From jumana.ahmad at kcl.ac.uk Mon Jul 3 15:15:34 2017 From: jumana.ahmad at kcl.ac.uk (Ahmad, Jumana) Date: Mon, 3 Jul 2017 13:15:34 +0000 Subject: [FieldTrip] inter trial coherence statistics Message-ID: Dear all, I have been struggling for awhile with inter trial coherence statistics. I found the ITC stats fun function online with cfg.statistic = 'diff_itc' I cannot get it to work. I have 300 participants per group, and a between subject design with only one outcome measure. I therefore wanted something akin to permutation between groups. However, when I use the ITC stats fun function, it complains if the design matrix is not as long as all the files across all participants so it becomes more like a single subject comparison. Has anybody had any luck using this function between groups, or with multiple people? If so, would it be OK to share a sample of your code or key parameters? Thank you very much, Jumana ------------------------------------------ Jumana Ahmad Post-Doctoral Research Worker in Cognitive Neuroscience EU-AIMS Longitudinal European Autism Project (LEAP) & SynaG Study Room M1.26.Department of Forensic and Neurodevelopmental Sciences (PO 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College London | 16 De Crespigny Park | London SE5 8AF Phone: 0207 848 5359| Email: jumana.ahmad at kcl.ac.uk | Website: www.eu-aims.eu | Facebook: www.facebook.com/euaims -------------- next part -------------- An HTML attachment was scrubbed... URL: From martabortoletto at yahoo.it Mon Jul 3 16:17:03 2017 From: martabortoletto at yahoo.it (Marta Bortoletto) Date: Mon, 3 Jul 2017 14:17:03 +0000 (UTC) Subject: [FieldTrip] Workshop - Ten years of Mind/Brain Sciences at the University of Trento - CIMeC, Italy References: <418890791.6270044.1499091423986.ref@mail.yahoo.com> Message-ID: <418890791.6270044.1499091423986@mail.yahoo.com> Tocelebrate its 10th anniversary, the Center for Mind/Brain Sciences (CIMeC) organizes a workshop on thefuture of cognitive neuroscience.WHERE and WHEN: The workshop will be held in Rovereto, Italy on October 19-21, 2017. WHAT: The themeof the event will be centered around the question: “Where do cognitiveneuroscientists see Mind/Brain Sciences in ten years?”Deadline for poster submission: September 1st. Workshop website: http://events.unitn.it/en/cimec-ten-yearsThe workshop has a limited number of availableplaces. Potential attendees are encouraged to register online as soon aspossible.Invited speakers:·       Cristina Becchio - Universityof Torino, Italy·       Nadia Bolognini - Universityof Milano Bicocca, Italy·       Ruth Byrne -Trinity College Dublin, Ireland·       Marco Catani - KingCollege London, UK·       Gustavo Deco - PompeuFabra Univesity, Spain·       Scott Fairhall -University of Trento, Italy·       Randy Gallistel -Rutgers University, USA·       Melvyn Goodale -Western University, Canada·       Patrick Haggard -University College London, UK·       Takao Hensch -Harvard University, USA·       Zoe Kourtzi -Cambridge University, UK·       Nikos Logothetis -Max Planck Institute, Germany·       Emiliano Macaluso -University of Lyon, France·       Tamar Makin -University College London, UK·       Alex Martin -National Institute of Mental Health, USA·       Louise McNally -Pompeu Fabra University, Spain·       Satu Palva -University of Helsinki, Finland·       Stefano Panzeri - ItalianInstitute of Technology, Italy·       David Poeppel -New York University, USA·       Tim Shallice -University College London, UK·       Antonino Vallesi -University of Padova, ItalyWe look forward to seeing you there.The Organizing CommitteeCarlo Miniussi, Yuri Bozzi, Veronica Mazza, FrancescoPavani, Luca Turella, Massimiliano Zampini.  Marta Bortoletto, PhD Cognitive Neuroscience Section, IRCCS Centro San Giovanni di Dio Fatebenefratelli Via Pilastroni 4, 25125 Brescia, Italy Phone number: (+39) 0303501594 E-mail: marta.bortoletto at cognitiveneuroscience.it web: http://www.cognitiveneuroscience.it/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Tue Jul 4 15:21:56 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Tue, 4 Jul 2017 13:21:56 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? References: <1460287005.7559270.1499174516032.ref@mail.yahoo.com> Message-ID: <1460287005.7559270.1499174516032@mail.yahoo.com> Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence). With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal). I hope this helps. Best,Maité El Jueves 29 de junio de 2017 12:24, Maria Hakonen escribió: Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.a.sprenger at rug.nl Tue Jul 4 16:56:51 2017 From: s.a.sprenger at rug.nl (Sprenger, S.A.) Date: Tue, 4 Jul 2017 16:56:51 +0200 Subject: [FieldTrip] How to adapt a layout file Message-ID: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/ template/layout/easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 18:03:47 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 16:03:47 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials Message-ID: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Hi everyone, I am now trying to use the DICS method for sourceanalysis, with 'powandcsd' output from ft_freqanalysis as its input and using a precomputed filter and leadfield. However, I would like to keep my separate trial estimates in the final source analysis, and while the documentation suggests I should be able to get that with cfg.keeptrials, but this doesn't have the expected effect. I previously made workaround using PCC on fourier data instead (see below), I think to deal with this issue. I was wondering if this is still the recommended option, i.e. workaround? Alternatively, and perhaps preferably, would someone have a suggestion for a solution consistent with the DICS implementation? Thanks for your time, Stephen % source analysis cfg.method = 'pcc'; ... cfg.keeptrials = 'yes'; cfg.pcc.keepmom = 'yes'; cfg.pcc.fixedori = 'no'; source_control = ft_sourceanalysis(cfg, FFT); and then: % project moment and tapers cfg = []; cfg.projectmom = 'no'; cfg.keeptrials = 'yes'; cfg.powmethod = 'lambda1'; source = ft_sourcedescriptives(cfg,source); -------------- next part -------------- An HTML attachment was scrubbed... URL: From magazzinil at gmail.com Tue Jul 4 18:32:27 2017 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Tue, 4 Jul 2017 17:32:27 +0100 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, Perhaps you could try to add the option cfg.rawtrial = 'yes'. I'm not entirely sure, but maybe by using a precomputed filter, the same filter is applied to each single trial separately (rather than constructing a different filter individually for each trial, which I guess is not what you want to do). Lorenzo Lorenzo Magazzini, PhD Research Associate CUBRIC Cardiff University Cardiff CF24 4HQ Tel: +44 (0)2920 870090 *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php * On 4 July 2017 at 17:03, Stephen Whitmarsh wrote: > Hi everyone, > > I am now trying to use the DICS method for sourceanalysis, with > 'powandcsd' output from ft_freqanalysis as its input and using a > precomputed filter and leadfield. However, I would like to keep my separate > trial estimates in the final source analysis, and while the documentation > suggests I should be able to get that with cfg.keeptrials, but this doesn't > have the expected effect. > > I previously made workaround using PCC on fourier data instead (see > below), I think to deal with this issue. I was wondering if this is still > the recommended option, i.e. workaround? Alternatively, and perhaps > preferably, would someone have a suggestion for a solution consistent with > the DICS implementation? > > Thanks for your time, > Stephen > > % source analysis > cfg.method = 'pcc'; > ... > cfg.keeptrials = 'yes'; > cfg.pcc.keepmom = 'yes'; > cfg.pcc.fixedori = 'no'; > source_control = ft_sourceanalysis(cfg, FFT); > > and then: > > % project moment and tapers > cfg = []; > cfg.projectmom = 'no'; > cfg.keeptrials = 'yes'; > cfg.powmethod = 'lambda1'; > source = ft_sourcedescriptives(cfg,source); > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 18:51:47 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 18:51:47 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Lorenzo, Thanks, I will give it a try tomorrow, but the documentation suggest that it's not what I want: Just for clarity, I would like to use the same filter on separate trials. Best wishes, Stephen On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > Hi Stephen, > > Perhaps you could try to add the option cfg.rawtrial = 'yes'. > > I'm not entirely sure, but maybe by using a precomputed filter, the same > filter is applied to each single trial separately (rather than constructing > a different filter individually for each trial, which I guess is not what > you want to do). > > Lorenzo > > > > Lorenzo Magazzini, PhD > > Research Associate > > CUBRIC > > Cardiff University > > Cardiff CF24 4HQ > > Tel: +44 (0)2920 870090 <+44%2029%202087%200090> > > *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php > * > > > > > On 4 July 2017 at 17:03, Stephen Whitmarsh > wrote: > >> Hi everyone, >> >> I am now trying to use the DICS method for sourceanalysis, with >> 'powandcsd' output from ft_freqanalysis as its input and using a >> precomputed filter and leadfield. However, I would like to keep my separate >> trial estimates in the final source analysis, and while the documentation >> suggests I should be able to get that with cfg.keeptrials, but this doesn't >> have the expected effect. >> >> I previously made workaround using PCC on fourier data instead (see >> below), I think to deal with this issue. I was wondering if this is still >> the recommended option, i.e. workaround? Alternatively, and perhaps >> preferably, would someone have a suggestion for a solution consistent with >> the DICS implementation? >> >> Thanks for your time, >> Stephen >> >> % source analysis >> cfg.method = 'pcc'; >> ... >> cfg.keeptrials = 'yes'; >> cfg.pcc.keepmom = 'yes'; >> cfg.pcc.fixedori = 'no'; >> source_control = ft_sourceanalysis(cfg, FFT); >> >> and then: >> >> % project moment and tapers >> cfg = []; >> cfg.projectmom = 'no'; >> cfg.keeptrials = 'yes'; >> cfg.powmethod = 'lambda1'; >> source = ft_sourcedescriptives(cfg,source); >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiew1202 at gmail.com Tue Jul 4 19:36:55 2017 From: xiew1202 at gmail.com (Xie Wanze) Date: Tue, 04 Jul 2017 17:36:55 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, I met the same issue last year when I did my source analysis and functional connectivity analysis. I asked it through the maillist but no one seemed to have an answer. What I ended up with doing was to maunally calculate the source analysis with the spatial filter for each single trial. So,1. Use the ft_sourceanalysis to get the filter. 2. Multiply the filter with your single trial data with a loop or whatever. Wanze Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > Hi Lorenzo, > > Thanks, I will give it a try tomorrow, but the documentation suggest that > it's not what I want: Just for clarity, I would like to use the same filter > on separate trials. > > Best wishes, > Stephen > > On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > >> Hi Stephen, >> >> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >> >> I'm not entirely sure, but maybe by using a precomputed filter, the same >> filter is applied to each single trial separately (rather than constructing >> a different filter individually for each trial, which I guess is not what >> you want to do). >> >> Lorenzo >> >> >> >> Lorenzo Magazzini, PhD >> >> Research Associate >> >> CUBRIC >> >> Cardiff University >> >> Cardiff CF24 4HQ >> >> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >> >> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >> * >> >> >> >> >> On 4 July 2017 at 17:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiew1202 at gmail.com Tue Jul 4 19:38:15 2017 From: xiew1202 at gmail.com (Xie Wanze) Date: Tue, 04 Jul 2017 17:38:15 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: I mean manually calculated the filter with ft source analysis. Sorry for my typo in my last email. Good luck. Wanze Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > Hi Lorenzo, > > Thanks, I will give it a try tomorrow, but the documentation suggest that > it's not what I want: Just for clarity, I would like to use the same filter > on separate trials. > > Best wishes, > Stephen > > On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > >> Hi Stephen, >> >> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >> >> I'm not entirely sure, but maybe by using a precomputed filter, the same >> filter is applied to each single trial separately (rather than constructing >> a different filter individually for each trial, which I guess is not what >> you want to do). >> >> Lorenzo >> >> >> >> Lorenzo Magazzini, PhD >> >> Research Associate >> >> CUBRIC >> >> Cardiff University >> >> Cardiff CF24 4HQ >> >> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >> >> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >> * >> >> >> >> >> On 4 July 2017 at 17:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 19:48:56 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 19:48:56 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Wanze, Sorry to hear you didn't get a response last year, but thanks for sharing yours! Indeed, that seems to be the most elegant work-around to me as well. I'll probably do that. Thanks! Stephen On 4 July 2017 at 19:38, Xie Wanze wrote: > I mean manually calculated the filter with ft source analysis. Sorry for > my typo in my last email. > > Good luck. > > Wanze > Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > >> Hi Lorenzo, >> >> Thanks, I will give it a try tomorrow, but the documentation suggest that >> it's not what I want: Just for clarity, I would like to use the same filter >> on separate trials. >> >> Best wishes, >> Stephen >> >> On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: >> >>> Hi Stephen, >>> >>> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >>> >>> I'm not entirely sure, but maybe by using a precomputed filter, the same >>> filter is applied to each single trial separately (rather than constructing >>> a different filter individually for each trial, which I guess is not what >>> you want to do). >>> >>> Lorenzo >>> >>> >>> >>> Lorenzo Magazzini, PhD >>> >>> Research Associate >>> >>> CUBRIC >>> >>> Cardiff University >>> >>> Cardiff CF24 4HQ >>> >>> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >>> >>> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >>> * >>> >>> >>> >>> >>> On 4 July 2017 at 17:03, Stephen Whitmarsh >>> wrote: >>> >>>> Hi everyone, >>>> >>>> I am now trying to use the DICS method for sourceanalysis, with >>>> 'powandcsd' output from ft_freqanalysis as its input and using a >>>> precomputed filter and leadfield. However, I would like to keep my separate >>>> trial estimates in the final source analysis, and while the documentation >>>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>>> have the expected effect. >>>> >>>> I previously made workaround using PCC on fourier data instead (see >>>> below), I think to deal with this issue. I was wondering if this is still >>>> the recommended option, i.e. workaround? Alternatively, and perhaps >>>> preferably, would someone have a suggestion for a solution consistent with >>>> the DICS implementation? >>>> >>>> Thanks for your time, >>>> Stephen >>>> >>>> % source analysis >>>> cfg.method = 'pcc'; >>>> ... >>>> cfg.keeptrials = 'yes'; >>>> cfg.pcc.keepmom = 'yes'; >>>> cfg.pcc.fixedori = 'no'; >>>> source_control = ft_sourceanalysis(cfg, FFT); >>>> >>>> and then: >>>> >>>> % project moment and tapers >>>> cfg = []; >>>> cfg.projectmom = 'no'; >>>> cfg.keeptrials = 'yes'; >>>> cfg.powmethod = 'lambda1'; >>>> source = ft_sourcedescriptives(cfg,source); >>>> >>>> >>>> >>>> _______________________________________________ >>>> fieldtrip mailing list >>>> fieldtrip at donders.ru.nl >>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Wed Jul 5 08:51:13 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Wed, 5 Jul 2017 06:51:13 +0000 Subject: [FieldTrip] Fwd: How to adapt a layout file References: Message-ID: <2D579D2D-F542-4FC2-A1A8-C0FCED73CC51@donders.ru.nl> Hi Simone, What is the question behind the question? The reason I ask this is because overcomplete layout files (i.e. files containing more channels than you need) don’t prevent you from visualizing your own data. If you anyhow want to manually remove channels (and the corresponding information in pos/height etc) your code is not foolproof, most likely because setdiff may inadvertently alphabetize the labels, causing the mismatch you report. you could do: remove = {…}; sel = ismember(lay.label, remove); lay.pos = lay.pos(~sel,:); lay.height = lay.height(~sel); etc. Best, Jan-Mathijs On 04 Jul 2017, at 16:56, Sprenger, S.A. > wrote: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/template/layout/easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Wed Jul 5 10:40:39 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Wed, 5 Jul 2017 11:40:39 +0300 Subject: [FieldTrip] dipin and refdip in beamformer_dics? Message-ID: Dear Fieldtrip experts, As far as I understand, beamformer_dics gives coherence between two brain areas if I define parameters dipin and refdip. Could you please let me kown how dipin and refdip should be calculated or in which format they should be? Best, Maria -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.a.sprenger at rug.nl Thu Jul 6 10:11:05 2017 From: s.a.sprenger at rug.nl (Sprenger, S.A.) Date: Thu, 6 Jul 2017 10:11:05 +0200 Subject: [FieldTrip] How to adapt a layout file: thanks for the solution Message-ID: Dear Jan-Mathijs, Thank you very much for your response with respect to the adaption of layout files. The solution that you suggested works fine and our issue has been solved. In case someone would like to review the question and response, please see below. Kind regards, Simone ____________ Message: 9 Date: Wed, 5 Jul 2017 06:51:13 +0000 From: "Schoffelen, J.M. (Jan Mathijs)" To: FieldTrip discussion list Subject: [FieldTrip] Fwd: How to adapt a layout file Message-ID: <2D579D2D-F542-4FC2-A1A8-C0FCED73CC51 at donders.ru.nl> Content-Type: text/plain; charset="utf-8" Hi Simone, What is the question behind the question? The reason I ask this is because overcomplete layout files (i.e. files containing more channels than you need) don?t prevent you from visualizing your own data. If you anyhow want to manually remove channels (and the corresponding information in pos/height etc) your code is not foolproof, most likely because setdiff may inadvertently alphabetize the labels, causing the mismatch you report. you could do: remove = {?}; sel = ismember(lay.label, remove); lay.pos = lay.pos(~sel,:); lay.height = lay.height(~sel); etc. Best, Jan-Mathijs On 04 Jul 2017, at 16:56, Sprenger, S.A. > wrote: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/template/layout/ easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 -------------- next part -------------- An HTML attachment was scrubbed... URL: From orekhova.elena.v at gmail.com Thu Jul 6 16:57:07 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Thu, 6 Jul 2017 16:57:07 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Just recently had the same problem. It worked with cfg.rawtrial='yes'. Best, Elena On 4 July 2017 at 18:03, Stephen Whitmarsh wrote: > Hi everyone, > > I am now trying to use the DICS method for sourceanalysis, with > 'powandcsd' output from ft_freqanalysis as its input and using a > precomputed filter and leadfield. However, I would like to keep my separate > trial estimates in the final source analysis, and while the documentation > suggests I should be able to get that with cfg.keeptrials, but this doesn't > have the expected effect. > > I previously made workaround using PCC on fourier data instead (see > below), I think to deal with this issue. I was wondering if this is still > the recommended option, i.e. workaround? Alternatively, and perhaps > preferably, would someone have a suggestion for a solution consistent with > the DICS implementation? > > Thanks for your time, > Stephen > > % source analysis > cfg.method = 'pcc'; > ... > cfg.keeptrials = 'yes'; > cfg.pcc.keepmom = 'yes'; > cfg.pcc.fixedori = 'no'; > source_control = ft_sourceanalysis(cfg, FFT); > > and then: > > % project moment and tapers > cfg = []; > cfg.projectmom = 'no'; > cfg.keeptrials = 'yes'; > cfg.powmethod = 'lambda1'; > source = ft_sourcedescriptives(cfg,source); > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Thu Jul 6 18:03:51 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Thu, 6 Jul 2017 18:03:51 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Elena! Thanks! But I do wonder.. did you check whether the common filter (specified in the cfg) was used or whether a filter was calculated for each trial separately (which does not make sense in my case)? Best, Stephen On 6 July 2017 at 16:57, Elena Orekhova wrote: > Just recently had the same problem. > It worked with cfg.rawtrial='yes'. > > Best, > Elena > > On 4 July 2017 at 18:03, Stephen Whitmarsh > wrote: > >> Hi everyone, >> >> I am now trying to use the DICS method for sourceanalysis, with >> 'powandcsd' output from ft_freqanalysis as its input and using a >> precomputed filter and leadfield. However, I would like to keep my separate >> trial estimates in the final source analysis, and while the documentation >> suggests I should be able to get that with cfg.keeptrials, but this doesn't >> have the expected effect. >> >> I previously made workaround using PCC on fourier data instead (see >> below), I think to deal with this issue. I was wondering if this is still >> the recommended option, i.e. workaround? Alternatively, and perhaps >> preferably, would someone have a suggestion for a solution consistent with >> the DICS implementation? >> >> Thanks for your time, >> Stephen >> >> % source analysis >> cfg.method = 'pcc'; >> ... >> cfg.keeptrials = 'yes'; >> cfg.pcc.keepmom = 'yes'; >> cfg.pcc.fixedori = 'no'; >> source_control = ft_sourceanalysis(cfg, FFT); >> >> and then: >> >> % project moment and tapers >> cfg = []; >> cfg.projectmom = 'no'; >> cfg.keeptrials = 'yes'; >> cfg.powmethod = 'lambda1'; >> source = ft_sourcedescriptives(cfg,source); >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From explena at gmail.com Fri Jul 7 05:21:58 2017 From: explena at gmail.com (Shen-Mou Hsu) Date: Fri, 7 Jul 2017 11:21:58 +0800 Subject: [FieldTrip] a question regarding the code for PPC computation Message-ID: Dear FT users, I am writing to request how pairwise phase consistency (PPC) is implemented in Fieldtrip. I trace the code and find that the following lines are relevant for PPC computation input = input./abs(input); % normalize the crosspectrum outsum = nansum(input); % compute the sum; this is 1 x size(2:end) c = (outsum.*conj(outsum) - n)./(n*(n-1)); % do the pairwise thing in a handy way However, when I try to verify the results by performing the equations indicated by Vinck et. al. (2010), the outcomes are totally different from those performed using ft_connectivity_ppc. My code is as follows and many thanks for any help. %%%%%%%%%%%%%%%%%%%%%%%%% nTrial = size(input,1); ppc_all = []; for j = 1:(nTrial-1) for k = (j+1):nTrial ppc_temp = input(j,1,:,:).*conj(input(k,1,:,:)); ppc_all = [ppc_all;ppc_temp]; end end PPC = squeeze(abs(nansum(ppc_all,1)*2/(nTrial*(nTrial-1)))); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Best, Shen-Mou Hsu -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Fri Jul 7 08:08:10 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Fri, 7 Jul 2017 09:08:10 +0300 Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence). With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal). I hope this helps. Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions. Best, Maria 2017-06-29 12:57 GMT+03:00 Maria Hakonen : > Hi Maria, > for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. > > Best,Maité > http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series > http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series > > Hi Maité, > > Thank for your answer again! > > However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics? > > Best, > > Maria > > > 2017-06-26 12:45 GMT+03:00 Maria Hakonen : > >> Hi Maria, >> maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. >> >> Best,Maité >> >> >> Hi Maité, >> >> Could you please yet let me know how to get the sources timecources? >> source = ft_sourceanalysis(cfg, freq); only gives >> source = >> >> freq: 18 >> cumtapcnt: [180x1 double] >> dim: [19 15 15] >> inside: [4275x1 logical] >> pos: [4275x3 double] >> method: 'average' >> avg: [1x1 struct] >> cfg: [1x1 struct] >> >> Best, >> Maria >> >> 2017-06-25 13:53 GMT+03:00 Maria Hakonen : >> >>> Hi Maité, >>> >>> Thank you for your answer! >>> >>> I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.org/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this? >>> >>> BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum. >>> >>> Best, >>> >>> Maria >>> >>> >>> Hi Maria, >>> Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: >>> >>> cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; >>> cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; >>> As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. >>> I hope it helps. >>> Best wishes,Maité >>> >>> >>> >>> Dear FieldTrip experts, >>> >>> I have just started to use Fieldtrip and would like to estimate >>> coherence between MEG responses measured in two different conditions from >>> the same cortical areas. The example in Appendix 1 is close to what I would >>> like to do: >>> http://www.fieldtriptoolbox.org/tutorial/coherence >>> >>> However, in the example, coherence is calculated between the reference >>> signal (EMG) and all MEG channels. Could it be possible to calculate >>> coherence between each MEG channel in one condition and the same MEG >>> channels in the other condition, that is: >>> ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... >>> >>> As far as I understand, the example in Appendix 1 would do this: >>> ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in >>> cond2, ... >>> >>> Best, >>> Maria >>> >>> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From christian.merkel at med.ovgu.de Fri Jul 7 09:19:06 2017 From: christian.merkel at med.ovgu.de (christian.merkel at med.ovgu.de) Date: Fri, 7 Jul 2017 07:19:06 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis Message-ID: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> Hallo to all, My name is Christian Merkel and im using fieldtrip to estimate sources within the visual cortex using high-res sourcemodels from freesurfer. We use an elekta system in our lab. I have a question regarding the time course of activation within the sourcespace once i calculated the spatial filter with ft_sourceanalysis. Here the code for ft_sourceanalysis: cfg = []; cfg.method = 'lcmv'; cfg.channel = sens_aligned.label(strcmp(sens_aligned.chantype,'megplanar')); cfg.grid = lead field_grad; cfg.vol = bem; cfg.projectnoise = 'yes'; cfg.keepfilter = 'yes'; cfg.lambda = 1; data_erf_source = ft_sourceanalysis(cfg, data_cond_erf_bl_avg); The filter looks good and everything works fine. However I have a conceptual question about the timecourse in sourcespace: As far as I understand, the field avg.mom of data_erf_source contains the activation time_course. So to plot one specific sourcedistribution at one time sample I use: pow = squeeze(sort(sum(cat(3,data_erf_source.avg.mom{:}).^2,1)))'; % i use the abs norm of the 3 orientation vectors as a value of source strength figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow(:,time_of_interest)); One other way to get the source distribution at that sample is to convolve the filter with the underlying erf-data: pow = squeeze(sort(sum(cat(3,data_erf_source.avg.filter{:}).^2,1)))'; figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow * data_cond_erf_bl_avg.avg(:,time_of_interest)); But those to distributions look different. Not completely different, but substantially. Why are those two ways of calculating the source-distribution different. I thought that ft_sourceanalysis calculates the field 'mom' by basically convolving the erf_data with the spatial filter and therefore should result in the same distribution as the second version. What is the 'right' way in this case and what do you recommend I use. I thank you for your help. From jan.schoffelen at donders.ru.nl Fri Jul 7 10:13:31 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 7 Jul 2017 08:13:31 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis In-Reply-To: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> References: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> Message-ID: Dear Christian, > pow = squeeze(sort(sum(cat(3,data_erf_source.avg.mom{:}).^2,1)))'; % i use the abs norm of the 3 orientation vectors as a value of source strength > figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow(:,time_of_interest)); > > One other way to get the source distribution at that sample is to convolve the filter with the underlying erf-data: > > pow = squeeze(sort(sum(cat(3,data_erf_source.avg.filter{:}).^2,1)))'; > figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow * data_cond_erf_bl_avg.avg(:,time_of_interest)); > > > But those to distributions look different. Not completely different, but substantially. Well, let me first be a bit pedantic, by saying that one does not ‘convolve’ the filter with the underlying erf-data, it’s just a multiplication. But no worries, that’s just terminology. The thing that goes wrong in your filter-times-erfdata step, is the fact that you already collapse the spatial filter across the three dipole orientations (and take the square), prior to doing the multiplication. So the difference lies in the order of the operations, it should be sum((F*sensorERF).^2,1). In this case F is a single entry from source.avg.filter. Best, Jan-Mathijs > Why are those two ways of calculating the source-distribution different. I thought that ft_sourceanalysis calculates the field 'mom' by basically convolving the erf_data with the spatial filter and therefore should result in the same distribution as the second version. What is the 'right' way in this case and what do you recommend I use. > > I thank you for your help. > > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From christian.merkel at med.ovgu.de Fri Jul 7 10:28:54 2017 From: christian.merkel at med.ovgu.de (christian.merkel at med.ovgu.de) Date: Fri, 7 Jul 2017 08:28:54 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis In-Reply-To: References: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de>, Message-ID: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D46@esen3.imed.uni-magdeburg.de> Thanks a lot, That makes sense!! I have one follow-up question: What if i want to correct with the noise-term? Should i do that on the single orientations as well or just after the multiplication? I could imagine after, as for the mom-field i can only apply it to the end-result anyway. You're a big help, Christian From orekhova.elena.v at gmail.com Fri Jul 7 10:31:37 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 10:31:37 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, I followed the tutorial in http://www.fieldtriptoolbox.org/tutorial/salzburg, but used 'dics' (see below). I think that in the example below the sourceavg.avg.filter was indeed used and my results look nice. Elena cfg=[];cfg.method='lcmv';cfg.grid =grid ;cfg.grid .filter =sourceavg.avg.filter ;cfg.rawtrial = 'yes';cfg.vol=hdm; sourcepreS1=ft_sourceanalysis(cfg, avgpre); sourcepstS1=ft_sourceanalysis(cfg, avgpst); On 6 July 2017 at 18:03, Stephen Whitmarsh wrote: > Hi Elena! > > Thanks! But I do wonder.. did you check whether the common filter > (specified in the cfg) was used or whether a filter was calculated for each > trial separately (which does not make sense in my case)? > > Best, > Stephen > > On 6 July 2017 at 16:57, Elena Orekhova > wrote: > >> Just recently had the same problem. >> It worked with cfg.rawtrial='yes'. >> >> Best, >> Elena >> >> On 4 July 2017 at 18:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Fri Jul 7 10:57:17 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Fri, 7 Jul 2017 10:57:17 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Elena, Thanks for the link - that is indeed a very nice and complete tutorial! A link in the current beamformer tutorial would be helpful for the next time I think - I will put one there. And yes, I see now that although the documentation is as follows: % cfg.rawtrial = 'no' or 'yes' *construct filter from single trials*, apply to single trials. Note that you also may want to set cfg.keeptrials='yes' to keep all trial information, especially if using in combination with grid.filter (I find the red part inconsistent) it does take the pre-specified filter when provided, which is suggested somewhat implicitly further down in the code: if strcmp(cfg.rawtrial,'yes') && isfield(cfg,'grid') && ~isfield(cfg.grid,'filter') warning('Using each trial to compute its own filter is not currently recommended. Use this option only with precomputed filters in grid.filter'); end So that really clears it up. I will suggest an edit to the documentation, for the sake of clarification, and next time I run my beamformer I will remove the loop over trials :-) Thanks again, Stephen On 7 July 2017 at 10:31, Elena Orekhova wrote: > Hi Stephen, > I followed the tutorial in http://www.fieldtriptoolbox.or > g/tutorial/salzburg, but used 'dics' (see below). > I think that in the example below the sourceavg.avg.filter was indeed > used and my results look nice. > > Elena > > cfg=[];cfg.method='lcmv';cfg.grid =grid ;cfg.grid .filter =sourceavg.avg.filter ;cfg.rawtrial = 'yes';cfg.vol=hdm; > sourcepreS1=ft_sourceanalysis(cfg, avgpre); > sourcepstS1=ft_sourceanalysis(cfg, avgpst); > > > > On 6 July 2017 at 18:03, Stephen Whitmarsh > wrote: > >> Hi Elena! >> >> Thanks! But I do wonder.. did you check whether the common filter >> (specified in the cfg) was used or whether a filter was calculated for each >> trial separately (which does not make sense in my case)? >> >> Best, >> Stephen >> >> On 6 July 2017 at 16:57, Elena Orekhova >> wrote: >> >>> Just recently had the same problem. >>> It worked with cfg.rawtrial='yes'. >>> >>> Best, >>> Elena >>> >>> On 4 July 2017 at 18:03, Stephen Whitmarsh >>> wrote: >>> >>>> Hi everyone, >>>> >>>> I am now trying to use the DICS method for sourceanalysis, with >>>> 'powandcsd' output from ft_freqanalysis as its input and using a >>>> precomputed filter and leadfield. However, I would like to keep my separate >>>> trial estimates in the final source analysis, and while the documentation >>>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>>> have the expected effect. >>>> >>>> I previously made workaround using PCC on fourier data instead (see >>>> below), I think to deal with this issue. I was wondering if this is still >>>> the recommended option, i.e. workaround? Alternatively, and perhaps >>>> preferably, would someone have a suggestion for a solution consistent with >>>> the DICS implementation? >>>> >>>> Thanks for your time, >>>> Stephen >>>> >>>> % source analysis >>>> cfg.method = 'pcc'; >>>> ... >>>> cfg.keeptrials = 'yes'; >>>> cfg.pcc.keepmom = 'yes'; >>>> cfg.pcc.fixedori = 'no'; >>>> source_control = ft_sourceanalysis(cfg, FFT); >>>> >>>> and then: >>>> >>>> % project moment and tapers >>>> cfg = []; >>>> cfg.projectmom = 'no'; >>>> cfg.keeptrials = 'yes'; >>>> cfg.powmethod = 'lambda1'; >>>> source = ft_sourcedescriptives(cfg,source); >>>> >>>> >>>> >>>> _______________________________________________ >>>> fieldtrip mailing list >>>> fieldtrip at donders.ru.nl >>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Fri Jul 7 11:17:16 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Fri, 7 Jul 2017 09:17:16 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: <35126809.503758.1499419036176@mail.yahoo.com> Hi Maria, You are right. I was having a look inside the "inverse\beamformer_dics" function (I suggest you check it out too). As you could see in line 519 of the same function, refdip can be an structure with a field called 'filter' containing the beamformer filter for a particular voxel (brain region of condition 2, for example). So, you could first compute the DICS filters for condition 2 and then passing them one by one in the cfg,refdip when calling the ft_sourceanalysis together with the data of condition 1. I hope this works out. Best wishes,Maité El Viernes 7 de julio de 2017 8:23, Maria Hakonen escribió: Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence).With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal).I hope this helps.  Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions.  Best,Maria    2017-06-29 12:57 GMT+03:00 Maria Hakonen : Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox. org/tutorial/connectivity# extract_the_virtual_channel_ time-series http://www.fieldtriptoolbox. org/tutorial/shared/virtual_ sensors#extract_the_virtual_ channel_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Fri Jul 7 11:25:06 2017 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Fri, 7 Jul 2017 10:25:06 +0100 Subject: [FieldTrip] PhD positions in Birmingham, UK with Prof. Noppeney Message-ID: Dear all, Prof. Uta Noppeney (with whom I now work) has available these 2 PhD positions for an exciting new project: 1. Robust audiovisual speech recognition in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87556 2. Syntactic parsing in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87595 Please contact Uta (U.Noppeney at bham.ac.uk) with any questions. Kind regards, Johanna -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Fri Jul 7 11:41:51 2017 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Fri, 7 Jul 2017 10:41:51 +0100 Subject: [FieldTrip] PhD positions in Birmingham, UK with Prof. Noppeney Message-ID: Dear all, Prof. Uta Noppeney (with whom I now work) has available these 2 PhD positions for an exciting new project: 1. Robust audiovisual speech recognition in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87556 2. Syntactic parsing in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87595 Please contact Uta (U.Noppeney at bham.ac.uk) with any questions. Kind regards, Johanna -------------- next part -------------- An HTML attachment was scrubbed... URL: From orekhova.elena.v at gmail.com Fri Jul 7 16:14:21 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 16:14:21 +0200 Subject: [FieldTrip] mri segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the fig. below). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena [image: Displaying image.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 70400 bytes Desc: not available URL: From orekhova.elena.v at gmail.com Fri Jul 7 16:26:17 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 16:26:17 +0200 Subject: [FieldTrip] mri segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the fig. below). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena [image: Displaying image.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 70400 bytes Desc: not available URL: From orekhova.elena.v at gmail.com Sat Jul 8 19:11:17 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Sat, 8 Jul 2017 19:11:17 +0200 Subject: [FieldTrip] brain segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fig1.png Type: image/png Size: 66721 bytes Desc: not available URL: From RICHARDS at mailbox.sc.edu Sun Jul 9 14:45:10 2017 From: RICHARDS at mailbox.sc.edu (RICHARDS, JOHN) Date: Sun, 9 Jul 2017 12:45:10 +0000 Subject: [FieldTrip] fieldtrip Digest, Vol 80, Issue 7 In-Reply-To: References: Message-ID: Elena The ft_volumesegment uses the SPM program that does gm/wm segmentation into probability maps. In the case of using = {'brain', 'skull', 'scalp'}; as input, the program sums the PVE for GM, WM and "CSF" (other matter) to create the brain (+ fill holes and some other); then has a formula for finding the skull (dilate brain, or use bone class from segmented MRI), and scalp. So the "skullstrip" portion consists of the brain PVEs from the SPM segmentation program. If that program does not work correctly then the overlap of the brain mask will not match the actual brain--could either not cover all the brain or cover more than the brain. I have had some issues with the SPM algorithm, and its use in the ft_volumesegment is not very flexible. I do the segmentation outside of FT using FSL tools (e.g., bet, bet2, betsurf) and then import the segmented head into FT format; FSL also has an algorithm for "skull stripping" found in its VBM script. This way I have more control over the initial segmented products. Additionally, neither the SPM nor the FSL routines work with some pediatric populations, especially infants under 2 years of age. In that case I often substitute the initial MRI template (in FT case, as SPM, they use the MNI segmented head) with an infant MRI template and get much better results. (e.g., neurodevelopmental MRI database). At times I have used the SPM algorithms for brain segmenting (GM, WM, CSF) and in this case also the PVEs from an age-appropriate brain improve the results. John *********************************************** John E. Richards Carolina Distinguished Professor Department of Psychology University of South Carolina Columbia, SC  29208 Dept Phone: 803 777 2079 Fax: 803 777 9558 Email: richards-john at sc.edu HTTP: jerlab.psych.sc.edu ************************************************* -----Original Message----- From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of fieldtrip-request at science.ru.nl Sent: Sunday, July 9, 2017 6:00 AM To: fieldtrip at science.ru.nl Subject: fieldtrip Digest, Vol 80, Issue 7 Send fieldtrip mailing list submissions to fieldtrip at science.ru.nl To subscribe or unsubscribe via the World Wide Web, visit https://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. brain segmentation problem (Elena Orekhova) ---------------------------------------------------------------------- Message: 1 Date: Sat, 8 Jul 2017 19:11:17 +0200 From: Elena Orekhova To: FieldTrip discussion list Subject: [FieldTrip] brain segmentation problem Message-ID: Content-Type: text/plain; charset="utf-8" Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fig1.png Type: image/png Size: 66721 bytes Desc: not available URL: ------------------------------ _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip End of fieldtrip Digest, Vol 80, Issue 7 **************************************** From anne.urai at gmail.com Mon Jul 10 10:38:59 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 10 Jul 2017 01:38:59 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 Message-ID: Dear Fieldtrippers, I'm using the VTPM atlas to define masks for all the visual regions described in the paper (Wang et al. 2014, https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bhu277). However, there seem to be no entries corresponding to the left IPS5. *% load atlas* *atl = ft_read_atlas('~/Documents/fieldtrip/vtpm/vtpm.mat');* *atl = ft_convert_units(atl, 'cm');* *% add mni coordinates* *[ax, ay, az] = voxelcoords(atl.dim, atl.transform);* *atl.pos = [ax(:) ay(:) az(:)];* *% make a binary mask for this ROI* *roi_idx = find(strcmp(lower(atl.tissuelabel), 'IPS5'));* *roi_mask = ismember(atl.tissue, roi_idx);* *% mask the voxels on the right side of the brain* *rightidx = find(atl.pos(:, 1) > 0); * *roi_mask(rightidx) = 0;* Now, sum(roi_mask(:)) = 0. This procedure of separating out the left and right regions works fine for all other regions in the atlas, as well as the right IPS5. The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? Thanks! — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Mon Jul 10 14:37:20 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Mon, 10 Jul 2017 15:37:20 +0300 Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: Hi Maité, Many thanks for your answer! I have now tried to get coherence between two conditions following the Appendix 1 (I have also used the same data as in Appendix 1; http://www.fieldtriptoolbox.org/tutorial/coherence). As far as I understand, I should first calculate ft_freqanalysis and ft_sourceanalysis separately for condition 1 and condition 2 as follows: *Condition 1:* Compute the cross-spectral density matrix for 18 Hz: cfg = []; cfg.method = 'mtmfft'; cfg.output = 'powandcsd'; cfg.foilim = [18 18]; cfg.tapsmofrq = 5; cfg.keeptrials = 'yes'; freq1 = ft_freqanalysis(cfg, data); The Appendix 1 also defines: cfg.channelcmb = {'MEG' 'MEG';'MEG' 'EMGlft'}; However, I think that in my case channelcmb is not needed since default = {'all' 'all'}. Thereafter, I used ft_sourceanalysis as follows: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; source1 = ft_sourceanalysis(cfg, freq); (The Appendix 1 also defines: cfg.refchan = 'EMGlft';) *Condition 2:* I calculated cross-spectral density exactly in the same way as in condition 1 but used data from condition 2. In ft_sourceanalysis, I set keepfilter and keepleadfiled as “yes”: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; cfg.keepfilter = ‘yes’; cfg.keepleadfield = ‘yes’; source2 = ft_sourceanalysis(cfg, freq2); Thereafter, I selected a source that in inside the brain from source2 and included it’s position, leadfield and filter in refdip: refdip = pos: [5 -5 -1] leadfield: {[151x3 double]} filetr: [3x151 double] After this, I run ft_sourceanalysis: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; cfg.refdip = refdip; source = ft_sourceanalysis(cfg, freq1); Here, I used cross spectral density matrix computed from condition 1 (i.e. freq1). I am not sure, whether I should also somehow take into account the data from condition 2 when calculating freq? Appendix 1 uses EMGlft as refchan in ft_sourceanalysis and has defined cfg.channelcmb = {'MEG' 'MEG';'MEG' 'EMGlft'}; in ft_freqanalysis. The coherence in the position of the reference dipole (i.e. 5 -5 -1) seems to be one, as would be expected since I used the same data in both conditions. Best, Maria 2017-07-07 9:08 GMT+03:00 Maria Hakonen : > Hi Maria, > > I think there is more than one solution for what you are aiming to do. > Maybe a more experienced user or developer could show you the most > straightforward way (?). > > IMO, using LCMV is more direct for this application because with DICS you > will need to provide the reference signal (i.e., the source timecourse from > the other condition). Therefore, you will need to apply LCMV anyway. > > You could apply a band-pass filter to the channel activity before > localizing the frequency band of interest with LCMV. Alternatively, you > could obtain the virtual channels (without band pass) and define the > frequency bands of interest when computing the coherence as in the tutorial > (see ft_freqanalysis steps at http://www.fieldtriptoolbox. > org/tutorial/coherence#computing_the_coherence). > With DICS, in this case, I see it more intricate: 1) obtain the source > timecourses of condition 2 with LCVM; 2) compute the cross spectral density > between all data channels and each source timecourse (reference signal); 3) > compute DICS for each reference signal. Of course, you don't need to > compute the coherence for the whole brain, but only for the source of > interest. For each reference signal, you could change the cfg.grid.inside > value to include only the position of the voxel of interest (the same voxel > of the reference signal). > I hope this helps. > > Best,Maité > > Hi Maité, > > Many thanks for your advice again! > > I have been wondering whether I could calculate coherence straight from > the cross spectros without reference signals or virtual channels by using > beamformer_dics. In beamformer_dics, it seems to be possible to define the > location of the dipole with which coherence is computed (i.e. refdip). > However, I am not sure if it is possible to calculate the coherence between > the same brain region in two different conditions. > > Best, > Maria > > 2017-06-29 12:57 GMT+03:00 Maria Hakonen : > >> Hi Maria, >> for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. >> >> Best,Maité >> http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series >> http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series >> >> Hi Maité, >> >> Thank for your answer again! >> >> However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics? >> >> Best, >> >> Maria >> >> >> 2017-06-26 12:45 GMT+03:00 Maria Hakonen : >> >>> Hi Maria, >>> maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. >>> >>> Best,Maité >>> >>> >>> Hi Maité, >>> >>> Could you please yet let me know how to get the sources timecources? >>> source = ft_sourceanalysis(cfg, freq); only gives >>> source = >>> >>> freq: 18 >>> cumtapcnt: [180x1 double] >>> dim: [19 15 15] >>> inside: [4275x1 logical] >>> pos: [4275x3 double] >>> method: 'average' >>> avg: [1x1 struct] >>> cfg: [1x1 struct] >>> >>> Best, >>> Maria >>> >>> 2017-06-25 13:53 GMT+03:00 Maria Hakonen : >>> >>>> Hi Maité, >>>> >>>> Thank you for your answer! >>>> >>>> I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.org/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this? >>>> >>>> BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum. >>>> >>>> Best, >>>> >>>> Maria >>>> >>>> >>>> Hi Maria, >>>> Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: >>>> >>>> cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; >>>> cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; >>>> As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. >>>> I hope it helps. >>>> Best wishes,Maité >>>> >>>> >>>> >>>> Dear FieldTrip experts, >>>> >>>> I have just started to use Fieldtrip and would like to estimate >>>> coherence between MEG responses measured in two different conditions from >>>> the same cortical areas. The example in Appendix 1 is close to what I would >>>> like to do: >>>> http://www.fieldtriptoolbox.org/tutorial/coherence >>>> >>>> However, in the example, coherence is calculated between the reference >>>> signal (EMG) and all MEG channels. Could it be possible to calculate >>>> coherence between each MEG channel in one condition and the same MEG >>>> channels in the other condition, that is: >>>> ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... >>>> >>>> As far as I understand, the example in Appendix 1 would do this: >>>> ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in >>>> cond2, ... >>>> >>>> Best, >>>> Maria >>>> >>>> >>> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From tzvetan.popov at uni-konstanz.de Mon Jul 10 14:58:24 2017 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Mon, 10 Jul 2017 14:58:24 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: <58C77EC6-E8FE-4C8B-978D-5C6C9C278CB1@uni-konstanz.de> Dear Anne, > > The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? this information was provided by the principle investigator of the paper. You might ask the corresponding author for further details on this. Best tzvetan -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Mon Jul 10 19:41:39 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Mon, 10 Jul 2017 17:41:39 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? References: <1981337653.3654632.1499708499318.ref@mail.yahoo.com> Message-ID: <1981337653.3654632.1499708499318@mail.yahoo.com> Dear Maria, you are right, the data from condition 2 should be contained in the channels cross-spectral-density matrix (Cf). If you would do it with the option 'dics_refchan', you could have the same situation as in the tutorial, but substituting the EMG signal by the source time-course. However, I understand you would prefer to use the option 'dics_refdip'; I am not sure whether it is programmed for your particular situation because the function uses only one Cf in this case. "Maybe" it works by providing the Cf including data from both conditions. But then, the dimension of the filters have to match this new Cf to fulfill the equation: csd = filt1 * Cf * ctranspose(filt2); (function beamformer_dics, line 562) And "maybe" you can extend the filters, setting to 0 the filters corresponding to the channels of the opposite condition. But here, you should get advice from somebody who knows the mathematics; I am just speculating, sorry. Best,Maité El Lunes 10 de julio de 2017 14:56, Maria Hakonen escribió: Hi Maité, Many thanksfor your answer! I have nowtried to get coherence between two conditions following the Appendix 1 (I have alsoused the same data as in Appendix 1; http://www.fieldtriptoolbox.org/tutorial/coherence).  As far as Iunderstand, I should first calculate ft_freqanalysis and ft_sourceanalysis separatelyfor condition 1 and condition 2 as follows: Condition1:Compute thecross-spectral density matrix for 18 Hz:cfg            = [];cfg.method     = 'mtmfft';cfg.output     = 'powandcsd';cfg.foilim     = [18 18];cfg.tapsmofrq  = 5;cfg.keeptrials = 'yes';freq1           = ft_freqanalysis(cfg, data); TheAppendix 1 also defines:cfg.channelcmb= {'MEG' 'MEG';'MEG' 'EMGlft'};However, Ithink that in my case channelcmb is not needed since default = {'all' 'all'}. Thereafter,I used ft_sourceanalysis as follows:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';source1              = ft_sourceanalysis(cfg, freq); (The Appendix1 also defines: cfg.refchan         = 'EMGlft';) Condition2:Icalculated cross-spectral density exactly in the same way as in condition 1 butused data from condition 2. In ft_sourceanalysis, I set keepfilterand keepleadfiled as “yes”:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';cfg.keepfilter = ‘yes’;  cfg.keepleadfield = ‘yes’;source2              = ft_sourceanalysis(cfg, freq2); Thereafter, I selected a source thatin inside the brain from source2 and included it’s position, leadfield andfilter in refdip:refdip =            pos: [5 -5 -1]   leadfield: {[151x3 double]}       filetr: [3x151 double] After this,I run ft_sourceanalysis:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';cfg.refdip = refdip;source              = ft_sourceanalysis(cfg, freq1); Here, I used cross spectral densitymatrix computed from condition 1 (i.e. freq1). I am not sure, whether I should alsosomehow take into account the data from condition 2 when calculating freq?  Appendix 1 uses EMGlft as refchan inft_sourceanalysis and has defined  cfg.channelcmb= {'MEG' 'MEG';'MEG' 'EMGlft'}; in ft_freqanalysis. The coherence in the position of thereference dipole (i.e. 5 -5 -1) seems to be one, as would be expected since Iused the same data in both conditions.  Best,Maria  2017-07-07 9:08 GMT+03:00 Maria Hakonen : Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox. org/tutorial/coherence# computing_the_coherence).With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal).I hope this helps.  Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions.  Best,Maria    2017-06-29 12:57 GMT+03:00 Maria Hakonen : Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox.or g/tutorial/connectivity#extrac t_the_virtual_channel_time- series http://www.fieldtriptoolbox.or g/tutorial/shared/virtual_sens ors#extract_the_virtual_channe l_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From werkle at mpib-berlin.mpg.de Tue Jul 11 13:38:09 2017 From: werkle at mpib-berlin.mpg.de (MWB) Date: Tue, 11 Jul 2017 13:38:09 +0200 Subject: [FieldTrip] PhD Position in Project Area CONMEM at MPI for Human Development Message-ID: <5739dbcd-e183-6698-3f80-46d5c4e6369b@mpib-berlin.mpg.de> Dear colleagues, the project area "Cognitive an Neural Dynamics of Memory Across the Lifespan (CONMEM)", headed by Myriam Sander & Markus Werkle-Bergner, is searching for a PhD-candiate. Details on the position and the application procedures can be found at: https://www.mpib-berlin.mpg.de/sites/default/files/download/jobs/30-2017_stellenanzeige_lip-ie.pdf For further information, please contact Markus Werkle-Bergner (werkle at mpib-berlin.mpg.de) Best regards, Markus Werkle-Bergner -- ************************************************************** Dr. rer. nat. Markus Werkle-Bergner, Dipl. Psych. Senior Research Scientist (W2) Jacobs Foundation Research Fellow 2017-2019 Center for Lifespan Psychology Max Planck Institute for Human Development Lentzeallee 94, Room 211, D-14195 Berlin, Germany. Phone: +49(0)30-82406-447 Fax: +49(0)30-8249939 ************************************************************** From werkle at mpib-berlin.mpg.de Tue Jul 11 13:38:41 2017 From: werkle at mpib-berlin.mpg.de (MWB) Date: Tue, 11 Jul 2017 13:38:41 +0200 Subject: [FieldTrip] Post-Doc Position in Project Area CONMEM at MPI for Human Development Message-ID: <203919e1-7483-968d-f522-72ad0a78b66b@mpib-berlin.mpg.de> Dear colleagues, the project area "Cognitive an Neural Dynamics of Memory Across the Lifespan (CONMEM)", headed by Myriam Sander & Markus Werkle-Bergner, is searching for a post-doc. Details on the position and the application procedures can be found at: https://www.mpib-berlin.mpg.de/sites/default/files/download/jobs/29-2017_stellenanzeige_lip-ie.pdf For further information, please contact Markus Werkle-Bergner (werkle at mpib-berlin.mpg.de) Best regards, Markus Werkle-Bergner -- ************************************************************** Dr. rer. nat. Markus Werkle-Bergner, Dipl. Psych. Senior Research Scientist (W2) Jacobs Foundation Research Fellow 2017-2019 Center for Lifespan Psychology Max Planck Institute for Human Development Lentzeallee 94, Room 211, D-14195 Berlin, Germany. Phone: +49(0)30-82406-447 Fax: +49(0)30-8249939 ************************************************************** From M.Wimber at bham.ac.uk Tue Jul 11 17:11:36 2017 From: M.Wimber at bham.ac.uk (Maria Wimber) Date: Tue, 11 Jul 2017 15:11:36 +0000 Subject: [FieldTrip] Postdoc on memory & iEEG in Birmingham Message-ID: Hi FieldTrippers We are currently seeking a postdoctoral research fellow to join the Birmingham Memory Group. The position is funded by a 5-year European Research Council (ERC) grant awarded to Dr Maria Wimber (www.memorybham.com/maria-wimber), which aims to draw a time- and space-resolved map of memory reactivation in the human brain. The postdoc will have the rare opportunity to work with intracranial EEG recordings from the human hippocampus, including local field potential and single neuron data. The post should be interesting for researchers with a strong background in electrophysiology - EEG/MEG/iEEG, human or animal - and a general interest in long-term memory. More details about the position and an application link can be found here Research Fellow - 56716 Deadline for applications is August 16th 2017. Please distribute to potential candidates, who should feel free to contact the PI directly by email at m.wimber at bham.ac.uk. ---------------------- Dr Maria Wimber Senior Lecturer School of Psychology University of Birmingham tel +44 121 4144659 www.memorybham.com/maria-wimber -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Wed Jul 12 09:35:09 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Wed, 12 Jul 2017 07:35:09 +0000 Subject: [FieldTrip] fieldtrip Digest, Vol 80, Issue 7 In-Reply-To: References: Message-ID: <184AAEB3-B2E5-4C2A-B23F-C46532EA7091@donders.ru.nl> Dear Elena, John and the rest, Allow me to chime in a bit here to bring across John’s answer even more clearly. Indeed ft_volumesegment applies some postprocessing to the tissue-probability-maps (TPMs) as extracted with SPM. This involves amongst others some smoothing and thresholding, which may indeed result in the output to not fit very snugly with the underlying anatomy. However, the amount of smoothing and threshold is in principle in your hands, so you can adjust the parameters to your need. Just have a look at the documentation of the function for how it can be adjusted. Note, also, that I have made some recent changes to ft_volumesegment to allow for SPM-options to be configureable, i.e. you can influence the behaviour of the SPM-based step of the procedure. It is hard to give an optimal set of parameters here as well, because these depend on the quality of the anatomical images (and probably on the spm version used). The default values that are used in ft_volumesegment have been taken from the defaults that SPM uses, but there is no strict reason why these are optimal for all MR images. Also, I’d like to advertise the fact that I have now implemented full support for using SPM12 for the segmentation, where there’s now the option to use 1) a 6-tissue type TPM-template (for this you need to specify cfg.spmversion = ‘spm12’, along with cfg.spmmethod=‘new’), and 2) you can even postprocess the segmentation with the spm add-on ‘mars’. This can be done when specifying cfg.spmmethod=‘mars’, in combination with cfg.spmversion=‘spm12’. For whatever it’s worth… Happy computing! Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands > On 09 Jul 2017, at 14:45, RICHARDS, JOHN wrote: > > Elena > > The ft_volumesegment uses the SPM program that does gm/wm segmentation into probability maps. In the case of using = {'brain', 'skull', 'scalp'}; as input, the program sums the PVE for GM, WM and "CSF" (other matter) to create the brain (+ fill holes and some other); then has a formula for finding the skull (dilate brain, or use bone class from segmented MRI), and scalp. > > So the "skullstrip" portion consists of the brain PVEs from the SPM segmentation program. If that program does not work correctly then the overlap of the brain mask will not match the actual brain--could either not cover all the brain or cover more than the brain. > > I have had some issues with the SPM algorithm, and its use in the ft_volumesegment is not very flexible. I do the segmentation outside of FT using FSL tools (e.g., bet, bet2, betsurf) and then import the segmented head into FT format; FSL also has an algorithm for "skull stripping" found in its VBM script. This way I have more control over the initial segmented products. Additionally, neither the SPM nor the FSL routines work with some pediatric populations, especially infants under 2 years of age. In that case I often substitute the initial MRI template (in FT case, as SPM, they use the MNI segmented head) with an infant MRI template and get much better results. (e.g., neurodevelopmental MRI database). At times I have used the SPM algorithms for brain segmenting (GM, WM, CSF) and in this case also the PVEs from an age-appropriate brain improve the results. > > John > > > *********************************************** > John E. Richards > Carolina Distinguished Professor > Department of Psychology > University of South Carolina > Columbia, SC 29208 > Dept Phone: 803 777 2079 > Fax: 803 777 9558 > Email: richards-john at sc.edu > HTTP: jerlab.psych.sc.edu > ************************************************* > > > -----Original Message----- > From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of fieldtrip-request at science.ru.nl > Sent: Sunday, July 9, 2017 6:00 AM > To: fieldtrip at science.ru.nl > Subject: fieldtrip Digest, Vol 80, Issue 7 > > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > https://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. brain segmentation problem (Elena Orekhova) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 8 Jul 2017 19:11:17 +0200 > From: Elena Orekhova > To: FieldTrip discussion list > Subject: [FieldTrip] brain segmentation problem > Message-ID: > > Content-Type: text/plain; charset="utf-8" > > Dear Fieldtrip experts, > > I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used > > mri_orig= ft_read_mri ('T1.mgz'); > ... > cfg = []; > cfg.output = {'brain', 'skull', 'scalp'}; > mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); > > Have anybody had such a problem. How can it be resolved? > > Elena > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: fig1.png > Type: image/png > Size: 66721 bytes > Desc: not available > URL: > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 80, Issue 7 > **************************************** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From nima.noury at student.uni-tuebingen.de Fri Jul 14 12:09:13 2017 From: nima.noury at student.uni-tuebingen.de (Nima Noury) Date: Fri, 14 Jul 2017 12:09:13 +0200 Subject: [FieldTrip] 2017 Tuebingen Systems Neuroscience Symposium (SNS), Oct 11-12 Message-ID: <20170714120913.Horde.hQkjKPaafdf1u-VgVFclO4N@webmail.uni-tuebingen.de> The Centre for Integrative Neuroscience and MEG Center Tuebingen are pleased to announce the 2017 Tuebingen Systems Neuroscience Symposium (SNS2017) The symposium takes place on October 11 and 12, 2017 at the University of Tuebingen. This annual international meeting brings together leading researchers in the field of systems neuroscience featuring plenary talks, poster sessions and social events. Join us in Tuebingen to learn about the latest advances in systems neuroscience. Confirmed speakers: Francesco Battaglia, Nijmegen Gustavo Deco, Barcelona Biyu He, New York Christoph Kayser, Glasgow Daniel Margulies, Leipzig Uta Noppeney, Birmingham Marios Philiastides, Glasgow Hansjörg Scherberger, Göttingen Woodrow Shew, Fayetteville Preejas Tewarie, Nottingham For more information and registration, please visit: http://meg.medizin.uni-tuebingen.de/2017/ Please forward this information to any of your colleagues and collaborators that may be interested in the symposium. Nima Noury AG Large-Scale Neuronal Interactions Centre for Integrative Neuroscience (CIN) University of Tübingen Otfried Müller-Straße 25 72076 Tübingen Germany From anne.urai at gmail.com Tue Jul 18 08:54:17 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 17 Jul 2017 23:54:17 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: Hi Tvetan, Thanks for your help. Dear Anne,>* The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? *this information was provided by the principle investigator of the paper. You might ask the corresponding author for further details on this. Best tzvetan I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI. Do you know by any chance which author provided the mat file, so I can work from the code they used? Best, — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai From: Anne Urai Reply: Anne Urai Date: 10 July 2017 at 10:38:59 To: fieldtrip at science.ru.nl Subject: vtpm atlas contains no right IPS5 Dear Fieldtrippers, I'm using the VTPM atlas to define masks for all the visual regions described in the paper (Wang et al. 2014, https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bhu277). However, there seem to be no entries corresponding to the left IPS5. *% load atlas* *atl = ft_read_atlas('~/Documents/fieldtrip/vtpm/vtpm.mat');* *atl = ft_convert_units(atl, 'cm');* *% add mni coordinates* *[ax, ay, az] = voxelcoords(atl.dim, atl.transform);* *atl.pos = [ax(:) ay(:) az(:)];* *% make a binary mask for this ROI* *roi_idx = find(strcmp(lower(atl.tissuelabel), 'IPS5'));* *roi_mask = ismember(atl.tissue, roi_idx);* *% mask the voxels on the right side of the brain* *rightidx = find(atl.pos(:, 1) > 0); * *roi_mask(rightidx) = 0;* Now, sum(roi_mask(:)) = 0. This procedure of separating out the left and right regions works fine for all other regions in the atlas, as well as the right IPS5. The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? Thanks! — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai -------------- next part -------------- An HTML attachment was scrubbed... URL: From tzvetan.popov at uni-konstanz.de Tue Jul 18 09:28:28 2017 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Tue, 18 Jul 2017 09:28:28 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Dear Anne, > I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI > Do you know by any chance which author provided the mat file I have created the mat file working from the nifti files. I don’t have the code anymore but it wasn’t too difficult. Yet, this code wouldn’t help since the ROI isn’t in the nifti files to begin with. I had exchange RE: missing ROI with Michael Arcaro back then. Here is what he wrote: "As you said, ROI 23 does not appear to be in the volume lh map. It’s there in the surface max prob map for the lh. I know Liang generated a separate probability map using nonlinear volumetric alignment, which was a little bit worse in quality than the surface map. It’s possible you’re using that map. I thought we sent you the volume projection of the surface max probability map though. It’s possible that the small area of ROI3 in the surface max probability map did not survive the projection back into volume space (since there is interpolation in the projection). I’ll double check with Liang and Ryan and see if they remember any issues with ROI23. It might be better to use the individual probability map for ROI 23 and use a more liberal threshold." So it seems that Liang could indeed provide some more info on whether and how to use a more liberal threshold to get the ROI back into the volumetric representation? Best tzvetan -------------- next part -------------- An HTML attachment was scrubbed... URL: From anne.urai at gmail.com Tue Jul 18 10:12:26 2017 From: anne.urai at gmail.com (Anne Urai) Date: Tue, 18 Jul 2017 01:12:26 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> References: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Message-ID: Dear Liang, cc Tzvetan, FieldTrip See the conversation below - Tzvetan has indicated that the volumetric representation is already missing IPS5. It would be great to try and redo the projection into volume space and play with the threshold to make sure that all regions are at least assigned to one voxel. Best, — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai From: Tzvetan Popov Reply: FieldTrip discussion list Date: 18 July 2017 at 09:28:28 To: FieldTrip discussion list Subject: Re: [FieldTrip] vtpm atlas contains no right IPS5 Dear Anne, I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI Do you know by any chance which author provided the mat file I have created the mat file working from the nifti files. I don’t have the code anymore but it wasn’t too difficult. Yet, this code wouldn’t help since the ROI isn’t in the nifti files to begin with. I had exchange RE: missing ROI with Michael Arcaro back then. Here is what he wrote: "As you said, ROI 23 does not appear to be in the volume lh map. It’s there in the surface max prob map for the lh. I know Liang generated a separate probability map using nonlinear volumetric alignment, which was a little bit worse in quality than the surface map. It’s possible you’re using that map. I thought we sent you the volume projection of the surface max probability map though. It’s possible that the small area of ROI3 in the surface max probability map did not survive the projection back into volume space (since there is interpolation in the projection). I’ll double check with Liang and Ryan and see if they remember any issues with ROI23. It might be better to use the individual probability map for ROI 23 and use a more liberal threshold." So it seems that Liang could indeed provide some more info on whether and how to use a more liberal threshold to get the ROI back into the volumetric representation? Best tzvetan _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From zk578 at york.ac.uk Thu Jul 20 15:56:48 2017 From: zk578 at york.ac.uk (=?iso-8859-1?Q?Zdenko_Koh=FAt?=) Date: Thu, 20 Jul 2017 13:56:48 +0000 Subject: [FieldTrip] ERP classification Message-ID: Dear Fieldtrippers, I would like to classify ERP data in one condition based on an averaged group ERP signal from a different condition. To describe it more clearly, imagine that I have a condition1 in which I observe a significant P300, and a condition2 which shows no significant effect, although some of the participants clearly show the P300 in this condition as well. I would like to use the signal from the condition1 to classify the participants in the condition2 into P300 and no-P300 group. Is there some way to go about this issue ? Thank you ! :) Kind regards, Zdenko -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nina.Merkel at kgu.de Thu Jul 20 17:35:58 2017 From: Nina.Merkel at kgu.de (Merkel, Nina) Date: Thu, 20 Jul 2017 15:35:58 +0000 Subject: [FieldTrip] sig file Message-ID: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina -------------- next part -------------- An HTML attachment was scrubbed... URL: From N.vanKlink-2 at umcutrecht.nl Fri Jul 21 09:13:56 2017 From: N.vanKlink-2 at umcutrecht.nl (Klink-3, N.E.C. van) Date: Fri, 21 Jul 2017 07:13:56 +0000 Subject: [FieldTrip] sig file In-Reply-To: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> References: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Message-ID: Hi Nina, These .sig files are Stellate EEG files, but Stellate does no longer exist anymore, so software is no longer supported. This makes it difficult to work with these files sometimes. The easiest way would be to convert your .sig to EDF with Stellate Reviewer, if you have access to that software. You would select the whole file with the selector tool, and then File-> Export As... There also is a matlab toolbox for reading .sig into matlab, but it only works with 32-bits matlab on a Windows system. Hope this helps, Nicole Van: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Namens Merkel, Nina Verzonden: 20 jul 17 17:36 Aan: 'fieldtrip at science.ru.nl' Onderwerp: [FieldTrip] sig file Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina ------------------------------------------------------------------------------ De informatie opgenomen in dit bericht kan vertrouwelijk zijn en is uitsluitend bestemd voor de geadresseerde. Indien u dit bericht onterecht ontvangt, wordt u verzocht de inhoud niet te gebruiken en de afzender direct te informeren door het bericht te retourneren. Het Universitair Medisch Centrum Utrecht is een publiekrechtelijke rechtspersoon in de zin van de W.H.W. (Wet Hoger Onderwijs en Wetenschappelijk Onderzoek) en staat geregistreerd bij de Kamer van Koophandel voor Midden-Nederland onder nr. 30244197. Denk s.v.p aan het milieu voor u deze e-mail afdrukt. ------------------------------------------------------------------------------ This message may contain confidential information and is intended exclusively for the addressee. If you receive this message unintentionally, please do not use the contents but notify the sender immediately by return e-mail. University Medical Center Utrecht is a legal person by public law and is registered at the Chamber of Commerce for Midden-Nederland under no. 30244197. Please consider the environment before printing this e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mailtome.2113 at gmail.com Mon Jul 24 07:04:54 2017 From: mailtome.2113 at gmail.com (Arti Abhishek) Date: Mon, 24 Jul 2017 15:04:54 +1000 Subject: [FieldTrip] Appending datasets with different channel order Message-ID: Dear list, I am working with some infant ERP data and I perform trial by trial channel interpolation. The trials are then concatenated using ft_appenddata. Since the number of interpolated channels are different across trials, the channel order is different across trials. I was wondering what will happen to the channel order in the case of appending. Since there are channel labels for each trial, does the ft_appenddata function takes this into account and match data to the channel label? Thanks Arti -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nina.Merkel at kgu.de Mon Jul 24 10:07:43 2017 From: Nina.Merkel at kgu.de (Merkel, Nina) Date: Mon, 24 Jul 2017 08:07:43 +0000 Subject: [FieldTrip] sig file In-Reply-To: References: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Message-ID: <5A40C6B713E9B243B4EBD708AFA674A7590D67@EXMEPDAG4.intra.kgu.de> Thank you Nicole! This was very helpful information! Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Klink-3, N.E.C. van Gesendet: Freitag, 21. Juli 2017 09:14 An: FieldTrip discussion list Betreff: Re: [FieldTrip] sig file Hi Nina, These .sig files are Stellate EEG files, but Stellate does no longer exist anymore, so software is no longer supported. This makes it difficult to work with these files sometimes. The easiest way would be to convert your .sig to EDF with Stellate Reviewer, if you have access to that software. You would select the whole file with the selector tool, and then File-> Export As... There also is a matlab toolbox for reading .sig into matlab, but it only works with 32-bits matlab on a Windows system. Hope this helps, Nicole Van: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Namens Merkel, Nina Verzonden: 20 jul 17 17:36 Aan: 'fieldtrip at science.ru.nl' Onderwerp: [FieldTrip] sig file Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina ________________________________ De informatie opgenomen in dit bericht kan vertrouwelijk zijn en is uitsluitend bestemd voor de geadresseerde. Indien u dit bericht onterecht ontvangt, wordt u verzocht de inhoud niet te gebruiken en de afzender direct te informeren door het bericht te retourneren. Het Universitair Medisch Centrum Utrecht is een publiekrechtelijke rechtspersoon in de zin van de W.H.W. (Wet Hoger Onderwijs en Wetenschappelijk Onderzoek) en staat geregistreerd bij de Kamer van Koophandel voor Midden-Nederland onder nr. 30244197. Denk s.v.p aan het milieu voor u deze e-mail afdrukt. ________________________________ This message may contain confidential information and is intended exclusively for the addressee. If you receive this message unintentionally, please do not use the contents but notify the sender immediately by return e-mail. University Medical Center Utrecht is a legal person by public law and is registered at the Chamber of Commerce for Midden-Nederland under no. 30244197. Please consider the environment before printing this e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From anne.urai at gmail.com Mon Jul 24 12:59:08 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 24 Jul 2017 12:59:08 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Message-ID: Hi Tzvetan, Fieldtrippers, see below the response I got from Liang Wang. *I double-check the original files of the maximum probabilistic atlas in the volume-based space. As you said, it did not include left IPS5 areas. In our paper, we had pointed out that there was a difference between volume- and surface-based atlas, because the registration used between two space was totally different. We think the surface-based atlas may be more accurate, compare to the volume-based atlas. If you need to get left IPS5, I suggest to use the probability map for that region that you also can download from the web. This map provides you a probability value for each voxel being to that region. * *Best,* *Liang* — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai On 18 July 2017 at 10:12, Anne Urai wrote: > Dear Liang, > cc Tzvetan, FieldTrip > > See the conversation below - Tzvetan has indicated that the volumetric > representation is already missing IPS5. It would be great to try and redo > the projection into volume space and play with the threshold to make sure > that all regions are at least assigned to one voxel. > > Best, > > — > Anne E. Urai, MSc > PhD student | Institut für Neurophysiologie und Pathophysiologie > Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | > Hamburg, Germany > www.anneurai.net / @AnneEUrai > > From: Tzvetan Popov > > Reply: FieldTrip discussion list > > Date: 18 July 2017 at 09:28:28 > To: FieldTrip discussion list > > Subject: Re: [FieldTrip] vtpm atlas contains no right IPS5 > > Dear Anne, > > I've been in touch with Dr. Liang Wang (first author on the paper), but he > could only point me to the original NIfTI files on the website which have > been converted in AFNI > > Do you know by any chance which author provided the mat file > > I have created the mat file working from the nifti files. I don’t have the > code anymore but it wasn’t too difficult. Yet, this code wouldn’t help > since the ROI isn’t in the nifti files to begin with. I had exchange RE: > missing ROI with Michael Arcaro back then. Here is what he wrote: > > "As you said, ROI 23 does not appear to be in the volume lh map. > It’s there in the surface max prob map for the lh. I know Liang generated > a separate probability map using nonlinear volumetric alignment, which was > a little bit worse in quality than the surface map. It’s possible you’re > using that map. I thought we sent you the volume projection of the surface > max probability map though. It’s possible that the small area of ROI3 in > the surface max probability map did not survive the projection back into > volume space (since there is interpolation in the projection). I’ll double > check with Liang and Ryan and see if they remember any issues with ROI23. > It might be better to use the individual probability map for ROI 23 and use > a more liberal threshold." > > So it seems that Liang could indeed provide some more info on whether and > how to use a more liberal threshold to get the ROI back into the volumetric > representation? > > Best > tzvetan > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Miguel.Granjaespiritosanto at nottingham.ac.uk Tue Jul 25 10:20:32 2017 From: Miguel.Granjaespiritosanto at nottingham.ac.uk (Miguel Granja Espirito Santo) Date: Tue, 25 Jul 2017 08:20:32 +0000 Subject: [FieldTrip] ft_topoplotER using highlight symbol size as proxy for length of significance of cluster. Message-ID: Hi all, I am trying to use the ft_topoplotER to show significant difference between conditions without having to do a large subplot of different times points. To do this I thought of adjusting the highlighting symbol size proportionally to the length of the duration of significance. This seem simple at first because I just had to plot the highlight for every channel one at time in a for loop and adjust the size accordingly and then use hold on. However, ft_topoplotER writes a new image through every iteration of the loop and therefore overwriting the previous highlight. Is there any way to get around this? Is there a way to enable hold on for ft_topoplotER? Best, Miguel PhD Student School of Psychology University of Nottingham This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation. -------------- next part -------------- An HTML attachment was scrubbed... URL: From smoratti at psi.ucm.es Wed Jul 26 17:11:32 2017 From: smoratti at psi.ucm.es (smoratti at psi.ucm.es) Date: Wed, 26 Jul 2017 17:11:32 +0200 Subject: [FieldTrip] 2-year post-doctoral position in human intracranial recordings in patients with schizophrenia Message-ID: <7AE53ED5-A06C-455B-993F-47DE9688A560@psi.ucm.es> On behalf of Bryan Strange a close collaborator of mine I send you this job offer: The Laboratory for Clinical Neuroscience in Madrid (www.thestrangelab.org ), in collaboration with the Neurosurgery and Psychiatry departments of the Clinico San Carlos, is pioneering the use of deep-brain stimulation in the management of medication-resistant schizophrenia. As part of this treatment, we perform electrophysiological recordings in patients to study the firing pattern of ventral midbrain (putatively dopaminergic) neurons. Secondly, we test patients in behavioural tasks such as working memory, in order to determine the cognitive effects of DBS treatment. The successful candidate will be involved in acquiring and analysing neurophysiological recordings from these patients: intra-operative single-unit recordings and post-operative intracranial local field potentials and scalp EEG. Funding is through the Behavior and Brain Research Foundation (https://www.bbrfoundation.org/blog/meet-our-2017-narsad-independent-investigator-grantees ) A PhD in neuroscience (or related discipline) is required. The ideal candidate will be highly competent in the analysis of electrophysiological recordings, particularly single-unit data. Knowledge of ventral tegmental single unit activity in animal models of schizophrenia is desirable. The start date will be in autumn/winter 2017. Fluent English is mandatory, Spanish is not required. Application: Send CV, motivation letter, and contact details of two academic referees to Prof. Bryan Strange bryan.strange at upm.es Deadline: 1 September 2017 -- Un cordial saludo, Stephan Moratti, PhD Profesor de Psicología Básica I Universidad Complutense de Madrid 91 394 3141 smoratti at ucm.es La información contenida en este correo es CONFIDENCIAL, de uso exclusivo del destinatario/a arriba mencionado. Si ha recibido este mensaje por error, notifíquelo inmediatamente por esta misma vía y proceda a su eliminación, ya que ud. tiene totalmente prohibida cualquier utilización del mismo, en virtud de la legislación vigente. Los datos personales recogidos serán incorporados y tratados en el fichero 'Correoweb', bajo la titularidad del Vicerrectorado de Tecnologías de la Información, y en él el interesado/a podrá ejercer los derechos de acceso, rectificación, cancelación y oposición ante el mismo (artículo 5 de la Ley Orgánica 15/1999, de 13 de diciembre, de Protección de Datos de Carácter Personal). Antes de imprimir este correo piense si es necesario: el medio ambiente es cosa de todos. This message is private and confidential and it is intended exclusively for the addressee. If you receive this message by mistake, you should not disseminate, distribute or copy this e-mail. Please inform the sender and delete the message and attachments from your system, as it is completely forbidden for you to use this information, according to the current legislation. No confidentiality nor any privilege regarding the information is waived or lost by any mistransmission or malfunction. The personal data herein will be collected in the file “Correoweb”, under the ownership of the Vice-Rectorate for Information Technologies, in which those interested may exercise their right to access, rectify, cancel or protest the contents (article 5 of Organic Law 15/1999 dated 13 December, on the Protection of Personal data). Before printing this mail please consider whether it is really necessary: the environment is a concern for us all. -------------- next part -------------- An HTML attachment was scrubbed... URL: From roycox.roycox at gmail.com Thu Jul 27 18:32:49 2017 From: roycox.roycox at gmail.com (Roy Cox) Date: Thu, 27 Jul 2017 12:32:49 -0400 Subject: [FieldTrip] postdoctoral opportunity Message-ID: Please see below for a postdoctoral opportunity in the lab of Dara Manoach at MGH/Harvard Medical School. Best, Roy ------------------------------------------------------------------------------------------------------------------------------- Postdoctoral Fellowship at the Martinos Center for Biomedical Imaging and the Psychiatric Neuroimaging Division of the Psychiatry Department at Massachusetts General Hospital, Charlestown, MA and Harvard Medical School *Position Description*: Clinical/Cognitive Neuroscience Research *Project*: Multimodal neuroimaging studies of sleep and memory *PI*: Dara S. Manoach, Ph.D. The position will involve investigating the role of sleep in memory consolidation, how these processes go awry in schizophrenia and autism, and the effects of pharmacological and other interventions. Our work has linked cognitive deficits to specific heritable mechanisms (sleep spindles and other sleep oscillations) and we are seeking effective interventions. In collaboration with Dr. Robert Stickgold’s lab at Beth Israel Deaconess Medical Center, we are extending and expanding this basic and clinical research program using state-of-the art tools including high density EEG, MEG, DTI, functional connectivity MRI, fMRI, and behavioral studies. We are seeking someone to participate in these foundation and NIMH-funded investigations who is familiar with cognitive neuroscience, neuroimaging methodology including MEG and/or EEG and data analysis, and is interested in developing research questions and optimizing analysis streams tailored to the study aims and populations. New approaches and ideas are encouraged, as are independent projects that dovetail with current studies. The position requires working closely with the PI, as well as with Dr. Stickgold, other Martinos Center investigators, particularly Dr. Matti Hamalainen, Director of the MEG Core Lab, and labmates to design studies, acquire data, and develop, explore, improve and apply data analytic techniques. Training in clinical research and in the acquisition, analysis, and interpretation of neuroimaging data will be provided. Requirements: PhD (or MD) in neuroscience, psychology, engineering or a related discipline and a strong research background are required. Ideal candidates would have extensive experience in data analysis, a background in computational neuroscience and/or signal processing, be proficient in Matlab/Python and be interested in methods development. The following are also beneficial: experience with MEG/EEG data analysis/methodology, background in cognitive neuroscience, experimental psychology and sleep; interest/experience with clinical populations; and experience in task design and analysis for cognitive experiments. Position available immediately. Interested applicants should email: (a) CV, (b) statement of post-doctoral and career goals, (c) writing sample (e.g., a published manuscript), and (d) letters and/or contact information for three references to Dara Manoach . Stipend levels are in line with experience and NIH. A two-year commitment is required. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Hisako.Fujiwara at cchmc.org Thu Jul 27 19:00:15 2017 From: Hisako.Fujiwara at cchmc.org (Fujiwara, Hisako) Date: Thu, 27 Jul 2017 17:00:15 +0000 Subject: [FieldTrip] how to segment continuous EEG data without triggers Message-ID: <64721b2dbaba463b9ea729893d08708d@cchmc.org> Dear experts, I have continuous EEG data in EDF format that does not include trigger channel. These EEG data was recorded as EEG-fMRI during a task (30-sec baseline and 30-sec active trial alternated 4 or 5 times depending on participants). I would like to segment out the active states 4 x 30-sec segments for each participants. Now, I have the separate marker files that have 2 sec TR trigger as a text (EV2) file. I can at least tell start and finish for each trial from the marker file. I have tired to use ft_definetrial and ft_redefinetri with function of cfg.toilim = [tmin tmax] but I am getting error message either: 1. undefined function or variable 'data' 2. Error using ft_notification (line 314) This function requires raw+comp or raw data as input. Error in ft_error (line 39) ft_notification(varargin{:}); Error in ft_checkdata (line 495) ft_error('This function requires %s data as input.', str); Error in ft_redefinetrial (line 117) data = ft_checkdata(data, 'datatype', {'raw+comp', 'raw'}, 'feedback', cfg.feedback); I tried to refer the http://www.fieldtriptoolbox.org/reference/ft_definetrial and also searched through the mailing archives but I have not found exact solution so fat. but I ma not really succeeding this. I am sure I am missing a lot of functions for that. Could you please kindly suggest any detailed explanation and solution for this? Thank you very much for your kind help in advance, Sincerely, Hisako -------------- next part -------------- An HTML attachment was scrubbed... URL: From a132467647 at gmail.com Sat Jul 29 10:47:22 2017 From: a132467647 at gmail.com (Jiun Wei Chen) Date: Sat, 29 Jul 2017 08:47:22 +0000 Subject: [FieldTrip] Having a error in installing Fieldtrip after installing SPM and brainstorm Message-ID: Dear Fieldtrip users: My name is Jiun-Wei Chen and I am working in Brain mapping lab in Taiwan on the brain science. I am analyzing data of MEG. I found the problem I can't properly installing Fieldtrip in my MATLAB. My versions of MATLAB are R2015b and R2016b. before installing Fieldtrip, I have installed SPM12 and brainstorm in my MATLAB. Then, I follow this website below to set path http://www.fieldtriptoolbox.org/faq/should_i_add_fieldtrip_with_all_subdirectories_to_my_matlab_path this is my instance below: >> addpath C:\Users\wei\Documents\MATLAB\Fieldtrip >> ft_defaults after I key in these commands, I get the error message below: Undefined function 'ft_platform_supports' for input arguments of type 'char'. Error in ft_defaults>checkMultipleToolbox (line 291) if ~ft_platform_supports('which-all') Error in ft_defaults (line 114) checkMultipleToolbox('FieldTrip', 'ft_defaults.m'); I also tried to install Fieldtrip only in my MATLAB and preprocess my data. (my data format is ".fif") but I got an error message again. Subscripted assignment between dissimilar structures. Error in mergeconfig>mergeconfig_helper (line 39) input(j) = mergeconfig_helper(input(j), default(j)); Error in mergeconfig>mergeconfig_helper (line 53) input.(fn) = mergeconfig_helper(input.(fn), default.(fn)); Error in mergeconfig>mergeconfig_helper (line 53) input.(fn) = mergeconfig_helper(input.(fn), default.(fn)); Error in mergeconfig (line 12) input = mergeconfig_helper(input, default); Error in ft_preamble_init (line 55) cfg = mergeconfig(cfg, rmfield(ft_default, 'preamble')); Error in ft_preamble (line 85) evalin('caller', full_cmd); Error in ft_preprocessing (line 182) ft_preamble init Error in ft_qualitycheck (line 212) data = ft_preprocessing(cfgpreproc); clear cfgpreproc; I upload my data in my google drive as it exceeds the critical file size of 1MB. Here is the link: https://drive.google.com/open?id=0B8Xo-QjG1y2TZjBnWjdpNjZXNlk the code I use are as follows: %% Quality check cfg = [];%configuration structure cfg.dataset = 'run1_sss.fif';%string with the filename ft_qualitycheck(cfg) I could preprocess this data by Fieldtrip code that exists in the external folder of SPM and brainstorm. but I got the warning message that altered me there is the same code in these folders. can someone tell me how to install Fieldtrip when brainstorm and SPM exist in the same time and how to avoid the warning message I mentioned above. Any help would be appreciated. Best, Jiun-Wei -------------- next part -------------- An HTML attachment was scrubbed... URL: From son.ta.dinh at tum.de Mon Jul 31 09:39:51 2017 From: son.ta.dinh at tum.de (Ta Dinh, Son) Date: Mon, 31 Jul 2017 07:39:51 +0000 Subject: [FieldTrip] Functional connectivity analysis with powcorr_ortho In-Reply-To: <0d81972648824a678682346413ec9456@tum.de> References: <0d81972648824a678682346413ec9456@tum.de> Message-ID: Hi Brian, In general I woulrd recommend that you comment or reply to posts in the FieldTrip list on the list instead of sending mails directly to people so that issues that are solved are visible to everybody. As to the issue at hand, I haven't heard from anybody and regretfully forgot to ask Mr. Schoffelen at the last conference I met him. My solution to this was to implement the algorithm by myself according to the description given in the paper by Hipp et al. I could offer to send you the code, it should be easy to integrate with a reasonable amount of Matlab skills. Naturally I will not be able to offer any guarantees that the code is correct, but the results look reasonable enough to me. Go to http://dropcanvas.com/1xfe7/1 for a plot of the grand average seed-based connectivity from the left somatosensory cortex (MNI = [- 40, - 30, 50]) to all other voxels within the Beta band for a group of 22 healthy subjects. The paradigm is 5 minutes eyes-closed resting-state. Best, Son Von: Brian Scally [RPG] [mailto:psbs at leeds.ac.uk] Gesendet: Donnerstag, 27. Juli 2017 15:54 An: Ta Dinh, Son > Betreff: Fieldtrip powcorr_ortho issue Dear Son Ta Dinh, Hope you are well. I came across a post you made on the Fieldtrip mailing list about the powcorr_ortho function for ft_connectivity analysis. I am essentially getting the same results - random connectivity patterns. I wondered if you had heard from anyone about this issue or managed to resolve it? All the best, Brian Scally PhD Student, School of Psychology, University of Leeds b.scally at leeds.ac.uk Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Ta Dinh, Son Gesendet: Donnerstag, 13. April 2017 14:58 An: fieldtrip at science.ru.nl Betreff: [FieldTrip] Functional connectivity analysis with powcorr_ortho Dear FieldTrip list, I am trying to do a functional connectivity analysis using the power envelope correlation introduced by Hipp et al. (Nat Neuroscience 2012) as implemented in the ft_connectivity_powcorr_ortho function. My data consists of 5 minutes of eyes-closed resting-state data and my schematic pipeline is as follows: 1. I use LCMV beamforming to source reconstruct my bandpassed and preprocessed data 2. Using the resulting spatial filter I get a projected time series for every voxel (virtual channel) 3. I do a frequency analysis on these time series 4. The results of this frequency analysis (the Fourier coefficients) are used for the connectivity analysis using powcorr_ortho To check the results of this analysis, I plotted the results of a seed-based connectivity analysis with a voxel in the left visual cortex (-20, -80, 20) as seed. In the alpha band, I expect to see a strong local connectivity pattern in the occipital region extending partially into the contralateral hemisphere, similar to what Siems et al. NeuroImage 2016 find. However, I get a basically random connectivity pattern. When using this pipeline with the debiased weighted phase lag index, I get exactly what I am expecting. I looked into the source code of the ft_connectivity_powcorr_ortho function and saw a few disconcerting comments (Fix-Me's and the like) and now I am wondering whether my pipeline is simply not suited to the connectivity analysis with powcorr_ortho as implemented in FieldTrip or if the function is simply not fully implemented yet. Has anyone used it successfully before? I use the following FieldTrip (pseudo-) code: %% LCMV source reconstruction cfg = []; cfg.method = 'lcmv'; cfg.keeptrials = 'yes'; cfg.elec = elec; cfg.grid = lf; % regular grid of 1 cm resolution cfg.headmodel = vol % standard_bem.mat cfg.lcmv.keepfilter = 'yes'; cfg.lcmv.lambda = '5%'; cfg.lcmv.projectnoise = 'yes'; source = ft_sourceanalysis(cfg, tlock_data); %% pseudo-code for the computation of the virtual channel time series virtChan_data = tlock_data; virtChan_data.label = [source.pos(:, 1), source.pos(:,2), source.pos(:,3)]; virtChan_data.trial = source.avg.filter * tlock_data.trial; %% frequency analysis of the virtual channels cfg = []; cfg.method = 'mtmfft'; cfg.output = 'fourier'; cfg.keeptrials = 'yes'; cfg.foi = 10; % alpha band cfg.taper = 'hanning' % I originally used 3 tapers but source code in ft_connectivity_powcorr_ortho implies that multitaper is not compatible virtFreq = ft_freqanalysis(cfg, virtChan_data); %% connectivity analysis cfg = []; cfg.method = 'powcorr_ortho'; conn = ft_connectivityanalysis(cfg,virtFreq); Any suggestions and/or comments would be immensely helpful! Thanks in advance. Best, Son Son Ta Dinh, M.Sc. PhD student in Human Pain Research Klinikum rechts der Isar Technische Universität München Munich, Germany Phone: +49 89 4140 7664 http://www.painlabmunich.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Fri Jul 21 05:08:45 2017 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 21 Jul 2017 03:08:45 -0000 Subject: [FieldTrip] 2nd MEG North America Meeting Message-ID: We are pleased to announce the 2nd MEG-North America meeting, to be held in Bethesda, Maryland November 8th and 9th, directly before the Society for Neuroscience Meeting. November 8th will consist of small workgroup meetings to discuss collaborative projects involving reproducibility, data sharing architecture, and consortium building. We are seeking community involvement for these committees! Please get involved, go to our website to find out how. Working groups will address reliability/reproducibility, data sharing, industry partnership, and facilitating best practices. The main meeting will be held on November 9th, with a scientific program, keynote speakers, and a poster session. Call for Abstracts opens today, and will Close September 8th. Speaking vs. poster assignments will be sent within two weeks. Please visit our website at https://megworkshop.nih.gov/MEGWorkshop/ Or register at: https://www.eventbrite.com/e/meg-north-america-2017-tickets-36315511673 We hope to see you there! Conference Chairs: Richard Coppola Allison Nugent Steering Committee: Sylvain Baillet Dimitrios Pantazis Timothy Roberts Julia Stephen -------------- next part -------------- An HTML attachment was scrubbed... URL: From rhancock at email.arizona.edu Thu Jul 27 05:17:39 2017 From: rhancock at email.arizona.edu (Roeland Hancock) Date: Wed, 26 Jul 2017 23:17:39 -0400 Subject: [FieldTrip] Job: Technical Director of the Brain Imaging Research Center Message-ID: *University of Connecticut* *Technical Director of the Brain Imaging Research Center * *Research Assistant III/Research Associate I* The University of Connecticut invites applications for a full-time position of Technical Director of UConn’s Brain Imaging Research Center (BIRC). The Technical Director is responsible for the development and maintenance of the BIRC’s technology infrastructure, and will contribute to day-to-day operations. Rank and salary will be commensurate with degree and experience. The BIRC’s focus is on cognitive neuroscience research using functional MRI. *To Apply: *Interested applicants should view the full ad and application instructions at www.jobs.uconn.edu. Please send inquiries to Inge-Marie Eigsti, Ph.D., Chair of Search #2017355, Department of Psychological Sciences, U-1020, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269-1020; BIRC at UConn.edu. Applications are preferred by August 15, 2017, but the position will remain open until filled. The University of Connecticut is an EEO/AA employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: From rhancock at email.arizona.edu Thu Jul 27 05:17:39 2017 From: rhancock at email.arizona.edu (Roeland Hancock) Date: Thu, 27 Jul 2017 03:17:39 +0000 Subject: [FieldTrip] Job: Technical Director of the Brain Imaging Research Center Message-ID: <52c10f2f79ff40c1be85c9a9eaf2fe9c@EXPRD98.hosting.ru.nl> University of Connecticut Technical Director of the Brain Imaging Research Center Research Assistant III/Research Associate I The University of Connecticut invites applications for a full-time position of Technical Director of UConn’s Brain Imaging Research Center (BIRC). The Technical Director is responsible for the development and maintenance of the BIRC’s technology infrastructure, and will contribute to day-to-day operations. Rank and salary will be commensurate with degree and experience. The BIRC’s focus is on cognitive neuroscience research using functional MRI. To Apply: Interested applicants should view the full ad and application instructions at www.jobs.uconn.edu. Please send inquiries to Inge-Marie Eigsti, Ph.D., Chair of Search #2017355, Department of Psychological Sciences, U-1020, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269-1020; BIRC at UConn.edu. Applications are preferred by August 15, 2017, but the position will remain open until filled. The University of Connecticut is an EEO/AA employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jumana.ahmad at kcl.ac.uk Mon Jul 3 15:15:34 2017 From: jumana.ahmad at kcl.ac.uk (Ahmad, Jumana) Date: Mon, 3 Jul 2017 13:15:34 +0000 Subject: [FieldTrip] inter trial coherence statistics Message-ID: Dear all, I have been struggling for awhile with inter trial coherence statistics. I found the ITC stats fun function online with cfg.statistic = 'diff_itc' I cannot get it to work. I have 300 participants per group, and a between subject design with only one outcome measure. I therefore wanted something akin to permutation between groups. However, when I use the ITC stats fun function, it complains if the design matrix is not as long as all the files across all participants so it becomes more like a single subject comparison. Has anybody had any luck using this function between groups, or with multiple people? If so, would it be OK to share a sample of your code or key parameters? Thank you very much, Jumana ------------------------------------------ Jumana Ahmad Post-Doctoral Research Worker in Cognitive Neuroscience EU-AIMS Longitudinal European Autism Project (LEAP) & SynaG Study Room M1.26.Department of Forensic and Neurodevelopmental Sciences (PO 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College London | 16 De Crespigny Park | London SE5 8AF Phone: 0207 848 5359| Email: jumana.ahmad at kcl.ac.uk | Website: www.eu-aims.eu | Facebook: www.facebook.com/euaims -------------- next part -------------- An HTML attachment was scrubbed... URL: From martabortoletto at yahoo.it Mon Jul 3 16:17:03 2017 From: martabortoletto at yahoo.it (Marta Bortoletto) Date: Mon, 3 Jul 2017 14:17:03 +0000 (UTC) Subject: [FieldTrip] Workshop - Ten years of Mind/Brain Sciences at the University of Trento - CIMeC, Italy References: <418890791.6270044.1499091423986.ref@mail.yahoo.com> Message-ID: <418890791.6270044.1499091423986@mail.yahoo.com> Tocelebrate its 10th anniversary, the Center for Mind/Brain Sciences (CIMeC) organizes a workshop on thefuture of cognitive neuroscience.WHERE and WHEN: The workshop will be held in Rovereto, Italy on October 19-21, 2017. WHAT: The themeof the event will be centered around the question: “Where do cognitiveneuroscientists see Mind/Brain Sciences in ten years?”Deadline for poster submission: September 1st. Workshop website: http://events.unitn.it/en/cimec-ten-yearsThe workshop has a limited number of availableplaces. Potential attendees are encouraged to register online as soon aspossible.Invited speakers:·       Cristina Becchio - Universityof Torino, Italy·       Nadia Bolognini - Universityof Milano Bicocca, Italy·       Ruth Byrne -Trinity College Dublin, Ireland·       Marco Catani - KingCollege London, UK·       Gustavo Deco - PompeuFabra Univesity, Spain·       Scott Fairhall -University of Trento, Italy·       Randy Gallistel -Rutgers University, USA·       Melvyn Goodale -Western University, Canada·       Patrick Haggard -University College London, UK·       Takao Hensch -Harvard University, USA·       Zoe Kourtzi -Cambridge University, UK·       Nikos Logothetis -Max Planck Institute, Germany·       Emiliano Macaluso -University of Lyon, France·       Tamar Makin -University College London, UK·       Alex Martin -National Institute of Mental Health, USA·       Louise McNally -Pompeu Fabra University, Spain·       Satu Palva -University of Helsinki, Finland·       Stefano Panzeri - ItalianInstitute of Technology, Italy·       David Poeppel -New York University, USA·       Tim Shallice -University College London, UK·       Antonino Vallesi -University of Padova, ItalyWe look forward to seeing you there.The Organizing CommitteeCarlo Miniussi, Yuri Bozzi, Veronica Mazza, FrancescoPavani, Luca Turella, Massimiliano Zampini.  Marta Bortoletto, PhD Cognitive Neuroscience Section, IRCCS Centro San Giovanni di Dio Fatebenefratelli Via Pilastroni 4, 25125 Brescia, Italy Phone number: (+39) 0303501594 E-mail: marta.bortoletto at cognitiveneuroscience.it web: http://www.cognitiveneuroscience.it/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Tue Jul 4 15:21:56 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Tue, 4 Jul 2017 13:21:56 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? References: <1460287005.7559270.1499174516032.ref@mail.yahoo.com> Message-ID: <1460287005.7559270.1499174516032@mail.yahoo.com> Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence). With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal). I hope this helps. Best,Maité El Jueves 29 de junio de 2017 12:24, Maria Hakonen escribió: Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.a.sprenger at rug.nl Tue Jul 4 16:56:51 2017 From: s.a.sprenger at rug.nl (Sprenger, S.A.) Date: Tue, 4 Jul 2017 16:56:51 +0200 Subject: [FieldTrip] How to adapt a layout file Message-ID: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/ template/layout/easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 18:03:47 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 16:03:47 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials Message-ID: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Hi everyone, I am now trying to use the DICS method for sourceanalysis, with 'powandcsd' output from ft_freqanalysis as its input and using a precomputed filter and leadfield. However, I would like to keep my separate trial estimates in the final source analysis, and while the documentation suggests I should be able to get that with cfg.keeptrials, but this doesn't have the expected effect. I previously made workaround using PCC on fourier data instead (see below), I think to deal with this issue. I was wondering if this is still the recommended option, i.e. workaround? Alternatively, and perhaps preferably, would someone have a suggestion for a solution consistent with the DICS implementation? Thanks for your time, Stephen % source analysis cfg.method = 'pcc'; ... cfg.keeptrials = 'yes'; cfg.pcc.keepmom = 'yes'; cfg.pcc.fixedori = 'no'; source_control = ft_sourceanalysis(cfg, FFT); and then: % project moment and tapers cfg = []; cfg.projectmom = 'no'; cfg.keeptrials = 'yes'; cfg.powmethod = 'lambda1'; source = ft_sourcedescriptives(cfg,source); -------------- next part -------------- An HTML attachment was scrubbed... URL: From magazzinil at gmail.com Tue Jul 4 18:32:27 2017 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Tue, 4 Jul 2017 17:32:27 +0100 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, Perhaps you could try to add the option cfg.rawtrial = 'yes'. I'm not entirely sure, but maybe by using a precomputed filter, the same filter is applied to each single trial separately (rather than constructing a different filter individually for each trial, which I guess is not what you want to do). Lorenzo Lorenzo Magazzini, PhD Research Associate CUBRIC Cardiff University Cardiff CF24 4HQ Tel: +44 (0)2920 870090 *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php * On 4 July 2017 at 17:03, Stephen Whitmarsh wrote: > Hi everyone, > > I am now trying to use the DICS method for sourceanalysis, with > 'powandcsd' output from ft_freqanalysis as its input and using a > precomputed filter and leadfield. However, I would like to keep my separate > trial estimates in the final source analysis, and while the documentation > suggests I should be able to get that with cfg.keeptrials, but this doesn't > have the expected effect. > > I previously made workaround using PCC on fourier data instead (see > below), I think to deal with this issue. I was wondering if this is still > the recommended option, i.e. workaround? Alternatively, and perhaps > preferably, would someone have a suggestion for a solution consistent with > the DICS implementation? > > Thanks for your time, > Stephen > > % source analysis > cfg.method = 'pcc'; > ... > cfg.keeptrials = 'yes'; > cfg.pcc.keepmom = 'yes'; > cfg.pcc.fixedori = 'no'; > source_control = ft_sourceanalysis(cfg, FFT); > > and then: > > % project moment and tapers > cfg = []; > cfg.projectmom = 'no'; > cfg.keeptrials = 'yes'; > cfg.powmethod = 'lambda1'; > source = ft_sourcedescriptives(cfg,source); > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 18:51:47 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 18:51:47 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Lorenzo, Thanks, I will give it a try tomorrow, but the documentation suggest that it's not what I want: Just for clarity, I would like to use the same filter on separate trials. Best wishes, Stephen On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > Hi Stephen, > > Perhaps you could try to add the option cfg.rawtrial = 'yes'. > > I'm not entirely sure, but maybe by using a precomputed filter, the same > filter is applied to each single trial separately (rather than constructing > a different filter individually for each trial, which I guess is not what > you want to do). > > Lorenzo > > > > Lorenzo Magazzini, PhD > > Research Associate > > CUBRIC > > Cardiff University > > Cardiff CF24 4HQ > > Tel: +44 (0)2920 870090 <+44%2029%202087%200090> > > *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php > * > > > > > On 4 July 2017 at 17:03, Stephen Whitmarsh > wrote: > >> Hi everyone, >> >> I am now trying to use the DICS method for sourceanalysis, with >> 'powandcsd' output from ft_freqanalysis as its input and using a >> precomputed filter and leadfield. However, I would like to keep my separate >> trial estimates in the final source analysis, and while the documentation >> suggests I should be able to get that with cfg.keeptrials, but this doesn't >> have the expected effect. >> >> I previously made workaround using PCC on fourier data instead (see >> below), I think to deal with this issue. I was wondering if this is still >> the recommended option, i.e. workaround? Alternatively, and perhaps >> preferably, would someone have a suggestion for a solution consistent with >> the DICS implementation? >> >> Thanks for your time, >> Stephen >> >> % source analysis >> cfg.method = 'pcc'; >> ... >> cfg.keeptrials = 'yes'; >> cfg.pcc.keepmom = 'yes'; >> cfg.pcc.fixedori = 'no'; >> source_control = ft_sourceanalysis(cfg, FFT); >> >> and then: >> >> % project moment and tapers >> cfg = []; >> cfg.projectmom = 'no'; >> cfg.keeptrials = 'yes'; >> cfg.powmethod = 'lambda1'; >> source = ft_sourcedescriptives(cfg,source); >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiew1202 at gmail.com Tue Jul 4 19:36:55 2017 From: xiew1202 at gmail.com (Xie Wanze) Date: Tue, 04 Jul 2017 17:36:55 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, I met the same issue last year when I did my source analysis and functional connectivity analysis. I asked it through the maillist but no one seemed to have an answer. What I ended up with doing was to maunally calculate the source analysis with the spatial filter for each single trial. So,1. Use the ft_sourceanalysis to get the filter. 2. Multiply the filter with your single trial data with a loop or whatever. Wanze Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > Hi Lorenzo, > > Thanks, I will give it a try tomorrow, but the documentation suggest that > it's not what I want: Just for clarity, I would like to use the same filter > on separate trials. > > Best wishes, > Stephen > > On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > >> Hi Stephen, >> >> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >> >> I'm not entirely sure, but maybe by using a precomputed filter, the same >> filter is applied to each single trial separately (rather than constructing >> a different filter individually for each trial, which I guess is not what >> you want to do). >> >> Lorenzo >> >> >> >> Lorenzo Magazzini, PhD >> >> Research Associate >> >> CUBRIC >> >> Cardiff University >> >> Cardiff CF24 4HQ >> >> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >> >> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >> * >> >> >> >> >> On 4 July 2017 at 17:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiew1202 at gmail.com Tue Jul 4 19:38:15 2017 From: xiew1202 at gmail.com (Xie Wanze) Date: Tue, 04 Jul 2017 17:38:15 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: I mean manually calculated the filter with ft source analysis. Sorry for my typo in my last email. Good luck. Wanze Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > Hi Lorenzo, > > Thanks, I will give it a try tomorrow, but the documentation suggest that > it's not what I want: Just for clarity, I would like to use the same filter > on separate trials. > > Best wishes, > Stephen > > On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > >> Hi Stephen, >> >> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >> >> I'm not entirely sure, but maybe by using a precomputed filter, the same >> filter is applied to each single trial separately (rather than constructing >> a different filter individually for each trial, which I guess is not what >> you want to do). >> >> Lorenzo >> >> >> >> Lorenzo Magazzini, PhD >> >> Research Associate >> >> CUBRIC >> >> Cardiff University >> >> Cardiff CF24 4HQ >> >> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >> >> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >> * >> >> >> >> >> On 4 July 2017 at 17:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 19:48:56 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 19:48:56 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Wanze, Sorry to hear you didn't get a response last year, but thanks for sharing yours! Indeed, that seems to be the most elegant work-around to me as well. I'll probably do that. Thanks! Stephen On 4 July 2017 at 19:38, Xie Wanze wrote: > I mean manually calculated the filter with ft source analysis. Sorry for > my typo in my last email. > > Good luck. > > Wanze > Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > >> Hi Lorenzo, >> >> Thanks, I will give it a try tomorrow, but the documentation suggest that >> it's not what I want: Just for clarity, I would like to use the same filter >> on separate trials. >> >> Best wishes, >> Stephen >> >> On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: >> >>> Hi Stephen, >>> >>> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >>> >>> I'm not entirely sure, but maybe by using a precomputed filter, the same >>> filter is applied to each single trial separately (rather than constructing >>> a different filter individually for each trial, which I guess is not what >>> you want to do). >>> >>> Lorenzo >>> >>> >>> >>> Lorenzo Magazzini, PhD >>> >>> Research Associate >>> >>> CUBRIC >>> >>> Cardiff University >>> >>> Cardiff CF24 4HQ >>> >>> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >>> >>> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >>> * >>> >>> >>> >>> >>> On 4 July 2017 at 17:03, Stephen Whitmarsh >>> wrote: >>> >>>> Hi everyone, >>>> >>>> I am now trying to use the DICS method for sourceanalysis, with >>>> 'powandcsd' output from ft_freqanalysis as its input and using a >>>> precomputed filter and leadfield. However, I would like to keep my separate >>>> trial estimates in the final source analysis, and while the documentation >>>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>>> have the expected effect. >>>> >>>> I previously made workaround using PCC on fourier data instead (see >>>> below), I think to deal with this issue. I was wondering if this is still >>>> the recommended option, i.e. workaround? Alternatively, and perhaps >>>> preferably, would someone have a suggestion for a solution consistent with >>>> the DICS implementation? >>>> >>>> Thanks for your time, >>>> Stephen >>>> >>>> % source analysis >>>> cfg.method = 'pcc'; >>>> ... >>>> cfg.keeptrials = 'yes'; >>>> cfg.pcc.keepmom = 'yes'; >>>> cfg.pcc.fixedori = 'no'; >>>> source_control = ft_sourceanalysis(cfg, FFT); >>>> >>>> and then: >>>> >>>> % project moment and tapers >>>> cfg = []; >>>> cfg.projectmom = 'no'; >>>> cfg.keeptrials = 'yes'; >>>> cfg.powmethod = 'lambda1'; >>>> source = ft_sourcedescriptives(cfg,source); >>>> >>>> >>>> >>>> _______________________________________________ >>>> fieldtrip mailing list >>>> fieldtrip at donders.ru.nl >>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Wed Jul 5 08:51:13 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Wed, 5 Jul 2017 06:51:13 +0000 Subject: [FieldTrip] Fwd: How to adapt a layout file References: Message-ID: <2D579D2D-F542-4FC2-A1A8-C0FCED73CC51@donders.ru.nl> Hi Simone, What is the question behind the question? The reason I ask this is because overcomplete layout files (i.e. files containing more channels than you need) don’t prevent you from visualizing your own data. If you anyhow want to manually remove channels (and the corresponding information in pos/height etc) your code is not foolproof, most likely because setdiff may inadvertently alphabetize the labels, causing the mismatch you report. you could do: remove = {…}; sel = ismember(lay.label, remove); lay.pos = lay.pos(~sel,:); lay.height = lay.height(~sel); etc. Best, Jan-Mathijs On 04 Jul 2017, at 16:56, Sprenger, S.A. > wrote: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/template/layout/easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Wed Jul 5 10:40:39 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Wed, 5 Jul 2017 11:40:39 +0300 Subject: [FieldTrip] dipin and refdip in beamformer_dics? Message-ID: Dear Fieldtrip experts, As far as I understand, beamformer_dics gives coherence between two brain areas if I define parameters dipin and refdip. Could you please let me kown how dipin and refdip should be calculated or in which format they should be? Best, Maria -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.a.sprenger at rug.nl Thu Jul 6 10:11:05 2017 From: s.a.sprenger at rug.nl (Sprenger, S.A.) Date: Thu, 6 Jul 2017 10:11:05 +0200 Subject: [FieldTrip] How to adapt a layout file: thanks for the solution Message-ID: Dear Jan-Mathijs, Thank you very much for your response with respect to the adaption of layout files. The solution that you suggested works fine and our issue has been solved. In case someone would like to review the question and response, please see below. Kind regards, Simone ____________ Message: 9 Date: Wed, 5 Jul 2017 06:51:13 +0000 From: "Schoffelen, J.M. (Jan Mathijs)" To: FieldTrip discussion list Subject: [FieldTrip] Fwd: How to adapt a layout file Message-ID: <2D579D2D-F542-4FC2-A1A8-C0FCED73CC51 at donders.ru.nl> Content-Type: text/plain; charset="utf-8" Hi Simone, What is the question behind the question? The reason I ask this is because overcomplete layout files (i.e. files containing more channels than you need) don?t prevent you from visualizing your own data. If you anyhow want to manually remove channels (and the corresponding information in pos/height etc) your code is not foolproof, most likely because setdiff may inadvertently alphabetize the labels, causing the mismatch you report. you could do: remove = {?}; sel = ismember(lay.label, remove); lay.pos = lay.pos(~sel,:); lay.height = lay.height(~sel); etc. Best, Jan-Mathijs On 04 Jul 2017, at 16:56, Sprenger, S.A. > wrote: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/template/layout/ easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 -------------- next part -------------- An HTML attachment was scrubbed... URL: From orekhova.elena.v at gmail.com Thu Jul 6 16:57:07 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Thu, 6 Jul 2017 16:57:07 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Just recently had the same problem. It worked with cfg.rawtrial='yes'. Best, Elena On 4 July 2017 at 18:03, Stephen Whitmarsh wrote: > Hi everyone, > > I am now trying to use the DICS method for sourceanalysis, with > 'powandcsd' output from ft_freqanalysis as its input and using a > precomputed filter and leadfield. However, I would like to keep my separate > trial estimates in the final source analysis, and while the documentation > suggests I should be able to get that with cfg.keeptrials, but this doesn't > have the expected effect. > > I previously made workaround using PCC on fourier data instead (see > below), I think to deal with this issue. I was wondering if this is still > the recommended option, i.e. workaround? Alternatively, and perhaps > preferably, would someone have a suggestion for a solution consistent with > the DICS implementation? > > Thanks for your time, > Stephen > > % source analysis > cfg.method = 'pcc'; > ... > cfg.keeptrials = 'yes'; > cfg.pcc.keepmom = 'yes'; > cfg.pcc.fixedori = 'no'; > source_control = ft_sourceanalysis(cfg, FFT); > > and then: > > % project moment and tapers > cfg = []; > cfg.projectmom = 'no'; > cfg.keeptrials = 'yes'; > cfg.powmethod = 'lambda1'; > source = ft_sourcedescriptives(cfg,source); > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Thu Jul 6 18:03:51 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Thu, 6 Jul 2017 18:03:51 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Elena! Thanks! But I do wonder.. did you check whether the common filter (specified in the cfg) was used or whether a filter was calculated for each trial separately (which does not make sense in my case)? Best, Stephen On 6 July 2017 at 16:57, Elena Orekhova wrote: > Just recently had the same problem. > It worked with cfg.rawtrial='yes'. > > Best, > Elena > > On 4 July 2017 at 18:03, Stephen Whitmarsh > wrote: > >> Hi everyone, >> >> I am now trying to use the DICS method for sourceanalysis, with >> 'powandcsd' output from ft_freqanalysis as its input and using a >> precomputed filter and leadfield. However, I would like to keep my separate >> trial estimates in the final source analysis, and while the documentation >> suggests I should be able to get that with cfg.keeptrials, but this doesn't >> have the expected effect. >> >> I previously made workaround using PCC on fourier data instead (see >> below), I think to deal with this issue. I was wondering if this is still >> the recommended option, i.e. workaround? Alternatively, and perhaps >> preferably, would someone have a suggestion for a solution consistent with >> the DICS implementation? >> >> Thanks for your time, >> Stephen >> >> % source analysis >> cfg.method = 'pcc'; >> ... >> cfg.keeptrials = 'yes'; >> cfg.pcc.keepmom = 'yes'; >> cfg.pcc.fixedori = 'no'; >> source_control = ft_sourceanalysis(cfg, FFT); >> >> and then: >> >> % project moment and tapers >> cfg = []; >> cfg.projectmom = 'no'; >> cfg.keeptrials = 'yes'; >> cfg.powmethod = 'lambda1'; >> source = ft_sourcedescriptives(cfg,source); >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From explena at gmail.com Fri Jul 7 05:21:58 2017 From: explena at gmail.com (Shen-Mou Hsu) Date: Fri, 7 Jul 2017 11:21:58 +0800 Subject: [FieldTrip] a question regarding the code for PPC computation Message-ID: Dear FT users, I am writing to request how pairwise phase consistency (PPC) is implemented in Fieldtrip. I trace the code and find that the following lines are relevant for PPC computation input = input./abs(input); % normalize the crosspectrum outsum = nansum(input); % compute the sum; this is 1 x size(2:end) c = (outsum.*conj(outsum) - n)./(n*(n-1)); % do the pairwise thing in a handy way However, when I try to verify the results by performing the equations indicated by Vinck et. al. (2010), the outcomes are totally different from those performed using ft_connectivity_ppc. My code is as follows and many thanks for any help. %%%%%%%%%%%%%%%%%%%%%%%%% nTrial = size(input,1); ppc_all = []; for j = 1:(nTrial-1) for k = (j+1):nTrial ppc_temp = input(j,1,:,:).*conj(input(k,1,:,:)); ppc_all = [ppc_all;ppc_temp]; end end PPC = squeeze(abs(nansum(ppc_all,1)*2/(nTrial*(nTrial-1)))); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Best, Shen-Mou Hsu -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Fri Jul 7 08:08:10 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Fri, 7 Jul 2017 09:08:10 +0300 Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence). With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal). I hope this helps. Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions. Best, Maria 2017-06-29 12:57 GMT+03:00 Maria Hakonen : > Hi Maria, > for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. > > Best,Maité > http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series > http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series > > Hi Maité, > > Thank for your answer again! > > However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics? > > Best, > > Maria > > > 2017-06-26 12:45 GMT+03:00 Maria Hakonen : > >> Hi Maria, >> maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. >> >> Best,Maité >> >> >> Hi Maité, >> >> Could you please yet let me know how to get the sources timecources? >> source = ft_sourceanalysis(cfg, freq); only gives >> source = >> >> freq: 18 >> cumtapcnt: [180x1 double] >> dim: [19 15 15] >> inside: [4275x1 logical] >> pos: [4275x3 double] >> method: 'average' >> avg: [1x1 struct] >> cfg: [1x1 struct] >> >> Best, >> Maria >> >> 2017-06-25 13:53 GMT+03:00 Maria Hakonen : >> >>> Hi Maité, >>> >>> Thank you for your answer! >>> >>> I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.org/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this? >>> >>> BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum. >>> >>> Best, >>> >>> Maria >>> >>> >>> Hi Maria, >>> Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: >>> >>> cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; >>> cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; >>> As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. >>> I hope it helps. >>> Best wishes,Maité >>> >>> >>> >>> Dear FieldTrip experts, >>> >>> I have just started to use Fieldtrip and would like to estimate >>> coherence between MEG responses measured in two different conditions from >>> the same cortical areas. The example in Appendix 1 is close to what I would >>> like to do: >>> http://www.fieldtriptoolbox.org/tutorial/coherence >>> >>> However, in the example, coherence is calculated between the reference >>> signal (EMG) and all MEG channels. Could it be possible to calculate >>> coherence between each MEG channel in one condition and the same MEG >>> channels in the other condition, that is: >>> ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... >>> >>> As far as I understand, the example in Appendix 1 would do this: >>> ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in >>> cond2, ... >>> >>> Best, >>> Maria >>> >>> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From christian.merkel at med.ovgu.de Fri Jul 7 09:19:06 2017 From: christian.merkel at med.ovgu.de (christian.merkel at med.ovgu.de) Date: Fri, 7 Jul 2017 07:19:06 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis Message-ID: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> Hallo to all, My name is Christian Merkel and im using fieldtrip to estimate sources within the visual cortex using high-res sourcemodels from freesurfer. We use an elekta system in our lab. I have a question regarding the time course of activation within the sourcespace once i calculated the spatial filter with ft_sourceanalysis. Here the code for ft_sourceanalysis: cfg = []; cfg.method = 'lcmv'; cfg.channel = sens_aligned.label(strcmp(sens_aligned.chantype,'megplanar')); cfg.grid = lead field_grad; cfg.vol = bem; cfg.projectnoise = 'yes'; cfg.keepfilter = 'yes'; cfg.lambda = 1; data_erf_source = ft_sourceanalysis(cfg, data_cond_erf_bl_avg); The filter looks good and everything works fine. However I have a conceptual question about the timecourse in sourcespace: As far as I understand, the field avg.mom of data_erf_source contains the activation time_course. So to plot one specific sourcedistribution at one time sample I use: pow = squeeze(sort(sum(cat(3,data_erf_source.avg.mom{:}).^2,1)))'; % i use the abs norm of the 3 orientation vectors as a value of source strength figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow(:,time_of_interest)); One other way to get the source distribution at that sample is to convolve the filter with the underlying erf-data: pow = squeeze(sort(sum(cat(3,data_erf_source.avg.filter{:}).^2,1)))'; figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow * data_cond_erf_bl_avg.avg(:,time_of_interest)); But those to distributions look different. Not completely different, but substantially. Why are those two ways of calculating the source-distribution different. I thought that ft_sourceanalysis calculates the field 'mom' by basically convolving the erf_data with the spatial filter and therefore should result in the same distribution as the second version. What is the 'right' way in this case and what do you recommend I use. I thank you for your help. From jan.schoffelen at donders.ru.nl Fri Jul 7 10:13:31 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 7 Jul 2017 08:13:31 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis In-Reply-To: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> References: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> Message-ID: Dear Christian, > pow = squeeze(sort(sum(cat(3,data_erf_source.avg.mom{:}).^2,1)))'; % i use the abs norm of the 3 orientation vectors as a value of source strength > figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow(:,time_of_interest)); > > One other way to get the source distribution at that sample is to convolve the filter with the underlying erf-data: > > pow = squeeze(sort(sum(cat(3,data_erf_source.avg.filter{:}).^2,1)))'; > figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow * data_cond_erf_bl_avg.avg(:,time_of_interest)); > > > But those to distributions look different. Not completely different, but substantially. Well, let me first be a bit pedantic, by saying that one does not ‘convolve’ the filter with the underlying erf-data, it’s just a multiplication. But no worries, that’s just terminology. The thing that goes wrong in your filter-times-erfdata step, is the fact that you already collapse the spatial filter across the three dipole orientations (and take the square), prior to doing the multiplication. So the difference lies in the order of the operations, it should be sum((F*sensorERF).^2,1). In this case F is a single entry from source.avg.filter. Best, Jan-Mathijs > Why are those two ways of calculating the source-distribution different. I thought that ft_sourceanalysis calculates the field 'mom' by basically convolving the erf_data with the spatial filter and therefore should result in the same distribution as the second version. What is the 'right' way in this case and what do you recommend I use. > > I thank you for your help. > > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From christian.merkel at med.ovgu.de Fri Jul 7 10:28:54 2017 From: christian.merkel at med.ovgu.de (christian.merkel at med.ovgu.de) Date: Fri, 7 Jul 2017 08:28:54 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis In-Reply-To: References: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de>, Message-ID: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D46@esen3.imed.uni-magdeburg.de> Thanks a lot, That makes sense!! I have one follow-up question: What if i want to correct with the noise-term? Should i do that on the single orientations as well or just after the multiplication? I could imagine after, as for the mom-field i can only apply it to the end-result anyway. You're a big help, Christian From orekhova.elena.v at gmail.com Fri Jul 7 10:31:37 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 10:31:37 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, I followed the tutorial in http://www.fieldtriptoolbox.org/tutorial/salzburg, but used 'dics' (see below). I think that in the example below the sourceavg.avg.filter was indeed used and my results look nice. Elena cfg=[];cfg.method='lcmv';cfg.grid =grid ;cfg.grid .filter =sourceavg.avg.filter ;cfg.rawtrial = 'yes';cfg.vol=hdm; sourcepreS1=ft_sourceanalysis(cfg, avgpre); sourcepstS1=ft_sourceanalysis(cfg, avgpst); On 6 July 2017 at 18:03, Stephen Whitmarsh wrote: > Hi Elena! > > Thanks! But I do wonder.. did you check whether the common filter > (specified in the cfg) was used or whether a filter was calculated for each > trial separately (which does not make sense in my case)? > > Best, > Stephen > > On 6 July 2017 at 16:57, Elena Orekhova > wrote: > >> Just recently had the same problem. >> It worked with cfg.rawtrial='yes'. >> >> Best, >> Elena >> >> On 4 July 2017 at 18:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Fri Jul 7 10:57:17 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Fri, 7 Jul 2017 10:57:17 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Elena, Thanks for the link - that is indeed a very nice and complete tutorial! A link in the current beamformer tutorial would be helpful for the next time I think - I will put one there. And yes, I see now that although the documentation is as follows: % cfg.rawtrial = 'no' or 'yes' *construct filter from single trials*, apply to single trials. Note that you also may want to set cfg.keeptrials='yes' to keep all trial information, especially if using in combination with grid.filter (I find the red part inconsistent) it does take the pre-specified filter when provided, which is suggested somewhat implicitly further down in the code: if strcmp(cfg.rawtrial,'yes') && isfield(cfg,'grid') && ~isfield(cfg.grid,'filter') warning('Using each trial to compute its own filter is not currently recommended. Use this option only with precomputed filters in grid.filter'); end So that really clears it up. I will suggest an edit to the documentation, for the sake of clarification, and next time I run my beamformer I will remove the loop over trials :-) Thanks again, Stephen On 7 July 2017 at 10:31, Elena Orekhova wrote: > Hi Stephen, > I followed the tutorial in http://www.fieldtriptoolbox.or > g/tutorial/salzburg, but used 'dics' (see below). > I think that in the example below the sourceavg.avg.filter was indeed > used and my results look nice. > > Elena > > cfg=[];cfg.method='lcmv';cfg.grid =grid ;cfg.grid .filter =sourceavg.avg.filter ;cfg.rawtrial = 'yes';cfg.vol=hdm; > sourcepreS1=ft_sourceanalysis(cfg, avgpre); > sourcepstS1=ft_sourceanalysis(cfg, avgpst); > > > > On 6 July 2017 at 18:03, Stephen Whitmarsh > wrote: > >> Hi Elena! >> >> Thanks! But I do wonder.. did you check whether the common filter >> (specified in the cfg) was used or whether a filter was calculated for each >> trial separately (which does not make sense in my case)? >> >> Best, >> Stephen >> >> On 6 July 2017 at 16:57, Elena Orekhova >> wrote: >> >>> Just recently had the same problem. >>> It worked with cfg.rawtrial='yes'. >>> >>> Best, >>> Elena >>> >>> On 4 July 2017 at 18:03, Stephen Whitmarsh >>> wrote: >>> >>>> Hi everyone, >>>> >>>> I am now trying to use the DICS method for sourceanalysis, with >>>> 'powandcsd' output from ft_freqanalysis as its input and using a >>>> precomputed filter and leadfield. However, I would like to keep my separate >>>> trial estimates in the final source analysis, and while the documentation >>>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>>> have the expected effect. >>>> >>>> I previously made workaround using PCC on fourier data instead (see >>>> below), I think to deal with this issue. I was wondering if this is still >>>> the recommended option, i.e. workaround? Alternatively, and perhaps >>>> preferably, would someone have a suggestion for a solution consistent with >>>> the DICS implementation? >>>> >>>> Thanks for your time, >>>> Stephen >>>> >>>> % source analysis >>>> cfg.method = 'pcc'; >>>> ... >>>> cfg.keeptrials = 'yes'; >>>> cfg.pcc.keepmom = 'yes'; >>>> cfg.pcc.fixedori = 'no'; >>>> source_control = ft_sourceanalysis(cfg, FFT); >>>> >>>> and then: >>>> >>>> % project moment and tapers >>>> cfg = []; >>>> cfg.projectmom = 'no'; >>>> cfg.keeptrials = 'yes'; >>>> cfg.powmethod = 'lambda1'; >>>> source = ft_sourcedescriptives(cfg,source); >>>> >>>> >>>> >>>> _______________________________________________ >>>> fieldtrip mailing list >>>> fieldtrip at donders.ru.nl >>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Fri Jul 7 11:17:16 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Fri, 7 Jul 2017 09:17:16 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: <35126809.503758.1499419036176@mail.yahoo.com> Hi Maria, You are right. I was having a look inside the "inverse\beamformer_dics" function (I suggest you check it out too). As you could see in line 519 of the same function, refdip can be an structure with a field called 'filter' containing the beamformer filter for a particular voxel (brain region of condition 2, for example). So, you could first compute the DICS filters for condition 2 and then passing them one by one in the cfg,refdip when calling the ft_sourceanalysis together with the data of condition 1. I hope this works out. Best wishes,Maité El Viernes 7 de julio de 2017 8:23, Maria Hakonen escribió: Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence).With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal).I hope this helps.  Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions.  Best,Maria    2017-06-29 12:57 GMT+03:00 Maria Hakonen : Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox. org/tutorial/connectivity# extract_the_virtual_channel_ time-series http://www.fieldtriptoolbox. org/tutorial/shared/virtual_ sensors#extract_the_virtual_ channel_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Fri Jul 7 11:25:06 2017 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Fri, 7 Jul 2017 10:25:06 +0100 Subject: [FieldTrip] PhD positions in Birmingham, UK with Prof. Noppeney Message-ID: Dear all, Prof. Uta Noppeney (with whom I now work) has available these 2 PhD positions for an exciting new project: 1. Robust audiovisual speech recognition in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87556 2. Syntactic parsing in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87595 Please contact Uta (U.Noppeney at bham.ac.uk) with any questions. Kind regards, Johanna -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Fri Jul 7 11:41:51 2017 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Fri, 7 Jul 2017 10:41:51 +0100 Subject: [FieldTrip] PhD positions in Birmingham, UK with Prof. Noppeney Message-ID: Dear all, Prof. Uta Noppeney (with whom I now work) has available these 2 PhD positions for an exciting new project: 1. Robust audiovisual speech recognition in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87556 2. Syntactic parsing in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87595 Please contact Uta (U.Noppeney at bham.ac.uk) with any questions. Kind regards, Johanna -------------- next part -------------- An HTML attachment was scrubbed... URL: From orekhova.elena.v at gmail.com Fri Jul 7 16:14:21 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 16:14:21 +0200 Subject: [FieldTrip] mri segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the fig. below). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena [image: Displaying image.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 70400 bytes Desc: not available URL: From orekhova.elena.v at gmail.com Fri Jul 7 16:26:17 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 16:26:17 +0200 Subject: [FieldTrip] mri segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the fig. below). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena [image: Displaying image.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 70400 bytes Desc: not available URL: From orekhova.elena.v at gmail.com Sat Jul 8 19:11:17 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Sat, 8 Jul 2017 19:11:17 +0200 Subject: [FieldTrip] brain segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fig1.png Type: image/png Size: 66721 bytes Desc: not available URL: From RICHARDS at mailbox.sc.edu Sun Jul 9 14:45:10 2017 From: RICHARDS at mailbox.sc.edu (RICHARDS, JOHN) Date: Sun, 9 Jul 2017 12:45:10 +0000 Subject: [FieldTrip] fieldtrip Digest, Vol 80, Issue 7 In-Reply-To: References: Message-ID: Elena The ft_volumesegment uses the SPM program that does gm/wm segmentation into probability maps. In the case of using = {'brain', 'skull', 'scalp'}; as input, the program sums the PVE for GM, WM and "CSF" (other matter) to create the brain (+ fill holes and some other); then has a formula for finding the skull (dilate brain, or use bone class from segmented MRI), and scalp. So the "skullstrip" portion consists of the brain PVEs from the SPM segmentation program. If that program does not work correctly then the overlap of the brain mask will not match the actual brain--could either not cover all the brain or cover more than the brain. I have had some issues with the SPM algorithm, and its use in the ft_volumesegment is not very flexible. I do the segmentation outside of FT using FSL tools (e.g., bet, bet2, betsurf) and then import the segmented head into FT format; FSL also has an algorithm for "skull stripping" found in its VBM script. This way I have more control over the initial segmented products. Additionally, neither the SPM nor the FSL routines work with some pediatric populations, especially infants under 2 years of age. In that case I often substitute the initial MRI template (in FT case, as SPM, they use the MNI segmented head) with an infant MRI template and get much better results. (e.g., neurodevelopmental MRI database). At times I have used the SPM algorithms for brain segmenting (GM, WM, CSF) and in this case also the PVEs from an age-appropriate brain improve the results. John *********************************************** John E. Richards Carolina Distinguished Professor Department of Psychology University of South Carolina Columbia, SC  29208 Dept Phone: 803 777 2079 Fax: 803 777 9558 Email: richards-john at sc.edu HTTP: jerlab.psych.sc.edu ************************************************* -----Original Message----- From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of fieldtrip-request at science.ru.nl Sent: Sunday, July 9, 2017 6:00 AM To: fieldtrip at science.ru.nl Subject: fieldtrip Digest, Vol 80, Issue 7 Send fieldtrip mailing list submissions to fieldtrip at science.ru.nl To subscribe or unsubscribe via the World Wide Web, visit https://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. brain segmentation problem (Elena Orekhova) ---------------------------------------------------------------------- Message: 1 Date: Sat, 8 Jul 2017 19:11:17 +0200 From: Elena Orekhova To: FieldTrip discussion list Subject: [FieldTrip] brain segmentation problem Message-ID: Content-Type: text/plain; charset="utf-8" Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fig1.png Type: image/png Size: 66721 bytes Desc: not available URL: ------------------------------ _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip End of fieldtrip Digest, Vol 80, Issue 7 **************************************** From anne.urai at gmail.com Mon Jul 10 10:38:59 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 10 Jul 2017 01:38:59 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 Message-ID: Dear Fieldtrippers, I'm using the VTPM atlas to define masks for all the visual regions described in the paper (Wang et al. 2014, https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bhu277). However, there seem to be no entries corresponding to the left IPS5. *% load atlas* *atl = ft_read_atlas('~/Documents/fieldtrip/vtpm/vtpm.mat');* *atl = ft_convert_units(atl, 'cm');* *% add mni coordinates* *[ax, ay, az] = voxelcoords(atl.dim, atl.transform);* *atl.pos = [ax(:) ay(:) az(:)];* *% make a binary mask for this ROI* *roi_idx = find(strcmp(lower(atl.tissuelabel), 'IPS5'));* *roi_mask = ismember(atl.tissue, roi_idx);* *% mask the voxels on the right side of the brain* *rightidx = find(atl.pos(:, 1) > 0); * *roi_mask(rightidx) = 0;* Now, sum(roi_mask(:)) = 0. This procedure of separating out the left and right regions works fine for all other regions in the atlas, as well as the right IPS5. The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? Thanks! — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Mon Jul 10 14:37:20 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Mon, 10 Jul 2017 15:37:20 +0300 Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: Hi Maité, Many thanks for your answer! I have now tried to get coherence between two conditions following the Appendix 1 (I have also used the same data as in Appendix 1; http://www.fieldtriptoolbox.org/tutorial/coherence). As far as I understand, I should first calculate ft_freqanalysis and ft_sourceanalysis separately for condition 1 and condition 2 as follows: *Condition 1:* Compute the cross-spectral density matrix for 18 Hz: cfg = []; cfg.method = 'mtmfft'; cfg.output = 'powandcsd'; cfg.foilim = [18 18]; cfg.tapsmofrq = 5; cfg.keeptrials = 'yes'; freq1 = ft_freqanalysis(cfg, data); The Appendix 1 also defines: cfg.channelcmb = {'MEG' 'MEG';'MEG' 'EMGlft'}; However, I think that in my case channelcmb is not needed since default = {'all' 'all'}. Thereafter, I used ft_sourceanalysis as follows: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; source1 = ft_sourceanalysis(cfg, freq); (The Appendix 1 also defines: cfg.refchan = 'EMGlft';) *Condition 2:* I calculated cross-spectral density exactly in the same way as in condition 1 but used data from condition 2. In ft_sourceanalysis, I set keepfilter and keepleadfiled as “yes”: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; cfg.keepfilter = ‘yes’; cfg.keepleadfield = ‘yes’; source2 = ft_sourceanalysis(cfg, freq2); Thereafter, I selected a source that in inside the brain from source2 and included it’s position, leadfield and filter in refdip: refdip = pos: [5 -5 -1] leadfield: {[151x3 double]} filetr: [3x151 double] After this, I run ft_sourceanalysis: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; cfg.refdip = refdip; source = ft_sourceanalysis(cfg, freq1); Here, I used cross spectral density matrix computed from condition 1 (i.e. freq1). I am not sure, whether I should also somehow take into account the data from condition 2 when calculating freq? Appendix 1 uses EMGlft as refchan in ft_sourceanalysis and has defined cfg.channelcmb = {'MEG' 'MEG';'MEG' 'EMGlft'}; in ft_freqanalysis. The coherence in the position of the reference dipole (i.e. 5 -5 -1) seems to be one, as would be expected since I used the same data in both conditions. Best, Maria 2017-07-07 9:08 GMT+03:00 Maria Hakonen : > Hi Maria, > > I think there is more than one solution for what you are aiming to do. > Maybe a more experienced user or developer could show you the most > straightforward way (?). > > IMO, using LCMV is more direct for this application because with DICS you > will need to provide the reference signal (i.e., the source timecourse from > the other condition). Therefore, you will need to apply LCMV anyway. > > You could apply a band-pass filter to the channel activity before > localizing the frequency band of interest with LCMV. Alternatively, you > could obtain the virtual channels (without band pass) and define the > frequency bands of interest when computing the coherence as in the tutorial > (see ft_freqanalysis steps at http://www.fieldtriptoolbox. > org/tutorial/coherence#computing_the_coherence). > With DICS, in this case, I see it more intricate: 1) obtain the source > timecourses of condition 2 with LCVM; 2) compute the cross spectral density > between all data channels and each source timecourse (reference signal); 3) > compute DICS for each reference signal. Of course, you don't need to > compute the coherence for the whole brain, but only for the source of > interest. For each reference signal, you could change the cfg.grid.inside > value to include only the position of the voxel of interest (the same voxel > of the reference signal). > I hope this helps. > > Best,Maité > > Hi Maité, > > Many thanks for your advice again! > > I have been wondering whether I could calculate coherence straight from > the cross spectros without reference signals or virtual channels by using > beamformer_dics. In beamformer_dics, it seems to be possible to define the > location of the dipole with which coherence is computed (i.e. refdip). > However, I am not sure if it is possible to calculate the coherence between > the same brain region in two different conditions. > > Best, > Maria > > 2017-06-29 12:57 GMT+03:00 Maria Hakonen : > >> Hi Maria, >> for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. >> >> Best,Maité >> http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series >> http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series >> >> Hi Maité, >> >> Thank for your answer again! >> >> However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics? >> >> Best, >> >> Maria >> >> >> 2017-06-26 12:45 GMT+03:00 Maria Hakonen : >> >>> Hi Maria, >>> maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. >>> >>> Best,Maité >>> >>> >>> Hi Maité, >>> >>> Could you please yet let me know how to get the sources timecources? >>> source = ft_sourceanalysis(cfg, freq); only gives >>> source = >>> >>> freq: 18 >>> cumtapcnt: [180x1 double] >>> dim: [19 15 15] >>> inside: [4275x1 logical] >>> pos: [4275x3 double] >>> method: 'average' >>> avg: [1x1 struct] >>> cfg: [1x1 struct] >>> >>> Best, >>> Maria >>> >>> 2017-06-25 13:53 GMT+03:00 Maria Hakonen : >>> >>>> Hi Maité, >>>> >>>> Thank you for your answer! >>>> >>>> I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.org/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this? >>>> >>>> BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum. >>>> >>>> Best, >>>> >>>> Maria >>>> >>>> >>>> Hi Maria, >>>> Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: >>>> >>>> cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; >>>> cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; >>>> As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. >>>> I hope it helps. >>>> Best wishes,Maité >>>> >>>> >>>> >>>> Dear FieldTrip experts, >>>> >>>> I have just started to use Fieldtrip and would like to estimate >>>> coherence between MEG responses measured in two different conditions from >>>> the same cortical areas. The example in Appendix 1 is close to what I would >>>> like to do: >>>> http://www.fieldtriptoolbox.org/tutorial/coherence >>>> >>>> However, in the example, coherence is calculated between the reference >>>> signal (EMG) and all MEG channels. Could it be possible to calculate >>>> coherence between each MEG channel in one condition and the same MEG >>>> channels in the other condition, that is: >>>> ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... >>>> >>>> As far as I understand, the example in Appendix 1 would do this: >>>> ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in >>>> cond2, ... >>>> >>>> Best, >>>> Maria >>>> >>>> >>> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From tzvetan.popov at uni-konstanz.de Mon Jul 10 14:58:24 2017 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Mon, 10 Jul 2017 14:58:24 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: <58C77EC6-E8FE-4C8B-978D-5C6C9C278CB1@uni-konstanz.de> Dear Anne, > > The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? this information was provided by the principle investigator of the paper. You might ask the corresponding author for further details on this. Best tzvetan -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Mon Jul 10 19:41:39 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Mon, 10 Jul 2017 17:41:39 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? References: <1981337653.3654632.1499708499318.ref@mail.yahoo.com> Message-ID: <1981337653.3654632.1499708499318@mail.yahoo.com> Dear Maria, you are right, the data from condition 2 should be contained in the channels cross-spectral-density matrix (Cf). If you would do it with the option 'dics_refchan', you could have the same situation as in the tutorial, but substituting the EMG signal by the source time-course. However, I understand you would prefer to use the option 'dics_refdip'; I am not sure whether it is programmed for your particular situation because the function uses only one Cf in this case. "Maybe" it works by providing the Cf including data from both conditions. But then, the dimension of the filters have to match this new Cf to fulfill the equation: csd = filt1 * Cf * ctranspose(filt2); (function beamformer_dics, line 562) And "maybe" you can extend the filters, setting to 0 the filters corresponding to the channels of the opposite condition. But here, you should get advice from somebody who knows the mathematics; I am just speculating, sorry. Best,Maité El Lunes 10 de julio de 2017 14:56, Maria Hakonen escribió: Hi Maité, Many thanksfor your answer! I have nowtried to get coherence between two conditions following the Appendix 1 (I have alsoused the same data as in Appendix 1; http://www.fieldtriptoolbox.org/tutorial/coherence).  As far as Iunderstand, I should first calculate ft_freqanalysis and ft_sourceanalysis separatelyfor condition 1 and condition 2 as follows: Condition1:Compute thecross-spectral density matrix for 18 Hz:cfg            = [];cfg.method     = 'mtmfft';cfg.output     = 'powandcsd';cfg.foilim     = [18 18];cfg.tapsmofrq  = 5;cfg.keeptrials = 'yes';freq1           = ft_freqanalysis(cfg, data); TheAppendix 1 also defines:cfg.channelcmb= {'MEG' 'MEG';'MEG' 'EMGlft'};However, Ithink that in my case channelcmb is not needed since default = {'all' 'all'}. Thereafter,I used ft_sourceanalysis as follows:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';source1              = ft_sourceanalysis(cfg, freq); (The Appendix1 also defines: cfg.refchan         = 'EMGlft';) Condition2:Icalculated cross-spectral density exactly in the same way as in condition 1 butused data from condition 2. In ft_sourceanalysis, I set keepfilterand keepleadfiled as “yes”:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';cfg.keepfilter = ‘yes’;  cfg.keepleadfield = ‘yes’;source2              = ft_sourceanalysis(cfg, freq2); Thereafter, I selected a source thatin inside the brain from source2 and included it’s position, leadfield andfilter in refdip:refdip =            pos: [5 -5 -1]   leadfield: {[151x3 double]}       filetr: [3x151 double] After this,I run ft_sourceanalysis:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';cfg.refdip = refdip;source              = ft_sourceanalysis(cfg, freq1); Here, I used cross spectral densitymatrix computed from condition 1 (i.e. freq1). I am not sure, whether I should alsosomehow take into account the data from condition 2 when calculating freq?  Appendix 1 uses EMGlft as refchan inft_sourceanalysis and has defined  cfg.channelcmb= {'MEG' 'MEG';'MEG' 'EMGlft'}; in ft_freqanalysis. The coherence in the position of thereference dipole (i.e. 5 -5 -1) seems to be one, as would be expected since Iused the same data in both conditions.  Best,Maria  2017-07-07 9:08 GMT+03:00 Maria Hakonen : Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox. org/tutorial/coherence# computing_the_coherence).With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal).I hope this helps.  Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions.  Best,Maria    2017-06-29 12:57 GMT+03:00 Maria Hakonen : Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox.or g/tutorial/connectivity#extrac t_the_virtual_channel_time- series http://www.fieldtriptoolbox.or g/tutorial/shared/virtual_sens ors#extract_the_virtual_channe l_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From werkle at mpib-berlin.mpg.de Tue Jul 11 13:38:09 2017 From: werkle at mpib-berlin.mpg.de (MWB) Date: Tue, 11 Jul 2017 13:38:09 +0200 Subject: [FieldTrip] PhD Position in Project Area CONMEM at MPI for Human Development Message-ID: <5739dbcd-e183-6698-3f80-46d5c4e6369b@mpib-berlin.mpg.de> Dear colleagues, the project area "Cognitive an Neural Dynamics of Memory Across the Lifespan (CONMEM)", headed by Myriam Sander & Markus Werkle-Bergner, is searching for a PhD-candiate. Details on the position and the application procedures can be found at: https://www.mpib-berlin.mpg.de/sites/default/files/download/jobs/30-2017_stellenanzeige_lip-ie.pdf For further information, please contact Markus Werkle-Bergner (werkle at mpib-berlin.mpg.de) Best regards, Markus Werkle-Bergner -- ************************************************************** Dr. rer. nat. Markus Werkle-Bergner, Dipl. Psych. Senior Research Scientist (W2) Jacobs Foundation Research Fellow 2017-2019 Center for Lifespan Psychology Max Planck Institute for Human Development Lentzeallee 94, Room 211, D-14195 Berlin, Germany. Phone: +49(0)30-82406-447 Fax: +49(0)30-8249939 ************************************************************** From werkle at mpib-berlin.mpg.de Tue Jul 11 13:38:41 2017 From: werkle at mpib-berlin.mpg.de (MWB) Date: Tue, 11 Jul 2017 13:38:41 +0200 Subject: [FieldTrip] Post-Doc Position in Project Area CONMEM at MPI for Human Development Message-ID: <203919e1-7483-968d-f522-72ad0a78b66b@mpib-berlin.mpg.de> Dear colleagues, the project area "Cognitive an Neural Dynamics of Memory Across the Lifespan (CONMEM)", headed by Myriam Sander & Markus Werkle-Bergner, is searching for a post-doc. Details on the position and the application procedures can be found at: https://www.mpib-berlin.mpg.de/sites/default/files/download/jobs/29-2017_stellenanzeige_lip-ie.pdf For further information, please contact Markus Werkle-Bergner (werkle at mpib-berlin.mpg.de) Best regards, Markus Werkle-Bergner -- ************************************************************** Dr. rer. nat. Markus Werkle-Bergner, Dipl. Psych. Senior Research Scientist (W2) Jacobs Foundation Research Fellow 2017-2019 Center for Lifespan Psychology Max Planck Institute for Human Development Lentzeallee 94, Room 211, D-14195 Berlin, Germany. Phone: +49(0)30-82406-447 Fax: +49(0)30-8249939 ************************************************************** From M.Wimber at bham.ac.uk Tue Jul 11 17:11:36 2017 From: M.Wimber at bham.ac.uk (Maria Wimber) Date: Tue, 11 Jul 2017 15:11:36 +0000 Subject: [FieldTrip] Postdoc on memory & iEEG in Birmingham Message-ID: Hi FieldTrippers We are currently seeking a postdoctoral research fellow to join the Birmingham Memory Group. The position is funded by a 5-year European Research Council (ERC) grant awarded to Dr Maria Wimber (www.memorybham.com/maria-wimber), which aims to draw a time- and space-resolved map of memory reactivation in the human brain. The postdoc will have the rare opportunity to work with intracranial EEG recordings from the human hippocampus, including local field potential and single neuron data. The post should be interesting for researchers with a strong background in electrophysiology - EEG/MEG/iEEG, human or animal - and a general interest in long-term memory. More details about the position and an application link can be found here Research Fellow - 56716 Deadline for applications is August 16th 2017. Please distribute to potential candidates, who should feel free to contact the PI directly by email at m.wimber at bham.ac.uk. ---------------------- Dr Maria Wimber Senior Lecturer School of Psychology University of Birmingham tel +44 121 4144659 www.memorybham.com/maria-wimber -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Wed Jul 12 09:35:09 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Wed, 12 Jul 2017 07:35:09 +0000 Subject: [FieldTrip] fieldtrip Digest, Vol 80, Issue 7 In-Reply-To: References: Message-ID: <184AAEB3-B2E5-4C2A-B23F-C46532EA7091@donders.ru.nl> Dear Elena, John and the rest, Allow me to chime in a bit here to bring across John’s answer even more clearly. Indeed ft_volumesegment applies some postprocessing to the tissue-probability-maps (TPMs) as extracted with SPM. This involves amongst others some smoothing and thresholding, which may indeed result in the output to not fit very snugly with the underlying anatomy. However, the amount of smoothing and threshold is in principle in your hands, so you can adjust the parameters to your need. Just have a look at the documentation of the function for how it can be adjusted. Note, also, that I have made some recent changes to ft_volumesegment to allow for SPM-options to be configureable, i.e. you can influence the behaviour of the SPM-based step of the procedure. It is hard to give an optimal set of parameters here as well, because these depend on the quality of the anatomical images (and probably on the spm version used). The default values that are used in ft_volumesegment have been taken from the defaults that SPM uses, but there is no strict reason why these are optimal for all MR images. Also, I’d like to advertise the fact that I have now implemented full support for using SPM12 for the segmentation, where there’s now the option to use 1) a 6-tissue type TPM-template (for this you need to specify cfg.spmversion = ‘spm12’, along with cfg.spmmethod=‘new’), and 2) you can even postprocess the segmentation with the spm add-on ‘mars’. This can be done when specifying cfg.spmmethod=‘mars’, in combination with cfg.spmversion=‘spm12’. For whatever it’s worth… Happy computing! Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands > On 09 Jul 2017, at 14:45, RICHARDS, JOHN wrote: > > Elena > > The ft_volumesegment uses the SPM program that does gm/wm segmentation into probability maps. In the case of using = {'brain', 'skull', 'scalp'}; as input, the program sums the PVE for GM, WM and "CSF" (other matter) to create the brain (+ fill holes and some other); then has a formula for finding the skull (dilate brain, or use bone class from segmented MRI), and scalp. > > So the "skullstrip" portion consists of the brain PVEs from the SPM segmentation program. If that program does not work correctly then the overlap of the brain mask will not match the actual brain--could either not cover all the brain or cover more than the brain. > > I have had some issues with the SPM algorithm, and its use in the ft_volumesegment is not very flexible. I do the segmentation outside of FT using FSL tools (e.g., bet, bet2, betsurf) and then import the segmented head into FT format; FSL also has an algorithm for "skull stripping" found in its VBM script. This way I have more control over the initial segmented products. Additionally, neither the SPM nor the FSL routines work with some pediatric populations, especially infants under 2 years of age. In that case I often substitute the initial MRI template (in FT case, as SPM, they use the MNI segmented head) with an infant MRI template and get much better results. (e.g., neurodevelopmental MRI database). At times I have used the SPM algorithms for brain segmenting (GM, WM, CSF) and in this case also the PVEs from an age-appropriate brain improve the results. > > John > > > *********************************************** > John E. Richards > Carolina Distinguished Professor > Department of Psychology > University of South Carolina > Columbia, SC 29208 > Dept Phone: 803 777 2079 > Fax: 803 777 9558 > Email: richards-john at sc.edu > HTTP: jerlab.psych.sc.edu > ************************************************* > > > -----Original Message----- > From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of fieldtrip-request at science.ru.nl > Sent: Sunday, July 9, 2017 6:00 AM > To: fieldtrip at science.ru.nl > Subject: fieldtrip Digest, Vol 80, Issue 7 > > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > https://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. brain segmentation problem (Elena Orekhova) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 8 Jul 2017 19:11:17 +0200 > From: Elena Orekhova > To: FieldTrip discussion list > Subject: [FieldTrip] brain segmentation problem > Message-ID: > > Content-Type: text/plain; charset="utf-8" > > Dear Fieldtrip experts, > > I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used > > mri_orig= ft_read_mri ('T1.mgz'); > ... > cfg = []; > cfg.output = {'brain', 'skull', 'scalp'}; > mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); > > Have anybody had such a problem. How can it be resolved? > > Elena > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: fig1.png > Type: image/png > Size: 66721 bytes > Desc: not available > URL: > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 80, Issue 7 > **************************************** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From nima.noury at student.uni-tuebingen.de Fri Jul 14 12:09:13 2017 From: nima.noury at student.uni-tuebingen.de (Nima Noury) Date: Fri, 14 Jul 2017 12:09:13 +0200 Subject: [FieldTrip] 2017 Tuebingen Systems Neuroscience Symposium (SNS), Oct 11-12 Message-ID: <20170714120913.Horde.hQkjKPaafdf1u-VgVFclO4N@webmail.uni-tuebingen.de> The Centre for Integrative Neuroscience and MEG Center Tuebingen are pleased to announce the 2017 Tuebingen Systems Neuroscience Symposium (SNS2017) The symposium takes place on October 11 and 12, 2017 at the University of Tuebingen. This annual international meeting brings together leading researchers in the field of systems neuroscience featuring plenary talks, poster sessions and social events. Join us in Tuebingen to learn about the latest advances in systems neuroscience. Confirmed speakers: Francesco Battaglia, Nijmegen Gustavo Deco, Barcelona Biyu He, New York Christoph Kayser, Glasgow Daniel Margulies, Leipzig Uta Noppeney, Birmingham Marios Philiastides, Glasgow Hansjörg Scherberger, Göttingen Woodrow Shew, Fayetteville Preejas Tewarie, Nottingham For more information and registration, please visit: http://meg.medizin.uni-tuebingen.de/2017/ Please forward this information to any of your colleagues and collaborators that may be interested in the symposium. Nima Noury AG Large-Scale Neuronal Interactions Centre for Integrative Neuroscience (CIN) University of Tübingen Otfried Müller-Straße 25 72076 Tübingen Germany From anne.urai at gmail.com Tue Jul 18 08:54:17 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 17 Jul 2017 23:54:17 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: Hi Tvetan, Thanks for your help. Dear Anne,>* The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? *this information was provided by the principle investigator of the paper. You might ask the corresponding author for further details on this. Best tzvetan I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI. Do you know by any chance which author provided the mat file, so I can work from the code they used? Best, — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai From: Anne Urai Reply: Anne Urai Date: 10 July 2017 at 10:38:59 To: fieldtrip at science.ru.nl Subject: vtpm atlas contains no right IPS5 Dear Fieldtrippers, I'm using the VTPM atlas to define masks for all the visual regions described in the paper (Wang et al. 2014, https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bhu277). However, there seem to be no entries corresponding to the left IPS5. *% load atlas* *atl = ft_read_atlas('~/Documents/fieldtrip/vtpm/vtpm.mat');* *atl = ft_convert_units(atl, 'cm');* *% add mni coordinates* *[ax, ay, az] = voxelcoords(atl.dim, atl.transform);* *atl.pos = [ax(:) ay(:) az(:)];* *% make a binary mask for this ROI* *roi_idx = find(strcmp(lower(atl.tissuelabel), 'IPS5'));* *roi_mask = ismember(atl.tissue, roi_idx);* *% mask the voxels on the right side of the brain* *rightidx = find(atl.pos(:, 1) > 0); * *roi_mask(rightidx) = 0;* Now, sum(roi_mask(:)) = 0. This procedure of separating out the left and right regions works fine for all other regions in the atlas, as well as the right IPS5. The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? Thanks! — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai -------------- next part -------------- An HTML attachment was scrubbed... URL: From tzvetan.popov at uni-konstanz.de Tue Jul 18 09:28:28 2017 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Tue, 18 Jul 2017 09:28:28 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Dear Anne, > I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI > Do you know by any chance which author provided the mat file I have created the mat file working from the nifti files. I don’t have the code anymore but it wasn’t too difficult. Yet, this code wouldn’t help since the ROI isn’t in the nifti files to begin with. I had exchange RE: missing ROI with Michael Arcaro back then. Here is what he wrote: "As you said, ROI 23 does not appear to be in the volume lh map. It’s there in the surface max prob map for the lh. I know Liang generated a separate probability map using nonlinear volumetric alignment, which was a little bit worse in quality than the surface map. It’s possible you’re using that map. I thought we sent you the volume projection of the surface max probability map though. It’s possible that the small area of ROI3 in the surface max probability map did not survive the projection back into volume space (since there is interpolation in the projection). I’ll double check with Liang and Ryan and see if they remember any issues with ROI23. It might be better to use the individual probability map for ROI 23 and use a more liberal threshold." So it seems that Liang could indeed provide some more info on whether and how to use a more liberal threshold to get the ROI back into the volumetric representation? Best tzvetan -------------- next part -------------- An HTML attachment was scrubbed... URL: From anne.urai at gmail.com Tue Jul 18 10:12:26 2017 From: anne.urai at gmail.com (Anne Urai) Date: Tue, 18 Jul 2017 01:12:26 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> References: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Message-ID: Dear Liang, cc Tzvetan, FieldTrip See the conversation below - Tzvetan has indicated that the volumetric representation is already missing IPS5. It would be great to try and redo the projection into volume space and play with the threshold to make sure that all regions are at least assigned to one voxel. Best, — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai From: Tzvetan Popov Reply: FieldTrip discussion list Date: 18 July 2017 at 09:28:28 To: FieldTrip discussion list Subject: Re: [FieldTrip] vtpm atlas contains no right IPS5 Dear Anne, I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI Do you know by any chance which author provided the mat file I have created the mat file working from the nifti files. I don’t have the code anymore but it wasn’t too difficult. Yet, this code wouldn’t help since the ROI isn’t in the nifti files to begin with. I had exchange RE: missing ROI with Michael Arcaro back then. Here is what he wrote: "As you said, ROI 23 does not appear to be in the volume lh map. It’s there in the surface max prob map for the lh. I know Liang generated a separate probability map using nonlinear volumetric alignment, which was a little bit worse in quality than the surface map. It’s possible you’re using that map. I thought we sent you the volume projection of the surface max probability map though. It’s possible that the small area of ROI3 in the surface max probability map did not survive the projection back into volume space (since there is interpolation in the projection). I’ll double check with Liang and Ryan and see if they remember any issues with ROI23. It might be better to use the individual probability map for ROI 23 and use a more liberal threshold." So it seems that Liang could indeed provide some more info on whether and how to use a more liberal threshold to get the ROI back into the volumetric representation? Best tzvetan _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From zk578 at york.ac.uk Thu Jul 20 15:56:48 2017 From: zk578 at york.ac.uk (=?iso-8859-1?Q?Zdenko_Koh=FAt?=) Date: Thu, 20 Jul 2017 13:56:48 +0000 Subject: [FieldTrip] ERP classification Message-ID: Dear Fieldtrippers, I would like to classify ERP data in one condition based on an averaged group ERP signal from a different condition. To describe it more clearly, imagine that I have a condition1 in which I observe a significant P300, and a condition2 which shows no significant effect, although some of the participants clearly show the P300 in this condition as well. I would like to use the signal from the condition1 to classify the participants in the condition2 into P300 and no-P300 group. Is there some way to go about this issue ? Thank you ! :) Kind regards, Zdenko -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nina.Merkel at kgu.de Thu Jul 20 17:35:58 2017 From: Nina.Merkel at kgu.de (Merkel, Nina) Date: Thu, 20 Jul 2017 15:35:58 +0000 Subject: [FieldTrip] sig file Message-ID: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina -------------- next part -------------- An HTML attachment was scrubbed... URL: From N.vanKlink-2 at umcutrecht.nl Fri Jul 21 09:13:56 2017 From: N.vanKlink-2 at umcutrecht.nl (Klink-3, N.E.C. van) Date: Fri, 21 Jul 2017 07:13:56 +0000 Subject: [FieldTrip] sig file In-Reply-To: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> References: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Message-ID: Hi Nina, These .sig files are Stellate EEG files, but Stellate does no longer exist anymore, so software is no longer supported. This makes it difficult to work with these files sometimes. The easiest way would be to convert your .sig to EDF with Stellate Reviewer, if you have access to that software. You would select the whole file with the selector tool, and then File-> Export As... There also is a matlab toolbox for reading .sig into matlab, but it only works with 32-bits matlab on a Windows system. Hope this helps, Nicole Van: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Namens Merkel, Nina Verzonden: 20 jul 17 17:36 Aan: 'fieldtrip at science.ru.nl' Onderwerp: [FieldTrip] sig file Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina ------------------------------------------------------------------------------ De informatie opgenomen in dit bericht kan vertrouwelijk zijn en is uitsluitend bestemd voor de geadresseerde. Indien u dit bericht onterecht ontvangt, wordt u verzocht de inhoud niet te gebruiken en de afzender direct te informeren door het bericht te retourneren. Het Universitair Medisch Centrum Utrecht is een publiekrechtelijke rechtspersoon in de zin van de W.H.W. (Wet Hoger Onderwijs en Wetenschappelijk Onderzoek) en staat geregistreerd bij de Kamer van Koophandel voor Midden-Nederland onder nr. 30244197. Denk s.v.p aan het milieu voor u deze e-mail afdrukt. ------------------------------------------------------------------------------ This message may contain confidential information and is intended exclusively for the addressee. If you receive this message unintentionally, please do not use the contents but notify the sender immediately by return e-mail. University Medical Center Utrecht is a legal person by public law and is registered at the Chamber of Commerce for Midden-Nederland under no. 30244197. Please consider the environment before printing this e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mailtome.2113 at gmail.com Mon Jul 24 07:04:54 2017 From: mailtome.2113 at gmail.com (Arti Abhishek) Date: Mon, 24 Jul 2017 15:04:54 +1000 Subject: [FieldTrip] Appending datasets with different channel order Message-ID: Dear list, I am working with some infant ERP data and I perform trial by trial channel interpolation. The trials are then concatenated using ft_appenddata. Since the number of interpolated channels are different across trials, the channel order is different across trials. I was wondering what will happen to the channel order in the case of appending. Since there are channel labels for each trial, does the ft_appenddata function takes this into account and match data to the channel label? Thanks Arti -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nina.Merkel at kgu.de Mon Jul 24 10:07:43 2017 From: Nina.Merkel at kgu.de (Merkel, Nina) Date: Mon, 24 Jul 2017 08:07:43 +0000 Subject: [FieldTrip] sig file In-Reply-To: References: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Message-ID: <5A40C6B713E9B243B4EBD708AFA674A7590D67@EXMEPDAG4.intra.kgu.de> Thank you Nicole! This was very helpful information! Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Klink-3, N.E.C. van Gesendet: Freitag, 21. Juli 2017 09:14 An: FieldTrip discussion list Betreff: Re: [FieldTrip] sig file Hi Nina, These .sig files are Stellate EEG files, but Stellate does no longer exist anymore, so software is no longer supported. This makes it difficult to work with these files sometimes. The easiest way would be to convert your .sig to EDF with Stellate Reviewer, if you have access to that software. You would select the whole file with the selector tool, and then File-> Export As... There also is a matlab toolbox for reading .sig into matlab, but it only works with 32-bits matlab on a Windows system. Hope this helps, Nicole Van: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Namens Merkel, Nina Verzonden: 20 jul 17 17:36 Aan: 'fieldtrip at science.ru.nl' Onderwerp: [FieldTrip] sig file Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina ________________________________ De informatie opgenomen in dit bericht kan vertrouwelijk zijn en is uitsluitend bestemd voor de geadresseerde. Indien u dit bericht onterecht ontvangt, wordt u verzocht de inhoud niet te gebruiken en de afzender direct te informeren door het bericht te retourneren. Het Universitair Medisch Centrum Utrecht is een publiekrechtelijke rechtspersoon in de zin van de W.H.W. (Wet Hoger Onderwijs en Wetenschappelijk Onderzoek) en staat geregistreerd bij de Kamer van Koophandel voor Midden-Nederland onder nr. 30244197. Denk s.v.p aan het milieu voor u deze e-mail afdrukt. ________________________________ This message may contain confidential information and is intended exclusively for the addressee. If you receive this message unintentionally, please do not use the contents but notify the sender immediately by return e-mail. University Medical Center Utrecht is a legal person by public law and is registered at the Chamber of Commerce for Midden-Nederland under no. 30244197. Please consider the environment before printing this e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From anne.urai at gmail.com Mon Jul 24 12:59:08 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 24 Jul 2017 12:59:08 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Message-ID: Hi Tzvetan, Fieldtrippers, see below the response I got from Liang Wang. *I double-check the original files of the maximum probabilistic atlas in the volume-based space. As you said, it did not include left IPS5 areas. In our paper, we had pointed out that there was a difference between volume- and surface-based atlas, because the registration used between two space was totally different. We think the surface-based atlas may be more accurate, compare to the volume-based atlas. If you need to get left IPS5, I suggest to use the probability map for that region that you also can download from the web. This map provides you a probability value for each voxel being to that region. * *Best,* *Liang* — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai On 18 July 2017 at 10:12, Anne Urai wrote: > Dear Liang, > cc Tzvetan, FieldTrip > > See the conversation below - Tzvetan has indicated that the volumetric > representation is already missing IPS5. It would be great to try and redo > the projection into volume space and play with the threshold to make sure > that all regions are at least assigned to one voxel. > > Best, > > — > Anne E. Urai, MSc > PhD student | Institut für Neurophysiologie und Pathophysiologie > Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | > Hamburg, Germany > www.anneurai.net / @AnneEUrai > > From: Tzvetan Popov > > Reply: FieldTrip discussion list > > Date: 18 July 2017 at 09:28:28 > To: FieldTrip discussion list > > Subject: Re: [FieldTrip] vtpm atlas contains no right IPS5 > > Dear Anne, > > I've been in touch with Dr. Liang Wang (first author on the paper), but he > could only point me to the original NIfTI files on the website which have > been converted in AFNI > > Do you know by any chance which author provided the mat file > > I have created the mat file working from the nifti files. I don’t have the > code anymore but it wasn’t too difficult. Yet, this code wouldn’t help > since the ROI isn’t in the nifti files to begin with. I had exchange RE: > missing ROI with Michael Arcaro back then. Here is what he wrote: > > "As you said, ROI 23 does not appear to be in the volume lh map. > It’s there in the surface max prob map for the lh. I know Liang generated > a separate probability map using nonlinear volumetric alignment, which was > a little bit worse in quality than the surface map. It’s possible you’re > using that map. I thought we sent you the volume projection of the surface > max probability map though. It’s possible that the small area of ROI3 in > the surface max probability map did not survive the projection back into > volume space (since there is interpolation in the projection). I’ll double > check with Liang and Ryan and see if they remember any issues with ROI23. > It might be better to use the individual probability map for ROI 23 and use > a more liberal threshold." > > So it seems that Liang could indeed provide some more info on whether and > how to use a more liberal threshold to get the ROI back into the volumetric > representation? > > Best > tzvetan > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Miguel.Granjaespiritosanto at nottingham.ac.uk Tue Jul 25 10:20:32 2017 From: Miguel.Granjaespiritosanto at nottingham.ac.uk (Miguel Granja Espirito Santo) Date: Tue, 25 Jul 2017 08:20:32 +0000 Subject: [FieldTrip] ft_topoplotER using highlight symbol size as proxy for length of significance of cluster. Message-ID: Hi all, I am trying to use the ft_topoplotER to show significant difference between conditions without having to do a large subplot of different times points. To do this I thought of adjusting the highlighting symbol size proportionally to the length of the duration of significance. This seem simple at first because I just had to plot the highlight for every channel one at time in a for loop and adjust the size accordingly and then use hold on. However, ft_topoplotER writes a new image through every iteration of the loop and therefore overwriting the previous highlight. Is there any way to get around this? Is there a way to enable hold on for ft_topoplotER? Best, Miguel PhD Student School of Psychology University of Nottingham This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation. -------------- next part -------------- An HTML attachment was scrubbed... URL: From smoratti at psi.ucm.es Wed Jul 26 17:11:32 2017 From: smoratti at psi.ucm.es (smoratti at psi.ucm.es) Date: Wed, 26 Jul 2017 17:11:32 +0200 Subject: [FieldTrip] 2-year post-doctoral position in human intracranial recordings in patients with schizophrenia Message-ID: <7AE53ED5-A06C-455B-993F-47DE9688A560@psi.ucm.es> On behalf of Bryan Strange a close collaborator of mine I send you this job offer: The Laboratory for Clinical Neuroscience in Madrid (www.thestrangelab.org ), in collaboration with the Neurosurgery and Psychiatry departments of the Clinico San Carlos, is pioneering the use of deep-brain stimulation in the management of medication-resistant schizophrenia. As part of this treatment, we perform electrophysiological recordings in patients to study the firing pattern of ventral midbrain (putatively dopaminergic) neurons. Secondly, we test patients in behavioural tasks such as working memory, in order to determine the cognitive effects of DBS treatment. The successful candidate will be involved in acquiring and analysing neurophysiological recordings from these patients: intra-operative single-unit recordings and post-operative intracranial local field potentials and scalp EEG. Funding is through the Behavior and Brain Research Foundation (https://www.bbrfoundation.org/blog/meet-our-2017-narsad-independent-investigator-grantees ) A PhD in neuroscience (or related discipline) is required. The ideal candidate will be highly competent in the analysis of electrophysiological recordings, particularly single-unit data. Knowledge of ventral tegmental single unit activity in animal models of schizophrenia is desirable. The start date will be in autumn/winter 2017. Fluent English is mandatory, Spanish is not required. Application: Send CV, motivation letter, and contact details of two academic referees to Prof. Bryan Strange bryan.strange at upm.es Deadline: 1 September 2017 -- Un cordial saludo, Stephan Moratti, PhD Profesor de Psicología Básica I Universidad Complutense de Madrid 91 394 3141 smoratti at ucm.es La información contenida en este correo es CONFIDENCIAL, de uso exclusivo del destinatario/a arriba mencionado. Si ha recibido este mensaje por error, notifíquelo inmediatamente por esta misma vía y proceda a su eliminación, ya que ud. tiene totalmente prohibida cualquier utilización del mismo, en virtud de la legislación vigente. Los datos personales recogidos serán incorporados y tratados en el fichero 'Correoweb', bajo la titularidad del Vicerrectorado de Tecnologías de la Información, y en él el interesado/a podrá ejercer los derechos de acceso, rectificación, cancelación y oposición ante el mismo (artículo 5 de la Ley Orgánica 15/1999, de 13 de diciembre, de Protección de Datos de Carácter Personal). Antes de imprimir este correo piense si es necesario: el medio ambiente es cosa de todos. This message is private and confidential and it is intended exclusively for the addressee. If you receive this message by mistake, you should not disseminate, distribute or copy this e-mail. Please inform the sender and delete the message and attachments from your system, as it is completely forbidden for you to use this information, according to the current legislation. No confidentiality nor any privilege regarding the information is waived or lost by any mistransmission or malfunction. The personal data herein will be collected in the file “Correoweb”, under the ownership of the Vice-Rectorate for Information Technologies, in which those interested may exercise their right to access, rectify, cancel or protest the contents (article 5 of Organic Law 15/1999 dated 13 December, on the Protection of Personal data). Before printing this mail please consider whether it is really necessary: the environment is a concern for us all. -------------- next part -------------- An HTML attachment was scrubbed... URL: From roycox.roycox at gmail.com Thu Jul 27 18:32:49 2017 From: roycox.roycox at gmail.com (Roy Cox) Date: Thu, 27 Jul 2017 12:32:49 -0400 Subject: [FieldTrip] postdoctoral opportunity Message-ID: Please see below for a postdoctoral opportunity in the lab of Dara Manoach at MGH/Harvard Medical School. Best, Roy ------------------------------------------------------------------------------------------------------------------------------- Postdoctoral Fellowship at the Martinos Center for Biomedical Imaging and the Psychiatric Neuroimaging Division of the Psychiatry Department at Massachusetts General Hospital, Charlestown, MA and Harvard Medical School *Position Description*: Clinical/Cognitive Neuroscience Research *Project*: Multimodal neuroimaging studies of sleep and memory *PI*: Dara S. Manoach, Ph.D. The position will involve investigating the role of sleep in memory consolidation, how these processes go awry in schizophrenia and autism, and the effects of pharmacological and other interventions. Our work has linked cognitive deficits to specific heritable mechanisms (sleep spindles and other sleep oscillations) and we are seeking effective interventions. In collaboration with Dr. Robert Stickgold’s lab at Beth Israel Deaconess Medical Center, we are extending and expanding this basic and clinical research program using state-of-the art tools including high density EEG, MEG, DTI, functional connectivity MRI, fMRI, and behavioral studies. We are seeking someone to participate in these foundation and NIMH-funded investigations who is familiar with cognitive neuroscience, neuroimaging methodology including MEG and/or EEG and data analysis, and is interested in developing research questions and optimizing analysis streams tailored to the study aims and populations. New approaches and ideas are encouraged, as are independent projects that dovetail with current studies. The position requires working closely with the PI, as well as with Dr. Stickgold, other Martinos Center investigators, particularly Dr. Matti Hamalainen, Director of the MEG Core Lab, and labmates to design studies, acquire data, and develop, explore, improve and apply data analytic techniques. Training in clinical research and in the acquisition, analysis, and interpretation of neuroimaging data will be provided. Requirements: PhD (or MD) in neuroscience, psychology, engineering or a related discipline and a strong research background are required. Ideal candidates would have extensive experience in data analysis, a background in computational neuroscience and/or signal processing, be proficient in Matlab/Python and be interested in methods development. The following are also beneficial: experience with MEG/EEG data analysis/methodology, background in cognitive neuroscience, experimental psychology and sleep; interest/experience with clinical populations; and experience in task design and analysis for cognitive experiments. Position available immediately. Interested applicants should email: (a) CV, (b) statement of post-doctoral and career goals, (c) writing sample (e.g., a published manuscript), and (d) letters and/or contact information for three references to Dara Manoach . Stipend levels are in line with experience and NIH. A two-year commitment is required. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Hisako.Fujiwara at cchmc.org Thu Jul 27 19:00:15 2017 From: Hisako.Fujiwara at cchmc.org (Fujiwara, Hisako) Date: Thu, 27 Jul 2017 17:00:15 +0000 Subject: [FieldTrip] how to segment continuous EEG data without triggers Message-ID: <64721b2dbaba463b9ea729893d08708d@cchmc.org> Dear experts, I have continuous EEG data in EDF format that does not include trigger channel. These EEG data was recorded as EEG-fMRI during a task (30-sec baseline and 30-sec active trial alternated 4 or 5 times depending on participants). I would like to segment out the active states 4 x 30-sec segments for each participants. Now, I have the separate marker files that have 2 sec TR trigger as a text (EV2) file. I can at least tell start and finish for each trial from the marker file. I have tired to use ft_definetrial and ft_redefinetri with function of cfg.toilim = [tmin tmax] but I am getting error message either: 1. undefined function or variable 'data' 2. Error using ft_notification (line 314) This function requires raw+comp or raw data as input. Error in ft_error (line 39) ft_notification(varargin{:}); Error in ft_checkdata (line 495) ft_error('This function requires %s data as input.', str); Error in ft_redefinetrial (line 117) data = ft_checkdata(data, 'datatype', {'raw+comp', 'raw'}, 'feedback', cfg.feedback); I tried to refer the http://www.fieldtriptoolbox.org/reference/ft_definetrial and also searched through the mailing archives but I have not found exact solution so fat. but I ma not really succeeding this. I am sure I am missing a lot of functions for that. Could you please kindly suggest any detailed explanation and solution for this? Thank you very much for your kind help in advance, Sincerely, Hisako -------------- next part -------------- An HTML attachment was scrubbed... URL: From a132467647 at gmail.com Sat Jul 29 10:47:22 2017 From: a132467647 at gmail.com (Jiun Wei Chen) Date: Sat, 29 Jul 2017 08:47:22 +0000 Subject: [FieldTrip] Having a error in installing Fieldtrip after installing SPM and brainstorm Message-ID: Dear Fieldtrip users: My name is Jiun-Wei Chen and I am working in Brain mapping lab in Taiwan on the brain science. I am analyzing data of MEG. I found the problem I can't properly installing Fieldtrip in my MATLAB. My versions of MATLAB are R2015b and R2016b. before installing Fieldtrip, I have installed SPM12 and brainstorm in my MATLAB. Then, I follow this website below to set path http://www.fieldtriptoolbox.org/faq/should_i_add_fieldtrip_with_all_subdirectories_to_my_matlab_path this is my instance below: >> addpath C:\Users\wei\Documents\MATLAB\Fieldtrip >> ft_defaults after I key in these commands, I get the error message below: Undefined function 'ft_platform_supports' for input arguments of type 'char'. Error in ft_defaults>checkMultipleToolbox (line 291) if ~ft_platform_supports('which-all') Error in ft_defaults (line 114) checkMultipleToolbox('FieldTrip', 'ft_defaults.m'); I also tried to install Fieldtrip only in my MATLAB and preprocess my data. (my data format is ".fif") but I got an error message again. Subscripted assignment between dissimilar structures. Error in mergeconfig>mergeconfig_helper (line 39) input(j) = mergeconfig_helper(input(j), default(j)); Error in mergeconfig>mergeconfig_helper (line 53) input.(fn) = mergeconfig_helper(input.(fn), default.(fn)); Error in mergeconfig>mergeconfig_helper (line 53) input.(fn) = mergeconfig_helper(input.(fn), default.(fn)); Error in mergeconfig (line 12) input = mergeconfig_helper(input, default); Error in ft_preamble_init (line 55) cfg = mergeconfig(cfg, rmfield(ft_default, 'preamble')); Error in ft_preamble (line 85) evalin('caller', full_cmd); Error in ft_preprocessing (line 182) ft_preamble init Error in ft_qualitycheck (line 212) data = ft_preprocessing(cfgpreproc); clear cfgpreproc; I upload my data in my google drive as it exceeds the critical file size of 1MB. Here is the link: https://drive.google.com/open?id=0B8Xo-QjG1y2TZjBnWjdpNjZXNlk the code I use are as follows: %% Quality check cfg = [];%configuration structure cfg.dataset = 'run1_sss.fif';%string with the filename ft_qualitycheck(cfg) I could preprocess this data by Fieldtrip code that exists in the external folder of SPM and brainstorm. but I got the warning message that altered me there is the same code in these folders. can someone tell me how to install Fieldtrip when brainstorm and SPM exist in the same time and how to avoid the warning message I mentioned above. Any help would be appreciated. Best, Jiun-Wei -------------- next part -------------- An HTML attachment was scrubbed... URL: From son.ta.dinh at tum.de Mon Jul 31 09:39:51 2017 From: son.ta.dinh at tum.de (Ta Dinh, Son) Date: Mon, 31 Jul 2017 07:39:51 +0000 Subject: [FieldTrip] Functional connectivity analysis with powcorr_ortho In-Reply-To: <0d81972648824a678682346413ec9456@tum.de> References: <0d81972648824a678682346413ec9456@tum.de> Message-ID: Hi Brian, In general I woulrd recommend that you comment or reply to posts in the FieldTrip list on the list instead of sending mails directly to people so that issues that are solved are visible to everybody. As to the issue at hand, I haven't heard from anybody and regretfully forgot to ask Mr. Schoffelen at the last conference I met him. My solution to this was to implement the algorithm by myself according to the description given in the paper by Hipp et al. I could offer to send you the code, it should be easy to integrate with a reasonable amount of Matlab skills. Naturally I will not be able to offer any guarantees that the code is correct, but the results look reasonable enough to me. Go to http://dropcanvas.com/1xfe7/1 for a plot of the grand average seed-based connectivity from the left somatosensory cortex (MNI = [- 40, - 30, 50]) to all other voxels within the Beta band for a group of 22 healthy subjects. The paradigm is 5 minutes eyes-closed resting-state. Best, Son Von: Brian Scally [RPG] [mailto:psbs at leeds.ac.uk] Gesendet: Donnerstag, 27. Juli 2017 15:54 An: Ta Dinh, Son > Betreff: Fieldtrip powcorr_ortho issue Dear Son Ta Dinh, Hope you are well. I came across a post you made on the Fieldtrip mailing list about the powcorr_ortho function for ft_connectivity analysis. I am essentially getting the same results - random connectivity patterns. I wondered if you had heard from anyone about this issue or managed to resolve it? All the best, Brian Scally PhD Student, School of Psychology, University of Leeds b.scally at leeds.ac.uk Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Ta Dinh, Son Gesendet: Donnerstag, 13. April 2017 14:58 An: fieldtrip at science.ru.nl Betreff: [FieldTrip] Functional connectivity analysis with powcorr_ortho Dear FieldTrip list, I am trying to do a functional connectivity analysis using the power envelope correlation introduced by Hipp et al. (Nat Neuroscience 2012) as implemented in the ft_connectivity_powcorr_ortho function. My data consists of 5 minutes of eyes-closed resting-state data and my schematic pipeline is as follows: 1. I use LCMV beamforming to source reconstruct my bandpassed and preprocessed data 2. Using the resulting spatial filter I get a projected time series for every voxel (virtual channel) 3. I do a frequency analysis on these time series 4. The results of this frequency analysis (the Fourier coefficients) are used for the connectivity analysis using powcorr_ortho To check the results of this analysis, I plotted the results of a seed-based connectivity analysis with a voxel in the left visual cortex (-20, -80, 20) as seed. In the alpha band, I expect to see a strong local connectivity pattern in the occipital region extending partially into the contralateral hemisphere, similar to what Siems et al. NeuroImage 2016 find. However, I get a basically random connectivity pattern. When using this pipeline with the debiased weighted phase lag index, I get exactly what I am expecting. I looked into the source code of the ft_connectivity_powcorr_ortho function and saw a few disconcerting comments (Fix-Me's and the like) and now I am wondering whether my pipeline is simply not suited to the connectivity analysis with powcorr_ortho as implemented in FieldTrip or if the function is simply not fully implemented yet. Has anyone used it successfully before? I use the following FieldTrip (pseudo-) code: %% LCMV source reconstruction cfg = []; cfg.method = 'lcmv'; cfg.keeptrials = 'yes'; cfg.elec = elec; cfg.grid = lf; % regular grid of 1 cm resolution cfg.headmodel = vol % standard_bem.mat cfg.lcmv.keepfilter = 'yes'; cfg.lcmv.lambda = '5%'; cfg.lcmv.projectnoise = 'yes'; source = ft_sourceanalysis(cfg, tlock_data); %% pseudo-code for the computation of the virtual channel time series virtChan_data = tlock_data; virtChan_data.label = [source.pos(:, 1), source.pos(:,2), source.pos(:,3)]; virtChan_data.trial = source.avg.filter * tlock_data.trial; %% frequency analysis of the virtual channels cfg = []; cfg.method = 'mtmfft'; cfg.output = 'fourier'; cfg.keeptrials = 'yes'; cfg.foi = 10; % alpha band cfg.taper = 'hanning' % I originally used 3 tapers but source code in ft_connectivity_powcorr_ortho implies that multitaper is not compatible virtFreq = ft_freqanalysis(cfg, virtChan_data); %% connectivity analysis cfg = []; cfg.method = 'powcorr_ortho'; conn = ft_connectivityanalysis(cfg,virtFreq); Any suggestions and/or comments would be immensely helpful! Thanks in advance. Best, Son Son Ta Dinh, M.Sc. PhD student in Human Pain Research Klinikum rechts der Isar Technische Universität München Munich, Germany Phone: +49 89 4140 7664 http://www.painlabmunich.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Fri Jul 21 05:08:45 2017 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 21 Jul 2017 03:08:45 -0000 Subject: [FieldTrip] 2nd MEG North America Meeting Message-ID: We are pleased to announce the 2nd MEG-North America meeting, to be held in Bethesda, Maryland November 8th and 9th, directly before the Society for Neuroscience Meeting. November 8th will consist of small workgroup meetings to discuss collaborative projects involving reproducibility, data sharing architecture, and consortium building. We are seeking community involvement for these committees! Please get involved, go to our website to find out how. Working groups will address reliability/reproducibility, data sharing, industry partnership, and facilitating best practices. The main meeting will be held on November 9th, with a scientific program, keynote speakers, and a poster session. Call for Abstracts opens today, and will Close September 8th. Speaking vs. poster assignments will be sent within two weeks. Please visit our website at https://megworkshop.nih.gov/MEGWorkshop/ Or register at: https://www.eventbrite.com/e/meg-north-america-2017-tickets-36315511673 We hope to see you there! Conference Chairs: Richard Coppola Allison Nugent Steering Committee: Sylvain Baillet Dimitrios Pantazis Timothy Roberts Julia Stephen -------------- next part -------------- An HTML attachment was scrubbed... URL: From rhancock at email.arizona.edu Thu Jul 27 05:17:39 2017 From: rhancock at email.arizona.edu (Roeland Hancock) Date: Wed, 26 Jul 2017 23:17:39 -0400 Subject: [FieldTrip] Job: Technical Director of the Brain Imaging Research Center Message-ID: *University of Connecticut* *Technical Director of the Brain Imaging Research Center * *Research Assistant III/Research Associate I* The University of Connecticut invites applications for a full-time position of Technical Director of UConn’s Brain Imaging Research Center (BIRC). The Technical Director is responsible for the development and maintenance of the BIRC’s technology infrastructure, and will contribute to day-to-day operations. Rank and salary will be commensurate with degree and experience. The BIRC’s focus is on cognitive neuroscience research using functional MRI. *To Apply: *Interested applicants should view the full ad and application instructions at www.jobs.uconn.edu. Please send inquiries to Inge-Marie Eigsti, Ph.D., Chair of Search #2017355, Department of Psychological Sciences, U-1020, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269-1020; BIRC at UConn.edu. Applications are preferred by August 15, 2017, but the position will remain open until filled. The University of Connecticut is an EEO/AA employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: From rhancock at email.arizona.edu Thu Jul 27 05:17:39 2017 From: rhancock at email.arizona.edu (Roeland Hancock) Date: Thu, 27 Jul 2017 03:17:39 +0000 Subject: [FieldTrip] Job: Technical Director of the Brain Imaging Research Center Message-ID: <52c10f2f79ff40c1be85c9a9eaf2fe9c@EXPRD98.hosting.ru.nl> University of Connecticut Technical Director of the Brain Imaging Research Center Research Assistant III/Research Associate I The University of Connecticut invites applications for a full-time position of Technical Director of UConn’s Brain Imaging Research Center (BIRC). The Technical Director is responsible for the development and maintenance of the BIRC’s technology infrastructure, and will contribute to day-to-day operations. Rank and salary will be commensurate with degree and experience. The BIRC’s focus is on cognitive neuroscience research using functional MRI. To Apply: Interested applicants should view the full ad and application instructions at www.jobs.uconn.edu. Please send inquiries to Inge-Marie Eigsti, Ph.D., Chair of Search #2017355, Department of Psychological Sciences, U-1020, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269-1020; BIRC at UConn.edu. Applications are preferred by August 15, 2017, but the position will remain open until filled. The University of Connecticut is an EEO/AA employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jumana.ahmad at kcl.ac.uk Mon Jul 3 15:15:34 2017 From: jumana.ahmad at kcl.ac.uk (Ahmad, Jumana) Date: Mon, 3 Jul 2017 13:15:34 +0000 Subject: [FieldTrip] inter trial coherence statistics Message-ID: Dear all, I have been struggling for awhile with inter trial coherence statistics. I found the ITC stats fun function online with cfg.statistic = 'diff_itc' I cannot get it to work. I have 300 participants per group, and a between subject design with only one outcome measure. I therefore wanted something akin to permutation between groups. However, when I use the ITC stats fun function, it complains if the design matrix is not as long as all the files across all participants so it becomes more like a single subject comparison. Has anybody had any luck using this function between groups, or with multiple people? If so, would it be OK to share a sample of your code or key parameters? Thank you very much, Jumana ------------------------------------------ Jumana Ahmad Post-Doctoral Research Worker in Cognitive Neuroscience EU-AIMS Longitudinal European Autism Project (LEAP) & SynaG Study Room M1.26.Department of Forensic and Neurodevelopmental Sciences (PO 23) | Institute of Psychiatry, Psychology & Neuroscience | King’s College London | 16 De Crespigny Park | London SE5 8AF Phone: 0207 848 5359| Email: jumana.ahmad at kcl.ac.uk | Website: www.eu-aims.eu | Facebook: www.facebook.com/euaims -------------- next part -------------- An HTML attachment was scrubbed... URL: From martabortoletto at yahoo.it Mon Jul 3 16:17:03 2017 From: martabortoletto at yahoo.it (Marta Bortoletto) Date: Mon, 3 Jul 2017 14:17:03 +0000 (UTC) Subject: [FieldTrip] Workshop - Ten years of Mind/Brain Sciences at the University of Trento - CIMeC, Italy References: <418890791.6270044.1499091423986.ref@mail.yahoo.com> Message-ID: <418890791.6270044.1499091423986@mail.yahoo.com> Tocelebrate its 10th anniversary, the Center for Mind/Brain Sciences (CIMeC) organizes a workshop on thefuture of cognitive neuroscience.WHERE and WHEN: The workshop will be held in Rovereto, Italy on October 19-21, 2017. WHAT: The themeof the event will be centered around the question: “Where do cognitiveneuroscientists see Mind/Brain Sciences in ten years?”Deadline for poster submission: September 1st. Workshop website: http://events.unitn.it/en/cimec-ten-yearsThe workshop has a limited number of availableplaces. Potential attendees are encouraged to register online as soon aspossible.Invited speakers:·       Cristina Becchio - Universityof Torino, Italy·       Nadia Bolognini - Universityof Milano Bicocca, Italy·       Ruth Byrne -Trinity College Dublin, Ireland·       Marco Catani - KingCollege London, UK·       Gustavo Deco - PompeuFabra Univesity, Spain·       Scott Fairhall -University of Trento, Italy·       Randy Gallistel -Rutgers University, USA·       Melvyn Goodale -Western University, Canada·       Patrick Haggard -University College London, UK·       Takao Hensch -Harvard University, USA·       Zoe Kourtzi -Cambridge University, UK·       Nikos Logothetis -Max Planck Institute, Germany·       Emiliano Macaluso -University of Lyon, France·       Tamar Makin -University College London, UK·       Alex Martin -National Institute of Mental Health, USA·       Louise McNally -Pompeu Fabra University, Spain·       Satu Palva -University of Helsinki, Finland·       Stefano Panzeri - ItalianInstitute of Technology, Italy·       David Poeppel -New York University, USA·       Tim Shallice -University College London, UK·       Antonino Vallesi -University of Padova, ItalyWe look forward to seeing you there.The Organizing CommitteeCarlo Miniussi, Yuri Bozzi, Veronica Mazza, FrancescoPavani, Luca Turella, Massimiliano Zampini.  Marta Bortoletto, PhD Cognitive Neuroscience Section, IRCCS Centro San Giovanni di Dio Fatebenefratelli Via Pilastroni 4, 25125 Brescia, Italy Phone number: (+39) 0303501594 E-mail: marta.bortoletto at cognitiveneuroscience.it web: http://www.cognitiveneuroscience.it/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Tue Jul 4 15:21:56 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Tue, 4 Jul 2017 13:21:56 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? References: <1460287005.7559270.1499174516032.ref@mail.yahoo.com> Message-ID: <1460287005.7559270.1499174516032@mail.yahoo.com> Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence). With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal). I hope this helps. Best,Maité El Jueves 29 de junio de 2017 12:24, Maria Hakonen escribió: Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.a.sprenger at rug.nl Tue Jul 4 16:56:51 2017 From: s.a.sprenger at rug.nl (Sprenger, S.A.) Date: Tue, 4 Jul 2017 16:56:51 +0200 Subject: [FieldTrip] How to adapt a layout file Message-ID: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/ template/layout/easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 18:03:47 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 16:03:47 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials Message-ID: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Hi everyone, I am now trying to use the DICS method for sourceanalysis, with 'powandcsd' output from ft_freqanalysis as its input and using a precomputed filter and leadfield. However, I would like to keep my separate trial estimates in the final source analysis, and while the documentation suggests I should be able to get that with cfg.keeptrials, but this doesn't have the expected effect. I previously made workaround using PCC on fourier data instead (see below), I think to deal with this issue. I was wondering if this is still the recommended option, i.e. workaround? Alternatively, and perhaps preferably, would someone have a suggestion for a solution consistent with the DICS implementation? Thanks for your time, Stephen % source analysis cfg.method = 'pcc'; ... cfg.keeptrials = 'yes'; cfg.pcc.keepmom = 'yes'; cfg.pcc.fixedori = 'no'; source_control = ft_sourceanalysis(cfg, FFT); and then: % project moment and tapers cfg = []; cfg.projectmom = 'no'; cfg.keeptrials = 'yes'; cfg.powmethod = 'lambda1'; source = ft_sourcedescriptives(cfg,source); -------------- next part -------------- An HTML attachment was scrubbed... URL: From magazzinil at gmail.com Tue Jul 4 18:32:27 2017 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Tue, 4 Jul 2017 17:32:27 +0100 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, Perhaps you could try to add the option cfg.rawtrial = 'yes'. I'm not entirely sure, but maybe by using a precomputed filter, the same filter is applied to each single trial separately (rather than constructing a different filter individually for each trial, which I guess is not what you want to do). Lorenzo Lorenzo Magazzini, PhD Research Associate CUBRIC Cardiff University Cardiff CF24 4HQ Tel: +44 (0)2920 870090 *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php * On 4 July 2017 at 17:03, Stephen Whitmarsh wrote: > Hi everyone, > > I am now trying to use the DICS method for sourceanalysis, with > 'powandcsd' output from ft_freqanalysis as its input and using a > precomputed filter and leadfield. However, I would like to keep my separate > trial estimates in the final source analysis, and while the documentation > suggests I should be able to get that with cfg.keeptrials, but this doesn't > have the expected effect. > > I previously made workaround using PCC on fourier data instead (see > below), I think to deal with this issue. I was wondering if this is still > the recommended option, i.e. workaround? Alternatively, and perhaps > preferably, would someone have a suggestion for a solution consistent with > the DICS implementation? > > Thanks for your time, > Stephen > > % source analysis > cfg.method = 'pcc'; > ... > cfg.keeptrials = 'yes'; > cfg.pcc.keepmom = 'yes'; > cfg.pcc.fixedori = 'no'; > source_control = ft_sourceanalysis(cfg, FFT); > > and then: > > % project moment and tapers > cfg = []; > cfg.projectmom = 'no'; > cfg.keeptrials = 'yes'; > cfg.powmethod = 'lambda1'; > source = ft_sourcedescriptives(cfg,source); > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 18:51:47 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 18:51:47 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Lorenzo, Thanks, I will give it a try tomorrow, but the documentation suggest that it's not what I want: Just for clarity, I would like to use the same filter on separate trials. Best wishes, Stephen On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > Hi Stephen, > > Perhaps you could try to add the option cfg.rawtrial = 'yes'. > > I'm not entirely sure, but maybe by using a precomputed filter, the same > filter is applied to each single trial separately (rather than constructing > a different filter individually for each trial, which I guess is not what > you want to do). > > Lorenzo > > > > Lorenzo Magazzini, PhD > > Research Associate > > CUBRIC > > Cardiff University > > Cardiff CF24 4HQ > > Tel: +44 (0)2920 870090 <+44%2029%202087%200090> > > *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php > * > > > > > On 4 July 2017 at 17:03, Stephen Whitmarsh > wrote: > >> Hi everyone, >> >> I am now trying to use the DICS method for sourceanalysis, with >> 'powandcsd' output from ft_freqanalysis as its input and using a >> precomputed filter and leadfield. However, I would like to keep my separate >> trial estimates in the final source analysis, and while the documentation >> suggests I should be able to get that with cfg.keeptrials, but this doesn't >> have the expected effect. >> >> I previously made workaround using PCC on fourier data instead (see >> below), I think to deal with this issue. I was wondering if this is still >> the recommended option, i.e. workaround? Alternatively, and perhaps >> preferably, would someone have a suggestion for a solution consistent with >> the DICS implementation? >> >> Thanks for your time, >> Stephen >> >> % source analysis >> cfg.method = 'pcc'; >> ... >> cfg.keeptrials = 'yes'; >> cfg.pcc.keepmom = 'yes'; >> cfg.pcc.fixedori = 'no'; >> source_control = ft_sourceanalysis(cfg, FFT); >> >> and then: >> >> % project moment and tapers >> cfg = []; >> cfg.projectmom = 'no'; >> cfg.keeptrials = 'yes'; >> cfg.powmethod = 'lambda1'; >> source = ft_sourcedescriptives(cfg,source); >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiew1202 at gmail.com Tue Jul 4 19:36:55 2017 From: xiew1202 at gmail.com (Xie Wanze) Date: Tue, 04 Jul 2017 17:36:55 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, I met the same issue last year when I did my source analysis and functional connectivity analysis. I asked it through the maillist but no one seemed to have an answer. What I ended up with doing was to maunally calculate the source analysis with the spatial filter for each single trial. So,1. Use the ft_sourceanalysis to get the filter. 2. Multiply the filter with your single trial data with a loop or whatever. Wanze Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > Hi Lorenzo, > > Thanks, I will give it a try tomorrow, but the documentation suggest that > it's not what I want: Just for clarity, I would like to use the same filter > on separate trials. > > Best wishes, > Stephen > > On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > >> Hi Stephen, >> >> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >> >> I'm not entirely sure, but maybe by using a precomputed filter, the same >> filter is applied to each single trial separately (rather than constructing >> a different filter individually for each trial, which I guess is not what >> you want to do). >> >> Lorenzo >> >> >> >> Lorenzo Magazzini, PhD >> >> Research Associate >> >> CUBRIC >> >> Cardiff University >> >> Cardiff CF24 4HQ >> >> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >> >> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >> * >> >> >> >> >> On 4 July 2017 at 17:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From xiew1202 at gmail.com Tue Jul 4 19:38:15 2017 From: xiew1202 at gmail.com (Xie Wanze) Date: Tue, 04 Jul 2017 17:38:15 +0000 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: I mean manually calculated the filter with ft source analysis. Sorry for my typo in my last email. Good luck. Wanze Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > Hi Lorenzo, > > Thanks, I will give it a try tomorrow, but the documentation suggest that > it's not what I want: Just for clarity, I would like to use the same filter > on separate trials. > > Best wishes, > Stephen > > On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: > >> Hi Stephen, >> >> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >> >> I'm not entirely sure, but maybe by using a precomputed filter, the same >> filter is applied to each single trial separately (rather than constructing >> a different filter individually for each trial, which I guess is not what >> you want to do). >> >> Lorenzo >> >> >> >> Lorenzo Magazzini, PhD >> >> Research Associate >> >> CUBRIC >> >> Cardiff University >> >> Cardiff CF24 4HQ >> >> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >> >> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >> * >> >> >> >> >> On 4 July 2017 at 17:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Tue Jul 4 19:48:56 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Tue, 4 Jul 2017 19:48:56 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Wanze, Sorry to hear you didn't get a response last year, but thanks for sharing yours! Indeed, that seems to be the most elegant work-around to me as well. I'll probably do that. Thanks! Stephen On 4 July 2017 at 19:38, Xie Wanze wrote: > I mean manually calculated the filter with ft source analysis. Sorry for > my typo in my last email. > > Good luck. > > Wanze > Stephen Whitmarsh 于2017年7月4日 周二上午9:52写道： > >> Hi Lorenzo, >> >> Thanks, I will give it a try tomorrow, but the documentation suggest that >> it's not what I want: Just for clarity, I would like to use the same filter >> on separate trials. >> >> Best wishes, >> Stephen >> >> On 4 July 2017 at 18:32, Lorenzo Magazzini wrote: >> >>> Hi Stephen, >>> >>> Perhaps you could try to add the option cfg.rawtrial = 'yes'. >>> >>> I'm not entirely sure, but maybe by using a precomputed filter, the same >>> filter is applied to each single trial separately (rather than constructing >>> a different filter individually for each trial, which I guess is not what >>> you want to do). >>> >>> Lorenzo >>> >>> >>> >>> Lorenzo Magazzini, PhD >>> >>> Research Associate >>> >>> CUBRIC >>> >>> Cardiff University >>> >>> Cardiff CF24 4HQ >>> >>> Tel: +44 (0)2920 870090 <+44%2029%202087%200090> >>> >>> *http://psych.cf.ac.uk/contactsandpeople/magazzinil.php >>> * >>> >>> >>> >>> >>> On 4 July 2017 at 17:03, Stephen Whitmarsh >>> wrote: >>> >>>> Hi everyone, >>>> >>>> I am now trying to use the DICS method for sourceanalysis, with >>>> 'powandcsd' output from ft_freqanalysis as its input and using a >>>> precomputed filter and leadfield. However, I would like to keep my separate >>>> trial estimates in the final source analysis, and while the documentation >>>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>>> have the expected effect. >>>> >>>> I previously made workaround using PCC on fourier data instead (see >>>> below), I think to deal with this issue. I was wondering if this is still >>>> the recommended option, i.e. workaround? Alternatively, and perhaps >>>> preferably, would someone have a suggestion for a solution consistent with >>>> the DICS implementation? >>>> >>>> Thanks for your time, >>>> Stephen >>>> >>>> % source analysis >>>> cfg.method = 'pcc'; >>>> ... >>>> cfg.keeptrials = 'yes'; >>>> cfg.pcc.keepmom = 'yes'; >>>> cfg.pcc.fixedori = 'no'; >>>> source_control = ft_sourceanalysis(cfg, FFT); >>>> >>>> and then: >>>> >>>> % project moment and tapers >>>> cfg = []; >>>> cfg.projectmom = 'no'; >>>> cfg.keeptrials = 'yes'; >>>> cfg.powmethod = 'lambda1'; >>>> source = ft_sourcedescriptives(cfg,source); >>>> >>>> >>>> >>>> _______________________________________________ >>>> fieldtrip mailing list >>>> fieldtrip at donders.ru.nl >>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Wed Jul 5 08:51:13 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Wed, 5 Jul 2017 06:51:13 +0000 Subject: [FieldTrip] Fwd: How to adapt a layout file References: Message-ID: <2D579D2D-F542-4FC2-A1A8-C0FCED73CC51@donders.ru.nl> Hi Simone, What is the question behind the question? The reason I ask this is because overcomplete layout files (i.e. files containing more channels than you need) don’t prevent you from visualizing your own data. If you anyhow want to manually remove channels (and the corresponding information in pos/height etc) your code is not foolproof, most likely because setdiff may inadvertently alphabetize the labels, causing the mismatch you report. you could do: remove = {…}; sel = ismember(lay.label, remove); lay.pos = lay.pos(~sel,:); lay.height = lay.height(~sel); etc. Best, Jan-Mathijs On 04 Jul 2017, at 16:56, Sprenger, S.A. > wrote: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/template/layout/easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Wed Jul 5 10:40:39 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Wed, 5 Jul 2017 11:40:39 +0300 Subject: [FieldTrip] dipin and refdip in beamformer_dics? Message-ID: Dear Fieldtrip experts, As far as I understand, beamformer_dics gives coherence between two brain areas if I define parameters dipin and refdip. Could you please let me kown how dipin and refdip should be calculated or in which format they should be? Best, Maria -------------- next part -------------- An HTML attachment was scrubbed... URL: From s.a.sprenger at rug.nl Thu Jul 6 10:11:05 2017 From: s.a.sprenger at rug.nl (Sprenger, S.A.) Date: Thu, 6 Jul 2017 10:11:05 +0200 Subject: [FieldTrip] How to adapt a layout file: thanks for the solution Message-ID: Dear Jan-Mathijs, Thank you very much for your response with respect to the adaption of layout files. The solution that you suggested works fine and our issue has been solved. In case someone would like to review the question and response, please see below. Kind regards, Simone ____________ Message: 9 Date: Wed, 5 Jul 2017 06:51:13 +0000 From: "Schoffelen, J.M. (Jan Mathijs)" To: FieldTrip discussion list Subject: [FieldTrip] Fwd: How to adapt a layout file Message-ID: <2D579D2D-F542-4FC2-A1A8-C0FCED73CC51 at donders.ru.nl> Content-Type: text/plain; charset="utf-8" Hi Simone, What is the question behind the question? The reason I ask this is because overcomplete layout files (i.e. files containing more channels than you need) don?t prevent you from visualizing your own data. If you anyhow want to manually remove channels (and the corresponding information in pos/height etc) your code is not foolproof, most likely because setdiff may inadvertently alphabetize the labels, causing the mismatch you report. you could do: remove = {?}; sel = ismember(lay.label, remove); lay.pos = lay.pos(~sel,:); lay.height = lay.height(~sel); etc. Best, Jan-Mathijs On 04 Jul 2017, at 16:56, Sprenger, S.A. > wrote: Dear colleagues, I was wondering whether someone could give us some advice on how to adapt an existing layout file. We would like to adapt easycapM1.mat, as our own layout is highly similar. Specifically, we would like to remove F1, F2, FT7, FT8, TP7, TP8, CP1 and CP2. In addition, we would like to add the mastoids (for ICA plotting purposes). We tried the following: % removing F1, F2, FT7, FT8, TP7, TP8, CP1, CP2: load('/Volumes/DATA/Applications/fieldtrip-20170425/template/layout/ easycapM1.mat'); % this plots the layout with electrodes on the correct positions: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); for i = {'F1', 'F2', 'FT7', 'FT8', 'TP7', 'TP8', 'CP1', 'CP2'} [truefalse, index] = ismember(i, lay.label); if truefalse == 1 lay.label = setdiff(lay.label, lay.label{index}); lay.width = lay.width([1:(index-1), (index+1):end]); lay.height = lay.height([1:(index-1), (index+1):end]); lay.pos = lay.pos([1:(index-1), (index+1):end],:); end end % now suddenly many electrodes are plotted on wrong locations, % but we just wanted to remove some electrodes: cfg = []; cfg.layout = lay; ft_layoutplot(cfg); Comments and suggestions will be much appreciated. Kind regards, Simone _____________________________________________ Dr. S.A. Sprenger University of Groningen Faculty of Arts Center for Language and Cognition Visiting address: Oude Kijk in 't Jatstraat 26 Room 1315.420 9712 EK Groningen Working hours: mo-thur 050 363 9619 -------------- next part -------------- An HTML attachment was scrubbed... URL: From orekhova.elena.v at gmail.com Thu Jul 6 16:57:07 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Thu, 6 Jul 2017 16:57:07 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Just recently had the same problem. It worked with cfg.rawtrial='yes'. Best, Elena On 4 July 2017 at 18:03, Stephen Whitmarsh wrote: > Hi everyone, > > I am now trying to use the DICS method for sourceanalysis, with > 'powandcsd' output from ft_freqanalysis as its input and using a > precomputed filter and leadfield. However, I would like to keep my separate > trial estimates in the final source analysis, and while the documentation > suggests I should be able to get that with cfg.keeptrials, but this doesn't > have the expected effect. > > I previously made workaround using PCC on fourier data instead (see > below), I think to deal with this issue. I was wondering if this is still > the recommended option, i.e. workaround? Alternatively, and perhaps > preferably, would someone have a suggestion for a solution consistent with > the DICS implementation? > > Thanks for your time, > Stephen > > % source analysis > cfg.method = 'pcc'; > ... > cfg.keeptrials = 'yes'; > cfg.pcc.keepmom = 'yes'; > cfg.pcc.fixedori = 'no'; > source_control = ft_sourceanalysis(cfg, FFT); > > and then: > > % project moment and tapers > cfg = []; > cfg.projectmom = 'no'; > cfg.keeptrials = 'yes'; > cfg.powmethod = 'lambda1'; > source = ft_sourcedescriptives(cfg,source); > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Thu Jul 6 18:03:51 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Thu, 6 Jul 2017 18:03:51 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Elena! Thanks! But I do wonder.. did you check whether the common filter (specified in the cfg) was used or whether a filter was calculated for each trial separately (which does not make sense in my case)? Best, Stephen On 6 July 2017 at 16:57, Elena Orekhova wrote: > Just recently had the same problem. > It worked with cfg.rawtrial='yes'. > > Best, > Elena > > On 4 July 2017 at 18:03, Stephen Whitmarsh > wrote: > >> Hi everyone, >> >> I am now trying to use the DICS method for sourceanalysis, with >> 'powandcsd' output from ft_freqanalysis as its input and using a >> precomputed filter and leadfield. However, I would like to keep my separate >> trial estimates in the final source analysis, and while the documentation >> suggests I should be able to get that with cfg.keeptrials, but this doesn't >> have the expected effect. >> >> I previously made workaround using PCC on fourier data instead (see >> below), I think to deal with this issue. I was wondering if this is still >> the recommended option, i.e. workaround? Alternatively, and perhaps >> preferably, would someone have a suggestion for a solution consistent with >> the DICS implementation? >> >> Thanks for your time, >> Stephen >> >> % source analysis >> cfg.method = 'pcc'; >> ... >> cfg.keeptrials = 'yes'; >> cfg.pcc.keepmom = 'yes'; >> cfg.pcc.fixedori = 'no'; >> source_control = ft_sourceanalysis(cfg, FFT); >> >> and then: >> >> % project moment and tapers >> cfg = []; >> cfg.projectmom = 'no'; >> cfg.keeptrials = 'yes'; >> cfg.powmethod = 'lambda1'; >> source = ft_sourcedescriptives(cfg,source); >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From explena at gmail.com Fri Jul 7 05:21:58 2017 From: explena at gmail.com (Shen-Mou Hsu) Date: Fri, 7 Jul 2017 11:21:58 +0800 Subject: [FieldTrip] a question regarding the code for PPC computation Message-ID: Dear FT users, I am writing to request how pairwise phase consistency (PPC) is implemented in Fieldtrip. I trace the code and find that the following lines are relevant for PPC computation input = input./abs(input); % normalize the crosspectrum outsum = nansum(input); % compute the sum; this is 1 x size(2:end) c = (outsum.*conj(outsum) - n)./(n*(n-1)); % do the pairwise thing in a handy way However, when I try to verify the results by performing the equations indicated by Vinck et. al. (2010), the outcomes are totally different from those performed using ft_connectivity_ppc. My code is as follows and many thanks for any help. %%%%%%%%%%%%%%%%%%%%%%%%% nTrial = size(input,1); ppc_all = []; for j = 1:(nTrial-1) for k = (j+1):nTrial ppc_temp = input(j,1,:,:).*conj(input(k,1,:,:)); ppc_all = [ppc_all;ppc_temp]; end end PPC = squeeze(abs(nansum(ppc_all,1)*2/(nTrial*(nTrial-1)))); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% Best, Shen-Mou Hsu -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Fri Jul 7 08:08:10 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Fri, 7 Jul 2017 09:08:10 +0300 Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence). With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal). I hope this helps. Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions. Best, Maria 2017-06-29 12:57 GMT+03:00 Maria Hakonen : > Hi Maria, > for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. > > Best,Maité > http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series > http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series > > Hi Maité, > > Thank for your answer again! > > However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics? > > Best, > > Maria > > > 2017-06-26 12:45 GMT+03:00 Maria Hakonen : > >> Hi Maria, >> maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. >> >> Best,Maité >> >> >> Hi Maité, >> >> Could you please yet let me know how to get the sources timecources? >> source = ft_sourceanalysis(cfg, freq); only gives >> source = >> >> freq: 18 >> cumtapcnt: [180x1 double] >> dim: [19 15 15] >> inside: [4275x1 logical] >> pos: [4275x3 double] >> method: 'average' >> avg: [1x1 struct] >> cfg: [1x1 struct] >> >> Best, >> Maria >> >> 2017-06-25 13:53 GMT+03:00 Maria Hakonen : >> >>> Hi Maité, >>> >>> Thank you for your answer! >>> >>> I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.org/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this? >>> >>> BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum. >>> >>> Best, >>> >>> Maria >>> >>> >>> Hi Maria, >>> Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: >>> >>> cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; >>> cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; >>> As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. >>> I hope it helps. >>> Best wishes,Maité >>> >>> >>> >>> Dear FieldTrip experts, >>> >>> I have just started to use Fieldtrip and would like to estimate >>> coherence between MEG responses measured in two different conditions from >>> the same cortical areas. The example in Appendix 1 is close to what I would >>> like to do: >>> http://www.fieldtriptoolbox.org/tutorial/coherence >>> >>> However, in the example, coherence is calculated between the reference >>> signal (EMG) and all MEG channels. Could it be possible to calculate >>> coherence between each MEG channel in one condition and the same MEG >>> channels in the other condition, that is: >>> ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... >>> >>> As far as I understand, the example in Appendix 1 would do this: >>> ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in >>> cond2, ... >>> >>> Best, >>> Maria >>> >>> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From christian.merkel at med.ovgu.de Fri Jul 7 09:19:06 2017 From: christian.merkel at med.ovgu.de (christian.merkel at med.ovgu.de) Date: Fri, 7 Jul 2017 07:19:06 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis Message-ID: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> Hallo to all, My name is Christian Merkel and im using fieldtrip to estimate sources within the visual cortex using high-res sourcemodels from freesurfer. We use an elekta system in our lab. I have a question regarding the time course of activation within the sourcespace once i calculated the spatial filter with ft_sourceanalysis. Here the code for ft_sourceanalysis: cfg = []; cfg.method = 'lcmv'; cfg.channel = sens_aligned.label(strcmp(sens_aligned.chantype,'megplanar')); cfg.grid = lead field_grad; cfg.vol = bem; cfg.projectnoise = 'yes'; cfg.keepfilter = 'yes'; cfg.lambda = 1; data_erf_source = ft_sourceanalysis(cfg, data_cond_erf_bl_avg); The filter looks good and everything works fine. However I have a conceptual question about the timecourse in sourcespace: As far as I understand, the field avg.mom of data_erf_source contains the activation time_course. So to plot one specific sourcedistribution at one time sample I use: pow = squeeze(sort(sum(cat(3,data_erf_source.avg.mom{:}).^2,1)))'; % i use the abs norm of the 3 orientation vectors as a value of source strength figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow(:,time_of_interest)); One other way to get the source distribution at that sample is to convolve the filter with the underlying erf-data: pow = squeeze(sort(sum(cat(3,data_erf_source.avg.filter{:}).^2,1)))'; figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow * data_cond_erf_bl_avg.avg(:,time_of_interest)); But those to distributions look different. Not completely different, but substantially. Why are those two ways of calculating the source-distribution different. I thought that ft_sourceanalysis calculates the field 'mom' by basically convolving the erf_data with the spatial filter and therefore should result in the same distribution as the second version. What is the 'right' way in this case and what do you recommend I use. I thank you for your help. From jan.schoffelen at donders.ru.nl Fri Jul 7 10:13:31 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 7 Jul 2017 08:13:31 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis In-Reply-To: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> References: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de> Message-ID: Dear Christian, > pow = squeeze(sort(sum(cat(3,data_erf_source.avg.mom{:}).^2,1)))'; % i use the abs norm of the 3 orientation vectors as a value of source strength > figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow(:,time_of_interest)); > > One other way to get the source distribution at that sample is to convolve the filter with the underlying erf-data: > > pow = squeeze(sort(sum(cat(3,data_erf_source.avg.filter{:}).^2,1)))'; > figure; ft_plot_mesh(sourcespace, 'vertexcolor', pow * data_cond_erf_bl_avg.avg(:,time_of_interest)); > > > But those to distributions look different. Not completely different, but substantially. Well, let me first be a bit pedantic, by saying that one does not ‘convolve’ the filter with the underlying erf-data, it’s just a multiplication. But no worries, that’s just terminology. The thing that goes wrong in your filter-times-erfdata step, is the fact that you already collapse the spatial filter across the three dipole orientations (and take the square), prior to doing the multiplication. So the difference lies in the order of the operations, it should be sum((F*sensorERF).^2,1). In this case F is a single entry from source.avg.filter. Best, Jan-Mathijs > Why are those two ways of calculating the source-distribution different. I thought that ft_sourceanalysis calculates the field 'mom' by basically convolving the erf_data with the spatial filter and therefore should result in the same distribution as the second version. What is the 'right' way in this case and what do you recommend I use. > > I thank you for your help. > > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From christian.merkel at med.ovgu.de Fri Jul 7 10:28:54 2017 From: christian.merkel at med.ovgu.de (christian.merkel at med.ovgu.de) Date: Fri, 7 Jul 2017 08:28:54 +0000 Subject: [FieldTrip] Calculate activation time-course in sourcespace for ERF-data using ft_sourceanalysis In-Reply-To: References: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D20@esen3.imed.uni-magdeburg.de>, Message-ID: <71D8A67A81D69A4CB5BE2B979021C26ECAFF3D46@esen3.imed.uni-magdeburg.de> Thanks a lot, That makes sense!! I have one follow-up question: What if i want to correct with the noise-term? Should i do that on the single orientations as well or just after the multiplication? I could imagine after, as for the mom-field i can only apply it to the end-result anyway. You're a big help, Christian From orekhova.elena.v at gmail.com Fri Jul 7 10:31:37 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 10:31:37 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Stephen, I followed the tutorial in http://www.fieldtriptoolbox.org/tutorial/salzburg, but used 'dics' (see below). I think that in the example below the sourceavg.avg.filter was indeed used and my results look nice. Elena cfg=[];cfg.method='lcmv';cfg.grid =grid ;cfg.grid .filter =sourceavg.avg.filter ;cfg.rawtrial = 'yes';cfg.vol=hdm; sourcepreS1=ft_sourceanalysis(cfg, avgpre); sourcepstS1=ft_sourceanalysis(cfg, avgpst); On 6 July 2017 at 18:03, Stephen Whitmarsh wrote: > Hi Elena! > > Thanks! But I do wonder.. did you check whether the common filter > (specified in the cfg) was used or whether a filter was calculated for each > trial separately (which does not make sense in my case)? > > Best, > Stephen > > On 6 July 2017 at 16:57, Elena Orekhova > wrote: > >> Just recently had the same problem. >> It worked with cfg.rawtrial='yes'. >> >> Best, >> Elena >> >> On 4 July 2017 at 18:03, Stephen Whitmarsh >> wrote: >> >>> Hi everyone, >>> >>> I am now trying to use the DICS method for sourceanalysis, with >>> 'powandcsd' output from ft_freqanalysis as its input and using a >>> precomputed filter and leadfield. However, I would like to keep my separate >>> trial estimates in the final source analysis, and while the documentation >>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>> have the expected effect. >>> >>> I previously made workaround using PCC on fourier data instead (see >>> below), I think to deal with this issue. I was wondering if this is still >>> the recommended option, i.e. workaround? Alternatively, and perhaps >>> preferably, would someone have a suggestion for a solution consistent with >>> the DICS implementation? >>> >>> Thanks for your time, >>> Stephen >>> >>> % source analysis >>> cfg.method = 'pcc'; >>> ... >>> cfg.keeptrials = 'yes'; >>> cfg.pcc.keepmom = 'yes'; >>> cfg.pcc.fixedori = 'no'; >>> source_control = ft_sourceanalysis(cfg, FFT); >>> >>> and then: >>> >>> % project moment and tapers >>> cfg = []; >>> cfg.projectmom = 'no'; >>> cfg.keeptrials = 'yes'; >>> cfg.powmethod = 'lambda1'; >>> source = ft_sourcedescriptives(cfg,source); >>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From stephen.whitmarsh at gmail.com Fri Jul 7 10:57:17 2017 From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh) Date: Fri, 7 Jul 2017 10:57:17 +0200 Subject: [FieldTrip] keeptrials = 'yes' with DICS does not keep trials In-Reply-To: References: <1e05d62c4f7e442cae18fdcbd3c3c07a@EXPRD03.hosting.ru.nl> Message-ID: Hi Elena, Thanks for the link - that is indeed a very nice and complete tutorial! A link in the current beamformer tutorial would be helpful for the next time I think - I will put one there. And yes, I see now that although the documentation is as follows: % cfg.rawtrial = 'no' or 'yes' *construct filter from single trials*, apply to single trials. Note that you also may want to set cfg.keeptrials='yes' to keep all trial information, especially if using in combination with grid.filter (I find the red part inconsistent) it does take the pre-specified filter when provided, which is suggested somewhat implicitly further down in the code: if strcmp(cfg.rawtrial,'yes') && isfield(cfg,'grid') && ~isfield(cfg.grid,'filter') warning('Using each trial to compute its own filter is not currently recommended. Use this option only with precomputed filters in grid.filter'); end So that really clears it up. I will suggest an edit to the documentation, for the sake of clarification, and next time I run my beamformer I will remove the loop over trials :-) Thanks again, Stephen On 7 July 2017 at 10:31, Elena Orekhova wrote: > Hi Stephen, > I followed the tutorial in http://www.fieldtriptoolbox.or > g/tutorial/salzburg, but used 'dics' (see below). > I think that in the example below the sourceavg.avg.filter was indeed > used and my results look nice. > > Elena > > cfg=[];cfg.method='lcmv';cfg.grid =grid ;cfg.grid .filter =sourceavg.avg.filter ;cfg.rawtrial = 'yes';cfg.vol=hdm; > sourcepreS1=ft_sourceanalysis(cfg, avgpre); > sourcepstS1=ft_sourceanalysis(cfg, avgpst); > > > > On 6 July 2017 at 18:03, Stephen Whitmarsh > wrote: > >> Hi Elena! >> >> Thanks! But I do wonder.. did you check whether the common filter >> (specified in the cfg) was used or whether a filter was calculated for each >> trial separately (which does not make sense in my case)? >> >> Best, >> Stephen >> >> On 6 July 2017 at 16:57, Elena Orekhova >> wrote: >> >>> Just recently had the same problem. >>> It worked with cfg.rawtrial='yes'. >>> >>> Best, >>> Elena >>> >>> On 4 July 2017 at 18:03, Stephen Whitmarsh >>> wrote: >>> >>>> Hi everyone, >>>> >>>> I am now trying to use the DICS method for sourceanalysis, with >>>> 'powandcsd' output from ft_freqanalysis as its input and using a >>>> precomputed filter and leadfield. However, I would like to keep my separate >>>> trial estimates in the final source analysis, and while the documentation >>>> suggests I should be able to get that with cfg.keeptrials, but this doesn't >>>> have the expected effect. >>>> >>>> I previously made workaround using PCC on fourier data instead (see >>>> below), I think to deal with this issue. I was wondering if this is still >>>> the recommended option, i.e. workaround? Alternatively, and perhaps >>>> preferably, would someone have a suggestion for a solution consistent with >>>> the DICS implementation? >>>> >>>> Thanks for your time, >>>> Stephen >>>> >>>> % source analysis >>>> cfg.method = 'pcc'; >>>> ... >>>> cfg.keeptrials = 'yes'; >>>> cfg.pcc.keepmom = 'yes'; >>>> cfg.pcc.fixedori = 'no'; >>>> source_control = ft_sourceanalysis(cfg, FFT); >>>> >>>> and then: >>>> >>>> % project moment and tapers >>>> cfg = []; >>>> cfg.projectmom = 'no'; >>>> cfg.keeptrials = 'yes'; >>>> cfg.powmethod = 'lambda1'; >>>> source = ft_sourcedescriptives(cfg,source); >>>> >>>> >>>> >>>> _______________________________________________ >>>> fieldtrip mailing list >>>> fieldtrip at donders.ru.nl >>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>>> >>> >>> >>> _______________________________________________ >>> fieldtrip mailing list >>> fieldtrip at donders.ru.nl >>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >>> >> >> >> _______________________________________________ >> fieldtrip mailing list >> fieldtrip at donders.ru.nl >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Fri Jul 7 11:17:16 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Fri, 7 Jul 2017 09:17:16 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: <35126809.503758.1499419036176@mail.yahoo.com> Hi Maria, You are right. I was having a look inside the "inverse\beamformer_dics" function (I suggest you check it out too). As you could see in line 519 of the same function, refdip can be an structure with a field called 'filter' containing the beamformer filter for a particular voxel (brain region of condition 2, for example). So, you could first compute the DICS filters for condition 2 and then passing them one by one in the cfg,refdip when calling the ft_sourceanalysis together with the data of condition 1. I hope this works out. Best wishes,Maité El Viernes 7 de julio de 2017 8:23, Maria Hakonen escribió: Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox.org/tutorial/coherence#computing_the_coherence).With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal).I hope this helps.  Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions.  Best,Maria    2017-06-29 12:57 GMT+03:00 Maria Hakonen : Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox. org/tutorial/connectivity# extract_the_virtual_channel_ time-series http://www.fieldtriptoolbox. org/tutorial/shared/virtual_ sensors#extract_the_virtual_ channel_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Fri Jul 7 11:25:06 2017 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Fri, 7 Jul 2017 10:25:06 +0100 Subject: [FieldTrip] PhD positions in Birmingham, UK with Prof. Noppeney Message-ID: Dear all, Prof. Uta Noppeney (with whom I now work) has available these 2 PhD positions for an exciting new project: 1. Robust audiovisual speech recognition in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87556 2. Syntactic parsing in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87595 Please contact Uta (U.Noppeney at bham.ac.uk) with any questions. Kind regards, Johanna -------------- next part -------------- An HTML attachment was scrubbed... URL: From johanna.zumer at gmail.com Fri Jul 7 11:41:51 2017 From: johanna.zumer at gmail.com (Johanna Zumer) Date: Fri, 7 Jul 2017 10:41:51 +0100 Subject: [FieldTrip] PhD positions in Birmingham, UK with Prof. Noppeney Message-ID: Dear all, Prof. Uta Noppeney (with whom I now work) has available these 2 PhD positions for an exciting new project: 1. Robust audiovisual speech recognition in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87556 2. Syntactic parsing in man and machine https://www.findaphd.com/search/ProjectDetails.aspx?PJID=87595 Please contact Uta (U.Noppeney at bham.ac.uk) with any questions. Kind regards, Johanna -------------- next part -------------- An HTML attachment was scrubbed... URL: From orekhova.elena.v at gmail.com Fri Jul 7 16:14:21 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 16:14:21 +0200 Subject: [FieldTrip] mri segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the fig. below). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena [image: Displaying image.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 70400 bytes Desc: not available URL: From orekhova.elena.v at gmail.com Fri Jul 7 16:26:17 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Fri, 7 Jul 2017 16:26:17 +0200 Subject: [FieldTrip] mri segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the fig. below). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena [image: Displaying image.png] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image.png Type: image/png Size: 70400 bytes Desc: not available URL: From orekhova.elena.v at gmail.com Sat Jul 8 19:11:17 2017 From: orekhova.elena.v at gmail.com (Elena Orekhova) Date: Sat, 8 Jul 2017 19:11:17 +0200 Subject: [FieldTrip] brain segmentation problem Message-ID: Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fig1.png Type: image/png Size: 66721 bytes Desc: not available URL: From RICHARDS at mailbox.sc.edu Sun Jul 9 14:45:10 2017 From: RICHARDS at mailbox.sc.edu (RICHARDS, JOHN) Date: Sun, 9 Jul 2017 12:45:10 +0000 Subject: [FieldTrip] fieldtrip Digest, Vol 80, Issue 7 In-Reply-To: References: Message-ID: Elena The ft_volumesegment uses the SPM program that does gm/wm segmentation into probability maps. In the case of using = {'brain', 'skull', 'scalp'}; as input, the program sums the PVE for GM, WM and "CSF" (other matter) to create the brain (+ fill holes and some other); then has a formula for finding the skull (dilate brain, or use bone class from segmented MRI), and scalp. So the "skullstrip" portion consists of the brain PVEs from the SPM segmentation program. If that program does not work correctly then the overlap of the brain mask will not match the actual brain--could either not cover all the brain or cover more than the brain. I have had some issues with the SPM algorithm, and its use in the ft_volumesegment is not very flexible. I do the segmentation outside of FT using FSL tools (e.g., bet, bet2, betsurf) and then import the segmented head into FT format; FSL also has an algorithm for "skull stripping" found in its VBM script. This way I have more control over the initial segmented products. Additionally, neither the SPM nor the FSL routines work with some pediatric populations, especially infants under 2 years of age. In that case I often substitute the initial MRI template (in FT case, as SPM, they use the MNI segmented head) with an infant MRI template and get much better results. (e.g., neurodevelopmental MRI database). At times I have used the SPM algorithms for brain segmenting (GM, WM, CSF) and in this case also the PVEs from an age-appropriate brain improve the results. John *********************************************** John E. Richards Carolina Distinguished Professor Department of Psychology University of South Carolina Columbia, SC  29208 Dept Phone: 803 777 2079 Fax: 803 777 9558 Email: richards-john at sc.edu HTTP: jerlab.psych.sc.edu ************************************************* -----Original Message----- From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of fieldtrip-request at science.ru.nl Sent: Sunday, July 9, 2017 6:00 AM To: fieldtrip at science.ru.nl Subject: fieldtrip Digest, Vol 80, Issue 7 Send fieldtrip mailing list submissions to fieldtrip at science.ru.nl To subscribe or unsubscribe via the World Wide Web, visit https://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. brain segmentation problem (Elena Orekhova) ---------------------------------------------------------------------- Message: 1 Date: Sat, 8 Jul 2017 19:11:17 +0200 From: Elena Orekhova To: FieldTrip discussion list Subject: [FieldTrip] brain segmentation problem Message-ID: Content-Type: text/plain; charset="utf-8" Dear Fieldtrip experts, I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used mri_orig= ft_read_mri ('T1.mgz'); ... cfg = []; cfg.output = {'brain', 'skull', 'scalp'}; mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); Have anybody had such a problem. How can it be resolved? Elena -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: fig1.png Type: image/png Size: 66721 bytes Desc: not available URL: ------------------------------ _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip End of fieldtrip Digest, Vol 80, Issue 7 **************************************** From anne.urai at gmail.com Mon Jul 10 10:38:59 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 10 Jul 2017 01:38:59 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 Message-ID: Dear Fieldtrippers, I'm using the VTPM atlas to define masks for all the visual regions described in the paper (Wang et al. 2014, https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bhu277). However, there seem to be no entries corresponding to the left IPS5. *% load atlas* *atl = ft_read_atlas('~/Documents/fieldtrip/vtpm/vtpm.mat');* *atl = ft_convert_units(atl, 'cm');* *% add mni coordinates* *[ax, ay, az] = voxelcoords(atl.dim, atl.transform);* *atl.pos = [ax(:) ay(:) az(:)];* *% make a binary mask for this ROI* *roi_idx = find(strcmp(lower(atl.tissuelabel), 'IPS5'));* *roi_mask = ismember(atl.tissue, roi_idx);* *% mask the voxels on the right side of the brain* *rightidx = find(atl.pos(:, 1) > 0); * *roi_mask(rightidx) = 0;* Now, sum(roi_mask(:)) = 0. This procedure of separating out the left and right regions works fine for all other regions in the atlas, as well as the right IPS5. The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? Thanks! — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai -------------- next part -------------- An HTML attachment was scrubbed... URL: From maria.hakonen at gmail.com Mon Jul 10 14:37:20 2017 From: maria.hakonen at gmail.com (Maria Hakonen) Date: Mon, 10 Jul 2017 15:37:20 +0300 Subject: [FieldTrip] Estimate coherence between conditions? In-Reply-To: References: Message-ID: Hi Maité, Many thanks for your answer! I have now tried to get coherence between two conditions following the Appendix 1 (I have also used the same data as in Appendix 1; http://www.fieldtriptoolbox.org/tutorial/coherence). As far as I understand, I should first calculate ft_freqanalysis and ft_sourceanalysis separately for condition 1 and condition 2 as follows: *Condition 1:* Compute the cross-spectral density matrix for 18 Hz: cfg = []; cfg.method = 'mtmfft'; cfg.output = 'powandcsd'; cfg.foilim = [18 18]; cfg.tapsmofrq = 5; cfg.keeptrials = 'yes'; freq1 = ft_freqanalysis(cfg, data); The Appendix 1 also defines: cfg.channelcmb = {'MEG' 'MEG';'MEG' 'EMGlft'}; However, I think that in my case channelcmb is not needed since default = {'all' 'all'}. Thereafter, I used ft_sourceanalysis as follows: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; source1 = ft_sourceanalysis(cfg, freq); (The Appendix 1 also defines: cfg.refchan = 'EMGlft';) *Condition 2:* I calculated cross-spectral density exactly in the same way as in condition 1 but used data from condition 2. In ft_sourceanalysis, I set keepfilter and keepleadfiled as “yes”: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; cfg.keepfilter = ‘yes’; cfg.keepleadfield = ‘yes’; source2 = ft_sourceanalysis(cfg, freq2); Thereafter, I selected a source that in inside the brain from source2 and included it’s position, leadfield and filter in refdip: refdip = pos: [5 -5 -1] leadfield: {[151x3 double]} filetr: [3x151 double] After this, I run ft_sourceanalysis: cfg = []; cfg.method = 'dics'; cfg.frequency = 18; cfg.hdmfile = 'SubjectCMC.hdm'; cfg.inwardshift = 1; cfg.grid.resolution = 1; cfg.grid.unit = 'cm'; cfg.refdip = refdip; source = ft_sourceanalysis(cfg, freq1); Here, I used cross spectral density matrix computed from condition 1 (i.e. freq1). I am not sure, whether I should also somehow take into account the data from condition 2 when calculating freq? Appendix 1 uses EMGlft as refchan in ft_sourceanalysis and has defined cfg.channelcmb = {'MEG' 'MEG';'MEG' 'EMGlft'}; in ft_freqanalysis. The coherence in the position of the reference dipole (i.e. 5 -5 -1) seems to be one, as would be expected since I used the same data in both conditions. Best, Maria 2017-07-07 9:08 GMT+03:00 Maria Hakonen : > Hi Maria, > > I think there is more than one solution for what you are aiming to do. > Maybe a more experienced user or developer could show you the most > straightforward way (?). > > IMO, using LCMV is more direct for this application because with DICS you > will need to provide the reference signal (i.e., the source timecourse from > the other condition). Therefore, you will need to apply LCMV anyway. > > You could apply a band-pass filter to the channel activity before > localizing the frequency band of interest with LCMV. Alternatively, you > could obtain the virtual channels (without band pass) and define the > frequency bands of interest when computing the coherence as in the tutorial > (see ft_freqanalysis steps at http://www.fieldtriptoolbox. > org/tutorial/coherence#computing_the_coherence). > With DICS, in this case, I see it more intricate: 1) obtain the source > timecourses of condition 2 with LCVM; 2) compute the cross spectral density > between all data channels and each source timecourse (reference signal); 3) > compute DICS for each reference signal. Of course, you don't need to > compute the coherence for the whole brain, but only for the source of > interest. For each reference signal, you could change the cfg.grid.inside > value to include only the position of the voxel of interest (the same voxel > of the reference signal). > I hope this helps. > > Best,Maité > > Hi Maité, > > Many thanks for your advice again! > > I have been wondering whether I could calculate coherence straight from > the cross spectros without reference signals or virtual channels by using > beamformer_dics. In beamformer_dics, it seems to be possible to define the > location of the dipole with which coherence is computed (i.e. refdip). > However, I am not sure if it is possible to calculate the coherence between > the same brain region in two different conditions. > > Best, > Maria > > 2017-06-29 12:57 GMT+03:00 Maria Hakonen : > >> Hi Maria, >> for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. >> >> Best,Maité >> http://www.fieldtriptoolbox.org/tutorial/connectivity#extract_the_virtual_channel_time-series >> http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors#extract_the_virtual_channel_time-series >> >> Hi Maité, >> >> Thank for your answer again! >> >> However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics? >> >> Best, >> >> Maria >> >> >> 2017-06-26 12:45 GMT+03:00 Maria Hakonen : >> >>> Hi Maria, >>> maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. >>> >>> Best,Maité >>> >>> >>> Hi Maité, >>> >>> Could you please yet let me know how to get the sources timecources? >>> source = ft_sourceanalysis(cfg, freq); only gives >>> source = >>> >>> freq: 18 >>> cumtapcnt: [180x1 double] >>> dim: [19 15 15] >>> inside: [4275x1 logical] >>> pos: [4275x3 double] >>> method: 'average' >>> avg: [1x1 struct] >>> cfg: [1x1 struct] >>> >>> Best, >>> Maria >>> >>> 2017-06-25 13:53 GMT+03:00 Maria Hakonen : >>> >>>> Hi Maité, >>>> >>>> Thank you for your answer! >>>> >>>> I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.org/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this? >>>> >>>> BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum. >>>> >>>> Best, >>>> >>>> Maria >>>> >>>> >>>> Hi Maria, >>>> Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: >>>> >>>> cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; >>>> cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; >>>> As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. >>>> I hope it helps. >>>> Best wishes,Maité >>>> >>>> >>>> >>>> Dear FieldTrip experts, >>>> >>>> I have just started to use Fieldtrip and would like to estimate >>>> coherence between MEG responses measured in two different conditions from >>>> the same cortical areas. The example in Appendix 1 is close to what I would >>>> like to do: >>>> http://www.fieldtriptoolbox.org/tutorial/coherence >>>> >>>> However, in the example, coherence is calculated between the reference >>>> signal (EMG) and all MEG channels. Could it be possible to calculate >>>> coherence between each MEG channel in one condition and the same MEG >>>> channels in the other condition, that is: >>>> ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... >>>> >>>> As far as I understand, the example in Appendix 1 would do this: >>>> ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in >>>> cond2, ... >>>> >>>> Best, >>>> Maria >>>> >>>> >>> >> > -------------- next part -------------- An HTML attachment was scrubbed... URL: From tzvetan.popov at uni-konstanz.de Mon Jul 10 14:58:24 2017 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Mon, 10 Jul 2017 14:58:24 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: <58C77EC6-E8FE-4C8B-978D-5C6C9C278CB1@uni-konstanz.de> Dear Anne, > > The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? this information was provided by the principle investigator of the paper. You might ask the corresponding author for further details on this. Best tzvetan -------------- next part -------------- An HTML attachment was scrubbed... URL: From maity_winky at yahoo.es Mon Jul 10 19:41:39 2017 From: maity_winky at yahoo.es (=?UTF-8?Q?Mait=C3=A9_Crespo_Garc=C3=ADa?=) Date: Mon, 10 Jul 2017 17:41:39 +0000 (UTC) Subject: [FieldTrip] Estimate coherence between conditions? References: <1981337653.3654632.1499708499318.ref@mail.yahoo.com> Message-ID: <1981337653.3654632.1499708499318@mail.yahoo.com> Dear Maria, you are right, the data from condition 2 should be contained in the channels cross-spectral-density matrix (Cf). If you would do it with the option 'dics_refchan', you could have the same situation as in the tutorial, but substituting the EMG signal by the source time-course. However, I understand you would prefer to use the option 'dics_refdip'; I am not sure whether it is programmed for your particular situation because the function uses only one Cf in this case. "Maybe" it works by providing the Cf including data from both conditions. But then, the dimension of the filters have to match this new Cf to fulfill the equation: csd = filt1 * Cf * ctranspose(filt2); (function beamformer_dics, line 562) And "maybe" you can extend the filters, setting to 0 the filters corresponding to the channels of the opposite condition. But here, you should get advice from somebody who knows the mathematics; I am just speculating, sorry. Best,Maité El Lunes 10 de julio de 2017 14:56, Maria Hakonen escribió: Hi Maité, Many thanksfor your answer! I have nowtried to get coherence between two conditions following the Appendix 1 (I have alsoused the same data as in Appendix 1; http://www.fieldtriptoolbox.org/tutorial/coherence).  As far as Iunderstand, I should first calculate ft_freqanalysis and ft_sourceanalysis separatelyfor condition 1 and condition 2 as follows: Condition1:Compute thecross-spectral density matrix for 18 Hz:cfg            = [];cfg.method     = 'mtmfft';cfg.output     = 'powandcsd';cfg.foilim     = [18 18];cfg.tapsmofrq  = 5;cfg.keeptrials = 'yes';freq1           = ft_freqanalysis(cfg, data); TheAppendix 1 also defines:cfg.channelcmb= {'MEG' 'MEG';'MEG' 'EMGlft'};However, Ithink that in my case channelcmb is not needed since default = {'all' 'all'}. Thereafter,I used ft_sourceanalysis as follows:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';source1              = ft_sourceanalysis(cfg, freq); (The Appendix1 also defines: cfg.refchan         = 'EMGlft';) Condition2:Icalculated cross-spectral density exactly in the same way as in condition 1 butused data from condition 2. In ft_sourceanalysis, I set keepfilterand keepleadfiled as “yes”:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';cfg.keepfilter = ‘yes’;  cfg.keepleadfield = ‘yes’;source2              = ft_sourceanalysis(cfg, freq2); Thereafter, I selected a source thatin inside the brain from source2 and included it’s position, leadfield andfilter in refdip:refdip =            pos: [5 -5 -1]   leadfield: {[151x3 double]}       filetr: [3x151 double] After this,I run ft_sourceanalysis:cfg                 = [];cfg.method          = 'dics';cfg.frequency       = 18;cfg.hdmfile         = 'SubjectCMC.hdm';cfg.inwardshift     = 1;cfg.grid.resolution = 1;cfg.grid.unit       = 'cm';cfg.refdip = refdip;source              = ft_sourceanalysis(cfg, freq1); Here, I used cross spectral densitymatrix computed from condition 1 (i.e. freq1). I am not sure, whether I should alsosomehow take into account the data from condition 2 when calculating freq?  Appendix 1 uses EMGlft as refchan inft_sourceanalysis and has defined  cfg.channelcmb= {'MEG' 'MEG';'MEG' 'EMGlft'}; in ft_freqanalysis. The coherence in the position of thereference dipole (i.e. 5 -5 -1) seems to be one, as would be expected since Iused the same data in both conditions.  Best,Maria  2017-07-07 9:08 GMT+03:00 Maria Hakonen : Hi Maria, I think there is more than one solution for what you are aiming to do. Maybe a more experienced user or developer could show you the most straightforward way (?). IMO, using LCMV is more direct for this application because with DICS you will need to provide the reference signal (i.e., the source timecourse from the other condition). Therefore, you will need to apply LCMV anyway. You could apply a band-pass filter to the channel activity before localizing the frequency band of interest with LCMV. Alternatively, you could obtain the virtual channels (without band pass) and define the frequency bands of interest when computing the coherence as in the tutorial (see ft_freqanalysis steps at http://www.fieldtriptoolbox. org/tutorial/coherence# computing_the_coherence).With DICS, in this case, I see it more intricate: 1) obtain the source timecourses of condition 2 with LCVM; 2) compute the cross spectral density between all data channels and each source timecourse (reference signal); 3) compute DICS for each reference signal. Of course, you don't need to compute the coherence for the whole brain, but only for the source of interest. For each reference signal, you could change the cfg.grid.inside value to include only the position of the voxel of interest (the same voxel of the reference signal).I hope this helps.  Best,Maité Hi Maité, Many thanks for your advice again! I have been wondering whether I could calculate coherence straight from the cross spectros without reference signals or virtual channels by using beamformer_dics. In beamformer_dics, it seems to be possible to define the location of the dipole with which coherence is computed (i.e. refdip). However, I am not sure if it is possible to calculate the coherence between the same brain region in two different conditions.  Best,Maria    2017-06-29 12:57 GMT+03:00 Maria Hakonen : Hi Maria, for obtaining the sources timecourses (aka virtual channels) you can follow the tutorials pasted below. Best,Maité http://www.fieldtriptoolbox.or g/tutorial/connectivity#extrac t_the_virtual_channel_time- series http://www.fieldtriptoolbox.or g/tutorial/shared/virtual_sens ors#extract_the_virtual_channe l_time-series Hi Maité,Thank for your answer again!However, I would need to calculate coherence within certain frequency bands and, therefore, I would like to use dics. The examples in the links seem to use lcmv. Could you please let me know how I can get coherence between conditions using dics?Best,Maria 2017-06-26 12:45 GMT+03:00 Maria Hakonen : Hi Maria, maybe in this case it is better that you export the sources timecourses, build a data matrix with them and treat them in the same way as you did with the channels. Best,Maité Hi Maité, Could you please yet let me know how to get the sources timecources? source = ft_sourceanalysis(cfg, freq); only gives  source =           freq: 18    cumtapcnt: [180x1 double]          dim: [19 15 15]       inside: [4275x1 logical]          pos: [4275x3 double]       method: 'average'          avg: [1x1 struct]          cfg: [1x1 struct] Best,Maria 2017-06-25 13:53 GMT+03:00 Maria Hakonen : Hi Maité,Thank you for your answer!I have managed to calculate the coherence between two conditions in the sensor space in the way you suggested. However, I haven't managed to calculate the coherence between conditions in the source space (i.e. Appendix 1 in http://www.fieldtriptoolbox.or g/tutorial/coherence). ft_sourceanalysis doesn't have channelcmb. I wonder if anyone has any solutions for this?BTW. I didn't get the answer to my question in my email but found it from Fieldtrip archive. However, I have also got some other emails from fieldtrip discussion forum.Best,Maria Hi Maria, Here it is a possible solution. First, rename channels from one of both conditions: for example, for condition 2, {'ch01cond2', 'ch02cond2', ...}. Then, append the data from both conditions. In ft_freqanalysis introduce all the channels combinations you want: cfg.channel = {'MEG' 'ch01cond2' 'ch02cond2' ...}; cfg.channelcmb = {'ch01' 'ch01cond2'; 'ch02' 'ch02cond2'}; As I understand, you could use the same channelcmb later on in ft_connectivityanalysis. I hope it helps. Best wishes,Maité Dear FieldTrip experts, I have just started to use Fieldtrip and would like to estimate coherence between MEG responses measured in two different conditions from the same cortical areas. The example in Appendix 1 is close to what I would like to do: http://www.fieldtriptoolbox.or g/tutorial/coherence However, in the example, coherence is calculated between the reference signal (EMG) and all MEG channels. Could it be possible to calculate coherence between each MEG channel in one condition and the same MEG channels in the other condition, that is: ch1 in cond1 vs. ch1 in cond2, ch2 in cond1 vs. ch2 in cond2, ... As far as I understand, the example in Appendix 1 would do this: ch1 in cond1 vs. all channels in cond2, ch2 in cond ch1 all channels in cond2, ... Best, Maria _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From werkle at mpib-berlin.mpg.de Tue Jul 11 13:38:09 2017 From: werkle at mpib-berlin.mpg.de (MWB) Date: Tue, 11 Jul 2017 13:38:09 +0200 Subject: [FieldTrip] PhD Position in Project Area CONMEM at MPI for Human Development Message-ID: <5739dbcd-e183-6698-3f80-46d5c4e6369b@mpib-berlin.mpg.de> Dear colleagues, the project area "Cognitive an Neural Dynamics of Memory Across the Lifespan (CONMEM)", headed by Myriam Sander & Markus Werkle-Bergner, is searching for a PhD-candiate. Details on the position and the application procedures can be found at: https://www.mpib-berlin.mpg.de/sites/default/files/download/jobs/30-2017_stellenanzeige_lip-ie.pdf For further information, please contact Markus Werkle-Bergner (werkle at mpib-berlin.mpg.de) Best regards, Markus Werkle-Bergner -- ************************************************************** Dr. rer. nat. Markus Werkle-Bergner, Dipl. Psych. Senior Research Scientist (W2) Jacobs Foundation Research Fellow 2017-2019 Center for Lifespan Psychology Max Planck Institute for Human Development Lentzeallee 94, Room 211, D-14195 Berlin, Germany. Phone: +49(0)30-82406-447 Fax: +49(0)30-8249939 ************************************************************** From werkle at mpib-berlin.mpg.de Tue Jul 11 13:38:41 2017 From: werkle at mpib-berlin.mpg.de (MWB) Date: Tue, 11 Jul 2017 13:38:41 +0200 Subject: [FieldTrip] Post-Doc Position in Project Area CONMEM at MPI for Human Development Message-ID: <203919e1-7483-968d-f522-72ad0a78b66b@mpib-berlin.mpg.de> Dear colleagues, the project area "Cognitive an Neural Dynamics of Memory Across the Lifespan (CONMEM)", headed by Myriam Sander & Markus Werkle-Bergner, is searching for a post-doc. Details on the position and the application procedures can be found at: https://www.mpib-berlin.mpg.de/sites/default/files/download/jobs/29-2017_stellenanzeige_lip-ie.pdf For further information, please contact Markus Werkle-Bergner (werkle at mpib-berlin.mpg.de) Best regards, Markus Werkle-Bergner -- ************************************************************** Dr. rer. nat. Markus Werkle-Bergner, Dipl. Psych. Senior Research Scientist (W2) Jacobs Foundation Research Fellow 2017-2019 Center for Lifespan Psychology Max Planck Institute for Human Development Lentzeallee 94, Room 211, D-14195 Berlin, Germany. Phone: +49(0)30-82406-447 Fax: +49(0)30-8249939 ************************************************************** From M.Wimber at bham.ac.uk Tue Jul 11 17:11:36 2017 From: M.Wimber at bham.ac.uk (Maria Wimber) Date: Tue, 11 Jul 2017 15:11:36 +0000 Subject: [FieldTrip] Postdoc on memory & iEEG in Birmingham Message-ID: Hi FieldTrippers We are currently seeking a postdoctoral research fellow to join the Birmingham Memory Group. The position is funded by a 5-year European Research Council (ERC) grant awarded to Dr Maria Wimber (www.memorybham.com/maria-wimber), which aims to draw a time- and space-resolved map of memory reactivation in the human brain. The postdoc will have the rare opportunity to work with intracranial EEG recordings from the human hippocampus, including local field potential and single neuron data. The post should be interesting for researchers with a strong background in electrophysiology - EEG/MEG/iEEG, human or animal - and a general interest in long-term memory. More details about the position and an application link can be found here Research Fellow - 56716 Deadline for applications is August 16th 2017. Please distribute to potential candidates, who should feel free to contact the PI directly by email at m.wimber at bham.ac.uk. ---------------------- Dr Maria Wimber Senior Lecturer School of Psychology University of Birmingham tel +44 121 4144659 www.memorybham.com/maria-wimber -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Wed Jul 12 09:35:09 2017 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Wed, 12 Jul 2017 07:35:09 +0000 Subject: [FieldTrip] fieldtrip Digest, Vol 80, Issue 7 In-Reply-To: References: Message-ID: <184AAEB3-B2E5-4C2A-B23F-C46532EA7091@donders.ru.nl> Dear Elena, John and the rest, Allow me to chime in a bit here to bring across John’s answer even more clearly. Indeed ft_volumesegment applies some postprocessing to the tissue-probability-maps (TPMs) as extracted with SPM. This involves amongst others some smoothing and thresholding, which may indeed result in the output to not fit very snugly with the underlying anatomy. However, the amount of smoothing and threshold is in principle in your hands, so you can adjust the parameters to your need. Just have a look at the documentation of the function for how it can be adjusted. Note, also, that I have made some recent changes to ft_volumesegment to allow for SPM-options to be configureable, i.e. you can influence the behaviour of the SPM-based step of the procedure. It is hard to give an optimal set of parameters here as well, because these depend on the quality of the anatomical images (and probably on the spm version used). The default values that are used in ft_volumesegment have been taken from the defaults that SPM uses, but there is no strict reason why these are optimal for all MR images. Also, I’d like to advertise the fact that I have now implemented full support for using SPM12 for the segmentation, where there’s now the option to use 1) a 6-tissue type TPM-template (for this you need to specify cfg.spmversion = ‘spm12’, along with cfg.spmmethod=‘new’), and 2) you can even postprocess the segmentation with the spm add-on ‘mars’. This can be done when specifying cfg.spmmethod=‘mars’, in combination with cfg.spmversion=‘spm12’. For whatever it’s worth… Happy computing! Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands > On 09 Jul 2017, at 14:45, RICHARDS, JOHN wrote: > > Elena > > The ft_volumesegment uses the SPM program that does gm/wm segmentation into probability maps. In the case of using = {'brain', 'skull', 'scalp'}; as input, the program sums the PVE for GM, WM and "CSF" (other matter) to create the brain (+ fill holes and some other); then has a formula for finding the skull (dilate brain, or use bone class from segmented MRI), and scalp. > > So the "skullstrip" portion consists of the brain PVEs from the SPM segmentation program. If that program does not work correctly then the overlap of the brain mask will not match the actual brain--could either not cover all the brain or cover more than the brain. > > I have had some issues with the SPM algorithm, and its use in the ft_volumesegment is not very flexible. I do the segmentation outside of FT using FSL tools (e.g., bet, bet2, betsurf) and then import the segmented head into FT format; FSL also has an algorithm for "skull stripping" found in its VBM script. This way I have more control over the initial segmented products. Additionally, neither the SPM nor the FSL routines work with some pediatric populations, especially infants under 2 years of age. In that case I often substitute the initial MRI template (in FT case, as SPM, they use the MNI segmented head) with an infant MRI template and get much better results. (e.g., neurodevelopmental MRI database). At times I have used the SPM algorithms for brain segmenting (GM, WM, CSF) and in this case also the PVEs from an age-appropriate brain improve the results. > > John > > > *********************************************** > John E. Richards > Carolina Distinguished Professor > Department of Psychology > University of South Carolina > Columbia, SC 29208 > Dept Phone: 803 777 2079 > Fax: 803 777 9558 > Email: richards-john at sc.edu > HTTP: jerlab.psych.sc.edu > ************************************************* > > > -----Original Message----- > From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of fieldtrip-request at science.ru.nl > Sent: Sunday, July 9, 2017 6:00 AM > To: fieldtrip at science.ru.nl > Subject: fieldtrip Digest, Vol 80, Issue 7 > > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > https://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. brain segmentation problem (Elena Orekhova) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Sat, 8 Jul 2017 19:11:17 +0200 > From: Elena Orekhova > To: FieldTrip discussion list > Subject: [FieldTrip] brain segmentation problem > Message-ID: > > Content-Type: text/plain; charset="utf-8" > > Dear Fieldtrip experts, > > I noticed that ft_volumesegment sometimes produces inaccurate results, extending the brain mask outside the brain (see the attached figure). I used > > mri_orig= ft_read_mri ('T1.mgz'); > ... > cfg = []; > cfg.output = {'brain', 'skull', 'scalp'}; > mri_segmented = ft_volumesegment(cfg, mri_orig_realigned); > > Have anybody had such a problem. How can it be resolved? > > Elena > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > -------------- next part -------------- > A non-text attachment was scrubbed... > Name: fig1.png > Type: image/png > Size: 66721 bytes > Desc: not available > URL: > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 80, Issue 7 > **************************************** > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From nima.noury at student.uni-tuebingen.de Fri Jul 14 12:09:13 2017 From: nima.noury at student.uni-tuebingen.de (Nima Noury) Date: Fri, 14 Jul 2017 12:09:13 +0200 Subject: [FieldTrip] 2017 Tuebingen Systems Neuroscience Symposium (SNS), Oct 11-12 Message-ID: <20170714120913.Horde.hQkjKPaafdf1u-VgVFclO4N@webmail.uni-tuebingen.de> The Centre for Integrative Neuroscience and MEG Center Tuebingen are pleased to announce the 2017 Tuebingen Systems Neuroscience Symposium (SNS2017) The symposium takes place on October 11 and 12, 2017 at the University of Tuebingen. This annual international meeting brings together leading researchers in the field of systems neuroscience featuring plenary talks, poster sessions and social events. Join us in Tuebingen to learn about the latest advances in systems neuroscience. Confirmed speakers: Francesco Battaglia, Nijmegen Gustavo Deco, Barcelona Biyu He, New York Christoph Kayser, Glasgow Daniel Margulies, Leipzig Uta Noppeney, Birmingham Marios Philiastides, Glasgow Hansjörg Scherberger, Göttingen Woodrow Shew, Fayetteville Preejas Tewarie, Nottingham For more information and registration, please visit: http://meg.medizin.uni-tuebingen.de/2017/ Please forward this information to any of your colleagues and collaborators that may be interested in the symposium. Nima Noury AG Large-Scale Neuronal Interactions Centre for Integrative Neuroscience (CIN) University of Tübingen Otfried Müller-Straße 25 72076 Tübingen Germany From anne.urai at gmail.com Tue Jul 18 08:54:17 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 17 Jul 2017 23:54:17 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: Hi Tvetan, Thanks for your help. Dear Anne,>* The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? *this information was provided by the principle investigator of the paper. You might ask the corresponding author for further details on this. Best tzvetan I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI. Do you know by any chance which author provided the mat file, so I can work from the code they used? Best, — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai From: Anne Urai Reply: Anne Urai Date: 10 July 2017 at 10:38:59 To: fieldtrip at science.ru.nl Subject: vtpm atlas contains no right IPS5 Dear Fieldtrippers, I'm using the VTPM atlas to define masks for all the visual regions described in the paper (Wang et al. 2014, https://academic.oup.com/cercor/article-lookup/doi/10.1093/cercor/bhu277). However, there seem to be no entries corresponding to the left IPS5. *% load atlas* *atl = ft_read_atlas('~/Documents/fieldtrip/vtpm/vtpm.mat');* *atl = ft_convert_units(atl, 'cm');* *% add mni coordinates* *[ax, ay, az] = voxelcoords(atl.dim, atl.transform);* *atl.pos = [ax(:) ay(:) az(:)];* *% make a binary mask for this ROI* *roi_idx = find(strcmp(lower(atl.tissuelabel), 'IPS5'));* *roi_mask = ismember(atl.tissue, roi_idx);* *% mask the voxels on the right side of the brain* *rightidx = find(atl.pos(:, 1) > 0); * *roi_mask(rightidx) = 0;* Now, sum(roi_mask(:)) = 0. This procedure of separating out the left and right regions works fine for all other regions in the atlas, as well as the right IPS5. The description on http://www.fieldtriptoolbox.org/template/atlas says "The version of the atlas included with FieldTrip was created by transforming data into standardized space using surface-based anatomical registration approaches." Is there any information available on the exact code that was used to go from this original file http://scholar.princeton.edu/napl/resources to the mat-file in FieldTrip, so that I can check where in the process the left IPS5 gets lost? Thanks! — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai -------------- next part -------------- An HTML attachment was scrubbed... URL: From tzvetan.popov at uni-konstanz.de Tue Jul 18 09:28:28 2017 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Tue, 18 Jul 2017 09:28:28 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: Message-ID: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Dear Anne, > I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI > Do you know by any chance which author provided the mat file I have created the mat file working from the nifti files. I don’t have the code anymore but it wasn’t too difficult. Yet, this code wouldn’t help since the ROI isn’t in the nifti files to begin with. I had exchange RE: missing ROI with Michael Arcaro back then. Here is what he wrote: "As you said, ROI 23 does not appear to be in the volume lh map. It’s there in the surface max prob map for the lh. I know Liang generated a separate probability map using nonlinear volumetric alignment, which was a little bit worse in quality than the surface map. It’s possible you’re using that map. I thought we sent you the volume projection of the surface max probability map though. It’s possible that the small area of ROI3 in the surface max probability map did not survive the projection back into volume space (since there is interpolation in the projection). I’ll double check with Liang and Ryan and see if they remember any issues with ROI23. It might be better to use the individual probability map for ROI 23 and use a more liberal threshold." So it seems that Liang could indeed provide some more info on whether and how to use a more liberal threshold to get the ROI back into the volumetric representation? Best tzvetan -------------- next part -------------- An HTML attachment was scrubbed... URL: From anne.urai at gmail.com Tue Jul 18 10:12:26 2017 From: anne.urai at gmail.com (Anne Urai) Date: Tue, 18 Jul 2017 01:12:26 -0700 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> References: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Message-ID: Dear Liang, cc Tzvetan, FieldTrip See the conversation below - Tzvetan has indicated that the volumetric representation is already missing IPS5. It would be great to try and redo the projection into volume space and play with the threshold to make sure that all regions are at least assigned to one voxel. Best, — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai From: Tzvetan Popov Reply: FieldTrip discussion list Date: 18 July 2017 at 09:28:28 To: FieldTrip discussion list Subject: Re: [FieldTrip] vtpm atlas contains no right IPS5 Dear Anne, I've been in touch with Dr. Liang Wang (first author on the paper), but he could only point me to the original NIfTI files on the website which have been converted in AFNI Do you know by any chance which author provided the mat file I have created the mat file working from the nifti files. I don’t have the code anymore but it wasn’t too difficult. Yet, this code wouldn’t help since the ROI isn’t in the nifti files to begin with. I had exchange RE: missing ROI with Michael Arcaro back then. Here is what he wrote: "As you said, ROI 23 does not appear to be in the volume lh map. It’s there in the surface max prob map for the lh. I know Liang generated a separate probability map using nonlinear volumetric alignment, which was a little bit worse in quality than the surface map. It’s possible you’re using that map. I thought we sent you the volume projection of the surface max probability map though. It’s possible that the small area of ROI3 in the surface max probability map did not survive the projection back into volume space (since there is interpolation in the projection). I’ll double check with Liang and Ryan and see if they remember any issues with ROI23. It might be better to use the individual probability map for ROI 23 and use a more liberal threshold." So it seems that Liang could indeed provide some more info on whether and how to use a more liberal threshold to get the ROI back into the volumetric representation? Best tzvetan _______________________________________________ fieldtrip mailing list fieldtrip at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip -------------- next part -------------- An HTML attachment was scrubbed... URL: From zk578 at york.ac.uk Thu Jul 20 15:56:48 2017 From: zk578 at york.ac.uk (=?iso-8859-1?Q?Zdenko_Koh=FAt?=) Date: Thu, 20 Jul 2017 13:56:48 +0000 Subject: [FieldTrip] ERP classification Message-ID: Dear Fieldtrippers, I would like to classify ERP data in one condition based on an averaged group ERP signal from a different condition. To describe it more clearly, imagine that I have a condition1 in which I observe a significant P300, and a condition2 which shows no significant effect, although some of the participants clearly show the P300 in this condition as well. I would like to use the signal from the condition1 to classify the participants in the condition2 into P300 and no-P300 group. Is there some way to go about this issue ? Thank you ! :) Kind regards, Zdenko -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nina.Merkel at kgu.de Thu Jul 20 17:35:58 2017 From: Nina.Merkel at kgu.de (Merkel, Nina) Date: Thu, 20 Jul 2017 15:35:58 +0000 Subject: [FieldTrip] sig file Message-ID: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina -------------- next part -------------- An HTML attachment was scrubbed... URL: From N.vanKlink-2 at umcutrecht.nl Fri Jul 21 09:13:56 2017 From: N.vanKlink-2 at umcutrecht.nl (Klink-3, N.E.C. van) Date: Fri, 21 Jul 2017 07:13:56 +0000 Subject: [FieldTrip] sig file In-Reply-To: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> References: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Message-ID: Hi Nina, These .sig files are Stellate EEG files, but Stellate does no longer exist anymore, so software is no longer supported. This makes it difficult to work with these files sometimes. The easiest way would be to convert your .sig to EDF with Stellate Reviewer, if you have access to that software. You would select the whole file with the selector tool, and then File-> Export As... There also is a matlab toolbox for reading .sig into matlab, but it only works with 32-bits matlab on a Windows system. Hope this helps, Nicole Van: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Namens Merkel, Nina Verzonden: 20 jul 17 17:36 Aan: 'fieldtrip at science.ru.nl' Onderwerp: [FieldTrip] sig file Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina ------------------------------------------------------------------------------ De informatie opgenomen in dit bericht kan vertrouwelijk zijn en is uitsluitend bestemd voor de geadresseerde. Indien u dit bericht onterecht ontvangt, wordt u verzocht de inhoud niet te gebruiken en de afzender direct te informeren door het bericht te retourneren. Het Universitair Medisch Centrum Utrecht is een publiekrechtelijke rechtspersoon in de zin van de W.H.W. (Wet Hoger Onderwijs en Wetenschappelijk Onderzoek) en staat geregistreerd bij de Kamer van Koophandel voor Midden-Nederland onder nr. 30244197. Denk s.v.p aan het milieu voor u deze e-mail afdrukt. ------------------------------------------------------------------------------ This message may contain confidential information and is intended exclusively for the addressee. If you receive this message unintentionally, please do not use the contents but notify the sender immediately by return e-mail. University Medical Center Utrecht is a legal person by public law and is registered at the Chamber of Commerce for Midden-Nederland under no. 30244197. Please consider the environment before printing this e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mailtome.2113 at gmail.com Mon Jul 24 07:04:54 2017 From: mailtome.2113 at gmail.com (Arti Abhishek) Date: Mon, 24 Jul 2017 15:04:54 +1000 Subject: [FieldTrip] Appending datasets with different channel order Message-ID: Dear list, I am working with some infant ERP data and I perform trial by trial channel interpolation. The trials are then concatenated using ft_appenddata. Since the number of interpolated channels are different across trials, the channel order is different across trials. I was wondering what will happen to the channel order in the case of appending. Since there are channel labels for each trial, does the ft_appenddata function takes this into account and match data to the channel label? Thanks Arti -------------- next part -------------- An HTML attachment was scrubbed... URL: From Nina.Merkel at kgu.de Mon Jul 24 10:07:43 2017 From: Nina.Merkel at kgu.de (Merkel, Nina) Date: Mon, 24 Jul 2017 08:07:43 +0000 Subject: [FieldTrip] sig file In-Reply-To: References: <5A40C6B713E9B243B4EBD708AFA674A7590D18@EXMEPDAG4.intra.kgu.de> Message-ID: <5A40C6B713E9B243B4EBD708AFA674A7590D67@EXMEPDAG4.intra.kgu.de> Thank you Nicole! This was very helpful information! Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Klink-3, N.E.C. van Gesendet: Freitag, 21. Juli 2017 09:14 An: FieldTrip discussion list Betreff: Re: [FieldTrip] sig file Hi Nina, These .sig files are Stellate EEG files, but Stellate does no longer exist anymore, so software is no longer supported. This makes it difficult to work with these files sometimes. The easiest way would be to convert your .sig to EDF with Stellate Reviewer, if you have access to that software. You would select the whole file with the selector tool, and then File-> Export As... There also is a matlab toolbox for reading .sig into matlab, but it only works with 32-bits matlab on a Windows system. Hope this helps, Nicole Van: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Namens Merkel, Nina Verzonden: 20 jul 17 17:36 Aan: 'fieldtrip at science.ru.nl' Onderwerp: [FieldTrip] sig file Dear Fieldtrippers, Does anyone know how I can convert .sig files (from an EEG system) to a format, that matlab can handle (maybe edf?)? Any help would be appreciated. Thanks, Nina ________________________________ De informatie opgenomen in dit bericht kan vertrouwelijk zijn en is uitsluitend bestemd voor de geadresseerde. Indien u dit bericht onterecht ontvangt, wordt u verzocht de inhoud niet te gebruiken en de afzender direct te informeren door het bericht te retourneren. Het Universitair Medisch Centrum Utrecht is een publiekrechtelijke rechtspersoon in de zin van de W.H.W. (Wet Hoger Onderwijs en Wetenschappelijk Onderzoek) en staat geregistreerd bij de Kamer van Koophandel voor Midden-Nederland onder nr. 30244197. Denk s.v.p aan het milieu voor u deze e-mail afdrukt. ________________________________ This message may contain confidential information and is intended exclusively for the addressee. If you receive this message unintentionally, please do not use the contents but notify the sender immediately by return e-mail. University Medical Center Utrecht is a legal person by public law and is registered at the Chamber of Commerce for Midden-Nederland under no. 30244197. Please consider the environment before printing this e-mail. -------------- next part -------------- An HTML attachment was scrubbed... URL: From anne.urai at gmail.com Mon Jul 24 12:59:08 2017 From: anne.urai at gmail.com (Anne Urai) Date: Mon, 24 Jul 2017 12:59:08 +0200 Subject: [FieldTrip] vtpm atlas contains no right IPS5 In-Reply-To: References: <6B99F9F5-DD11-4251-8CCE-5440C7252F73@uni-konstanz.de> Message-ID: Hi Tzvetan, Fieldtrippers, see below the response I got from Liang Wang. *I double-check the original files of the maximum probabilistic atlas in the volume-based space. As you said, it did not include left IPS5 areas. In our paper, we had pointed out that there was a difference between volume- and surface-based atlas, because the registration used between two space was totally different. We think the surface-based atlas may be more accurate, compare to the volume-based atlas. If you need to get left IPS5, I suggest to use the probability map for that region that you also can download from the web. This map provides you a probability value for each voxel being to that region. * *Best,* *Liang* — Anne E. Urai, MSc PhD student | Institut für Neurophysiologie und Pathophysiologie Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | Hamburg, Germany www.anneurai.net / @AnneEUrai On 18 July 2017 at 10:12, Anne Urai wrote: > Dear Liang, > cc Tzvetan, FieldTrip > > See the conversation below - Tzvetan has indicated that the volumetric > representation is already missing IPS5. It would be great to try and redo > the projection into volume space and play with the threshold to make sure > that all regions are at least assigned to one voxel. > > Best, > > — > Anne E. Urai, MSc > PhD student | Institut für Neurophysiologie und Pathophysiologie > Universitätsklinikum Hamburg-Eppendorf | Martinistrasse 52, 20246 | > Hamburg, Germany > www.anneurai.net / @AnneEUrai > > From: Tzvetan Popov > > Reply: FieldTrip discussion list > > Date: 18 July 2017 at 09:28:28 > To: FieldTrip discussion list > > Subject: Re: [FieldTrip] vtpm atlas contains no right IPS5 > > Dear Anne, > > I've been in touch with Dr. Liang Wang (first author on the paper), but he > could only point me to the original NIfTI files on the website which have > been converted in AFNI > > Do you know by any chance which author provided the mat file > > I have created the mat file working from the nifti files. I don’t have the > code anymore but it wasn’t too difficult. Yet, this code wouldn’t help > since the ROI isn’t in the nifti files to begin with. I had exchange RE: > missing ROI with Michael Arcaro back then. Here is what he wrote: > > "As you said, ROI 23 does not appear to be in the volume lh map. > It’s there in the surface max prob map for the lh. I know Liang generated > a separate probability map using nonlinear volumetric alignment, which was > a little bit worse in quality than the surface map. It’s possible you’re > using that map. I thought we sent you the volume projection of the surface > max probability map though. It’s possible that the small area of ROI3 in > the surface max probability map did not survive the projection back into > volume space (since there is interpolation in the projection). I’ll double > check with Liang and Ryan and see if they remember any issues with ROI23. > It might be better to use the individual probability map for ROI 23 and use > a more liberal threshold." > > So it seems that Liang could indeed provide some more info on whether and > how to use a more liberal threshold to get the ROI back into the volumetric > representation? > > Best > tzvetan > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > -------------- next part -------------- An HTML attachment was scrubbed... URL: From Miguel.Granjaespiritosanto at nottingham.ac.uk Tue Jul 25 10:20:32 2017 From: Miguel.Granjaespiritosanto at nottingham.ac.uk (Miguel Granja Espirito Santo) Date: Tue, 25 Jul 2017 08:20:32 +0000 Subject: [FieldTrip] ft_topoplotER using highlight symbol size as proxy for length of significance of cluster. Message-ID: Hi all, I am trying to use the ft_topoplotER to show significant difference between conditions without having to do a large subplot of different times points. To do this I thought of adjusting the highlighting symbol size proportionally to the length of the duration of significance. This seem simple at first because I just had to plot the highlight for every channel one at time in a for loop and adjust the size accordingly and then use hold on. However, ft_topoplotER writes a new image through every iteration of the loop and therefore overwriting the previous highlight. Is there any way to get around this? Is there a way to enable hold on for ft_topoplotER? Best, Miguel PhD Student School of Psychology University of Nottingham This message and any attachment are intended solely for the addressee and may contain confidential information. If you have received this message in error, please send it back to me, and immediately delete it. Please do not use, copy or disclose the information contained in this message or in any attachment. Any views or opinions expressed by the author of this email do not necessarily reflect the views of the University of Nottingham. This message has been checked for viruses but the contents of an attachment may still contain software viruses which could damage your computer system, you are advised to perform your own checks. Email communications with the University of Nottingham may be monitored as permitted by UK legislation. -------------- next part -------------- An HTML attachment was scrubbed... URL: From smoratti at psi.ucm.es Wed Jul 26 17:11:32 2017 From: smoratti at psi.ucm.es (smoratti at psi.ucm.es) Date: Wed, 26 Jul 2017 17:11:32 +0200 Subject: [FieldTrip] 2-year post-doctoral position in human intracranial recordings in patients with schizophrenia Message-ID: <7AE53ED5-A06C-455B-993F-47DE9688A560@psi.ucm.es> On behalf of Bryan Strange a close collaborator of mine I send you this job offer: The Laboratory for Clinical Neuroscience in Madrid (www.thestrangelab.org ), in collaboration with the Neurosurgery and Psychiatry departments of the Clinico San Carlos, is pioneering the use of deep-brain stimulation in the management of medication-resistant schizophrenia. As part of this treatment, we perform electrophysiological recordings in patients to study the firing pattern of ventral midbrain (putatively dopaminergic) neurons. Secondly, we test patients in behavioural tasks such as working memory, in order to determine the cognitive effects of DBS treatment. The successful candidate will be involved in acquiring and analysing neurophysiological recordings from these patients: intra-operative single-unit recordings and post-operative intracranial local field potentials and scalp EEG. Funding is through the Behavior and Brain Research Foundation (https://www.bbrfoundation.org/blog/meet-our-2017-narsad-independent-investigator-grantees ) A PhD in neuroscience (or related discipline) is required. The ideal candidate will be highly competent in the analysis of electrophysiological recordings, particularly single-unit data. Knowledge of ventral tegmental single unit activity in animal models of schizophrenia is desirable. The start date will be in autumn/winter 2017. Fluent English is mandatory, Spanish is not required. Application: Send CV, motivation letter, and contact details of two academic referees to Prof. Bryan Strange bryan.strange at upm.es Deadline: 1 September 2017 -- Un cordial saludo, Stephan Moratti, PhD Profesor de Psicología Básica I Universidad Complutense de Madrid 91 394 3141 smoratti at ucm.es La información contenida en este correo es CONFIDENCIAL, de uso exclusivo del destinatario/a arriba mencionado. Si ha recibido este mensaje por error, notifíquelo inmediatamente por esta misma vía y proceda a su eliminación, ya que ud. tiene totalmente prohibida cualquier utilización del mismo, en virtud de la legislación vigente. Los datos personales recogidos serán incorporados y tratados en el fichero 'Correoweb', bajo la titularidad del Vicerrectorado de Tecnologías de la Información, y en él el interesado/a podrá ejercer los derechos de acceso, rectificación, cancelación y oposición ante el mismo (artículo 5 de la Ley Orgánica 15/1999, de 13 de diciembre, de Protección de Datos de Carácter Personal). Antes de imprimir este correo piense si es necesario: el medio ambiente es cosa de todos. This message is private and confidential and it is intended exclusively for the addressee. If you receive this message by mistake, you should not disseminate, distribute or copy this e-mail. Please inform the sender and delete the message and attachments from your system, as it is completely forbidden for you to use this information, according to the current legislation. No confidentiality nor any privilege regarding the information is waived or lost by any mistransmission or malfunction. The personal data herein will be collected in the file “Correoweb”, under the ownership of the Vice-Rectorate for Information Technologies, in which those interested may exercise their right to access, rectify, cancel or protest the contents (article 5 of Organic Law 15/1999 dated 13 December, on the Protection of Personal data). Before printing this mail please consider whether it is really necessary: the environment is a concern for us all. -------------- next part -------------- An HTML attachment was scrubbed... URL: From roycox.roycox at gmail.com Thu Jul 27 18:32:49 2017 From: roycox.roycox at gmail.com (Roy Cox) Date: Thu, 27 Jul 2017 12:32:49 -0400 Subject: [FieldTrip] postdoctoral opportunity Message-ID: Please see below for a postdoctoral opportunity in the lab of Dara Manoach at MGH/Harvard Medical School. Best, Roy ------------------------------------------------------------------------------------------------------------------------------- Postdoctoral Fellowship at the Martinos Center for Biomedical Imaging and the Psychiatric Neuroimaging Division of the Psychiatry Department at Massachusetts General Hospital, Charlestown, MA and Harvard Medical School *Position Description*: Clinical/Cognitive Neuroscience Research *Project*: Multimodal neuroimaging studies of sleep and memory *PI*: Dara S. Manoach, Ph.D. The position will involve investigating the role of sleep in memory consolidation, how these processes go awry in schizophrenia and autism, and the effects of pharmacological and other interventions. Our work has linked cognitive deficits to specific heritable mechanisms (sleep spindles and other sleep oscillations) and we are seeking effective interventions. In collaboration with Dr. Robert Stickgold’s lab at Beth Israel Deaconess Medical Center, we are extending and expanding this basic and clinical research program using state-of-the art tools including high density EEG, MEG, DTI, functional connectivity MRI, fMRI, and behavioral studies. We are seeking someone to participate in these foundation and NIMH-funded investigations who is familiar with cognitive neuroscience, neuroimaging methodology including MEG and/or EEG and data analysis, and is interested in developing research questions and optimizing analysis streams tailored to the study aims and populations. New approaches and ideas are encouraged, as are independent projects that dovetail with current studies. The position requires working closely with the PI, as well as with Dr. Stickgold, other Martinos Center investigators, particularly Dr. Matti Hamalainen, Director of the MEG Core Lab, and labmates to design studies, acquire data, and develop, explore, improve and apply data analytic techniques. Training in clinical research and in the acquisition, analysis, and interpretation of neuroimaging data will be provided. Requirements: PhD (or MD) in neuroscience, psychology, engineering or a related discipline and a strong research background are required. Ideal candidates would have extensive experience in data analysis, a background in computational neuroscience and/or signal processing, be proficient in Matlab/Python and be interested in methods development. The following are also beneficial: experience with MEG/EEG data analysis/methodology, background in cognitive neuroscience, experimental psychology and sleep; interest/experience with clinical populations; and experience in task design and analysis for cognitive experiments. Position available immediately. Interested applicants should email: (a) CV, (b) statement of post-doctoral and career goals, (c) writing sample (e.g., a published manuscript), and (d) letters and/or contact information for three references to Dara Manoach . Stipend levels are in line with experience and NIH. A two-year commitment is required. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Hisako.Fujiwara at cchmc.org Thu Jul 27 19:00:15 2017 From: Hisako.Fujiwara at cchmc.org (Fujiwara, Hisako) Date: Thu, 27 Jul 2017 17:00:15 +0000 Subject: [FieldTrip] how to segment continuous EEG data without triggers Message-ID: <64721b2dbaba463b9ea729893d08708d@cchmc.org> Dear experts, I have continuous EEG data in EDF format that does not include trigger channel. These EEG data was recorded as EEG-fMRI during a task (30-sec baseline and 30-sec active trial alternated 4 or 5 times depending on participants). I would like to segment out the active states 4 x 30-sec segments for each participants. Now, I have the separate marker files that have 2 sec TR trigger as a text (EV2) file. I can at least tell start and finish for each trial from the marker file. I have tired to use ft_definetrial and ft_redefinetri with function of cfg.toilim = [tmin tmax] but I am getting error message either: 1. undefined function or variable 'data' 2. Error using ft_notification (line 314) This function requires raw+comp or raw data as input. Error in ft_error (line 39) ft_notification(varargin{:}); Error in ft_checkdata (line 495) ft_error('This function requires %s data as input.', str); Error in ft_redefinetrial (line 117) data = ft_checkdata(data, 'datatype', {'raw+comp', 'raw'}, 'feedback', cfg.feedback); I tried to refer the http://www.fieldtriptoolbox.org/reference/ft_definetrial and also searched through the mailing archives but I have not found exact solution so fat. but I ma not really succeeding this. I am sure I am missing a lot of functions for that. Could you please kindly suggest any detailed explanation and solution for this? Thank you very much for your kind help in advance, Sincerely, Hisako -------------- next part -------------- An HTML attachment was scrubbed... URL: From a132467647 at gmail.com Sat Jul 29 10:47:22 2017 From: a132467647 at gmail.com (Jiun Wei Chen) Date: Sat, 29 Jul 2017 08:47:22 +0000 Subject: [FieldTrip] Having a error in installing Fieldtrip after installing SPM and brainstorm Message-ID: Dear Fieldtrip users: My name is Jiun-Wei Chen and I am working in Brain mapping lab in Taiwan on the brain science. I am analyzing data of MEG. I found the problem I can't properly installing Fieldtrip in my MATLAB. My versions of MATLAB are R2015b and R2016b. before installing Fieldtrip, I have installed SPM12 and brainstorm in my MATLAB. Then, I follow this website below to set path http://www.fieldtriptoolbox.org/faq/should_i_add_fieldtrip_with_all_subdirectories_to_my_matlab_path this is my instance below: >> addpath C:\Users\wei\Documents\MATLAB\Fieldtrip >> ft_defaults after I key in these commands, I get the error message below: Undefined function 'ft_platform_supports' for input arguments of type 'char'. Error in ft_defaults>checkMultipleToolbox (line 291) if ~ft_platform_supports('which-all') Error in ft_defaults (line 114) checkMultipleToolbox('FieldTrip', 'ft_defaults.m'); I also tried to install Fieldtrip only in my MATLAB and preprocess my data. (my data format is ".fif") but I got an error message again. Subscripted assignment between dissimilar structures. Error in mergeconfig>mergeconfig_helper (line 39) input(j) = mergeconfig_helper(input(j), default(j)); Error in mergeconfig>mergeconfig_helper (line 53) input.(fn) = mergeconfig_helper(input.(fn), default.(fn)); Error in mergeconfig>mergeconfig_helper (line 53) input.(fn) = mergeconfig_helper(input.(fn), default.(fn)); Error in mergeconfig (line 12) input = mergeconfig_helper(input, default); Error in ft_preamble_init (line 55) cfg = mergeconfig(cfg, rmfield(ft_default, 'preamble')); Error in ft_preamble (line 85) evalin('caller', full_cmd); Error in ft_preprocessing (line 182) ft_preamble init Error in ft_qualitycheck (line 212) data = ft_preprocessing(cfgpreproc); clear cfgpreproc; I upload my data in my google drive as it exceeds the critical file size of 1MB. Here is the link: https://drive.google.com/open?id=0B8Xo-QjG1y2TZjBnWjdpNjZXNlk the code I use are as follows: %% Quality check cfg = [];%configuration structure cfg.dataset = 'run1_sss.fif';%string with the filename ft_qualitycheck(cfg) I could preprocess this data by Fieldtrip code that exists in the external folder of SPM and brainstorm. but I got the warning message that altered me there is the same code in these folders. can someone tell me how to install Fieldtrip when brainstorm and SPM exist in the same time and how to avoid the warning message I mentioned above. Any help would be appreciated. Best, Jiun-Wei -------------- next part -------------- An HTML attachment was scrubbed... URL: From son.ta.dinh at tum.de Mon Jul 31 09:39:51 2017 From: son.ta.dinh at tum.de (Ta Dinh, Son) Date: Mon, 31 Jul 2017 07:39:51 +0000 Subject: [FieldTrip] Functional connectivity analysis with powcorr_ortho In-Reply-To: <0d81972648824a678682346413ec9456@tum.de> References: <0d81972648824a678682346413ec9456@tum.de> Message-ID: Hi Brian, In general I woulrd recommend that you comment or reply to posts in the FieldTrip list on the list instead of sending mails directly to people so that issues that are solved are visible to everybody. As to the issue at hand, I haven't heard from anybody and regretfully forgot to ask Mr. Schoffelen at the last conference I met him. My solution to this was to implement the algorithm by myself according to the description given in the paper by Hipp et al. I could offer to send you the code, it should be easy to integrate with a reasonable amount of Matlab skills. Naturally I will not be able to offer any guarantees that the code is correct, but the results look reasonable enough to me. Go to http://dropcanvas.com/1xfe7/1 for a plot of the grand average seed-based connectivity from the left somatosensory cortex (MNI = [- 40, - 30, 50]) to all other voxels within the Beta band for a group of 22 healthy subjects. The paradigm is 5 minutes eyes-closed resting-state. Best, Son Von: Brian Scally [RPG] [mailto:psbs at leeds.ac.uk] Gesendet: Donnerstag, 27. Juli 2017 15:54 An: Ta Dinh, Son > Betreff: Fieldtrip powcorr_ortho issue Dear Son Ta Dinh, Hope you are well. I came across a post you made on the Fieldtrip mailing list about the powcorr_ortho function for ft_connectivity analysis. I am essentially getting the same results - random connectivity patterns. I wondered if you had heard from anyone about this issue or managed to resolve it? All the best, Brian Scally PhD Student, School of Psychology, University of Leeds b.scally at leeds.ac.uk Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Ta Dinh, Son Gesendet: Donnerstag, 13. April 2017 14:58 An: fieldtrip at science.ru.nl Betreff: [FieldTrip] Functional connectivity analysis with powcorr_ortho Dear FieldTrip list, I am trying to do a functional connectivity analysis using the power envelope correlation introduced by Hipp et al. (Nat Neuroscience 2012) as implemented in the ft_connectivity_powcorr_ortho function. My data consists of 5 minutes of eyes-closed resting-state data and my schematic pipeline is as follows: 1. I use LCMV beamforming to source reconstruct my bandpassed and preprocessed data 2. Using the resulting spatial filter I get a projected time series for every voxel (virtual channel) 3. I do a frequency analysis on these time series 4. The results of this frequency analysis (the Fourier coefficients) are used for the connectivity analysis using powcorr_ortho To check the results of this analysis, I plotted the results of a seed-based connectivity analysis with a voxel in the left visual cortex (-20, -80, 20) as seed. In the alpha band, I expect to see a strong local connectivity pattern in the occipital region extending partially into the contralateral hemisphere, similar to what Siems et al. NeuroImage 2016 find. However, I get a basically random connectivity pattern. When using this pipeline with the debiased weighted phase lag index, I get exactly what I am expecting. I looked into the source code of the ft_connectivity_powcorr_ortho function and saw a few disconcerting comments (Fix-Me's and the like) and now I am wondering whether my pipeline is simply not suited to the connectivity analysis with powcorr_ortho as implemented in FieldTrip or if the function is simply not fully implemented yet. Has anyone used it successfully before? I use the following FieldTrip (pseudo-) code: %% LCMV source reconstruction cfg = []; cfg.method = 'lcmv'; cfg.keeptrials = 'yes'; cfg.elec = elec; cfg.grid = lf; % regular grid of 1 cm resolution cfg.headmodel = vol % standard_bem.mat cfg.lcmv.keepfilter = 'yes'; cfg.lcmv.lambda = '5%'; cfg.lcmv.projectnoise = 'yes'; source = ft_sourceanalysis(cfg, tlock_data); %% pseudo-code for the computation of the virtual channel time series virtChan_data = tlock_data; virtChan_data.label = [source.pos(:, 1), source.pos(:,2), source.pos(:,3)]; virtChan_data.trial = source.avg.filter * tlock_data.trial; %% frequency analysis of the virtual channels cfg = []; cfg.method = 'mtmfft'; cfg.output = 'fourier'; cfg.keeptrials = 'yes'; cfg.foi = 10; % alpha band cfg.taper = 'hanning' % I originally used 3 tapers but source code in ft_connectivity_powcorr_ortho implies that multitaper is not compatible virtFreq = ft_freqanalysis(cfg, virtChan_data); %% connectivity analysis cfg = []; cfg.method = 'powcorr_ortho'; conn = ft_connectivityanalysis(cfg,virtFreq); Any suggestions and/or comments would be immensely helpful! Thanks in advance. Best, Son Son Ta Dinh, M.Sc. PhD student in Human Pain Research Klinikum rechts der Isar Technische Universität München Munich, Germany Phone: +49 89 4140 7664 http://www.painlabmunich.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From nugenta at mail.nih.gov Fri Jul 21 05:08:45 2017 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Fri, 21 Jul 2017 03:08:45 -0000 Subject: [FieldTrip] 2nd MEG North America Meeting Message-ID: We are pleased to announce the 2nd MEG-North America meeting, to be held in Bethesda, Maryland November 8th and 9th, directly before the Society for Neuroscience Meeting. November 8th will consist of small workgroup meetings to discuss collaborative projects involving reproducibility, data sharing architecture, and consortium building. We are seeking community involvement for these committees! Please get involved, go to our website to find out how. Working groups will address reliability/reproducibility, data sharing, industry partnership, and facilitating best practices. The main meeting will be held on November 9th, with a scientific program, keynote speakers, and a poster session. Call for Abstracts opens today, and will Close September 8th. Speaking vs. poster assignments will be sent within two weeks. Please visit our website at https://megworkshop.nih.gov/MEGWorkshop/ Or register at: https://www.eventbrite.com/e/meg-north-america-2017-tickets-36315511673 We hope to see you there! Conference Chairs: Richard Coppola Allison Nugent Steering Committee: Sylvain Baillet Dimitrios Pantazis Timothy Roberts Julia Stephen -------------- next part -------------- An HTML attachment was scrubbed... URL: From rhancock at email.arizona.edu Thu Jul 27 05:17:39 2017 From: rhancock at email.arizona.edu (Roeland Hancock) Date: Wed, 26 Jul 2017 23:17:39 -0400 Subject: [FieldTrip] Job: Technical Director of the Brain Imaging Research Center Message-ID: *University of Connecticut* *Technical Director of the Brain Imaging Research Center * *Research Assistant III/Research Associate I* The University of Connecticut invites applications for a full-time position of Technical Director of UConn’s Brain Imaging Research Center (BIRC). The Technical Director is responsible for the development and maintenance of the BIRC’s technology infrastructure, and will contribute to day-to-day operations. Rank and salary will be commensurate with degree and experience. The BIRC’s focus is on cognitive neuroscience research using functional MRI. *To Apply: *Interested applicants should view the full ad and application instructions at www.jobs.uconn.edu. Please send inquiries to Inge-Marie Eigsti, Ph.D., Chair of Search #2017355, Department of Psychological Sciences, U-1020, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269-1020; BIRC at UConn.edu. Applications are preferred by August 15, 2017, but the position will remain open until filled. The University of Connecticut is an EEO/AA employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: From rhancock at email.arizona.edu Thu Jul 27 05:17:39 2017 From: rhancock at email.arizona.edu (Roeland Hancock) Date: Thu, 27 Jul 2017 03:17:39 +0000 Subject: [FieldTrip] Job: Technical Director of the Brain Imaging Research Center Message-ID: <52c10f2f79ff40c1be85c9a9eaf2fe9c@EXPRD98.hosting.ru.nl> University of Connecticut Technical Director of the Brain Imaging Research Center Research Assistant III/Research Associate I The University of Connecticut invites applications for a full-time position of Technical Director of UConn’s Brain Imaging Research Center (BIRC). The Technical Director is responsible for the development and maintenance of the BIRC’s technology infrastructure, and will contribute to day-to-day operations. Rank and salary will be commensurate with degree and experience. The BIRC’s focus is on cognitive neuroscience research using functional MRI. To Apply: Interested applicants should view the full ad and application instructions at www.jobs.uconn.edu. Please send inquiries to Inge-Marie Eigsti, Ph.D., Chair of Search #2017355, Department of Psychological Sciences, U-1020, 406 Babbidge Road, University of Connecticut, Storrs, CT 06269-1020; BIRC at UConn.edu. Applications are preferred by August 15, 2017, but the position will remain open until filled. The University of Connecticut is an EEO/AA employer. -------------- next part -------------- An HTML attachment was scrubbed... URL: