451-8863 nugenta at mail.nih.gov _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -- Jörn M. Horschig PhD Student Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen Neuronal Oscillations Group FieldTrip Development Team P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Contact: E-Mail: jm.horschig at donders.ru.nl Tel: +31-(0)24-36-68493 Web: http://www.ru.nl/donders Visiting address: Trigon, room 2.30 Kapittelweg 29 NL-6525 EN Nijmegen The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From ricardoojm at gmail.com Sun Feb 17 19:23:05 2013 From: ricardoojm at gmail.com (Ricardo Moura) Date: Sun, 17 Feb 2013 19:23:05 +0100 Subject: [FieldTrip] Reading brainvision data: problem with channel's resolution In-Reply-To: References: Message-ID: Hi, I solved this problem already. But as I have seen, the marks for the bad intervals that were defined in the brainvision analyzer are not automatically imported. Is it really right? And how could I use these already defined bad intervals, instead of doing the whole artifact correction again (is there a function in fieldtrip that does it, or do I have to write one myself)? Thank you very much once again, Best regards Ricardo On 15 February 2013 11:52, Ricardo Moura wrote: > Hi Jan-Mathijs, > Thank you very much for your reply. > > I found a mistake of mine in the data export. I didn't export it as ".dat" > binary file. I was exporting it as text file. Now, the same script I sent > in the first email is working in the sense that the program is properly > recognizing the samples in the data (the 797740 sampling points, instead of > only 80). Nevertheless, I still have a problem with the channel's > resolution. > > I saw that when exporting the binary files as ieee 32-bit floating, the > resolution of the channels is not recorded in the header. So I changed it > to the "32-bit signed integer" format, and now I have the resolution (in > the header, it appears as "Ch1=AF3,NewRef,4.1322874E-08,µV", under "Channel > Infos"), but then, another error message is returned: > > ??? Error using ==> read_brainvision_eeg at 155 > unsupported sub-fileformat > > I tried to export the data in different ways, but the error persists. > > I am afraid there is something else wrong in the way I am exporting the > data. Could you tell me how I must export the data, or just show me where I > can find more detailed specifications about it? I searched through the site > and mailing list, and haven't find further information about it. > > Thanks again, > Best wishes, > Ricardo > > > > > > On 14 February 2013 16:12, Ricardo Moura wrote: > >> Dear all, >> >> I am very new to fieldtrip and I am experiencing a problem when reading >> brainvision data. I searched in the mailinglist archives but I didn't find >> anything that could help me. In case there is information about it >> somewhere else, I would appreciate if someone can send me a reference. >> >> The problem is the following. I am tring to read continuous data from the >> brainvision analyzer (already preprocessed), but I always have an error >> which seems to be due to a problem with the identification of the channels >> resolution. I exported the data from brainvision in ".dat" vectorized >> format, and I am loading it first with the ft_preprocessing command. >> >> Here is the command I am running to load it: >> cfg = []; >> cfg.dataset = 'Raw Data Inspection.dat'; >> eegData = ft_preprocessing(cfg) >> >> >> Then the following warning message is returned, for each of the 56 >> channels I have in the data: >> Warning: Unknown resolution for channel 55 in Raw Data Inspection.vhdr! >> > In fileio\private\read_brainvision_vhdr at 50 >> In ft_read_header at 381 >> In ft_preprocessing at 394 >> >> >> And at the end, I have the following error: >> ??? Index exceeds matrix dimensions. >> >> Error in ==> read_brainvision_eeg at 150 >> dat(chan,:) = tmp(begsample:endsample); >> >> Error in ==> ft_read_data at 400 >> dat = read_brainvision_eeg(filename, hdr.orig, begsample, endsample, >> chanindx); >> >> Error in ==> ft_preprocessing at 573 >> dat = ft_read_data(cfg.datafile, 'header', hdr, 'begsample', >> begsample, 'endsample', endsample, 'chanindx', rawindx, >> 'checkboundary', strcmp(cfg.continuous, 'no'), 'dataformat', >> cfg.dataformat) >> >> >> Interestingly, when I read the header file with the "hdr = >> ft_read_header('Raw Data Inspection.vhdr')", it says that I have only 80 >> samples in the data. When checking the header file with the notepad, it >> says that there are actualy 797740 data points. >> >> So, am I realling doing it right? >> Thank you very much in advance, and best wishes, >> Ricardo >> > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stidimitriadis at gmail.com Tue Feb 19 10:33:53 2013 From: stidimitriadis at gmail.com (Stavros Dimitriadis) Date: Tue, 19 Feb 2013 11:33:53 +0200 Subject: [FieldTrip] from axial to planar gradiometers Message-ID: Hello to everybody ! I am facing a problem with the transformation of data from axial to planar gradiometers ! I manipulate data recorded from 248- channel BTi (4D Neuroimaging) axial gradiometer system ! I am using cfg.planarmethod='sincos'; The basic problem is the output of ft_megplanar where labels sections have 2x248 labels (vertical & horizontal) but only 248 channels in avg section of the struct. I cannot understand the problem! Can anyone have any idea ? Best regards Dimitriadis Stavros users.auth.gr/~stdimitr/index.html -------------- next part -------------- An HTML attachment was scrubbed... URL: From sammler at cbs.mpg.de Tue Feb 19 13:33:55 2013 From: sammler at cbs.mpg.de (Daniela Sammler) Date: Tue, 19 Feb 2013 13:33:55 +0100 (CET) Subject: [FieldTrip] PhD position on "Intonation in speech" at MPI-CBS in Leipzig, Germany In-Reply-To: <291809232.3656.1361277182103.JavaMail.root@zimbra> Message-ID: <1757739675.3682.1361277235866.JavaMail.root@zimbra> The Max Planck Institute for Human Cognitive and Brain Sciences (MPI-CBS) in Leipzig and its newly established Otto Hahn Group on the "Neural Bases of Intonation in Speech", led by Daniela Sammler, are now offering a PhD position for 3 years in a research project on social aspects of prosody perception in speech using fMRI, MEG and/or TMS. There is much more to human communication than the (de)coding of the explicit, propositional meaning of a vocal speech signal. Between the lines, the vocal output reveals a lot about the speakers’ believes, attitudes (e.g., sympathy, dominance), and communicative intentions (e.g., to warn, to request, to command, to tease). Much of such implicit, illocutionary meaning is conveyed by the “manner of saying”, i.e. the speech prosody, and the interpretation of those subtleties involves a lot of pragmatic inference. There is growing evidence that this latter faculty is distinct from our language abilities such as phonology, syntax and semantics, making it reasonable to assume the involvement of brain areas beyond the well-known fronto-temporal language network in human vocal communication. The goal of the PhD project is to investigate the neural bases of decoding communicative intentions conveyed by prosody (i.e. HOW something is said) in contrast to and in interaction with the decoding of propositional meaning (i.e. WHAT is said). Applicants must have a master degree (or equivalent) in psychology, cognitive sciences, neuroscience, medicine, linguistics, or a related field. Proficiency in oral and written English is necessary. A solid methods background (statistics and programming) as well as prior experience with either fMRI or EEG/MEG are highly desirable. Most importantly, the successful applicant will share our enthusiasm in research questions on prosody and the social brain in vocal communication. Preferable starting date is July 2013. Salary is dependent on experience and based on MPI stipends or equivalent salary according to German Public service regulations. The research will be conducted at the MPI-CBS in Leipzig, Germany, an internationally leading center for cognitive and imaging neuroscience equipped with a 7T MRI scanner, three 3T MRI scanners, a 306 channels MEG system, a TMS system and several EEG suites. All facilities are supported by experienced IT and physicist staff. Our institute (just 190 km or 70 minutes by train, south of Berlin) offers a very international environment, with English and German being the languages spoken in the laboratory. It offers a friendly and generous environment of researchers with diverse backgrounds and with an excellent infrastructure. In order to increase the proportion of female staff members, applications from female scientists are particularly encouraged. Preference will be given to disabled persons with the same qualification. Applications should be sent to the email below as a single, appropriately named pdf email attachment. It should enclose a cover letter (max. 2 pages) that also specifies your future research interests; a CV; up to three representative reprints; and contact details of two personal references. This call remains open until the position is filled. The application should be kindly sent to personal at cbs.mpg.de using the code "PhD 3/13" in the subject. For further details please contact Dr Daniela Sammler, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, sammler at cbs.mpg.de -- Daniela SAMMLER, Ph.D. Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1a 04103 Leipzig phone: +49 341 9940 2679 fax: +49 341 9940 2260 From r.oostenveld at donders.ru.nl Tue Feb 19 14:30:47 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Tue, 19 Feb 2013 14:30:47 +0100 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 References: <002201ce0e9a$e18ab740$a4a025c0$@stijns@fcdonders.ru.nl> Message-ID: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> NIHC-BrainGain Tutorial Day: Tools and novelties in neurotechnology research We invite PhD students, post-docs and senior researchers working in the fields of brain-computer interfacing (BCI), neurofeedback, cognitive neuroscience, neuroinformatics, neurosurgery and related topics to our Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen. The day marks the end of the BrainGain consortium, a six-year joint-effort project on Brain-Computer Interfacing and related technologies. More information on BrainGain can be found here. The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. The 'tools' track is intended to provide both newcomers to the field and experienced researchers with an overview of the tools needed to integrate cognitive neuroscience and advanced invasive and non-invasive technology. Topics range from data streaming to modelling and statistics, and from online fMRI decoding to a crash course in neuroethics., You will also receive some helpful insights for a future career, in case you are interested in applying for a grant in the near future or considering setting up your own company. The 'novelties' track covers a wide range of topics indicating some of the possible topics to be further explored in BCI and neurotechnology research, including genetics, robotics and intracranial recordings. There is no need to stick to one of the two tracks the whole day: you are free to switch between tracks any time. In parallel to the lectures, there will be several interesting demonstrations. The full programme and registration form can be found on the NIHC website (https://www.hersenenencognitie.nl). Please register before 1 March 2013. Participation is free. Lunch and drinks will be provided. We hope to welcome you on March 21st in Nijmegen! Susanna Bicknell Radboud University Nijmegen ____________________________________________________________________ Faculty of Science | Finance and Economic Affairs | Project Management | LC-IMPACT Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | Project Manager T +31 24 3653300 | HG00.616 (Monday, Thursday) Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, Wednesday) Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands Visiting and courier service address: Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: From mcgoiv0 at wfu.edu Tue Feb 19 18:47:39 2013 From: mcgoiv0 at wfu.edu (McGowin, Inna) Date: Tue, 19 Feb 2013 12:47:39 -0500 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 In-Reply-To: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> References: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> Message-ID: Hello Susanna, Thanks for the information. Is the tutorial day a local event or it can be accessed through a webinar? Thanks, Inna On Tue, Feb 19, 2013 at 8:30 AM, Robert Oostenveld < r.oostenveld at donders.ru.nl> wrote: > > *NIHC-BrainGain Tutorial Day:* > *Tools and novelties in neurotechnology research * > ** ** > We invite PhD students, post-docs and senior researchers working in the > fields of brain-computer interfacing (BCI), neurofeedback, cognitive > neuroscience, neuroinformatics, neurosurgery and related topics to our > Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen.**** > The day marks the end of the BrainGain consortium, a six-year joint-effort > project on Brain-Computer Interfacing and related technologies. More > information on BrainGain can be found here .**** > ** ** > The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. > The 'tools' track is intended to provide both newcomers to the field and > experienced researchers with an overview of the tools needed to integrate > cognitive neuroscience and advanced invasive and non-invasive technology. > Topics range from data streaming to modelling and statistics, and from > online fMRI decoding to a crash course in neuroethics., You will also > receive some helpful insights for a future career, in case you are > interested in applying for a grant in the near future or considering > setting up your own company.**** > The 'novelties' track covers a wide range of topics indicating some of the > possible topics to be further explored in BCI and neurotechnology research, > including genetics, robotics and intracranial recordings. **** > There is no need to stick to one of the two tracks the whole day: you are > free to switch between tracks any time.**** > ** ** > In parallel to the lectures, there will be several interesting > demonstrations. **** > ** ** > The full programme and registration form can be found on the NIHC website > (https://www.hersenenencognitie.nl)*. *Please register before 1 March > 2013. Participation is free. Lunch and drinks will be provided. **** > ** ** > We hope to welcome you on March 21st in Nijmegen!**** > ** ** > Susanna Bicknell**** > Radboud University Nijmegen**** > ____________________________________________________________________**** > Faculty of Science | Finance and Economic Affairs | Project Management | > LC-IMPACT**** > Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | > Project Manager**** > T +31 24 3653300 | HG00.616 (Monday, Thursday)**** > Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, > Wednesday)**** > Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands**** > Visiting and courier service address: Heyendaalseweg 135, 6525 AJ > Nijmegen, The Netherlands > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -- Inna McGowin -------------- next part -------------- An HTML attachment was scrubbed... URL: From inieuwenhuis at berkeley.edu Wed Feb 20 00:59:13 2013 From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis) Date: Tue, 19 Feb 2013 15:59:13 -0800 Subject: [FieldTrip] cluster analysis correlation Message-ID: <512411D1.6040901@berkeley.edu> Hi all, I've computer correlations (kendall's tau) between EEG power and a behavioral measure over participants (made my own statfun using corr). Now I'd like to use the cluster randomization framework to correct for multiple comparisons. I think it would be valid to shuffle the assignment of EEG power to behavioral measure (which is specified in cfg.design for correlation), make a distribution and test my correlations against that. So shuffle the data so that say EEG power of subect1 get's linked to behavioral measure of subject3, subject2 to subject6 etc, etc, just as we do with t-values shuffling who belongs to which condition. Questions: 1) is this implemented in FieldTrip? How would I do this? Cause the design needs to be shuffled now, this is different from how it would work for a t-test no? 2) If 1== false, Anyone done this, got some tips? 3) Is the above approach I suggest statistically valid? I think testing the tau against zero is not valid (seeing if it is significantly different from zero by making some dummy stat with zeros), but what I suggest is, anyone any thoughts? Thanks!! Ingrid -- Ingrid Nieuwenhuis PhD Postdoctoral Fellow Sleep and Neuroimaging Laboratory Department of Psychology University of California, Berkeley California 94720-1650 Tolman Hall, room 5305 From simonjameslittle at gmail.com Thu Feb 21 14:17:17 2013 From: simonjameslittle at gmail.com (Simon Little) Date: Thu, 21 Feb 2013 13:17:17 +0000 Subject: [FieldTrip] LAYOUT PAIN! Message-ID: Hi, I would be really very grateful for some help regarding setting layout for EEG. Im analysing (or trying to!) some clinical EEG 10-20 data on epilepsy patients and am struggling to get the layout working using the standardised layout files. My channel names concur with those of standard EEG 10 -20 systems (see below) (http://en.wikipedia.org/wiki/10-20_system_(EEG)) Number of questions - 1. The EEG 10-20 standard layout does not seem to match what I thought of (and have checked online) as the standard 10-20 format. Specifically - it includes channels Fpz and Oz for example which aren't on the standard layoutand excludes T3 T4 T5 T6 ( http://en.wikipedia.org/wiki/10-20_system_(EEG)) 2. When I check what my layout should be - >> [type]=ft_senstype(datast_A.label) type = ext1020 Yep there is no layout file for ext1020 in the standard layout templates that seem to come with fieldtrip to use with ft_prepare_layout. Given that all the channels are I need are in the EEG1010 file, I hoped that I could use that instead but then I end up with a layout has 80 odd channels when I only need 21. I'd be so grateful for any help with this! I'm very sorry if its something very simple but I have been looking at it for many many hours without any luck! Many thanks Simon Little My channel names - 'Fp1' 'Fp2' 'F3' 'F4' 'C3' 'C4' 'P3' 'P4' 'O1' 'O2' 'F7' 'F8' 'T3' 'T4' 'T5' 'T6' 'A1' 'A2' 'Fz' 'Cz' 'Pz' EEG1020 - channel names from lay file. 1 -0.485328 1.493835 0.393101 0.294826 Fp1 2 0.000000 1.570696 0.393101 0.294826 Fpz 3 0.485501 1.493884 0.393101 0.294826 Fp2 4 -1.270781 0.923319 0.393101 0.294826 F7 5 -0.652084 0.812357 0.393101 0.294826 F3 6 0.000000 0.785398 0.393101 0.294826 Fz 7 0.652084 0.812357 0.393101 0.294826 F4 8 1.270781 0.923319 0.393101 0.294826 F8 9 -1.570796 0.000000 0.393101 0.294826 T7 10 -0.785398 0.000111 0.393101 0.294826 C3 11 0.000000 0.000200 0.393101 0.294826 Cz 12 0.785398 0.000111 0.393101 0.294826 C4 13 1.570796 -0.000000 0.393101 0.294826 T8 14 -1.270862 -0.923378 0.393101 0.294826 P7 15 -0.652231 -0.811998 0.393101 0.294826 P3 16 -0.000000 -0.785257 0.393101 0.294826 Pz 17 0.652231 -0.811998 0.393101 0.294826 P4 18 1.270862 -0.923378 0.393101 0.294826 P8 19 -0.485359 -1.493930 0.393101 0.294826 O1 20 -0.000000 -1.570796 0.393101 0.294826 Oz 21 0.485359 -1.493930 0.393101 0.294826 O2 22 -1.570796 1.570696 0.393101 0.294826 COMNT 23 1.570796 1.570696 0.393101 0.294826 SCALE -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.herring at fcdonders.ru.nl Thu Feb 21 16:34:31 2013 From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim)) Date: Thu, 21 Feb 2013 16:34:31 +0100 (CET) Subject: [FieldTrip] Notification for users with different channel ordering between participants Message-ID: <004701ce1048$f16daeb0$d4490c10$@herring@fcdonders.ru.nl> Dear Fieldtrip users, It has come to our attention by Philip Ruhnau that when averaging across participants using ft_XXXgrandaverage, due to a bug, no care was taken when the channel-order was different between participants (see http://bugzilla.fcdonders.nl/show_bug.cgi?id=1986). This could occur, for example, when after interpolating channels, the interpolated channels are added to the end of the data and thus changing the channel ordering. Particularly for EEG data this bug could be a problem because often different channels are interpolated for different subjects. No problems should have occurred when merely removing channels. For MEG data, the same problem occurred when using ft_combineplanar after interpolating, for example, vertical or horizontal channels separately. In this instance the wrong channel pairs were combined. However, if channels were interpolated after using ft_combineplanar, or if pairs of horizontal and vertical channels were removed you should have no problems given that the same channels were affected across all participants. The bug has been fixed as of rev. 7519. We strongly advise users that have data containing different channel ordering between participants to download the newest version of Fieldtrip and re-check grand averaged data. Best, Jim -------------- next part -------------- An HTML attachment was scrubbed... URL: From skelly2 at ccny.cuny.edu Mon Feb 25 03:16:15 2013 From: skelly2 at ccny.cuny.edu (Simon Kelly) Date: Sun, 24 Feb 2013 21:16:15 -0500 (EST) Subject: [FieldTrip] Postdoc position in systems/cognitive neuroscience (New York) Message-ID: <201302250216.020279@pelican.admin.ccny.cuny.edu> Applications are invited for a Postdoctoral position in the Neural Systems Lab of Simon Kelly in The City College of New York. The position is funded by the Endeavor Scientists Program of the Child Mind Institute (CMI; http://www.childmind.org/en/endeavor-scientists/) and will be jointly supervised by Simon Kelly (http://bme.ccny.cuny.edu/people/faculty/skelly) and Michael Milham (http://www.childmind.org/en/directory/clinicians/mmilham). The goal of the collaboration is to develop novel paradigms for the study of perception, attention and decision making in humans using EEG and/or fMRI, and to deploy these paradigms in clinical studies of child and adolescent populations in CMI as well as in basic research studies in the Kelly Lab. Any innovative analytic tools and paradigms developed in the course of this position will be made publicly available. Applicants must have a Ph.D. in neuroscience or a related field and have experience and strong interest in cognitive neuroscience. The candidate must have strong analytic skills, be proficient in programming (especially Matlab), and have experience in psychophysics and EEG recording and analysis. Experience with fMRI is a strong plus. The ideal candidate will be reliable, highly motivated and productive, and enjoy working collaboratively. Applicants should send a curriculum vitae, contact information for 2-3 references, and a cover letter with a brief description of past research accomplishments as well as future research interests and career goals to Simon Kelly: skelly2 at ccny.cuny.edu. From paul.sowman at mq.edu.au Mon Feb 25 07:20:55 2013 From: paul.sowman at mq.edu.au (Paul Sowman) Date: Mon, 25 Feb 2013 17:20:55 +1100 Subject: [FieldTrip] FT_CONNECTIVITYANALYIS Message-ID: Hi, which is the appropriate option in FT_CONNECTIVITYANALYIS to implement connectivity analysis via the imaginary part of coherency? The 2011 Computational Intelligence and Neuroscience paper says that the method from the Nolte paper is implemented but I'm not sure which is the right option to do this from the list: coh', coherence, support for freq, freqmvar and source data. For partial coherence also specify cfg.partchannel 'csd', cross-spectral density matrix, can also calculate partial csds - if cfg.partchannel is specified, support for freq and freqmvar data 'plv', phase-locking value, support for freq and freqmvar data 'powcorr', power correlation, support for freq and source data 'amplcorr', amplitude correlation, support for freq and source data 'granger', granger causality, support for freq and freqmvar data 'dtf', directed transfer function, support for freq and freqmvar data 'pdc', partial directed coherence, support for freq and freqmvar data 'psi', phaseslope index, support for freq and freqmvar data 'wpli', weighted phase lag index (signed one, still have to take absolute value to get indication of strength of interaction. Note: measure has positive bias. Use wpli_debiased to avoid this. 'wpli_debiased' debiased weighted phase lag index (estimates squared wpli) 'ppc' pairwise phase consistency 'wppc' weighted pairwise phase consistency G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. -- Paul F Sowman NHMRC Postdoctoral Training Fellow ARC Centre of Excellence for Cognition and its Disorders (CCD) MACQUARIE UNIVERSITY NSW 2109 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Feb 25 09:35:21 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Mon, 25 Feb 2013 09:35:21 +0100 Subject: [FieldTrip] FT_CONNECTIVITYANALYIS In-Reply-To: References: Message-ID: <05D58012-4719-4188-94AF-237EE1D58007@donders.ru.nl> Hi Paul, You should specify cfg.method = 'coh' in conjunction with cfg.complex = 'imag'; I'll update the documentation. Best, Jan-Mathijs On Feb 25, 2013, at 7:20 AM, Paul Sowman wrote: > Hi, which is the appropriate option in FT_CONNECTIVITYANALYIS to implement connectivity analysis via the imaginary part of coherency? The 2011 Computational Intelligence and Neuroscience paper says that the method from the Nolte paper is implemented but I'm not sure which is the right option to do this from the list: > coh', coherence, support for freq, freqmvar and > source data. For partial coherence also > specify cfg.partchannel > 'csd', cross-spectral density matrix, can also > calculate partial csds - > if cfg.partchannel is specified, support for freq and > freqmvar data > 'plv', phase-locking value, support for freq and freqmvar data > 'powcorr', power correlation, support for freq and source data > 'amplcorr', amplitude correlation, support for freq and source data > 'granger', granger causality, support for freq and freqmvar data > 'dtf', directed transfer function, support for freq and freqmvar data > 'pdc', partial directed coherence, support for freq and freqmvar data > 'psi', phaseslope index, support for freq and freqmvar data > 'wpli', weighted phase lag index (signed one, > still have to take absolute value to get indication of > strength of interaction. Note: measure has > positive bias. Use wpli_debiased to avoid > this. > 'wpli_debiased' debiased weighted phase lag index > (estimates squared wpli) > 'ppc' pairwise phase consistency > 'wppc' weighted pairwise phase consistency > > G. Nolte, O. Bai, L. Wheaton, Z. Mari, S. Vorbach, and M. Hallett, “Identifying true brain interaction from EEG data using the imaginary part of coherency,” Clinical Neurophysiology, vol. 115, no. 10, pp. 2292–2307, 2004. > > -- > Paul F Sowman > NHMRC Postdoctoral Training Fellow > ARC Centre of Excellence for Cognition and its Disorders (CCD) > MACQUARIE UNIVERSITY NSW 2109 > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From polomacnenad at gmail.com Mon Feb 25 10:27:44 2013 From: polomacnenad at gmail.com (Nenad Polomac) Date: Mon, 25 Feb 2013 10:27:44 +0100 Subject: [FieldTrip] loreta in ft_sourceanalysis Message-ID: Dear Fieldtrip users, I would like to ask you which version of loreta is implemented in ft_sourceanalysis. Is it eloreta or sloreta? Thank you in advance! Kind regards! Nenad -------------- next part -------------- An HTML attachment was scrubbed... URL: From pd25588 at berkeley.edu Mon Feb 25 21:23:28 2013 From: pd25588 at berkeley.edu (Pascasie L. Dombert) Date: Mon, 25 Feb 2013 12:23:28 -0800 Subject: [FieldTrip] problem using ft_artifact_muscle Message-ID: Hi all, I am a fieldtrip starter working on an EEG data set. I have a question concerning the muscle artifact detection function and I was hoping that you could help me with this. I am calling the function [cfg,artifact_muscle] = ft_artifact_muscle(cfg,ref_data) as explained in the manual (settings suggested) and get the following error message (see code + error): ________________________________________________________________________________________________ > %detect the MUSCLE artifacts > cfg = []; > cfg.continuous = 'yes'; > % define trial first > cfg.dataset = 'xx’; > cfg.trialfun ='trialfun_general'; > cfg.trialdef.triallength =1; % creates 1-second data segments > cfg.trialdef.ntrials = inf; % i.e. the complete file > cfg = ft_definetrial(cfg); > > % cutoff > cfg.artfctdef.muscle.channel = 'all'; > cfg.artfctdef.muscle.cutoff = 4; > > % algorithmic parameters > cfg.artfctdef.muscle.bpfilter = 'yes'; > cfg.artfctdef.muscle.bpfreq = [110 140]; > cfg.artfctdef.muscle.bpfiltord = 9; > cfg.artfctdef.muscle.bpfilttype = 'but'; > cfg.artfctdef.muscle.hilbert = 'yes'; > cfg.artfctdef.muscle.boxcar = 0.2; > > % feedback > %cfg.artfctdef.muscle.interactive = 'yes'; % to adjust cutoff zvalue if needed > > [cfg, artifact_muscle] = ft_artifact_muscle(cfg,ref_data); > > > > > ERROR: > Subscript indices must either be real positive integers or logicals. > > Error in ft_fetch_data (line 123) > count = count(begsample:endsample); > > Error in ft_artifact_zvalue (line 195) > dat{trlop} = ft_fetch_data(data, 'header', hdr, 'begsample', trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding, 'chanindx', > sgnind, 'checkboundary', strcmp(cfg.continuous,' > Error in ft_artifact_muscle (line 156) > [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data); > _______________________________________________________ However, I only get the error message with the default/suggested values. When I use: cfg.artfctdef.muscle.bpfreq = [110 120]; and cfg.artfctdef.muscle.bpfiltord = 7; I don't get the error message and the script runs properly. Does anyone happen to know what could have let to this problem? Thanks a lot in advance! Best, Leonie -------------- next part -------------- An HTML attachment was scrubbed... URL: From eeguser at hotmail.com Mon Feb 25 22:52:49 2013 From: eeguser at hotmail.com (Subramaniam Iyer) Date: Tue, 26 Feb 2013 00:52:49 +0300 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order Message-ID: Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable : http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance.Subbu -------------- next part -------------- An HTML attachment was scrubbed... URL: From k.kouroupaki at med.uoc.gr Tue Feb 26 13:27:07 2013 From: k.kouroupaki at med.uoc.gr (k.kouroupaki at med.uoc.gr) Date: Tue, 26 Feb 2013 14:27:07 +0200 Subject: [FieldTrip] cfg.latency Message-ID: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> HI everyone! I am a new field trip user and have been using it for EEG SOURCE LOCALIZATION. I have a problem though. When I run the ft_sourceanalysis as: source = ft_sourceanalysis(cfg, freq) I get the following error: ??? Reference to non-existent field 'latency'. Error in ==> prepare_freq_matrices at 55 tbin = nearest(freq.time, cfg.latency); Error in ==> ft_sourceanalysis at 458 [Cf, Cr, Pr, Ntrials, cfg] = prepare_freq_matrices(cfg, data); Could you please help me to localize where the problem is and solve it? Thank you in advance, Kleo ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. From evaladez at psych.udel.edu Tue Feb 26 21:26:30 2013 From: evaladez at psych.udel.edu (Emilio Valadez) Date: Tue, 26 Feb 2013 15:26:30 -0500 Subject: [FieldTrip] Performing time-frequency statistical tests on regional source data Message-ID: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> Dear FieldTrip users, I have an EEG dataset that was reduced to 8 regional sources with BESA and then exported for FieldTrip analysis. I want to perform a statistical test on the regional sources' time-frequency data, comparing two experimental conditions, but I don't know whether it would be appropriate to use ft_freqstatistics (because I have regional sources instead of a complete sensor layout - making cluster formation problematic) or ft_sourcestatistics. Can you suggest a method for performing a statistical test in this situation? Thanks in advance for your help. Best, Emilio Valadez From jan.schoffelen at donders.ru.nl Tue Feb 26 21:36:28 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:36:28 +0100 Subject: [FieldTrip] Performing time-frequency statistical tests on regional source data In-Reply-To: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> References: <10DBEA48DAE8BB4F8F588B1254C0D92E0161DD51399E@razor.psych.udel.edu> Message-ID: <1ECC8F93-0E0D-4646-B407-96F3E5F13631@donders.ru.nl> Hi Emilio, Using ft_freqstatistics is very possible. Indeed you will not be able to use clustering for multiple comparison correction. In fact, having reduced the number of comparisons to 8 already almost gets rid of the multiple comparison problem. You can use a nonparametric permutation test without a cluster-based test statistic, and do a bonferroni correction on the p-values. Best, Jan-Mathijs On Feb 26, 2013, at 9:26 PM, Emilio Valadez wrote: > Dear FieldTrip users, > > I have an EEG dataset that was reduced to 8 regional sources with BESA and then exported for FieldTrip analysis. I want to perform a statistical test on the regional sources' time-frequency data, comparing two experimental conditions, but I don't know whether it would be appropriate to use ft_freqstatistics (because I have regional sources instead of a complete sensor layout - making cluster formation problematic) or ft_sourcestatistics. Can you suggest a method for performing a statistical test in this situation? Thanks in advance for your help. > > Best, > Emilio Valadez > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 21:44:21 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:44:21 +0100 Subject: [FieldTrip] cfg.latency In-Reply-To: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> References: <20130226142707.12453yvzhxm8ot8g@webmail.med.uoc.gr> Message-ID: <2C7B27EF-6A82-4781-B57D-5E2918DF8FEF@donders.ru.nl> Hi Kleo, Did you try following the suggestion that is in the error message, and specified a cfg.latency prior to calling ft_sourceanalysis? Best wishes, Jan-Mathijs On Feb 26, 2013, at 1:27 PM, k.kouroupaki at med.uoc.gr wrote: > HI everyone! > > I am a new field trip user and have been using it for EEG SOURCE LOCALIZATION. > I have a problem though. When I run the ft_sourceanalysis as: source = ft_sourceanalysis(cfg, freq) I get the following error: > > ??? Reference to non-existent field 'latency'. > > Error in ==> prepare_freq_matrices at 55 > tbin = nearest(freq.time, cfg.latency); > > Error in ==> ft_sourceanalysis at 458 > [Cf, Cr, Pr, Ntrials, cfg] = prepare_freq_matrices(cfg, data); > > Could you please help me to localize where the problem is and solve it? > Thank you in advance, > Kleo > > ---------------------------------------------------------------- > This message was sent using IMP, the Internet Messaging Program. > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 21:52:37 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 21:52:37 +0100 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: References: Message-ID: <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote: > Dear FieldTrip users > > I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. > > 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? > 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? > 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? > > Thanks in advance. > Subbu > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Tue Feb 26 22:03:23 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Tue, 26 Feb 2013 22:03:23 +0100 Subject: [FieldTrip] problem using ft_artifact_muscle In-Reply-To: References: Message-ID: <2AD4BB54-F01D-40C7-89F2-20982BBBFD1F@donders.ru.nl> Hi Leonie, > > ERROR: > > > Subscript indices must either be real positive integers or logicals. > > > > > > Error in ft_fetch_data (line 123) > > > count = count(begsample:endsample); > > > > The error message indicates that either begsample or endsample are badly behaved. I put my money on begsample, in that its value <= 0 in the case of a bandpassfilter-order of 9. My guess is that ft_fetch_data tries to get some data that is not there. Did you check the cfg.artfctdef.muscle.fltpadding? In general, when supplying data in the input to ft_artifact_muscle, the value of this parameter should be set to 0. Best, Jan-Mathijs On Feb 25, 2013, at 9:23 PM, Pascasie L. Dombert wrote: > Hi all, > > > I am a fieldtrip starter working on an EEG data set. I have a question concerning the muscle artifact detection function and I was hoping that you could help me with this. > > I am calling the function > > [cfg,artifact_muscle] = ft_artifact_muscle(cfg,ref_data) as explained in the manual (settings suggested) and get the following error message (see code + error): > > ________________________________________________________________________________________________ > > > %detect the MUSCLE artifacts > > > cfg = []; > > > cfg.continuous = 'yes'; > > > % define trial first > > > cfg.dataset = 'xx’; > > > cfg.trialfun ='trialfun_general'; > > > cfg.trialdef.triallength =1; % creates 1-second data segments > > > cfg.trialdef.ntrials = inf; > > % i.e. the complete file > > > cfg = ft_definetrial(cfg); > > > > > > % cutoff > > > cfg.artfctdef.muscle.channel = 'all'; > > > cfg.artfctdef.muscle.cutoff = 4; > > > > > > % algorithmic parameters > > > cfg.artfctdef.muscle.bpfilter = 'yes'; > > > cfg.artfctdef.muscle.bpfreq = [110 140]; > > > cfg.artfctdef.muscle.bpfiltord = 9; > > > cfg.artfctdef.muscle.bpfilttype = 'but'; > > > cfg.artfctdef.muscle.hilbert = 'yes'; > > > cfg.artfctdef.muscle.boxcar = 0.2; > > > > > > % feedback > > > %cfg.artfctdef.muscle.interactive = 'yes'; % to adjust cutoff zvalue if needed > > > > > > [cfg, artifact_muscle] = ft_artifact_muscle(cfg,ref_data); > > > > > > > > > > > > > > > ERROR: > > > Subscript indices must either be real positive integers or logicals. > > > > > > Error in ft_fetch_data (line 123) > > > count = count(begsample:endsample); > > > > > > Error in ft_artifact_zvalue (line 195) > > > dat{trlop} = ft_fetch_data(data, 'header', hdr, 'begsample', trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding, 'chanindx', > > > sgnind, 'checkboundary', strcmp(cfg.continuous,' > > > Error in ft_artifact_muscle (line 156) > > > [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data); > > > _______________________________________________________ > > > > However, I only get the error message with the default/suggested values. > > When I use: > > cfg.artfctdef.muscle.bpfreq = [110 120]; and cfg.artfctdef.muscle.bpfiltord = 7; > > I don't get the error message and the script runs properly. Does anyone happen to know what could have let to this problem? > > > Thanks a lot in advance! > > Best, Leonie > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From eeguser at hotmail.com Wed Feb 27 00:07:00 2013 From: eeguser at hotmail.com (Subramaniam Iyer) Date: Wed, 27 Feb 2013 02:07:00 +0300 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> References: , <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl> Message-ID: Dear Jan-Mathjis Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first.I have never done source localization before, but I will try it by going through the extensive FT documentation. However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ? RegardsSubbu From: jan.schoffelen at donders.ru.nl Date: Tue, 26 Feb 2013 21:52:37 +0100 To: fieldtrip at science.ru.nl Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote:Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance.Subbu_______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics,Nijmegen, The Netherlands J.Schoffelen at donders.ru.nlTelephone: +31-24-3614793 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From carlo.huber at uk-koeln.de Wed Feb 27 10:21:27 2013 From: carlo.huber at uk-koeln.de (Carlo Huber) Date: Wed, 27 Feb 2013 09:21:27 +0000 Subject: [FieldTrip] Preprocessing before connectivity analysis and model order In-Reply-To: References: , <0DB4AD0F-90B1-47B2-A9EB-3BCD8AB59726@donders.ru.nl>, Message-ID: <877B32852B5C3A40978EA1F48A10B5022C9854B7@UKK087.ADS.UK-KOELN.DE> Dear Subbu, PDC seems to be influenced by filtering, see http://www.ncbi.nlm.nih.gov/pubmed/20026279 by Florin et al., 2010, Neuroimage. I would not recommend therefore applying PDC to source data. Other views are much welcome. Best, Carlo ________________________________ Von: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]" im Auftrag von "Subramaniam Iyer [eeguser at hotmail.com] Gesendet: Mittwoch, 27. Februar 2013 00:07 An: FieldTrip Betreff: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Jan-Mathjis Thanks for your reply. So if I understand correctly, performing PDC on EEG data can still be affected due to volume conduction, hence I will have to do source localization first. I have never done source localization before, but I will try it by going through the extensive FT documentation. However, is performing ICA before computing inverse solution recommended or is it better to simply reject artifactual sections as you mentioned even in this case ? Regards Subbu ________________________________ From: jan.schoffelen at donders.ru.nl Date: Tue, 26 Feb 2013 21:52:37 +0100 To: fieldtrip at science.ru.nl Subject: Re: [FieldTrip] Preprocessing before connectivity analysis and model order Dear Subbu, In general I would discourage people to perform connectivity analysis on (non-invasively obtained) sensor-level data, with or without ICA cleaning. If, however, you are bold enough to try, I'd recommend to discard epochs that are contaminated by eye-blinks/EMG activity etc., rather than using ICA for cleaning. The main reason is that removing topographies of artifactual components may actually inject correlations onto the recordings. I don't know the wikipedia article myself, but I would say that DTF and PDC are not immune for volume conduction. Also, it is important to keep in mind that your choice of reference is important when interpreting results. Best, Jan-Mathijs On Feb 25, 2013, at 10:52 PM, Subramaniam Iyer wrote: Dear FieldTrip users I am trying to compute PDC from a set of EEG data from 10 subjects. I have three questions regarding connectivity analysis. 1) Since the data has artifacts (EOG,EMG) , would it be alright to preprocess the data using for ex. ICA ? This wikipedia article says, its not advisable :http://en.wikipedia.org/wiki/Brain_connectivity_estimators#DTF_and_PDC_are_not_influenced_by_volume_conduction. What would be your opinion ? Is there any article that would shed some light on this ? 2) How do I compute the model order in FieldTrip ? Before that, how can I check if the data is stable and stationary before computing the MVAR model in FieldTrip ? 3) How do I compute the threshold for PDC above which I can safely assume, a link exists between two regions ? Thanks in advance. Subbu _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From sophiechen33 at gmail.com Wed Feb 27 13:51:27 2013 From: sophiechen33 at gmail.com (sophie chen) Date: Wed, 27 Feb 2013 13:51:27 +0100 Subject: [FieldTrip] troubles while reading 4D MEG files in getting the MEG channels In-Reply-To: <1538559706.484002.1361969272444.JavaMail.root@bureau-frontal1> References: <1538559706.484002.1361969272444.JavaMail.root@bureau-frontal1> Message-ID: Dear all, I am trying to read MEG 4D files with Fieldtrip version 20130226 using ft_preprocessing file with a preselection of MEG channels ( 'MEG' or a cell array of channel names, here is MEG_LABEL) but the output data contains only 152 channels while I have 248 channels... I tried the same code with Fieldtrip version 20121015, and I get everything properly (i.e. 248 channels) Following the script I am running and the corresponding results in matlab. *cfg = []; cfg.dataset = 'c,rfDC'; cfg.trialdef.eventtype = 'TRIGGER'; cfg.trialdef.eventvalue = 2; cfg.trialdef.prestim = 1; cfg.trialdef.poststim = 2; [cfg] = ft_definetrial(cfg); % cfg.channel = 'MEG'; cfg.channel = MEG_LABEL; cfg.continous = 'yes'; data_2 = ft_preprocessing (cfg)* *I get this >>* Warning: no trialfun was specified, using ft_trialfun_general > In ft_definetrial at 123 evaluating trialfunction 'ft_trialfun_general' applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_trialfun_general at 71 In ft_definetrial at 162 undoing the Supine balancing reading the events from 'c,rfDC' applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_read_event at 174 In ft_trialfun_general at 80 In ft_definetrial at 162 found 677 events created 249 trials the call to "ft_definetrial" took 5 seconds applying digital weights in the gradiometer balancing matrix Warning: all channels must have unique labels, creating unique labels > In ft_read_header at 1681 In ft_preprocessing at 394 processing channel { 'A2' 'A104' 'A241' 'A138' 'A71' 'A125' 'A20' 'A65' 'A9' 'A114' 'A175' 'A228' 'A35' 'A191' 'A37' 'A170' 'A207' 'A224' 'A82' 'A238' 'A28' 'A239' 'A13' 'A165' 'A204' 'A25' 'A70' 'A11' 'A47' 'A64' 'A177' 'A127' 'A247' 'A194' 'A5' 'A242' 'A168' 'A31' 'A245' 'A219' 'A105' 'A222' 'A76' 'A188' 'A215' 'A235' 'A181' 'A38' 'A230' 'A91' 'A212' 'A24' 'A96' 'A57' 'A86' 'A116' 'A141' 'A120' 'A80' 'A210' 'A113' 'A27' 'A135' 'A167' 'A206' 'A100' 'A43' 'A200' 'A102' 'A132' 'A122' 'A62' 'A21' 'A229' 'A55' 'A32' 'A85' 'A58' 'A60' 'A88' 'A79' 'A203' 'A145' 'A139' 'A156' 'A68' 'A159' 'A236' 'A161' 'A6' 'A126' 'A94' 'A15' 'A193' 'A150' 'A36' 'A225' 'A195' 'A172' 'A108' 'A81' 'A171' 'A218' 'A173' 'A201' 'A74' 'A29' 'A164' 'A232' 'A69' 'A157' 'A97' 'A124' 'A40' 'A178' 'A179' 'A33' 'A147' 'A148' 'A89' 'A119' 'A52' 'A190' 'A73' 'A136' 'A184' 'A51' 'A77' 'A129' 'A197' 'A182' 'A46' 'A92' 'A41' 'A90' 'A23' 'A154' 'A18' 'A248' 'A149' 'A118' 'A152' 'A140' 'A110' 'A185' 'A162' 'A106' 'A187' 'A221' 'A133' 'A158' 'A216' } reading and preprocessing reading and preprocessing trial 249 from 249 the call to "ft_preprocessing" took 20 seconds data_2 = hdr: [1x1 struct] label: {152x1 cell} time: {1x249 cell} trial: {1x249 cell} fsample: 2.0345e+03 sampleinfo: [249x2 double] trialinfo: [249x1 double] grad: [1x1 struct] cfg: [1x1 struct] *This is what I get with Fieldtrip 20121015:* Warning: no trialfun was specified, using ft_trialfun_general > In ft_definetrial at 123 evaluating trialfunction 'ft_trialfun_general' applying digital weights in the gradiometer balancing matrix undoing the Supine balancing reading the events from 'c,rfDC' applying digital weights in the gradiometer balancing matrix undoing the Supine balancing found 677 events created 249 trials the call to "ft_definetrial" took 7 seconds applying digital weights in the gradiometer balancing matrix undoing the Supine balancing processing channel { 'A22' 'A2' 'A104' 'A241' 'A138' 'A214' 'A71' 'A26' 'A93' 'A39' 'A125' 'A20' 'A65' 'A9' 'A8' 'A95' 'A114' 'A175' 'A16' 'A228' 'A35' 'A191' 'A37' 'A170' 'A207' 'A112' 'A224' 'A82' 'A238' 'A202' 'A220' 'A28' 'A239' 'A13' 'A165' 'A204' 'A233' 'A98' 'A25' 'A70' 'A72' 'A11' 'A47' 'A160' 'A64' 'A3' 'A177' 'A63' 'A155' 'A10' 'A127' 'A67' 'A115' 'A247' 'A174' 'A194' 'A5' 'A242' 'A176' 'A78' 'A168' 'A31' 'A223' 'A245' 'A219' 'A12' 'A186' 'A105' 'A222' 'A76' 'A50' 'A188' 'A231' 'A45' 'A180' 'A99' 'A234' 'A215' 'A235' 'A181' 'A38' 'A230' 'A91' 'A212' 'A24' 'A66' 'A42' 'A96' 'A57' 'A86' 'A56' 'A116' 'A151' 'A141' 'A120' 'A189' 'A80' 'A210' 'A143' 'A113' 'A27' 'A137' 'A135' 'A167' 'A75' 'A240' 'A206' 'A107' 'A130' 'A100' 'A43' 'A200' 'A102' 'A132' 'A183' 'A199' 'A122' 'A19' 'A62' 'A21' 'A229' 'A84' 'A213' 'A55' 'A32' 'A85' 'A146' 'A58' 'A60' 'A88' 'A79' 'A169' 'A54' 'A203' 'A145' 'A103' 'A163' 'A139' 'A49' 'A166' 'A156' 'A128' 'A68' 'A159' 'A236' 'A161' 'A121' 'A4' 'A61' 'A6' 'A126' 'A14' 'A94' 'A15' 'A193' 'A150' 'A227' 'A59' 'A36' 'A225' 'A195' 'A30' 'A109' 'A172' 'A108' 'A81' 'A171' 'A218' 'A173' 'A201' 'A74' 'A29' 'A164' 'A205' 'A232' 'A69' 'A157' 'A97' 'A217' 'A101' 'A124' 'A40' 'A123' 'A153' 'A178' 'A1' 'A179' 'A33' 'A147' 'A117' 'A148' 'A87' 'A89' 'A243' 'A119' 'A52' 'A142' 'A211' 'A190' 'A53' 'A192' 'A73' 'A226' 'A136' 'A184' 'A51' 'A237' 'A77' 'A129' 'A131' 'A198' 'A197' 'A182' 'A46' 'A92' 'A41' 'A90' 'A7' 'A23' 'A83' 'A154' 'A34' 'A17' 'A18' 'A248' 'A149' 'A118' 'A208' 'A152' 'A140' 'A144' 'A209' 'A110' 'A111' 'A244' 'A185' 'A246' 'A162' 'A106' 'A187' 'A48' 'A221' 'A196' 'A133' 'A158' 'A44' 'A134' 'A216' } reading and preprocessing reading and preprocessing trial 249 from 249 the call to "ft_preprocessing" took 24 seconds data_2 = hdr: [1x1 struct] label: {248x1 cell} time: {1x249 cell} trial: {1x249 cell} fsample: 2.0345e+03 sampleinfo: [249x2 double] trialinfo: [249x1 double] grad: [1x1 struct] cfg: [1x1 struct] I hope this helps to find out where the problem is coming from... Thanks in advance for your help Cheers, Sophie Chen -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 28 17:38:21 2013 From: frank.ye.mei at gmail.com (Ye Mei) Date: Thu, 28 Feb 2013 11:38:21 -0500 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well Message-ID: <512F87FD.80500@gmail.com> Hello FieldtripList, After segmentation and alignment using 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented brain seems rotated forward in the sensor helmet(brain.png) and the cerebellum part seems to be segmented out. However, his head MRI seems fitting the sensor helmet well(head.jpg). My another subject's brain seem to be correctly segmented without missing the cerebellum part. And the brain is not rotated forward. Could might be the problem? thanks ahead, Ye -------------- next part -------------- A non-text attachment was scrubbed... Name: brain.png Type: image/png Size: 15197 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: head.jpg Type: image/jpeg Size: 50294 bytes Desc: not available URL: From r.oostenveld at donders.ru.nl Thu Feb 28 17:46:39 2013 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Thu, 28 Feb 2013 17:46:39 +0100 Subject: [FieldTrip] NIHC-BrainGain Tutorial Day - March 21, 2013 In-Reply-To: <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> References: <002201ce0e9a$e18ab740$a4a025c0$@stijns@fcdonders.ru.nl> <6396F1E6-A946-4EA2-9FC5-E0345639C8EF@donders.ru.nl> Message-ID: <9741C083-F00A-4BC9-86EF-FB99715576A7@donders.ru.nl> Dear FieldTrip users, The NIHC-BrainGain Tutorial Day marks the end of the BrainGain project. For the last 6 years, the development and continued support of FieldTrip for normal/offline and realtime/online analysis has received support from the BrainGain project. There is now more information available online on this tutorial day, please see https://www.hersenenencognitie.nl/contents/1876 https://www.hersenenencognitie.nl/contents/1915 If you happen to be close to Nijmegen, you might also want to come to the "Breinfest" on Tuesday evening 19 March in the city centre with talks by international speakers and BCI demo's for the general public. Personally, I will be demonstrating how real-time data streaming and processing can be done using the FieldTrip buffer to various platforms (OS X, WIndows, Linux), to the Raspberry Pi and even to an Arduino (yes, fieldtrip runs on an arduino! ... well, a small part of it runs on an arduino). See http://www.ru.nl/breinfest for details on the evening. best regards, Robert On 19 Feb 2013, at 14:30, Robert Oostenveld wrote: > > NIHC-BrainGain Tutorial Day: > Tools and novelties in neurotechnology research > > We invite PhD students, post-docs and senior researchers working in the fields of brain-computer interfacing (BCI), neurofeedback, cognitive neuroscience, neuroinformatics, neurosurgery and related topics to our Tutorial Day on March 21st, 2013 in the Sanadome Nijmegen. > The day marks the end of the BrainGain consortium, a six-year joint-effort project on Brain-Computer Interfacing and related technologies. More information on BrainGain can be found here. > > The Tutorial Day will consist of a 'tools' track and a 'novelties’ track. The 'tools' track is intended to provide both newcomers to the field and experienced researchers with an overview of the tools needed to integrate cognitive neuroscience and advanced invasive and non-invasive technology. Topics range from data streaming to modelling and statistics, and from online fMRI decoding to a crash course in neuroethics., You will also receive some helpful insights for a future career, in case you are interested in applying for a grant in the near future or considering setting up your own company. > The 'novelties' track covers a wide range of topics indicating some of the possible topics to be further explored in BCI and neurotechnology research, including genetics, robotics and intracranial recordings. > There is no need to stick to one of the two tracks the whole day: you are free to switch between tracks any time. > > In parallel to the lectures, there will be several interesting demonstrations. > > The full programme and registration form can be found on the NIHC website (https://www.hersenenencognitie.nl). Please register before 1 March 2013. Participation is free. Lunch and drinks will be provided. > > We hope to welcome you on March 21st in Nijmegen! > > Susanna Bicknell > Radboud University Nijmegen > ____________________________________________________________________ > Faculty of Science | Finance and Economic Affairs | Project Management | LC-IMPACT > Faculty of Social Sciences | Donders Centre for Cognition | BRAINGAIN | Project Manager > T +31 24 3653300 | HG00.616 (Monday, Thursday) > Faculty of Science | IMAPP | T +31 24 3652972 | HG07.315 (Tuesday, Wednesday) > Postal address: P.O. Box 9010, 6500 GL Nijmegen, The Netherlands > Visiting and courier service address: Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip From jan.schoffelen at donders.ru.nl Thu Feb 28 18:54:14 2013 From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen) Date: Thu, 28 Feb 2013 18:54:14 +0100 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well In-Reply-To: <512F87FD.80500@gmail.com> References: <512F87FD.80500@gmail.com> Message-ID: Hi Ye, Looks like a coregistration problem to me. In other words, something went wrong in ft_volumesegment, because the images were not sufficiently aligned. You need to investigate the input and output of ft_volumesegment. Do you use ft_volumerealign after calling ft_volumesegment? This should be the other way around. Best, Jan-Mathijs On Feb 28, 2013, at 5:38 PM, Ye Mei wrote: > Hello FieldtripList, > > After segmentation and alignment using > 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented > brain seems rotated forward in the sensor helmet(brain.png) and the > cerebellum part seems to be segmented out. However, his head MRI seems > fitting the sensor helmet well(head.jpg). My another subject's brain > seem to be correctly segmented without missing the cerebellum part. And > the brain is not rotated forward. > > Could might be the problem? > > thanks ahead, > Ye > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip Jan-Mathijs Schoffelen, MD PhD Donders Institute for Brain, Cognition and Behaviour, Centre for Cognitive Neuroimaging, Radboud University Nijmegen, The Netherlands Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands J.Schoffelen at donders.ru.nl Telephone: +31-24-3614793 -------------- next part -------------- An HTML attachment was scrubbed... URL: From frank.ye.mei at gmail.com Thu Feb 28 23:09:57 2013 From: frank.ye.mei at gmail.com (Ye Mei) Date: Thu, 28 Feb 2013 17:09:57 -0500 Subject: [FieldTrip] segmented brain seems not fitting the sensor helmet well In-Reply-To: References: Message-ID: <512FD5B5.8080700@gmail.com> Hello All, I found the problem I mentioned in the previous email was caused by using "mri_sliced = ft_volumereslice([], mri);" before using ft_volumesegment. After erasing the line "mri_sliced = ft_volumereslice([], mri);", the segmented brain seems to be normal and fits the sensor helmet well now, as show in the attached figure(notvolumnsliced.jpg). For another of my subject, if the "ft_volumereslice" is included, the brain looks sliced on the top(subject2vs.jpg). If no "ft_volumreslice" it looks normal(subject2.jpg). I notice in the fieldtrip headmodel tutorial (http://fieldtrip.fcdonders.nl/tutorial/headmodel_meg), "ft_volumereslice" is not used. but in the field trip beamformer tutorial(http://fieldtrip.fcdonders.nl/tutorial/beamformer), it is used. I am wondering if I should include "ft_volumereslice" in my source localization code. Can anyone give me some suggestions? thanks ahead, Ye On 13-02-28 11:45 AM, fieldtrip-request at science.ru.nl wrote: > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > or, via email, send a message with subject or body 'help' to > fieldtrip-request at science.ru.nl > > You can reach the person managing the list at > fieldtrip-owner at science.ru.nl > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of fieldtrip digest..." > > > Today's Topics: > > 1. segmented brain seems not fitting the sensor helmet well (Ye Mei) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Thu, 28 Feb 2013 11:38:21 -0500 > From: Ye Mei > To: fieldtrip at science.ru.nl > Subject: [FieldTrip] segmented brain seems not fitting the sensor > helmet well > Message-ID: <512F87FD.80500 at gmail.com> > Content-Type: text/plain; charset="iso-8859-1"; Format="flowed" > > Hello FieldtripList, > > After segmentation and alignment using > 'ft_volumesegment' and 'ft_volumerealign', one of the subjects' segmented > brain seems rotated forward in the sensor helmet(brain.png) and the > cerebellum part seems to be segmented out. However, his head MRI seems > fitting the sensor helmet well(head.jpg). My another subject's brain > seem to be correctly segmented without missing the cerebellum part. And > the brain is not rotated forward. > > Could might be the problem? > > thanks ahead, > Ye > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: brain.png > Type: image/png > Size: 15197 bytes > Desc: not available > URL: > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: head.jpg > Type: image/jpeg > Size: 50294 bytes > Desc: not available > URL: > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 27, Issue 31 > ***************************************** -------------- next part -------------- A non-text attachment was scrubbed... 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