From mikexcohen at gmail.com Thu Sep 1 13:38:12 2016 From: mikexcohen at gmail.com (Mike X Cohen) Date: Thu, 1 Sep 2016 13:38:12 +0200 Subject: [FieldTrip] Biomag 2016 Data Analysis Competition Message-ID: Dear all, We are happy to announce a deadline extension (to September 20th) for three data-analysis competitions at Biomag 2016. Please see details at http://www.biomag2016.org/data_analysis_competition.php The aim of the competitions is to promote the development and application of new analysis techniques. The challenges will help to elucidate pros and cons of different techniques and attract experts from outside the MEG field. The winners of the competition will be given the opportunity to present their proposal at the Biomag meeting in Seoul (Oct 1-6) in order to spark discussions on analysis. Please encourage colleagues to participate! Best regards, Ole Jensen (sent by Mike Cohen, and on behalf of all competition organizers) -- Mike X Cohen, PhD mikexcohen.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From mikexcohen at gmail.com Thu Sep 1 13:58:36 2016 From: mikexcohen at gmail.com (Mike X Cohen) Date: Thu, 1 Sep 2016 13:58:36 +0200 Subject: [FieldTrip] Conference announcement: ICON XIII Message-ID: We are happy to make the second announcement for the ICON XIII conference, which will take place on 5-8 August 2017 in Amsterdam (the Netherlands). Amsterdam is an easily-accessible and progressive city. ICON will take place at the Beurs van Berlage, located in downtown Amsterdam and one of the most beautiful conference venues in Europe! Visit the website: http://www.icon2017.org ICON stands for International Conference for Cognitive Neuroscience. ICON has taken place every 2-3 years since 1980. This conference brings together researchers from diverse backgrounds, joined by their interest in studying the relationships amongst brain, mind, and behavior. ICON conferences are always a big success, and 2017 in Amsterdam will follow this same tradition! Symposia and poster submissions will be open from early 2017, with deadlines of 1 February for symposia and 31 March for posters. Plan your research accordingly! NEW SYMPOSIA OPTIONS In addition to standard-format symposia, ICON2017 will feature two novel formats (see "What" and "Submit" links on icon2017.org for more details): 1) "Hackathons" are computer-based sessions that can involve either a group of people working towards solving a problem, or can be more tutorial-like with the goal of teaching hands-on skills (e.g., using a toolbox or implementing an analysis in Matlab) that can be accomplished in ~2 hours (for longer workshops, consider organizing a satellite). 2) "Ask-the-experts" is a panel of experts in a topic. No specific lectures are prepared; instead there is an open Q&A/discussion session. The focus can be on a theoretical issue, methodological issue, or hotly-debated topic in cognitive neuroscience. PRE-CONFERENCE WORKSHOPS/SATELLITES We welcome pre-conference satellites, and will be happy to advertise them on the ICON website. Note that satellites are independent from ICON in terms of organization, registration, and costs. If you have any questions or would like to discuss ideas for your satellite, please contact Mike Cohen (mikexcohen at gmail.com) and Birte Forstmann (buforstmann at gmail.com). FOLLOW US ON TWITTER For up-to-date announcements before and during the ICON meeting, follow @icon2017 (see also "Media" tab on the website). http://www.icon2017.org We look forward to seeing you in beautiful Amsterdam! Mike X Cohen and Birte Forstmann -- Mike X Cohen, PhD mikexcohen.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From niels.focke at uni-tuebingen.de Thu Sep 1 16:30:49 2016 From: niels.focke at uni-tuebingen.de (Niels Focke) Date: Thu, 1 Sep 2016 16:30:49 +0200 Subject: [FieldTrip] =?iso-8859-1?q?PhD_/_Research_Fellow_Position_in_Epil?= =?iso-8859-1?q?epsy_Imaging_=28MEG_/_hd-EEG=29_in_T=FCbingen/Germa?= =?iso-8859-1?q?ny?= Message-ID: <016601d2045d$6f6dc460$4e494d20$@uni-tuebingen.de> We are happy to announce a job opening: 1 PhD Student / Research Fellow (Wissenschaftlicher Mitarbeiter, 50%) for the AG Translational Neuroimaging, Neurological Clinic and Hertie Institute for Clinical Brain Research for a DFG-funded 3-years project. The successful applicant will work primarily on functional connectivity in MEG and hd-EEG in patients with genetic epilepsy. This involves graph-theoretical concepts and machine learning approaches. The aim of this project is to link the genetic causes of epilepsy with imaging patterns and improve our understanding of the pathophysiology and genotype-phenotype relations in general. The aim of this project is to link the genetic causes of epilepsy with imaging patterns and improve our understanding of the pathophysiology and genotype-phenotype relations in general. Applicants need a university degree (MA or equivalent) in physics, mathematics, biology, biomedical engineering, medicine or other related disciplines. Programming skills (Matlab) are essential as is previous knowledge of MEG or EEG and common imaging toolboxes (e.g. Fieldtrip, Brainstorm, SPM, FSL). Publications on network analysis/graph theory are beneficial for a successful application, as is previous experience with epilepsy. Since the study involves interaction with patients, German language skills are advantageous. The applicant has to be fluent in English, both written and oral. The focus of our group is the utilization of imaging and post-processing methods to better understand the neurobiology of focal and generalized epilepsies, allow individualized diagnostics and translate methodological advances into clinical applications. The applicant will have access to a unique setting including high-density MR-compatible 256-channel EEG, 3T- and 9.4T-MRI scanners, human and fetal MEG and hybrid human PET-MR facilities. The medical university clinics runs a comprehensive epilepsy surgery program including invasive EEG recordings. The applicant can be enrolled into the neuroscience PhD program including various teaching courses and further benefits (http://www.neuroschool-tuebingen.de/). The salary is according to German federal scale (TV-L, E13 50%). The initial contract is for one year. After successful interim evaluation (PhD advisory board), a prolongation for further two years is available. The university is especially encouraging the application of women. Disabled applicant are preferred in case of equal qualification. The intended start date is November 2016 with some flexibility. Please send a letter of motivation, CV, references and, if available, a sample publication to: Universitätsklinikum Tübingen Abteilung Neurologie mit Schwerpunkt Epileptologie PD Dr. Niels Focke Hoppe-Seyler-Str. 3 76076 Tübingen Germany or via E-Mail: niels.focke at uni-tuebingen.de __________________________________________________________________________ PD Dr. Niels Focke Oberarzt Abt. Neurologie mit Schwerpunkt Epileptologie Universitätsklinikum Tübingen AG Translationale Bildgebung Hertie Institut für Klinische Hirnforschung Werner Reichhardt Centre for Integrative Neuroscience -------------- next part -------------- A non-text attachment was scrubbed... Name: PhD_offer_genetic_epilepsy_imaging.pdf Type: application/pdf Size: 251282 bytes Desc: not available URL: From aborna at sandia.gov Fri Sep 2 01:10:03 2016 From: aborna at sandia.gov (Borna, Amir) Date: Thu, 1 Sep 2016 23:10:03 +0000 Subject: [FieldTrip] Importing arbitrary dataset using ft_definetrial Message-ID: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Sep 2 09:05:16 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 2 Sep 2016 07:05:16 +0000 Subject: [FieldTrip] Importing arbitrary dataset using ft_definetrial In-Reply-To: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> References: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> Message-ID: <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> Hi Amir, It should be possible to bypass ft_definetrial when calling ft_artifact_jump. One needs to supply a second input argument, i.e. ft_artifact_jump(cfg, data); As long as the cfg does not point to a dataset (i.e. does not have cfg.datafile/dataset etc.) it should work, as far as I know. Best, Jan-Mathijs On 02 Sep 2016, at 01:10, Borna, Amir > wrote: Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. _______________________________________________ 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 aborna at sandia.gov Fri Sep 2 17:59:38 2016 From: aborna at sandia.gov (Borna, Amir) Date: Fri, 2 Sep 2016 15:59:38 +0000 Subject: [FieldTrip] [EXTERNAL] Re: Importing arbitrary dataset using ft_definetrial In-Reply-To: <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> References: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> Message-ID: Hi Jan-Mathijs, Thank you for your suggestion. I haven't tried your solution yet as my question is not specific to any function; it looks like many of the ft functions require the configuration (cfg) argument which is created only by calling ft_definetial. So is there a way to call ft_definetial on a custom dataset? Thank you. Best, Amir Borna. Sandia National Lab. From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Schoffelen, J.M. (Jan Mathijs) Sent: Friday, September 02, 2016 1:05 AM To: FieldTrip discussion list Subject: [EXTERNAL] Re: [FieldTrip] Importing arbitrary dataset using ft_definetrial Hi Amir, It should be possible to bypass ft_definetrial when calling ft_artifact_jump. One needs to supply a second input argument, i.e. ft_artifact_jump(cfg, data); As long as the cfg does not point to a dataset (i.e. does not have cfg.datafile/dataset etc.) it should work, as far as I know. Best, Jan-Mathijs On 02 Sep 2016, at 01:10, Borna, Amir > wrote: Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. _______________________________________________ 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 belahian at memphis.edu Fri Sep 2 21:45:44 2016 From: belahian at memphis.edu (Bahareh Elahian (belahian)) Date: Fri, 2 Sep 2016 19:45:44 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: Message-ID: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis - FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_freqanalysis". FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis - FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_freqanalysis". FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Sun Sep 4 09:25:27 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sun, 4 Sep 2016 07:25:27 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: Message-ID: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 rb643 at medschl.cam.ac.uk Sun Sep 4 18:20:17 2016 From: rb643 at medschl.cam.ac.uk (Richard Bethlehem) Date: Sun, 4 Sep 2016 16:20:17 +0000 Subject: [FieldTrip] multi-taper smoothing and frequency of interest Message-ID: <3188FAB8621D294696F13E80A7BBC97E010A621686@me-mbx4.medschl.cam.ac.uk> Dear field trippers, Would anyone be able to offer some advice on smoothing settings used for the MTMFFT method when I want to isolate lower frequencies as well as some guidance on setting the frequency of interest. What I eventually want is just the power and crosspectra for a frequency band. So, for example I am currently looking at the delta range (2-4Hz) and then it would seem a bit odd to use a smoothing kernel of 2Hz as it would provide very frequency specific information for that range right? In addition, I initially just set the foilim to [2 4], but this gives me 2 datapoints that I assume just refer to the information at 2Hz and 4Hz? Thus, instead I changed it to setting the foi as a logspaced set of frequencies within the delta range. However when I run that I still only get 9 datapoints/dimensions for the frequency. Can anyone explain why it would default to 9 or what the correct settings would be to simply get the power and crosspectra for a specific frequency band (at the moment I am simply averaging over the frequency range later on anyway)? Cheers, Richard ps: This is the code I am using: cfg_freq = []; cfg_freq.method = 'mtmfft'; cfg_freq.output = 'powandcsd'; cfg_freq.channel = 1:64; cfg_freq.keeptrials ='yes'; %do not return an average of all trials for subsequent wpli analysis cfg_freq.taper = 'dpss'; %delta cfg_freq.tapsmofrq = 0.25; cfg_freq.foi = exp(linspace(log(2),log(4),20)); [freq_data.delta] = ft_freqanalysis(cfg_freq, data_iccleaned); And this is what I used to get some adjacency matrices for subsequent network analyses: cfg_conn = []; cfg_conn.method = 'wpli'; conn.delta = ft_connectivityanalysis(cfg_conn, freq_data.delta); conn.delta = ft_checkdata(conn.delta, 'cmbrepresentation', 'full','datatype','freq'); network_delta = squeeze(nanmean(conn.delta.wplispctrm,3)); This is resting-state EEG data that has already been pre-processed and I've segmented the continuous recording into 4-second segment to create 'trials' as I want to follow up this analysis with WPLI connectivity analysis and hence I need multiple trials (correct me if I'm wrong on that as well please, but that is probably a different thread altogether). From r.oostenveld at donders.ru.nl Mon Sep 5 09:00:39 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Mon, 5 Sep 2016 09:00:39 +0200 Subject: [FieldTrip] response requested - please check the FieldTrip website Message-ID: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> Dear FieldTrip users I just got word from someone who received a warning when opening the FieldTrip website. See below, it appears blacklisted by his (institutional) security software. I checked: for me it looks fine. I also don’t see anything unusual on the server itself, but a website hack is sometimes hard to detect. Could you please check the website on unusual or suspicious behaviour? But don’t click on anything if you see something unexpected! Please let me know in a PERSONAL REPLY to this email whether it works or not. Please do NOT REPLY to all people on the list, as the others on the list won’t be able to fix it anyway and will probably be annoyed by all those email messages. Thanks, Robert -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.jpeg Type: image/jpeg Size: 31648 bytes Desc: not available URL: From r.oostenveld at donders.ru.nl Mon Sep 5 11:49:30 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Mon, 5 Sep 2016 11:49:30 +0200 Subject: [FieldTrip] response requested - please check the FieldTrip website In-Reply-To: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> References: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> Message-ID: Dear all Thanks for all of your replies from all over the world! It appears that the warning/error message is specific for the lab where it was initially reported, which happens to be a centre here in Nijmegen on the other side of the campus. I’ll discuss in more detail with them what might be causing it. So right now I don’t see a reason to be concerned about the website itself. cheers Robert > On 05 Sep 2016, at 09:00, Robert Oostenveld wrote: > > Dear FieldTrip users > > I just got word from someone who received a warning when opening the FieldTrip website. See below, it appears blacklisted by his (institutional) security software. I checked: for me it looks fine. I also don’t see anything unusual on the server itself, but a website hack is sometimes hard to detect. > > Could you please check the website on unusual or suspicious behaviour? But don’t click on anything if you see something unexpected! > > Please let me know in a PERSONAL REPLY to this email whether it works or not. Please do NOT REPLY to all people on the list, as the others on the list won’t be able to fix it anyway and will probably be annoyed by all those email messages. > > Thanks, > Robert > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From belahian at memphis.edu Mon Sep 5 18:59:57 2016 From: belahian at memphis.edu (Bahareh Elahian (belahian)) Date: Mon, 5 Sep 2016 16:59:57 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> References: , <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Message-ID: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 pgoodin at swin.edu.au Tue Sep 6 00:28:34 2016 From: pgoodin at swin.edu.au (Peter Goodin) Date: Mon, 5 Sep 2016 22:28:34 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot Message-ID: Hi Bahar, There's no problem. The matrix returned is simply a channel x frequency x time matrix. Hope that helps, Peter. On 6 Sep 2016 3:24 AM, "Bahareh Elahian (belahian)" wrote: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 Tue Sep 6 08:51:24 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 6 Sep 2016 06:51:24 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Message-ID: <0B7BC124-9612-4684-A746-7F52CE75F1B7@donders.ru.nl> Hi Bahar, May I add to Peter’s reply that you should specify 4000, rather than 4 as resamplefs. JM On 05 Sep 2016, at 18:59, Bahareh Elahian (belahian) > wrote: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl > on behalf of Schoffelen, J.M. (Jan Mathijs) > Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 stefan.debener at uni-oldenburg.de Tue Sep 6 15:52:14 2016 From: stefan.debener at uni-oldenburg.de (Stefan Debener) Date: Tue, 6 Sep 2016 15:52:14 +0200 Subject: [FieldTrip] LSL Workshop in Germany Message-ID: <57CECA0E.6040500@uni-oldenburg.de> Dear all, The 1st International Lab Streaming Layer workshop will take place in Delmenhorst, Germany, on 19-20 December, 2016. LSL is a (phantastic) software project for time-synchronized streaming of multimodal data (https://github.com/sccn/labstreaminglayer). For preliminary program and registration details, please visit: http://www.h-w-k.de/index.php?id=2224 Best wishes, Stefan Debener & Martin Bleichner From ignasisols at gmail.com Tue Sep 6 22:01:14 2016 From: ignasisols at gmail.com (Ignasi Sols Balcells) Date: Tue, 6 Sep 2016 16:01:14 -0400 Subject: [FieldTrip] fieldtrip Functions that have the same name as MATLAB built in scripts - conflict. Message-ID: Hi all, I am using the last fieldtrip version and Matlab 2015b (Mac). When I start Matlab I get this warnings: *"Warning: Function iscolumn has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function ismatrix has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function isrow has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function isequaln has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.* *Warning: Function isstring has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict".* Did this happen to other users? I think that renaming the scripts, as suggested by Matlab, is not the best idea because many other fieldtrip scripts that call this affected scripts should be changed manually... Thanks, Ignasi -------------- next part -------------- An HTML attachment was scrubbed... URL: From ekenaykut at gmail.com Tue Sep 6 22:07:15 2016 From: ekenaykut at gmail.com (Aykut Eken) Date: Tue, 6 Sep 2016 23:07:15 +0300 Subject: [FieldTrip] fieldtrip Functions that have the same name as MATLAB built in scripts - conflict. In-Reply-To: References: Message-ID: Hi Ignasi, This happened to me when I changed the version of MATLAB. However, I continued to use Fieldtrip without any problems. If any error occurs during code running, you can change the built in function with the fieldtrip function that has the same name. Best Aykut > On 06 Sep 2016, at 23:01, Ignasi Sols Balcells wrote: > > Hi all, > > I am using the last fieldtrip version and Matlab 2015b (Mac). > When I start Matlab I get this warnings: > > "Warning: Function iscolumn has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function ismatrix has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isrow has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isequaln has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isstring has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict". > > Did this happen to other users? I think that renaming the scripts, as suggested by Matlab, is not the best idea because many other fieldtrip scripts that call this affected scripts should be changed manually... > > Thanks, > > Ignasi > _______________________________________________ > 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 giovannipellegrino at gmail.com Thu Sep 8 18:40:52 2016 From: giovannipellegrino at gmail.com (Giovanni Pellegrino) Date: Thu, 8 Sep 2016 18:40:52 +0200 Subject: [FieldTrip] Fwd: Postdoc positions @ Campus Bio-Medico University, Rome, Italy In-Reply-To: References: Message-ID: - Apologies for cross-postings - In the context of the European Research Council Grant “RESHAPE: REstoring the Self with embodiable HAnd ProsthesEs”, we are seeking two outstanding *Post-Doc scientists* to join us in developing new tools and methods to improve the embodiment of robotic hand prostheses and study the related brain processes. Activities will be carried out in a multidisciplinary research environment (Clinical Neurophysiology and Neuroengineering) @ Campus Bio-Medico University, Rome Italy (www.unicampus.it). Post-Doc ideal candidates should · - have relevant publications in international journals and experience in fund raising · - be English mother tongue or have almost comparable fluency · - *own at least two of the following expertise*: 1. Programming for development/customization of interactive Virtual/Augmented Reality environment 2. EEG/MRI signal processing 3. Body ownership, embodiment, cognitive neuroscience. Suitable candidates can introduce themselves by contacting Giovanni Di Pino (g.dipino at unicampus.it) and Domenico Formica(d.formica at unicampus.it). -- Giovanni Pellegrino, MD -------------- next part -------------- An HTML attachment was scrubbed... URL: From seymourr at aston.ac.uk Thu Sep 8 19:11:00 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Thu, 8 Sep 2016 17:11:00 +0000 Subject: [FieldTrip] Elekta Head Position Information --> FT Message-ID: Hi all, Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. Many thanks, Robert Seymour (PhD Student, Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From alexandre.gramfort at telecom-paristech.fr Thu Sep 8 21:50:22 2016 From: alexandre.gramfort at telecom-paristech.fr (Alexandre Gramfort) Date: Thu, 8 Sep 2016 21:50:22 +0200 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: References: Message-ID: hi Robert, unfortunately correcting for head movements is more difficult that using a linear regression (like done with fMRI). I doubt you can avoid a proper head movement correction using the physics of the sensors etc. You can use MNE open implementation of maxfilter prior to using fieldtrip if you want http://martinos.org/mne/dev/manual/preprocessing/maxwell.html http://martinos.org/mne/dev/generated/mne.preprocessing.maxwell_filter.html http://martinos.org/mne/dev/generated/commands.html#mne-maxfilter Hope this helps Alex On Thu, Sep 8, 2016 at 7:11 PM, Seymour, Robert (Research Student) wrote: > Hi all, > > > Just wondering whether anyone using an Elekta MEG system has managed to > import the head position estimation logs generated by Maxfilter into > Fieldtrip via the ft_preprocessing command? There must be a way of tricking > the function into accepting the data as an extra channel... My thinking is > that it should ultimately be possible to use ft_regressconfound to address > head movement right issues before ft_sourcestatistics without having to use > Maxfilter's native head position correction. > > > Many thanks, > > > Robert Seymour (PhD Student, Aston Brain Centre) > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail. > From a.stolk8 at gmail.com Fri Sep 9 01:12:26 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Thu, 8 Sep 2016 16:12:26 -0700 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: References: Message-ID: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> Hi Robert, Hopefully the following page is still accurate: http://www.fieldtriptoolbox.org/faq/how_can_i_visualize_the_neuromag_head_position_indicator_coils And more generally: http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis Hope that gets you started, Arjen > On Sep 8, 2016, at 10:11 AM, Seymour, Robert (Research Student) wrote: > > Hi all, > > > Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. > > > Many thanks, > > > Robert Seymour (PhD Student, Aston Brain Centre) > > _______________________________________________ > 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 a.stolk8 at gmail.com Fri Sep 9 01:21:54 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Thu, 8 Sep 2016 16:21:54 -0700 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> References: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> Message-ID: <4296702C-8916-4639-AD69-ADDFFF5BAFC0@gmail.com> Actually, while looking at it again, it doesnt provide the elekta headpositions, but creates position traces through dipolefitting. It's been a while but I recall this procedure wasn't that straightforward, producing shaky results. Perhaps someone in the list can point you in the right direction in terms of how to read in the elekta headpositions using ft_preproc. > On Sep 8, 2016, at 4:12 PM, Arjen Stolk wrote: > > Hi Robert, > > Hopefully the following page is still accurate: > http://www.fieldtriptoolbox.org/faq/how_can_i_visualize_the_neuromag_head_position_indicator_coils > > And more generally: > http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis > > Hope that gets you started, > Arjen > >> On Sep 8, 2016, at 10:11 AM, Seymour, Robert (Research Student) wrote: >> >> Hi all, >> >> >> Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. >> >> >> Many thanks, >> >> >> Robert Seymour (PhD Student, Aston Brain Centre) >> >> _______________________________________________ >> 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 virginie.van.wassenhove at gmail.com Fri Sep 9 11:54:43 2016 From: virginie.van.wassenhove at gmail.com (Virginie van Wassenhove) Date: Fri, 9 Sep 2016 11:54:43 +0200 Subject: [FieldTrip] [postdoc position] Message-ID: Dear colleagues, I would be grateful if you could pass on the following open position. Applications are invited for a postdoc position in the team of Dr Franck Ramus (LSCP, Department of Cognitive Studies, Ecole Normale Supérieure, Paris, France) on the study of auditory processing in developmental dyslexia using magnetoencephalography (MEG). Specific information about the position here: http://www.lscp.net/persons/ramus/docs/Postdoc_position.pdf Specific information about the project here: http://www.lscp.net/persons/ramus/docs/MEG_project_2016.pdf Best wishes, Virginie -- Virginie van Wassenhove CEA/NeuroSpin MEG - UNICOG Bat 145 PC 156 F-91191 Gif s/ Yvette FRANCE office: +33(0)1 69 08 1667 cell: +33(0)6 15 83 4955 skype, twitter: virginie_vw sites.google.com/site/virginievanwassenhove/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Fri Sep 9 20:45:01 2016 From: mklados at gmail.com (Manousos Klados) Date: Fri, 9 Sep 2016 20:45:01 +0200 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados [image: photo] *Manousos Klados, MSc, PhD* Postdoctoral Researcher, Max Planck Institute for Human Cognitive & Brain Sciences, +49(0)-341-9940-2507 | +49(0)-176-6988-1781 | http://www.mklados.com | Skype: mklados | Stephanstraße 1a PC D-04103 Leipzig Germany ------------------------------ *Call for Papers (Frontiers):*Applied Neuroscience: Methodology, Modeling, Theory, Applications and Reviews *Online Webinar in Brain Networks (hands on) - Live: 10-06-16 at 11:00 AM EEST (reserve your seat now )* ------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From zhangk28 at mcmaster.ca Fri Sep 9 20:53:26 2016 From: zhangk28 at mcmaster.ca (KAIJIE ZHANG) Date: Fri, 9 Sep 2016 18:53:26 +0000 Subject: [FieldTrip] Mailing List Message-ID: Hi, Can I be removed from the field trip mailing list please? I have e-mailed unsubscribe already, but I am still receiving e-mails. Best Regards, Kaijie -- Kaijie Zhang Electrical & Biomedical Engineering, Level IV McMaster University -------------- next part -------------- An HTML attachment was scrubbed... URL: From matt.euler at psych.utah.edu Fri Sep 9 21:16:39 2016 From: matt.euler at psych.utah.edu (Matt Euler) Date: Fri, 9 Sep 2016 19:16:39 +0000 Subject: [FieldTrip] tenure-track position in Applied Cognitive Neuroscience at the University of Utah Message-ID: <8063208343AC35429BADDD1D51C326E270EE1D17@X-MB12.xds.umail.utah.edu> Dear all, The University of Utah Psychology department is currently seeking applications for a tenure-track faculty position in Applied Cognitive Neuroscience at the assistant professor level. Apologies for cross-postings: Cognitive Neuroscience at the University of Utah. The Department of Psychology at the University of Utah invites applications for a tenure-track faculty position in Applied Cognitive Neuroscience at the assistant professor level. This position is part of a new multi-disciplinary strategic cluster of hires across the School of Medicine, Bioengineering, and Psychology, in the area of Neural Basis of Behavior, Learning, and Memory, with opportunities to participate in the University of Utah's Neuroscience Initiative, www.neurogateway.utah.edu. We welcome applications from any area of cognitive psychology (including but not limited to: memory, executive functioning, attention, perception, decision-making, and reasoning) with a strong theory-based research program that employs neuroscientific methods. We especially welcome applicants who conduct research in both the laboratory and applied settings and who can speak to the real-world impact of the processes they study. Applicants should have the ability and interest to teach undergraduate and graduate courses in cognitive neuroscience. In addition to a doctoral program in cognition and neural science, the University of Utah has an interdepartmental neuroscience graduate program http://neuroscience.med.utah.edu. Ideal candidates could mentor students in both programs. Candidates should have an excellent and sustained record of research and evidence of the potential or demonstrated ability to generate extramural funding, commensurate with their career stage. The Department of Psychology values interdisciplinary approaches to research and training, and strongly encourages collaboration across four traditional programs (Developmental, Clinical, Cognition and Neural Sciences, and Social). The department promotes multidisciplinary collaboration outside of the Department of Psychology with active ties to the Consortium for Families and Health Research, University of Utah Neuroscience Initiative, the School of Computing, Civil and Environmental Engineering, Bioengineering, the Business School, the College of Education, Pediatrics, Anesthesiology, Neurology, Psychiatry, Radiology, the Huntsman Cancer Institute, and the Salt Lake Veterans Administration Medical Center. The Department of Psychology is committed to the goal of promoting diversity in academia and welcomes candidates whose interests and skills contribute to this goal. The University of Utah is a PAC-12 institution located in Salt Lake City nestled in the foothills of the Wasatch Mountains. With an enrollment of 31,000 students, it is the flagship university for the state of Utah. The university administration provides strong support for faculty research in the Psychology Department. The University of Utah values candidates who have experience working in settings with students from diverse backgrounds, and possess a strong commitment to improving access to higher education for historically underrepresented students. The University of Utah is an Affirmative Action/Equal Opportunity employer and does not discriminate based upon race, national origin, color, religion, sex, age, sexual orientation, gender identity/expression, status as a person with a disability, genetic information, or Protected Veteran status. Individuals from historically underrepresented groups, such as minorities, women, qualified persons with disabilities and protected veterans are encouraged to apply. Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities. To inquire about the University's nondiscrimination or affirmative action policies or to request disability accommodation, please contact: Director, Office of Equal Opportunity and Affirmative Action, 201 S. Presidents Circle, Rm 135, (801) 581-8365. Please submit a letter detailing current research and teaching interests, a curriculum vitae, three representative reprints or preprints of publications, and contact information for three individuals who will provide letters of recommendation. Applications should be submitted at: http://utah.peopleadmin.com/postings/55506. Review of applications will begin October 1, 2016 and will continue until the position is filled. Matthew J. Euler, Ph.D. Assistant Professor Department of Psychology University of Utah Salt Lake City, UT 84112 -------------- next part -------------- An HTML attachment was scrubbed... URL: From smoratti at psi.ucm.es Tue Sep 13 21:34:33 2016 From: smoratti at psi.ucm.es (smoratti at psi.ucm.es) Date: Tue, 13 Sep 2016 21:34:33 +0200 Subject: [FieldTrip] PhD Position Clinical Neuroscience Lab CTB Madrid Message-ID: <019C5012-57D9-46ED-B699-04DFAD1B1FC9@psi.ucm.es> On behalf of Dr. Bryan Strange I send this job posting: Applications are invited for a 4-year funded PhD position in neuroscience. The Laboratory for Clinical Neuroscience in Madrid (www.thestrangelab.org ) focuses on the study of memory in healthy humans and different patient populations. We apply a multi-modal approach to better understand what factors influence memory, and are currently working on deep-brain stimulation (DBS) techniques to improve memory. The successful applicant would - Be part of a multi-disciplinary team comprising neurosurgeons, neurologists, psychiatrists, psychologists and biomedical engineers - Develop a novel DBS technique to enhance memory in human patients - Adopt methods to localise deep-brain electrodes using pre- and post-operative CT and MRI scans - Perform and analyse simultaneous DBS and MEG recordings - Perform simultaneous intracranial local field potential and scalp high density EEG recordings We provide funding for one four-year PhD position. This is a government funded position, with starting date is early 2017. Additional funding is also provided for international visits to other laboratories to enhance the PhD training. We are looking for a highly motivated individual who wishes to pursue a career in science, and has an interest in clinical and cognitive neuroscience of memory. Applicants should have MSc or equivalent in neuroscience, biology, biomedical engineering, psychology, or a related science/engineering discipline. Prior experience is required in either cognitive neuroscience, theoretical neuroscience, or animal models of memory. Familiarity with electrophysiology or MRI and Matlab or R, would be useful. 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 Applications deadline is 25 September 2016 -- ___________________________ Bryan Strange MRCP PhD Director, Laboratory for Clinical Neuroscience, CTB-UPM and Department of Neuroimaging, Reina Sofia Centre for Alzheimer's Research, Madrid, Spain www.thestrangelab.org ________________________________________________________ Stephan Moratti, PhD see also: Stephan Moratti Universidad Complutense de Madrid Facultad de Psicología Departamento de Psicología Básica I Campus de Somosaguas 28223 Pozuelo de Alarcón (Madrid) Spain and Center for Biomedical Technology Laboratory for Cognitive and Computational Neuroscience Parque Científico y Tecnológico de la Universidad Politecnica de Madrid Campus Montegancedo 28223 Pozuelo de Alarcón (Madrid) Spain email: smoratti at psi.ucm.es Tel.: +34 679219982 -------------- next part -------------- An HTML attachment was scrubbed... URL: From hesham.elshafei at inserm.fr Wed Sep 14 16:04:22 2016 From: hesham.elshafei at inserm.fr (Hesham ElShafei) Date: Wed, 14 Sep 2016 16:04:22 +0200 Subject: [FieldTrip] Virtual Electrodes Message-ID: <93e198c44edd942b7df24688d7ac08c0@inserm.fr> Hello fieldtrippers , For my Phd , I am trying to investigate the dynamics of alpha oscillations during anticipatory attention. I have analysed the data in the sensor level and based upon these analyses I have define time-frequency windows of interest to which I have applied the DICS beamformer. Based on statistical results, I have defined regions of interest (the left Heschl Gyrus, for example). Now I would like to have a look at the time couse of these sources. I have followed this tutorial: http://www.fieldtriptoolbox.org/tutorial/salzburg?s[]=virtual&s[]=sensors However, there is a step I would like to expert opinions. In the tutorial, after having defined voxels of interest , they have re-calculated the leadfield for these voxels. (let's call that method A) Should this operation be different to Method B which involves marking only the voxels of interest in the leadfield (that has been used for the DICS) as inside the brain? I've tried both methods, and results are different. So I would like to know why such difference exists and which is method is better? Also in the aforementioned tutorial , there is this: cfg.grid.pos=[btiposCML;btiposHGL;btiposHGR]./1000; % units of m Which I don't think is correct since conversion should be done from mm to cm (if we follow the tutorial) Thank you very much Hesham ElShafei -------------- next part -------------- An HTML attachment was scrubbed... URL: From roycox.roycox at gmail.com Wed Sep 14 22:25:04 2016 From: roycox.roycox at gmail.com (Roy Cox) Date: Wed, 14 Sep 2016 16:25:04 -0400 Subject: [FieldTrip] postdoctoral position on sleep and memory In-Reply-To: References: Message-ID: > > hi all, >> >> Apologies for re- and cross-posting, but see below for an open >> postdoctoral position. >> >> 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 > > 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 efficacy of pharmacological and other interventions. Our work has > linked cognitive deficits to a specific heritable mechanism (sleep > spindles) 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 (polysomnography), 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 MEG/EEG methodology and data analysis, > comfortable with methodological innovation, and is interested in optimizing > and developing 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 lab mates 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 Experience with MEG/EEG data analysis/methodology > and/or other signal processing. Background in cognitive neuroscience, > experimental psychology, and an interest in clinical applications are a > plus. > > > > 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 mailtome.2113 at gmail.com Thu Sep 15 07:36:53 2016 From: mailtome.2113 at gmail.com (Arti Abhishek) Date: Thu, 15 Sep 2016 15:36:53 +1000 Subject: [FieldTrip] Plotting confidence intervals in multiplotER Message-ID: Dear fieldtrip community, I was wondering whether there is a way to plot the confidence intervals in the ERP plot? I see that this question was asked multiple times in the discussion list before, but I could not find an answer to this. Thanks, Arti -------------- next part -------------- An HTML attachment was scrubbed... URL: From sarathykousik at gmail.com Thu Sep 15 09:39:16 2016 From: sarathykousik at gmail.com (kousik sarathy) Date: Thu, 15 Sep 2016 09:39:16 +0200 Subject: [FieldTrip] Plotting confidence intervals in multiplotER In-Reply-To: References: Message-ID: Hey Arti, This is not such a trivial thing to solve. Here's a recipe I used. You need to find and edit two scripts. If this spurns any more interest, I'll initiate a 'bug' and try to send in a pull request. This is a dirty fix and in all probability will be considered blasphemy. ;) 1. Find in ft_multiplotER : ft_plot_vector(xval, yval, 'width', width(m), 'height', height(m), 'hpos', layX(m), 'vpos', layY(m), 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'color', color, 'style', cfg.linestyle{i}, 'linewidth', cfg.linewidth, 'axis', cfg.axes, 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'label', label, 'box', cfg.box, 'fontsize', cfg.fontsize); This basically calls a plotting function which in turn does the plotting for you. You need to send in the extra 'sem' or a 'ci' variable. Change this to: ft_plot_vector(xval, yval, 'ysem', ysem, 'width', width(m), 'height', height(m), 'hpos', layX(m), 'vpos', layY(m), 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'color', color, 'style', cfg.linestyle{i}, 'linewidth', cfg.linewidth, 'axis', cfg.axes, 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'label', label, 'box', cfg.box, 'fontsize', cfg.fontsize); 2. Find in ft_plot_vector : You need to first get the sem parameter from your data and setup so FT can see your sem or CI info. Follow the code here . Search for "data_sem" and fix those lines. Then: h = plot(hdat, vdat, style, 'LineWidth', linewidth, 'Color', color, ' markersize', markersize, 'markerfacecolor', markerfacecolor); Change this to: [h hp ]= boundedline(hdat, vdat, vdat_sem); Boundedline is a submission in the MATLAB file exchange. You can use any other thing. Good luck trying! :) -- Regards, Kousik Sarathy, S On Thu, Sep 15, 2016 at 7:36 AM, Arti Abhishek wrote: > Dear fieldtrip community, > > I was wondering whether there is a way to plot the confidence intervals in > the ERP plot? I see that this question was asked multiple times in the > discussion list before, but I could not find an answer to this. > > Thanks, > Arti > > _______________________________________________ > 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 nima.noury at student.uni-tuebingen.de Thu Sep 15 12:35:48 2016 From: nima.noury at student.uni-tuebingen.de (Nima Noury) Date: Thu, 15 Sep 2016 12:35:48 +0200 Subject: [FieldTrip] 2016 Tuebingen MEG Symposium, Oct 26-27 Message-ID: <20160915123548.Horde.jS8bdBmAx3EbFIq-0uCVWMX@webmail.uni-tuebingen.de> The MEG Center Tuebingen is pleased to announce the 2016 Tuebingen MEG Symposium The symposium takes place on October 26 and 27, 2016 at the University Hospital’s Conference Center. The meeting brings together leading researchers in the field of MEG and related disciplines. Join us to learn about the latest advances in MEG research and beyond. Confirmed speakers: Radoslaw Cichy, Berlin Michael Cohen, Nijmegen Freek van Ede, Oxford Stefan Haufe, New York Vladimir Litvak, London Laura Marzetti, Chieti Satu Palva, Helsinki Rafael Polania, Zurich Martin Vinck, New Haven Mark Woolrich, Oxford For more information and registration, please visit: http://meg.medizin.uni-tuebingen.de/2016/ 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 -------------- next part -------------- An embedded message was scrubbed... From: Nima Noury Subject: 2016 Tuebingen MEG Symposium, Oct 26-27 Date: Tue, 13 Sep 2016 12:38:52 +0200 Size: 1704 URL: From maorwolf at gmail.com Thu Sep 15 12:57:49 2016 From: maorwolf at gmail.com (Maor Wolf) Date: Thu, 15 Sep 2016 10:57:49 +0000 Subject: [FieldTrip] 2x3x3 cluster analysis Message-ID: Dear fieldtripers, I am trying to run a mixed repeated measures ANOVA cluster analysis with one between subject variable (schizoprhenics vs. neurotypicals) and two within subject variables (each one with three conditions) and I'm struggling with the design matrix. Has anyone encountered this issue before? Thank you, Maor -------------- next part -------------- An HTML attachment was scrubbed... URL: From t.rusch at uke.uni-hamburg.de Thu Sep 15 14:01:41 2016 From: t.rusch at uke.uni-hamburg.de (Tessa Rusch) Date: Thu, 15 Sep 2016 14:01:41 +0200 Subject: [FieldTrip] postdoctoral position on social decision-making Message-ID: <001301d20f48$eb93f550$c2bbdff0$@uke.uni-hamburg.de> Hi! Sorry for cross-posting, but find below the details of an open postdoctoral position Kind regards Tessa Postdoctoral Position in Social Decision-Making Hamburg, Germany A Post-doctoral position in the field of social decision-making is available at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany. The position is funded through the program “Collaborative Research in Computational Neuroscience” co-funded by the German Ministry of Science and Research (BMBF) and by the American National Science Foundation (NSF). The project entitled “Computational Modeling of Cooperative Success” investigates social decision-making and the construction of mental models with EEG hyperscanning and computational modeling. The collaborative partner in the project is Prof. M. Spezio (Scripps College, CA). Research visits in the respective other labs are part of the project. We are searching for enthusiastic candidates with a strong interest in cognitive and social neuroscience and a PhD in (cognitive) neuroscience, cognitive science, psychology, biology, computer science, or a related discipline. Prior experience in the acquisition and analysis of human EEG data (ERPs, time-frequency analyses) and good programming skills (e.g. Matlab/R) are required. Starting date is Dec 1st 2016 or a few months later. The position is available for 3 years. The institute provides an excellent multi-disciplinary and interactive research environment with a research-dedicated 3T MRI scanner, EEG/MEG facilities and behavioral labs. Additional information about the research group and other scientific projects are available at www.glascherlab.org. Interested candidates should submit their application as a single PDF document (including CV, publication list, contact details of two references and a short statement of research interests) via email to Dr. Jan Gläscher (glaescher at uke.de). -- _____________________________________________________________________ Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | www.uke.de Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Prof. Dr. Dr. Uwe Koch-Gromus, Joachim Prölß, Rainer Schoppik _____________________________________________________________________ SAVE PAPER - THINK BEFORE PRINTING -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Thu Sep 15 16:40:23 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Thu, 15 Sep 2016 16:40:23 +0200 Subject: [FieldTrip] From raw MEG to publication - BIOMAG16 satellite workshop, Oct 2, 2016 Message-ID: <282A2185-4DB3-4072-9D55-B5817DD25F95@donders.ru.nl> Dear colleagues, Apologies in advance for cross-posting. We would like to attract your attention to the BIOMAG2016 satellite symposium which will take place on Oct 2nd 2016 and is dedicated to group analysis of MEG data with free academic toolboxes. Please read the full description below. With best wishes, Arnaud Delorme Alexandre Gramfort Vladimir Litvak Srikantan Nagarajan Robert Oostenveld Francois Tadel ------------------------------------------------------------------------------- From raw MEG to publication: how to perform MEG group analysis with free academic software. Organisers: Arnaud Delorme, Alexandre Gramfort, Vladimir Litvak, Srikantan Nagarajan, Robert Oostenveld, Francois Tadel Free academic toolboxes have gained increasing prominence in MEG analysis as a means to disseminate cutting edge methods, share best practices between different research groups and pool resources for developing essential tools for the MEG community. In the recent years large and vibrant research communities have emerged around several of these toolboxes. Teaching events are regularly held around the world where the basics of each toolbox are explained by its respective developers and experienced power users. There are, however, two knowledge gaps that our BIOMAG satellite symposium aims to address. Firstly, most teaching examples only show analysis of a single ‘typical best’ subject whereas most real MEG studies involve analysis of group data. It is then left to the researchers in the field to figure out for themselves how to make the transition and obtain significant group results. Secondly, we are not familiar with any examples of fully analyzing the same group dataset with different academic toolboxes to assess the degree of agreement in scientific conclusions and compare strengths and weaknesses of various analysis methods and their independent implementations. Our workshop is organised by the lead developers of six most popular free academic MEG toolboxes (in alphabetic order): Brainstorm, EEGLAB, FieldTrip, MNE, NUTMEG, and SPM. Ahead of the workshop the research team for each toolbox will analyze the same group MEG/EEG dataset. This dataset containing evoked responses to face stimuli was acquired by Richard Henson and Daniel Wakeman, who won a special award at BIOMAG2010 to make it freely available to the community. All the raw data are available at ftp://ftp.mrc-cbu.cam.ac.uk/personal/rik.henson/wakemandg_hensonrn/ and https://openfmri.org/dataset/ds000117/ Detailed instructions for each toolbox will be made available online including analysis scripts and figures of results. All analyses will show a full pipeline from the raw data to detailed publication quality results. Researchers who are interested in using the respective toolbox will then be able to reproduce the analysis in their lab and port it to their own data. At the workshop each group will briefly introduce their software and present the key results from their analysis. This will be followed by a panel discussion and questions from the audience. Following the event we plan to integrate the suggestions and questions from the workshop audience and to publish the analyses details as part of a special research topic in Frontiers in Neuroscience, section Brain Imaging Methods so that the proposed best practices will be endorsed by peer review and become citable in future publications. Other research groups will be invited to contribute to the research topic as long as they present detailed descriptions of analyses of group data that are freely available online and make it possible for others to fully reproduce their analysis and results. We hope that this proposal will lead to creation of invaluable resource for the whole MEG community and the workshop will contribute to establishment of good practice and promoting consistent and reproducible analysis approaches. The event will also showcase all the toolboxes and will be of interest to beginners in the field with basic background in MEG who contemplate the most suitable analysis approach and software for their study as well as to experienced researchers who would like to get up to date with the latest methodological developments. -------------- next part -------------- An HTML attachment was scrubbed... URL: From iris.steinmann at med.uni-goettingen.de Thu Sep 15 16:41:30 2016 From: iris.steinmann at med.uni-goettingen.de (Steinmann, Iris) Date: Thu, 15 Sep 2016 14:41:30 +0000 Subject: [FieldTrip] Inter-trial variability of power amplitude for time-frequency spectra Message-ID: Dear Fieldtripper, I'm working on a spectral analysis of LFP data and calculated so far time-frequency spectra for every single trial. To describe the consistency/variability of phases on every time-frequency bin over trials I calculated 'Inter-trial Phase coherence (ITPC)' as described in the fieldtrip tutorial. But, what would I do to determine the consistency/variability of the power (squared amplitude) for every time-frequency bin over trials? Maybe simply calculate for every time-frequency bin a Standard Deviation over trials and relate this to the according mean: Variability(t,f) = Standard Deviation(t,f) / mean(t,f) Would it be that simple, or am I running into some statistical trouble (maybe because the power values are not normally distributed or anything else). Should I baseline correct the single trials before calculating the 'variability' of the power amplitude. Or am I missing an important point and the whole idea is not meaningful at all? Would be great if anyone has an idea, an answer, or even just a hint for a reference to read (couldn't find one so far)... Thanks! Iris -------------- next part -------------- An HTML attachment was scrubbed... URL: From nasseroleslami at gmail.com Fri Sep 16 17:57:52 2016 From: nasseroleslami at gmail.com (Bahman Nasseroleslami) Date: Fri, 16 Sep 2016 16:57:52 +0100 Subject: [FieldTrip] Fwd: Research Fellow (Biostatistics) Position - Trinity College Dublin, the University of Dublin, Dublin, Ireland In-Reply-To: References: Message-ID: Dear All, There is a research fellow position available in Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin, Ireland. ------------------------------------ Post Specification: 031885 Post Title: Research Fellow Post Status: 23 month Fixed Term Contract (Full-time) (Subject to satisfactory probation) Research Group/Department/School: Academic Unit of Neurology, School of Medicine, Trinity College Dublin, the University of Dublin London School of Hygiene and Tropical Medicine, London Location: Trinity Biomedical Sciences Institute, Trinity College Dublin, the University of Dublin College Green, Dublin 2, Ireland And close links with London School of Hygiene and Tropical Medicine Reports to: Professor Orla Hardiman (Dublin) Prof. Neil Pearce (London) Salary: Post-Doctorate Researcher Salary Scale, commensurate with experience Closing Date and Time: 12 noon on Friday, 14th October 2016 Applications are invited for a motivated and self-driven individual for the position of Biostatistician with the Irish ALS Research Group, hosted in the Trinity Biomedical Sciences Institute's Academic Unit of Neurology.The ideal candidate will have a PhD in Biostatistics or a cognate area. Amyotrophic Lateral Sclerosis (ALS) or Motor Neurone Disease (MND) is a degenerative brain disease that leads to progressive decline and death within 3-5 years of first symptom. Our detailed assessment of cognitive, behavioural and social cognitive function in ALS points to significant disruption in extra-motor systems in some patients. This project will combine high resolution structural and dynamic imaging of the brain at 3 Tesla and spectral EEG/ EMG with clinical and genomic data to identify sub-clusters of ALS patients. Using robust mathematical models and building on key imaging and signal processing signatures we will develop observed-independent, quantitative markers of disease that can be utilized to generate disease clusters. These clusters will then be further analysed based on discriminatory clinical, neuropsychological and genomic data. The detailed job description file (PDF) and the application instructions can be found online at http://jobs.tcd.ie. ------------------------------------ It would be really appreciated if you could share this with those that may be interested. Sincerely Bahman –––––––––––– Bahman Nasseroleslami Irish Research Council Postdoctoral Research Fellow Academic Unit of Neurology, School of Medicine Trinity College Dublin, the University of Dublin Dublin 2, Ireland. Room 5.43, Trinity Biomedical Sciences Institute 152-160 Pearse Street, Dublin D02 R590, Ireland. nasserob at tcd.ie, nasseroleslami at gmail.com www.tcd.ie Trinity College Dublin, the University of Dublin is ranked 1st in Ireland and in the top 100 world universities by the QS World University Rankings. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Sun Sep 18 20:55:04 2016 From: mklados at gmail.com (Manousos Klados) Date: Sun, 18 Sep 2016 14:55:04 -0400 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From hallmbh at aston.ac.uk Mon Sep 19 12:25:23 2016 From: hallmbh at aston.ac.uk (Hall, Michael (Research Student)) Date: Mon, 19 Sep 2016 10:25:23 +0000 Subject: [FieldTrip] Maxfilter and PCA Message-ID: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall -------------- next part -------------- An HTML attachment was scrubbed... URL: From magazzinil at gmail.com Mon Sep 19 13:48:55 2016 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Mon, 19 Sep 2016 12:48:55 +0100 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: Message-ID: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) < hallmbh at aston.ac.uk> wrote: > Dear All, > > I've been doing some testing with elekta neuromag data in Fieldtrip using > different sensor types (meg, meggrad, megmag) and different preprocessing > steps (tSSS 0.9 corr limit, no tSSS). > > A step that was proposed at the MEG UK 2015 demo was to use PCA to > compensate for the ill-conditioned estimate of the cov/csd matrix due to > maxfilter - could I ask why running a PCA and reducing the number of > components further would compensate for this? Apologies if this a naive > question, however I would assume that you would not want to reduce the rank > of your data further? Please see below for the link and code that I'm > referring to. > > http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtr > ip-beamformer-demo > > > %% deal with maxfilter > > % the data has been maxfiltered and subsequently concatenated > % this results in an ill-conditioned estimate of covariance or CSD > > cfg = []; > cfg.method = 'pca'; > cfg.updatesens = 'no'; > cfg.channel = 'MEGMAG'; > comp = ft_componentanalysis(cfg, data); > > cfg = []; > cfg.updatesens = 'no'; > cfg.component = comp.label(51:end); > data_fix = ft_rejectcomponent(cfg, comp); > > > Many thanks, > Mike Hall > > > > > _______________________________________________ > 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 Mon Sep 19 14:45:00 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 19 Sep 2016 12:45:00 +0000 Subject: [FieldTrip] Maxfilter and PCA References: Message-ID: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Hi all, The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. Best, Jan-Mathijs On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall _______________________________________________ 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 magazzinil at gmail.com Mon Sep 19 15:00:11 2016 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Mon, 19 Sep 2016 14:00:11 +0100 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: Hi Jan-Mathijs, Thanks for your answer. Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? Thanks, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Hi all, > > The reason to do the PCA has to do in this context with the fact that a > beamformer is used further down in the tutorial. The beamformer uses the > inverse of the covariance matrix, which behaves unpredictably (but usually > quite bad) when the smallest (usually poorly conditioned) components are > not well estimated. > The data that is used for the source reconstruction comes from three > separate runs, each of which was separately maxfiltered. As a consequence, > the low-rank subspace that is spanned by the individual runs’ data is > slightly different (each of which has approximately, say, a rank of 60). > Upon concatenation, however, the rank is suddenly increased to >> 60, where > most likely quite a lot of the ‘higher’ components represent noise. In > order to account for that in the covariance inversion, the whole data > matrix is ‘stabilized’ with a PCA. > > Best, > Jan-Mathijs > > > On 19 Sep 2016, at 13:48, Lorenzo Magazzini wrote: > > Hi Mike, > > This is a question that I've been asking myself too and I'd love to hear > an expert (and more technical) answer. In the meantime, these discussions > may be of help: > > https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html > https://mailman.science.ru.nl/pipermail/fieldtrip/2013- > November/007170.html > http://www.fieldtriptoolbox.org/faq/why_does_my_ica_ > output_contain_complex_numbers?s[ > > I wonder if the confusion arises from the difference between rank and > number of components? My understanding is that maxfilter reduces the rank > of the data (from 306 to 64, apparently). Therefore, my best guess is that > by performing a PCA and rejecting a number of components (only the first 50 > are kept, in the tutorial example), the data is no longer rank-deficient, > i.e. the rank is equal or greater than the number of components in the data. > > Clearly, this is a very non-technical interpretation, and a correction > would be more than welcome.. :) > > Best, > Lorenzo > > > > > > Lorenzo Magazzini > PhD Student > magazzinil at cardiff.ac.uk > > CUBRIC Building > Maindy Road > Cardiff > CF24 4HQ > > > On 19 September 2016 at 11:25, Hall, Michael (Research Student) < > hallmbh at aston.ac.uk> wrote: > >> Dear All, >> >> I've been doing some testing with elekta neuromag data in Fieldtrip using >> different sensor types (meg, meggrad, megmag) and different preprocessing >> steps (tSSS 0.9 corr limit, no tSSS). >> >> A step that was proposed at the MEG UK 2015 demo was to use PCA to >> compensate for the ill-conditioned estimate of the cov/csd matrix due to >> maxfilter - could I ask why running a PCA and reducing the number of >> components further would compensate for this? Apologies if this a naive >> question, however I would assume that you would not want to reduce the rank >> of your data further? Please see below for the link and code that I'm >> referring to. >> >> http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtr >> ip-beamformer-demo >> >> >> %% deal with maxfilter >> >> % the data has been maxfiltered and subsequently concatenated >> % this results in an ill-conditioned estimate of covariance or CSD >> >> cfg = []; >> cfg.method = 'pca'; >> cfg.updatesens = 'no'; >> cfg.channel = 'MEGMAG'; >> comp = ft_componentanalysis(cfg, data); >> >> cfg = []; >> cfg.updatesens = 'no'; >> cfg.component = comp.label(51:end); >> data_fix = ft_rejectcomponent(cfg, comp); >> >> >> Many thanks, >> Mike Hall >> >> >> >> >> _______________________________________________ >> 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 seymourr at aston.ac.uk Mon Sep 19 15:09:45 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Mon, 19 Sep 2016 13:09:45 +0000 Subject: [FieldTrip] Maxfilter and PCA Message-ID: Hi Mike & others, Instead of specifying a set number of components (e.g. 51) I tend to use data-driven approach that reduces my data to the number of components that describes 99% of the variance in my covar matrix. I do this like so: covar = zeros(numel(data.label)); for itrial = 1:numel(data.trial) currtrial = data.trial{itrial}; covar = covar + currtrial*currtrial.'; end [V, D] = eig(covar); D = sort(diag(D),'descend'); D = D ./ sum(D); Dcum = cumsum(D); numcomponent = find(Dcum>.99,1,'first') +1; % number of components accounting for 99% of variance in covar matrix disp(sprintf('\n Reducing the data to %d components \n',numcomponent)); cfg = []; cfg.method = 'pca'; cfg.updatesens = 'yes'; cfg.channel = 'MEG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'yes'; cfg.component = comp.label(numcomponent:end); data_fix = ft_rejectcomponent(cfg, comp); Cheers, Robert Seymour (Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Sep 19 15:53:39 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 19 Sep 2016 13:53:39 +0000 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: Hi Lorenzo, Well, your interpretation was almost OK, yet by keeping a certain number of components one makes the data explicitly rank deficient (so that’s the part that was not fully correctly stated in your pre-previous e-mail) The thing is that with keeping only (e.g.) 50 components, your data will still be rank deficient, yet the small components (those that end up as component 51 and up) cannot negatively affect the inverse of the data covariance matrix (which needs to be regularized anyway). Best, Jan-Mathijs On 19 Sep 2016, at 15:00, Lorenzo Magazzini > wrote: Hi Jan-Mathijs, Thanks for your answer. Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? Thanks, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) > wrote: Hi all, The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. Best, Jan-Mathijs On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall _______________________________________________ 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 russgport at gmail.com Mon Sep 19 17:30:48 2016 From: russgport at gmail.com (russ port) Date: Mon, 19 Sep 2016 11:30:48 -0400 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: <6474D29F-4B8F-4B9C-AF35-30E2C18A9DC6@gmail.com> Hi All, Just to clarify, as I am certainly worried about the implications of this chain on my own analyses. I have been following old posts from the email list/server, where it says that to do ICA on Neuromag data (for instance if you want to do EOG rejection) you must reduce the components you output to at most the rank of your data (because of TSSS/SSS basically drastically reduces the rank of your data because of how it works). As such, based on old email discussions, I ran an artifact rejection (for the artifacts mentioned in this email [muscle/Jump etc]) and then did a component analysis (runica) with the cfg set to give only enough outputs as valid by the rank of the data. Importantly, this data is only SSS (instead of TSSS) because the cHPI (continuous head position indicator monitoring) was not turned on. As such the script ultimately reads something like this: cfg=[] cfg.artfctdef.eog.artifact = artifact_EOG; cfg.artfctdef.jump.artifact = artifact_jump; cfg.artfctdef.muscle.artifact = artifact_muscle; data_no_artifacts = ft_rejectartifact(cfg,datanoline); cfg=[] cfg.resamplefs=300 cfg.detrend='no' resampleartifactfree=ft_resampledata(cfg,data_no_artifacts) cfg = []; cfg.method='runica' n_comp = rank(resampleartifactfree.trial{1} * resampleartifactfree.trial{1}') cfg.numcomponent = n_comp; cfg.runica.stop = 1e-7; ic_data = ft_componentanalysis(cfgeog,resampleartifactfree); I then go through the components and reject any component that are EC(or K depending on your nationality)G/ECG [heart and eye] artifacts. I then do ft_rejectcomponents for artifact components and use the resulting data in beamforming. My ICA components have real values, and the topos/timecourses look legit. Is this valid OR should I be doing a PCA/ICA to get the X (X=rank of data) components, and then again running it through ft_componentanalysis to check for heart/eye artifacts? Best (and sorry for the email, I’m a little paranoid when it comes to these things), Russ > On Sep 19, 2016, at 9:53 AM, Schoffelen, J.M. (Jan Mathijs) wrote: > > Hi Lorenzo, > > Well, your interpretation was almost OK, yet by keeping a certain number of components one makes the data explicitly rank deficient (so that’s the part that was not fully correctly stated in your pre-previous e-mail) The thing is that with keeping only (e.g.) 50 components, your data will still be rank deficient, yet the small components (those that end up as component 51 and up) cannot negatively affect the inverse of the data covariance matrix (which needs to be regularized anyway). > > Best, > Jan-Mathijs > > > >> On 19 Sep 2016, at 15:00, Lorenzo Magazzini > wrote: >> >> Hi Jan-Mathijs, >> >> Thanks for your answer. >> >> Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? >> >> Thanks, >> Lorenzo >> >> >> >> Lorenzo Magazzini >> PhD Student >> magazzinil at cardiff.ac.uk >> >> CUBRIC Building >> Maindy Road >> Cardiff >> CF24 4HQ >> >> >> On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) > wrote: >> Hi all, >> >> The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. >> The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. >> >> Best, >> Jan-Mathijs >> >> >>> On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: >>> >>> Hi Mike, >>> >>> This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: >>> >>> https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html >>> https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html >>> http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ >>> >>> I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. >>> >>> Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) >>> >>> Best, >>> Lorenzo >>> >>> >>> >>> >>> >>> Lorenzo Magazzini >>> PhD Student >>> magazzinil at cardiff.ac.uk >>> >>> CUBRIC Building >>> Maindy Road >>> Cardiff >>> CF24 4HQ >>> >>> >>> On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: >>> Dear All, >>> >>> I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). >>> >>> A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. >>> >>> http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo >>> >>> %% deal with maxfilter >>> >>> % the data has been maxfiltered and subsequently concatenated >>> % this results in an ill-conditioned estimate of covariance or CSD >>> >>> cfg = []; >>> cfg.method = 'pca'; >>> cfg.updatesens = 'no'; >>> cfg.channel = 'MEGMAG'; >>> comp = ft_componentanalysis(cfg, data); >>> >>> cfg = []; >>> cfg.updatesens = 'no'; >>> cfg.component = comp.label(51:end); >>> data_fix = ft_rejectcomponent(cfg, comp); >>> >>> >>> Many thanks, >>> Mike Hall >>> >>> >>> >>> >>> >>> _______________________________________________ >>> 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 > > _______________________________________________ > 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 B.Haendel at gmx.net Mon Sep 19 22:30:52 2016 From: B.Haendel at gmx.net (Barbara Haendel) Date: Mon, 19 Sep 2016 22:30:52 +0200 Subject: [FieldTrip] NEW PhD positions: Neuroscience - University of Wuerzburg (Germany) Message-ID: An HTML attachment was scrubbed... URL: From mklados at gmail.com Tue Sep 20 00:08:08 2016 From: mklados at gmail.com (Manousos Klados) Date: Tue, 20 Sep 2016 00:08:08 +0200 Subject: [FieldTrip] =?utf-8?q?Society_of_Applied_Neuroscience_Biennial_co?= =?utf-8?b?bmZlcmVuY2UgKFNBTjIwMTbigI8pIOKAkyBmaW5hbCBwcm9ncmFtbWU=?= Message-ID: Dear colleagues, I am proud to announce you that the final programme for SAN2016 is now online (http://www.applied-neuroscience.org/san2016/ index.php/conference-info/program) and a summarised snapshot with the its highlights is attached to this email. With this information we would also like to cordially invite you to participate in and attend SAN2016 (http://applied-neuroscience.org/san2016/), which is organised by the Society of Applied Neuroscience (SAN, http://www.applied-neuroscience.org/) in cooperation with the Medical School of the Aristotle University of Thessaloniki and the Department of Neurology of the Max Planck Institute for Human Cognitive and Brain Sciences. SAN2016 will be held October6-9, 2016 in Corfu Island, Greece. As you will see, there is an attractive list of planned hands-on workshops and conference symposia in place as well as, an attractive list of distinguished speakers Numerous special issues and research topics are also planned by Society members as per tradition. We look forward to seeing you in Corfu, Greece! Panos Bamidis John Gruzelier Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: SAN2016_Brochure_Final.pdf Type: application/pdf Size: 593075 bytes Desc: not available URL: From matt.gerhold at gmail.com Tue Sep 20 09:17:33 2016 From: matt.gerhold at gmail.com (Matt Gerhold) Date: Tue, 20 Sep 2016 09:17:33 +0200 Subject: [FieldTrip] Inverse-modelling requirements Message-ID: MEG Mavens: I am looking to perform a source-level analysis on some EEG event-related data. I would be very grateful if you can assist me in understanding some of the methods in your toolbox and also some of the requirements in terms of the experimental protocols if one envisages performing source-level analysis. I have reviewed the tutorials on your website and viewed a number of video lectures from you institute. I have one or two points I would like to clear-up and one or two questions that require answers. >From the available information that I have reviewed, it is recommended that one have at least the following items: i. hi-res EEG/MEG datasets, ii. polhemus measurement data, and iii. MRI data for each of the participants within the study. Having these items enables one to compute the necessary models to source-localise the EEG/MEG sensor-space data. What I would like to know is how far one can stretch the boundaries of these requirements and still produce publishable scientific outcomes: what items are indispensable to the source localisation methodology? There are many examples of researchers using standard MRI templates, but how reliable are analytical outcomes in such instances? Does using a standard MRI image for all participants really produce useful scientific outcomes, especially in clinical populations wherein cortical structural changes are well-documented? There is a fair amount of structural variation within the cortex across healthy individuals; surely, a single standard MRI scan would lead to erroneous localisation in some instances? In terms of electro/magnetic field data: what is the minimum requirement in terms of how many electrodes are needed (spatial sampling across the scalp) in order to perform subsequent source-localisation via inverse modelling? Can one justify using the method(s) in instances of sparse spatial sampling (32-channels) and expect acceptable scientific outcomes? If one uses generic sensor/head-model co-registration in the absence of polhemus data, does this lead to analytical outcomes that are accepted by yourselves? What are the standards currently being set within the journals; being mavens in the field, what would you recommend? I appreciate that most people will embark on the analysis and build understanding along the way; however, I would like to gain some clarity before embarking on this analytical journey. Many thanks in advance. Kind Regards, Matthew -------------- next part -------------- An HTML attachment was scrubbed... URL: From Darren.Price at mrc-cbu.cam.ac.uk Tue Sep 20 16:43:36 2016 From: Darren.Price at mrc-cbu.cam.ac.uk (Darren Price) Date: Tue, 20 Sep 2016 14:43:36 +0000 Subject: [FieldTrip] Combined EEG MEG Source Reconstruction Message-ID: Dear Fieldtrippers We are interested in using fieldtrip for data fusion and source reconstruction of three different types of sensors: EEG (64 Channels), MEG planar gradiometers (204), MEG magnetometers (102) (Elekta Neuromag 306 Channel). I found the following page, with a quick sample script demonstrating how to perform the forward solutions, http://www.fieldtriptoolbox.org/example/combined_eeg_and_meg_source_reconstruction. However, the page does not give much detail on the inversion part. Also, it does not mention whether fieldtrip takes care of scaling of the data or any other preprocessing steps such as pre-whitening. That post is also a couple of years old so I thought there may be some more current but undocumented way to achieve this. Any help would be much appreciated. Kind Regards Darren ------------------------------------------------------- Dr. Darren Price Investigator Scientist and Cam-CAN Data Manager MRC Cognition & Brain Sciences Unit 15 Chaucer Road Cambridge, CB2 7EF England EMAIL: darren.price at mrc-cbu.cam.ac.uk URL: http://www.mrc-cbu.cam.ac.uk/people/darren.price TEL +44 (0)1223 355 294 x202 FAX +44 (0)1223 359 062 MOB +44 (0)7717822431 ------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.brehm at uu.nl Wed Sep 21 09:52:29 2016 From: j.brehm at uu.nl (Brehm, J. (Julia)) Date: Wed, 21 Sep 2016 07:52:29 +0000 Subject: [FieldTrip] EEG Visual Artifact Detection - Settings Message-ID: <385DDA785CF9764B8E184EF28D01ADE0F63153@WP0045.soliscom.uu.nl> Dear FieldTrippers, I am looking for options to achieve the following functionality in visual EEG artifact detection: 1. mark channel-by-trial pairs as bad (as in ft_rejectvisual -> method = ’trial’). 2. plot trials on a specific channel layout. 3. return marked data, and not yet cleaned data (as in ft_databrowser) OR return list of excluded channel-by-trial pairs in addition to cleaned data. Is there any way to achieve this functionality with some settings that are readily available? All the best, Julia -------------- next part -------------- An HTML attachment was scrubbed... URL: From seymourr at aston.ac.uk Wed Sep 21 12:10:14 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Wed, 21 Sep 2016 10:10:14 +0000 Subject: [FieldTrip] Combined EEG MEG Source Reconstruction Message-ID: Hi Darren, Have you had a look at this tutorial? http://www.fieldtriptoolbox.org/tutorial/natmeg/beamforming I'm also interested in the answer to this question - it would be really helpful for someone to clarify the steps Fieldtrip takes to combine MAGS + GRADS from an Elekta Neuromag 306 scanner... I know that Fieldtrip pre-whitens the data for ICA with combined MAGS+GRADS but it is unclear whether this is also done when computing the forward solution? Many thanks, Robert Seymour (PhD Student Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From c.vanheck at donders.ru.nl Wed Sep 21 14:24:57 2016 From: c.vanheck at donders.ru.nl (Casper van Heck) Date: Wed, 21 Sep 2016 14:24:57 +0200 Subject: [FieldTrip] Lost reference location Message-ID: Dear all, We've recently started working on an old dataset, but have ran into a problem; nobody bothered to write down where the reference was placed... Does anybody have ideas on how to reconstruct the location of the reference, based on (some aspect of) the data? Best regards, Casper van Heck and Tineke van Rijn -------------- next part -------------- An HTML attachment was scrubbed... URL: From dlozanosoldevilla at gmail.com Wed Sep 21 14:54:48 2016 From: dlozanosoldevilla at gmail.com (Diego Lozano-Soldevilla) Date: Wed, 21 Sep 2016 14:54:48 +0200 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Casper, Very difficult... One idea would be to play with the data rank. Referencing to a specific sensor produces rank deficiency in your data. You can try to figure out which is the sensor that depends on the rest reading this thread: http://fr.mathworks.com/matlabcentral/newsreader/view_thread/157533 This ONLY can work if the sensor recordings are not correlated which is not always the case... Good luck! Diego On 21 September 2016 at 14:24, Casper van Heck wrote: > Dear all, > > We've recently started working on an old dataset, but have ran into a > problem; nobody bothered to write down where the reference was placed... > Does anybody have ideas on how to reconstruct the location of the > reference, based on (some aspect of) the data? > > Best regards, > > Casper van Heck and Tineke van Rijn > > _______________________________________________ > 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 christine.blume at sbg.ac.at Wed Sep 21 14:57:51 2016 From: christine.blume at sbg.ac.at (Blume Christine) Date: Wed, 21 Sep 2016 12:57:51 +0000 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Casper and Tineke, As voltage is always the difference between the reference and an electrode, voltages are lowest for electrodes closest to the reference electrode. You could check where voltages are minimal across trials and for each participant. If then for example that is close to Cz, it is likely that data were referenced to the vertex. Just an idea, it might work…but perhaps someone else has a better idea? Best, Christine Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Casper van Heck Gesendet: Mittwoch, 21. September 2016 14:25 An: fieldtrip at science.ru.nl Betreff: [FieldTrip] Lost reference location Dear all, We've recently started working on an old dataset, but have ran into a problem; nobody bothered to write down where the reference was placed... Does anybody have ideas on how to reconstruct the location of the reference, based on (some aspect of) the data? Best regards, Casper van Heck and Tineke van Rijn -------------- next part -------------- An HTML attachment was scrubbed... URL: From litvak.vladimir at gmail.com Wed Sep 21 16:26:28 2016 From: litvak.vladimir at gmail.com (Vladimir Litvak) Date: Wed, 21 Sep 2016 15:26:28 +0100 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: If you need to know the reference for analysis purposes the easiest thing is to just rereference to another electrode or the average reference. Then it wouldn't matter what the original reference was. Best, Vladimir On Wed, Sep 21, 2016 at 1:57 PM, Blume Christine wrote: > Dear Casper and Tineke, > > > > As voltage is always the difference between the reference and an > electrode, voltages are lowest for electrodes closest to the reference > electrode. You could check where voltages are minimal across trials and for > each participant. If then for example that is close to Cz, it is likely > that data were referenced to the vertex. Just an idea, it might work…but > perhaps someone else has a better idea? > > > > Best, > > Christine > > > > *Von:* fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces@ > science.ru.nl] *Im Auftrag von *Casper van Heck > *Gesendet:* Mittwoch, 21. September 2016 14:25 > *An:* fieldtrip at science.ru.nl > *Betreff:* [FieldTrip] Lost reference location > > > > Dear all, > > > > We've recently started working on an old dataset, but have ran into a > problem; nobody bothered to write down where the reference was placed... > Does anybody have ideas on how to reconstruct the location of the > reference, based on (some aspect of) the data? > > > > Best regards, > > > > Casper van Heck and Tineke van Rijn > > _______________________________________________ > 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 xianwei.che at monash.edu Thu Sep 22 06:26:21 2016 From: xianwei.che at monash.edu (Xianwei Che) Date: Thu, 22 Sep 2016 14:26:21 +1000 Subject: [FieldTrip] creating difference wave Message-ID: Dear list, I have some concerns of how to create difference wave between two conditions. Here is what I want to look at: I have grand average time-freqency data of two conditions ("GA1","GA2"), and one behavioural measurement. Now I want to do so some regression/correlation analysis between the behavioural measurement and the contrasted time-freqency data (GA1-GA2). I did some googling and it is suggested to create the difference wave first, as per here (http://www.fieldtriptoolbox.org/faq/how_can_i_test_an_ interaction_effect_using_cluster-based_permutation_tests). >From these 4 data structures, you now make 2 difference data structures in the following way: - Copy GA11 to GAdiff11_12 and perform the assignment GAdiff11_12.avg=GA11.avg-GA12.avg. - Copy GA21 to GAdiff21_22 and perform the assignment GAdiff21_22.avg=GA21.avg-GA22.avg. I got confused about the '.avg' here. Powspctrm is 4-d data in each GA (subject.channel.frequency.time); so what is and how to calculate the average (.avg) in each GA structure. Or is it just a filed in each GA as I cannot find one. Thanks a lot *-------------* *Mr Xianwei Che* *PhD Candidate* *Monash Alfred Psychiatry Research Centre (MAPrc)* *Central Clinical School & the Alfred * *Monash University* *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* -------------- next part -------------- An HTML attachment was scrubbed... URL: From xianwei.che at monash.edu Thu Sep 22 08:31:14 2016 From: xianwei.che at monash.edu (Xianwei Che) Date: Thu, 22 Sep 2016 16:31:14 +1000 Subject: [FieldTrip] creating difference wave In-Reply-To: References: Message-ID: Dear list, Here is my understanding of this. The field ".avg" is in the output of timelockanalysis, which is the average across the trials. But in the output of freqanalysis there is no ".avg" field as the field "powspctrm " is the "averaged" results. So, if I want to create a difference wave of the freqanalysis between two conditions; I just use the ft_math to subtract the field "powspctrm" in one condition from the other one. I don't know if this is right; any suggestion would be appreciated. Thanks *-------------* *Mr Xianwei Che* *PhD Candidate* *Monash Alfred Psychiatry Research Centre (MAPrc)* *Central Clinical School & the Alfred * *Monash University* *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* On 22 September 2016 at 14:26, Xianwei Che wrote: > Dear list, > > I have some concerns of how to create difference wave between two > conditions. Here is what I want to look at: > > I have grand average time-freqency data of two conditions ("GA1","GA2"), > and one behavioural measurement. Now I want to do so some > regression/correlation analysis between the behavioural measurement and the > contrasted time-freqency data (GA1-GA2). > > I did some googling and it is suggested to create the difference wave > first, as per here (http://www.fieldtriptoolbox.o > rg/faq/how_can_i_test_an_interaction_effect_using_cluster- > based_permutation_tests). > > From these 4 data structures, you now make 2 difference data structures in > the following way: > > - Copy GA11 to GAdiff11_12 and perform the assignment > GAdiff11_12.avg=GA11.avg-GA12.avg. > - Copy GA21 to GAdiff21_22 and perform the assignment > GAdiff21_22.avg=GA21.avg-GA22.avg. > > > I got confused about the '.avg' here. Powspctrm is 4-d data in each GA > (subject.channel.frequency.time); so what is and how to calculate the > average (.avg) in each GA structure. > > Or is it just a filed in each GA as I cannot find one. > > Thanks a lot > > *-------------* > *Mr Xianwei Che* > *PhD Candidate* > *Monash Alfred Psychiatry Research Centre (MAPrc)* > *Central Clinical School & the Alfred * > *Monash University* > *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* > -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Thu Sep 22 20:55:07 2016 From: mklados at gmail.com (Manousos Klados) Date: Thu, 22 Sep 2016 14:55:07 -0400 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From Elana.Harris at cchmc.org Fri Sep 23 19:21:15 2016 From: Elana.Harris at cchmc.org (Harris, Elana) Date: Fri, 23 Sep 2016 17:21:15 +0000 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: References: Message-ID: <1cfe2a63112349099f027f080d671a30@cchmc.org> Hello, Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? Thanks, Elana ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Nugent, Allison C. (NIH/NIMH) [E] Sent: Wednesday, August 24, 2016 12:11 PM To: 'fieldtrip at science.ru.nl' Subject: [FieldTrip] NIH MEG Workshop Reminder! A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. At this meeting, we plan to address the following four themes: 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? 3. How can we develop and support infrastructure to share data and facilitate big science? 4. How could an MEG-North America consortium work to address these issues? Keynote Speakers: Sylvain Baillet, PhD, Director, MEG Core McGill University, McConnell Brain Imaging Center Dimitrios Pantazis, PhD, Director of MEG Lab, Martinos Imaging Center Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia Julia M. Stephen, PhD, Director, MEG/EEG Core, The Mind Research Network For more details, visit http://megworkshop.nih.gov Registration to this NIH sponsored event is free of charge. We hope to see you in Bethesda in November! Dr. Richard Coppola, Director, NIMH MEG Core Dr. Allison C Nugent, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH Register Now at Eventbrite! Allison Nugent, PhD Director of Neuroimaging Research Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph 301-451-8863 -------------- next part -------------- An HTML attachment was scrubbed... URL: From Douglas.Rose at cchmc.org Fri Sep 23 22:39:46 2016 From: Douglas.Rose at cchmc.org (Rose, Douglas) Date: Fri, 23 Sep 2016 20:39:46 +0000 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: <1cfe2a63112349099f027f080d671a30@cchmc.org> References: <1cfe2a63112349099f027f080d671a30@cchmc.org> Message-ID: <2EBA7945365E4C4498225168A217A7C8975AE4A0@MCEXMB2.chmccorp.cchmc.org> Congrats on going to workshop. Used to live in DC so did not ever need to use hotels. Hotels there in Bethesda probably very expensive. Hotels.com might be helpful. You could probably write Rich Coppola for suggestions. There is the Metro station on campus and some buses perhaps from there to the NIMH station where conference is. So some not too expensive hotel on the same Metro line might be good. Doug From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Harris, Elana Sent: Friday, September 23, 2016 1:21 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] NIH MEG Workshop Hello, Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? Thanks, Elana ________________________________ From: fieldtrip-bounces at science.ru.nl > on behalf of Nugent, Allison C. (NIH/NIMH) [E] > Sent: Wednesday, August 24, 2016 12:11 PM To: 'fieldtrip at science.ru.nl' Subject: [FieldTrip] NIH MEG Workshop Reminder! A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. At this meeting, we plan to address the following four themes: 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? 3. How can we develop and support infrastructure to share data and facilitate big science? 4. How could an MEG-North America consortium work to address these issues? Keynote Speakers: Sylvain Baillet, PhD, Director, MEG Core McGill University, McConnell Brain Imaging Center Dimitrios Pantazis, PhD, Director of MEG Lab, Martinos Imaging Center Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia Julia M. Stephen, PhD, Director, MEG/EEG Core, The Mind Research Network For more details, visit http://megworkshop.nih.gov Registration to this NIH sponsored event is free of charge. We hope to see you in Bethesda in November! Dr. Richard Coppola, Director, NIMH MEG Core Dr. Allison C Nugent, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH Register Now at Eventbrite! Allison Nugent, PhD Director of Neuroimaging Research Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph 301-451-8863 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nick.peatfield at gmail.com Sat Sep 24 01:55:27 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Fri, 23 Sep 2016 16:55:27 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM Message-ID: Hi all, I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. With Regards, Nick [image: Inline images 1] -- Nicholas Peatfield, PhD -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image (3).png Type: image/png Size: 80865 bytes Desc: not available URL: From a.stolk8 at gmail.com Sat Sep 24 03:46:04 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Fri, 23 Sep 2016 18:46:04 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: References: Message-ID: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Hi Nick, You may want to have a look at ft_convert_coordsys which can switch volumes between different coordinate systems. Best, Arjen > On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield wrote: > > Hi all, > > I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). > > So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). > > Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. > > With Regards, > > Nick > > > > -- > Nicholas Peatfield, PhD > > _______________________________________________ > 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 nick.peatfield at gmail.com Sat Sep 24 06:24:10 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Fri, 23 Sep 2016 21:24:10 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Message-ID: Hi Arjen, Yeah I looked into that but spm to ctf is not supported. And changing the grads to spm seems also not possible. Unless I use ft realignsens but the behaviour of that seems a little weird in my experience, and seems more suited to electrodes. Cheers Nick On Sep 23, 2016 7:35 PM, "Arjen Stolk" wrote: > Hi Nick, > > You may want to have a look at ft_convert_coordsys which can switch > volumes between different coordinate systems. > > Best, > Arjen > > On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield < > nick.peatfield at gmail.com> wrote: > > Hi all, > > I'm getting into a problem wherein I have headmodel that are in SPM space > and the grads are in CTF space. I would usually keep all the headmodels in > CTF space and align based on that but for this dataset and the format of > the MRIs,POS etc... there seems to be some problems (could take longer to > explain but lets keep this brief). > > So this of course leads to the issue that the grad and the headmodel > within beamformer_lcmv is misaligned by 90 degrees, which is of course not > good. Is there a quick solution that I have not come across to either > convert the headmodel to ctf or convert the grad structure to spm coordsys? > When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys > = 'ctf') but the outputted sourcemodel is still misaligned between the > headmodel and the grads (see attached image - oh and the lf is also > misaligned of course). > > Any help would be greatly appreciated. And I hope that this question > hasn't come up before as I did quite a bit of google searching before > sending this email. > > With Regards, > > Nick > > > > -- > Nicholas Peatfield, PhD > > _______________________________________________ > 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 Sat Sep 24 13:27:10 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sat, 24 Sep 2016 11:27:10 +0000 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Message-ID: <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> Hi Nick, You need to use the anatomical MRI that you used to create your headmodel etc., register it to ctf-space using ft_volumerealign (in the interactive mode, it seems), and then use some magical matrix multiplications to get the appropriate transformation matrix that can be applied to the headmodel (to get it in ctf space), or (when taking the inverse of this transformation matrix) to the grad structure (to get it in spm space). The solution is embedded here: http://www.fieldtriptoolbox.org/tutorial/minimumnormestimate look for the transform_vox2spm and transform_vox2ctf, and the magical variable T. Best, Jan-Mathijs On 24 Sep 2016, at 06:24, Nicholas A. Peatfield > wrote: Hi Arjen, Yeah I looked into that but spm to ctf is not supported. And changing the grads to spm seems also not possible. Unless I use ft realignsens but the behaviour of that seems a little weird in my experience, and seems more suited to electrodes. Cheers Nick On Sep 23, 2016 7:35 PM, "Arjen Stolk" > wrote: Hi Nick, You may want to have a look at ft_convert_coordsys which can switch volumes between different coordinate systems. Best, Arjen On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield > wrote: Hi all, I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. With Regards, Nick -- Nicholas Peatfield, PhD _______________________________________________ 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 nick.peatfield at gmail.com Sat Sep 24 22:35:36 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Sat, 24 Sep 2016 13:35:36 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> Message-ID: Hi Jan-Mathijs, I found the magical variable T - thanks for the solution! Regards, Nick On 24 September 2016 at 04:27, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Hi Nick, > > You need to use the anatomical MRI that you used to create your headmodel > etc., register it to ctf-space using ft_volumerealign (in the interactive > mode, it seems), and then use some magical matrix multiplications to get > the appropriate transformation matrix that can be applied to the headmodel > (to get it in ctf space), or (when taking the inverse of this > transformation matrix) to the grad structure (to get it in spm space). > > The solution is embedded here: http://www.fieldtriptoolbox.org/tutorial/ > minimumnormestimate > > look for the transform_vox2spm and transform_vox2ctf, and the magical > variable T. > > Best, > Jan-Mathijs > > > On 24 Sep 2016, at 06:24, Nicholas A. Peatfield > wrote: > > Hi Arjen, > > Yeah I looked into that but spm to ctf is not supported. And changing the > grads to spm seems also not possible. Unless I use ft realignsens but the > behaviour of that seems a little weird in my experience, and seems more > suited to electrodes. > > Cheers > > Nick > > On Sep 23, 2016 7:35 PM, "Arjen Stolk" wrote: > >> Hi Nick, >> >> You may want to have a look at ft_convert_coordsys which can switch >> volumes between different coordinate systems. >> >> Best, >> Arjen >> >> On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield < >> nick.peatfield at gmail.com> wrote: >> >> Hi all, >> >> I'm getting into a problem wherein I have headmodel that are in SPM space >> and the grads are in CTF space. I would usually keep all the headmodels in >> CTF space and align based on that but for this dataset and the format of >> the MRIs,POS etc... there seems to be some problems (could take longer to >> explain but lets keep this brief). >> >> So this of course leads to the issue that the grad and the headmodel >> within beamformer_lcmv is misaligned by 90 degrees, which is of course not >> good. Is there a quick solution that I have not come across to either >> convert the headmodel to ctf or convert the grad structure to spm coordsys? >> When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys >> = 'ctf') but the outputted sourcemodel is still misaligned between the >> headmodel and the grads (see attached image - oh and the lf is also >> misaligned of course). >> >> Any help would be greatly appreciated. And I hope that this question >> hasn't come up before as I did quite a bit of google searching before >> sending this email. >> >> With Regards, >> >> Nick >> >> >> >> -- >> Nicholas Peatfield, PhD >> >> _______________________________________________ >> 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 > -- Nicholas Peatfield, PhD -------------- next part -------------- An HTML attachment was scrubbed... URL: From dkicic at gmail.com Sat Sep 24 22:46:28 2016 From: dkicic at gmail.com (Dubravko Kicic) Date: Sat, 24 Sep 2016 22:46:28 +0200 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: <1cfe2a63112349099f027f080d671a30@cchmc.org> References: <1cfe2a63112349099f027f080d671a30@cchmc.org> Message-ID: Dear Elana, I recently stayed in DoubleTree by Hilton Bethesda, which is some 10 minutes walk from NIH campus. The prices were not that expensive, some 160 USD per night (dependining on current events, though). The hotel is very clean and the service is good. Very quiet rooms, good sleep. The from opposite side of the hotel there is a super nice residential area, excellent for a morning walk or jogging. At the rear side, on 5 minutes walk there are streets with very cosy restaurants and bars. Metro station is 5 minutes walk towards the city, and the other one is at about 10 minutes walk in NIH campus. A highly recommended hotel! Best regards! Dubravko Dubravko Kičić, Ph.D., EMBA CEO & President of the Board Bicro BIOCentre Ltd. Biosciences Technology Commercialisation and Incubation Centre Borongajska cesta 83h, 10000 Zagreb, CROATIA E-mail: dubravko.kicic at biocentre.hr T: +385 1 6458 643 | M: +385 91 5956 569 | W: www.biocentre.hr > On 23 Sep 2016, at 19:21, Harris, Elana wrote: > > Hello, > > Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? > > Thanks, > > Elana > > > From: fieldtrip-bounces at science.ru.nl > on behalf of Nugent, Allison C. (NIH/NIMH) [E] > > Sent: Wednesday, August 24, 2016 12:11 PM > To: 'fieldtrip at science.ru.nl ' > Subject: [FieldTrip] NIH MEG Workshop > > Reminder! > > A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. > > At this meeting, we plan to address the following four themes: > > 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? > 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? > 3. How can we develop and support infrastructure to share data and facilitate big science? > 4. How could an MEG-North America consortium work to address these issues? > > Keynote Speakers: > > Sylvain Baillet, PhD , Director, MEG Core McGill University, McConnell Brain Imaging Center > Dimitrios Pantazis, PhD , Director of MEG Lab, Martinos Imaging Center > Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children’s Hospital of Philadelphia > Julia M. Stephen, PhD , Director, MEG/EEG Core, The Mind Research Network > > For more details, visit http://megworkshop.nih.gov > > Registration to this NIH sponsored event is free of charge. > > We hope to see you in Bethesda in November! > > Dr. Richard Coppola , Director, NIMH MEG Core > Dr. Allison C Nugent , Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH > > Register Now at Eventbrite! > > > Allison Nugent, PhD > Director of Neuroimaging Research > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph 301-451-8863 > > > _______________________________________________ > 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 na.so.ir at gmail.com Mon Sep 26 08:50:03 2016 From: na.so.ir at gmail.com (Narjes Soltani) Date: Mon, 26 Sep 2016 10:20:03 +0330 Subject: [FieldTrip] Change in configuration file Message-ID: Hi I am writing my own trial function in fieldtrip and I need to pass some additional information as input argument to this function, but I wonder if it is also possible to include these information in ft_definetrial configuration file instead of passing them as input argument in the function. I checked the already available parameters in ft_definetrial configuration file, but none of them seemed to be useful for me for passing the new information I need for further processing. Best Regards Narjes Soltani -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Sep 26 10:13:36 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 26 Sep 2016 08:13:36 +0000 Subject: [FieldTrip] Change in configuration file In-Reply-To: References: Message-ID: <3328E538-26E3-49C4-A322-36CB35D81B37@donders.ru.nl> Hi Narjes, I believe you could put the required creative stuff in cfg.trialdef. This should pass unscathed through ft_definetrial into the trialfun. Best, Jan-Mathijs > On 26 Sep 2016, at 08:50, Narjes Soltani wrote: > > Hi > I am writing my own trial function in fieldtrip and I need to pass some additional information as input argument to this function, but I wonder if it is also possible to include these information in ft_definetrial configuration file instead of passing them as input argument in the function. I checked the already available parameters in ft_definetrial configuration file, but none of them seemed to be useful for me for passing the new information I need for further processing. > > > Best Regards > Narjes Soltani > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From mklados at gmail.com Mon Sep 26 20:55:06 2016 From: mklados at gmail.com (Manousos Klados) Date: Mon, 26 Sep 2016 11:55:06 -0700 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From pooneh.baniasad at gmail.com Tue Sep 27 13:15:20 2016 From: pooneh.baniasad at gmail.com (pooneh baniasad) Date: Tue, 27 Sep 2016 14:45:20 +0330 Subject: [FieldTrip] Fwd: Convert MNI to ctf In-Reply-To: References: Message-ID: Dear FieldTrip community ​I'm using the 'Subject01.mri'​ for constructing BEM headmodel for EEG source analysis which is defined in ctf coordination. On the other hand I use 'cortex_20484.surf.gii' which is defined in MNI coordination for adding the dipole sources. I want to convert the MNI into ctf to match the headmodel with template. I already found ft_volumenormalise function although it needs the inputs that I don't know what are they. ​ Can anyone help me? -- Bests Pouneh Baniasad -------------- next part -------------- An HTML attachment was scrubbed... URL: From elisabethsusanne.may at gmail.com Tue Sep 27 14:46:55 2016 From: elisabethsusanne.may at gmail.com (Elisabeth May) Date: Tue, 27 Sep 2016 14:46:55 +0200 Subject: [FieldTrip] Question about cluster-based permutation tests on linear mixed models Message-ID: Dear FieldTripers, I have a question about the potential use of cluster-based permutation tests for results obtained using linear mixed models. We are working with data from a 10 min EEG experiment on source level with the aim to quantify the relationship of brain activity in different frequency bands with continous perceptual ratings across 20 subjects in different experimental conditions. Thus, we have 10 min time courses of brain activity and ratings for each voxel for different conditions and want to test a) if there are significant relationships in the single conditions and b) if these relationships differ between two conditions. To this end, I have calculated linear mixed models in R using the lme4 toolbox. For both the single condition relationships and the condition contrasts, they result in a single t-value (and a corresponding p-value), which is based on information on both the single subject and the group level (i.e. we perform a multi-level analysis). However, with more than 2000 voxels, we have a lot of t-values and are wondering if there is a way to apply cluster-based tests to correct for multiple comparisons. The main problem I see is that I only have one multilevel t-value for the effect across all subjects, i.e. I don't have single subjects values, which I could then e.g. randomize between conditions as normally done in cluster-based permutation tests. (Or rather, I would be able to extract single subject values but would then loose the advantage of the multi-level analysis.) I found an old thread in the mailinglist archive where it was suggested to flip the signs of the t-statistic for cluster-level correction ( https://mailman.science.ru.nl/pipermail/fieldtrip/2012-July/005375.html). I understand that, in our case, I would do this randomly for all voxels in each randomization and then build spatial clusters on the resulting (partly flipped) t-values. However, I am not sure if that is a valid approach based on the null hypothesis that there are no significant relations in my single conditions (a) or no significant relationship differences in my condition contrasts (b). For the condition contrasts, I would be able to permute the condition labels as normally done in cluster-based permutation tests,I think, but would then have to recalculate the linear mixed models for all voxels in every permutation. This would result in a very high computational load. Does anyone have any experience with this kind of analysis? Would the flipping of t-values be a valid approach (and if yes, is there anything to keep in mind in particular)? Can you think of other ways to combine linear mixed models with a multiple comparison correction on the cluster level? Any help would be greatly appreciated! Best wishes from Munich, Elisabeth -- Elisabeth S. May, PhD Klinikum rechts der Isar Technische Universität München Ismaninger Str. 22 81675 München http://www.painlabmunich.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From caspervanheck at gmail.com Tue Sep 27 15:32:59 2016 From: caspervanheck at gmail.com (Casper van Heck) Date: Tue, 27 Sep 2016 15:32:59 +0200 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Christine, As there are only a few possibilities, this might work! We'll try that! Dear Vladimir, If the original reference is close to an electrode we're interested in, and we do not see an effect on that electrode, then we cannot determine if there is indeed no effect or if the original reference made the effect disappear (due to it also 'seeing' the same activity). Thanks, all! Best regards, Casper On 21 September 2016 at 16:26, Vladimir Litvak wrote: > If you need to know the reference for analysis purposes the easiest thing > is to just rereference to another electrode or the average reference. Then > it wouldn't matter what the original reference was. > > Best, > > Vladimir > > On Wed, Sep 21, 2016 at 1:57 PM, Blume Christine < > christine.blume at sbg.ac.at> wrote: > >> Dear Casper and Tineke, >> >> >> >> As voltage is always the difference between the reference and an >> electrode, voltages are lowest for electrodes closest to the reference >> electrode. You could check where voltages are minimal across trials and for >> each participant. If then for example that is close to Cz, it is likely >> that data were referenced to the vertex. Just an idea, it might work…but >> perhaps someone else has a better idea? >> >> >> >> Best, >> >> Christine >> >> >> >> *Von:* fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at scie >> nce.ru.nl] *Im Auftrag von *Casper van Heck >> *Gesendet:* Mittwoch, 21. September 2016 14:25 >> *An:* fieldtrip at science.ru.nl >> *Betreff:* [FieldTrip] Lost reference location >> >> >> >> Dear all, >> >> >> >> We've recently started working on an old dataset, but have ran into a >> problem; nobody bothered to write down where the reference was placed... >> Does anybody have ideas on how to reconstruct the location of the >> reference, based on (some aspect of) the data? >> >> >> >> Best regards, >> >> >> >> Casper van Heck and Tineke van Rijn >> >> _______________________________________________ >> 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 carsten.wolters at uni-muenster.de Wed Sep 28 15:30:20 2016 From: carsten.wolters at uni-muenster.de (Carsten Wolters) Date: Wed, 28 Sep 2016 15:30:20 +0200 Subject: [FieldTrip] Ref. 11890: Neuroscientist(s) with focus on simulation of high-definition transcranial electric stimulation (hd-tES) Message-ID: <57EBC5EC.3080700@uni-muenster.de> Dear colleagues, please forward the ad below to anyone who could be interested and post to your departmental lists. Thanks and sorry for possible multiple postings. I will be on Biomag2016 in Seoul from Oct.1-6 and would be happy to discuss with possible candidates. Best regards Carsten Wolters ********************************************************************************************************* Neuroscientist(s) with focus on simulation of high-definition transcranial electric stimulation (hd-tES) Ref. 11890 The*Institute for Biomagnetism and Biosignalanalysis* at the medical faculty of the University of Münster, Germany, invites applications for a PostDoctoral Researcher and/or for Doctoral Students *Salary according to TV-L E13 **(100% or 50 %)** **Full-Time with 38,5 (hours/week) or Part-Time with 19,25 (hours/week)** *** for three year positions to work on the development and evaluation of new (i.e., new inverse electrode optimization and new forward finite element method algorithms) simulation approaches for hd-tES using realistic head volume conductor models within the DFG-funded priority program SPP1665/2 (second funding period: from 2016 to 2019) “Resolving and manipulating neuronal networks in the mammalian brain - from correlative to causal analysis” in project “Individualized closed-loop transcranial alternating current stimulation”. More informations can be found on http://www.spp1665.de/. The successful applicant holds a PhD degree and/or a Master’s degree (or equivalent) in a relevant academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, or equivalent) and experience with the Linux operating system is expected, because large software toolboxes are used and further developed. The working language at the institute is English. Experience with brain stimulation and with the measurement and analysis of brain signals is advantageous, but not essential. The applicant’s merits are assessed on the basis of the quality of PhD and/or Master’s level studies and thesis, previous experience with numerical mathematics, inverse problems and optimization approaches, software development, motivation and research interests. The location for this research will mainly be the workgroups “SIM-NEURO: Simulation, Imaging and Modeling of NEUROnal networks in the human brain” of PD Dr. Wolters at the Institute for Biomagnetism and Biosignalanalysis (IBB), “Imaging” of Prof. Dr. Martin Burger at the Institute for Computational and Applied Mathematics and “Applications of Partial Differential Equations” of JProf. Dr. Christian Engwer, all at the University of Münster in Germany. Expected close collaborations and visits are to the partnering institutes, namely the University of Oldenburg (Prof. Dr. Christoph Herrmann) and the University of Hamburg (Dr. Till Schneider). The application should include a statement of research interests and reasons for applying to the project, a curriculum vitae (max. 5 pages) composed according to good scientific practice, a certificate of PhD and/or Master’s degree, copy of the master’s thesis and grades of Master’s level studies, the names and e-mail addresses of two referees and a proof of proficiency in English. The position will be open until filled. To apply for the position until *Oct.31*, *2016*, please send the above documents as pdfs to *PD Dr. Carsten Wolters, **Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, 48149 Münster, Germany*, or by Email to *carsten.wolters(at)­uni-muenster(dot)­de* . For additional information please contact *PD Dr. Carsten Wolters* (Email: *carsten.wolters(at)­uni-muenster(dot)­de* , Phone: +49 (0)251/83-56904). Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference. Link to the position: http://klinikum.uni-muenster.de/index.php?id=3290&tx_ttnews[tt_news]=6562&cHash=afb5f5f3421732c32f5c0de0bfc6587c -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: carsten_wolters.vcf Type: text/x-vcard Size: 402 bytes Desc: not available URL: From joseluisblues at gmail.com Wed Sep 28 17:02:39 2016 From: joseluisblues at gmail.com (Jose) Date: Wed, 28 Sep 2016 17:02:39 +0200 Subject: [FieldTrip] axial gradiometers vs planar gradient Message-ID: dear fieldtrip community, I'm working with CTF MEG data, I have a confusion regarding the use of the (pure) axial gradiometers and the synthetic planar gradients, >From what I have read "the planar field gradient simplifies the interpretation of the sensor-level data because the maximal signal power is located above the source". In practice, this means that the topography would resemble more the sources? Is that correct? Would be meaningless to do this if one intend to do source analyses anyway? However is not clear for me if the planar gradient is used only for visualization purposes, or if is intended to replace the use of axial gradiometers for data analysis. Some papers do mention the aforementioned transformation but then they do not specify which data is used to run statistical analysis so I assume they do it with planar gradients. Others they clearly perform statistical analyses such as non-parametric cluster permutation tests with planar gradient data. So, the second question would be if one should run statistical analyses in planar gradient or axial gradiometers data?. What is the criteria to choose one or the other? If one apply cluster-based permutation tests to either axial gradiometers or the planar gradient one will find distinct results because the activity is distributed in different sensors, so distinct clusters will be observed, right? Does make sense to find different results depending on whether we analyze gradiometer or planar data? Some recommend use planar gradient data to perform statistics ( https://mailman.science.ru.nl/pipermail/fieldtrip/2012-November/005905.html) while others other advise against it ( https://mailman.science.ru.nl/pipermail/fieldtrip/2010-March/002657.html), Is there a consensus at the moment? I would really appreciate some directions here, best, Jose -------------- next part -------------- An HTML attachment was scrubbed... URL: From tomh at kurage.nimh.nih.gov Wed Sep 28 17:48:18 2016 From: tomh at kurage.nimh.nih.gov (Tom Holroyd) Date: Wed, 28 Sep 2016 11:48:18 -0400 Subject: [FieldTrip] axial gradiometers vs planar gradient In-Reply-To: References: Message-ID: <20160928114818.73806877@kurage.nimh.nih.gov> On Wed, 28 Sep 2016 17:02:39 +0200 Jose wrote: > dear fieldtrip community, > > I'm working with CTF MEG data, > I have a confusion regarding the use of the (pure) axial gradiometers and > the synthetic planar gradients, If you are doing source localization, there is no reason to convert to planar. It can only degrade the data, because it is an interpolation. -- Dr. Tom -- "A man of genius makes no mistakes. His errors are volitional and are the portals of discovery." -- James Joyce From joseluisblues at gmail.com Wed Sep 28 18:05:15 2016 From: joseluisblues at gmail.com (Jose) Date: Wed, 28 Sep 2016 18:05:15 +0200 Subject: [FieldTrip] axial gradiometers vs planar gradient In-Reply-To: <20160928114818.73806877@kurage.nimh.nih.gov> References: <20160928114818.73806877@kurage.nimh.nih.gov> Message-ID: Thanks Tom, Yes, I've read that for performing source reconstruction one use the axial gradiometer data, But, at the moment I'm at the sensor-level analysis, best Jose -------------- next part -------------- An HTML attachment was scrubbed... URL: From robert.oostenveld at donders.ru.nl Wed Sep 28 19:05:07 2016 From: robert.oostenveld at donders.ru.nl (Oostenveld, R. (Robert)) Date: Wed, 28 Sep 2016 17:05:07 +0000 Subject: [FieldTrip] Fwd: open engineer position focused on EEG of baby brains References: Message-ID: <5C55D865-B79F-440B-94EF-4297553C4099@donders.ru.nl> Begin forwarded message: From: Virginie van Wassenhove > Subject: [FieldTrip-news] Fwd: Offre de poste Stat Date: 28 September 2016 at 11:46:34 GMT+2 To: >, > Cc: Ghislaine Dehaene > Dear all, please find below information about an open engineer position focused on EEG of baby brains. Best, Virginie Engineer/Statistician position The INSERM / CEA Development of Neuroimaging lab in Neurospin, Saclay (91, France) offers a 2 to 5 years position for a research engineer or statistician to develop robust processing and analysis methods of infants’ brain signal measured by magnetic resonance imaging (MRI) and electroencephalography (EEG). Brain imaging techniques provide large amounts of data that require new analysis techniques and a robust control of the reliability of the results, particularly in infants whose patience is minimal, the vigilance variable and the movements important. All these factors affect the quality of the signal. Furthermore infants’ spontaneous activity is variable and ample generating greater endogenous background noise than in adults. The aim of the work will be to 1) Develop robust pipelines for EEG/MRI data processing taking into account the infants’ signal characteristics in order to robustly extract the brain activity associated with a cognitive task from the endogenous and exogenous noise 2) Characterize the properties of the endogenous brain activity and its maturation during the first year of life in order to understand the functional architecture of the main networks that allow the development of complex cognitive functions (e.g. language, consciousness) in the human species. Applicants should possess a solid technical background in signal processing and/or statistics and be able to code in Matlab and/or Python. The position is opened for a maximum of 5 years, funded by a European contract (CDD use) from 1 November 2016. Salary is based on qualifications (from 1900 euros / month, medical insurance comprised) Send your CV and a motivation letter to ghislaine.dehaene at cea.fr Lab Website http://www.unicog.org/site_2016/ Ghislaine Dehaene-Lambertz, M.D., Ph.D. Director of the Developmental Neuroimaging Lab http://moncerveaualecole.com/ ################################################# Developmental Neuroimaging Lab INSERM, U992 CEA/SAC/DSV/DRM/NeuroSpin Bat 145, point courrier 156 91191 GIF/YVETTE, France Phone: +33 1 69 08 81 72 Fax: +33 1 69 08 79 73 Mail: ghislaineDOTdehaeneAROBASEcea.fr www.unicog.org Publications in http://www.unicog.org/biblio/Author/DEHAENE-LAMBERTZ-G.html ################################################# -- Virginie van Wassenhove CEA/NeuroSpin MEG - UNICOG Bat 145 PC 156 F-91191 Gif s/ Yvette FRANCE office: +33(0)1 69 08 1667 cell: +33(0)6 15 83 4955 skype, twitter: virginie_vw sites.google.com/site/virginievanwassenhove/ _______________________________________________ fieldtrip-news mailing list fieldtrip-news at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip-news -------------- next part -------------- An HTML attachment was scrubbed... URL: From bioeng.yoosofzadeh at gmail.com Wed Sep 28 19:28:25 2016 From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh) Date: Wed, 28 Sep 2016 13:28:25 -0400 Subject: [FieldTrip] Fwd: Issue with projection In-Reply-To: References: Message-ID: Hi all, I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). Any comment would be appreciated! Best, Vahab -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: sample_resutls.png Type: image/png Size: 321899 bytes Desc: not available URL: From tzvetan.popov at uni-konstanz.de Wed Sep 28 20:22:04 2016 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Wed, 28 Sep 2016 20:22:04 +0200 Subject: [FieldTrip] Fwd: Issue with projection In-Reply-To: References: Message-ID: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> Hi Vehab, You have to normalize the individual volume to the MNI template. So use ft_volumenormalise first and try again. Or, if you used MNI aligned grid that specify the source.pos = template grid.pos. Good luck Tzvetan > Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh : > > Hi all, > > I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). > > Any comment would be appreciated! > > Best, > Vahab > > _______________________________________________ > 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 Thu Sep 29 14:24:23 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 29 Sep 2016 12:24:23 +0000 Subject: [FieldTrip] Issue with projection In-Reply-To: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> References: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> Message-ID: <286F8441-A34B-41E4-8892-435AAF19AD4F@donders.ru.nl> In addition to Tzvetan’s comment: please do not try and interpolate directly onto the inflated cortical sheet. You also need to provide the non-inflated sheet for the interpolation (after which the interpolated data can be displayed on the inflated sheet). Jan-Mathijs On 28 Sep 2016, at 20:22, Tzvetan Popov > wrote: Hi Vehab, You have to normalize the individual volume to the MNI template. So use ft_volumenormalise first and try again. Or, if you used MNI aligned grid that specify the source.pos = template grid.pos. Good luck Tzvetan Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh >: Hi all, I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). Any comment would be appreciated! Best, Vahab _______________________________________________ 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 bioeng.yoosofzadeh at gmail.com Thu Sep 29 14:54:50 2016 From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh) Date: Thu, 29 Sep 2016 08:54:50 -0400 Subject: [FieldTrip] fieldtrip Digest, Vol 70, Issue 27 In-Reply-To: References: Message-ID: Dear Tzvetan, I really appreciate your help. Actually, I tried ft_volumenormalise before however with no success. When I saw your comments, I tried again. It turns out that there is an issue with my older Matlab (2012b). Now, I tried with Matlab 2016 and it worked perfectly :D Thank you again, Vahab On Thu, Sep 29, 2016 at 6:00 AM, wrote: > 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. Re: Fwd: Issue with projection (Tzvetan Popov) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Wed, 28 Sep 2016 20:22:04 +0200 > From: Tzvetan Popov > To: FieldTrip discussion list > Subject: Re: [FieldTrip] Fwd: Issue with projection > Message-ID: <896534AC-FD7B-4429-AC23-3F227E50097D at uni-konstanz.de> > Content-Type: text/plain; charset="us-ascii" > > Hi Vehab, > You have to normalize the individual volume to the MNI template. So use > ft_volumenormalise first and try again. Or, if you used MNI aligned grid > that specify the source.pos = template grid.pos. > Good luck > Tzvetan > > > Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh < > bioeng.yoosofzadeh at gmail.com>: > > > > Hi all, > > > > I am having an issue in projecting my results on a (template) cortical > map in FT and using ft_sourceplot. It seems a subset of the brain > activations has only been projected (see attached). > > > > Any comment would be appreciated! > > > > Best, > > Vahab > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: attachments/20160928/5c685362/attachment-0001.html> > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 70, Issue 27 > ***************************************** > -------------- next part -------------- An HTML attachment was scrubbed... URL: From knutsenpm at gmail.com Fri Sep 30 15:11:44 2016 From: knutsenpm at gmail.com (Per Knutsen) Date: Fri, 30 Sep 2016 15:11:44 +0200 Subject: [FieldTrip] Reading data from arbitrary source Message-ID: Hi, I am new to fieldtrip with the intention of analyzing mouse ECoG/LFP data. I already have my datasets loaded into Matlab (from a format not directly supported by fieldtrip). Next, I need to read this data into a fieldtrip structure for processing. I see frequent use of a structure called cfg, with fields: cfg.dataset cfg.trialdef.threshold cfg.trialdef.prestim cfg.trialdef.poststim etc Can anyone direct me to the documentation of this structure's format. What data is stored, what is the format, units etc? *Per M Knutsen* University of Oslo Dept. of Molecular Medicine, Physiology Sect. PB 1103 Blindern, NO-0317 Oslo +47.45103762 -------------- next part -------------- An HTML attachment was scrubbed... URL: From dlozanosoldevilla at gmail.com Fri Sep 30 15:25:14 2016 From: dlozanosoldevilla at gmail.com (Diego Lozano-Soldevilla) Date: Fri, 30 Sep 2016 15:25:14 +0200 Subject: [FieldTrip] Reading data from arbitrary source In-Reply-To: References: Message-ID: Hi Per, These two FAQs will be relevant to you: http://www.fieldtriptoolbox.org/faq/how_can_i_import_my_own_dataformat http://www.fieldtriptoolbox.org/faq/how_are_the_various_data_structures_defined best, Diego On 30 September 2016 at 15:11, Per Knutsen wrote: > Hi, > I am new to fieldtrip with the intention of analyzing mouse ECoG/LFP data. > > I already have my datasets loaded into Matlab (from a format not directly > supported by fieldtrip). Next, I need to read this data into a fieldtrip > structure for processing. I see frequent use of a structure called cfg, > with fields: > > cfg.dataset > cfg.trialdef.threshold > cfg.trialdef.prestim > cfg.trialdef.poststim > > etc > > Can anyone direct me to the documentation of this structure's format. What > data is stored, what is the format, units etc? > > > *Per M Knutsen* > University of Oslo > Dept. of Molecular Medicine, Physiology Sect. > PB 1103 Blindern, NO-0317 Oslo > +47.45103762 > > _______________________________________________ > 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 susmitasen.ece at gmail.com Fri Sep 30 19:16:52 2016 From: susmitasen.ece at gmail.com (Susmita Sen) Date: Fri, 30 Sep 2016 22:46:52 +0530 Subject: [FieldTrip] Regarding headmodel construction Message-ID: I am Susmita Sen, MS research scholar in the dept of Electronics and Electrical Communication Engineering, IIT Kharagpur. I am currently working on MEG data recorded by yokogawa system. I want to perform source reconstruction on the data. However, I do not have the MRI data along with that. so, I have planned to use the standard MRI provided by fieldtrip (downloaded from https://github.com/fieldtrip/ fieldtrip/blob/master/template/headmodel/standard_mri.mat). For preparing the head model I have followed the steps provided in the fieldtrip tutorial (http://www.fieldtriptoolbox.org/tutorial/headmodel_meg ). %% align the coordinate system load('standard_mri.mat'); % load mri data disp(mri) cfg = []; cfg.method = 'interactive'; cfg.coordsys = 'yokogawa'; cfg.snapshot = 'yes'; [mri_aligned] = ft_volumerealign(cfg,mri); %% SEGMENTATION cfg = []; cfg.output = 'brain'; segmentedmri = ft_volumesegment(cfg, mri_aligned); %% create headmodel cfg = []; cfg.method='singleshell'; vol = ft_prepare_headmodel(cfg, segmentedmri); %% visualize load grad % load gradiometer info vol = ft_convert_units(vol,'cm'); % the gradiometer info is given in cm figure; ft_plot_sens(grad, 'style', '*b'); hold on ft_plot_vol(vol); while aligning the coordinate system I have chosen fiducial points (naison, LPA and RPA) using the instruction given by http://neuroimage.usc.edu/ brainstorm/CoordinateSystems. I am attaching the figures that display the shape of the 'vol' along with the position of the sensors (from different viewing angle). However, I doubt the headmodel is corrected prepared (It dosen't look alike the figure given in the tutorial). It seems I have made some mistakes, but I am not able to detect it. I would be very thankful if you can help me in this regard. Thanks and Regards, Susmita Sen Research Scholar Audio and Bio Signal Processing Lab. E & ECE Dept. IIT Kharagpur -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol1.png Type: image/png Size: 20100 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol2.png Type: image/png Size: 22926 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol3.png Type: image/png Size: 26661 bytes Desc: not available URL: From mikexcohen at gmail.com Thu Sep 1 13:38:12 2016 From: mikexcohen at gmail.com (Mike X Cohen) Date: Thu, 1 Sep 2016 13:38:12 +0200 Subject: [FieldTrip] Biomag 2016 Data Analysis Competition Message-ID: Dear all, We are happy to announce a deadline extension (to September 20th) for three data-analysis competitions at Biomag 2016. Please see details at http://www.biomag2016.org/data_analysis_competition.php The aim of the competitions is to promote the development and application of new analysis techniques. The challenges will help to elucidate pros and cons of different techniques and attract experts from outside the MEG field. The winners of the competition will be given the opportunity to present their proposal at the Biomag meeting in Seoul (Oct 1-6) in order to spark discussions on analysis. Please encourage colleagues to participate! Best regards, Ole Jensen (sent by Mike Cohen, and on behalf of all competition organizers) -- Mike X Cohen, PhD mikexcohen.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From mikexcohen at gmail.com Thu Sep 1 13:58:36 2016 From: mikexcohen at gmail.com (Mike X Cohen) Date: Thu, 1 Sep 2016 13:58:36 +0200 Subject: [FieldTrip] Conference announcement: ICON XIII Message-ID: We are happy to make the second announcement for the ICON XIII conference, which will take place on 5-8 August 2017 in Amsterdam (the Netherlands). Amsterdam is an easily-accessible and progressive city. ICON will take place at the Beurs van Berlage, located in downtown Amsterdam and one of the most beautiful conference venues in Europe! Visit the website: http://www.icon2017.org ICON stands for International Conference for Cognitive Neuroscience. ICON has taken place every 2-3 years since 1980. This conference brings together researchers from diverse backgrounds, joined by their interest in studying the relationships amongst brain, mind, and behavior. ICON conferences are always a big success, and 2017 in Amsterdam will follow this same tradition! Symposia and poster submissions will be open from early 2017, with deadlines of 1 February for symposia and 31 March for posters. Plan your research accordingly! NEW SYMPOSIA OPTIONS In addition to standard-format symposia, ICON2017 will feature two novel formats (see "What" and "Submit" links on icon2017.org for more details): 1) "Hackathons" are computer-based sessions that can involve either a group of people working towards solving a problem, or can be more tutorial-like with the goal of teaching hands-on skills (e.g., using a toolbox or implementing an analysis in Matlab) that can be accomplished in ~2 hours (for longer workshops, consider organizing a satellite). 2) "Ask-the-experts" is a panel of experts in a topic. No specific lectures are prepared; instead there is an open Q&A/discussion session. The focus can be on a theoretical issue, methodological issue, or hotly-debated topic in cognitive neuroscience. PRE-CONFERENCE WORKSHOPS/SATELLITES We welcome pre-conference satellites, and will be happy to advertise them on the ICON website. Note that satellites are independent from ICON in terms of organization, registration, and costs. If you have any questions or would like to discuss ideas for your satellite, please contact Mike Cohen (mikexcohen at gmail.com) and Birte Forstmann (buforstmann at gmail.com). FOLLOW US ON TWITTER For up-to-date announcements before and during the ICON meeting, follow @icon2017 (see also "Media" tab on the website). http://www.icon2017.org We look forward to seeing you in beautiful Amsterdam! Mike X Cohen and Birte Forstmann -- Mike X Cohen, PhD mikexcohen.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From niels.focke at uni-tuebingen.de Thu Sep 1 16:30:49 2016 From: niels.focke at uni-tuebingen.de (Niels Focke) Date: Thu, 1 Sep 2016 16:30:49 +0200 Subject: [FieldTrip] =?iso-8859-1?q?PhD_/_Research_Fellow_Position_in_Epil?= =?iso-8859-1?q?epsy_Imaging_=28MEG_/_hd-EEG=29_in_T=FCbingen/Germa?= =?iso-8859-1?q?ny?= Message-ID: <016601d2045d$6f6dc460$4e494d20$@uni-tuebingen.de> We are happy to announce a job opening: 1 PhD Student / Research Fellow (Wissenschaftlicher Mitarbeiter, 50%) for the AG Translational Neuroimaging, Neurological Clinic and Hertie Institute for Clinical Brain Research for a DFG-funded 3-years project. The successful applicant will work primarily on functional connectivity in MEG and hd-EEG in patients with genetic epilepsy. This involves graph-theoretical concepts and machine learning approaches. The aim of this project is to link the genetic causes of epilepsy with imaging patterns and improve our understanding of the pathophysiology and genotype-phenotype relations in general. The aim of this project is to link the genetic causes of epilepsy with imaging patterns and improve our understanding of the pathophysiology and genotype-phenotype relations in general. Applicants need a university degree (MA or equivalent) in physics, mathematics, biology, biomedical engineering, medicine or other related disciplines. Programming skills (Matlab) are essential as is previous knowledge of MEG or EEG and common imaging toolboxes (e.g. Fieldtrip, Brainstorm, SPM, FSL). Publications on network analysis/graph theory are beneficial for a successful application, as is previous experience with epilepsy. Since the study involves interaction with patients, German language skills are advantageous. The applicant has to be fluent in English, both written and oral. The focus of our group is the utilization of imaging and post-processing methods to better understand the neurobiology of focal and generalized epilepsies, allow individualized diagnostics and translate methodological advances into clinical applications. The applicant will have access to a unique setting including high-density MR-compatible 256-channel EEG, 3T- and 9.4T-MRI scanners, human and fetal MEG and hybrid human PET-MR facilities. The medical university clinics runs a comprehensive epilepsy surgery program including invasive EEG recordings. The applicant can be enrolled into the neuroscience PhD program including various teaching courses and further benefits (http://www.neuroschool-tuebingen.de/). The salary is according to German federal scale (TV-L, E13 50%). The initial contract is for one year. After successful interim evaluation (PhD advisory board), a prolongation for further two years is available. The university is especially encouraging the application of women. Disabled applicant are preferred in case of equal qualification. The intended start date is November 2016 with some flexibility. Please send a letter of motivation, CV, references and, if available, a sample publication to: Universitätsklinikum Tübingen Abteilung Neurologie mit Schwerpunkt Epileptologie PD Dr. Niels Focke Hoppe-Seyler-Str. 3 76076 Tübingen Germany or via E-Mail: niels.focke at uni-tuebingen.de __________________________________________________________________________ PD Dr. Niels Focke Oberarzt Abt. Neurologie mit Schwerpunkt Epileptologie Universitätsklinikum Tübingen AG Translationale Bildgebung Hertie Institut für Klinische Hirnforschung Werner Reichhardt Centre for Integrative Neuroscience -------------- next part -------------- A non-text attachment was scrubbed... Name: PhD_offer_genetic_epilepsy_imaging.pdf Type: application/pdf Size: 251282 bytes Desc: not available URL: From aborna at sandia.gov Fri Sep 2 01:10:03 2016 From: aborna at sandia.gov (Borna, Amir) Date: Thu, 1 Sep 2016 23:10:03 +0000 Subject: [FieldTrip] Importing arbitrary dataset using ft_definetrial Message-ID: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Sep 2 09:05:16 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 2 Sep 2016 07:05:16 +0000 Subject: [FieldTrip] Importing arbitrary dataset using ft_definetrial In-Reply-To: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> References: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> Message-ID: <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> Hi Amir, It should be possible to bypass ft_definetrial when calling ft_artifact_jump. One needs to supply a second input argument, i.e. ft_artifact_jump(cfg, data); As long as the cfg does not point to a dataset (i.e. does not have cfg.datafile/dataset etc.) it should work, as far as I know. Best, Jan-Mathijs On 02 Sep 2016, at 01:10, Borna, Amir > wrote: Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. _______________________________________________ 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 aborna at sandia.gov Fri Sep 2 17:59:38 2016 From: aborna at sandia.gov (Borna, Amir) Date: Fri, 2 Sep 2016 15:59:38 +0000 Subject: [FieldTrip] [EXTERNAL] Re: Importing arbitrary dataset using ft_definetrial In-Reply-To: <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> References: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> Message-ID: Hi Jan-Mathijs, Thank you for your suggestion. I haven't tried your solution yet as my question is not specific to any function; it looks like many of the ft functions require the configuration (cfg) argument which is created only by calling ft_definetial. So is there a way to call ft_definetial on a custom dataset? Thank you. Best, Amir Borna. Sandia National Lab. From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Schoffelen, J.M. (Jan Mathijs) Sent: Friday, September 02, 2016 1:05 AM To: FieldTrip discussion list Subject: [EXTERNAL] Re: [FieldTrip] Importing arbitrary dataset using ft_definetrial Hi Amir, It should be possible to bypass ft_definetrial when calling ft_artifact_jump. One needs to supply a second input argument, i.e. ft_artifact_jump(cfg, data); As long as the cfg does not point to a dataset (i.e. does not have cfg.datafile/dataset etc.) it should work, as far as I know. Best, Jan-Mathijs On 02 Sep 2016, at 01:10, Borna, Amir > wrote: Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. _______________________________________________ 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 belahian at memphis.edu Fri Sep 2 21:45:44 2016 From: belahian at memphis.edu (Bahareh Elahian (belahian)) Date: Fri, 2 Sep 2016 19:45:44 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: Message-ID: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis - FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_freqanalysis". FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis - FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_freqanalysis". FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Sun Sep 4 09:25:27 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sun, 4 Sep 2016 07:25:27 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: Message-ID: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 rb643 at medschl.cam.ac.uk Sun Sep 4 18:20:17 2016 From: rb643 at medschl.cam.ac.uk (Richard Bethlehem) Date: Sun, 4 Sep 2016 16:20:17 +0000 Subject: [FieldTrip] multi-taper smoothing and frequency of interest Message-ID: <3188FAB8621D294696F13E80A7BBC97E010A621686@me-mbx4.medschl.cam.ac.uk> Dear field trippers, Would anyone be able to offer some advice on smoothing settings used for the MTMFFT method when I want to isolate lower frequencies as well as some guidance on setting the frequency of interest. What I eventually want is just the power and crosspectra for a frequency band. So, for example I am currently looking at the delta range (2-4Hz) and then it would seem a bit odd to use a smoothing kernel of 2Hz as it would provide very frequency specific information for that range right? In addition, I initially just set the foilim to [2 4], but this gives me 2 datapoints that I assume just refer to the information at 2Hz and 4Hz? Thus, instead I changed it to setting the foi as a logspaced set of frequencies within the delta range. However when I run that I still only get 9 datapoints/dimensions for the frequency. Can anyone explain why it would default to 9 or what the correct settings would be to simply get the power and crosspectra for a specific frequency band (at the moment I am simply averaging over the frequency range later on anyway)? Cheers, Richard ps: This is the code I am using: cfg_freq = []; cfg_freq.method = 'mtmfft'; cfg_freq.output = 'powandcsd'; cfg_freq.channel = 1:64; cfg_freq.keeptrials ='yes'; %do not return an average of all trials for subsequent wpli analysis cfg_freq.taper = 'dpss'; %delta cfg_freq.tapsmofrq = 0.25; cfg_freq.foi = exp(linspace(log(2),log(4),20)); [freq_data.delta] = ft_freqanalysis(cfg_freq, data_iccleaned); And this is what I used to get some adjacency matrices for subsequent network analyses: cfg_conn = []; cfg_conn.method = 'wpli'; conn.delta = ft_connectivityanalysis(cfg_conn, freq_data.delta); conn.delta = ft_checkdata(conn.delta, 'cmbrepresentation', 'full','datatype','freq'); network_delta = squeeze(nanmean(conn.delta.wplispctrm,3)); This is resting-state EEG data that has already been pre-processed and I've segmented the continuous recording into 4-second segment to create 'trials' as I want to follow up this analysis with WPLI connectivity analysis and hence I need multiple trials (correct me if I'm wrong on that as well please, but that is probably a different thread altogether). From r.oostenveld at donders.ru.nl Mon Sep 5 09:00:39 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Mon, 5 Sep 2016 09:00:39 +0200 Subject: [FieldTrip] response requested - please check the FieldTrip website Message-ID: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> Dear FieldTrip users I just got word from someone who received a warning when opening the FieldTrip website. See below, it appears blacklisted by his (institutional) security software. I checked: for me it looks fine. I also don’t see anything unusual on the server itself, but a website hack is sometimes hard to detect. Could you please check the website on unusual or suspicious behaviour? But don’t click on anything if you see something unexpected! Please let me know in a PERSONAL REPLY to this email whether it works or not. Please do NOT REPLY to all people on the list, as the others on the list won’t be able to fix it anyway and will probably be annoyed by all those email messages. Thanks, Robert -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.jpeg Type: image/jpeg Size: 31648 bytes Desc: not available URL: From r.oostenveld at donders.ru.nl Mon Sep 5 11:49:30 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Mon, 5 Sep 2016 11:49:30 +0200 Subject: [FieldTrip] response requested - please check the FieldTrip website In-Reply-To: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> References: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> Message-ID: Dear all Thanks for all of your replies from all over the world! It appears that the warning/error message is specific for the lab where it was initially reported, which happens to be a centre here in Nijmegen on the other side of the campus. I’ll discuss in more detail with them what might be causing it. So right now I don’t see a reason to be concerned about the website itself. cheers Robert > On 05 Sep 2016, at 09:00, Robert Oostenveld wrote: > > Dear FieldTrip users > > I just got word from someone who received a warning when opening the FieldTrip website. See below, it appears blacklisted by his (institutional) security software. I checked: for me it looks fine. I also don’t see anything unusual on the server itself, but a website hack is sometimes hard to detect. > > Could you please check the website on unusual or suspicious behaviour? But don’t click on anything if you see something unexpected! > > Please let me know in a PERSONAL REPLY to this email whether it works or not. Please do NOT REPLY to all people on the list, as the others on the list won’t be able to fix it anyway and will probably be annoyed by all those email messages. > > Thanks, > Robert > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From belahian at memphis.edu Mon Sep 5 18:59:57 2016 From: belahian at memphis.edu (Bahareh Elahian (belahian)) Date: Mon, 5 Sep 2016 16:59:57 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> References: , <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Message-ID: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 pgoodin at swin.edu.au Tue Sep 6 00:28:34 2016 From: pgoodin at swin.edu.au (Peter Goodin) Date: Mon, 5 Sep 2016 22:28:34 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot Message-ID: Hi Bahar, There's no problem. The matrix returned is simply a channel x frequency x time matrix. Hope that helps, Peter. On 6 Sep 2016 3:24 AM, "Bahareh Elahian (belahian)" wrote: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 Tue Sep 6 08:51:24 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 6 Sep 2016 06:51:24 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Message-ID: <0B7BC124-9612-4684-A746-7F52CE75F1B7@donders.ru.nl> Hi Bahar, May I add to Peter’s reply that you should specify 4000, rather than 4 as resamplefs. JM On 05 Sep 2016, at 18:59, Bahareh Elahian (belahian) > wrote: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl > on behalf of Schoffelen, J.M. (Jan Mathijs) > Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 stefan.debener at uni-oldenburg.de Tue Sep 6 15:52:14 2016 From: stefan.debener at uni-oldenburg.de (Stefan Debener) Date: Tue, 6 Sep 2016 15:52:14 +0200 Subject: [FieldTrip] LSL Workshop in Germany Message-ID: <57CECA0E.6040500@uni-oldenburg.de> Dear all, The 1st International Lab Streaming Layer workshop will take place in Delmenhorst, Germany, on 19-20 December, 2016. LSL is a (phantastic) software project for time-synchronized streaming of multimodal data (https://github.com/sccn/labstreaminglayer). For preliminary program and registration details, please visit: http://www.h-w-k.de/index.php?id=2224 Best wishes, Stefan Debener & Martin Bleichner From ignasisols at gmail.com Tue Sep 6 22:01:14 2016 From: ignasisols at gmail.com (Ignasi Sols Balcells) Date: Tue, 6 Sep 2016 16:01:14 -0400 Subject: [FieldTrip] fieldtrip Functions that have the same name as MATLAB built in scripts - conflict. Message-ID: Hi all, I am using the last fieldtrip version and Matlab 2015b (Mac). When I start Matlab I get this warnings: *"Warning: Function iscolumn has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function ismatrix has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function isrow has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function isequaln has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.* *Warning: Function isstring has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict".* Did this happen to other users? I think that renaming the scripts, as suggested by Matlab, is not the best idea because many other fieldtrip scripts that call this affected scripts should be changed manually... Thanks, Ignasi -------------- next part -------------- An HTML attachment was scrubbed... URL: From ekenaykut at gmail.com Tue Sep 6 22:07:15 2016 From: ekenaykut at gmail.com (Aykut Eken) Date: Tue, 6 Sep 2016 23:07:15 +0300 Subject: [FieldTrip] fieldtrip Functions that have the same name as MATLAB built in scripts - conflict. In-Reply-To: References: Message-ID: Hi Ignasi, This happened to me when I changed the version of MATLAB. However, I continued to use Fieldtrip without any problems. If any error occurs during code running, you can change the built in function with the fieldtrip function that has the same name. Best Aykut > On 06 Sep 2016, at 23:01, Ignasi Sols Balcells wrote: > > Hi all, > > I am using the last fieldtrip version and Matlab 2015b (Mac). > When I start Matlab I get this warnings: > > "Warning: Function iscolumn has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function ismatrix has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isrow has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isequaln has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isstring has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict". > > Did this happen to other users? I think that renaming the scripts, as suggested by Matlab, is not the best idea because many other fieldtrip scripts that call this affected scripts should be changed manually... > > Thanks, > > Ignasi > _______________________________________________ > 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 giovannipellegrino at gmail.com Thu Sep 8 18:40:52 2016 From: giovannipellegrino at gmail.com (Giovanni Pellegrino) Date: Thu, 8 Sep 2016 18:40:52 +0200 Subject: [FieldTrip] Fwd: Postdoc positions @ Campus Bio-Medico University, Rome, Italy In-Reply-To: References: Message-ID: - Apologies for cross-postings - In the context of the European Research Council Grant “RESHAPE: REstoring the Self with embodiable HAnd ProsthesEs”, we are seeking two outstanding *Post-Doc scientists* to join us in developing new tools and methods to improve the embodiment of robotic hand prostheses and study the related brain processes. Activities will be carried out in a multidisciplinary research environment (Clinical Neurophysiology and Neuroengineering) @ Campus Bio-Medico University, Rome Italy (www.unicampus.it). Post-Doc ideal candidates should · - have relevant publications in international journals and experience in fund raising · - be English mother tongue or have almost comparable fluency · - *own at least two of the following expertise*: 1. Programming for development/customization of interactive Virtual/Augmented Reality environment 2. EEG/MRI signal processing 3. Body ownership, embodiment, cognitive neuroscience. Suitable candidates can introduce themselves by contacting Giovanni Di Pino (g.dipino at unicampus.it) and Domenico Formica(d.formica at unicampus.it). -- Giovanni Pellegrino, MD -------------- next part -------------- An HTML attachment was scrubbed... URL: From seymourr at aston.ac.uk Thu Sep 8 19:11:00 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Thu, 8 Sep 2016 17:11:00 +0000 Subject: [FieldTrip] Elekta Head Position Information --> FT Message-ID: Hi all, Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. Many thanks, Robert Seymour (PhD Student, Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From alexandre.gramfort at telecom-paristech.fr Thu Sep 8 21:50:22 2016 From: alexandre.gramfort at telecom-paristech.fr (Alexandre Gramfort) Date: Thu, 8 Sep 2016 21:50:22 +0200 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: References: Message-ID: hi Robert, unfortunately correcting for head movements is more difficult that using a linear regression (like done with fMRI). I doubt you can avoid a proper head movement correction using the physics of the sensors etc. You can use MNE open implementation of maxfilter prior to using fieldtrip if you want http://martinos.org/mne/dev/manual/preprocessing/maxwell.html http://martinos.org/mne/dev/generated/mne.preprocessing.maxwell_filter.html http://martinos.org/mne/dev/generated/commands.html#mne-maxfilter Hope this helps Alex On Thu, Sep 8, 2016 at 7:11 PM, Seymour, Robert (Research Student) wrote: > Hi all, > > > Just wondering whether anyone using an Elekta MEG system has managed to > import the head position estimation logs generated by Maxfilter into > Fieldtrip via the ft_preprocessing command? There must be a way of tricking > the function into accepting the data as an extra channel... My thinking is > that it should ultimately be possible to use ft_regressconfound to address > head movement right issues before ft_sourcestatistics without having to use > Maxfilter's native head position correction. > > > Many thanks, > > > Robert Seymour (PhD Student, Aston Brain Centre) > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail. > From a.stolk8 at gmail.com Fri Sep 9 01:12:26 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Thu, 8 Sep 2016 16:12:26 -0700 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: References: Message-ID: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> Hi Robert, Hopefully the following page is still accurate: http://www.fieldtriptoolbox.org/faq/how_can_i_visualize_the_neuromag_head_position_indicator_coils And more generally: http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis Hope that gets you started, Arjen > On Sep 8, 2016, at 10:11 AM, Seymour, Robert (Research Student) wrote: > > Hi all, > > > Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. > > > Many thanks, > > > Robert Seymour (PhD Student, Aston Brain Centre) > > _______________________________________________ > 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 a.stolk8 at gmail.com Fri Sep 9 01:21:54 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Thu, 8 Sep 2016 16:21:54 -0700 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> References: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> Message-ID: <4296702C-8916-4639-AD69-ADDFFF5BAFC0@gmail.com> Actually, while looking at it again, it doesnt provide the elekta headpositions, but creates position traces through dipolefitting. It's been a while but I recall this procedure wasn't that straightforward, producing shaky results. Perhaps someone in the list can point you in the right direction in terms of how to read in the elekta headpositions using ft_preproc. > On Sep 8, 2016, at 4:12 PM, Arjen Stolk wrote: > > Hi Robert, > > Hopefully the following page is still accurate: > http://www.fieldtriptoolbox.org/faq/how_can_i_visualize_the_neuromag_head_position_indicator_coils > > And more generally: > http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis > > Hope that gets you started, > Arjen > >> On Sep 8, 2016, at 10:11 AM, Seymour, Robert (Research Student) wrote: >> >> Hi all, >> >> >> Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. >> >> >> Many thanks, >> >> >> Robert Seymour (PhD Student, Aston Brain Centre) >> >> _______________________________________________ >> 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 virginie.van.wassenhove at gmail.com Fri Sep 9 11:54:43 2016 From: virginie.van.wassenhove at gmail.com (Virginie van Wassenhove) Date: Fri, 9 Sep 2016 11:54:43 +0200 Subject: [FieldTrip] [postdoc position] Message-ID: Dear colleagues, I would be grateful if you could pass on the following open position. Applications are invited for a postdoc position in the team of Dr Franck Ramus (LSCP, Department of Cognitive Studies, Ecole Normale Supérieure, Paris, France) on the study of auditory processing in developmental dyslexia using magnetoencephalography (MEG). Specific information about the position here: http://www.lscp.net/persons/ramus/docs/Postdoc_position.pdf Specific information about the project here: http://www.lscp.net/persons/ramus/docs/MEG_project_2016.pdf Best wishes, Virginie -- Virginie van Wassenhove CEA/NeuroSpin MEG - UNICOG Bat 145 PC 156 F-91191 Gif s/ Yvette FRANCE office: +33(0)1 69 08 1667 cell: +33(0)6 15 83 4955 skype, twitter: virginie_vw sites.google.com/site/virginievanwassenhove/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Fri Sep 9 20:45:01 2016 From: mklados at gmail.com (Manousos Klados) Date: Fri, 9 Sep 2016 20:45:01 +0200 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados [image: photo] *Manousos Klados, MSc, PhD* Postdoctoral Researcher, Max Planck Institute for Human Cognitive & Brain Sciences, +49(0)-341-9940-2507 | +49(0)-176-6988-1781 | http://www.mklados.com | Skype: mklados | Stephanstraße 1a PC D-04103 Leipzig Germany ------------------------------ *Call for Papers (Frontiers):*Applied Neuroscience: Methodology, Modeling, Theory, Applications and Reviews *Online Webinar in Brain Networks (hands on) - Live: 10-06-16 at 11:00 AM EEST (reserve your seat now )* ------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From zhangk28 at mcmaster.ca Fri Sep 9 20:53:26 2016 From: zhangk28 at mcmaster.ca (KAIJIE ZHANG) Date: Fri, 9 Sep 2016 18:53:26 +0000 Subject: [FieldTrip] Mailing List Message-ID: Hi, Can I be removed from the field trip mailing list please? I have e-mailed unsubscribe already, but I am still receiving e-mails. Best Regards, Kaijie -- Kaijie Zhang Electrical & Biomedical Engineering, Level IV McMaster University -------------- next part -------------- An HTML attachment was scrubbed... URL: From matt.euler at psych.utah.edu Fri Sep 9 21:16:39 2016 From: matt.euler at psych.utah.edu (Matt Euler) Date: Fri, 9 Sep 2016 19:16:39 +0000 Subject: [FieldTrip] tenure-track position in Applied Cognitive Neuroscience at the University of Utah Message-ID: <8063208343AC35429BADDD1D51C326E270EE1D17@X-MB12.xds.umail.utah.edu> Dear all, The University of Utah Psychology department is currently seeking applications for a tenure-track faculty position in Applied Cognitive Neuroscience at the assistant professor level. Apologies for cross-postings: Cognitive Neuroscience at the University of Utah. The Department of Psychology at the University of Utah invites applications for a tenure-track faculty position in Applied Cognitive Neuroscience at the assistant professor level. This position is part of a new multi-disciplinary strategic cluster of hires across the School of Medicine, Bioengineering, and Psychology, in the area of Neural Basis of Behavior, Learning, and Memory, with opportunities to participate in the University of Utah's Neuroscience Initiative, www.neurogateway.utah.edu. We welcome applications from any area of cognitive psychology (including but not limited to: memory, executive functioning, attention, perception, decision-making, and reasoning) with a strong theory-based research program that employs neuroscientific methods. We especially welcome applicants who conduct research in both the laboratory and applied settings and who can speak to the real-world impact of the processes they study. Applicants should have the ability and interest to teach undergraduate and graduate courses in cognitive neuroscience. In addition to a doctoral program in cognition and neural science, the University of Utah has an interdepartmental neuroscience graduate program http://neuroscience.med.utah.edu. Ideal candidates could mentor students in both programs. Candidates should have an excellent and sustained record of research and evidence of the potential or demonstrated ability to generate extramural funding, commensurate with their career stage. The Department of Psychology values interdisciplinary approaches to research and training, and strongly encourages collaboration across four traditional programs (Developmental, Clinical, Cognition and Neural Sciences, and Social). The department promotes multidisciplinary collaboration outside of the Department of Psychology with active ties to the Consortium for Families and Health Research, University of Utah Neuroscience Initiative, the School of Computing, Civil and Environmental Engineering, Bioengineering, the Business School, the College of Education, Pediatrics, Anesthesiology, Neurology, Psychiatry, Radiology, the Huntsman Cancer Institute, and the Salt Lake Veterans Administration Medical Center. The Department of Psychology is committed to the goal of promoting diversity in academia and welcomes candidates whose interests and skills contribute to this goal. The University of Utah is a PAC-12 institution located in Salt Lake City nestled in the foothills of the Wasatch Mountains. With an enrollment of 31,000 students, it is the flagship university for the state of Utah. The university administration provides strong support for faculty research in the Psychology Department. The University of Utah values candidates who have experience working in settings with students from diverse backgrounds, and possess a strong commitment to improving access to higher education for historically underrepresented students. The University of Utah is an Affirmative Action/Equal Opportunity employer and does not discriminate based upon race, national origin, color, religion, sex, age, sexual orientation, gender identity/expression, status as a person with a disability, genetic information, or Protected Veteran status. Individuals from historically underrepresented groups, such as minorities, women, qualified persons with disabilities and protected veterans are encouraged to apply. Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities. To inquire about the University's nondiscrimination or affirmative action policies or to request disability accommodation, please contact: Director, Office of Equal Opportunity and Affirmative Action, 201 S. Presidents Circle, Rm 135, (801) 581-8365. Please submit a letter detailing current research and teaching interests, a curriculum vitae, three representative reprints or preprints of publications, and contact information for three individuals who will provide letters of recommendation. Applications should be submitted at: http://utah.peopleadmin.com/postings/55506. Review of applications will begin October 1, 2016 and will continue until the position is filled. Matthew J. Euler, Ph.D. Assistant Professor Department of Psychology University of Utah Salt Lake City, UT 84112 -------------- next part -------------- An HTML attachment was scrubbed... URL: From smoratti at psi.ucm.es Tue Sep 13 21:34:33 2016 From: smoratti at psi.ucm.es (smoratti at psi.ucm.es) Date: Tue, 13 Sep 2016 21:34:33 +0200 Subject: [FieldTrip] PhD Position Clinical Neuroscience Lab CTB Madrid Message-ID: <019C5012-57D9-46ED-B699-04DFAD1B1FC9@psi.ucm.es> On behalf of Dr. Bryan Strange I send this job posting: Applications are invited for a 4-year funded PhD position in neuroscience. The Laboratory for Clinical Neuroscience in Madrid (www.thestrangelab.org ) focuses on the study of memory in healthy humans and different patient populations. We apply a multi-modal approach to better understand what factors influence memory, and are currently working on deep-brain stimulation (DBS) techniques to improve memory. The successful applicant would - Be part of a multi-disciplinary team comprising neurosurgeons, neurologists, psychiatrists, psychologists and biomedical engineers - Develop a novel DBS technique to enhance memory in human patients - Adopt methods to localise deep-brain electrodes using pre- and post-operative CT and MRI scans - Perform and analyse simultaneous DBS and MEG recordings - Perform simultaneous intracranial local field potential and scalp high density EEG recordings We provide funding for one four-year PhD position. This is a government funded position, with starting date is early 2017. Additional funding is also provided for international visits to other laboratories to enhance the PhD training. We are looking for a highly motivated individual who wishes to pursue a career in science, and has an interest in clinical and cognitive neuroscience of memory. Applicants should have MSc or equivalent in neuroscience, biology, biomedical engineering, psychology, or a related science/engineering discipline. Prior experience is required in either cognitive neuroscience, theoretical neuroscience, or animal models of memory. Familiarity with electrophysiology or MRI and Matlab or R, would be useful. 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 Applications deadline is 25 September 2016 -- ___________________________ Bryan Strange MRCP PhD Director, Laboratory for Clinical Neuroscience, CTB-UPM and Department of Neuroimaging, Reina Sofia Centre for Alzheimer's Research, Madrid, Spain www.thestrangelab.org ________________________________________________________ Stephan Moratti, PhD see also: Stephan Moratti Universidad Complutense de Madrid Facultad de Psicología Departamento de Psicología Básica I Campus de Somosaguas 28223 Pozuelo de Alarcón (Madrid) Spain and Center for Biomedical Technology Laboratory for Cognitive and Computational Neuroscience Parque Científico y Tecnológico de la Universidad Politecnica de Madrid Campus Montegancedo 28223 Pozuelo de Alarcón (Madrid) Spain email: smoratti at psi.ucm.es Tel.: +34 679219982 -------------- next part -------------- An HTML attachment was scrubbed... URL: From hesham.elshafei at inserm.fr Wed Sep 14 16:04:22 2016 From: hesham.elshafei at inserm.fr (Hesham ElShafei) Date: Wed, 14 Sep 2016 16:04:22 +0200 Subject: [FieldTrip] Virtual Electrodes Message-ID: <93e198c44edd942b7df24688d7ac08c0@inserm.fr> Hello fieldtrippers , For my Phd , I am trying to investigate the dynamics of alpha oscillations during anticipatory attention. I have analysed the data in the sensor level and based upon these analyses I have define time-frequency windows of interest to which I have applied the DICS beamformer. Based on statistical results, I have defined regions of interest (the left Heschl Gyrus, for example). Now I would like to have a look at the time couse of these sources. I have followed this tutorial: http://www.fieldtriptoolbox.org/tutorial/salzburg?s[]=virtual&s[]=sensors However, there is a step I would like to expert opinions. In the tutorial, after having defined voxels of interest , they have re-calculated the leadfield for these voxels. (let's call that method A) Should this operation be different to Method B which involves marking only the voxels of interest in the leadfield (that has been used for the DICS) as inside the brain? I've tried both methods, and results are different. So I would like to know why such difference exists and which is method is better? Also in the aforementioned tutorial , there is this: cfg.grid.pos=[btiposCML;btiposHGL;btiposHGR]./1000; % units of m Which I don't think is correct since conversion should be done from mm to cm (if we follow the tutorial) Thank you very much Hesham ElShafei -------------- next part -------------- An HTML attachment was scrubbed... URL: From roycox.roycox at gmail.com Wed Sep 14 22:25:04 2016 From: roycox.roycox at gmail.com (Roy Cox) Date: Wed, 14 Sep 2016 16:25:04 -0400 Subject: [FieldTrip] postdoctoral position on sleep and memory In-Reply-To: References: Message-ID: > > hi all, >> >> Apologies for re- and cross-posting, but see below for an open >> postdoctoral position. >> >> 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 > > 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 efficacy of pharmacological and other interventions. Our work has > linked cognitive deficits to a specific heritable mechanism (sleep > spindles) 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 (polysomnography), 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 MEG/EEG methodology and data analysis, > comfortable with methodological innovation, and is interested in optimizing > and developing 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 lab mates 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 Experience with MEG/EEG data analysis/methodology > and/or other signal processing. Background in cognitive neuroscience, > experimental psychology, and an interest in clinical applications are a > plus. > > > > 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 mailtome.2113 at gmail.com Thu Sep 15 07:36:53 2016 From: mailtome.2113 at gmail.com (Arti Abhishek) Date: Thu, 15 Sep 2016 15:36:53 +1000 Subject: [FieldTrip] Plotting confidence intervals in multiplotER Message-ID: Dear fieldtrip community, I was wondering whether there is a way to plot the confidence intervals in the ERP plot? I see that this question was asked multiple times in the discussion list before, but I could not find an answer to this. Thanks, Arti -------------- next part -------------- An HTML attachment was scrubbed... URL: From sarathykousik at gmail.com Thu Sep 15 09:39:16 2016 From: sarathykousik at gmail.com (kousik sarathy) Date: Thu, 15 Sep 2016 09:39:16 +0200 Subject: [FieldTrip] Plotting confidence intervals in multiplotER In-Reply-To: References: Message-ID: Hey Arti, This is not such a trivial thing to solve. Here's a recipe I used. You need to find and edit two scripts. If this spurns any more interest, I'll initiate a 'bug' and try to send in a pull request. This is a dirty fix and in all probability will be considered blasphemy. ;) 1. Find in ft_multiplotER : ft_plot_vector(xval, yval, 'width', width(m), 'height', height(m), 'hpos', layX(m), 'vpos', layY(m), 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'color', color, 'style', cfg.linestyle{i}, 'linewidth', cfg.linewidth, 'axis', cfg.axes, 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'label', label, 'box', cfg.box, 'fontsize', cfg.fontsize); This basically calls a plotting function which in turn does the plotting for you. You need to send in the extra 'sem' or a 'ci' variable. Change this to: ft_plot_vector(xval, yval, 'ysem', ysem, 'width', width(m), 'height', height(m), 'hpos', layX(m), 'vpos', layY(m), 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'color', color, 'style', cfg.linestyle{i}, 'linewidth', cfg.linewidth, 'axis', cfg.axes, 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'label', label, 'box', cfg.box, 'fontsize', cfg.fontsize); 2. Find in ft_plot_vector : You need to first get the sem parameter from your data and setup so FT can see your sem or CI info. Follow the code here . Search for "data_sem" and fix those lines. Then: h = plot(hdat, vdat, style, 'LineWidth', linewidth, 'Color', color, ' markersize', markersize, 'markerfacecolor', markerfacecolor); Change this to: [h hp ]= boundedline(hdat, vdat, vdat_sem); Boundedline is a submission in the MATLAB file exchange. You can use any other thing. Good luck trying! :) -- Regards, Kousik Sarathy, S On Thu, Sep 15, 2016 at 7:36 AM, Arti Abhishek wrote: > Dear fieldtrip community, > > I was wondering whether there is a way to plot the confidence intervals in > the ERP plot? I see that this question was asked multiple times in the > discussion list before, but I could not find an answer to this. > > Thanks, > Arti > > _______________________________________________ > 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 nima.noury at student.uni-tuebingen.de Thu Sep 15 12:35:48 2016 From: nima.noury at student.uni-tuebingen.de (Nima Noury) Date: Thu, 15 Sep 2016 12:35:48 +0200 Subject: [FieldTrip] 2016 Tuebingen MEG Symposium, Oct 26-27 Message-ID: <20160915123548.Horde.jS8bdBmAx3EbFIq-0uCVWMX@webmail.uni-tuebingen.de> The MEG Center Tuebingen is pleased to announce the 2016 Tuebingen MEG Symposium The symposium takes place on October 26 and 27, 2016 at the University Hospital’s Conference Center. The meeting brings together leading researchers in the field of MEG and related disciplines. Join us to learn about the latest advances in MEG research and beyond. Confirmed speakers: Radoslaw Cichy, Berlin Michael Cohen, Nijmegen Freek van Ede, Oxford Stefan Haufe, New York Vladimir Litvak, London Laura Marzetti, Chieti Satu Palva, Helsinki Rafael Polania, Zurich Martin Vinck, New Haven Mark Woolrich, Oxford For more information and registration, please visit: http://meg.medizin.uni-tuebingen.de/2016/ 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 -------------- next part -------------- An embedded message was scrubbed... From: Nima Noury Subject: 2016 Tuebingen MEG Symposium, Oct 26-27 Date: Tue, 13 Sep 2016 12:38:52 +0200 Size: 1704 URL: From maorwolf at gmail.com Thu Sep 15 12:57:49 2016 From: maorwolf at gmail.com (Maor Wolf) Date: Thu, 15 Sep 2016 10:57:49 +0000 Subject: [FieldTrip] 2x3x3 cluster analysis Message-ID: Dear fieldtripers, I am trying to run a mixed repeated measures ANOVA cluster analysis with one between subject variable (schizoprhenics vs. neurotypicals) and two within subject variables (each one with three conditions) and I'm struggling with the design matrix. Has anyone encountered this issue before? Thank you, Maor -------------- next part -------------- An HTML attachment was scrubbed... URL: From t.rusch at uke.uni-hamburg.de Thu Sep 15 14:01:41 2016 From: t.rusch at uke.uni-hamburg.de (Tessa Rusch) Date: Thu, 15 Sep 2016 14:01:41 +0200 Subject: [FieldTrip] postdoctoral position on social decision-making Message-ID: <001301d20f48$eb93f550$c2bbdff0$@uke.uni-hamburg.de> Hi! Sorry for cross-posting, but find below the details of an open postdoctoral position Kind regards Tessa Postdoctoral Position in Social Decision-Making Hamburg, Germany A Post-doctoral position in the field of social decision-making is available at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany. The position is funded through the program “Collaborative Research in Computational Neuroscience” co-funded by the German Ministry of Science and Research (BMBF) and by the American National Science Foundation (NSF). The project entitled “Computational Modeling of Cooperative Success” investigates social decision-making and the construction of mental models with EEG hyperscanning and computational modeling. The collaborative partner in the project is Prof. M. Spezio (Scripps College, CA). Research visits in the respective other labs are part of the project. We are searching for enthusiastic candidates with a strong interest in cognitive and social neuroscience and a PhD in (cognitive) neuroscience, cognitive science, psychology, biology, computer science, or a related discipline. Prior experience in the acquisition and analysis of human EEG data (ERPs, time-frequency analyses) and good programming skills (e.g. Matlab/R) are required. Starting date is Dec 1st 2016 or a few months later. The position is available for 3 years. The institute provides an excellent multi-disciplinary and interactive research environment with a research-dedicated 3T MRI scanner, EEG/MEG facilities and behavioral labs. Additional information about the research group and other scientific projects are available at www.glascherlab.org. Interested candidates should submit their application as a single PDF document (including CV, publication list, contact details of two references and a short statement of research interests) via email to Dr. Jan Gläscher (glaescher at uke.de). -- _____________________________________________________________________ Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | www.uke.de Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Prof. Dr. Dr. Uwe Koch-Gromus, Joachim Prölß, Rainer Schoppik _____________________________________________________________________ SAVE PAPER - THINK BEFORE PRINTING -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Thu Sep 15 16:40:23 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Thu, 15 Sep 2016 16:40:23 +0200 Subject: [FieldTrip] From raw MEG to publication - BIOMAG16 satellite workshop, Oct 2, 2016 Message-ID: <282A2185-4DB3-4072-9D55-B5817DD25F95@donders.ru.nl> Dear colleagues, Apologies in advance for cross-posting. We would like to attract your attention to the BIOMAG2016 satellite symposium which will take place on Oct 2nd 2016 and is dedicated to group analysis of MEG data with free academic toolboxes. Please read the full description below. With best wishes, Arnaud Delorme Alexandre Gramfort Vladimir Litvak Srikantan Nagarajan Robert Oostenveld Francois Tadel ------------------------------------------------------------------------------- From raw MEG to publication: how to perform MEG group analysis with free academic software. Organisers: Arnaud Delorme, Alexandre Gramfort, Vladimir Litvak, Srikantan Nagarajan, Robert Oostenveld, Francois Tadel Free academic toolboxes have gained increasing prominence in MEG analysis as a means to disseminate cutting edge methods, share best practices between different research groups and pool resources for developing essential tools for the MEG community. In the recent years large and vibrant research communities have emerged around several of these toolboxes. Teaching events are regularly held around the world where the basics of each toolbox are explained by its respective developers and experienced power users. There are, however, two knowledge gaps that our BIOMAG satellite symposium aims to address. Firstly, most teaching examples only show analysis of a single ‘typical best’ subject whereas most real MEG studies involve analysis of group data. It is then left to the researchers in the field to figure out for themselves how to make the transition and obtain significant group results. Secondly, we are not familiar with any examples of fully analyzing the same group dataset with different academic toolboxes to assess the degree of agreement in scientific conclusions and compare strengths and weaknesses of various analysis methods and their independent implementations. Our workshop is organised by the lead developers of six most popular free academic MEG toolboxes (in alphabetic order): Brainstorm, EEGLAB, FieldTrip, MNE, NUTMEG, and SPM. Ahead of the workshop the research team for each toolbox will analyze the same group MEG/EEG dataset. This dataset containing evoked responses to face stimuli was acquired by Richard Henson and Daniel Wakeman, who won a special award at BIOMAG2010 to make it freely available to the community. All the raw data are available at ftp://ftp.mrc-cbu.cam.ac.uk/personal/rik.henson/wakemandg_hensonrn/ and https://openfmri.org/dataset/ds000117/ Detailed instructions for each toolbox will be made available online including analysis scripts and figures of results. All analyses will show a full pipeline from the raw data to detailed publication quality results. Researchers who are interested in using the respective toolbox will then be able to reproduce the analysis in their lab and port it to their own data. At the workshop each group will briefly introduce their software and present the key results from their analysis. This will be followed by a panel discussion and questions from the audience. Following the event we plan to integrate the suggestions and questions from the workshop audience and to publish the analyses details as part of a special research topic in Frontiers in Neuroscience, section Brain Imaging Methods so that the proposed best practices will be endorsed by peer review and become citable in future publications. Other research groups will be invited to contribute to the research topic as long as they present detailed descriptions of analyses of group data that are freely available online and make it possible for others to fully reproduce their analysis and results. We hope that this proposal will lead to creation of invaluable resource for the whole MEG community and the workshop will contribute to establishment of good practice and promoting consistent and reproducible analysis approaches. The event will also showcase all the toolboxes and will be of interest to beginners in the field with basic background in MEG who contemplate the most suitable analysis approach and software for their study as well as to experienced researchers who would like to get up to date with the latest methodological developments. -------------- next part -------------- An HTML attachment was scrubbed... URL: From iris.steinmann at med.uni-goettingen.de Thu Sep 15 16:41:30 2016 From: iris.steinmann at med.uni-goettingen.de (Steinmann, Iris) Date: Thu, 15 Sep 2016 14:41:30 +0000 Subject: [FieldTrip] Inter-trial variability of power amplitude for time-frequency spectra Message-ID: Dear Fieldtripper, I'm working on a spectral analysis of LFP data and calculated so far time-frequency spectra for every single trial. To describe the consistency/variability of phases on every time-frequency bin over trials I calculated 'Inter-trial Phase coherence (ITPC)' as described in the fieldtrip tutorial. But, what would I do to determine the consistency/variability of the power (squared amplitude) for every time-frequency bin over trials? Maybe simply calculate for every time-frequency bin a Standard Deviation over trials and relate this to the according mean: Variability(t,f) = Standard Deviation(t,f) / mean(t,f) Would it be that simple, or am I running into some statistical trouble (maybe because the power values are not normally distributed or anything else). Should I baseline correct the single trials before calculating the 'variability' of the power amplitude. Or am I missing an important point and the whole idea is not meaningful at all? Would be great if anyone has an idea, an answer, or even just a hint for a reference to read (couldn't find one so far)... Thanks! Iris -------------- next part -------------- An HTML attachment was scrubbed... URL: From nasseroleslami at gmail.com Fri Sep 16 17:57:52 2016 From: nasseroleslami at gmail.com (Bahman Nasseroleslami) Date: Fri, 16 Sep 2016 16:57:52 +0100 Subject: [FieldTrip] Fwd: Research Fellow (Biostatistics) Position - Trinity College Dublin, the University of Dublin, Dublin, Ireland In-Reply-To: References: Message-ID: Dear All, There is a research fellow position available in Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin, Ireland. ------------------------------------ Post Specification: 031885 Post Title: Research Fellow Post Status: 23 month Fixed Term Contract (Full-time) (Subject to satisfactory probation) Research Group/Department/School: Academic Unit of Neurology, School of Medicine, Trinity College Dublin, the University of Dublin London School of Hygiene and Tropical Medicine, London Location: Trinity Biomedical Sciences Institute, Trinity College Dublin, the University of Dublin College Green, Dublin 2, Ireland And close links with London School of Hygiene and Tropical Medicine Reports to: Professor Orla Hardiman (Dublin) Prof. Neil Pearce (London) Salary: Post-Doctorate Researcher Salary Scale, commensurate with experience Closing Date and Time: 12 noon on Friday, 14th October 2016 Applications are invited for a motivated and self-driven individual for the position of Biostatistician with the Irish ALS Research Group, hosted in the Trinity Biomedical Sciences Institute's Academic Unit of Neurology.The ideal candidate will have a PhD in Biostatistics or a cognate area. Amyotrophic Lateral Sclerosis (ALS) or Motor Neurone Disease (MND) is a degenerative brain disease that leads to progressive decline and death within 3-5 years of first symptom. Our detailed assessment of cognitive, behavioural and social cognitive function in ALS points to significant disruption in extra-motor systems in some patients. This project will combine high resolution structural and dynamic imaging of the brain at 3 Tesla and spectral EEG/ EMG with clinical and genomic data to identify sub-clusters of ALS patients. Using robust mathematical models and building on key imaging and signal processing signatures we will develop observed-independent, quantitative markers of disease that can be utilized to generate disease clusters. These clusters will then be further analysed based on discriminatory clinical, neuropsychological and genomic data. The detailed job description file (PDF) and the application instructions can be found online at http://jobs.tcd.ie. ------------------------------------ It would be really appreciated if you could share this with those that may be interested. Sincerely Bahman –––––––––––– Bahman Nasseroleslami Irish Research Council Postdoctoral Research Fellow Academic Unit of Neurology, School of Medicine Trinity College Dublin, the University of Dublin Dublin 2, Ireland. Room 5.43, Trinity Biomedical Sciences Institute 152-160 Pearse Street, Dublin D02 R590, Ireland. nasserob at tcd.ie, nasseroleslami at gmail.com www.tcd.ie Trinity College Dublin, the University of Dublin is ranked 1st in Ireland and in the top 100 world universities by the QS World University Rankings. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Sun Sep 18 20:55:04 2016 From: mklados at gmail.com (Manousos Klados) Date: Sun, 18 Sep 2016 14:55:04 -0400 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From hallmbh at aston.ac.uk Mon Sep 19 12:25:23 2016 From: hallmbh at aston.ac.uk (Hall, Michael (Research Student)) Date: Mon, 19 Sep 2016 10:25:23 +0000 Subject: [FieldTrip] Maxfilter and PCA Message-ID: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall -------------- next part -------------- An HTML attachment was scrubbed... URL: From magazzinil at gmail.com Mon Sep 19 13:48:55 2016 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Mon, 19 Sep 2016 12:48:55 +0100 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: Message-ID: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) < hallmbh at aston.ac.uk> wrote: > Dear All, > > I've been doing some testing with elekta neuromag data in Fieldtrip using > different sensor types (meg, meggrad, megmag) and different preprocessing > steps (tSSS 0.9 corr limit, no tSSS). > > A step that was proposed at the MEG UK 2015 demo was to use PCA to > compensate for the ill-conditioned estimate of the cov/csd matrix due to > maxfilter - could I ask why running a PCA and reducing the number of > components further would compensate for this? Apologies if this a naive > question, however I would assume that you would not want to reduce the rank > of your data further? Please see below for the link and code that I'm > referring to. > > http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtr > ip-beamformer-demo > > > %% deal with maxfilter > > % the data has been maxfiltered and subsequently concatenated > % this results in an ill-conditioned estimate of covariance or CSD > > cfg = []; > cfg.method = 'pca'; > cfg.updatesens = 'no'; > cfg.channel = 'MEGMAG'; > comp = ft_componentanalysis(cfg, data); > > cfg = []; > cfg.updatesens = 'no'; > cfg.component = comp.label(51:end); > data_fix = ft_rejectcomponent(cfg, comp); > > > Many thanks, > Mike Hall > > > > > _______________________________________________ > 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 Mon Sep 19 14:45:00 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 19 Sep 2016 12:45:00 +0000 Subject: [FieldTrip] Maxfilter and PCA References: Message-ID: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Hi all, The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. Best, Jan-Mathijs On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall _______________________________________________ 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 magazzinil at gmail.com Mon Sep 19 15:00:11 2016 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Mon, 19 Sep 2016 14:00:11 +0100 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: Hi Jan-Mathijs, Thanks for your answer. Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? Thanks, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Hi all, > > The reason to do the PCA has to do in this context with the fact that a > beamformer is used further down in the tutorial. The beamformer uses the > inverse of the covariance matrix, which behaves unpredictably (but usually > quite bad) when the smallest (usually poorly conditioned) components are > not well estimated. > The data that is used for the source reconstruction comes from three > separate runs, each of which was separately maxfiltered. As a consequence, > the low-rank subspace that is spanned by the individual runs’ data is > slightly different (each of which has approximately, say, a rank of 60). > Upon concatenation, however, the rank is suddenly increased to >> 60, where > most likely quite a lot of the ‘higher’ components represent noise. In > order to account for that in the covariance inversion, the whole data > matrix is ‘stabilized’ with a PCA. > > Best, > Jan-Mathijs > > > On 19 Sep 2016, at 13:48, Lorenzo Magazzini wrote: > > Hi Mike, > > This is a question that I've been asking myself too and I'd love to hear > an expert (and more technical) answer. In the meantime, these discussions > may be of help: > > https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html > https://mailman.science.ru.nl/pipermail/fieldtrip/2013- > November/007170.html > http://www.fieldtriptoolbox.org/faq/why_does_my_ica_ > output_contain_complex_numbers?s[ > > I wonder if the confusion arises from the difference between rank and > number of components? My understanding is that maxfilter reduces the rank > of the data (from 306 to 64, apparently). Therefore, my best guess is that > by performing a PCA and rejecting a number of components (only the first 50 > are kept, in the tutorial example), the data is no longer rank-deficient, > i.e. the rank is equal or greater than the number of components in the data. > > Clearly, this is a very non-technical interpretation, and a correction > would be more than welcome.. :) > > Best, > Lorenzo > > > > > > Lorenzo Magazzini > PhD Student > magazzinil at cardiff.ac.uk > > CUBRIC Building > Maindy Road > Cardiff > CF24 4HQ > > > On 19 September 2016 at 11:25, Hall, Michael (Research Student) < > hallmbh at aston.ac.uk> wrote: > >> Dear All, >> >> I've been doing some testing with elekta neuromag data in Fieldtrip using >> different sensor types (meg, meggrad, megmag) and different preprocessing >> steps (tSSS 0.9 corr limit, no tSSS). >> >> A step that was proposed at the MEG UK 2015 demo was to use PCA to >> compensate for the ill-conditioned estimate of the cov/csd matrix due to >> maxfilter - could I ask why running a PCA and reducing the number of >> components further would compensate for this? Apologies if this a naive >> question, however I would assume that you would not want to reduce the rank >> of your data further? Please see below for the link and code that I'm >> referring to. >> >> http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtr >> ip-beamformer-demo >> >> >> %% deal with maxfilter >> >> % the data has been maxfiltered and subsequently concatenated >> % this results in an ill-conditioned estimate of covariance or CSD >> >> cfg = []; >> cfg.method = 'pca'; >> cfg.updatesens = 'no'; >> cfg.channel = 'MEGMAG'; >> comp = ft_componentanalysis(cfg, data); >> >> cfg = []; >> cfg.updatesens = 'no'; >> cfg.component = comp.label(51:end); >> data_fix = ft_rejectcomponent(cfg, comp); >> >> >> Many thanks, >> Mike Hall >> >> >> >> >> _______________________________________________ >> 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 seymourr at aston.ac.uk Mon Sep 19 15:09:45 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Mon, 19 Sep 2016 13:09:45 +0000 Subject: [FieldTrip] Maxfilter and PCA Message-ID: Hi Mike & others, Instead of specifying a set number of components (e.g. 51) I tend to use data-driven approach that reduces my data to the number of components that describes 99% of the variance in my covar matrix. I do this like so: covar = zeros(numel(data.label)); for itrial = 1:numel(data.trial) currtrial = data.trial{itrial}; covar = covar + currtrial*currtrial.'; end [V, D] = eig(covar); D = sort(diag(D),'descend'); D = D ./ sum(D); Dcum = cumsum(D); numcomponent = find(Dcum>.99,1,'first') +1; % number of components accounting for 99% of variance in covar matrix disp(sprintf('\n Reducing the data to %d components \n',numcomponent)); cfg = []; cfg.method = 'pca'; cfg.updatesens = 'yes'; cfg.channel = 'MEG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'yes'; cfg.component = comp.label(numcomponent:end); data_fix = ft_rejectcomponent(cfg, comp); Cheers, Robert Seymour (Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Sep 19 15:53:39 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 19 Sep 2016 13:53:39 +0000 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: Hi Lorenzo, Well, your interpretation was almost OK, yet by keeping a certain number of components one makes the data explicitly rank deficient (so that’s the part that was not fully correctly stated in your pre-previous e-mail) The thing is that with keeping only (e.g.) 50 components, your data will still be rank deficient, yet the small components (those that end up as component 51 and up) cannot negatively affect the inverse of the data covariance matrix (which needs to be regularized anyway). Best, Jan-Mathijs On 19 Sep 2016, at 15:00, Lorenzo Magazzini > wrote: Hi Jan-Mathijs, Thanks for your answer. Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? Thanks, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) > wrote: Hi all, The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. Best, Jan-Mathijs On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall _______________________________________________ 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 russgport at gmail.com Mon Sep 19 17:30:48 2016 From: russgport at gmail.com (russ port) Date: Mon, 19 Sep 2016 11:30:48 -0400 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: <6474D29F-4B8F-4B9C-AF35-30E2C18A9DC6@gmail.com> Hi All, Just to clarify, as I am certainly worried about the implications of this chain on my own analyses. I have been following old posts from the email list/server, where it says that to do ICA on Neuromag data (for instance if you want to do EOG rejection) you must reduce the components you output to at most the rank of your data (because of TSSS/SSS basically drastically reduces the rank of your data because of how it works). As such, based on old email discussions, I ran an artifact rejection (for the artifacts mentioned in this email [muscle/Jump etc]) and then did a component analysis (runica) with the cfg set to give only enough outputs as valid by the rank of the data. Importantly, this data is only SSS (instead of TSSS) because the cHPI (continuous head position indicator monitoring) was not turned on. As such the script ultimately reads something like this: cfg=[] cfg.artfctdef.eog.artifact = artifact_EOG; cfg.artfctdef.jump.artifact = artifact_jump; cfg.artfctdef.muscle.artifact = artifact_muscle; data_no_artifacts = ft_rejectartifact(cfg,datanoline); cfg=[] cfg.resamplefs=300 cfg.detrend='no' resampleartifactfree=ft_resampledata(cfg,data_no_artifacts) cfg = []; cfg.method='runica' n_comp = rank(resampleartifactfree.trial{1} * resampleartifactfree.trial{1}') cfg.numcomponent = n_comp; cfg.runica.stop = 1e-7; ic_data = ft_componentanalysis(cfgeog,resampleartifactfree); I then go through the components and reject any component that are EC(or K depending on your nationality)G/ECG [heart and eye] artifacts. I then do ft_rejectcomponents for artifact components and use the resulting data in beamforming. My ICA components have real values, and the topos/timecourses look legit. Is this valid OR should I be doing a PCA/ICA to get the X (X=rank of data) components, and then again running it through ft_componentanalysis to check for heart/eye artifacts? Best (and sorry for the email, I’m a little paranoid when it comes to these things), Russ > On Sep 19, 2016, at 9:53 AM, Schoffelen, J.M. (Jan Mathijs) wrote: > > Hi Lorenzo, > > Well, your interpretation was almost OK, yet by keeping a certain number of components one makes the data explicitly rank deficient (so that’s the part that was not fully correctly stated in your pre-previous e-mail) The thing is that with keeping only (e.g.) 50 components, your data will still be rank deficient, yet the small components (those that end up as component 51 and up) cannot negatively affect the inverse of the data covariance matrix (which needs to be regularized anyway). > > Best, > Jan-Mathijs > > > >> On 19 Sep 2016, at 15:00, Lorenzo Magazzini > wrote: >> >> Hi Jan-Mathijs, >> >> Thanks for your answer. >> >> Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? >> >> Thanks, >> Lorenzo >> >> >> >> Lorenzo Magazzini >> PhD Student >> magazzinil at cardiff.ac.uk >> >> CUBRIC Building >> Maindy Road >> Cardiff >> CF24 4HQ >> >> >> On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) > wrote: >> Hi all, >> >> The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. >> The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. >> >> Best, >> Jan-Mathijs >> >> >>> On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: >>> >>> Hi Mike, >>> >>> This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: >>> >>> https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html >>> https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html >>> http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ >>> >>> I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. >>> >>> Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) >>> >>> Best, >>> Lorenzo >>> >>> >>> >>> >>> >>> Lorenzo Magazzini >>> PhD Student >>> magazzinil at cardiff.ac.uk >>> >>> CUBRIC Building >>> Maindy Road >>> Cardiff >>> CF24 4HQ >>> >>> >>> On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: >>> Dear All, >>> >>> I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). >>> >>> A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. >>> >>> http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo >>> >>> %% deal with maxfilter >>> >>> % the data has been maxfiltered and subsequently concatenated >>> % this results in an ill-conditioned estimate of covariance or CSD >>> >>> cfg = []; >>> cfg.method = 'pca'; >>> cfg.updatesens = 'no'; >>> cfg.channel = 'MEGMAG'; >>> comp = ft_componentanalysis(cfg, data); >>> >>> cfg = []; >>> cfg.updatesens = 'no'; >>> cfg.component = comp.label(51:end); >>> data_fix = ft_rejectcomponent(cfg, comp); >>> >>> >>> Many thanks, >>> Mike Hall >>> >>> >>> >>> >>> >>> _______________________________________________ >>> 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 > > _______________________________________________ > 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 B.Haendel at gmx.net Mon Sep 19 22:30:52 2016 From: B.Haendel at gmx.net (Barbara Haendel) Date: Mon, 19 Sep 2016 22:30:52 +0200 Subject: [FieldTrip] NEW PhD positions: Neuroscience - University of Wuerzburg (Germany) Message-ID: An HTML attachment was scrubbed... URL: From mklados at gmail.com Tue Sep 20 00:08:08 2016 From: mklados at gmail.com (Manousos Klados) Date: Tue, 20 Sep 2016 00:08:08 +0200 Subject: [FieldTrip] =?utf-8?q?Society_of_Applied_Neuroscience_Biennial_co?= =?utf-8?b?bmZlcmVuY2UgKFNBTjIwMTbigI8pIOKAkyBmaW5hbCBwcm9ncmFtbWU=?= Message-ID: Dear colleagues, I am proud to announce you that the final programme for SAN2016 is now online (http://www.applied-neuroscience.org/san2016/ index.php/conference-info/program) and a summarised snapshot with the its highlights is attached to this email. With this information we would also like to cordially invite you to participate in and attend SAN2016 (http://applied-neuroscience.org/san2016/), which is organised by the Society of Applied Neuroscience (SAN, http://www.applied-neuroscience.org/) in cooperation with the Medical School of the Aristotle University of Thessaloniki and the Department of Neurology of the Max Planck Institute for Human Cognitive and Brain Sciences. SAN2016 will be held October6-9, 2016 in Corfu Island, Greece. As you will see, there is an attractive list of planned hands-on workshops and conference symposia in place as well as, an attractive list of distinguished speakers Numerous special issues and research topics are also planned by Society members as per tradition. We look forward to seeing you in Corfu, Greece! Panos Bamidis John Gruzelier Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: SAN2016_Brochure_Final.pdf Type: application/pdf Size: 593075 bytes Desc: not available URL: From matt.gerhold at gmail.com Tue Sep 20 09:17:33 2016 From: matt.gerhold at gmail.com (Matt Gerhold) Date: Tue, 20 Sep 2016 09:17:33 +0200 Subject: [FieldTrip] Inverse-modelling requirements Message-ID: MEG Mavens: I am looking to perform a source-level analysis on some EEG event-related data. I would be very grateful if you can assist me in understanding some of the methods in your toolbox and also some of the requirements in terms of the experimental protocols if one envisages performing source-level analysis. I have reviewed the tutorials on your website and viewed a number of video lectures from you institute. I have one or two points I would like to clear-up and one or two questions that require answers. >From the available information that I have reviewed, it is recommended that one have at least the following items: i. hi-res EEG/MEG datasets, ii. polhemus measurement data, and iii. MRI data for each of the participants within the study. Having these items enables one to compute the necessary models to source-localise the EEG/MEG sensor-space data. What I would like to know is how far one can stretch the boundaries of these requirements and still produce publishable scientific outcomes: what items are indispensable to the source localisation methodology? There are many examples of researchers using standard MRI templates, but how reliable are analytical outcomes in such instances? Does using a standard MRI image for all participants really produce useful scientific outcomes, especially in clinical populations wherein cortical structural changes are well-documented? There is a fair amount of structural variation within the cortex across healthy individuals; surely, a single standard MRI scan would lead to erroneous localisation in some instances? In terms of electro/magnetic field data: what is the minimum requirement in terms of how many electrodes are needed (spatial sampling across the scalp) in order to perform subsequent source-localisation via inverse modelling? Can one justify using the method(s) in instances of sparse spatial sampling (32-channels) and expect acceptable scientific outcomes? If one uses generic sensor/head-model co-registration in the absence of polhemus data, does this lead to analytical outcomes that are accepted by yourselves? What are the standards currently being set within the journals; being mavens in the field, what would you recommend? I appreciate that most people will embark on the analysis and build understanding along the way; however, I would like to gain some clarity before embarking on this analytical journey. Many thanks in advance. Kind Regards, Matthew -------------- next part -------------- An HTML attachment was scrubbed... URL: From Darren.Price at mrc-cbu.cam.ac.uk Tue Sep 20 16:43:36 2016 From: Darren.Price at mrc-cbu.cam.ac.uk (Darren Price) Date: Tue, 20 Sep 2016 14:43:36 +0000 Subject: [FieldTrip] Combined EEG MEG Source Reconstruction Message-ID: Dear Fieldtrippers We are interested in using fieldtrip for data fusion and source reconstruction of three different types of sensors: EEG (64 Channels), MEG planar gradiometers (204), MEG magnetometers (102) (Elekta Neuromag 306 Channel). I found the following page, with a quick sample script demonstrating how to perform the forward solutions, http://www.fieldtriptoolbox.org/example/combined_eeg_and_meg_source_reconstruction. However, the page does not give much detail on the inversion part. Also, it does not mention whether fieldtrip takes care of scaling of the data or any other preprocessing steps such as pre-whitening. That post is also a couple of years old so I thought there may be some more current but undocumented way to achieve this. Any help would be much appreciated. Kind Regards Darren ------------------------------------------------------- Dr. Darren Price Investigator Scientist and Cam-CAN Data Manager MRC Cognition & Brain Sciences Unit 15 Chaucer Road Cambridge, CB2 7EF England EMAIL: darren.price at mrc-cbu.cam.ac.uk URL: http://www.mrc-cbu.cam.ac.uk/people/darren.price TEL +44 (0)1223 355 294 x202 FAX +44 (0)1223 359 062 MOB +44 (0)7717822431 ------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.brehm at uu.nl Wed Sep 21 09:52:29 2016 From: j.brehm at uu.nl (Brehm, J. (Julia)) Date: Wed, 21 Sep 2016 07:52:29 +0000 Subject: [FieldTrip] EEG Visual Artifact Detection - Settings Message-ID: <385DDA785CF9764B8E184EF28D01ADE0F63153@WP0045.soliscom.uu.nl> Dear FieldTrippers, I am looking for options to achieve the following functionality in visual EEG artifact detection: 1. mark channel-by-trial pairs as bad (as in ft_rejectvisual -> method = ’trial’). 2. plot trials on a specific channel layout. 3. return marked data, and not yet cleaned data (as in ft_databrowser) OR return list of excluded channel-by-trial pairs in addition to cleaned data. Is there any way to achieve this functionality with some settings that are readily available? All the best, Julia -------------- next part -------------- An HTML attachment was scrubbed... URL: From seymourr at aston.ac.uk Wed Sep 21 12:10:14 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Wed, 21 Sep 2016 10:10:14 +0000 Subject: [FieldTrip] Combined EEG MEG Source Reconstruction Message-ID: Hi Darren, Have you had a look at this tutorial? http://www.fieldtriptoolbox.org/tutorial/natmeg/beamforming I'm also interested in the answer to this question - it would be really helpful for someone to clarify the steps Fieldtrip takes to combine MAGS + GRADS from an Elekta Neuromag 306 scanner... I know that Fieldtrip pre-whitens the data for ICA with combined MAGS+GRADS but it is unclear whether this is also done when computing the forward solution? Many thanks, Robert Seymour (PhD Student Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From c.vanheck at donders.ru.nl Wed Sep 21 14:24:57 2016 From: c.vanheck at donders.ru.nl (Casper van Heck) Date: Wed, 21 Sep 2016 14:24:57 +0200 Subject: [FieldTrip] Lost reference location Message-ID: Dear all, We've recently started working on an old dataset, but have ran into a problem; nobody bothered to write down where the reference was placed... Does anybody have ideas on how to reconstruct the location of the reference, based on (some aspect of) the data? Best regards, Casper van Heck and Tineke van Rijn -------------- next part -------------- An HTML attachment was scrubbed... URL: From dlozanosoldevilla at gmail.com Wed Sep 21 14:54:48 2016 From: dlozanosoldevilla at gmail.com (Diego Lozano-Soldevilla) Date: Wed, 21 Sep 2016 14:54:48 +0200 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Casper, Very difficult... One idea would be to play with the data rank. Referencing to a specific sensor produces rank deficiency in your data. You can try to figure out which is the sensor that depends on the rest reading this thread: http://fr.mathworks.com/matlabcentral/newsreader/view_thread/157533 This ONLY can work if the sensor recordings are not correlated which is not always the case... Good luck! Diego On 21 September 2016 at 14:24, Casper van Heck wrote: > Dear all, > > We've recently started working on an old dataset, but have ran into a > problem; nobody bothered to write down where the reference was placed... > Does anybody have ideas on how to reconstruct the location of the > reference, based on (some aspect of) the data? > > Best regards, > > Casper van Heck and Tineke van Rijn > > _______________________________________________ > 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 christine.blume at sbg.ac.at Wed Sep 21 14:57:51 2016 From: christine.blume at sbg.ac.at (Blume Christine) Date: Wed, 21 Sep 2016 12:57:51 +0000 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Casper and Tineke, As voltage is always the difference between the reference and an electrode, voltages are lowest for electrodes closest to the reference electrode. You could check where voltages are minimal across trials and for each participant. If then for example that is close to Cz, it is likely that data were referenced to the vertex. Just an idea, it might work…but perhaps someone else has a better idea? Best, Christine Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Casper van Heck Gesendet: Mittwoch, 21. September 2016 14:25 An: fieldtrip at science.ru.nl Betreff: [FieldTrip] Lost reference location Dear all, We've recently started working on an old dataset, but have ran into a problem; nobody bothered to write down where the reference was placed... Does anybody have ideas on how to reconstruct the location of the reference, based on (some aspect of) the data? Best regards, Casper van Heck and Tineke van Rijn -------------- next part -------------- An HTML attachment was scrubbed... URL: From litvak.vladimir at gmail.com Wed Sep 21 16:26:28 2016 From: litvak.vladimir at gmail.com (Vladimir Litvak) Date: Wed, 21 Sep 2016 15:26:28 +0100 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: If you need to know the reference for analysis purposes the easiest thing is to just rereference to another electrode or the average reference. Then it wouldn't matter what the original reference was. Best, Vladimir On Wed, Sep 21, 2016 at 1:57 PM, Blume Christine wrote: > Dear Casper and Tineke, > > > > As voltage is always the difference between the reference and an > electrode, voltages are lowest for electrodes closest to the reference > electrode. You could check where voltages are minimal across trials and for > each participant. If then for example that is close to Cz, it is likely > that data were referenced to the vertex. Just an idea, it might work…but > perhaps someone else has a better idea? > > > > Best, > > Christine > > > > *Von:* fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces@ > science.ru.nl] *Im Auftrag von *Casper van Heck > *Gesendet:* Mittwoch, 21. September 2016 14:25 > *An:* fieldtrip at science.ru.nl > *Betreff:* [FieldTrip] Lost reference location > > > > Dear all, > > > > We've recently started working on an old dataset, but have ran into a > problem; nobody bothered to write down where the reference was placed... > Does anybody have ideas on how to reconstruct the location of the > reference, based on (some aspect of) the data? > > > > Best regards, > > > > Casper van Heck and Tineke van Rijn > > _______________________________________________ > 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 xianwei.che at monash.edu Thu Sep 22 06:26:21 2016 From: xianwei.che at monash.edu (Xianwei Che) Date: Thu, 22 Sep 2016 14:26:21 +1000 Subject: [FieldTrip] creating difference wave Message-ID: Dear list, I have some concerns of how to create difference wave between two conditions. Here is what I want to look at: I have grand average time-freqency data of two conditions ("GA1","GA2"), and one behavioural measurement. Now I want to do so some regression/correlation analysis between the behavioural measurement and the contrasted time-freqency data (GA1-GA2). I did some googling and it is suggested to create the difference wave first, as per here (http://www.fieldtriptoolbox.org/faq/how_can_i_test_an_ interaction_effect_using_cluster-based_permutation_tests). >From these 4 data structures, you now make 2 difference data structures in the following way: - Copy GA11 to GAdiff11_12 and perform the assignment GAdiff11_12.avg=GA11.avg-GA12.avg. - Copy GA21 to GAdiff21_22 and perform the assignment GAdiff21_22.avg=GA21.avg-GA22.avg. I got confused about the '.avg' here. Powspctrm is 4-d data in each GA (subject.channel.frequency.time); so what is and how to calculate the average (.avg) in each GA structure. Or is it just a filed in each GA as I cannot find one. Thanks a lot *-------------* *Mr Xianwei Che* *PhD Candidate* *Monash Alfred Psychiatry Research Centre (MAPrc)* *Central Clinical School & the Alfred * *Monash University* *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* -------------- next part -------------- An HTML attachment was scrubbed... URL: From xianwei.che at monash.edu Thu Sep 22 08:31:14 2016 From: xianwei.che at monash.edu (Xianwei Che) Date: Thu, 22 Sep 2016 16:31:14 +1000 Subject: [FieldTrip] creating difference wave In-Reply-To: References: Message-ID: Dear list, Here is my understanding of this. The field ".avg" is in the output of timelockanalysis, which is the average across the trials. But in the output of freqanalysis there is no ".avg" field as the field "powspctrm " is the "averaged" results. So, if I want to create a difference wave of the freqanalysis between two conditions; I just use the ft_math to subtract the field "powspctrm" in one condition from the other one. I don't know if this is right; any suggestion would be appreciated. Thanks *-------------* *Mr Xianwei Che* *PhD Candidate* *Monash Alfred Psychiatry Research Centre (MAPrc)* *Central Clinical School & the Alfred * *Monash University* *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* On 22 September 2016 at 14:26, Xianwei Che wrote: > Dear list, > > I have some concerns of how to create difference wave between two > conditions. Here is what I want to look at: > > I have grand average time-freqency data of two conditions ("GA1","GA2"), > and one behavioural measurement. Now I want to do so some > regression/correlation analysis between the behavioural measurement and the > contrasted time-freqency data (GA1-GA2). > > I did some googling and it is suggested to create the difference wave > first, as per here (http://www.fieldtriptoolbox.o > rg/faq/how_can_i_test_an_interaction_effect_using_cluster- > based_permutation_tests). > > From these 4 data structures, you now make 2 difference data structures in > the following way: > > - Copy GA11 to GAdiff11_12 and perform the assignment > GAdiff11_12.avg=GA11.avg-GA12.avg. > - Copy GA21 to GAdiff21_22 and perform the assignment > GAdiff21_22.avg=GA21.avg-GA22.avg. > > > I got confused about the '.avg' here. Powspctrm is 4-d data in each GA > (subject.channel.frequency.time); so what is and how to calculate the > average (.avg) in each GA structure. > > Or is it just a filed in each GA as I cannot find one. > > Thanks a lot > > *-------------* > *Mr Xianwei Che* > *PhD Candidate* > *Monash Alfred Psychiatry Research Centre (MAPrc)* > *Central Clinical School & the Alfred * > *Monash University* > *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* > -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Thu Sep 22 20:55:07 2016 From: mklados at gmail.com (Manousos Klados) Date: Thu, 22 Sep 2016 14:55:07 -0400 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From Elana.Harris at cchmc.org Fri Sep 23 19:21:15 2016 From: Elana.Harris at cchmc.org (Harris, Elana) Date: Fri, 23 Sep 2016 17:21:15 +0000 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: References: Message-ID: <1cfe2a63112349099f027f080d671a30@cchmc.org> Hello, Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? Thanks, Elana ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Nugent, Allison C. (NIH/NIMH) [E] Sent: Wednesday, August 24, 2016 12:11 PM To: 'fieldtrip at science.ru.nl' Subject: [FieldTrip] NIH MEG Workshop Reminder! A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. At this meeting, we plan to address the following four themes: 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? 3. How can we develop and support infrastructure to share data and facilitate big science? 4. How could an MEG-North America consortium work to address these issues? Keynote Speakers: Sylvain Baillet, PhD, Director, MEG Core McGill University, McConnell Brain Imaging Center Dimitrios Pantazis, PhD, Director of MEG Lab, Martinos Imaging Center Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia Julia M. Stephen, PhD, Director, MEG/EEG Core, The Mind Research Network For more details, visit http://megworkshop.nih.gov Registration to this NIH sponsored event is free of charge. We hope to see you in Bethesda in November! Dr. Richard Coppola, Director, NIMH MEG Core Dr. Allison C Nugent, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH Register Now at Eventbrite! Allison Nugent, PhD Director of Neuroimaging Research Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph 301-451-8863 -------------- next part -------------- An HTML attachment was scrubbed... URL: From Douglas.Rose at cchmc.org Fri Sep 23 22:39:46 2016 From: Douglas.Rose at cchmc.org (Rose, Douglas) Date: Fri, 23 Sep 2016 20:39:46 +0000 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: <1cfe2a63112349099f027f080d671a30@cchmc.org> References: <1cfe2a63112349099f027f080d671a30@cchmc.org> Message-ID: <2EBA7945365E4C4498225168A217A7C8975AE4A0@MCEXMB2.chmccorp.cchmc.org> Congrats on going to workshop. Used to live in DC so did not ever need to use hotels. Hotels there in Bethesda probably very expensive. Hotels.com might be helpful. You could probably write Rich Coppola for suggestions. There is the Metro station on campus and some buses perhaps from there to the NIMH station where conference is. So some not too expensive hotel on the same Metro line might be good. Doug From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Harris, Elana Sent: Friday, September 23, 2016 1:21 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] NIH MEG Workshop Hello, Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? Thanks, Elana ________________________________ From: fieldtrip-bounces at science.ru.nl > on behalf of Nugent, Allison C. (NIH/NIMH) [E] > Sent: Wednesday, August 24, 2016 12:11 PM To: 'fieldtrip at science.ru.nl' Subject: [FieldTrip] NIH MEG Workshop Reminder! A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. At this meeting, we plan to address the following four themes: 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? 3. How can we develop and support infrastructure to share data and facilitate big science? 4. How could an MEG-North America consortium work to address these issues? Keynote Speakers: Sylvain Baillet, PhD, Director, MEG Core McGill University, McConnell Brain Imaging Center Dimitrios Pantazis, PhD, Director of MEG Lab, Martinos Imaging Center Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia Julia M. Stephen, PhD, Director, MEG/EEG Core, The Mind Research Network For more details, visit http://megworkshop.nih.gov Registration to this NIH sponsored event is free of charge. We hope to see you in Bethesda in November! Dr. Richard Coppola, Director, NIMH MEG Core Dr. Allison C Nugent, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH Register Now at Eventbrite! Allison Nugent, PhD Director of Neuroimaging Research Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph 301-451-8863 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nick.peatfield at gmail.com Sat Sep 24 01:55:27 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Fri, 23 Sep 2016 16:55:27 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM Message-ID: Hi all, I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. With Regards, Nick [image: Inline images 1] -- Nicholas Peatfield, PhD -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image (3).png Type: image/png Size: 80865 bytes Desc: not available URL: From a.stolk8 at gmail.com Sat Sep 24 03:46:04 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Fri, 23 Sep 2016 18:46:04 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: References: Message-ID: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Hi Nick, You may want to have a look at ft_convert_coordsys which can switch volumes between different coordinate systems. Best, Arjen > On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield wrote: > > Hi all, > > I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). > > So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). > > Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. > > With Regards, > > Nick > > > > -- > Nicholas Peatfield, PhD > > _______________________________________________ > 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 nick.peatfield at gmail.com Sat Sep 24 06:24:10 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Fri, 23 Sep 2016 21:24:10 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Message-ID: Hi Arjen, Yeah I looked into that but spm to ctf is not supported. And changing the grads to spm seems also not possible. Unless I use ft realignsens but the behaviour of that seems a little weird in my experience, and seems more suited to electrodes. Cheers Nick On Sep 23, 2016 7:35 PM, "Arjen Stolk" wrote: > Hi Nick, > > You may want to have a look at ft_convert_coordsys which can switch > volumes between different coordinate systems. > > Best, > Arjen > > On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield < > nick.peatfield at gmail.com> wrote: > > Hi all, > > I'm getting into a problem wherein I have headmodel that are in SPM space > and the grads are in CTF space. I would usually keep all the headmodels in > CTF space and align based on that but for this dataset and the format of > the MRIs,POS etc... there seems to be some problems (could take longer to > explain but lets keep this brief). > > So this of course leads to the issue that the grad and the headmodel > within beamformer_lcmv is misaligned by 90 degrees, which is of course not > good. Is there a quick solution that I have not come across to either > convert the headmodel to ctf or convert the grad structure to spm coordsys? > When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys > = 'ctf') but the outputted sourcemodel is still misaligned between the > headmodel and the grads (see attached image - oh and the lf is also > misaligned of course). > > Any help would be greatly appreciated. And I hope that this question > hasn't come up before as I did quite a bit of google searching before > sending this email. > > With Regards, > > Nick > > > > -- > Nicholas Peatfield, PhD > > _______________________________________________ > 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 Sat Sep 24 13:27:10 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sat, 24 Sep 2016 11:27:10 +0000 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Message-ID: <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> Hi Nick, You need to use the anatomical MRI that you used to create your headmodel etc., register it to ctf-space using ft_volumerealign (in the interactive mode, it seems), and then use some magical matrix multiplications to get the appropriate transformation matrix that can be applied to the headmodel (to get it in ctf space), or (when taking the inverse of this transformation matrix) to the grad structure (to get it in spm space). The solution is embedded here: http://www.fieldtriptoolbox.org/tutorial/minimumnormestimate look for the transform_vox2spm and transform_vox2ctf, and the magical variable T. Best, Jan-Mathijs On 24 Sep 2016, at 06:24, Nicholas A. Peatfield > wrote: Hi Arjen, Yeah I looked into that but spm to ctf is not supported. And changing the grads to spm seems also not possible. Unless I use ft realignsens but the behaviour of that seems a little weird in my experience, and seems more suited to electrodes. Cheers Nick On Sep 23, 2016 7:35 PM, "Arjen Stolk" > wrote: Hi Nick, You may want to have a look at ft_convert_coordsys which can switch volumes between different coordinate systems. Best, Arjen On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield > wrote: Hi all, I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. With Regards, Nick -- Nicholas Peatfield, PhD _______________________________________________ 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 nick.peatfield at gmail.com Sat Sep 24 22:35:36 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Sat, 24 Sep 2016 13:35:36 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> Message-ID: Hi Jan-Mathijs, I found the magical variable T - thanks for the solution! Regards, Nick On 24 September 2016 at 04:27, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Hi Nick, > > You need to use the anatomical MRI that you used to create your headmodel > etc., register it to ctf-space using ft_volumerealign (in the interactive > mode, it seems), and then use some magical matrix multiplications to get > the appropriate transformation matrix that can be applied to the headmodel > (to get it in ctf space), or (when taking the inverse of this > transformation matrix) to the grad structure (to get it in spm space). > > The solution is embedded here: http://www.fieldtriptoolbox.org/tutorial/ > minimumnormestimate > > look for the transform_vox2spm and transform_vox2ctf, and the magical > variable T. > > Best, > Jan-Mathijs > > > On 24 Sep 2016, at 06:24, Nicholas A. Peatfield > wrote: > > Hi Arjen, > > Yeah I looked into that but spm to ctf is not supported. And changing the > grads to spm seems also not possible. Unless I use ft realignsens but the > behaviour of that seems a little weird in my experience, and seems more > suited to electrodes. > > Cheers > > Nick > > On Sep 23, 2016 7:35 PM, "Arjen Stolk" wrote: > >> Hi Nick, >> >> You may want to have a look at ft_convert_coordsys which can switch >> volumes between different coordinate systems. >> >> Best, >> Arjen >> >> On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield < >> nick.peatfield at gmail.com> wrote: >> >> Hi all, >> >> I'm getting into a problem wherein I have headmodel that are in SPM space >> and the grads are in CTF space. I would usually keep all the headmodels in >> CTF space and align based on that but for this dataset and the format of >> the MRIs,POS etc... there seems to be some problems (could take longer to >> explain but lets keep this brief). >> >> So this of course leads to the issue that the grad and the headmodel >> within beamformer_lcmv is misaligned by 90 degrees, which is of course not >> good. Is there a quick solution that I have not come across to either >> convert the headmodel to ctf or convert the grad structure to spm coordsys? >> When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys >> = 'ctf') but the outputted sourcemodel is still misaligned between the >> headmodel and the grads (see attached image - oh and the lf is also >> misaligned of course). >> >> Any help would be greatly appreciated. And I hope that this question >> hasn't come up before as I did quite a bit of google searching before >> sending this email. >> >> With Regards, >> >> Nick >> >> >> >> -- >> Nicholas Peatfield, PhD >> >> _______________________________________________ >> 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 > -- Nicholas Peatfield, PhD -------------- next part -------------- An HTML attachment was scrubbed... URL: From dkicic at gmail.com Sat Sep 24 22:46:28 2016 From: dkicic at gmail.com (Dubravko Kicic) Date: Sat, 24 Sep 2016 22:46:28 +0200 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: <1cfe2a63112349099f027f080d671a30@cchmc.org> References: <1cfe2a63112349099f027f080d671a30@cchmc.org> Message-ID: Dear Elana, I recently stayed in DoubleTree by Hilton Bethesda, which is some 10 minutes walk from NIH campus. The prices were not that expensive, some 160 USD per night (dependining on current events, though). The hotel is very clean and the service is good. Very quiet rooms, good sleep. The from opposite side of the hotel there is a super nice residential area, excellent for a morning walk or jogging. At the rear side, on 5 minutes walk there are streets with very cosy restaurants and bars. Metro station is 5 minutes walk towards the city, and the other one is at about 10 minutes walk in NIH campus. A highly recommended hotel! Best regards! Dubravko Dubravko Kičić, Ph.D., EMBA CEO & President of the Board Bicro BIOCentre Ltd. Biosciences Technology Commercialisation and Incubation Centre Borongajska cesta 83h, 10000 Zagreb, CROATIA E-mail: dubravko.kicic at biocentre.hr T: +385 1 6458 643 | M: +385 91 5956 569 | W: www.biocentre.hr > On 23 Sep 2016, at 19:21, Harris, Elana wrote: > > Hello, > > Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? > > Thanks, > > Elana > > > From: fieldtrip-bounces at science.ru.nl > on behalf of Nugent, Allison C. (NIH/NIMH) [E] > > Sent: Wednesday, August 24, 2016 12:11 PM > To: 'fieldtrip at science.ru.nl ' > Subject: [FieldTrip] NIH MEG Workshop > > Reminder! > > A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. > > At this meeting, we plan to address the following four themes: > > 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? > 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? > 3. How can we develop and support infrastructure to share data and facilitate big science? > 4. How could an MEG-North America consortium work to address these issues? > > Keynote Speakers: > > Sylvain Baillet, PhD , Director, MEG Core McGill University, McConnell Brain Imaging Center > Dimitrios Pantazis, PhD , Director of MEG Lab, Martinos Imaging Center > Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children’s Hospital of Philadelphia > Julia M. Stephen, PhD , Director, MEG/EEG Core, The Mind Research Network > > For more details, visit http://megworkshop.nih.gov > > Registration to this NIH sponsored event is free of charge. > > We hope to see you in Bethesda in November! > > Dr. Richard Coppola , Director, NIMH MEG Core > Dr. Allison C Nugent , Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH > > Register Now at Eventbrite! > > > Allison Nugent, PhD > Director of Neuroimaging Research > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph 301-451-8863 > > > _______________________________________________ > 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 na.so.ir at gmail.com Mon Sep 26 08:50:03 2016 From: na.so.ir at gmail.com (Narjes Soltani) Date: Mon, 26 Sep 2016 10:20:03 +0330 Subject: [FieldTrip] Change in configuration file Message-ID: Hi I am writing my own trial function in fieldtrip and I need to pass some additional information as input argument to this function, but I wonder if it is also possible to include these information in ft_definetrial configuration file instead of passing them as input argument in the function. I checked the already available parameters in ft_definetrial configuration file, but none of them seemed to be useful for me for passing the new information I need for further processing. Best Regards Narjes Soltani -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Sep 26 10:13:36 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 26 Sep 2016 08:13:36 +0000 Subject: [FieldTrip] Change in configuration file In-Reply-To: References: Message-ID: <3328E538-26E3-49C4-A322-36CB35D81B37@donders.ru.nl> Hi Narjes, I believe you could put the required creative stuff in cfg.trialdef. This should pass unscathed through ft_definetrial into the trialfun. Best, Jan-Mathijs > On 26 Sep 2016, at 08:50, Narjes Soltani wrote: > > Hi > I am writing my own trial function in fieldtrip and I need to pass some additional information as input argument to this function, but I wonder if it is also possible to include these information in ft_definetrial configuration file instead of passing them as input argument in the function. I checked the already available parameters in ft_definetrial configuration file, but none of them seemed to be useful for me for passing the new information I need for further processing. > > > Best Regards > Narjes Soltani > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From mklados at gmail.com Mon Sep 26 20:55:06 2016 From: mklados at gmail.com (Manousos Klados) Date: Mon, 26 Sep 2016 11:55:06 -0700 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From pooneh.baniasad at gmail.com Tue Sep 27 13:15:20 2016 From: pooneh.baniasad at gmail.com (pooneh baniasad) Date: Tue, 27 Sep 2016 14:45:20 +0330 Subject: [FieldTrip] Fwd: Convert MNI to ctf In-Reply-To: References: Message-ID: Dear FieldTrip community ​I'm using the 'Subject01.mri'​ for constructing BEM headmodel for EEG source analysis which is defined in ctf coordination. On the other hand I use 'cortex_20484.surf.gii' which is defined in MNI coordination for adding the dipole sources. I want to convert the MNI into ctf to match the headmodel with template. I already found ft_volumenormalise function although it needs the inputs that I don't know what are they. ​ Can anyone help me? -- Bests Pouneh Baniasad -------------- next part -------------- An HTML attachment was scrubbed... URL: From elisabethsusanne.may at gmail.com Tue Sep 27 14:46:55 2016 From: elisabethsusanne.may at gmail.com (Elisabeth May) Date: Tue, 27 Sep 2016 14:46:55 +0200 Subject: [FieldTrip] Question about cluster-based permutation tests on linear mixed models Message-ID: Dear FieldTripers, I have a question about the potential use of cluster-based permutation tests for results obtained using linear mixed models. We are working with data from a 10 min EEG experiment on source level with the aim to quantify the relationship of brain activity in different frequency bands with continous perceptual ratings across 20 subjects in different experimental conditions. Thus, we have 10 min time courses of brain activity and ratings for each voxel for different conditions and want to test a) if there are significant relationships in the single conditions and b) if these relationships differ between two conditions. To this end, I have calculated linear mixed models in R using the lme4 toolbox. For both the single condition relationships and the condition contrasts, they result in a single t-value (and a corresponding p-value), which is based on information on both the single subject and the group level (i.e. we perform a multi-level analysis). However, with more than 2000 voxels, we have a lot of t-values and are wondering if there is a way to apply cluster-based tests to correct for multiple comparisons. The main problem I see is that I only have one multilevel t-value for the effect across all subjects, i.e. I don't have single subjects values, which I could then e.g. randomize between conditions as normally done in cluster-based permutation tests. (Or rather, I would be able to extract single subject values but would then loose the advantage of the multi-level analysis.) I found an old thread in the mailinglist archive where it was suggested to flip the signs of the t-statistic for cluster-level correction ( https://mailman.science.ru.nl/pipermail/fieldtrip/2012-July/005375.html). I understand that, in our case, I would do this randomly for all voxels in each randomization and then build spatial clusters on the resulting (partly flipped) t-values. However, I am not sure if that is a valid approach based on the null hypothesis that there are no significant relations in my single conditions (a) or no significant relationship differences in my condition contrasts (b). For the condition contrasts, I would be able to permute the condition labels as normally done in cluster-based permutation tests,I think, but would then have to recalculate the linear mixed models for all voxels in every permutation. This would result in a very high computational load. Does anyone have any experience with this kind of analysis? Would the flipping of t-values be a valid approach (and if yes, is there anything to keep in mind in particular)? Can you think of other ways to combine linear mixed models with a multiple comparison correction on the cluster level? Any help would be greatly appreciated! Best wishes from Munich, Elisabeth -- Elisabeth S. May, PhD Klinikum rechts der Isar Technische Universität München Ismaninger Str. 22 81675 München http://www.painlabmunich.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From caspervanheck at gmail.com Tue Sep 27 15:32:59 2016 From: caspervanheck at gmail.com (Casper van Heck) Date: Tue, 27 Sep 2016 15:32:59 +0200 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Christine, As there are only a few possibilities, this might work! We'll try that! Dear Vladimir, If the original reference is close to an electrode we're interested in, and we do not see an effect on that electrode, then we cannot determine if there is indeed no effect or if the original reference made the effect disappear (due to it also 'seeing' the same activity). Thanks, all! Best regards, Casper On 21 September 2016 at 16:26, Vladimir Litvak wrote: > If you need to know the reference for analysis purposes the easiest thing > is to just rereference to another electrode or the average reference. Then > it wouldn't matter what the original reference was. > > Best, > > Vladimir > > On Wed, Sep 21, 2016 at 1:57 PM, Blume Christine < > christine.blume at sbg.ac.at> wrote: > >> Dear Casper and Tineke, >> >> >> >> As voltage is always the difference between the reference and an >> electrode, voltages are lowest for electrodes closest to the reference >> electrode. You could check where voltages are minimal across trials and for >> each participant. If then for example that is close to Cz, it is likely >> that data were referenced to the vertex. Just an idea, it might work…but >> perhaps someone else has a better idea? >> >> >> >> Best, >> >> Christine >> >> >> >> *Von:* fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at scie >> nce.ru.nl] *Im Auftrag von *Casper van Heck >> *Gesendet:* Mittwoch, 21. September 2016 14:25 >> *An:* fieldtrip at science.ru.nl >> *Betreff:* [FieldTrip] Lost reference location >> >> >> >> Dear all, >> >> >> >> We've recently started working on an old dataset, but have ran into a >> problem; nobody bothered to write down where the reference was placed... >> Does anybody have ideas on how to reconstruct the location of the >> reference, based on (some aspect of) the data? >> >> >> >> Best regards, >> >> >> >> Casper van Heck and Tineke van Rijn >> >> _______________________________________________ >> 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 carsten.wolters at uni-muenster.de Wed Sep 28 15:30:20 2016 From: carsten.wolters at uni-muenster.de (Carsten Wolters) Date: Wed, 28 Sep 2016 15:30:20 +0200 Subject: [FieldTrip] Ref. 11890: Neuroscientist(s) with focus on simulation of high-definition transcranial electric stimulation (hd-tES) Message-ID: <57EBC5EC.3080700@uni-muenster.de> Dear colleagues, please forward the ad below to anyone who could be interested and post to your departmental lists. Thanks and sorry for possible multiple postings. I will be on Biomag2016 in Seoul from Oct.1-6 and would be happy to discuss with possible candidates. Best regards Carsten Wolters ********************************************************************************************************* Neuroscientist(s) with focus on simulation of high-definition transcranial electric stimulation (hd-tES) Ref. 11890 The*Institute for Biomagnetism and Biosignalanalysis* at the medical faculty of the University of Münster, Germany, invites applications for a PostDoctoral Researcher and/or for Doctoral Students *Salary according to TV-L E13 **(100% or 50 %)** **Full-Time with 38,5 (hours/week) or Part-Time with 19,25 (hours/week)** *** for three year positions to work on the development and evaluation of new (i.e., new inverse electrode optimization and new forward finite element method algorithms) simulation approaches for hd-tES using realistic head volume conductor models within the DFG-funded priority program SPP1665/2 (second funding period: from 2016 to 2019) “Resolving and manipulating neuronal networks in the mammalian brain - from correlative to causal analysis” in project “Individualized closed-loop transcranial alternating current stimulation”. More informations can be found on http://www.spp1665.de/. The successful applicant holds a PhD degree and/or a Master’s degree (or equivalent) in a relevant academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, or equivalent) and experience with the Linux operating system is expected, because large software toolboxes are used and further developed. The working language at the institute is English. Experience with brain stimulation and with the measurement and analysis of brain signals is advantageous, but not essential. The applicant’s merits are assessed on the basis of the quality of PhD and/or Master’s level studies and thesis, previous experience with numerical mathematics, inverse problems and optimization approaches, software development, motivation and research interests. The location for this research will mainly be the workgroups “SIM-NEURO: Simulation, Imaging and Modeling of NEUROnal networks in the human brain” of PD Dr. Wolters at the Institute for Biomagnetism and Biosignalanalysis (IBB), “Imaging” of Prof. Dr. Martin Burger at the Institute for Computational and Applied Mathematics and “Applications of Partial Differential Equations” of JProf. Dr. Christian Engwer, all at the University of Münster in Germany. Expected close collaborations and visits are to the partnering institutes, namely the University of Oldenburg (Prof. Dr. Christoph Herrmann) and the University of Hamburg (Dr. Till Schneider). The application should include a statement of research interests and reasons for applying to the project, a curriculum vitae (max. 5 pages) composed according to good scientific practice, a certificate of PhD and/or Master’s degree, copy of the master’s thesis and grades of Master’s level studies, the names and e-mail addresses of two referees and a proof of proficiency in English. The position will be open until filled. To apply for the position until *Oct.31*, *2016*, please send the above documents as pdfs to *PD Dr. Carsten Wolters, **Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, 48149 Münster, Germany*, or by Email to *carsten.wolters(at)­uni-muenster(dot)­de* . For additional information please contact *PD Dr. Carsten Wolters* (Email: *carsten.wolters(at)­uni-muenster(dot)­de* , Phone: +49 (0)251/83-56904). Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference. Link to the position: http://klinikum.uni-muenster.de/index.php?id=3290&tx_ttnews[tt_news]=6562&cHash=afb5f5f3421732c32f5c0de0bfc6587c -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: carsten_wolters.vcf Type: text/x-vcard Size: 402 bytes Desc: not available URL: From joseluisblues at gmail.com Wed Sep 28 17:02:39 2016 From: joseluisblues at gmail.com (Jose) Date: Wed, 28 Sep 2016 17:02:39 +0200 Subject: [FieldTrip] axial gradiometers vs planar gradient Message-ID: dear fieldtrip community, I'm working with CTF MEG data, I have a confusion regarding the use of the (pure) axial gradiometers and the synthetic planar gradients, >From what I have read "the planar field gradient simplifies the interpretation of the sensor-level data because the maximal signal power is located above the source". In practice, this means that the topography would resemble more the sources? Is that correct? Would be meaningless to do this if one intend to do source analyses anyway? However is not clear for me if the planar gradient is used only for visualization purposes, or if is intended to replace the use of axial gradiometers for data analysis. Some papers do mention the aforementioned transformation but then they do not specify which data is used to run statistical analysis so I assume they do it with planar gradients. Others they clearly perform statistical analyses such as non-parametric cluster permutation tests with planar gradient data. So, the second question would be if one should run statistical analyses in planar gradient or axial gradiometers data?. What is the criteria to choose one or the other? If one apply cluster-based permutation tests to either axial gradiometers or the planar gradient one will find distinct results because the activity is distributed in different sensors, so distinct clusters will be observed, right? Does make sense to find different results depending on whether we analyze gradiometer or planar data? Some recommend use planar gradient data to perform statistics ( https://mailman.science.ru.nl/pipermail/fieldtrip/2012-November/005905.html) while others other advise against it ( https://mailman.science.ru.nl/pipermail/fieldtrip/2010-March/002657.html), Is there a consensus at the moment? I would really appreciate some directions here, best, Jose -------------- next part -------------- An HTML attachment was scrubbed... URL: From tomh at kurage.nimh.nih.gov Wed Sep 28 17:48:18 2016 From: tomh at kurage.nimh.nih.gov (Tom Holroyd) Date: Wed, 28 Sep 2016 11:48:18 -0400 Subject: [FieldTrip] axial gradiometers vs planar gradient In-Reply-To: References: Message-ID: <20160928114818.73806877@kurage.nimh.nih.gov> On Wed, 28 Sep 2016 17:02:39 +0200 Jose wrote: > dear fieldtrip community, > > I'm working with CTF MEG data, > I have a confusion regarding the use of the (pure) axial gradiometers and > the synthetic planar gradients, If you are doing source localization, there is no reason to convert to planar. It can only degrade the data, because it is an interpolation. -- Dr. Tom -- "A man of genius makes no mistakes. His errors are volitional and are the portals of discovery." -- James Joyce From joseluisblues at gmail.com Wed Sep 28 18:05:15 2016 From: joseluisblues at gmail.com (Jose) Date: Wed, 28 Sep 2016 18:05:15 +0200 Subject: [FieldTrip] axial gradiometers vs planar gradient In-Reply-To: <20160928114818.73806877@kurage.nimh.nih.gov> References: <20160928114818.73806877@kurage.nimh.nih.gov> Message-ID: Thanks Tom, Yes, I've read that for performing source reconstruction one use the axial gradiometer data, But, at the moment I'm at the sensor-level analysis, best Jose -------------- next part -------------- An HTML attachment was scrubbed... URL: From robert.oostenveld at donders.ru.nl Wed Sep 28 19:05:07 2016 From: robert.oostenveld at donders.ru.nl (Oostenveld, R. (Robert)) Date: Wed, 28 Sep 2016 17:05:07 +0000 Subject: [FieldTrip] Fwd: open engineer position focused on EEG of baby brains References: Message-ID: <5C55D865-B79F-440B-94EF-4297553C4099@donders.ru.nl> Begin forwarded message: From: Virginie van Wassenhove > Subject: [FieldTrip-news] Fwd: Offre de poste Stat Date: 28 September 2016 at 11:46:34 GMT+2 To: >, > Cc: Ghislaine Dehaene > Dear all, please find below information about an open engineer position focused on EEG of baby brains. Best, Virginie Engineer/Statistician position The INSERM / CEA Development of Neuroimaging lab in Neurospin, Saclay (91, France) offers a 2 to 5 years position for a research engineer or statistician to develop robust processing and analysis methods of infants’ brain signal measured by magnetic resonance imaging (MRI) and electroencephalography (EEG). Brain imaging techniques provide large amounts of data that require new analysis techniques and a robust control of the reliability of the results, particularly in infants whose patience is minimal, the vigilance variable and the movements important. All these factors affect the quality of the signal. Furthermore infants’ spontaneous activity is variable and ample generating greater endogenous background noise than in adults. The aim of the work will be to 1) Develop robust pipelines for EEG/MRI data processing taking into account the infants’ signal characteristics in order to robustly extract the brain activity associated with a cognitive task from the endogenous and exogenous noise 2) Characterize the properties of the endogenous brain activity and its maturation during the first year of life in order to understand the functional architecture of the main networks that allow the development of complex cognitive functions (e.g. language, consciousness) in the human species. Applicants should possess a solid technical background in signal processing and/or statistics and be able to code in Matlab and/or Python. The position is opened for a maximum of 5 years, funded by a European contract (CDD use) from 1 November 2016. Salary is based on qualifications (from 1900 euros / month, medical insurance comprised) Send your CV and a motivation letter to ghislaine.dehaene at cea.fr Lab Website http://www.unicog.org/site_2016/ Ghislaine Dehaene-Lambertz, M.D., Ph.D. Director of the Developmental Neuroimaging Lab http://moncerveaualecole.com/ ################################################# Developmental Neuroimaging Lab INSERM, U992 CEA/SAC/DSV/DRM/NeuroSpin Bat 145, point courrier 156 91191 GIF/YVETTE, France Phone: +33 1 69 08 81 72 Fax: +33 1 69 08 79 73 Mail: ghislaineDOTdehaeneAROBASEcea.fr www.unicog.org Publications in http://www.unicog.org/biblio/Author/DEHAENE-LAMBERTZ-G.html ################################################# -- Virginie van Wassenhove CEA/NeuroSpin MEG - UNICOG Bat 145 PC 156 F-91191 Gif s/ Yvette FRANCE office: +33(0)1 69 08 1667 cell: +33(0)6 15 83 4955 skype, twitter: virginie_vw sites.google.com/site/virginievanwassenhove/ _______________________________________________ fieldtrip-news mailing list fieldtrip-news at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip-news -------------- next part -------------- An HTML attachment was scrubbed... URL: From bioeng.yoosofzadeh at gmail.com Wed Sep 28 19:28:25 2016 From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh) Date: Wed, 28 Sep 2016 13:28:25 -0400 Subject: [FieldTrip] Fwd: Issue with projection In-Reply-To: References: Message-ID: Hi all, I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). Any comment would be appreciated! Best, Vahab -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: sample_resutls.png Type: image/png Size: 321899 bytes Desc: not available URL: From tzvetan.popov at uni-konstanz.de Wed Sep 28 20:22:04 2016 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Wed, 28 Sep 2016 20:22:04 +0200 Subject: [FieldTrip] Fwd: Issue with projection In-Reply-To: References: Message-ID: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> Hi Vehab, You have to normalize the individual volume to the MNI template. So use ft_volumenormalise first and try again. Or, if you used MNI aligned grid that specify the source.pos = template grid.pos. Good luck Tzvetan > Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh : > > Hi all, > > I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). > > Any comment would be appreciated! > > Best, > Vahab > > _______________________________________________ > 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 Thu Sep 29 14:24:23 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 29 Sep 2016 12:24:23 +0000 Subject: [FieldTrip] Issue with projection In-Reply-To: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> References: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> Message-ID: <286F8441-A34B-41E4-8892-435AAF19AD4F@donders.ru.nl> In addition to Tzvetan’s comment: please do not try and interpolate directly onto the inflated cortical sheet. You also need to provide the non-inflated sheet for the interpolation (after which the interpolated data can be displayed on the inflated sheet). Jan-Mathijs On 28 Sep 2016, at 20:22, Tzvetan Popov > wrote: Hi Vehab, You have to normalize the individual volume to the MNI template. So use ft_volumenormalise first and try again. Or, if you used MNI aligned grid that specify the source.pos = template grid.pos. Good luck Tzvetan Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh >: Hi all, I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). Any comment would be appreciated! Best, Vahab _______________________________________________ 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 bioeng.yoosofzadeh at gmail.com Thu Sep 29 14:54:50 2016 From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh) Date: Thu, 29 Sep 2016 08:54:50 -0400 Subject: [FieldTrip] fieldtrip Digest, Vol 70, Issue 27 In-Reply-To: References: Message-ID: Dear Tzvetan, I really appreciate your help. Actually, I tried ft_volumenormalise before however with no success. When I saw your comments, I tried again. It turns out that there is an issue with my older Matlab (2012b). Now, I tried with Matlab 2016 and it worked perfectly :D Thank you again, Vahab On Thu, Sep 29, 2016 at 6:00 AM, wrote: > 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. Re: Fwd: Issue with projection (Tzvetan Popov) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Wed, 28 Sep 2016 20:22:04 +0200 > From: Tzvetan Popov > To: FieldTrip discussion list > Subject: Re: [FieldTrip] Fwd: Issue with projection > Message-ID: <896534AC-FD7B-4429-AC23-3F227E50097D at uni-konstanz.de> > Content-Type: text/plain; charset="us-ascii" > > Hi Vehab, > You have to normalize the individual volume to the MNI template. So use > ft_volumenormalise first and try again. Or, if you used MNI aligned grid > that specify the source.pos = template grid.pos. > Good luck > Tzvetan > > > Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh < > bioeng.yoosofzadeh at gmail.com>: > > > > Hi all, > > > > I am having an issue in projecting my results on a (template) cortical > map in FT and using ft_sourceplot. It seems a subset of the brain > activations has only been projected (see attached). > > > > Any comment would be appreciated! > > > > Best, > > Vahab > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: attachments/20160928/5c685362/attachment-0001.html> > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 70, Issue 27 > ***************************************** > -------------- next part -------------- An HTML attachment was scrubbed... URL: From knutsenpm at gmail.com Fri Sep 30 15:11:44 2016 From: knutsenpm at gmail.com (Per Knutsen) Date: Fri, 30 Sep 2016 15:11:44 +0200 Subject: [FieldTrip] Reading data from arbitrary source Message-ID: Hi, I am new to fieldtrip with the intention of analyzing mouse ECoG/LFP data. I already have my datasets loaded into Matlab (from a format not directly supported by fieldtrip). Next, I need to read this data into a fieldtrip structure for processing. I see frequent use of a structure called cfg, with fields: cfg.dataset cfg.trialdef.threshold cfg.trialdef.prestim cfg.trialdef.poststim etc Can anyone direct me to the documentation of this structure's format. What data is stored, what is the format, units etc? *Per M Knutsen* University of Oslo Dept. of Molecular Medicine, Physiology Sect. PB 1103 Blindern, NO-0317 Oslo +47.45103762 -------------- next part -------------- An HTML attachment was scrubbed... URL: From dlozanosoldevilla at gmail.com Fri Sep 30 15:25:14 2016 From: dlozanosoldevilla at gmail.com (Diego Lozano-Soldevilla) Date: Fri, 30 Sep 2016 15:25:14 +0200 Subject: [FieldTrip] Reading data from arbitrary source In-Reply-To: References: Message-ID: Hi Per, These two FAQs will be relevant to you: http://www.fieldtriptoolbox.org/faq/how_can_i_import_my_own_dataformat http://www.fieldtriptoolbox.org/faq/how_are_the_various_data_structures_defined best, Diego On 30 September 2016 at 15:11, Per Knutsen wrote: > Hi, > I am new to fieldtrip with the intention of analyzing mouse ECoG/LFP data. > > I already have my datasets loaded into Matlab (from a format not directly > supported by fieldtrip). Next, I need to read this data into a fieldtrip > structure for processing. I see frequent use of a structure called cfg, > with fields: > > cfg.dataset > cfg.trialdef.threshold > cfg.trialdef.prestim > cfg.trialdef.poststim > > etc > > Can anyone direct me to the documentation of this structure's format. What > data is stored, what is the format, units etc? > > > *Per M Knutsen* > University of Oslo > Dept. of Molecular Medicine, Physiology Sect. > PB 1103 Blindern, NO-0317 Oslo > +47.45103762 > > _______________________________________________ > 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 susmitasen.ece at gmail.com Fri Sep 30 19:16:52 2016 From: susmitasen.ece at gmail.com (Susmita Sen) Date: Fri, 30 Sep 2016 22:46:52 +0530 Subject: [FieldTrip] Regarding headmodel construction Message-ID: I am Susmita Sen, MS research scholar in the dept of Electronics and Electrical Communication Engineering, IIT Kharagpur. I am currently working on MEG data recorded by yokogawa system. I want to perform source reconstruction on the data. However, I do not have the MRI data along with that. so, I have planned to use the standard MRI provided by fieldtrip (downloaded from https://github.com/fieldtrip/ fieldtrip/blob/master/template/headmodel/standard_mri.mat). For preparing the head model I have followed the steps provided in the fieldtrip tutorial (http://www.fieldtriptoolbox.org/tutorial/headmodel_meg ). %% align the coordinate system load('standard_mri.mat'); % load mri data disp(mri) cfg = []; cfg.method = 'interactive'; cfg.coordsys = 'yokogawa'; cfg.snapshot = 'yes'; [mri_aligned] = ft_volumerealign(cfg,mri); %% SEGMENTATION cfg = []; cfg.output = 'brain'; segmentedmri = ft_volumesegment(cfg, mri_aligned); %% create headmodel cfg = []; cfg.method='singleshell'; vol = ft_prepare_headmodel(cfg, segmentedmri); %% visualize load grad % load gradiometer info vol = ft_convert_units(vol,'cm'); % the gradiometer info is given in cm figure; ft_plot_sens(grad, 'style', '*b'); hold on ft_plot_vol(vol); while aligning the coordinate system I have chosen fiducial points (naison, LPA and RPA) using the instruction given by http://neuroimage.usc.edu/ brainstorm/CoordinateSystems. I am attaching the figures that display the shape of the 'vol' along with the position of the sensors (from different viewing angle). However, I doubt the headmodel is corrected prepared (It dosen't look alike the figure given in the tutorial). It seems I have made some mistakes, but I am not able to detect it. I would be very thankful if you can help me in this regard. Thanks and Regards, Susmita Sen Research Scholar Audio and Bio Signal Processing Lab. E & ECE Dept. IIT Kharagpur -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol1.png Type: image/png Size: 20100 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol2.png Type: image/png Size: 22926 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol3.png Type: image/png Size: 26661 bytes Desc: not available URL: From mikexcohen at gmail.com Thu Sep 1 13:38:12 2016 From: mikexcohen at gmail.com (Mike X Cohen) Date: Thu, 1 Sep 2016 13:38:12 +0200 Subject: [FieldTrip] Biomag 2016 Data Analysis Competition Message-ID: Dear all, We are happy to announce a deadline extension (to September 20th) for three data-analysis competitions at Biomag 2016. Please see details at http://www.biomag2016.org/data_analysis_competition.php The aim of the competitions is to promote the development and application of new analysis techniques. The challenges will help to elucidate pros and cons of different techniques and attract experts from outside the MEG field. The winners of the competition will be given the opportunity to present their proposal at the Biomag meeting in Seoul (Oct 1-6) in order to spark discussions on analysis. Please encourage colleagues to participate! Best regards, Ole Jensen (sent by Mike Cohen, and on behalf of all competition organizers) -- Mike X Cohen, PhD mikexcohen.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From mikexcohen at gmail.com Thu Sep 1 13:58:36 2016 From: mikexcohen at gmail.com (Mike X Cohen) Date: Thu, 1 Sep 2016 13:58:36 +0200 Subject: [FieldTrip] Conference announcement: ICON XIII Message-ID: We are happy to make the second announcement for the ICON XIII conference, which will take place on 5-8 August 2017 in Amsterdam (the Netherlands). Amsterdam is an easily-accessible and progressive city. ICON will take place at the Beurs van Berlage, located in downtown Amsterdam and one of the most beautiful conference venues in Europe! Visit the website: http://www.icon2017.org ICON stands for International Conference for Cognitive Neuroscience. ICON has taken place every 2-3 years since 1980. This conference brings together researchers from diverse backgrounds, joined by their interest in studying the relationships amongst brain, mind, and behavior. ICON conferences are always a big success, and 2017 in Amsterdam will follow this same tradition! Symposia and poster submissions will be open from early 2017, with deadlines of 1 February for symposia and 31 March for posters. Plan your research accordingly! NEW SYMPOSIA OPTIONS In addition to standard-format symposia, ICON2017 will feature two novel formats (see "What" and "Submit" links on icon2017.org for more details): 1) "Hackathons" are computer-based sessions that can involve either a group of people working towards solving a problem, or can be more tutorial-like with the goal of teaching hands-on skills (e.g., using a toolbox or implementing an analysis in Matlab) that can be accomplished in ~2 hours (for longer workshops, consider organizing a satellite). 2) "Ask-the-experts" is a panel of experts in a topic. No specific lectures are prepared; instead there is an open Q&A/discussion session. The focus can be on a theoretical issue, methodological issue, or hotly-debated topic in cognitive neuroscience. PRE-CONFERENCE WORKSHOPS/SATELLITES We welcome pre-conference satellites, and will be happy to advertise them on the ICON website. Note that satellites are independent from ICON in terms of organization, registration, and costs. If you have any questions or would like to discuss ideas for your satellite, please contact Mike Cohen (mikexcohen at gmail.com) and Birte Forstmann (buforstmann at gmail.com). FOLLOW US ON TWITTER For up-to-date announcements before and during the ICON meeting, follow @icon2017 (see also "Media" tab on the website). http://www.icon2017.org We look forward to seeing you in beautiful Amsterdam! Mike X Cohen and Birte Forstmann -- Mike X Cohen, PhD mikexcohen.com -------------- next part -------------- An HTML attachment was scrubbed... URL: From niels.focke at uni-tuebingen.de Thu Sep 1 16:30:49 2016 From: niels.focke at uni-tuebingen.de (Niels Focke) Date: Thu, 1 Sep 2016 16:30:49 +0200 Subject: [FieldTrip] =?iso-8859-1?q?PhD_/_Research_Fellow_Position_in_Epil?= =?iso-8859-1?q?epsy_Imaging_=28MEG_/_hd-EEG=29_in_T=FCbingen/Germa?= =?iso-8859-1?q?ny?= Message-ID: <016601d2045d$6f6dc460$4e494d20$@uni-tuebingen.de> We are happy to announce a job opening: 1 PhD Student / Research Fellow (Wissenschaftlicher Mitarbeiter, 50%) for the AG Translational Neuroimaging, Neurological Clinic and Hertie Institute for Clinical Brain Research for a DFG-funded 3-years project. The successful applicant will work primarily on functional connectivity in MEG and hd-EEG in patients with genetic epilepsy. This involves graph-theoretical concepts and machine learning approaches. The aim of this project is to link the genetic causes of epilepsy with imaging patterns and improve our understanding of the pathophysiology and genotype-phenotype relations in general. The aim of this project is to link the genetic causes of epilepsy with imaging patterns and improve our understanding of the pathophysiology and genotype-phenotype relations in general. Applicants need a university degree (MA or equivalent) in physics, mathematics, biology, biomedical engineering, medicine or other related disciplines. Programming skills (Matlab) are essential as is previous knowledge of MEG or EEG and common imaging toolboxes (e.g. Fieldtrip, Brainstorm, SPM, FSL). Publications on network analysis/graph theory are beneficial for a successful application, as is previous experience with epilepsy. Since the study involves interaction with patients, German language skills are advantageous. The applicant has to be fluent in English, both written and oral. The focus of our group is the utilization of imaging and post-processing methods to better understand the neurobiology of focal and generalized epilepsies, allow individualized diagnostics and translate methodological advances into clinical applications. The applicant will have access to a unique setting including high-density MR-compatible 256-channel EEG, 3T- and 9.4T-MRI scanners, human and fetal MEG and hybrid human PET-MR facilities. The medical university clinics runs a comprehensive epilepsy surgery program including invasive EEG recordings. The applicant can be enrolled into the neuroscience PhD program including various teaching courses and further benefits (http://www.neuroschool-tuebingen.de/). The salary is according to German federal scale (TV-L, E13 50%). The initial contract is for one year. After successful interim evaluation (PhD advisory board), a prolongation for further two years is available. The university is especially encouraging the application of women. Disabled applicant are preferred in case of equal qualification. The intended start date is November 2016 with some flexibility. Please send a letter of motivation, CV, references and, if available, a sample publication to: Universitätsklinikum Tübingen Abteilung Neurologie mit Schwerpunkt Epileptologie PD Dr. Niels Focke Hoppe-Seyler-Str. 3 76076 Tübingen Germany or via E-Mail: niels.focke at uni-tuebingen.de __________________________________________________________________________ PD Dr. Niels Focke Oberarzt Abt. Neurologie mit Schwerpunkt Epileptologie Universitätsklinikum Tübingen AG Translationale Bildgebung Hertie Institut für Klinische Hirnforschung Werner Reichhardt Centre for Integrative Neuroscience -------------- next part -------------- A non-text attachment was scrubbed... Name: PhD_offer_genetic_epilepsy_imaging.pdf Type: application/pdf Size: 251282 bytes Desc: not available URL: From aborna at sandia.gov Fri Sep 2 01:10:03 2016 From: aborna at sandia.gov (Borna, Amir) Date: Thu, 1 Sep 2016 23:10:03 +0000 Subject: [FieldTrip] Importing arbitrary dataset using ft_definetrial Message-ID: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Sep 2 09:05:16 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 2 Sep 2016 07:05:16 +0000 Subject: [FieldTrip] Importing arbitrary dataset using ft_definetrial In-Reply-To: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> References: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> Message-ID: <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> Hi Amir, It should be possible to bypass ft_definetrial when calling ft_artifact_jump. One needs to supply a second input argument, i.e. ft_artifact_jump(cfg, data); As long as the cfg does not point to a dataset (i.e. does not have cfg.datafile/dataset etc.) it should work, as far as I know. Best, Jan-Mathijs On 02 Sep 2016, at 01:10, Borna, Amir > wrote: Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. _______________________________________________ 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 aborna at sandia.gov Fri Sep 2 17:59:38 2016 From: aborna at sandia.gov (Borna, Amir) Date: Fri, 2 Sep 2016 15:59:38 +0000 Subject: [FieldTrip] [EXTERNAL] Re: Importing arbitrary dataset using ft_definetrial In-Reply-To: <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> References: <1a7134b4462b4aaea6fef04d987f17ce@ES06AMSNLNT.srn.sandia.gov> <1C4957AB-E29C-456F-9CA1-4120037B4C21@donders.ru.nl> Message-ID: Hi Jan-Mathijs, Thank you for your suggestion. I haven't tried your solution yet as my question is not specific to any function; it looks like many of the ft functions require the configuration (cfg) argument which is created only by calling ft_definetial. So is there a way to call ft_definetial on a custom dataset? Thank you. Best, Amir Borna. Sandia National Lab. From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Schoffelen, J.M. (Jan Mathijs) Sent: Friday, September 02, 2016 1:05 AM To: FieldTrip discussion list Subject: [EXTERNAL] Re: [FieldTrip] Importing arbitrary dataset using ft_definetrial Hi Amir, It should be possible to bypass ft_definetrial when calling ft_artifact_jump. One needs to supply a second input argument, i.e. ft_artifact_jump(cfg, data); As long as the cfg does not point to a dataset (i.e. does not have cfg.datafile/dataset etc.) it should work, as far as I know. Best, Jan-Mathijs On 02 Sep 2016, at 01:10, Borna, Amir > wrote: Dear Fieldtrip community, I have a basic question regarding importing an arbitrary dataset into the fieldtrip. I have acquired MEG data using atomic magnetometers, and have imported my MEG data into fieldtrip and have had limited success running ICA, etc. To use most ft functions, e.g. ft_artifact_jump, it is essential to import the data using ft_definetrial. I was wondering if there is a way to use ft_definetrial to import an arbitrary dataset into fieldtrip. Thank you in advance for your help. Best, Amir Borna. Sandia National Lab. _______________________________________________ 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 belahian at memphis.edu Fri Sep 2 21:45:44 2016 From: belahian at memphis.edu (Bahareh Elahian (belahian)) Date: Fri, 2 Sep 2016 19:45:44 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: Message-ID: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis - FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_freqanalysis". FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis - FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type "help ft_freqanalysis". FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Sun Sep 4 09:25:27 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sun, 4 Sep 2016 07:25:27 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: Message-ID: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 rb643 at medschl.cam.ac.uk Sun Sep 4 18:20:17 2016 From: rb643 at medschl.cam.ac.uk (Richard Bethlehem) Date: Sun, 4 Sep 2016 16:20:17 +0000 Subject: [FieldTrip] multi-taper smoothing and frequency of interest Message-ID: <3188FAB8621D294696F13E80A7BBC97E010A621686@me-mbx4.medschl.cam.ac.uk> Dear field trippers, Would anyone be able to offer some advice on smoothing settings used for the MTMFFT method when I want to isolate lower frequencies as well as some guidance on setting the frequency of interest. What I eventually want is just the power and crosspectra for a frequency band. So, for example I am currently looking at the delta range (2-4Hz) and then it would seem a bit odd to use a smoothing kernel of 2Hz as it would provide very frequency specific information for that range right? In addition, I initially just set the foilim to [2 4], but this gives me 2 datapoints that I assume just refer to the information at 2Hz and 4Hz? Thus, instead I changed it to setting the foi as a logspaced set of frequencies within the delta range. However when I run that I still only get 9 datapoints/dimensions for the frequency. Can anyone explain why it would default to 9 or what the correct settings would be to simply get the power and crosspectra for a specific frequency band (at the moment I am simply averaging over the frequency range later on anyway)? Cheers, Richard ps: This is the code I am using: cfg_freq = []; cfg_freq.method = 'mtmfft'; cfg_freq.output = 'powandcsd'; cfg_freq.channel = 1:64; cfg_freq.keeptrials ='yes'; %do not return an average of all trials for subsequent wpli analysis cfg_freq.taper = 'dpss'; %delta cfg_freq.tapsmofrq = 0.25; cfg_freq.foi = exp(linspace(log(2),log(4),20)); [freq_data.delta] = ft_freqanalysis(cfg_freq, data_iccleaned); And this is what I used to get some adjacency matrices for subsequent network analyses: cfg_conn = []; cfg_conn.method = 'wpli'; conn.delta = ft_connectivityanalysis(cfg_conn, freq_data.delta); conn.delta = ft_checkdata(conn.delta, 'cmbrepresentation', 'full','datatype','freq'); network_delta = squeeze(nanmean(conn.delta.wplispctrm,3)); This is resting-state EEG data that has already been pre-processed and I've segmented the continuous recording into 4-second segment to create 'trials' as I want to follow up this analysis with WPLI connectivity analysis and hence I need multiple trials (correct me if I'm wrong on that as well please, but that is probably a different thread altogether). From r.oostenveld at donders.ru.nl Mon Sep 5 09:00:39 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Mon, 5 Sep 2016 09:00:39 +0200 Subject: [FieldTrip] response requested - please check the FieldTrip website Message-ID: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> Dear FieldTrip users I just got word from someone who received a warning when opening the FieldTrip website. See below, it appears blacklisted by his (institutional) security software. I checked: for me it looks fine. I also don’t see anything unusual on the server itself, but a website hack is sometimes hard to detect. Could you please check the website on unusual or suspicious behaviour? But don’t click on anything if you see something unexpected! Please let me know in a PERSONAL REPLY to this email whether it works or not. Please do NOT REPLY to all people on the list, as the others on the list won’t be able to fix it anyway and will probably be annoyed by all those email messages. Thanks, Robert -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.jpeg Type: image/jpeg Size: 31648 bytes Desc: not available URL: From r.oostenveld at donders.ru.nl Mon Sep 5 11:49:30 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Mon, 5 Sep 2016 11:49:30 +0200 Subject: [FieldTrip] response requested - please check the FieldTrip website In-Reply-To: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> References: <9C1227FB-8B2D-4B96-96DC-27CCAD6408D2@donders.ru.nl> Message-ID: Dear all Thanks for all of your replies from all over the world! It appears that the warning/error message is specific for the lab where it was initially reported, which happens to be a centre here in Nijmegen on the other side of the campus. I’ll discuss in more detail with them what might be causing it. So right now I don’t see a reason to be concerned about the website itself. cheers Robert > On 05 Sep 2016, at 09:00, Robert Oostenveld wrote: > > Dear FieldTrip users > > I just got word from someone who received a warning when opening the FieldTrip website. See below, it appears blacklisted by his (institutional) security software. I checked: for me it looks fine. I also don’t see anything unusual on the server itself, but a website hack is sometimes hard to detect. > > Could you please check the website on unusual or suspicious behaviour? But don’t click on anything if you see something unexpected! > > Please let me know in a PERSONAL REPLY to this email whether it works or not. Please do NOT REPLY to all people on the list, as the others on the list won’t be able to fix it anyway and will probably be annoyed by all those email messages. > > Thanks, > Robert > > > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From belahian at memphis.edu Mon Sep 5 18:59:57 2016 From: belahian at memphis.edu (Bahareh Elahian (belahian)) Date: Mon, 5 Sep 2016 16:59:57 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> References: , <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Message-ID: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 pgoodin at swin.edu.au Tue Sep 6 00:28:34 2016 From: pgoodin at swin.edu.au (Peter Goodin) Date: Mon, 5 Sep 2016 22:28:34 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot Message-ID: Hi Bahar, There's no problem. The matrix returned is simply a channel x frequency x time matrix. Hope that helps, Peter. On 6 Sep 2016 3:24 AM, "Bahareh Elahian (belahian)" wrote: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 Tue Sep 6 08:51:24 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 6 Sep 2016 06:51:24 +0000 Subject: [FieldTrip] Wavelet and time-frequency plot In-Reply-To: References: <961BF276-F370-4173-8B45-CAD46D5C1F29@donders.ru.nl> Message-ID: <0B7BC124-9612-4684-A746-7F52CE75F1B7@donders.ru.nl> Hi Bahar, May I add to Peter’s reply that you should specify 4000, rather than 4 as resamplefs. JM On 05 Sep 2016, at 18:59, Bahareh Elahian (belahian) > wrote: Thanks for your complete answer. Yes . I have one trial and 8 channels. I have changed the code as following and I got the [freq] structure. % Resample Data cfg = []; cfg.resamplefs = 4; cfg.detrend = 'No'; cfg.trials = 'all'; [data_resam] = ft_resampledata(cfg, data1); %% wavelet cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; cfg.toi = data_resam.time{1}(1):0.1:data_resam.time{1}(end); cfg.foi = 0:5:500; [freq] = ft_freqanalysis(cfg, data_resam); The problem here is that the freq.powspctrm is a 3 dimentional matrix which I beleive it should be a 2 dimensional. The dimension is (8*100*1380). In online tutorials, I found the other examples that the freq.powspctrm had 2 dimensional. Do you know where is the problem (if there is any)? Thanks! Bahar ________________________________ From: fieldtrip-bounces at science.ru.nl > on behalf of Schoffelen, J.M. (Jan Mathijs) > Sent: Sunday, September 4, 2016 2:25:27 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Wavelet and time-frequency plot Dear Bahar, Perhaps you should first acquaint yourself a bit more with some of the basics of spectral analysis, and with some of the details of what the consequences are of specific choices about cfg-options that you specify before calling the function. Although you provide too few details to be sure, I suspect that you have a single stretch of data (sampled at 30K), i.e. a single trial, and I assume this to be of a certain length. If you want to create a single time-frequency spectrum, without epoching (again, I assume that this is what you want to do), this can become quite memory consuming, even when only considering the amount of memory it takes to store the results. In your case, you ask in cfg.toi to return an estimate of power for each time point in your original data. This is certainly an overkill, due to the temporal smoothness of the estimates. As a consequence, with 30.000 samples per second, and (e.g.) 15 minutes of recording each frequency’s time cours will have 27.000.000 samples. Since MATLAB needs 16 bytes for each complex-valued double precision number, this will eat up 432MB of memory. Per channel and per frequency… Next, not specifying the frequency range, will cause FieldTrip to compute and return all frequencies, from 0 until the Nyquist frequency, which is 15.000 Hz in your case. Now, if you indeed have 15 minutes of recording, this gives you a spectral resolution of 1/900 Hz, i.e. 900 frequency estimates per Hz. This all amounts to 1350000 frequency bins to be estimated. I can imagine that computers may choke on this. I suggest to do the following: 1) resample your data to a lower sampling rate, using ft_resampledata. If you go down to 2 or 4 kHz, no information is lost for the time being (at least not if you want to look up until 500 Hz). 2) ask for more reasonable parameters, e.g. cfg.toi = data.time{1}(1):0.1:data.time{1}(end); cfg.foi = 0:5:500; 3) think about the cfg.width parameter, and think twice whether you would want to use the ‘wavelet’ method, rather than ‘mtmconvol’, which gives you more control about the temporal integration window. Note that a width parameter of e.g. 5 (a typical, i think even the default, value) leads to the wavelet to be ~10 ms wide at 500 Hz, which may be a bit short. Best and good luck, Jan-Mathijs On 02 Sep 2016, at 21:45, Bahareh Elahian (belahian) > wrote: Hi All, I am asking this question again since I tried on our HPC server, and still I need more memory for computation. Do you have any idea how can I plot my signal in time-frequency? I wrote down the detail in my following post. Thanks! Bahar Hello All, I am trying to apply wavelet on my signal to see HFOs in time-frequency plot. The sampling rate of my signal is 30K. I will get an error: " Error using fft Out of memory. Type HELP MEMORY for your options. " here is what I wrote according to http://www.fieldtriptoolbox.org/reference/ft_freqanalysis: [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... [http://www.fieldtriptoolbox.org/_media/logo-share.png] reference:ft_freqanalysis – FieldTrip www.fieldtriptoolbox.org Note that this reference documentation is identical to the help that is displayed in MATLAB when you type “help ft_freqanalysis”. FT_FREQANALYSIS performs ... cfg= []; cfg.pad = 'maxperlen'; cfg.method = 'wavelet'; cfg.output = 'pow'; %cfg.channel = 'chan 4'; cfg.toi = (1:size(eeg.eeg_data,2))/Fs; % cfg.foilim = [80 500]; [freq] = ft_freqanalysis(cfg, data1); Do you have any idea? is it realted to my sampling rate? Thanks! Bahar _______________________________________________ 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 stefan.debener at uni-oldenburg.de Tue Sep 6 15:52:14 2016 From: stefan.debener at uni-oldenburg.de (Stefan Debener) Date: Tue, 6 Sep 2016 15:52:14 +0200 Subject: [FieldTrip] LSL Workshop in Germany Message-ID: <57CECA0E.6040500@uni-oldenburg.de> Dear all, The 1st International Lab Streaming Layer workshop will take place in Delmenhorst, Germany, on 19-20 December, 2016. LSL is a (phantastic) software project for time-synchronized streaming of multimodal data (https://github.com/sccn/labstreaminglayer). For preliminary program and registration details, please visit: http://www.h-w-k.de/index.php?id=2224 Best wishes, Stefan Debener & Martin Bleichner From ignasisols at gmail.com Tue Sep 6 22:01:14 2016 From: ignasisols at gmail.com (Ignasi Sols Balcells) Date: Tue, 6 Sep 2016 16:01:14 -0400 Subject: [FieldTrip] fieldtrip Functions that have the same name as MATLAB built in scripts - conflict. Message-ID: Hi all, I am using the last fieldtrip version and Matlab 2015b (Mac). When I start Matlab I get this warnings: *"Warning: Function iscolumn has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function ismatrix has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function isrow has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.Warning: Function isequaln has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict.* *Warning: Function isstring has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict".* Did this happen to other users? I think that renaming the scripts, as suggested by Matlab, is not the best idea because many other fieldtrip scripts that call this affected scripts should be changed manually... Thanks, Ignasi -------------- next part -------------- An HTML attachment was scrubbed... URL: From ekenaykut at gmail.com Tue Sep 6 22:07:15 2016 From: ekenaykut at gmail.com (Aykut Eken) Date: Tue, 6 Sep 2016 23:07:15 +0300 Subject: [FieldTrip] fieldtrip Functions that have the same name as MATLAB built in scripts - conflict. In-Reply-To: References: Message-ID: Hi Ignasi, This happened to me when I changed the version of MATLAB. However, I continued to use Fieldtrip without any problems. If any error occurs during code running, you can change the built in function with the fieldtrip function that has the same name. Best Aykut > On 06 Sep 2016, at 23:01, Ignasi Sols Balcells wrote: > > Hi all, > > I am using the last fieldtrip version and Matlab 2015b (Mac). > When I start Matlab I get this warnings: > > "Warning: Function iscolumn has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function ismatrix has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isrow has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isequaln has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict. > Warning: Function isstring has the same name as a MATLAB builtin. We suggest you rename the function to avoid a potential name conflict". > > Did this happen to other users? I think that renaming the scripts, as suggested by Matlab, is not the best idea because many other fieldtrip scripts that call this affected scripts should be changed manually... > > Thanks, > > Ignasi > _______________________________________________ > 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 giovannipellegrino at gmail.com Thu Sep 8 18:40:52 2016 From: giovannipellegrino at gmail.com (Giovanni Pellegrino) Date: Thu, 8 Sep 2016 18:40:52 +0200 Subject: [FieldTrip] Fwd: Postdoc positions @ Campus Bio-Medico University, Rome, Italy In-Reply-To: References: Message-ID: - Apologies for cross-postings - In the context of the European Research Council Grant “RESHAPE: REstoring the Self with embodiable HAnd ProsthesEs”, we are seeking two outstanding *Post-Doc scientists* to join us in developing new tools and methods to improve the embodiment of robotic hand prostheses and study the related brain processes. Activities will be carried out in a multidisciplinary research environment (Clinical Neurophysiology and Neuroengineering) @ Campus Bio-Medico University, Rome Italy (www.unicampus.it). Post-Doc ideal candidates should · - have relevant publications in international journals and experience in fund raising · - be English mother tongue or have almost comparable fluency · - *own at least two of the following expertise*: 1. Programming for development/customization of interactive Virtual/Augmented Reality environment 2. EEG/MRI signal processing 3. Body ownership, embodiment, cognitive neuroscience. Suitable candidates can introduce themselves by contacting Giovanni Di Pino (g.dipino at unicampus.it) and Domenico Formica(d.formica at unicampus.it). -- Giovanni Pellegrino, MD -------------- next part -------------- An HTML attachment was scrubbed... URL: From seymourr at aston.ac.uk Thu Sep 8 19:11:00 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Thu, 8 Sep 2016 17:11:00 +0000 Subject: [FieldTrip] Elekta Head Position Information --> FT Message-ID: Hi all, Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. Many thanks, Robert Seymour (PhD Student, Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From alexandre.gramfort at telecom-paristech.fr Thu Sep 8 21:50:22 2016 From: alexandre.gramfort at telecom-paristech.fr (Alexandre Gramfort) Date: Thu, 8 Sep 2016 21:50:22 +0200 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: References: Message-ID: hi Robert, unfortunately correcting for head movements is more difficult that using a linear regression (like done with fMRI). I doubt you can avoid a proper head movement correction using the physics of the sensors etc. You can use MNE open implementation of maxfilter prior to using fieldtrip if you want http://martinos.org/mne/dev/manual/preprocessing/maxwell.html http://martinos.org/mne/dev/generated/mne.preprocessing.maxwell_filter.html http://martinos.org/mne/dev/generated/commands.html#mne-maxfilter Hope this helps Alex On Thu, Sep 8, 2016 at 7:11 PM, Seymour, Robert (Research Student) wrote: > Hi all, > > > Just wondering whether anyone using an Elekta MEG system has managed to > import the head position estimation logs generated by Maxfilter into > Fieldtrip via the ft_preprocessing command? There must be a way of tricking > the function into accepting the data as an extra channel... My thinking is > that it should ultimately be possible to use ft_regressconfound to address > head movement right issues before ft_sourcestatistics without having to use > Maxfilter's native head position correction. > > > Many thanks, > > > Robert Seymour (PhD Student, Aston Brain Centre) > > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > The information in this e-mail is intended only for the person to whom it is > addressed. If you believe this e-mail was sent to you in error and the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail. > From a.stolk8 at gmail.com Fri Sep 9 01:12:26 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Thu, 8 Sep 2016 16:12:26 -0700 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: References: Message-ID: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> Hi Robert, Hopefully the following page is still accurate: http://www.fieldtriptoolbox.org/faq/how_can_i_visualize_the_neuromag_head_position_indicator_coils And more generally: http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis Hope that gets you started, Arjen > On Sep 8, 2016, at 10:11 AM, Seymour, Robert (Research Student) wrote: > > Hi all, > > > Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. > > > Many thanks, > > > Robert Seymour (PhD Student, Aston Brain Centre) > > _______________________________________________ > 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 a.stolk8 at gmail.com Fri Sep 9 01:21:54 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Thu, 8 Sep 2016 16:21:54 -0700 Subject: [FieldTrip] Elekta Head Position Information --> FT In-Reply-To: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> References: <3E80AFFA-53D8-43E8-9125-E2F77A2A1350@gmail.com> Message-ID: <4296702C-8916-4639-AD69-ADDFFF5BAFC0@gmail.com> Actually, while looking at it again, it doesnt provide the elekta headpositions, but creates position traces through dipolefitting. It's been a while but I recall this procedure wasn't that straightforward, producing shaky results. Perhaps someone in the list can point you in the right direction in terms of how to read in the elekta headpositions using ft_preproc. > On Sep 8, 2016, at 4:12 PM, Arjen Stolk wrote: > > Hi Robert, > > Hopefully the following page is still accurate: > http://www.fieldtriptoolbox.org/faq/how_can_i_visualize_the_neuromag_head_position_indicator_coils > > And more generally: > http://www.fieldtriptoolbox.org/example/how_to_incorporate_head_movements_in_meg_analysis > > Hope that gets you started, > Arjen > >> On Sep 8, 2016, at 10:11 AM, Seymour, Robert (Research Student) wrote: >> >> Hi all, >> >> >> Just wondering whether anyone using an Elekta MEG system has managed to import the head position estimation logs generated by Maxfilter into Fieldtrip via the ft_preprocessing command? There must be a way of tricking the function into accepting the data as an extra channel... My thinking is that it should ultimately be possible to use ft_regressconfound to address head movement right issues before ft_sourcestatistics without having to use Maxfilter's native head position correction. >> >> >> Many thanks, >> >> >> Robert Seymour (PhD Student, Aston Brain Centre) >> >> _______________________________________________ >> 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 virginie.van.wassenhove at gmail.com Fri Sep 9 11:54:43 2016 From: virginie.van.wassenhove at gmail.com (Virginie van Wassenhove) Date: Fri, 9 Sep 2016 11:54:43 +0200 Subject: [FieldTrip] [postdoc position] Message-ID: Dear colleagues, I would be grateful if you could pass on the following open position. Applications are invited for a postdoc position in the team of Dr Franck Ramus (LSCP, Department of Cognitive Studies, Ecole Normale Supérieure, Paris, France) on the study of auditory processing in developmental dyslexia using magnetoencephalography (MEG). Specific information about the position here: http://www.lscp.net/persons/ramus/docs/Postdoc_position.pdf Specific information about the project here: http://www.lscp.net/persons/ramus/docs/MEG_project_2016.pdf Best wishes, Virginie -- Virginie van Wassenhove CEA/NeuroSpin MEG - UNICOG Bat 145 PC 156 F-91191 Gif s/ Yvette FRANCE office: +33(0)1 69 08 1667 cell: +33(0)6 15 83 4955 skype, twitter: virginie_vw sites.google.com/site/virginievanwassenhove/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Fri Sep 9 20:45:01 2016 From: mklados at gmail.com (Manousos Klados) Date: Fri, 9 Sep 2016 20:45:01 +0200 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados [image: photo] *Manousos Klados, MSc, PhD* Postdoctoral Researcher, Max Planck Institute for Human Cognitive & Brain Sciences, +49(0)-341-9940-2507 | +49(0)-176-6988-1781 | http://www.mklados.com | Skype: mklados | Stephanstraße 1a PC D-04103 Leipzig Germany ------------------------------ *Call for Papers (Frontiers):*Applied Neuroscience: Methodology, Modeling, Theory, Applications and Reviews *Online Webinar in Brain Networks (hands on) - Live: 10-06-16 at 11:00 AM EEST (reserve your seat now )* ------------------------------ -------------- next part -------------- An HTML attachment was scrubbed... URL: From zhangk28 at mcmaster.ca Fri Sep 9 20:53:26 2016 From: zhangk28 at mcmaster.ca (KAIJIE ZHANG) Date: Fri, 9 Sep 2016 18:53:26 +0000 Subject: [FieldTrip] Mailing List Message-ID: Hi, Can I be removed from the field trip mailing list please? I have e-mailed unsubscribe already, but I am still receiving e-mails. Best Regards, Kaijie -- Kaijie Zhang Electrical & Biomedical Engineering, Level IV McMaster University -------------- next part -------------- An HTML attachment was scrubbed... URL: From matt.euler at psych.utah.edu Fri Sep 9 21:16:39 2016 From: matt.euler at psych.utah.edu (Matt Euler) Date: Fri, 9 Sep 2016 19:16:39 +0000 Subject: [FieldTrip] tenure-track position in Applied Cognitive Neuroscience at the University of Utah Message-ID: <8063208343AC35429BADDD1D51C326E270EE1D17@X-MB12.xds.umail.utah.edu> Dear all, The University of Utah Psychology department is currently seeking applications for a tenure-track faculty position in Applied Cognitive Neuroscience at the assistant professor level. Apologies for cross-postings: Cognitive Neuroscience at the University of Utah. The Department of Psychology at the University of Utah invites applications for a tenure-track faculty position in Applied Cognitive Neuroscience at the assistant professor level. This position is part of a new multi-disciplinary strategic cluster of hires across the School of Medicine, Bioengineering, and Psychology, in the area of Neural Basis of Behavior, Learning, and Memory, with opportunities to participate in the University of Utah's Neuroscience Initiative, www.neurogateway.utah.edu. We welcome applications from any area of cognitive psychology (including but not limited to: memory, executive functioning, attention, perception, decision-making, and reasoning) with a strong theory-based research program that employs neuroscientific methods. We especially welcome applicants who conduct research in both the laboratory and applied settings and who can speak to the real-world impact of the processes they study. Applicants should have the ability and interest to teach undergraduate and graduate courses in cognitive neuroscience. In addition to a doctoral program in cognition and neural science, the University of Utah has an interdepartmental neuroscience graduate program http://neuroscience.med.utah.edu. Ideal candidates could mentor students in both programs. Candidates should have an excellent and sustained record of research and evidence of the potential or demonstrated ability to generate extramural funding, commensurate with their career stage. The Department of Psychology values interdisciplinary approaches to research and training, and strongly encourages collaboration across four traditional programs (Developmental, Clinical, Cognition and Neural Sciences, and Social). The department promotes multidisciplinary collaboration outside of the Department of Psychology with active ties to the Consortium for Families and Health Research, University of Utah Neuroscience Initiative, the School of Computing, Civil and Environmental Engineering, Bioengineering, the Business School, the College of Education, Pediatrics, Anesthesiology, Neurology, Psychiatry, Radiology, the Huntsman Cancer Institute, and the Salt Lake Veterans Administration Medical Center. The Department of Psychology is committed to the goal of promoting diversity in academia and welcomes candidates whose interests and skills contribute to this goal. The University of Utah is a PAC-12 institution located in Salt Lake City nestled in the foothills of the Wasatch Mountains. With an enrollment of 31,000 students, it is the flagship university for the state of Utah. The university administration provides strong support for faculty research in the Psychology Department. The University of Utah values candidates who have experience working in settings with students from diverse backgrounds, and possess a strong commitment to improving access to higher education for historically underrepresented students. The University of Utah is an Affirmative Action/Equal Opportunity employer and does not discriminate based upon race, national origin, color, religion, sex, age, sexual orientation, gender identity/expression, status as a person with a disability, genetic information, or Protected Veteran status. Individuals from historically underrepresented groups, such as minorities, women, qualified persons with disabilities and protected veterans are encouraged to apply. Veterans' preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities. To inquire about the University's nondiscrimination or affirmative action policies or to request disability accommodation, please contact: Director, Office of Equal Opportunity and Affirmative Action, 201 S. Presidents Circle, Rm 135, (801) 581-8365. Please submit a letter detailing current research and teaching interests, a curriculum vitae, three representative reprints or preprints of publications, and contact information for three individuals who will provide letters of recommendation. Applications should be submitted at: http://utah.peopleadmin.com/postings/55506. Review of applications will begin October 1, 2016 and will continue until the position is filled. Matthew J. Euler, Ph.D. Assistant Professor Department of Psychology University of Utah Salt Lake City, UT 84112 -------------- next part -------------- An HTML attachment was scrubbed... URL: From smoratti at psi.ucm.es Tue Sep 13 21:34:33 2016 From: smoratti at psi.ucm.es (smoratti at psi.ucm.es) Date: Tue, 13 Sep 2016 21:34:33 +0200 Subject: [FieldTrip] PhD Position Clinical Neuroscience Lab CTB Madrid Message-ID: <019C5012-57D9-46ED-B699-04DFAD1B1FC9@psi.ucm.es> On behalf of Dr. Bryan Strange I send this job posting: Applications are invited for a 4-year funded PhD position in neuroscience. The Laboratory for Clinical Neuroscience in Madrid (www.thestrangelab.org ) focuses on the study of memory in healthy humans and different patient populations. We apply a multi-modal approach to better understand what factors influence memory, and are currently working on deep-brain stimulation (DBS) techniques to improve memory. The successful applicant would - Be part of a multi-disciplinary team comprising neurosurgeons, neurologists, psychiatrists, psychologists and biomedical engineers - Develop a novel DBS technique to enhance memory in human patients - Adopt methods to localise deep-brain electrodes using pre- and post-operative CT and MRI scans - Perform and analyse simultaneous DBS and MEG recordings - Perform simultaneous intracranial local field potential and scalp high density EEG recordings We provide funding for one four-year PhD position. This is a government funded position, with starting date is early 2017. Additional funding is also provided for international visits to other laboratories to enhance the PhD training. We are looking for a highly motivated individual who wishes to pursue a career in science, and has an interest in clinical and cognitive neuroscience of memory. Applicants should have MSc or equivalent in neuroscience, biology, biomedical engineering, psychology, or a related science/engineering discipline. Prior experience is required in either cognitive neuroscience, theoretical neuroscience, or animal models of memory. Familiarity with electrophysiology or MRI and Matlab or R, would be useful. 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 Applications deadline is 25 September 2016 -- ___________________________ Bryan Strange MRCP PhD Director, Laboratory for Clinical Neuroscience, CTB-UPM and Department of Neuroimaging, Reina Sofia Centre for Alzheimer's Research, Madrid, Spain www.thestrangelab.org ________________________________________________________ Stephan Moratti, PhD see also: Stephan Moratti Universidad Complutense de Madrid Facultad de Psicología Departamento de Psicología Básica I Campus de Somosaguas 28223 Pozuelo de Alarcón (Madrid) Spain and Center for Biomedical Technology Laboratory for Cognitive and Computational Neuroscience Parque Científico y Tecnológico de la Universidad Politecnica de Madrid Campus Montegancedo 28223 Pozuelo de Alarcón (Madrid) Spain email: smoratti at psi.ucm.es Tel.: +34 679219982 -------------- next part -------------- An HTML attachment was scrubbed... URL: From hesham.elshafei at inserm.fr Wed Sep 14 16:04:22 2016 From: hesham.elshafei at inserm.fr (Hesham ElShafei) Date: Wed, 14 Sep 2016 16:04:22 +0200 Subject: [FieldTrip] Virtual Electrodes Message-ID: <93e198c44edd942b7df24688d7ac08c0@inserm.fr> Hello fieldtrippers , For my Phd , I am trying to investigate the dynamics of alpha oscillations during anticipatory attention. I have analysed the data in the sensor level and based upon these analyses I have define time-frequency windows of interest to which I have applied the DICS beamformer. Based on statistical results, I have defined regions of interest (the left Heschl Gyrus, for example). Now I would like to have a look at the time couse of these sources. I have followed this tutorial: http://www.fieldtriptoolbox.org/tutorial/salzburg?s[]=virtual&s[]=sensors However, there is a step I would like to expert opinions. In the tutorial, after having defined voxels of interest , they have re-calculated the leadfield for these voxels. (let's call that method A) Should this operation be different to Method B which involves marking only the voxels of interest in the leadfield (that has been used for the DICS) as inside the brain? I've tried both methods, and results are different. So I would like to know why such difference exists and which is method is better? Also in the aforementioned tutorial , there is this: cfg.grid.pos=[btiposCML;btiposHGL;btiposHGR]./1000; % units of m Which I don't think is correct since conversion should be done from mm to cm (if we follow the tutorial) Thank you very much Hesham ElShafei -------------- next part -------------- An HTML attachment was scrubbed... URL: From roycox.roycox at gmail.com Wed Sep 14 22:25:04 2016 From: roycox.roycox at gmail.com (Roy Cox) Date: Wed, 14 Sep 2016 16:25:04 -0400 Subject: [FieldTrip] postdoctoral position on sleep and memory In-Reply-To: References: Message-ID: > > hi all, >> >> Apologies for re- and cross-posting, but see below for an open >> postdoctoral position. >> >> 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 > > 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 efficacy of pharmacological and other interventions. Our work has > linked cognitive deficits to a specific heritable mechanism (sleep > spindles) 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 (polysomnography), 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 MEG/EEG methodology and data analysis, > comfortable with methodological innovation, and is interested in optimizing > and developing 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 lab mates 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 Experience with MEG/EEG data analysis/methodology > and/or other signal processing. Background in cognitive neuroscience, > experimental psychology, and an interest in clinical applications are a > plus. > > > > 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 mailtome.2113 at gmail.com Thu Sep 15 07:36:53 2016 From: mailtome.2113 at gmail.com (Arti Abhishek) Date: Thu, 15 Sep 2016 15:36:53 +1000 Subject: [FieldTrip] Plotting confidence intervals in multiplotER Message-ID: Dear fieldtrip community, I was wondering whether there is a way to plot the confidence intervals in the ERP plot? I see that this question was asked multiple times in the discussion list before, but I could not find an answer to this. Thanks, Arti -------------- next part -------------- An HTML attachment was scrubbed... URL: From sarathykousik at gmail.com Thu Sep 15 09:39:16 2016 From: sarathykousik at gmail.com (kousik sarathy) Date: Thu, 15 Sep 2016 09:39:16 +0200 Subject: [FieldTrip] Plotting confidence intervals in multiplotER In-Reply-To: References: Message-ID: Hey Arti, This is not such a trivial thing to solve. Here's a recipe I used. You need to find and edit two scripts. If this spurns any more interest, I'll initiate a 'bug' and try to send in a pull request. This is a dirty fix and in all probability will be considered blasphemy. ;) 1. Find in ft_multiplotER : ft_plot_vector(xval, yval, 'width', width(m), 'height', height(m), 'hpos', layX(m), 'vpos', layY(m), 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'color', color, 'style', cfg.linestyle{i}, 'linewidth', cfg.linewidth, 'axis', cfg.axes, 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'label', label, 'box', cfg.box, 'fontsize', cfg.fontsize); This basically calls a plotting function which in turn does the plotting for you. You need to send in the extra 'sem' or a 'ci' variable. Change this to: ft_plot_vector(xval, yval, 'ysem', ysem, 'width', width(m), 'height', height(m), 'hpos', layX(m), 'vpos', layY(m), 'hlim', [xmin xmax], 'vlim', [ymin ymax], 'color', color, 'style', cfg.linestyle{i}, 'linewidth', cfg.linewidth, 'axis', cfg.axes, 'highlight', mask, 'highlightstyle', cfg.maskstyle, 'label', label, 'box', cfg.box, 'fontsize', cfg.fontsize); 2. Find in ft_plot_vector : You need to first get the sem parameter from your data and setup so FT can see your sem or CI info. Follow the code here . Search for "data_sem" and fix those lines. Then: h = plot(hdat, vdat, style, 'LineWidth', linewidth, 'Color', color, ' markersize', markersize, 'markerfacecolor', markerfacecolor); Change this to: [h hp ]= boundedline(hdat, vdat, vdat_sem); Boundedline is a submission in the MATLAB file exchange. You can use any other thing. Good luck trying! :) -- Regards, Kousik Sarathy, S On Thu, Sep 15, 2016 at 7:36 AM, Arti Abhishek wrote: > Dear fieldtrip community, > > I was wondering whether there is a way to plot the confidence intervals in > the ERP plot? I see that this question was asked multiple times in the > discussion list before, but I could not find an answer to this. > > Thanks, > Arti > > _______________________________________________ > 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 nima.noury at student.uni-tuebingen.de Thu Sep 15 12:35:48 2016 From: nima.noury at student.uni-tuebingen.de (Nima Noury) Date: Thu, 15 Sep 2016 12:35:48 +0200 Subject: [FieldTrip] 2016 Tuebingen MEG Symposium, Oct 26-27 Message-ID: <20160915123548.Horde.jS8bdBmAx3EbFIq-0uCVWMX@webmail.uni-tuebingen.de> The MEG Center Tuebingen is pleased to announce the 2016 Tuebingen MEG Symposium The symposium takes place on October 26 and 27, 2016 at the University Hospital’s Conference Center. The meeting brings together leading researchers in the field of MEG and related disciplines. Join us to learn about the latest advances in MEG research and beyond. Confirmed speakers: Radoslaw Cichy, Berlin Michael Cohen, Nijmegen Freek van Ede, Oxford Stefan Haufe, New York Vladimir Litvak, London Laura Marzetti, Chieti Satu Palva, Helsinki Rafael Polania, Zurich Martin Vinck, New Haven Mark Woolrich, Oxford For more information and registration, please visit: http://meg.medizin.uni-tuebingen.de/2016/ 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 -------------- next part -------------- An embedded message was scrubbed... From: Nima Noury Subject: 2016 Tuebingen MEG Symposium, Oct 26-27 Date: Tue, 13 Sep 2016 12:38:52 +0200 Size: 1704 URL: From maorwolf at gmail.com Thu Sep 15 12:57:49 2016 From: maorwolf at gmail.com (Maor Wolf) Date: Thu, 15 Sep 2016 10:57:49 +0000 Subject: [FieldTrip] 2x3x3 cluster analysis Message-ID: Dear fieldtripers, I am trying to run a mixed repeated measures ANOVA cluster analysis with one between subject variable (schizoprhenics vs. neurotypicals) and two within subject variables (each one with three conditions) and I'm struggling with the design matrix. Has anyone encountered this issue before? Thank you, Maor -------------- next part -------------- An HTML attachment was scrubbed... URL: From t.rusch at uke.uni-hamburg.de Thu Sep 15 14:01:41 2016 From: t.rusch at uke.uni-hamburg.de (Tessa Rusch) Date: Thu, 15 Sep 2016 14:01:41 +0200 Subject: [FieldTrip] postdoctoral position on social decision-making Message-ID: <001301d20f48$eb93f550$c2bbdff0$@uke.uni-hamburg.de> Hi! Sorry for cross-posting, but find below the details of an open postdoctoral position Kind regards Tessa Postdoctoral Position in Social Decision-Making Hamburg, Germany A Post-doctoral position in the field of social decision-making is available at the Institute for Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany. The position is funded through the program “Collaborative Research in Computational Neuroscience” co-funded by the German Ministry of Science and Research (BMBF) and by the American National Science Foundation (NSF). The project entitled “Computational Modeling of Cooperative Success” investigates social decision-making and the construction of mental models with EEG hyperscanning and computational modeling. The collaborative partner in the project is Prof. M. Spezio (Scripps College, CA). Research visits in the respective other labs are part of the project. We are searching for enthusiastic candidates with a strong interest in cognitive and social neuroscience and a PhD in (cognitive) neuroscience, cognitive science, psychology, biology, computer science, or a related discipline. Prior experience in the acquisition and analysis of human EEG data (ERPs, time-frequency analyses) and good programming skills (e.g. Matlab/R) are required. Starting date is Dec 1st 2016 or a few months later. The position is available for 3 years. The institute provides an excellent multi-disciplinary and interactive research environment with a research-dedicated 3T MRI scanner, EEG/MEG facilities and behavioral labs. Additional information about the research group and other scientific projects are available at www.glascherlab.org. Interested candidates should submit their application as a single PDF document (including CV, publication list, contact details of two references and a short statement of research interests) via email to Dr. Jan Gläscher (glaescher at uke.de). -- _____________________________________________________________________ Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | www.uke.de Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Prof. Dr. Dr. Uwe Koch-Gromus, Joachim Prölß, Rainer Schoppik _____________________________________________________________________ SAVE PAPER - THINK BEFORE PRINTING -------------- next part -------------- An HTML attachment was scrubbed... URL: From r.oostenveld at donders.ru.nl Thu Sep 15 16:40:23 2016 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Thu, 15 Sep 2016 16:40:23 +0200 Subject: [FieldTrip] From raw MEG to publication - BIOMAG16 satellite workshop, Oct 2, 2016 Message-ID: <282A2185-4DB3-4072-9D55-B5817DD25F95@donders.ru.nl> Dear colleagues, Apologies in advance for cross-posting. We would like to attract your attention to the BIOMAG2016 satellite symposium which will take place on Oct 2nd 2016 and is dedicated to group analysis of MEG data with free academic toolboxes. Please read the full description below. With best wishes, Arnaud Delorme Alexandre Gramfort Vladimir Litvak Srikantan Nagarajan Robert Oostenveld Francois Tadel ------------------------------------------------------------------------------- From raw MEG to publication: how to perform MEG group analysis with free academic software. Organisers: Arnaud Delorme, Alexandre Gramfort, Vladimir Litvak, Srikantan Nagarajan, Robert Oostenveld, Francois Tadel Free academic toolboxes have gained increasing prominence in MEG analysis as a means to disseminate cutting edge methods, share best practices between different research groups and pool resources for developing essential tools for the MEG community. In the recent years large and vibrant research communities have emerged around several of these toolboxes. Teaching events are regularly held around the world where the basics of each toolbox are explained by its respective developers and experienced power users. There are, however, two knowledge gaps that our BIOMAG satellite symposium aims to address. Firstly, most teaching examples only show analysis of a single ‘typical best’ subject whereas most real MEG studies involve analysis of group data. It is then left to the researchers in the field to figure out for themselves how to make the transition and obtain significant group results. Secondly, we are not familiar with any examples of fully analyzing the same group dataset with different academic toolboxes to assess the degree of agreement in scientific conclusions and compare strengths and weaknesses of various analysis methods and their independent implementations. Our workshop is organised by the lead developers of six most popular free academic MEG toolboxes (in alphabetic order): Brainstorm, EEGLAB, FieldTrip, MNE, NUTMEG, and SPM. Ahead of the workshop the research team for each toolbox will analyze the same group MEG/EEG dataset. This dataset containing evoked responses to face stimuli was acquired by Richard Henson and Daniel Wakeman, who won a special award at BIOMAG2010 to make it freely available to the community. All the raw data are available at ftp://ftp.mrc-cbu.cam.ac.uk/personal/rik.henson/wakemandg_hensonrn/ and https://openfmri.org/dataset/ds000117/ Detailed instructions for each toolbox will be made available online including analysis scripts and figures of results. All analyses will show a full pipeline from the raw data to detailed publication quality results. Researchers who are interested in using the respective toolbox will then be able to reproduce the analysis in their lab and port it to their own data. At the workshop each group will briefly introduce their software and present the key results from their analysis. This will be followed by a panel discussion and questions from the audience. Following the event we plan to integrate the suggestions and questions from the workshop audience and to publish the analyses details as part of a special research topic in Frontiers in Neuroscience, section Brain Imaging Methods so that the proposed best practices will be endorsed by peer review and become citable in future publications. Other research groups will be invited to contribute to the research topic as long as they present detailed descriptions of analyses of group data that are freely available online and make it possible for others to fully reproduce their analysis and results. We hope that this proposal will lead to creation of invaluable resource for the whole MEG community and the workshop will contribute to establishment of good practice and promoting consistent and reproducible analysis approaches. The event will also showcase all the toolboxes and will be of interest to beginners in the field with basic background in MEG who contemplate the most suitable analysis approach and software for their study as well as to experienced researchers who would like to get up to date with the latest methodological developments. -------------- next part -------------- An HTML attachment was scrubbed... URL: From iris.steinmann at med.uni-goettingen.de Thu Sep 15 16:41:30 2016 From: iris.steinmann at med.uni-goettingen.de (Steinmann, Iris) Date: Thu, 15 Sep 2016 14:41:30 +0000 Subject: [FieldTrip] Inter-trial variability of power amplitude for time-frequency spectra Message-ID: Dear Fieldtripper, I'm working on a spectral analysis of LFP data and calculated so far time-frequency spectra for every single trial. To describe the consistency/variability of phases on every time-frequency bin over trials I calculated 'Inter-trial Phase coherence (ITPC)' as described in the fieldtrip tutorial. But, what would I do to determine the consistency/variability of the power (squared amplitude) for every time-frequency bin over trials? Maybe simply calculate for every time-frequency bin a Standard Deviation over trials and relate this to the according mean: Variability(t,f) = Standard Deviation(t,f) / mean(t,f) Would it be that simple, or am I running into some statistical trouble (maybe because the power values are not normally distributed or anything else). Should I baseline correct the single trials before calculating the 'variability' of the power amplitude. Or am I missing an important point and the whole idea is not meaningful at all? Would be great if anyone has an idea, an answer, or even just a hint for a reference to read (couldn't find one so far)... Thanks! Iris -------------- next part -------------- An HTML attachment was scrubbed... URL: From nasseroleslami at gmail.com Fri Sep 16 17:57:52 2016 From: nasseroleslami at gmail.com (Bahman Nasseroleslami) Date: Fri, 16 Sep 2016 16:57:52 +0100 Subject: [FieldTrip] Fwd: Research Fellow (Biostatistics) Position - Trinity College Dublin, the University of Dublin, Dublin, Ireland In-Reply-To: References: Message-ID: Dear All, There is a research fellow position available in Academic Unit of Neurology, Trinity College Dublin, the University of Dublin, Dublin, Ireland. ------------------------------------ Post Specification: 031885 Post Title: Research Fellow Post Status: 23 month Fixed Term Contract (Full-time) (Subject to satisfactory probation) Research Group/Department/School: Academic Unit of Neurology, School of Medicine, Trinity College Dublin, the University of Dublin London School of Hygiene and Tropical Medicine, London Location: Trinity Biomedical Sciences Institute, Trinity College Dublin, the University of Dublin College Green, Dublin 2, Ireland And close links with London School of Hygiene and Tropical Medicine Reports to: Professor Orla Hardiman (Dublin) Prof. Neil Pearce (London) Salary: Post-Doctorate Researcher Salary Scale, commensurate with experience Closing Date and Time: 12 noon on Friday, 14th October 2016 Applications are invited for a motivated and self-driven individual for the position of Biostatistician with the Irish ALS Research Group, hosted in the Trinity Biomedical Sciences Institute's Academic Unit of Neurology.The ideal candidate will have a PhD in Biostatistics or a cognate area. Amyotrophic Lateral Sclerosis (ALS) or Motor Neurone Disease (MND) is a degenerative brain disease that leads to progressive decline and death within 3-5 years of first symptom. Our detailed assessment of cognitive, behavioural and social cognitive function in ALS points to significant disruption in extra-motor systems in some patients. This project will combine high resolution structural and dynamic imaging of the brain at 3 Tesla and spectral EEG/ EMG with clinical and genomic data to identify sub-clusters of ALS patients. Using robust mathematical models and building on key imaging and signal processing signatures we will develop observed-independent, quantitative markers of disease that can be utilized to generate disease clusters. These clusters will then be further analysed based on discriminatory clinical, neuropsychological and genomic data. The detailed job description file (PDF) and the application instructions can be found online at http://jobs.tcd.ie. ------------------------------------ It would be really appreciated if you could share this with those that may be interested. Sincerely Bahman –––––––––––– Bahman Nasseroleslami Irish Research Council Postdoctoral Research Fellow Academic Unit of Neurology, School of Medicine Trinity College Dublin, the University of Dublin Dublin 2, Ireland. Room 5.43, Trinity Biomedical Sciences Institute 152-160 Pearse Street, Dublin D02 R590, Ireland. nasserob at tcd.ie, nasseroleslami at gmail.com www.tcd.ie Trinity College Dublin, the University of Dublin is ranked 1st in Ireland and in the top 100 world universities by the QS World University Rankings. -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Sun Sep 18 20:55:04 2016 From: mklados at gmail.com (Manousos Klados) Date: Sun, 18 Sep 2016 14:55:04 -0400 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From hallmbh at aston.ac.uk Mon Sep 19 12:25:23 2016 From: hallmbh at aston.ac.uk (Hall, Michael (Research Student)) Date: Mon, 19 Sep 2016 10:25:23 +0000 Subject: [FieldTrip] Maxfilter and PCA Message-ID: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall -------------- next part -------------- An HTML attachment was scrubbed... URL: From magazzinil at gmail.com Mon Sep 19 13:48:55 2016 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Mon, 19 Sep 2016 12:48:55 +0100 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: Message-ID: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) < hallmbh at aston.ac.uk> wrote: > Dear All, > > I've been doing some testing with elekta neuromag data in Fieldtrip using > different sensor types (meg, meggrad, megmag) and different preprocessing > steps (tSSS 0.9 corr limit, no tSSS). > > A step that was proposed at the MEG UK 2015 demo was to use PCA to > compensate for the ill-conditioned estimate of the cov/csd matrix due to > maxfilter - could I ask why running a PCA and reducing the number of > components further would compensate for this? Apologies if this a naive > question, however I would assume that you would not want to reduce the rank > of your data further? Please see below for the link and code that I'm > referring to. > > http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtr > ip-beamformer-demo > > > %% deal with maxfilter > > % the data has been maxfiltered and subsequently concatenated > % this results in an ill-conditioned estimate of covariance or CSD > > cfg = []; > cfg.method = 'pca'; > cfg.updatesens = 'no'; > cfg.channel = 'MEGMAG'; > comp = ft_componentanalysis(cfg, data); > > cfg = []; > cfg.updatesens = 'no'; > cfg.component = comp.label(51:end); > data_fix = ft_rejectcomponent(cfg, comp); > > > Many thanks, > Mike Hall > > > > > _______________________________________________ > 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 Mon Sep 19 14:45:00 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 19 Sep 2016 12:45:00 +0000 Subject: [FieldTrip] Maxfilter and PCA References: Message-ID: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Hi all, The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. Best, Jan-Mathijs On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall _______________________________________________ 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 magazzinil at gmail.com Mon Sep 19 15:00:11 2016 From: magazzinil at gmail.com (Lorenzo Magazzini) Date: Mon, 19 Sep 2016 14:00:11 +0100 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: Hi Jan-Mathijs, Thanks for your answer. Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? Thanks, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Hi all, > > The reason to do the PCA has to do in this context with the fact that a > beamformer is used further down in the tutorial. The beamformer uses the > inverse of the covariance matrix, which behaves unpredictably (but usually > quite bad) when the smallest (usually poorly conditioned) components are > not well estimated. > The data that is used for the source reconstruction comes from three > separate runs, each of which was separately maxfiltered. As a consequence, > the low-rank subspace that is spanned by the individual runs’ data is > slightly different (each of which has approximately, say, a rank of 60). > Upon concatenation, however, the rank is suddenly increased to >> 60, where > most likely quite a lot of the ‘higher’ components represent noise. In > order to account for that in the covariance inversion, the whole data > matrix is ‘stabilized’ with a PCA. > > Best, > Jan-Mathijs > > > On 19 Sep 2016, at 13:48, Lorenzo Magazzini wrote: > > Hi Mike, > > This is a question that I've been asking myself too and I'd love to hear > an expert (and more technical) answer. In the meantime, these discussions > may be of help: > > https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html > https://mailman.science.ru.nl/pipermail/fieldtrip/2013- > November/007170.html > http://www.fieldtriptoolbox.org/faq/why_does_my_ica_ > output_contain_complex_numbers?s[ > > I wonder if the confusion arises from the difference between rank and > number of components? My understanding is that maxfilter reduces the rank > of the data (from 306 to 64, apparently). Therefore, my best guess is that > by performing a PCA and rejecting a number of components (only the first 50 > are kept, in the tutorial example), the data is no longer rank-deficient, > i.e. the rank is equal or greater than the number of components in the data. > > Clearly, this is a very non-technical interpretation, and a correction > would be more than welcome.. :) > > Best, > Lorenzo > > > > > > Lorenzo Magazzini > PhD Student > magazzinil at cardiff.ac.uk > > CUBRIC Building > Maindy Road > Cardiff > CF24 4HQ > > > On 19 September 2016 at 11:25, Hall, Michael (Research Student) < > hallmbh at aston.ac.uk> wrote: > >> Dear All, >> >> I've been doing some testing with elekta neuromag data in Fieldtrip using >> different sensor types (meg, meggrad, megmag) and different preprocessing >> steps (tSSS 0.9 corr limit, no tSSS). >> >> A step that was proposed at the MEG UK 2015 demo was to use PCA to >> compensate for the ill-conditioned estimate of the cov/csd matrix due to >> maxfilter - could I ask why running a PCA and reducing the number of >> components further would compensate for this? Apologies if this a naive >> question, however I would assume that you would not want to reduce the rank >> of your data further? Please see below for the link and code that I'm >> referring to. >> >> http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtr >> ip-beamformer-demo >> >> >> %% deal with maxfilter >> >> % the data has been maxfiltered and subsequently concatenated >> % this results in an ill-conditioned estimate of covariance or CSD >> >> cfg = []; >> cfg.method = 'pca'; >> cfg.updatesens = 'no'; >> cfg.channel = 'MEGMAG'; >> comp = ft_componentanalysis(cfg, data); >> >> cfg = []; >> cfg.updatesens = 'no'; >> cfg.component = comp.label(51:end); >> data_fix = ft_rejectcomponent(cfg, comp); >> >> >> Many thanks, >> Mike Hall >> >> >> >> >> _______________________________________________ >> 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 seymourr at aston.ac.uk Mon Sep 19 15:09:45 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Mon, 19 Sep 2016 13:09:45 +0000 Subject: [FieldTrip] Maxfilter and PCA Message-ID: Hi Mike & others, Instead of specifying a set number of components (e.g. 51) I tend to use data-driven approach that reduces my data to the number of components that describes 99% of the variance in my covar matrix. I do this like so: covar = zeros(numel(data.label)); for itrial = 1:numel(data.trial) currtrial = data.trial{itrial}; covar = covar + currtrial*currtrial.'; end [V, D] = eig(covar); D = sort(diag(D),'descend'); D = D ./ sum(D); Dcum = cumsum(D); numcomponent = find(Dcum>.99,1,'first') +1; % number of components accounting for 99% of variance in covar matrix disp(sprintf('\n Reducing the data to %d components \n',numcomponent)); cfg = []; cfg.method = 'pca'; cfg.updatesens = 'yes'; cfg.channel = 'MEG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'yes'; cfg.component = comp.label(numcomponent:end); data_fix = ft_rejectcomponent(cfg, comp); Cheers, Robert Seymour (Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Sep 19 15:53:39 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 19 Sep 2016 13:53:39 +0000 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: Hi Lorenzo, Well, your interpretation was almost OK, yet by keeping a certain number of components one makes the data explicitly rank deficient (so that’s the part that was not fully correctly stated in your pre-previous e-mail) The thing is that with keeping only (e.g.) 50 components, your data will still be rank deficient, yet the small components (those that end up as component 51 and up) cannot negatively affect the inverse of the data covariance matrix (which needs to be regularized anyway). Best, Jan-Mathijs On 19 Sep 2016, at 15:00, Lorenzo Magazzini > wrote: Hi Jan-Mathijs, Thanks for your answer. Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? Thanks, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) > wrote: Hi all, The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. Best, Jan-Mathijs On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: Hi Mike, This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) Best, Lorenzo Lorenzo Magazzini PhD Student magazzinil at cardiff.ac.uk CUBRIC Building Maindy Road Cardiff CF24 4HQ On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: Dear All, I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo %% deal with maxfilter % the data has been maxfiltered and subsequently concatenated % this results in an ill-conditioned estimate of covariance or CSD cfg = []; cfg.method = 'pca'; cfg.updatesens = 'no'; cfg.channel = 'MEGMAG'; comp = ft_componentanalysis(cfg, data); cfg = []; cfg.updatesens = 'no'; cfg.component = comp.label(51:end); data_fix = ft_rejectcomponent(cfg, comp); Many thanks, Mike Hall _______________________________________________ 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 russgport at gmail.com Mon Sep 19 17:30:48 2016 From: russgport at gmail.com (russ port) Date: Mon, 19 Sep 2016 11:30:48 -0400 Subject: [FieldTrip] Maxfilter and PCA In-Reply-To: References: <2939ECC3-00A3-408C-BD36-6EFC14FE5206@donders.ru.nl> Message-ID: <6474D29F-4B8F-4B9C-AF35-30E2C18A9DC6@gmail.com> Hi All, Just to clarify, as I am certainly worried about the implications of this chain on my own analyses. I have been following old posts from the email list/server, where it says that to do ICA on Neuromag data (for instance if you want to do EOG rejection) you must reduce the components you output to at most the rank of your data (because of TSSS/SSS basically drastically reduces the rank of your data because of how it works). As such, based on old email discussions, I ran an artifact rejection (for the artifacts mentioned in this email [muscle/Jump etc]) and then did a component analysis (runica) with the cfg set to give only enough outputs as valid by the rank of the data. Importantly, this data is only SSS (instead of TSSS) because the cHPI (continuous head position indicator monitoring) was not turned on. As such the script ultimately reads something like this: cfg=[] cfg.artfctdef.eog.artifact = artifact_EOG; cfg.artfctdef.jump.artifact = artifact_jump; cfg.artfctdef.muscle.artifact = artifact_muscle; data_no_artifacts = ft_rejectartifact(cfg,datanoline); cfg=[] cfg.resamplefs=300 cfg.detrend='no' resampleartifactfree=ft_resampledata(cfg,data_no_artifacts) cfg = []; cfg.method='runica' n_comp = rank(resampleartifactfree.trial{1} * resampleartifactfree.trial{1}') cfg.numcomponent = n_comp; cfg.runica.stop = 1e-7; ic_data = ft_componentanalysis(cfgeog,resampleartifactfree); I then go through the components and reject any component that are EC(or K depending on your nationality)G/ECG [heart and eye] artifacts. I then do ft_rejectcomponents for artifact components and use the resulting data in beamforming. My ICA components have real values, and the topos/timecourses look legit. Is this valid OR should I be doing a PCA/ICA to get the X (X=rank of data) components, and then again running it through ft_componentanalysis to check for heart/eye artifacts? Best (and sorry for the email, I’m a little paranoid when it comes to these things), Russ > On Sep 19, 2016, at 9:53 AM, Schoffelen, J.M. (Jan Mathijs) wrote: > > Hi Lorenzo, > > Well, your interpretation was almost OK, yet by keeping a certain number of components one makes the data explicitly rank deficient (so that’s the part that was not fully correctly stated in your pre-previous e-mail) The thing is that with keeping only (e.g.) 50 components, your data will still be rank deficient, yet the small components (those that end up as component 51 and up) cannot negatively affect the inverse of the data covariance matrix (which needs to be regularized anyway). > > Best, > Jan-Mathijs > > > >> On 19 Sep 2016, at 15:00, Lorenzo Magazzini > wrote: >> >> Hi Jan-Mathijs, >> >> Thanks for your answer. >> >> Just for clarity also to the other users, am I right to say that my previous interpretation was wrong, then? Is the purpose of the PCA simply that of 'stabilizing' the data matrix? The number of components has nothing to do with the rank deficiency (or what is the relationship between the two)? >> >> Thanks, >> Lorenzo >> >> >> >> Lorenzo Magazzini >> PhD Student >> magazzinil at cardiff.ac.uk >> >> CUBRIC Building >> Maindy Road >> Cardiff >> CF24 4HQ >> >> >> On 19 September 2016 at 13:45, Schoffelen, J.M. (Jan Mathijs) > wrote: >> Hi all, >> >> The reason to do the PCA has to do in this context with the fact that a beamformer is used further down in the tutorial. The beamformer uses the inverse of the covariance matrix, which behaves unpredictably (but usually quite bad) when the smallest (usually poorly conditioned) components are not well estimated. >> The data that is used for the source reconstruction comes from three separate runs, each of which was separately maxfiltered. As a consequence, the low-rank subspace that is spanned by the individual runs’ data is slightly different (each of which has approximately, say, a rank of 60). Upon concatenation, however, the rank is suddenly increased to >> 60, where most likely quite a lot of the ‘higher’ components represent noise. In order to account for that in the covariance inversion, the whole data matrix is ‘stabilized’ with a PCA. >> >> Best, >> Jan-Mathijs >> >> >>> On 19 Sep 2016, at 13:48, Lorenzo Magazzini > wrote: >>> >>> Hi Mike, >>> >>> This is a question that I've been asking myself too and I'd love to hear an expert (and more technical) answer. In the meantime, these discussions may be of help: >>> >>> https://mailman.science.ru.nl/pipermail/fieldtrip/2013-March/006270.html >>> https://mailman.science.ru.nl/pipermail/fieldtrip/2013-November/007170.html >>> http://www.fieldtriptoolbox.org/faq/why_does_my_ica_output_contain_complex_numbers?s[ >>> >>> I wonder if the confusion arises from the difference between rank and number of components? My understanding is that maxfilter reduces the rank of the data (from 306 to 64, apparently). Therefore, my best guess is that by performing a PCA and rejecting a number of components (only the first 50 are kept, in the tutorial example), the data is no longer rank-deficient, i.e. the rank is equal or greater than the number of components in the data. >>> >>> Clearly, this is a very non-technical interpretation, and a correction would be more than welcome.. :) >>> >>> Best, >>> Lorenzo >>> >>> >>> >>> >>> >>> Lorenzo Magazzini >>> PhD Student >>> magazzinil at cardiff.ac.uk >>> >>> CUBRIC Building >>> Maindy Road >>> Cardiff >>> CF24 4HQ >>> >>> >>> On 19 September 2016 at 11:25, Hall, Michael (Research Student) > wrote: >>> Dear All, >>> >>> I've been doing some testing with elekta neuromag data in Fieldtrip using different sensor types (meg, meggrad, megmag) and different preprocessing steps (tSSS 0.9 corr limit, no tSSS). >>> >>> A step that was proposed at the MEG UK 2015 demo was to use PCA to compensate for the ill-conditioned estimate of the cov/csd matrix due to maxfilter - could I ask why running a PCA and reducing the number of components further would compensate for this? Apologies if this a naive question, however I would assume that you would not want to reduce the rank of your data further? Please see below for the link and code that I'm referring to. >>> >>> http://www.fieldtriptoolbox.org/workshop/meg-uk-2015/fieldtrip-beamformer-demo >>> >>> %% deal with maxfilter >>> >>> % the data has been maxfiltered and subsequently concatenated >>> % this results in an ill-conditioned estimate of covariance or CSD >>> >>> cfg = []; >>> cfg.method = 'pca'; >>> cfg.updatesens = 'no'; >>> cfg.channel = 'MEGMAG'; >>> comp = ft_componentanalysis(cfg, data); >>> >>> cfg = []; >>> cfg.updatesens = 'no'; >>> cfg.component = comp.label(51:end); >>> data_fix = ft_rejectcomponent(cfg, comp); >>> >>> >>> Many thanks, >>> Mike Hall >>> >>> >>> >>> >>> >>> _______________________________________________ >>> 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 > > _______________________________________________ > 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 B.Haendel at gmx.net Mon Sep 19 22:30:52 2016 From: B.Haendel at gmx.net (Barbara Haendel) Date: Mon, 19 Sep 2016 22:30:52 +0200 Subject: [FieldTrip] NEW PhD positions: Neuroscience - University of Wuerzburg (Germany) Message-ID: An HTML attachment was scrubbed... URL: From mklados at gmail.com Tue Sep 20 00:08:08 2016 From: mklados at gmail.com (Manousos Klados) Date: Tue, 20 Sep 2016 00:08:08 +0200 Subject: [FieldTrip] =?utf-8?q?Society_of_Applied_Neuroscience_Biennial_co?= =?utf-8?b?bmZlcmVuY2UgKFNBTjIwMTbigI8pIOKAkyBmaW5hbCBwcm9ncmFtbWU=?= Message-ID: Dear colleagues, I am proud to announce you that the final programme for SAN2016 is now online (http://www.applied-neuroscience.org/san2016/ index.php/conference-info/program) and a summarised snapshot with the its highlights is attached to this email. With this information we would also like to cordially invite you to participate in and attend SAN2016 (http://applied-neuroscience.org/san2016/), which is organised by the Society of Applied Neuroscience (SAN, http://www.applied-neuroscience.org/) in cooperation with the Medical School of the Aristotle University of Thessaloniki and the Department of Neurology of the Max Planck Institute for Human Cognitive and Brain Sciences. SAN2016 will be held October6-9, 2016 in Corfu Island, Greece. As you will see, there is an attractive list of planned hands-on workshops and conference symposia in place as well as, an attractive list of distinguished speakers Numerous special issues and research topics are also planned by Society members as per tradition. We look forward to seeing you in Corfu, Greece! Panos Bamidis John Gruzelier Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: SAN2016_Brochure_Final.pdf Type: application/pdf Size: 593075 bytes Desc: not available URL: From matt.gerhold at gmail.com Tue Sep 20 09:17:33 2016 From: matt.gerhold at gmail.com (Matt Gerhold) Date: Tue, 20 Sep 2016 09:17:33 +0200 Subject: [FieldTrip] Inverse-modelling requirements Message-ID: MEG Mavens: I am looking to perform a source-level analysis on some EEG event-related data. I would be very grateful if you can assist me in understanding some of the methods in your toolbox and also some of the requirements in terms of the experimental protocols if one envisages performing source-level analysis. I have reviewed the tutorials on your website and viewed a number of video lectures from you institute. I have one or two points I would like to clear-up and one or two questions that require answers. >From the available information that I have reviewed, it is recommended that one have at least the following items: i. hi-res EEG/MEG datasets, ii. polhemus measurement data, and iii. MRI data for each of the participants within the study. Having these items enables one to compute the necessary models to source-localise the EEG/MEG sensor-space data. What I would like to know is how far one can stretch the boundaries of these requirements and still produce publishable scientific outcomes: what items are indispensable to the source localisation methodology? There are many examples of researchers using standard MRI templates, but how reliable are analytical outcomes in such instances? Does using a standard MRI image for all participants really produce useful scientific outcomes, especially in clinical populations wherein cortical structural changes are well-documented? There is a fair amount of structural variation within the cortex across healthy individuals; surely, a single standard MRI scan would lead to erroneous localisation in some instances? In terms of electro/magnetic field data: what is the minimum requirement in terms of how many electrodes are needed (spatial sampling across the scalp) in order to perform subsequent source-localisation via inverse modelling? Can one justify using the method(s) in instances of sparse spatial sampling (32-channels) and expect acceptable scientific outcomes? If one uses generic sensor/head-model co-registration in the absence of polhemus data, does this lead to analytical outcomes that are accepted by yourselves? What are the standards currently being set within the journals; being mavens in the field, what would you recommend? I appreciate that most people will embark on the analysis and build understanding along the way; however, I would like to gain some clarity before embarking on this analytical journey. Many thanks in advance. Kind Regards, Matthew -------------- next part -------------- An HTML attachment was scrubbed... URL: From Darren.Price at mrc-cbu.cam.ac.uk Tue Sep 20 16:43:36 2016 From: Darren.Price at mrc-cbu.cam.ac.uk (Darren Price) Date: Tue, 20 Sep 2016 14:43:36 +0000 Subject: [FieldTrip] Combined EEG MEG Source Reconstruction Message-ID: Dear Fieldtrippers We are interested in using fieldtrip for data fusion and source reconstruction of three different types of sensors: EEG (64 Channels), MEG planar gradiometers (204), MEG magnetometers (102) (Elekta Neuromag 306 Channel). I found the following page, with a quick sample script demonstrating how to perform the forward solutions, http://www.fieldtriptoolbox.org/example/combined_eeg_and_meg_source_reconstruction. However, the page does not give much detail on the inversion part. Also, it does not mention whether fieldtrip takes care of scaling of the data or any other preprocessing steps such as pre-whitening. That post is also a couple of years old so I thought there may be some more current but undocumented way to achieve this. Any help would be much appreciated. Kind Regards Darren ------------------------------------------------------- Dr. Darren Price Investigator Scientist and Cam-CAN Data Manager MRC Cognition & Brain Sciences Unit 15 Chaucer Road Cambridge, CB2 7EF England EMAIL: darren.price at mrc-cbu.cam.ac.uk URL: http://www.mrc-cbu.cam.ac.uk/people/darren.price TEL +44 (0)1223 355 294 x202 FAX +44 (0)1223 359 062 MOB +44 (0)7717822431 ------------------------------------------------------- -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.brehm at uu.nl Wed Sep 21 09:52:29 2016 From: j.brehm at uu.nl (Brehm, J. (Julia)) Date: Wed, 21 Sep 2016 07:52:29 +0000 Subject: [FieldTrip] EEG Visual Artifact Detection - Settings Message-ID: <385DDA785CF9764B8E184EF28D01ADE0F63153@WP0045.soliscom.uu.nl> Dear FieldTrippers, I am looking for options to achieve the following functionality in visual EEG artifact detection: 1. mark channel-by-trial pairs as bad (as in ft_rejectvisual -> method = ’trial’). 2. plot trials on a specific channel layout. 3. return marked data, and not yet cleaned data (as in ft_databrowser) OR return list of excluded channel-by-trial pairs in addition to cleaned data. Is there any way to achieve this functionality with some settings that are readily available? All the best, Julia -------------- next part -------------- An HTML attachment was scrubbed... URL: From seymourr at aston.ac.uk Wed Sep 21 12:10:14 2016 From: seymourr at aston.ac.uk (Seymour, Robert (Research Student)) Date: Wed, 21 Sep 2016 10:10:14 +0000 Subject: [FieldTrip] Combined EEG MEG Source Reconstruction Message-ID: Hi Darren, Have you had a look at this tutorial? http://www.fieldtriptoolbox.org/tutorial/natmeg/beamforming I'm also interested in the answer to this question - it would be really helpful for someone to clarify the steps Fieldtrip takes to combine MAGS + GRADS from an Elekta Neuromag 306 scanner... I know that Fieldtrip pre-whitens the data for ICA with combined MAGS+GRADS but it is unclear whether this is also done when computing the forward solution? Many thanks, Robert Seymour (PhD Student Aston Brain Centre) -------------- next part -------------- An HTML attachment was scrubbed... URL: From c.vanheck at donders.ru.nl Wed Sep 21 14:24:57 2016 From: c.vanheck at donders.ru.nl (Casper van Heck) Date: Wed, 21 Sep 2016 14:24:57 +0200 Subject: [FieldTrip] Lost reference location Message-ID: Dear all, We've recently started working on an old dataset, but have ran into a problem; nobody bothered to write down where the reference was placed... Does anybody have ideas on how to reconstruct the location of the reference, based on (some aspect of) the data? Best regards, Casper van Heck and Tineke van Rijn -------------- next part -------------- An HTML attachment was scrubbed... URL: From dlozanosoldevilla at gmail.com Wed Sep 21 14:54:48 2016 From: dlozanosoldevilla at gmail.com (Diego Lozano-Soldevilla) Date: Wed, 21 Sep 2016 14:54:48 +0200 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Casper, Very difficult... One idea would be to play with the data rank. Referencing to a specific sensor produces rank deficiency in your data. You can try to figure out which is the sensor that depends on the rest reading this thread: http://fr.mathworks.com/matlabcentral/newsreader/view_thread/157533 This ONLY can work if the sensor recordings are not correlated which is not always the case... Good luck! Diego On 21 September 2016 at 14:24, Casper van Heck wrote: > Dear all, > > We've recently started working on an old dataset, but have ran into a > problem; nobody bothered to write down where the reference was placed... > Does anybody have ideas on how to reconstruct the location of the > reference, based on (some aspect of) the data? > > Best regards, > > Casper van Heck and Tineke van Rijn > > _______________________________________________ > 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 christine.blume at sbg.ac.at Wed Sep 21 14:57:51 2016 From: christine.blume at sbg.ac.at (Blume Christine) Date: Wed, 21 Sep 2016 12:57:51 +0000 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Casper and Tineke, As voltage is always the difference between the reference and an electrode, voltages are lowest for electrodes closest to the reference electrode. You could check where voltages are minimal across trials and for each participant. If then for example that is close to Cz, it is likely that data were referenced to the vertex. Just an idea, it might work…but perhaps someone else has a better idea? Best, Christine Von: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] Im Auftrag von Casper van Heck Gesendet: Mittwoch, 21. September 2016 14:25 An: fieldtrip at science.ru.nl Betreff: [FieldTrip] Lost reference location Dear all, We've recently started working on an old dataset, but have ran into a problem; nobody bothered to write down where the reference was placed... Does anybody have ideas on how to reconstruct the location of the reference, based on (some aspect of) the data? Best regards, Casper van Heck and Tineke van Rijn -------------- next part -------------- An HTML attachment was scrubbed... URL: From litvak.vladimir at gmail.com Wed Sep 21 16:26:28 2016 From: litvak.vladimir at gmail.com (Vladimir Litvak) Date: Wed, 21 Sep 2016 15:26:28 +0100 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: If you need to know the reference for analysis purposes the easiest thing is to just rereference to another electrode or the average reference. Then it wouldn't matter what the original reference was. Best, Vladimir On Wed, Sep 21, 2016 at 1:57 PM, Blume Christine wrote: > Dear Casper and Tineke, > > > > As voltage is always the difference between the reference and an > electrode, voltages are lowest for electrodes closest to the reference > electrode. You could check where voltages are minimal across trials and for > each participant. If then for example that is close to Cz, it is likely > that data were referenced to the vertex. Just an idea, it might work…but > perhaps someone else has a better idea? > > > > Best, > > Christine > > > > *Von:* fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces@ > science.ru.nl] *Im Auftrag von *Casper van Heck > *Gesendet:* Mittwoch, 21. September 2016 14:25 > *An:* fieldtrip at science.ru.nl > *Betreff:* [FieldTrip] Lost reference location > > > > Dear all, > > > > We've recently started working on an old dataset, but have ran into a > problem; nobody bothered to write down where the reference was placed... > Does anybody have ideas on how to reconstruct the location of the > reference, based on (some aspect of) the data? > > > > Best regards, > > > > Casper van Heck and Tineke van Rijn > > _______________________________________________ > 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 xianwei.che at monash.edu Thu Sep 22 06:26:21 2016 From: xianwei.che at monash.edu (Xianwei Che) Date: Thu, 22 Sep 2016 14:26:21 +1000 Subject: [FieldTrip] creating difference wave Message-ID: Dear list, I have some concerns of how to create difference wave between two conditions. Here is what I want to look at: I have grand average time-freqency data of two conditions ("GA1","GA2"), and one behavioural measurement. Now I want to do so some regression/correlation analysis between the behavioural measurement and the contrasted time-freqency data (GA1-GA2). I did some googling and it is suggested to create the difference wave first, as per here (http://www.fieldtriptoolbox.org/faq/how_can_i_test_an_ interaction_effect_using_cluster-based_permutation_tests). >From these 4 data structures, you now make 2 difference data structures in the following way: - Copy GA11 to GAdiff11_12 and perform the assignment GAdiff11_12.avg=GA11.avg-GA12.avg. - Copy GA21 to GAdiff21_22 and perform the assignment GAdiff21_22.avg=GA21.avg-GA22.avg. I got confused about the '.avg' here. Powspctrm is 4-d data in each GA (subject.channel.frequency.time); so what is and how to calculate the average (.avg) in each GA structure. Or is it just a filed in each GA as I cannot find one. Thanks a lot *-------------* *Mr Xianwei Che* *PhD Candidate* *Monash Alfred Psychiatry Research Centre (MAPrc)* *Central Clinical School & the Alfred * *Monash University* *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* -------------- next part -------------- An HTML attachment was scrubbed... URL: From xianwei.che at monash.edu Thu Sep 22 08:31:14 2016 From: xianwei.che at monash.edu (Xianwei Che) Date: Thu, 22 Sep 2016 16:31:14 +1000 Subject: [FieldTrip] creating difference wave In-Reply-To: References: Message-ID: Dear list, Here is my understanding of this. The field ".avg" is in the output of timelockanalysis, which is the average across the trials. But in the output of freqanalysis there is no ".avg" field as the field "powspctrm " is the "averaged" results. So, if I want to create a difference wave of the freqanalysis between two conditions; I just use the ft_math to subtract the field "powspctrm" in one condition from the other one. I don't know if this is right; any suggestion would be appreciated. Thanks *-------------* *Mr Xianwei Che* *PhD Candidate* *Monash Alfred Psychiatry Research Centre (MAPrc)* *Central Clinical School & the Alfred * *Monash University* *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* On 22 September 2016 at 14:26, Xianwei Che wrote: > Dear list, > > I have some concerns of how to create difference wave between two > conditions. Here is what I want to look at: > > I have grand average time-freqency data of two conditions ("GA1","GA2"), > and one behavioural measurement. Now I want to do so some > regression/correlation analysis between the behavioural measurement and the > contrasted time-freqency data (GA1-GA2). > > I did some googling and it is suggested to create the difference wave > first, as per here (http://www.fieldtriptoolbox.o > rg/faq/how_can_i_test_an_interaction_effect_using_cluster- > based_permutation_tests). > > From these 4 data structures, you now make 2 difference data structures in > the following way: > > - Copy GA11 to GAdiff11_12 and perform the assignment > GAdiff11_12.avg=GA11.avg-GA12.avg. > - Copy GA21 to GAdiff21_22 and perform the assignment > GAdiff21_22.avg=GA21.avg-GA22.avg. > > > I got confused about the '.avg' here. Powspctrm is 4-d data in each GA > (subject.channel.frequency.time); so what is and how to calculate the > average (.avg) in each GA structure. > > Or is it just a filed in each GA as I cannot find one. > > Thanks a lot > > *-------------* > *Mr Xianwei Che* > *PhD Candidate* > *Monash Alfred Psychiatry Research Centre (MAPrc)* > *Central Clinical School & the Alfred * > *Monash University* > *Level 4, 607 St Kilda Road, Melbourne **3004, **Australia* > -------------- next part -------------- An HTML attachment was scrubbed... URL: From mklados at gmail.com Thu Sep 22 20:55:07 2016 From: mklados at gmail.com (Manousos Klados) Date: Thu, 22 Sep 2016 14:55:07 -0400 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From Elana.Harris at cchmc.org Fri Sep 23 19:21:15 2016 From: Elana.Harris at cchmc.org (Harris, Elana) Date: Fri, 23 Sep 2016 17:21:15 +0000 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: References: Message-ID: <1cfe2a63112349099f027f080d671a30@cchmc.org> Hello, Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? Thanks, Elana ________________________________ From: fieldtrip-bounces at science.ru.nl on behalf of Nugent, Allison C. (NIH/NIMH) [E] Sent: Wednesday, August 24, 2016 12:11 PM To: 'fieldtrip at science.ru.nl' Subject: [FieldTrip] NIH MEG Workshop Reminder! A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. At this meeting, we plan to address the following four themes: 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? 3. How can we develop and support infrastructure to share data and facilitate big science? 4. How could an MEG-North America consortium work to address these issues? Keynote Speakers: Sylvain Baillet, PhD, Director, MEG Core McGill University, McConnell Brain Imaging Center Dimitrios Pantazis, PhD, Director of MEG Lab, Martinos Imaging Center Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia Julia M. Stephen, PhD, Director, MEG/EEG Core, The Mind Research Network For more details, visit http://megworkshop.nih.gov Registration to this NIH sponsored event is free of charge. We hope to see you in Bethesda in November! Dr. Richard Coppola, Director, NIMH MEG Core Dr. Allison C Nugent, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH Register Now at Eventbrite! Allison Nugent, PhD Director of Neuroimaging Research Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph 301-451-8863 -------------- next part -------------- An HTML attachment was scrubbed... URL: From Douglas.Rose at cchmc.org Fri Sep 23 22:39:46 2016 From: Douglas.Rose at cchmc.org (Rose, Douglas) Date: Fri, 23 Sep 2016 20:39:46 +0000 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: <1cfe2a63112349099f027f080d671a30@cchmc.org> References: <1cfe2a63112349099f027f080d671a30@cchmc.org> Message-ID: <2EBA7945365E4C4498225168A217A7C8975AE4A0@MCEXMB2.chmccorp.cchmc.org> Congrats on going to workshop. Used to live in DC so did not ever need to use hotels. Hotels there in Bethesda probably very expensive. Hotels.com might be helpful. You could probably write Rich Coppola for suggestions. There is the Metro station on campus and some buses perhaps from there to the NIMH station where conference is. So some not too expensive hotel on the same Metro line might be good. Doug From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Harris, Elana Sent: Friday, September 23, 2016 1:21 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] NIH MEG Workshop Hello, Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? Thanks, Elana ________________________________ From: fieldtrip-bounces at science.ru.nl > on behalf of Nugent, Allison C. (NIH/NIMH) [E] > Sent: Wednesday, August 24, 2016 12:11 PM To: 'fieldtrip at science.ru.nl' Subject: [FieldTrip] NIH MEG Workshop Reminder! A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. At this meeting, we plan to address the following four themes: 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? 3. How can we develop and support infrastructure to share data and facilitate big science? 4. How could an MEG-North America consortium work to address these issues? Keynote Speakers: Sylvain Baillet, PhD, Director, MEG Core McGill University, McConnell Brain Imaging Center Dimitrios Pantazis, PhD, Director of MEG Lab, Martinos Imaging Center Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia Julia M. Stephen, PhD, Director, MEG/EEG Core, The Mind Research Network For more details, visit http://megworkshop.nih.gov Registration to this NIH sponsored event is free of charge. We hope to see you in Bethesda in November! Dr. Richard Coppola, Director, NIMH MEG Core Dr. Allison C Nugent, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH Register Now at Eventbrite! Allison Nugent, PhD Director of Neuroimaging Research Experimental Therapeutics and Pathophysiology Branch NIMH/NIH/DHHS Ph 301-451-8863 -------------- next part -------------- An HTML attachment was scrubbed... URL: From nick.peatfield at gmail.com Sat Sep 24 01:55:27 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Fri, 23 Sep 2016 16:55:27 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM Message-ID: Hi all, I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. With Regards, Nick [image: Inline images 1] -- Nicholas Peatfield, PhD -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image (3).png Type: image/png Size: 80865 bytes Desc: not available URL: From a.stolk8 at gmail.com Sat Sep 24 03:46:04 2016 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Fri, 23 Sep 2016 18:46:04 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: References: Message-ID: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Hi Nick, You may want to have a look at ft_convert_coordsys which can switch volumes between different coordinate systems. Best, Arjen > On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield wrote: > > Hi all, > > I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). > > So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). > > Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. > > With Regards, > > Nick > > > > -- > Nicholas Peatfield, PhD > > _______________________________________________ > 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 nick.peatfield at gmail.com Sat Sep 24 06:24:10 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Fri, 23 Sep 2016 21:24:10 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Message-ID: Hi Arjen, Yeah I looked into that but spm to ctf is not supported. And changing the grads to spm seems also not possible. Unless I use ft realignsens but the behaviour of that seems a little weird in my experience, and seems more suited to electrodes. Cheers Nick On Sep 23, 2016 7:35 PM, "Arjen Stolk" wrote: > Hi Nick, > > You may want to have a look at ft_convert_coordsys which can switch > volumes between different coordinate systems. > > Best, > Arjen > > On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield < > nick.peatfield at gmail.com> wrote: > > Hi all, > > I'm getting into a problem wherein I have headmodel that are in SPM space > and the grads are in CTF space. I would usually keep all the headmodels in > CTF space and align based on that but for this dataset and the format of > the MRIs,POS etc... there seems to be some problems (could take longer to > explain but lets keep this brief). > > So this of course leads to the issue that the grad and the headmodel > within beamformer_lcmv is misaligned by 90 degrees, which is of course not > good. Is there a quick solution that I have not come across to either > convert the headmodel to ctf or convert the grad structure to spm coordsys? > When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys > = 'ctf') but the outputted sourcemodel is still misaligned between the > headmodel and the grads (see attached image - oh and the lf is also > misaligned of course). > > Any help would be greatly appreciated. And I hope that this question > hasn't come up before as I did quite a bit of google searching before > sending this email. > > With Regards, > > Nick > > > > -- > Nicholas Peatfield, PhD > > _______________________________________________ > 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 Sat Sep 24 13:27:10 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sat, 24 Sep 2016 11:27:10 +0000 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> Message-ID: <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> Hi Nick, You need to use the anatomical MRI that you used to create your headmodel etc., register it to ctf-space using ft_volumerealign (in the interactive mode, it seems), and then use some magical matrix multiplications to get the appropriate transformation matrix that can be applied to the headmodel (to get it in ctf space), or (when taking the inverse of this transformation matrix) to the grad structure (to get it in spm space). The solution is embedded here: http://www.fieldtriptoolbox.org/tutorial/minimumnormestimate look for the transform_vox2spm and transform_vox2ctf, and the magical variable T. Best, Jan-Mathijs On 24 Sep 2016, at 06:24, Nicholas A. Peatfield > wrote: Hi Arjen, Yeah I looked into that but spm to ctf is not supported. And changing the grads to spm seems also not possible. Unless I use ft realignsens but the behaviour of that seems a little weird in my experience, and seems more suited to electrodes. Cheers Nick On Sep 23, 2016 7:35 PM, "Arjen Stolk" > wrote: Hi Nick, You may want to have a look at ft_convert_coordsys which can switch volumes between different coordinate systems. Best, Arjen On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield > wrote: Hi all, I'm getting into a problem wherein I have headmodel that are in SPM space and the grads are in CTF space. I would usually keep all the headmodels in CTF space and align based on that but for this dataset and the format of the MRIs,POS etc... there seems to be some problems (could take longer to explain but lets keep this brief). So this of course leads to the issue that the grad and the headmodel within beamformer_lcmv is misaligned by 90 degrees, which is of course not good. Is there a quick solution that I have not come across to either convert the headmodel to ctf or convert the grad structure to spm coordsys? When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys = 'ctf') but the outputted sourcemodel is still misaligned between the headmodel and the grads (see attached image - oh and the lf is also misaligned of course). Any help would be greatly appreciated. And I hope that this question hasn't come up before as I did quite a bit of google searching before sending this email. With Regards, Nick -- Nicholas Peatfield, PhD _______________________________________________ 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 nick.peatfield at gmail.com Sat Sep 24 22:35:36 2016 From: nick.peatfield at gmail.com (Nicholas A. Peatfield) Date: Sat, 24 Sep 2016 13:35:36 -0700 Subject: [FieldTrip] Coordsys problems CTF and SPM In-Reply-To: <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> References: <136D03B2-0AC1-4565-8100-0FD3A7B3ED10@gmail.com> <3E51290A-165E-49BA-B0A0-19CB10458E8D@donders.ru.nl> Message-ID: Hi Jan-Mathijs, I found the magical variable T - thanks for the solution! Regards, Nick On 24 September 2016 at 04:27, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Hi Nick, > > You need to use the anatomical MRI that you used to create your headmodel > etc., register it to ctf-space using ft_volumerealign (in the interactive > mode, it seems), and then use some magical matrix multiplications to get > the appropriate transformation matrix that can be applied to the headmodel > (to get it in ctf space), or (when taking the inverse of this > transformation matrix) to the grad structure (to get it in spm space). > > The solution is embedded here: http://www.fieldtriptoolbox.org/tutorial/ > minimumnormestimate > > look for the transform_vox2spm and transform_vox2ctf, and the magical > variable T. > > Best, > Jan-Mathijs > > > On 24 Sep 2016, at 06:24, Nicholas A. Peatfield > wrote: > > Hi Arjen, > > Yeah I looked into that but spm to ctf is not supported. And changing the > grads to spm seems also not possible. Unless I use ft realignsens but the > behaviour of that seems a little weird in my experience, and seems more > suited to electrodes. > > Cheers > > Nick > > On Sep 23, 2016 7:35 PM, "Arjen Stolk" wrote: > >> Hi Nick, >> >> You may want to have a look at ft_convert_coordsys which can switch >> volumes between different coordinate systems. >> >> Best, >> Arjen >> >> On Sep 23, 2016, at 4:55 PM, Nicholas A. Peatfield < >> nick.peatfield at gmail.com> wrote: >> >> Hi all, >> >> I'm getting into a problem wherein I have headmodel that are in SPM space >> and the grads are in CTF space. I would usually keep all the headmodels in >> CTF space and align based on that but for this dataset and the format of >> the MRIs,POS etc... there seems to be some problems (could take longer to >> explain but lets keep this brief). >> >> So this of course leads to the issue that the grad and the headmodel >> within beamformer_lcmv is misaligned by 90 degrees, which is of course not >> good. Is there a quick solution that I have not come across to either >> convert the headmodel to ctf or convert the grad structure to spm coordsys? >> When I specify in the ft_prepare_sourcemodel I explicitly say (cfg.coordsys >> = 'ctf') but the outputted sourcemodel is still misaligned between the >> headmodel and the grads (see attached image - oh and the lf is also >> misaligned of course). >> >> Any help would be greatly appreciated. And I hope that this question >> hasn't come up before as I did quite a bit of google searching before >> sending this email. >> >> With Regards, >> >> Nick >> >> >> >> -- >> Nicholas Peatfield, PhD >> >> _______________________________________________ >> 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 > -- Nicholas Peatfield, PhD -------------- next part -------------- An HTML attachment was scrubbed... URL: From dkicic at gmail.com Sat Sep 24 22:46:28 2016 From: dkicic at gmail.com (Dubravko Kicic) Date: Sat, 24 Sep 2016 22:46:28 +0200 Subject: [FieldTrip] NIH MEG Workshop In-Reply-To: <1cfe2a63112349099f027f080d671a30@cchmc.org> References: <1cfe2a63112349099f027f080d671a30@cchmc.org> Message-ID: Dear Elana, I recently stayed in DoubleTree by Hilton Bethesda, which is some 10 minutes walk from NIH campus. The prices were not that expensive, some 160 USD per night (dependining on current events, though). The hotel is very clean and the service is good. Very quiet rooms, good sleep. The from opposite side of the hotel there is a super nice residential area, excellent for a morning walk or jogging. At the rear side, on 5 minutes walk there are streets with very cosy restaurants and bars. Metro station is 5 minutes walk towards the city, and the other one is at about 10 minutes walk in NIH campus. A highly recommended hotel! Best regards! Dubravko Dubravko Kičić, Ph.D., EMBA CEO & President of the Board Bicro BIOCentre Ltd. Biosciences Technology Commercialisation and Incubation Centre Borongajska cesta 83h, 10000 Zagreb, CROATIA E-mail: dubravko.kicic at biocentre.hr T: +385 1 6458 643 | M: +385 91 5956 569 | W: www.biocentre.hr > On 23 Sep 2016, at 19:21, Harris, Elana wrote: > > Hello, > > Can anyone recommend a good hotel near the NIMH when I am in Bethesda for this workshop? > > Thanks, > > Elana > > > From: fieldtrip-bounces at science.ru.nl > on behalf of Nugent, Allison C. (NIH/NIMH) [E] > > Sent: Wednesday, August 24, 2016 12:11 PM > To: 'fieldtrip at science.ru.nl ' > Subject: [FieldTrip] NIH MEG Workshop > > Reminder! > > A call for abstracts is currently open! We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session. Visit http://megworkshop.nih.gov for more details. The abstract deadline has been extended to September 15st. > > At this meeting, we plan to address the following four themes: > > 1. What does MEG add to the field of neuroscience above and beyond other existing techniques? > 2. How can we support the evolution of MEG acquisition and methods, through both software and hardware? > 3. How can we develop and support infrastructure to share data and facilitate big science? > 4. How could an MEG-North America consortium work to address these issues? > > Keynote Speakers: > > Sylvain Baillet, PhD , Director, MEG Core McGill University, McConnell Brain Imaging Center > Dimitrios Pantazis, PhD , Director of MEG Lab, Martinos Imaging Center > Timothy P. Roberts, PhD, Vice Chair of Research, Department of Radiology, The Children’s Hospital of Philadelphia > Julia M. Stephen, PhD , Director, MEG/EEG Core, The Mind Research Network > > For more details, visit http://megworkshop.nih.gov > > Registration to this NIH sponsored event is free of charge. > > We hope to see you in Bethesda in November! > > Dr. Richard Coppola , Director, NIMH MEG Core > Dr. Allison C Nugent , Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH > > Register Now at Eventbrite! > > > Allison Nugent, PhD > Director of Neuroimaging Research > Experimental Therapeutics and Pathophysiology Branch > NIMH/NIH/DHHS > Ph 301-451-8863 > > > _______________________________________________ > 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 na.so.ir at gmail.com Mon Sep 26 08:50:03 2016 From: na.so.ir at gmail.com (Narjes Soltani) Date: Mon, 26 Sep 2016 10:20:03 +0330 Subject: [FieldTrip] Change in configuration file Message-ID: Hi I am writing my own trial function in fieldtrip and I need to pass some additional information as input argument to this function, but I wonder if it is also possible to include these information in ft_definetrial configuration file instead of passing them as input argument in the function. I checked the already available parameters in ft_definetrial configuration file, but none of them seemed to be useful for me for passing the new information I need for further processing. Best Regards Narjes Soltani -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Sep 26 10:13:36 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 26 Sep 2016 08:13:36 +0000 Subject: [FieldTrip] Change in configuration file In-Reply-To: References: Message-ID: <3328E538-26E3-49C4-A322-36CB35D81B37@donders.ru.nl> Hi Narjes, I believe you could put the required creative stuff in cfg.trialdef. This should pass unscathed through ft_definetrial into the trialfun. Best, Jan-Mathijs > On 26 Sep 2016, at 08:50, Narjes Soltani wrote: > > Hi > I am writing my own trial function in fieldtrip and I need to pass some additional information as input argument to this function, but I wonder if it is also possible to include these information in ft_definetrial configuration file instead of passing them as input argument in the function. I checked the already available parameters in ft_definetrial configuration file, but none of them seemed to be useful for me for passing the new information I need for further processing. > > > Best Regards > Narjes Soltani > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip From mklados at gmail.com Mon Sep 26 20:55:06 2016 From: mklados at gmail.com (Manousos Klados) Date: Mon, 26 Sep 2016 11:55:06 -0700 Subject: [FieldTrip] Online Webinar in Brain Networks (hands-on) Message-ID: Dear colleagues, please, accept my advanced apologies for any multiple cross-postings..., As a part of SAN 2016 conference (http://applied-neuroscience.org/san2016) I am organizing a hands-on workshop in Brain Networks on Thursday 6 OCT. This workshop aims to present some novel processing approaches, as well as different ways for visualizing the human connectome and some real studies. After participating in this workshop you will have the ability: - to analyze connectivity using graph theoretical models - to reduce the dimension and consequently the computation complexity of brain networks - to visualize with different ways the human connectome - to apply all these analyses to your data. Considering the huge amount of emails I received asking me for an online version of the workshop, I made an online webinar which is going to run in parallel with the live workshop. *After the first round of emails, few places are left and I am not planning to perform the same workshop in the near future. * You can reserve your seat as well as find more information about the programme in http://app.webinarsonair.com/register/?uuid=7961a35f44ab4cc2a3596492e7fc1ee1 If you need more information please don't hesitate to come in touch with me. Best wishes Manousos Klados -------------- next part -------------- An HTML attachment was scrubbed... URL: From pooneh.baniasad at gmail.com Tue Sep 27 13:15:20 2016 From: pooneh.baniasad at gmail.com (pooneh baniasad) Date: Tue, 27 Sep 2016 14:45:20 +0330 Subject: [FieldTrip] Fwd: Convert MNI to ctf In-Reply-To: References: Message-ID: Dear FieldTrip community ​I'm using the 'Subject01.mri'​ for constructing BEM headmodel for EEG source analysis which is defined in ctf coordination. On the other hand I use 'cortex_20484.surf.gii' which is defined in MNI coordination for adding the dipole sources. I want to convert the MNI into ctf to match the headmodel with template. I already found ft_volumenormalise function although it needs the inputs that I don't know what are they. ​ Can anyone help me? -- Bests Pouneh Baniasad -------------- next part -------------- An HTML attachment was scrubbed... URL: From elisabethsusanne.may at gmail.com Tue Sep 27 14:46:55 2016 From: elisabethsusanne.may at gmail.com (Elisabeth May) Date: Tue, 27 Sep 2016 14:46:55 +0200 Subject: [FieldTrip] Question about cluster-based permutation tests on linear mixed models Message-ID: Dear FieldTripers, I have a question about the potential use of cluster-based permutation tests for results obtained using linear mixed models. We are working with data from a 10 min EEG experiment on source level with the aim to quantify the relationship of brain activity in different frequency bands with continous perceptual ratings across 20 subjects in different experimental conditions. Thus, we have 10 min time courses of brain activity and ratings for each voxel for different conditions and want to test a) if there are significant relationships in the single conditions and b) if these relationships differ between two conditions. To this end, I have calculated linear mixed models in R using the lme4 toolbox. For both the single condition relationships and the condition contrasts, they result in a single t-value (and a corresponding p-value), which is based on information on both the single subject and the group level (i.e. we perform a multi-level analysis). However, with more than 2000 voxels, we have a lot of t-values and are wondering if there is a way to apply cluster-based tests to correct for multiple comparisons. The main problem I see is that I only have one multilevel t-value for the effect across all subjects, i.e. I don't have single subjects values, which I could then e.g. randomize between conditions as normally done in cluster-based permutation tests. (Or rather, I would be able to extract single subject values but would then loose the advantage of the multi-level analysis.) I found an old thread in the mailinglist archive where it was suggested to flip the signs of the t-statistic for cluster-level correction ( https://mailman.science.ru.nl/pipermail/fieldtrip/2012-July/005375.html). I understand that, in our case, I would do this randomly for all voxels in each randomization and then build spatial clusters on the resulting (partly flipped) t-values. However, I am not sure if that is a valid approach based on the null hypothesis that there are no significant relations in my single conditions (a) or no significant relationship differences in my condition contrasts (b). For the condition contrasts, I would be able to permute the condition labels as normally done in cluster-based permutation tests,I think, but would then have to recalculate the linear mixed models for all voxels in every permutation. This would result in a very high computational load. Does anyone have any experience with this kind of analysis? Would the flipping of t-values be a valid approach (and if yes, is there anything to keep in mind in particular)? Can you think of other ways to combine linear mixed models with a multiple comparison correction on the cluster level? Any help would be greatly appreciated! Best wishes from Munich, Elisabeth -- Elisabeth S. May, PhD Klinikum rechts der Isar Technische Universität München Ismaninger Str. 22 81675 München http://www.painlabmunich.de/ -------------- next part -------------- An HTML attachment was scrubbed... URL: From caspervanheck at gmail.com Tue Sep 27 15:32:59 2016 From: caspervanheck at gmail.com (Casper van Heck) Date: Tue, 27 Sep 2016 15:32:59 +0200 Subject: [FieldTrip] Lost reference location In-Reply-To: References: Message-ID: Dear Christine, As there are only a few possibilities, this might work! We'll try that! Dear Vladimir, If the original reference is close to an electrode we're interested in, and we do not see an effect on that electrode, then we cannot determine if there is indeed no effect or if the original reference made the effect disappear (due to it also 'seeing' the same activity). Thanks, all! Best regards, Casper On 21 September 2016 at 16:26, Vladimir Litvak wrote: > If you need to know the reference for analysis purposes the easiest thing > is to just rereference to another electrode or the average reference. Then > it wouldn't matter what the original reference was. > > Best, > > Vladimir > > On Wed, Sep 21, 2016 at 1:57 PM, Blume Christine < > christine.blume at sbg.ac.at> wrote: > >> Dear Casper and Tineke, >> >> >> >> As voltage is always the difference between the reference and an >> electrode, voltages are lowest for electrodes closest to the reference >> electrode. You could check where voltages are minimal across trials and for >> each participant. If then for example that is close to Cz, it is likely >> that data were referenced to the vertex. Just an idea, it might work…but >> perhaps someone else has a better idea? >> >> >> >> Best, >> >> Christine >> >> >> >> *Von:* fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at scie >> nce.ru.nl] *Im Auftrag von *Casper van Heck >> *Gesendet:* Mittwoch, 21. September 2016 14:25 >> *An:* fieldtrip at science.ru.nl >> *Betreff:* [FieldTrip] Lost reference location >> >> >> >> Dear all, >> >> >> >> We've recently started working on an old dataset, but have ran into a >> problem; nobody bothered to write down where the reference was placed... >> Does anybody have ideas on how to reconstruct the location of the >> reference, based on (some aspect of) the data? >> >> >> >> Best regards, >> >> >> >> Casper van Heck and Tineke van Rijn >> >> _______________________________________________ >> 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 carsten.wolters at uni-muenster.de Wed Sep 28 15:30:20 2016 From: carsten.wolters at uni-muenster.de (Carsten Wolters) Date: Wed, 28 Sep 2016 15:30:20 +0200 Subject: [FieldTrip] Ref. 11890: Neuroscientist(s) with focus on simulation of high-definition transcranial electric stimulation (hd-tES) Message-ID: <57EBC5EC.3080700@uni-muenster.de> Dear colleagues, please forward the ad below to anyone who could be interested and post to your departmental lists. Thanks and sorry for possible multiple postings. I will be on Biomag2016 in Seoul from Oct.1-6 and would be happy to discuss with possible candidates. Best regards Carsten Wolters ********************************************************************************************************* Neuroscientist(s) with focus on simulation of high-definition transcranial electric stimulation (hd-tES) Ref. 11890 The*Institute for Biomagnetism and Biosignalanalysis* at the medical faculty of the University of Münster, Germany, invites applications for a PostDoctoral Researcher and/or for Doctoral Students *Salary according to TV-L E13 **(100% or 50 %)** **Full-Time with 38,5 (hours/week) or Part-Time with 19,25 (hours/week)** *** for three year positions to work on the development and evaluation of new (i.e., new inverse electrode optimization and new forward finite element method algorithms) simulation approaches for hd-tES using realistic head volume conductor models within the DFG-funded priority program SPP1665/2 (second funding period: from 2016 to 2019) “Resolving and manipulating neuronal networks in the mammalian brain - from correlative to causal analysis” in project “Individualized closed-loop transcranial alternating current stimulation”. More informations can be found on http://www.spp1665.de/. The successful applicant holds a PhD degree and/or a Master’s degree (or equivalent) in a relevant academic area such as applied mathematics, computer science, physics, biomedical or electrical engineering or similar disciplines. Good programming expertise (Matlab, C++, or equivalent) and experience with the Linux operating system is expected, because large software toolboxes are used and further developed. The working language at the institute is English. Experience with brain stimulation and with the measurement and analysis of brain signals is advantageous, but not essential. The applicant’s merits are assessed on the basis of the quality of PhD and/or Master’s level studies and thesis, previous experience with numerical mathematics, inverse problems and optimization approaches, software development, motivation and research interests. The location for this research will mainly be the workgroups “SIM-NEURO: Simulation, Imaging and Modeling of NEUROnal networks in the human brain” of PD Dr. Wolters at the Institute for Biomagnetism and Biosignalanalysis (IBB), “Imaging” of Prof. Dr. Martin Burger at the Institute for Computational and Applied Mathematics and “Applications of Partial Differential Equations” of JProf. Dr. Christian Engwer, all at the University of Münster in Germany. Expected close collaborations and visits are to the partnering institutes, namely the University of Oldenburg (Prof. Dr. Christoph Herrmann) and the University of Hamburg (Dr. Till Schneider). The application should include a statement of research interests and reasons for applying to the project, a curriculum vitae (max. 5 pages) composed according to good scientific practice, a certificate of PhD and/or Master’s degree, copy of the master’s thesis and grades of Master’s level studies, the names and e-mail addresses of two referees and a proof of proficiency in English. The position will be open until filled. To apply for the position until *Oct.31*, *2016*, please send the above documents as pdfs to *PD Dr. Carsten Wolters, **Institute for Biomagnetism and Biosignalanalysis, University of Münster, Malmedyweg 15, 48149 Münster, Germany*, or by Email to *carsten.wolters(at)­uni-muenster(dot)­de* . For additional information please contact *PD Dr. Carsten Wolters* (Email: *carsten.wolters(at)­uni-muenster(dot)­de* , Phone: +49 (0)251/83-56904). Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference. Link to the position: http://klinikum.uni-muenster.de/index.php?id=3290&tx_ttnews[tt_news]=6562&cHash=afb5f5f3421732c32f5c0de0bfc6587c -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: carsten_wolters.vcf Type: text/x-vcard Size: 402 bytes Desc: not available URL: From joseluisblues at gmail.com Wed Sep 28 17:02:39 2016 From: joseluisblues at gmail.com (Jose) Date: Wed, 28 Sep 2016 17:02:39 +0200 Subject: [FieldTrip] axial gradiometers vs planar gradient Message-ID: dear fieldtrip community, I'm working with CTF MEG data, I have a confusion regarding the use of the (pure) axial gradiometers and the synthetic planar gradients, >From what I have read "the planar field gradient simplifies the interpretation of the sensor-level data because the maximal signal power is located above the source". In practice, this means that the topography would resemble more the sources? Is that correct? Would be meaningless to do this if one intend to do source analyses anyway? However is not clear for me if the planar gradient is used only for visualization purposes, or if is intended to replace the use of axial gradiometers for data analysis. Some papers do mention the aforementioned transformation but then they do not specify which data is used to run statistical analysis so I assume they do it with planar gradients. Others they clearly perform statistical analyses such as non-parametric cluster permutation tests with planar gradient data. So, the second question would be if one should run statistical analyses in planar gradient or axial gradiometers data?. What is the criteria to choose one or the other? If one apply cluster-based permutation tests to either axial gradiometers or the planar gradient one will find distinct results because the activity is distributed in different sensors, so distinct clusters will be observed, right? Does make sense to find different results depending on whether we analyze gradiometer or planar data? Some recommend use planar gradient data to perform statistics ( https://mailman.science.ru.nl/pipermail/fieldtrip/2012-November/005905.html) while others other advise against it ( https://mailman.science.ru.nl/pipermail/fieldtrip/2010-March/002657.html), Is there a consensus at the moment? I would really appreciate some directions here, best, Jose -------------- next part -------------- An HTML attachment was scrubbed... URL: From tomh at kurage.nimh.nih.gov Wed Sep 28 17:48:18 2016 From: tomh at kurage.nimh.nih.gov (Tom Holroyd) Date: Wed, 28 Sep 2016 11:48:18 -0400 Subject: [FieldTrip] axial gradiometers vs planar gradient In-Reply-To: References: Message-ID: <20160928114818.73806877@kurage.nimh.nih.gov> On Wed, 28 Sep 2016 17:02:39 +0200 Jose wrote: > dear fieldtrip community, > > I'm working with CTF MEG data, > I have a confusion regarding the use of the (pure) axial gradiometers and > the synthetic planar gradients, If you are doing source localization, there is no reason to convert to planar. It can only degrade the data, because it is an interpolation. -- Dr. Tom -- "A man of genius makes no mistakes. His errors are volitional and are the portals of discovery." -- James Joyce From joseluisblues at gmail.com Wed Sep 28 18:05:15 2016 From: joseluisblues at gmail.com (Jose) Date: Wed, 28 Sep 2016 18:05:15 +0200 Subject: [FieldTrip] axial gradiometers vs planar gradient In-Reply-To: <20160928114818.73806877@kurage.nimh.nih.gov> References: <20160928114818.73806877@kurage.nimh.nih.gov> Message-ID: Thanks Tom, Yes, I've read that for performing source reconstruction one use the axial gradiometer data, But, at the moment I'm at the sensor-level analysis, best Jose -------------- next part -------------- An HTML attachment was scrubbed... URL: From robert.oostenveld at donders.ru.nl Wed Sep 28 19:05:07 2016 From: robert.oostenveld at donders.ru.nl (Oostenveld, R. (Robert)) Date: Wed, 28 Sep 2016 17:05:07 +0000 Subject: [FieldTrip] Fwd: open engineer position focused on EEG of baby brains References: Message-ID: <5C55D865-B79F-440B-94EF-4297553C4099@donders.ru.nl> Begin forwarded message: From: Virginie van Wassenhove > Subject: [FieldTrip-news] Fwd: Offre de poste Stat Date: 28 September 2016 at 11:46:34 GMT+2 To: >, > Cc: Ghislaine Dehaene > Dear all, please find below information about an open engineer position focused on EEG of baby brains. Best, Virginie Engineer/Statistician position The INSERM / CEA Development of Neuroimaging lab in Neurospin, Saclay (91, France) offers a 2 to 5 years position for a research engineer or statistician to develop robust processing and analysis methods of infants’ brain signal measured by magnetic resonance imaging (MRI) and electroencephalography (EEG). Brain imaging techniques provide large amounts of data that require new analysis techniques and a robust control of the reliability of the results, particularly in infants whose patience is minimal, the vigilance variable and the movements important. All these factors affect the quality of the signal. Furthermore infants’ spontaneous activity is variable and ample generating greater endogenous background noise than in adults. The aim of the work will be to 1) Develop robust pipelines for EEG/MRI data processing taking into account the infants’ signal characteristics in order to robustly extract the brain activity associated with a cognitive task from the endogenous and exogenous noise 2) Characterize the properties of the endogenous brain activity and its maturation during the first year of life in order to understand the functional architecture of the main networks that allow the development of complex cognitive functions (e.g. language, consciousness) in the human species. Applicants should possess a solid technical background in signal processing and/or statistics and be able to code in Matlab and/or Python. The position is opened for a maximum of 5 years, funded by a European contract (CDD use) from 1 November 2016. Salary is based on qualifications (from 1900 euros / month, medical insurance comprised) Send your CV and a motivation letter to ghislaine.dehaene at cea.fr Lab Website http://www.unicog.org/site_2016/ Ghislaine Dehaene-Lambertz, M.D., Ph.D. Director of the Developmental Neuroimaging Lab http://moncerveaualecole.com/ ################################################# Developmental Neuroimaging Lab INSERM, U992 CEA/SAC/DSV/DRM/NeuroSpin Bat 145, point courrier 156 91191 GIF/YVETTE, France Phone: +33 1 69 08 81 72 Fax: +33 1 69 08 79 73 Mail: ghislaineDOTdehaeneAROBASEcea.fr www.unicog.org Publications in http://www.unicog.org/biblio/Author/DEHAENE-LAMBERTZ-G.html ################################################# -- Virginie van Wassenhove CEA/NeuroSpin MEG - UNICOG Bat 145 PC 156 F-91191 Gif s/ Yvette FRANCE office: +33(0)1 69 08 1667 cell: +33(0)6 15 83 4955 skype, twitter: virginie_vw sites.google.com/site/virginievanwassenhove/ _______________________________________________ fieldtrip-news mailing list fieldtrip-news at donders.ru.nl https://mailman.science.ru.nl/mailman/listinfo/fieldtrip-news -------------- next part -------------- An HTML attachment was scrubbed... URL: From bioeng.yoosofzadeh at gmail.com Wed Sep 28 19:28:25 2016 From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh) Date: Wed, 28 Sep 2016 13:28:25 -0400 Subject: [FieldTrip] Fwd: Issue with projection In-Reply-To: References: Message-ID: Hi all, I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). Any comment would be appreciated! Best, Vahab -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: sample_resutls.png Type: image/png Size: 321899 bytes Desc: not available URL: From tzvetan.popov at uni-konstanz.de Wed Sep 28 20:22:04 2016 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Wed, 28 Sep 2016 20:22:04 +0200 Subject: [FieldTrip] Fwd: Issue with projection In-Reply-To: References: Message-ID: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> Hi Vehab, You have to normalize the individual volume to the MNI template. So use ft_volumenormalise first and try again. Or, if you used MNI aligned grid that specify the source.pos = template grid.pos. Good luck Tzvetan > Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh : > > Hi all, > > I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). > > Any comment would be appreciated! > > Best, > Vahab > > _______________________________________________ > 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 Thu Sep 29 14:24:23 2016 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 29 Sep 2016 12:24:23 +0000 Subject: [FieldTrip] Issue with projection In-Reply-To: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> References: <896534AC-FD7B-4429-AC23-3F227E50097D@uni-konstanz.de> Message-ID: <286F8441-A34B-41E4-8892-435AAF19AD4F@donders.ru.nl> In addition to Tzvetan’s comment: please do not try and interpolate directly onto the inflated cortical sheet. You also need to provide the non-inflated sheet for the interpolation (after which the interpolated data can be displayed on the inflated sheet). Jan-Mathijs On 28 Sep 2016, at 20:22, Tzvetan Popov > wrote: Hi Vehab, You have to normalize the individual volume to the MNI template. So use ft_volumenormalise first and try again. Or, if you used MNI aligned grid that specify the source.pos = template grid.pos. Good luck Tzvetan Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh >: Hi all, I am having an issue in projecting my results on a (template) cortical map in FT and using ft_sourceplot. It seems a subset of the brain activations has only been projected (see attached). Any comment would be appreciated! Best, Vahab _______________________________________________ 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 bioeng.yoosofzadeh at gmail.com Thu Sep 29 14:54:50 2016 From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh) Date: Thu, 29 Sep 2016 08:54:50 -0400 Subject: [FieldTrip] fieldtrip Digest, Vol 70, Issue 27 In-Reply-To: References: Message-ID: Dear Tzvetan, I really appreciate your help. Actually, I tried ft_volumenormalise before however with no success. When I saw your comments, I tried again. It turns out that there is an issue with my older Matlab (2012b). Now, I tried with Matlab 2016 and it worked perfectly :D Thank you again, Vahab On Thu, Sep 29, 2016 at 6:00 AM, wrote: > 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. Re: Fwd: Issue with projection (Tzvetan Popov) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Wed, 28 Sep 2016 20:22:04 +0200 > From: Tzvetan Popov > To: FieldTrip discussion list > Subject: Re: [FieldTrip] Fwd: Issue with projection > Message-ID: <896534AC-FD7B-4429-AC23-3F227E50097D at uni-konstanz.de> > Content-Type: text/plain; charset="us-ascii" > > Hi Vehab, > You have to normalize the individual volume to the MNI template. So use > ft_volumenormalise first and try again. Or, if you used MNI aligned grid > that specify the source.pos = template grid.pos. > Good luck > Tzvetan > > > Am 28.09.2016 um 19:28 schrieb Vahab Yousofzadeh < > bioeng.yoosofzadeh at gmail.com>: > > > > Hi all, > > > > I am having an issue in projecting my results on a (template) cortical > map in FT and using ft_sourceplot. It seems a subset of the brain > activations has only been projected (see attached). > > > > Any comment would be appreciated! > > > > Best, > > Vahab > > > > _______________________________________________ > > fieldtrip mailing list > > fieldtrip at donders.ru.nl > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: attachments/20160928/5c685362/attachment-0001.html> > > ------------------------------ > > _______________________________________________ > fieldtrip mailing list > fieldtrip at donders.ru.nl > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > End of fieldtrip Digest, Vol 70, Issue 27 > ***************************************** > -------------- next part -------------- An HTML attachment was scrubbed... URL: From knutsenpm at gmail.com Fri Sep 30 15:11:44 2016 From: knutsenpm at gmail.com (Per Knutsen) Date: Fri, 30 Sep 2016 15:11:44 +0200 Subject: [FieldTrip] Reading data from arbitrary source Message-ID: Hi, I am new to fieldtrip with the intention of analyzing mouse ECoG/LFP data. I already have my datasets loaded into Matlab (from a format not directly supported by fieldtrip). Next, I need to read this data into a fieldtrip structure for processing. I see frequent use of a structure called cfg, with fields: cfg.dataset cfg.trialdef.threshold cfg.trialdef.prestim cfg.trialdef.poststim etc Can anyone direct me to the documentation of this structure's format. What data is stored, what is the format, units etc? *Per M Knutsen* University of Oslo Dept. of Molecular Medicine, Physiology Sect. PB 1103 Blindern, NO-0317 Oslo +47.45103762 -------------- next part -------------- An HTML attachment was scrubbed... URL: From dlozanosoldevilla at gmail.com Fri Sep 30 15:25:14 2016 From: dlozanosoldevilla at gmail.com (Diego Lozano-Soldevilla) Date: Fri, 30 Sep 2016 15:25:14 +0200 Subject: [FieldTrip] Reading data from arbitrary source In-Reply-To: References: Message-ID: Hi Per, These two FAQs will be relevant to you: http://www.fieldtriptoolbox.org/faq/how_can_i_import_my_own_dataformat http://www.fieldtriptoolbox.org/faq/how_are_the_various_data_structures_defined best, Diego On 30 September 2016 at 15:11, Per Knutsen wrote: > Hi, > I am new to fieldtrip with the intention of analyzing mouse ECoG/LFP data. > > I already have my datasets loaded into Matlab (from a format not directly > supported by fieldtrip). Next, I need to read this data into a fieldtrip > structure for processing. I see frequent use of a structure called cfg, > with fields: > > cfg.dataset > cfg.trialdef.threshold > cfg.trialdef.prestim > cfg.trialdef.poststim > > etc > > Can anyone direct me to the documentation of this structure's format. What > data is stored, what is the format, units etc? > > > *Per M Knutsen* > University of Oslo > Dept. of Molecular Medicine, Physiology Sect. > PB 1103 Blindern, NO-0317 Oslo > +47.45103762 > > _______________________________________________ > 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 susmitasen.ece at gmail.com Fri Sep 30 19:16:52 2016 From: susmitasen.ece at gmail.com (Susmita Sen) Date: Fri, 30 Sep 2016 22:46:52 +0530 Subject: [FieldTrip] Regarding headmodel construction Message-ID: I am Susmita Sen, MS research scholar in the dept of Electronics and Electrical Communication Engineering, IIT Kharagpur. I am currently working on MEG data recorded by yokogawa system. I want to perform source reconstruction on the data. However, I do not have the MRI data along with that. so, I have planned to use the standard MRI provided by fieldtrip (downloaded from https://github.com/fieldtrip/ fieldtrip/blob/master/template/headmodel/standard_mri.mat). For preparing the head model I have followed the steps provided in the fieldtrip tutorial (http://www.fieldtriptoolbox.org/tutorial/headmodel_meg ). %% align the coordinate system load('standard_mri.mat'); % load mri data disp(mri) cfg = []; cfg.method = 'interactive'; cfg.coordsys = 'yokogawa'; cfg.snapshot = 'yes'; [mri_aligned] = ft_volumerealign(cfg,mri); %% SEGMENTATION cfg = []; cfg.output = 'brain'; segmentedmri = ft_volumesegment(cfg, mri_aligned); %% create headmodel cfg = []; cfg.method='singleshell'; vol = ft_prepare_headmodel(cfg, segmentedmri); %% visualize load grad % load gradiometer info vol = ft_convert_units(vol,'cm'); % the gradiometer info is given in cm figure; ft_plot_sens(grad, 'style', '*b'); hold on ft_plot_vol(vol); while aligning the coordinate system I have chosen fiducial points (naison, LPA and RPA) using the instruction given by http://neuroimage.usc.edu/ brainstorm/CoordinateSystems. I am attaching the figures that display the shape of the 'vol' along with the position of the sensors (from different viewing angle). However, I doubt the headmodel is corrected prepared (It dosen't look alike the figure given in the tutorial). It seems I have made some mistakes, but I am not able to detect it. I would be very thankful if you can help me in this regard. Thanks and Regards, Susmita Sen Research Scholar Audio and Bio Signal Processing Lab. E & ECE Dept. IIT Kharagpur -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol1.png Type: image/png Size: 20100 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: vol2.png Type: image/png Size: 22926 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... 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