From g.piantoni at NIN.KNAW.NL Tue Jun 2 10:37:19 2009 From: g.piantoni at NIN.KNAW.NL (Giovanni Piantoni) Date: Tue, 2 Jun 2009 10:37:19 +0200 Subject: ICA after megrealign Message-ID: dear Fieldtrip users, I am trying to run an ICA decomposition on some MEG/CTF data (normal infomax runica.m algorithm). The ICA is generally successful (there are components that have a clear dipole scalp projection). As I am using ICA not only for artifact rejection but also for data analysis, I'd like to realign the data first. However, if I try to run ICA after megrealign (cfg.pruning = 0, to avoid rank-deficient data), the topoplots of the components look weird (the same topoplot for all the components with only one electrode active or with a strong activation on the edges). I tried to change some parameters in megrealign and componentanalysis but with little improvement. Is there any theoretical limitation on running ICA after realignment? Has anybody tried megrealign + ICA with more success? Thanks, Giovanni ------ Giovanni Piantoni, Ph.D. student Dept. Sleep & Cognition Netherlands Institute for Neuroscience Meibergdreef 47 1105 BA Amsterdam (NL) +31 (0)20 5665492 g.piantoni at nin.knaw.nl www.nin.knaw.nl/research_teams/van_someren_group ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From Martijn.Barendregt at PHIL.UU.NL Tue Jun 2 14:08:55 2009 From: Martijn.Barendregt at PHIL.UU.NL (Martijn Barendregt) Date: Tue, 2 Jun 2009 14:08:55 +0200 Subject: Difference between tfr and wltconvol Message-ID: Dear all, when I want to compute a time-frequency representation with wavelets there are two functions: freqanalysis_tfr and freqanalysis_wltconvol . I don't understand what the difference is between these two methods. Could anyone enlighten me? Thanks, Martijn ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From rmontefusco at MED.UCHILE.CL Wed Jun 3 22:19:58 2009 From: rmontefusco at MED.UCHILE.CL (Rodrigo A. Montefusco Siegmund) Date: Wed, 3 Jun 2009 16:19:58 -0400 Subject: Difference between tfr and wltconvol In-Reply-To: Message-ID: Dear FTers I have (still) problems with my timelock statistic script. I tried to develop a very simple analysis to prove all the posibilities, inclusive doing all manually. But it continues with error messages. I'll copy my code and de erros that apear when I ran it. I'm trying to compare one subject in two diferent conditions. %------------------------------------------ cfg.channel = 'all'; cfg.latency = 'all'; cfg.avgoverchan = 'no'; cfg.avgovertime = 'yes'; cfg.parameter = 'individual'; cfg.method = 'analytic'; cfg.statistic = 'depsamplesT'; cfg.alpha = 0.05; cfg.correctm = 'bonferoni'; Nsub = 1; cfg.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)]; cfg.design(2,1:2*Nsub) = [1:Nsub 1:Nsub]; cfg.ivar = 1; % the 1st row in cfg.design contains the independent variable cfg.uvar = 1; % the 2nd row in cfg.design contains the subject number [stat] = timelockstatistics(cfg, avg1, avg2); %---------------------------------------------------------- actually is almost the same as in the tutorial. the errors are... ----------------------------------------------------------- ??? Error using ==> statfun_depsamplesT at 81 Invalid specification of the design array. Error in ==> statistics_analytic at 92 [stat, cfg] = statfun(cfg, dat, design); Error in ==> statistics_wrapper at 381 [stat, cfg] = statmethod(cfg, dat, cfg.design); Error in ==> timelockstatistics at 112 [stat] = statistics_wrapper(cfg, varargin{:}); Error in ==> ERPStatistics at 19 [stat] = timelockstatistics(cfg, avg1, avg2); ----------------------------------------------------------- please help! warm regards for all! Rodrigo =================================== Rodrigo A. Montefusco Siegmund Doctorado en Ciencias Biomédicas Programa de Fisiología y Biofí­sica I. C. B. M. Facultad de Medicina Universidad de Chile Fono: 56 09 82793847 email: rmontefusco at med.uchile.cl =================================== ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From ingrid.nieuwenhuis at DONDERS.RU.NL Wed Jun 3 22:25:23 2009 From: ingrid.nieuwenhuis at DONDERS.RU.NL (Ingrid Nieuwenhuis) Date: Wed, 3 Jun 2009 22:25:23 +0200 Subject: Difference between tfr and wltconvol In-Reply-To: <47838.172.16.72.151.1244060398.squirrel@correo.med.uchile.cl> Message-ID: Dear Rodrigo, I think you have a typo in your design specification cfg.ivar and cfg.uvar is both 1, but in your comment you correctly state that uvar should be 2. Hope this helps, Ingrid > -----Original Message----- > From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On > Behalf Of Rodrigo A. Montefusco Siegmund > Sent: Wednesday, June 03, 2009 10:20 PM > To: FIELDTRIP at NIC.SURFNET.NL > Subject: Re: [FIELDTRIP] Difference between tfr and wltconvol > > Dear FTers > > I have (still) problems with my timelock statistic script. I tried to > develop a very simple analysis to prove all the posibilities, inclusive > doing all manually. But it continues with error messages. I'll copy my > code and de erros that apear when I ran it. I'm trying to compare one > subject in two diferent conditions. > > %------------------------------------------ > cfg.channel = 'all'; > cfg.latency = 'all'; > cfg.avgoverchan = 'no'; > cfg.avgovertime = 'yes'; > cfg.parameter = 'individual'; > cfg.method = 'analytic'; > cfg.statistic = 'depsamplesT'; > cfg.alpha = 0.05; > cfg.correctm = 'bonferoni'; > > Nsub = 1; > cfg.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)]; > cfg.design(2,1:2*Nsub) = [1:Nsub 1:Nsub]; > cfg.ivar = 1; % the 1st row in cfg.design contains the > independent variable > cfg.uvar = 1; % the 2nd row in cfg.design contains the > subject number > > [stat] = timelockstatistics(cfg, avg1, avg2); > %---------------------------------------------------------- > > actually is almost the same as in the tutorial. > > the errors are... > > ----------------------------------------------------------- > ??? Error using ==> statfun_depsamplesT at 81 > Invalid specification of the design array. > > Error in ==> statistics_analytic at 92 > [stat, cfg] = statfun(cfg, dat, design); > > Error in ==> statistics_wrapper at 381 > [stat, cfg] = statmethod(cfg, dat, cfg.design); > > Error in ==> timelockstatistics at 112 > [stat] = statistics_wrapper(cfg, varargin{:}); > > Error in ==> ERPStatistics at 19 > [stat] = timelockstatistics(cfg, avg1, avg2); > ----------------------------------------------------------- > > please help! > > warm regards for all! > > Rodrigo > > > > =================================== > Rodrigo A. Montefusco Siegmund > Doctorado en Ciencias Biomédicas > Programa de Fisiología y Biofí­sica > I. C. B. M. Facultad de Medicina > Universidad de Chile > Fono: 56 09 82793847 > email: rmontefusco at med.uchile.cl > =================================== > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the > FieldTrip toolbox, to share experiences and to discuss new ideas for MEG > and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From rmontefusco at MED.UCHILE.CL Wed Jun 3 22:30:09 2009 From: rmontefusco at MED.UCHILE.CL (Rodrigo A. Montefusco Siegmund) Date: Wed, 3 Jun 2009 16:30:09 -0400 Subject: timelock statistic In-Reply-To: <000001c9e489$6c96e290$642dae83@fcdonders.nl> Message-ID: Dear Ingrid I tried with many numbers combinations...but nothing happens. :( Rodrigo > Dear Rodrigo, > > I think you have a typo in your design specification cfg.ivar and cfg.uvar > is both 1, but in your comment you correctly state that uvar should be 2. > > Hope this helps, > Ingrid > >> -----Original Message----- >> From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On >> Behalf Of Rodrigo A. Montefusco Siegmund >> Sent: Wednesday, June 03, 2009 10:20 PM >> To: FIELDTRIP at NIC.SURFNET.NL >> Subject: Re: [FIELDTRIP] Difference between tfr and wltconvol >> >> Dear FTers >> >> I have (still) problems with my timelock statistic script. I tried to >> develop a very simple analysis to prove all the posibilities, inclusive >> doing all manually. But it continues with error messages. I'll copy my >> code and de erros that apear when I ran it. I'm trying to compare one >> subject in two diferent conditions. >> >> %------------------------------------------ >> cfg.channel = 'all'; >> cfg.latency = 'all'; >> cfg.avgoverchan = 'no'; >> cfg.avgovertime = 'yes'; >> cfg.parameter = 'individual'; >> cfg.method = 'analytic'; >> cfg.statistic = 'depsamplesT'; >> cfg.alpha = 0.05; >> cfg.correctm = 'bonferoni'; >> >> Nsub = 1; >> cfg.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)]; >> cfg.design(2,1:2*Nsub) = [1:Nsub 1:Nsub]; >> cfg.ivar = 1; % the 1st row in cfg.design contains the >> independent variable >> cfg.uvar = 1; % the 2nd row in cfg.design contains the >> subject number >> >> [stat] = timelockstatistics(cfg, avg1, avg2); >> %---------------------------------------------------------- >> >> actually is almost the same as in the tutorial. >> >> the errors are... >> >> ----------------------------------------------------------- >> ??? Error using ==> statfun_depsamplesT at 81 >> Invalid specification of the design array. >> >> Error in ==> statistics_analytic at 92 >> [stat, cfg] = statfun(cfg, dat, design); >> >> Error in ==> statistics_wrapper at 381 >> [stat, cfg] = statmethod(cfg, dat, cfg.design); >> >> Error in ==> timelockstatistics at 112 >> [stat] = statistics_wrapper(cfg, varargin{:}); >> >> Error in ==> ERPStatistics at 19 >> [stat] = timelockstatistics(cfg, avg1, avg2); >> ----------------------------------------------------------- >> >> please help! >> >> warm regards for all! >> >> Rodrigo >> >> >> >> =================================== >> Rodrigo A. Montefusco Siegmund >> Doctorado en Ciencias Biomédicas >> Programa de Fisiología y Biofí­sica >> I. C. B. M. Facultad de Medicina >> Universidad de Chile >> Fono: 56 09 82793847 >> email: rmontefusco at med.uchile.cl >> =================================== >> >> ---------------------------------- >> The aim of this list is to facilitate the discussion between users of >> the >> FieldTrip toolbox, to share experiences and to discuss new ideas for >> MEG >> and EEG analysis. See also >> http://listserv.surfnet.nl/archives/fieldtrip.html and >> http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the > FieldTrip toolbox, to share experiences and to discuss new ideas for MEG > and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. > =================================== Rodrigo A. Montefusco Siegmund Doctorado en Ciencias Biomédicas Programa de Fisiología y Biofí­sica I. C. B. M. Facultad de Medicina Universidad de Chile Fono: 56 09 82793847 email: rmontefusco at med.uchile.cl =================================== ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From Hanneke.vanDijk at MED.UNI-DUESSELDORF.DE Thu Jun 4 11:01:37 2009 From: Hanneke.vanDijk at MED.UNI-DUESSELDORF.DE (Hanneke Van Dijk) Date: Thu, 4 Jun 2009 11:01:37 +0200 Subject: timelockstatistic Message-ID: Dear Rodrigo, I'm wondering if the error is the same for all number-combinations that you used. I agree with Ingrid that cfg.uvar should be 2. When I test this specific part of the scripts, it seems to work for me (I don't get any error). So next I wonder what the avg1 and avg2 variables look like. The tutorial is written for grandaverage variables which include the field 'individual' (therefore, cfg.parameter='individual', cfg.parameter is the value you want to do statistics on). This field 'individual' contains the data for all subjects. Since you are looking at one subject only I guess you don't have this field. So the cfg.parameter should be 'trial'. So check if avg1 and avg2 have the field 'trial' if not do timelockanalysis again with cfg.keeptrials = 'yes'. cfg.design should then be dependent on the number of trials and not on number of subjects. If you have 10 trials for both conditions it should look something like this: Ntrials = 10 ; cfg.design(1,1:2*Ntrials) = [ones(1,Ntrials) 2*ones(1,Ntrials)]; cfg.design(2,1:2*Ntrials) = [1:Ntrials 1:trials]; cfg.design then will look like this: cfg.design ans = Columns 1 through 15 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 Columns 16 through 20 2 2 2 2 2 6 7 8 9 10 The first 10 trials belong to condition 1 and the second 10 to condition 2. This is probably why you get the design error. It doesn't fit with the parameter you want to do statistics on. I hope this was a correct hypothesis and my reply will help you! Best Regards, Hanneke ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Hanneke.vanDijk at MED.UNI-DUESSELDORF.DE Thu Jun 4 11:07:52 2009 From: Hanneke.vanDijk at MED.UNI-DUESSELDORF.DE (Hanneke van Dijk) Date: Thu, 4 Jun 2009 11:07:52 +0200 Subject: timelock statistic In-Reply-To: Message-ID: Dear Rodrigo, > > I'm wondering if the error is the same for all number-combinations that you > used. I agree with Ingrid that cfg.uvar should be 2. When I test this > specific part of the scripts, it seems to work for me (I don't get any > error). > > So next I wonder what the avg1 and avg2 variables look like. The tutorial > is written for grandaverage variables which include the field 'individual' > (therefore, cfg.parameter='individual', cfg.parameter is the value you want > to do statistics on). This field 'individual' contains the data for all > subjects. > > Since you are looking at one subject only I guess you don't have this > field. So the cfg.parameter should be 'trial'. So check if avg1 and avg2 > have the field 'trial' if not do timelockanalysis again with cfg.keeptrials > = 'yes'. > > cfg.design should then be dependent on the number of trials and not on > number of subjects. If you have 10 trials for both conditions it should look > something like this: > > Ntrials = 10 ; > cfg.design(1,1:2*Ntrials) = [ones(1,Ntrials) 2*ones(1,Ntrials)]; > cfg.design(2,1:2*Ntrials) = [1:Ntrials 1:trials]; > > cfg.design then will look like this: > > cfg.design > > ans = > > Columns 1 through 15 > > 1 1 1 1 1 1 1 1 1 1 2 > 2 2 2 2 > 1 2 3 4 5 6 7 8 9 10 1 > 2 3 4 5 > > Columns 16 through 20 > > 2 2 2 2 2 > 6 7 8 9 10 > > The first 10 trials belong to condition 1 and the second 10 to condition 2. > > This is probably why you get the design error. It doesn't fit with the > parameter you want to do statistics on. > > I hope this was a correct hypothesis and my reply will help you! > > Best Regards, > > Hanneke > > On Wed, Jun 3, 2009 at 10:30 PM, Rodrigo A. Montefusco Siegmund < > rmontefusco at med.uchile.cl> wrote: > >> Dear Ingrid >> >> I tried with many numbers combinations...but nothing happens. >> >> :( >> >> Rodrigo >> >> > Dear Rodrigo, >> > >> > I think you have a typo in your design specification cfg.ivar and >> cfg.uvar >> > is both 1, but in your comment you correctly state that uvar should be >> 2. >> > >> > Hope this helps, >> > Ingrid >> > >> >> -----Original Message----- >> >> From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On >> >> Behalf Of Rodrigo A. Montefusco Siegmund >> >> Sent: Wednesday, June 03, 2009 10:20 PM >> >> To: FIELDTRIP at NIC.SURFNET.NL >> >> Subject: Re: [FIELDTRIP] Difference between tfr and wltconvol >> >> >> >> Dear FTers >> >> >> >> I have (still) problems with my timelock statistic script. I tried to >> >> develop a very simple analysis to prove all the posibilities, inclusive >> >> doing all manually. But it continues with error messages. I'll copy my >> >> code and de erros that apear when I ran it. I'm trying to compare one >> >> subject in two diferent conditions. >> >> >> >> %------------------------------------------ >> >> cfg.channel = 'all'; >> >> cfg.latency = 'all'; >> >> cfg.avgoverchan = 'no'; >> >> cfg.avgovertime = 'yes'; >> >> cfg.parameter = 'individual'; >> >> cfg.method = 'analytic'; >> >> cfg.statistic = 'depsamplesT'; >> >> cfg.alpha = 0.05; >> >> cfg.correctm = 'bonferoni'; >> >> >> >> Nsub = 1; >> >> cfg.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)]; >> >> cfg.design(2,1:2*Nsub) = [1:Nsub 1:Nsub]; >> >> cfg.ivar = 1; % the 1st row in cfg.design contains the >> >> independent variable >> >> cfg.uvar = 1; % the 2nd row in cfg.design contains the >> >> subject number >> >> >> >> [stat] = timelockstatistics(cfg, avg1, avg2); >> >> %---------------------------------------------------------- >> >> >> >> actually is almost the same as in the tutorial. >> >> >> >> the errors are... >> >> >> >> ----------------------------------------------------------- >> >> ??? Error using ==> statfun_depsamplesT at 81 >> >> Invalid specification of the design array. >> >> >> >> Error in ==> statistics_analytic at 92 >> >> [stat, cfg] = statfun(cfg, dat, design); >> >> >> >> Error in ==> statistics_wrapper at 381 >> >> [stat, cfg] = statmethod(cfg, dat, cfg.design); >> >> >> >> Error in ==> timelockstatistics at 112 >> >> [stat] = statistics_wrapper(cfg, varargin{:}); >> >> >> >> Error in ==> ERPStatistics at 19 >> >> [stat] = timelockstatistics(cfg, avg1, avg2); >> >> ----------------------------------------------------------- >> >> >> >> please help! >> >> >> >> warm regards for all! >> >> >> >> Rodrigo >> >> >> >> >> >> >> >> =================================== >> >> Rodrigo A. Montefusco Siegmund >> >> Doctorado en Ciencias Biomédicas >> >> Programa de Fisiología y Biofí­sica >> >> I. C. B. M. Facultad de Medicina >> >> Universidad de Chile >> >> Fono: 56 09 82793847 >> >> email: rmontefusco at med.uchile.cl >> >> =================================== >> >> >> >> ---------------------------------- >> >> The aim of this list is to facilitate the discussion between users of >> >> the >> >> FieldTrip toolbox, to share experiences and to discuss new ideas for >> >> MEG >> >> and EEG analysis. See also >> >> http://listserv.surfnet.nl/archives/fieldtrip.html and >> >> http://www.ru.nl/neuroimaging/fieldtrip. >> > >> > ---------------------------------- >> > The aim of this list is to facilitate the discussion between users of >> the >> > FieldTrip toolbox, to share experiences and to discuss new ideas for >> MEG >> > and EEG analysis. See also >> > http://listserv.surfnet.nl/archives/fieldtrip.html and >> > http://www.ru.nl/neuroimaging/fieldtrip. >> > >> >> >> =================================== >> Rodrigo A. Montefusco Siegmund >> Doctorado en Ciencias Biomédicas >> Programa de Fisiología y Biofí­sica >> I. C. B. M. Facultad de Medicina >> Universidad de Chile >> Fono: 56 09 82793847 >> email: rmontefusco at med.uchile.cl >> =================================== >> >> ---------------------------------- >> The aim of this list is to facilitate the discussion between users of the >> FieldTrip toolbox, to share experiences and to discuss new ideas for MEG >> and EEG analysis. See also >> http://listserv.surfnet.nl/archives/fieldtrip.html and >> http://www.ru.nl/neuroimaging/fieldtrip. >> >> > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From charles.cook at ULETH.CA Thu Jun 4 18:04:38 2009 From: charles.cook at ULETH.CA (Charles Cook) Date: Thu, 4 Jun 2009 18:04:38 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: I've been having trouble still trying to perform cluster-based permutation tests with Fieldtrip. What I'm attempting to do is compare male and female participant's time-frequency data (between group or independent samples) generated from BESA on a spatial memory task. We've been trying to increasing the alpha levels to determine if we have any significant clusters, and even moving it up to 0.9 still does not provide any significance. Any suggestions would be much appreciated. Cheers, Charles -------------------------------- % this is the list of BESA datafiles in the Female Location condition filename_femloc = { . . }; for i=1:11 femloc{i} = besa2fieldtrip(filename_femloc{i}); end % this is the list of BESA datafiles in the Male Location condition filename_maleloc = { . . }; for i=11 maleloc{i} = besa2fieldtrip(filename_maleloc{i}); end %} % collect all single subject data in a convenient cell-array for i=1:11 femloc{i} = besa2fieldtrip(filename_femloc{i}); maleloc{i} = besa2fieldtrip(filename_maleloc{i}); end %Reading in the electrode locations for the Std.81 montage elec = read_fcdc_elec('EGI-BESA_Standard_81.sfp'); % recompute the average, except do _not_ average but keepindividual % this collects all identical time/frequency/channel samples over all subjects into a single data structure cfg = []; cfg.keepindividual = 'yes'; maleloc_all = freqgrandaverage(cfg, maleloc{:}); femloc_all = freqgrandaverage(cfg, femloc{:}); % perform the statistical test using randomization and a clustering approach % using the NEW freqstatistics function cfg = []; cfg.elec = elec; cfg.neighbourdist = 4; cfg.statistic = 'indepsamplesT'; cfg.minnbchan = 0; cfg.clusteralpha = 0.05; cfg.clustertail = 0; crg.makeclusters = 'yes'; cfg.numrandomization = 100; cfg.latency = 'all'; cfg.frequency = 'all'; cfg.avgovertime = 'no'; cfg.avgoverfreq = 'no'; cfg.avgoverchan = 'no'; cfg.correctm = 'bonferoni'; cfg.method = 'montecarlo'; cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11 % subject number is 1-11 males and 1-11 females 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % condition number with 1 being males and 2 being females cfg.uvar = 1; % "subject" is unit of observation cfg.ivar = 2; % "condition" is the independent variable [stat] = freqstatistics(cfg, maleloc_all, femloc_all); cfg = []; [freq_maleloc] = freqdescriptives(cfg, maleloc_all); [freq_femloc] = freqdescriptives(cfg, femloc_all); cfg = []; cfg.zlim = [-6 6]; cfg.alpha = 0.025; clusterplot(cfg, stat); -------------------------------- Reading time-frequency representation using BESA toolbox reading power on 81 channels . . not computing grand average, but keeping individual power for 11 subjects not computing grand average, but keeping individual power for 11 subjects selected 81 channels selected 31 time bins selected 79 frequency bins Warning: PACK can only be used from the MATLAB command line. > In fieldtrip\private\prepare_timefreq_data at 310 In fieldtrip\private\statistics_wrapper at 206 In freqstatistics at 132 In CMCWM2_std81 at 194 using "statistics_montecarlo" for the statistical testing using "statfun_indepsamplesT" for the single-sample statistics constructing randomized design total number of measurements = 22 total number of variables = 2 number of independent variables = 1 number of unit variables = 1 number of within-cell variables = 0 number of control variables = 0 using a permutation resampling approach repeated measurement in variable 1 over 11 levels number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 computing statistic estimated time per randomization is 1 seconds computing statistic 1 from 100 . . computing statistic 100 from 100 performing Bonferoni correction for multiple comparisons the returned probabilities are uncorrected, the thresholded mask is corrected the input is freq data with 81 channels, 79 frequencybins and 31 timebins computing the leave-one-out averages [---| ] computing the leave-one-out averages [-------/ ] computing the leave-one-out averages [----------- ] computing the leave-one-out averages [-------------\ ] computing the leave-one-out averages [----------------| ] computing the leave-one-out averages [--------------------/ ] computing the leave-one-out averages [------------------------ ] computing the leave-one-out averages [--------------------------\ ] computing the leave-one-out averages [-----------------------------| ] computing the leave-one-out averages [---------------------------------/ ] computing the leave-one-out averages [-------------------------------------] the input is freq data with 81 channels, 79 frequencybins and 31 timebins computing the leave-one-out averages [---| ] computing the leave-one-out averages [-------/ ] computing the leave-one-out averages [----------- ] computing the leave-one-out averages [-------------\ ] computing the leave-one-out averages [----------------| ] computing the leave-one-out averages [--------------------/ ] computing the leave-one-out averages [------------------------ ] computing the leave-one-out averages [--------------------------\ ] computing the leave-one-out averages [-----------------------------| ] computing the leave-one-out averages [---------------------------------/ ] computing the leave-one-out averages [-------------------------------------] no significant clusters in data; nothing to plot >> ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From wibral at BIC.UNI-FRANKFURT.DE Fri Jun 5 10:58:47 2009 From: wibral at BIC.UNI-FRANKFURT.DE (Michael Wibral) Date: Fri, 5 Jun 2009 10:58:47 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: Hi Charles, from your output: ... computing statistic 100 from 100 performing Bonferoni correction for multiple comparisons ... it seems that you're only computing 100 randomizations. It follows that the best p-value you could EVER get is 0.01. You then do bonferroni correction (not the cluster based correction you intended!). So if you set an alpha of 0.9 and divide this by - say - 2000 for your bonferoni corrcetion you alpha is 0.9/2000=0.00045. You see that you'll never reach this limit given that you do only 100 randomizations and by defibition cannot get below p=0.01. In addition you won't get clusters when you use Bonferroni. I suggest using: cfg.numrandomization = 5000; cfg.corectm='cluster'; % or 'fdr' Good Luck! Michael > -----Ursprüngliche Nachricht----- > Von: "Charles Cook" > Gesendet: 04.06.09 18:07:02 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: [FIELDTRIP] Freqstatistics Yields Zero Significant Clusters? > I've been having trouble still trying to perform cluster-based permutation > tests with Fieldtrip. What I'm attempting to do is compare male and female > participant's time-frequency data (between group or independent samples) > generated from BESA on a spatial memory task. We've been trying to > increasing the alpha levels to determine if we have any significant > clusters, and even moving it up to 0.9 still does not provide any > significance. > > Any suggestions would be much appreciated. > > Cheers, > > Charles > -------------------------------- > > % this is the list of BESA datafiles in the Female Location condition > filename_femloc = { > . > . > }; > for i=1:11 > femloc{i} = besa2fieldtrip(filename_femloc{i}); > end > > % this is the list of BESA datafiles in the Male Location condition > filename_maleloc = { > . > . > }; > for i=11 > maleloc{i} = besa2fieldtrip(filename_maleloc{i}); > end > %} > > % collect all single subject data in a convenient cell-array > for i=1:11 > femloc{i} = besa2fieldtrip(filename_femloc{i}); > maleloc{i} = besa2fieldtrip(filename_maleloc{i}); > end > > > %Reading in the electrode locations for the Std.81 montage > elec = read_fcdc_elec('EGI-BESA_Standard_81.sfp'); > > % recompute the average, except do _not_ average but keepindividual > % this collects all identical time/frequency/channel samples over all > subjects into a single data structure > cfg = []; > cfg.keepindividual = 'yes'; > maleloc_all = freqgrandaverage(cfg, maleloc{:}); > femloc_all = freqgrandaverage(cfg, femloc{:}); > > > % perform the statistical test using randomization and a clustering approach > % using the NEW freqstatistics function > cfg = []; > cfg.elec = elec; > cfg.neighbourdist = 4; > cfg.statistic = 'indepsamplesT'; > cfg.minnbchan = 0; > cfg.clusteralpha = 0.05; > cfg.clustertail = 0; > crg.makeclusters = 'yes'; > cfg.numrandomization = 100; > cfg.latency = 'all'; > cfg.frequency = 'all'; > cfg.avgovertime = 'no'; > cfg.avgoverfreq = 'no'; > cfg.avgoverchan = 'no'; > cfg.correctm = 'bonferoni'; > cfg.method = 'montecarlo'; > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11 % > subject number is 1-11 males and 1-11 females > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % > condition number with 1 being males and 2 being females > > cfg.uvar = 1; % "subject" is unit of > observation > cfg.ivar = 2; % "condition" is the > independent variable > [stat] = freqstatistics(cfg, maleloc_all, femloc_all); > > cfg = []; > [freq_maleloc] = freqdescriptives(cfg, maleloc_all); > [freq_femloc] = freqdescriptives(cfg, femloc_all); > > cfg = []; > cfg.zlim = [-6 6]; > cfg.alpha = 0.025; > clusterplot(cfg, stat); > > -------------------------------- > Reading time-frequency representation using BESA toolbox > reading power on 81 channels > . > . > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > selected 81 channels > selected 31 time bins > selected 79 frequency bins > Warning: PACK can only be used from the MATLAB command line. > > In fieldtrip\private\prepare_timefreq_data at 310 > In fieldtrip\private\statistics_wrapper at 206 > In freqstatistics at 132 > In CMCWM2_std81 at 194 > using "statistics_montecarlo" for the statistical testing > using "statfun_indepsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 11 levels > number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 > computing statistic > estimated time per randomization is 1 seconds > computing statistic 1 from 100 > . > . > computing statistic 100 from 100 > performing Bonferoni correction for multiple comparisons > the returned probabilities are uncorrected, the thresholded mask is corrected > the input is freq data with 81 channels, 79 frequencybins and 31 timebins > > computing the leave-one-out averages [---| ] > computing the leave-one-out averages [-------/ ] > computing the leave-one-out averages [----------- ] > computing the leave-one-out averages [-------------\ ] > computing the leave-one-out averages [----------------| ] > computing the leave-one-out averages [--------------------/ ] > computing the leave-one-out averages [------------------------ ] > computing the leave-one-out averages [--------------------------\ ] > computing the leave-one-out averages [-----------------------------| ] > computing the leave-one-out averages [---------------------------------/ ] > computing the leave-one-out averages [-------------------------------------] > the input is freq data with 81 channels, 79 frequencybins and 31 timebins > > computing the leave-one-out averages [---| ] > computing the leave-one-out averages [-------/ ] > computing the leave-one-out averages [----------- ] > computing the leave-one-out averages [-------------\ ] > computing the leave-one-out averages [----------------| ] > computing the leave-one-out averages [--------------------/ ] > computing the leave-one-out averages [------------------------ ] > computing the leave-one-out averages [--------------------------\ ] > computing the leave-one-out averages [-----------------------------| ] > computing the leave-one-out averages [---------------------------------/ ] > computing the leave-one-out averages [-------------------------------------] > no significant clusters in data; nothing to plot > >> > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 344 bytes Desc: not available URL: From Martijn.Barendregt at PHIL.UU.NL Fri Jun 5 11:07:57 2009 From: Martijn.Barendregt at PHIL.UU.NL (Martijn Barendregt) Date: Fri, 5 Jun 2009 11:07:57 +0200 Subject: Difference between tfr and wltconvol In-Reply-To: <47838.172.16.72.151.1244060398.squirrel@correo.med.uchile.cl> Message-ID: Dear Rodrigo, could you perhaps reply to my question only with something relevant instead of with your own problem? regards, Martijn Barendregt > Dear FTers > > I have (still) problems with my timelock statistic script. I tried to > develop a very simple analysis to prove all the posibilities, inclusive > doing all manually. But it continues with error messages. I'll copy my > code and de erros that apear when I ran it. I'm trying to compare one > subject in two diferent conditions. > > %------------------------------------------ > cfg.channel = 'all'; > cfg.latency = 'all'; > cfg.avgoverchan = 'no'; > cfg.avgovertime = 'yes'; > cfg.parameter = 'individual'; > cfg.method = 'analytic'; > cfg.statistic = 'depsamplesT'; > cfg.alpha = 0.05; > cfg.correctm = 'bonferoni'; > > Nsub = 1; > cfg.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)]; > cfg.design(2,1:2*Nsub) = [1:Nsub 1:Nsub]; > cfg.ivar = 1; % the 1st row in cfg.design contains the > independent variable > cfg.uvar = 1; % the 2nd row in cfg.design contains the > subject number > > [stat] = timelockstatistics(cfg, avg1, avg2); > %---------------------------------------------------------- > > actually is almost the same as in the tutorial. > > the errors are... > > ----------------------------------------------------------- > ??? Error using ==> statfun_depsamplesT at 81 > Invalid specification of the design array. > > Error in ==> statistics_analytic at 92 > [stat, cfg] = statfun(cfg, dat, design); > > Error in ==> statistics_wrapper at 381 > [stat, cfg] = statmethod(cfg, dat, cfg.design); > > Error in ==> timelockstatistics at 112 > [stat] = statistics_wrapper(cfg, varargin{:}); > > Error in ==> ERPStatistics at 19 > [stat] = timelockstatistics(cfg, avg1, avg2); > ----------------------------------------------------------- > > please help! > > warm regards for all! > > Rodrigo > > > > =================================== > Rodrigo A. Montefusco Siegmund > Doctorado en Ciencias Biomédicas > Programa de Fisiología y Biofí­sica > I. C. B. M. Facultad de Medicina > Universidad de Chile > Fono: 56 09 82793847 > email: rmontefusco at med.uchile.cl > =================================== > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the > FieldTrip toolbox, to share experiences and to discuss new ideas for MEG > and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From Erick.Ortiz at MED.UNI-TUEBINGEN.DE Fri Jun 5 18:11:52 2009 From: Erick.Ortiz at MED.UNI-TUEBINGEN.DE (Erick Britis Ortiz) Date: Fri, 5 Jun 2009 18:11:52 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: <984158235@web.de> Message-ID: Dear fieldtrip users, (with special thanks to Michael Wibral's assessment) Following up on the discussion, we have also tried to use the cluster option for multiple comparisons correction in a previous study and thought that our results were not significant. Now, we tried again with 1000 randomizations and cfg.correctm = 'cluster', to no avail. Since we are interested in p<0.05, 1000 iterations seem large enough, but most of the probabilities calculated are near or equal to 100%. Further testing with 10000 permutations yielded similar results. We are fairly sure that there is something there, because calculating analytically we see big clusters that extend in a consistent way to neighboring frequency and time bins, even at low p thresholds (<10^-4). Since Bonferroni is over-strict, Montecarlo is the option of choice for a corrected result that we will trust. But now something seems off. Our data is 275 channels x 13 time x 31 frequency bins. The attached graphics show: Fig.1: old study, histogram of montecarlo results Fig.2: present study, histogram of analytical results Fig.3: present study, histogram of montecarlo results Fig.4: present study, imagesc of montecarlo results (sum with channels with prob.<0.001 for each time and freq.) Questions: 1) What do these results mean? 2) How to get a mask for a new p threshold without having to recalculate everything? (the probabilities are valid, but since the thresholds are dynamic, we cannot make a meaningful comparison with a fixed value) Any ideas will be appreciated! Thank you in advance, Erick Britis Ortiz MEG-Zentrum, University of Tübingen Michael Wibral wrote: > Hi Charles, > > from your output: ... computing statistic 100 from 100 performing > Bonferoni correction for multiple comparisons ... > > it seems that you're only computing 100 randomizations. It follows > that the best p-value you could EVER get is 0.01. You then do > bonferroni correction (not the cluster based correction you > intended!). So if you set an alpha of 0.9 and divide this by - say - > 2000 for your bonferoni corrcetion you alpha is 0.9/2000=0.00045. You > see that you'll never reach this limit given that you do only 100 > randomizations and by defibition cannot get below p=0.01. In addition > you won't get clusters when you use Bonferroni. > > I suggest using: > > cfg.numrandomization = 5000; cfg.corectm='cluster'; % or 'fdr' > > > Good Luck! Michael ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig1_Study1_hist_mc.png Type: image/png Size: 2650 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig2_Study2_hist_an.png Type: image/png Size: 3083 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig3_Study2_hist_mc.png Type: image/png Size: 2853 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig4_Study2_montecarlo_imagesc.png Type: image/png Size: 4950 bytes Desc: not available URL: From adrian.m.bartlett at GMAIL.COM Fri Jun 5 20:32:43 2009 From: adrian.m.bartlett at GMAIL.COM (Adrian Bartlett) Date: Fri, 5 Jun 2009 14:32:43 -0400 Subject: Modying Maris et al. (2007) for acute animal recordings Message-ID: I am wondering if any of you have any advice or experience adapting the methods of Maris et al. (2007) to acute animal recordings. The basic problem is that we sample different locations on different days, each yielding different trial numbers, and they certainly aren't 'the same trial'. The simplest way to deal with this, as I see it, is as follows: Carry out Maris et al. (2007) methods within each session, clustering across time (we are working with dynamic spectra and coherencies), frequency, and space. To correct for the multiple recording sessions, use a crude bonferonni-corrected P-value as the threshold for the Monte-Carlo P value (prcit/nsess) for identifying significant clusters. ((or correct the critical value for establishing what the empirical clusters are initially)) Is this unsound in any way? Any alternatives? The obvious drawbacks are having to introduce bonferroni-correction, as well as losing sensitivity to weak effects seen in spatial proximity across different sessions (i.e. the same guide tube position over many days). Any input on this would be greatly appreciated, Thanks in advance. -- Adrian M. Bartlett, BA Neuroscience Graduate Diploma Program Graduate Program in Psychology Perception & Plasticity Laboratory Centre for Vision Research York University, Toronto, ON, Canada -- ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From charles.cook at ULETH.CA Fri Jun 5 21:47:39 2009 From: charles.cook at ULETH.CA (Charles Cook) Date: Fri, 5 Jun 2009 21:47:39 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: Hi Michael, Excellent points, which were well taken. I've made those changes and modified my time and frequency windows a bit as well to better reflect our a priori hypotheses. I first ran the analysis with cfg.latency = [0 250], and again came up with zero significant clusters. While it's entirely possible there might not be anything significant, the topo plots I'd generated certainly suggested some serious qualitative differences between male and female images. But be that as it may, I then changed the cfg.latency = [250 500] and received this as an error: -------------------------------------------------------------------------- . . computing clusters in randomization 4999 from 5000 computing clusters in randomization 5000 from 5000 using a cluster-based method for multiple comparison correction the returned probabilities and the thresholded mask are corrected for multiple comparisons the input is freq data with 81 channels, 79 frequencybins and 31 timebins computing the leave-one-out averages [---| ] computing the leave-one-out averages [-------/ ] computing the leave-one-out averages [----------- ] computing the leave-one-out averages [-------------\ ] computing the leave-one-out averages [----------------| ] computing the leave-one-out averages [--------------------/ ] computing the leave-one-out averages [------------------------ ] computing the leave-one-out averages [--------------------------\ ] computing the leave-one-out averages [-----------------------------| ] computing the leave-one-out averages [---------------------------------/ ] computing the leave-one-out averages [-------------------------------------] the input is freq data with 81 channels, 79 frequencybins and 31 timebins computing the leave-one-out averages [---| ] computing the leave-one-out averages [-------/ ] computing the leave-one-out averages [----------- ] computing the leave-one-out averages [-------------\ ] computing the leave-one-out averages [----------------| ] computing the leave-one-out averages [--------------------/ ] computing the leave-one-out averages [------------------------ ] computing the leave-one-out averages [--------------------------\ ] computing the leave-one-out averages [-----------------------------| ] computing the leave-one-out averages [---------------------------------/ ] computing the leave-one-out averages [-------------------------------------] ??? Assignment has more non-singleton rhs dimensions than non-singleton subscripts Error in ==> clusterplot at 91 sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); Error in ==> CMCWM2_std81 at 160 clusterplot(cfg, stat); ------------------------------------------------------------ I'm assuming that this particular analysis does have significant clusters since it passed where other simply reported 'no significant clusters'. Not sure what's going on here with the clusterplot though. One further question is whether calculations are still being performed on all 79 frequencybins and 31 timebins when I have specified otherwise. And lastly I would also like to take this opportunity to thank Michael for his much valued assistance into these many questions I've had, both on the board and personal correspondence. Cheers, Charles On Fri, 5 Jun 2009 10:58:47 +0200, Michael Wibral wrote: >Hi Charles, > >from your output: >... >computing statistic 100 from 100 >performing Bonferoni correction for multiple comparisons >... > >it seems that you're only computing 100 randomizations. It follows that the best p-value you could EVER get is 0.01. You then do bonferroni correction (not the cluster based correction you intended!). So if you set an alpha of 0.9 and divide this by - say - 2000 for your bonferoni corrcetion you alpha is 0.9/2000=0.00045. You see that you'll never reach this limit given that you do only 100 randomizations and by defibition cannot get below p=0.01. In addition you won't get clusters when you use Bonferroni. > >I suggest using: > >cfg.numrandomization = 5000; >cfg.corectm='cluster'; % or 'fdr' > > >Good Luck! >Michael ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Sat Jun 6 09:04:43 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Sat, 6 Jun 2009 09:04:43 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: Message-ID: Hi Charles, Although I'm not 100 percent sure that this is the cause of your problems, the way you specify the unit of observation is definitely wrong. You have 22 units of observations (i.c., subjects) so the first row of cfg.design must be [1 2 ... 22; ... ] Also, did you check whether cfg.design is a 2-by-22 array? In the lines below, a semicolon seems to be missing. > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11 % > subject number is 1-11 males and 1-11 females > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % > condition number with 1 being males and 2 being females > > cfg.uvar = 1; % "subject" is unit of > observation > cfg.ivar = 2; % "condition" is the > independent variable Good luck, dr. Eric Maris Donders Institute for Brain, Cognition and Behavior Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging Radboud University P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 F:+31 24 3616066 E: e.maris at donders.ru.nl MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > [stat] = freqstatistics(cfg, maleloc_all, femloc_all); > > cfg = []; > [freq_maleloc] = freqdescriptives(cfg, maleloc_all); > [freq_femloc] = freqdescriptives(cfg, femloc_all); > > cfg = []; > cfg.zlim = [-6 6]; > cfg.alpha = 0.025; > clusterplot(cfg, stat); > > -------------------------------- > Reading time-frequency representation using BESA toolbox > reading power on 81 channels > . > .. > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > selected 81 channels > selected 31 time bins > selected 79 frequency bins > Warning: PACK can only be used from the MATLAB command line. > > In fieldtrip\private\prepare_timefreq_data at 310 > In fieldtrip\private\statistics_wrapper at 206 > In freqstatistics at 132 > In CMCWM2_std81 at 194 > using "statistics_montecarlo" for the statistical testing > using "statfun_indepsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 11 levels > number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 > computing statistic > estimated time per randomization is 1 seconds > computing statistic 1 from 100 > . > .. > computing statistic 100 from 100 > performing Bonferoni correction for multiple comparisons > the returned probabilities are uncorrected, the thresholded mask is corrected > the input is freq data with 81 channels, 79 frequencybins and 31 timebins > > computing the leave-one-out averages [---| ] > computing the leave-one-out averages [-------/ ] > computing the leave-one-out averages [----------- ] > computing the leave-one-out averages [-------------\ ] > computing the leave-one-out averages [----------------| ] > computing the leave-one-out averages [--------------------/ ] > computing the leave-one-out averages [------------------------ ] > computing the leave-one-out averages [--------------------------\ ] > computing the leave-one-out averages [-----------------------------| ] > computing the leave-one-out averages [---------------------------------/ ] > computing the leave-one-out averages [-------------------------------------] > the input is freq data with 81 channels, 79 frequencybins and 31 timebins > > computing the leave-one-out averages [---| ] > computing the leave-one-out averages [-------/ ] > computing the leave-one-out averages [----------- ] > computing the leave-one-out averages [-------------\ ] > computing the leave-one-out averages [----------------| ] > computing the leave-one-out averages [--------------------/ ] > computing the leave-one-out averages [------------------------ ] > computing the leave-one-out averages [--------------------------\ ] > computing the leave-one-out averages [-----------------------------| ] > computing the leave-one-out averages [---------------------------------/ ] > computing the leave-one-out averages [-------------------------------------] > no significant clusters in data; nothing to plot > >> > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Sat Jun 6 09:07:58 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Sat, 6 Jun 2009 09:07:58 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: <4A2943C8.4040600@med.uni-tuebingen.de> Message-ID: Dear Erick, > Following up on the discussion, we have also tried to use the cluster > option for multiple comparisons correction in a previous study and > thought that our results were not significant. Now, we tried again with > 1000 randomizations and cfg.correctm = 'cluster', to no avail. Since we > are interested in p<0.05, 1000 iterations seem large enough, but most of > the probabilities calculated are near or equal to 100%. Further testing > with 10000 permutations yielded similar results. > > We are fairly sure that there is something there, because calculating > analytically we see big clusters that extend in a consistent way to > neighboring frequency and time bins, even at low p thresholds (<10^-4). > Since Bonferroni is over-strict, Montecarlo is the option of choice for > a corrected result that we will trust. But now something seems off. Can you post the configuration that you used for these analyses? dr. Eric Maris Donders Institute for Brain, Cognition and Behavior Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging Radboud University P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 F:+31 24 3616066 E: e.maris at donders.ru.nl MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > > > Thank you in advance, > Erick Britis Ortiz > MEG-Zentrum, University of Tübingen > > > Michael Wibral wrote: > > Hi Charles, > > > > from your output: ... computing statistic 100 from 100 performing > > Bonferoni correction for multiple comparisons ... > > > > it seems that you're only computing 100 randomizations. It follows > > that the best p-value you could EVER get is 0.01. You then do > > bonferroni correction (not the cluster based correction you > > intended!). So if you set an alpha of 0.9 and divide this by - say - > > 2000 for your bonferoni corrcetion you alpha is 0.9/2000=0.00045. You > > see that you'll never reach this limit given that you do only 100 > > randomizations and by defibition cannot get below p=0.01. In addition > > you won't get clusters when you use Bonferroni. > > > > I suggest using: > > > > cfg.numrandomization = 5000; cfg.corectm='cluster'; % or 'fdr' > > > > > > Good Luck! Michael > > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Sat Jun 6 11:31:32 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Sat, 6 Jun 2009 11:31:32 +0200 Subject: Modying Maris et al. (2007) for acute animal recordings In-Reply-To: <7834c8d30906051132w48525e10k84d093b40f9dcb2a@mail.gmail.com> Message-ID: Dear Adrian, I am wondering if any of you have any advice or experience adapting the methods of Maris et al. (2007) to acute animal recordings. The basic problem is that we sample different locations on different days, each yielding different trial numbers, and they certainly aren't 'the same trial'. The simplest way to deal with this, as I see it, is as follows: Carry out Maris et al. (2007) methods within each session, clustering across time (we are working with dynamic spectra and coherencies), frequency, and space. To correct for the multiple recording sessions, use a crude bonferonni-corrected P-value as the threshold for the Monte-Carlo P value (prcit/nsess) for identifying significant clusters. ((or correct the critical value for establishing what the empirical clusters are initially)) Is this unsound in any way? Any alternatives? The obvious drawbacks are having to introduce bonferroni-correction, as well as losing sensitivity to weak effects seen in spatial proximity across different sessions (i.e. the same guide tube position over many days). A lot can be said in response to your questions. Actually, it's on my Todo list to write a methodological paper about some of the issues that you raise. These are the main points I can think about: 1. As your unit of observation, you can choose for trials as well as sessions. If you choose for sessions, then your dependent variable is an average over the trials within every session. 2. If your unit of observation is trials AND if there is heterogeneity across the different sessions, then you should incorporate the variable SESSION as a blocking variable. The theory of permutation tests also applies in the context of blocking variables. I have added the blocking variable option in the statfuns for testing regression coefficients. This was for a joint project with Vladimir Litvak, and the paper should be somewhere under review now. I have not yet added it to the indepsamplesT and depsamplesT statfuns, but that shouldn't be too much of an effort. 3. The presence of effects that are confined to a particular subvolume of the brain tissue from which you sample, is a tricky one. Clustering in space definitely is an option, but the current Fieldtrip code cannot deal with the fact that the different recording sites were only partly sampled concurrently (because the probes are lowered to different locations on different sessions), at least not in a straightforward fashion. This differs from extracranial recordings in which there is typically only a single recording session with a single channel configuration. With good Matlab programming skills, it is definitely possible to make the required changes to the Fieldtrip code. Good luck, dr. Eric Maris Donders Institute for Brain, Cognition and Behavior Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging Radboud University P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 F:+31 24 3616066 E: e. maris at donders.ru.nl MSc Cognitive Neuroscience: www.ru.nl/master/cns/ Any input on this would be greatly appreciated, Thanks in advance. -- Adrian M. Bartlett, BA Neuroscience Graduate Diploma Program Graduate Program in Psychology Perception & Plasticity Laboratory Centre for Vision Research York University, Toronto, ON, Canada -- ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. http://listserv.surfnet.nl/archives/fieldtrip.html http://www.ru.nl/fcdonders/fieldtrip/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From cmuehl at GMAIL.COM Sun Jun 7 12:29:06 2009 From: cmuehl at GMAIL.COM (Christian Muehl) Date: Sun, 7 Jun 2009 12:29:06 +0200 Subject: 2.CfP Workshop on Affective Brain Computer Interfaces - submission deadline extension Message-ID: -------------------------------------------------------------- ! 2nd Call for Papers + deadline extension ! -------------------------------------------------------------- Workshop on Affective Brain-Computer Interfaces (held in conjunction with ACII’09) Amsterdam, The Netherlands, 09.09.2009 -------------------------------------------------------------- ! Due to changes of the workshop proceedings to IEEE format the submission deadline is extended to the 22th of June ! Please check the new format requirements. Overview This workshop will explore the advantages and limitations of using neurophysiological signals as a modality for the automatic recognition of affective and cognitive states, and the possibilities of using this information about the user state in innovative and adaptive applications. Theme of the workshop: Recent research in brain-computer interfaces (BCI) shows that brain activity can be used as an active/voluntary, or passive/involuntary control modality in man-machine interaction. While active BCI paradigms have received a lot of attention in recent years, research on passive approaches to BCI still desperately needs concerted activity. However, it has been shown more than once that brain activations can carry information about the affective and cognitive state of a subject, and that the interaction between humans and machines can be aided by the recognition of those user states. To achieve robust passive BCIs, efforts from applied and basic sciences have to be combined. On the one hand, applied fields such as affective computing aim at the development of applications that adapt to changes in the user states and thereby enrich the interaction, leading to a more natural and effective usability. On the other hand, basic research in neuroscience advances our understanding of the neural processes associated with emotions. Furthermore, similar advancements are being made for more cognitive mental states, for example, attention, fatigue, and work load, which strongly interact with affective states. We encourage submissions exploring one or more of the following topics: * emotion elicitation and data collection for affective BCI * detection of affective and cognitive states with BCI and other modalities * adaptive interfaces and affective BCI Goal of the workshop: The goal of this workshop is to bring researchers from the communities of brain computer interfacing, affective computing, neuroergonomics, affective and cognitive neuroscience together to present state-of-the-art progress and visions on the various overlaps between those disciplines. Paper submissions: Papers should be 6 - 12 pages long and in IEEE format specified on the workshop page. Submissions should have a clear relationship to brain-computer interfacing and to one or more of the other topics listed above. The accepted papers will be published in IEEE workshop proceedings accompanying the ACII proceedings. Please submit your papers in PDF format to ABCI at ewi.utwente.nl . Important Dates: Paper Submission: 22.06.2009 Acceptance Note: 20.07.2009 Camera-ready versions: 15.08.2009 Further information can be found on the workshop website. Workshop Website: http://hmi.ewi.utwente.nl/abci2009 Email: ABCI at ewi.utwente.nl Programme Chairs: * Brendan Allison, Technische Universitaet Graz, Austria * Stephen Dunne, StarLabs Barcelona, Spain * Dirk Heylen, Universiteit Twente, The Netherlands * Anton Nijholt, Universiteit Twente, The Netherlands Local Organizer: * Christian Muehl, Universiteit Twente, The Netherlands Programme Committee: * Anne-Marie Brouwer, TNO Soesterberg, The Netherlands * Stephen Fairclough, John Moores University Liverpool, United Kingdom * Peter Desain, Radboud University Nijmegen, The Netherlands * Grandjean Didier, University Geneva, Switzerland * Markus Junghöfer, Universität Münster, Germany * Jonghwa Kim, Universitaet Augsburg, Germany * Gary Garcia Molina, Phillips Research Eindhoven, The Netherlands * Femke Nijboer, Fatronik - Tecnalia, Donostia, Spain * Ioannis Patras, Queen Mary University of London, United Kingdom * Gert Pfurtscheller, Technische Universitaet Graz, Austria * Thierry Pun, University of Geneva, Switzerland * Egon van den Broek, University of Twente, The Netherlands * Thorsten Oliver Zander, Technische Universität Berlin, Germany ------------------------------------------------------------------------ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From Erick.Ortiz at MED.UNI-TUEBINGEN.DE Mon Jun 8 15:05:48 2009 From: Erick.Ortiz at MED.UNI-TUEBINGEN.DE (Erick Britis Ortiz) Date: Mon, 8 Jun 2009 15:05:48 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: <200906060707.n5677tHJ024181@smtp20.nijmegen.internl.net> Message-ID: Dear Eric, this is the configuration used for the analysis. % Configuration for statistics cfg = []; cfg.channel = 'MEG'; cfg.latency = [ 0.0 0.6 ]; cfg.avgovertime = 'no'; cfg.method = 'montecarlo'; cfg.numrandomization = 1000; cfg.statistic = 'depsamplesT'; cfg.alpha = 0.05; cfg.tail = 0; cfg.correctm = 'cluster'; cfg.grad = grad; cfg.clusteralpha = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.minnbchan = 2; cfg.clustertail = 0; cfg.design(1,1:2*numsubj) = [ones(1,numsubj) 2*ones(1,numsubj)]; cfg.design(2,1:2*numsubj) = [1:numsubj 1:numsubj]; cfg.ivar = 1; % the 1st row in cfg.design contains the independent variable cfg.uvar = 2; % the 2nd row in cfg.design contains the subject number Cordially, Erick Eric Maris wrote: > Dear Erick, > > >> Following up on the discussion, we have also tried to use the cluster >> option for multiple comparisons correction in a previous study and >> thought that our results were not significant. Now, we tried again with >> 1000 randomizations and cfg.correctm = 'cluster', to no avail. Since we >> are interested in p<0.05, 1000 iterations seem large enough, but most of >> the probabilities calculated are near or equal to 100%. Further testing >> with 10000 permutations yielded similar results. >> >> We are fairly sure that there is something there, because calculating >> analytically we see big clusters that extend in a consistent way to >> neighboring frequency and time bins, even at low p thresholds (<10^-4). >> Since Bonferroni is over-strict, Montecarlo is the option of choice for >> a corrected result that we will trust. But now something seems off. > > > Can you post the configuration that you used for these analyses? > > > dr. Eric Maris > Donders Institute for Brain, Cognition and Behavior > Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging > Radboud University > P.O. Box 9104 > 6500 HE Nijmegen > The Netherlands > T:+31 24 3612651 > F:+31 24 3616066 > E: e.maris at donders.ru.nl > > MSc Cognitive Neuroscience: www.ru.nl/master/cns/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Mon Jun 8 16:34:55 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Mon, 8 Jun 2009 16:34:55 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: Dear Erick, The configuration that you posted seems OK. I am a bit puzzled by the following lines that you posted previously: >> We are fairly sure that there is something there, because calculating >> analytically we see big clusters that extend in a consistent way to >> neighboring frequency and time bins, even at low p thresholds (<10^-4). >> Since Bonferroni is over-strict, Montecarlo is the option of choice >> for a corrected result that we will trust. But now something seems off. I'm trying to find out what might be off. One way to perform a check on the cluster-based permutation test is trying to find the biggest cluster that you identified using other code than the one in freqstatistics. This biggest positive cluster should show up in statout.posclusters(1) and the biggest negative cluster in statout.negclusters(1) (statout is the output of freqstatistics). With cfg.clusteralpha, you can control the size of the clusters (the smaller cfg.clusteralpha, the smaller the clusters). Another way to get some confidence in freqstatistics is reducing the dimensionality of data arrays. I understood that you now compare three-dimensional data arrays (channels X frequency X time). By selecting two- or one-dimensional slices from this three-dimensional array, the Monte Carlo p-values should become smaller, at least if you select channels, frequencies, or time points that show differences between the two conditions. At the extreme, using cluster-based permutation to test a single (channel,frequency,time)-triplet, the Monte Carlo p-value should be approximately equal to the analytical (T-distribution-based) p-value. Good luck, Eric dr. Eric Maris Donders Institute for Brain, Cognition and Behavior Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging Radboud University P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 F:+31 24 3616066 E: e.maris at donders.ru.nl MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > -----Oorspronkelijk bericht----- > Van: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] Namens Erick > Britis Ortiz > Verzonden: maandag 8 juni 2009 15:06 > Aan: FIELDTRIP at NIC.SURFNET.NL > Onderwerp: Re: [FIELDTRIP] Freqstatistics Yields Zero Significant Clusters? > > Dear Eric, > > this is the configuration used for the analysis. > > % Configuration for statistics > cfg = []; > cfg.channel = 'MEG'; > cfg.latency = [ 0.0 0.6 ]; > cfg.avgovertime = 'no'; > cfg.method = 'montecarlo'; > cfg.numrandomization = 1000; > cfg.statistic = 'depsamplesT'; > cfg.alpha = 0.05; > cfg.tail = 0; > cfg.correctm = 'cluster'; cfg.grad = grad; > cfg.clusteralpha = 0.05; > cfg.clusterstatistic = 'maxsum'; > cfg.minnbchan = 2; > cfg.clustertail = 0; > cfg.design(1,1:2*numsubj) = [ones(1,numsubj) 2*ones(1,numsubj)]; > cfg.design(2,1:2*numsubj) = [1:numsubj 1:numsubj]; > cfg.ivar = 1; % the 1st row in cfg.design contains the > independent variable > cfg.uvar = 2; % the 2nd row in cfg.design contains the > subject number > > Cordially, > Erick > > > Eric Maris wrote: > > Dear Erick, > > > > > >> Following up on the discussion, we have also tried to use the cluster > >> option for multiple comparisons correction in a previous study and > >> thought that our results were not significant. Now, we tried again with > >> 1000 randomizations and cfg.correctm = 'cluster', to no avail. Since we > >> are interested in p<0.05, 1000 iterations seem large enough, but most of > >> the probabilities calculated are near or equal to 100%. Further testing > >> with 10000 permutations yielded similar results. > >> > >> We are fairly sure that there is something there, because calculating > >> analytically we see big clusters that extend in a consistent way to > >> neighboring frequency and time bins, even at low p thresholds (<10^-4). > >> Since Bonferroni is over-strict, Montecarlo is the option of choice for > >> a corrected result that we will trust. But now something seems off. > > > > > > Can you post the configuration that you used for these analyses? > > > > > > dr. Eric Maris > > Donders Institute for Brain, Cognition and Behavior > > Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging > > Radboud University > > P.O. Box 9104 > > 6500 HE Nijmegen > > The Netherlands > > T:+31 24 3612651 > > F:+31 24 3616066 > > E: e.maris at donders.ru.nl > > > > MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From charles.cook at ULETH.CA Mon Jun 8 16:40:41 2009 From: charles.cook at ULETH.CA (Charles Cook) Date: Mon, 8 Jun 2009 16:40:41 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: Hi Eric, We have modified the code based on your suggestions and I think we're very close now. This is our most recent output: ------------------------------------- reading power on 81 channels not computing grand average, but keeping individual power for 11 subjects not computing grand average, but keeping individual power for 11 subjects selected 81 channels selected 6 time bins selected 4 frequency bins Warning: PACK can only be used from the MATLAB command line. > In fieldtrip\private\prepare_timefreq_data at 310 In fieldtrip\private\statistics_wrapper at 206 In freqstatistics at 132 In CMCWM2_std81_junk_with at 144 Obtaining the electrode configuration from the configuration. there are on average 83.0 neighbours per channel using "statistics_montecarlo" for the statistical testing using "statfun_indepsamplesT" for the single-sample statistics constructing randomized design total number of measurements = 22 total number of variables = 2 number of independent variables = 1 number of unit variables = 1 number of within-cell variables = 0 number of control variables = 0 using a permutation resampling approach repeated measurement in variable 1 over 22 levels number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 computing a parmetric threshold for clustering estimated time per randomization is 0 seconds found 2 positive clusters in observed data found 1 negative clusters in observed data using a cluster-based method for multiple comparison correction the returned probabilities and the thresholded mask are corrected for multiple comparisons ??? Assignment has more non-singleton rhs dimensions than non-singleton subscripts Error in ==> clusterplot at 91 sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); Error in ==> CMCWM2_std81_junk_with at 153 clusterplot (cfg, stat); ----------------- We do keep running into this error with clusterplot. Which we have as follows: cfg = []; cfg.zlim = [-6 6]; cfg.alpha = 0.05; clusterplot(cfg, stat); It crashes on the last line. Does anyone have any ideas where we might be going wrong here? Cheers, Charles On Sat, 6 Jun 2009 09:04:43 +0200, Eric Maris wrote: >Hi Charles, > > > >Although I'm not 100 percent sure that this is the cause of your problems, >the way you specify the unit of observation is definitely wrong. You have 22 >units of observations (i.c., subjects) so the first row of cfg.design must >be [1 2 ... 22; ... ] > >Also, did you check whether cfg.design is a 2-by-22 array? In the lines >below, a semicolon seems to be missing. > >> cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11 % >> subject number is 1-11 males and 1-11 females >> 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % >> condition number with 1 being males and 2 being females >> >> cfg.uvar = 1; % "subject" is unit of >> observation >> cfg.ivar = 2; % "condition" is the >> independent variable > > >Good luck, > > >dr. Eric Maris >Donders Institute for Brain, Cognition and Behavior >Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging >Radboud University >P.O. Box 9104 >6500 HE Nijmegen >The Netherlands >T:+31 24 3612651 >F:+31 24 3616066 >E: e.maris at donders.ru.nl > >MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Mon Jun 8 17:00:22 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Mon, 8 Jun 2009 17:00:22 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: Message-ID: Hi Charles, > We have modified the code based on your suggestions and I think we're very > close now. This is our most recent output: > > ------------------------------------- > reading power on 81 channels > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > selected 81 channels > selected 6 time bins > selected 4 frequency bins > Warning: PACK can only be used from the MATLAB command line. > > In fieldtrip\private\prepare_timefreq_data at 310 > In fieldtrip\private\statistics_wrapper at 206 > In freqstatistics at 132 > In CMCWM2_std81_junk_with at 144 > Obtaining the electrode configuration from the configuration. > there are on average 83.0 neighbours per channel 83.0 neighbours per channel does not make sense. For EEG-channels this number typically is 4 and for MEG-channels it is typically 6. Have a look at the neighbourhood geometry structure that is constructed by freqstatistics. I guess this structure is far too wide (a channel is considered a neighbour of almost every other channel). Best, Eric > using "statistics_montecarlo" for the statistical testing > using "statfun_indepsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 22 levels > number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 1 > 1 1 1 1 1 1 1 1 > computing a parmetric threshold for clustering > estimated time per randomization is 0 seconds > found 2 positive clusters in observed data > found 1 negative clusters in observed data > using a cluster-based method for multiple comparison correction > the returned probabilities and the thresholded mask are corrected for > multiple comparisons > ??? Assignment has more non-singleton rhs dimensions than non-singleton > subscripts > > Error in ==> clusterplot at 91 > sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); > > Error in ==> CMCWM2_std81_junk_with at 153 > clusterplot (cfg, stat); > > ----------------- > > We do keep running into this error with clusterplot. Which we have as follows: > > cfg = []; > cfg.zlim = [-6 6]; > cfg.alpha = 0.05; > clusterplot(cfg, stat); > > It crashes on the last line. Does anyone have any ideas where we might be > going wrong here? > > Cheers, > > Charles > > On Sat, 6 Jun 2009 09:04:43 +0200, Eric Maris > wrote: > > >Hi Charles, > > > > > > > >Although I'm not 100 percent sure that this is the cause of your problems, > >the way you specify the unit of observation is definitely wrong. You have 22 > >units of observations (i.c., subjects) so the first row of cfg.design must > >be [1 2 ... 22; ... ] > > > >Also, did you check whether cfg.design is a 2-by-22 array? In the lines > >below, a semicolon seems to be missing. > > > >> cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11 % > >> subject number is 1-11 males and 1-11 females > >> 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % > >> condition number with 1 being males and 2 being females > >> > >> cfg.uvar = 1; % "subject" is unit of > >> observation > >> cfg.ivar = 2; % "condition" is the > >> independent variable > > > > > >Good luck, > > > > > >dr. Eric Maris > >Donders Institute for Brain, Cognition and Behavior > >Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging > >Radboud University > >P.O. Box 9104 > >6500 HE Nijmegen > >The Netherlands > >T:+31 24 3612651 > >F:+31 24 3616066 > >E: e.maris at donders.ru.nl > > > >MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From charles.cook at ULETH.CA Mon Jun 8 21:51:51 2009 From: charles.cook at ULETH.CA (Charles Cook) Date: Mon, 8 Jun 2009 21:51:51 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: Hi Eric, Yes that did seem to a further unusually high number, especially since they're all standard-81! Let me give you an idea of where our code is presently at: ============================================ cfg = []; cfg.neighbourdist = 4; cfg.elec = elec; cfg.statistic = 'indepsamplesT'; cfg.minnbchan = 0; cfg.clusteralpha = 0.05; cfg.alpha = 0.05; cfg.clustertail = 0; cfg.numrandomization = 5000; cfg.latency = [250 500]; cfg.frequency = [4 7]; cfg.avgovertime = 'no'; cfg.avgoverfreq = 'no'; cfg.avgoverchan = 'no'; cfg.correctm = 'cluster'; cfg.method = 'montecarlo'; cfg.feedback = 'gui'; cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22; % subject number 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % condition number cfg.uvar = 1; % "subject" is unit of observation cfg.ivar = 2; % "condition" is the independent variable stat = freqstatistics(cfg, malefeat_all, femloc_all); %cfg = []; %[freq_maleloc] = freqdescriptives(cfg, maleloc_all); %[freq_femloc] = freqdescriptives(cfg, femloc_all); cfg = []; cfg.zlim = [-6 6]; cfg.alpha = 0.05; clusterplot (cfg, stat); <----still failing here ============================================ Reading power on 81 channels not computing grand average, but keeping individual power for 11 subjects not computing grand average, but keeping individual power for 11 subjects selected 81 channels selected 6 time bins selected 4 frequency bins Warning: PACK can only be used from the MATLAB command line. > In fieldtrip\private\prepare_timefreq_data at 310 In fieldtrip\private\statistics_wrapper at 206 In freqstatistics at 132 In CMCWM2_std81_junk_with at 144 Obtaining the electrode configuration from the configuration. there are on average 83.0 neighbours per channel using "statistics_montecarlo" for the statistical testing using "statfun_indepsamplesT" for the single-sample statistics constructing randomized design total number of measurements = 22 total number of variables = 2 number of independent variables = 1 number of unit variables = 1 number of within-cell variables = 0 number of control variables = 0 using a permutation resampling approach repeated measurement in variable 1 over 22 levels number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 computing a parmetric threshold for clustering estimated time per randomization is 0 seconds found 2 positive clusters in observed data found 1 negative clusters in observed data using a cluster-based method for multiple comparison correction the returned probabilities and the thresholded mask are corrected for multiple comparisons ??? Assignment has more non-singleton rhs dimensions than non-singleton subscripts Error in ==> clusterplot at 91 sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); Error in ==> CMCWM2_std81_junk_with at 153 clusterplot (cfg, stat); ============================================ Should our cfg.neighbourdist have a higher number if we are using a Standard-81 layout? We've tried a few different variations with that number and still ended up with the same error. Cheers, Charles On Mon, 8 Jun 2009 17:00:22 +0200, Eric Maris wrote: >Hi Charles, > >83.0 neighbours per channel does not make sense. For EEG-channels this >number typically is 4 and for MEG-channels it is typically 6. Have a look at >the neighbourhood geometry structure that is constructed by freqstatistics. >I guess this structure is far too wide (a channel is considered a neighbour >of almost every other channel). > > >Best, > >Eric > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Mon Jun 8 22:21:12 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Mon, 8 Jun 2009 22:21:12 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: Message-ID: Hi Charles, > Yes that did seem to a further unusually high number, especially since > they're all standard-81! Let me give you an idea of where our code is > presently at: > > ============================================ > > cfg = []; > cfg.neighbourdist = 4; > cfg.elec = elec; Have a look in the electrode configuration "elec" and I suspect that you will see that cfg.neighbourdist=4 is inappropriate for the dimension in which the electrodes positions are given. Best, Eric > cfg.statistic = 'indepsamplesT'; > cfg.minnbchan = 0; > cfg.clusteralpha = 0.05; > cfg.alpha = 0.05; > cfg.clustertail = 0; > cfg.numrandomization = 5000; > > cfg.latency = [250 500]; > cfg.frequency = [4 7]; > cfg.avgovertime = 'no'; > cfg.avgoverfreq = 'no'; > cfg.avgoverchan = 'no'; > > cfg.correctm = 'cluster'; > cfg.method = 'montecarlo'; > cfg.feedback = 'gui'; > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > 21 22; % subject number > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 > 2]; % condition number > > cfg.uvar = 1; % "subject" is unit of > observation > cfg.ivar = 2; % "condition" is the > independent variable > stat = freqstatistics(cfg, malefeat_all, femloc_all); > > %cfg = []; > %[freq_maleloc] = freqdescriptives(cfg, maleloc_all); > %[freq_femloc] = freqdescriptives(cfg, femloc_all); > > cfg = []; > cfg.zlim = [-6 6]; > cfg.alpha = 0.05; > clusterplot (cfg, stat); <----still failing here > > ============================================ > > Reading power on 81 channels > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > selected 81 channels > selected 6 time bins > selected 4 frequency bins > Warning: PACK can only be used from the MATLAB command line. > > In fieldtrip\private\prepare_timefreq_data at 310 > In fieldtrip\private\statistics_wrapper at 206 > In freqstatistics at 132 > In CMCWM2_std81_junk_with at 144 > Obtaining the electrode configuration from the configuration. > there are on average 83.0 neighbours per channel > using "statistics_montecarlo" for the statistical testing > using "statfun_indepsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 22 levels > number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 1 > 1 1 1 1 1 1 1 1 > computing a parmetric threshold for clustering > estimated time per randomization is 0 seconds > found 2 positive clusters in observed data > found 1 negative clusters in observed data > using a cluster-based method for multiple comparison correction > the returned probabilities and the thresholded mask are corrected for > multiple comparisons > ??? Assignment has more non-singleton rhs dimensions than non-singleton > subscripts > > Error in ==> clusterplot at 91 > sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); > > Error in ==> CMCWM2_std81_junk_with at 153 > clusterplot (cfg, stat); > > ============================================ > > Should our cfg.neighbourdist have a higher number if we are using a > Standard-81 layout? We've tried a few different variations with that number > and still ended up with the same error. > > Cheers, > > Charles > > On Mon, 8 Jun 2009 17:00:22 +0200, Eric Maris > wrote: > > >Hi Charles, > > > >83.0 neighbours per channel does not make sense. For EEG-channels this > >number typically is 4 and for MEG-channels it is typically 6. Have a look at > >the neighbourhood geometry structure that is constructed by freqstatistics. > >I guess this structure is far too wide (a channel is considered a neighbour > >of almost every other channel). > > > > > >Best, > > > >Eric > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From saskia.haegens at DONDERS.RU.NL Mon Jun 8 22:31:18 2009 From: saskia.haegens at DONDERS.RU.NL (Saskia Haegens) Date: Mon, 8 Jun 2009 22:31:18 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? In-Reply-To: Message-ID: Hi Charles, The reason that clusterplot gives an error is because you do not average over frequencies (which is required for clusterplot). So you should either set cfg.avgoverfreq='yes' when running freqstatistics, or plot the results in another way (e.g. use singleplot or feed only one freqbin at a time into clusterplot). Hope this helps! Best, Saskia > -----Original Message----- > From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On > Behalf Of Charles Cook > Sent: 08 June 2009 21:52 > To: FIELDTRIP at NIC.SURFNET.NL > Subject: Re: [FIELDTRIP] Freqstatistics Yields Zero Significant Clusters? > > Hi Eric, > > Yes that did seem to a further unusually high number, especially since > they're all standard-81! Let me give you an idea of where our code is > presently at: > > ============================================ > > cfg = []; > cfg.neighbourdist = 4; > cfg.elec = elec; > cfg.statistic = 'indepsamplesT'; > cfg.minnbchan = 0; > cfg.clusteralpha = 0.05; > cfg.alpha = 0.05; > cfg.clustertail = 0; > cfg.numrandomization = 5000; > > cfg.latency = [250 500]; > cfg.frequency = [4 7]; > cfg.avgovertime = 'no'; > cfg.avgoverfreq = 'no'; > cfg.avgoverchan = 'no'; > > cfg.correctm = 'cluster'; > cfg.method = 'montecarlo'; > cfg.feedback = 'gui'; > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > 21 22; % subject number > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 > 2 > 2]; % condition number > > cfg.uvar = 1; % "subject" is unit of > observation > cfg.ivar = 2; % "condition" is the > independent variable > stat = freqstatistics(cfg, malefeat_all, femloc_all); > > %cfg = []; > %[freq_maleloc] = freqdescriptives(cfg, maleloc_all); > %[freq_femloc] = freqdescriptives(cfg, femloc_all); > > cfg = []; > cfg.zlim = [-6 6]; > cfg.alpha = 0.05; > clusterplot (cfg, stat); <----still failing here > > ============================================ > > Reading power on 81 channels > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > selected 81 channels > selected 6 time bins > selected 4 frequency bins > Warning: PACK can only be used from the MATLAB command line. > > In fieldtrip\private\prepare_timefreq_data at 310 > In fieldtrip\private\statistics_wrapper at 206 > In freqstatistics at 132 > In CMCWM2_std81_junk_with at 144 > Obtaining the electrode configuration from the configuration. > there are on average 83.0 neighbours per channel > using "statistics_montecarlo" for the statistical testing > using "statfun_indepsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 22 levels > number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 > 1 > 1 1 1 1 1 1 1 1 > computing a parmetric threshold for clustering > estimated time per randomization is 0 seconds > found 2 positive clusters in observed data > found 1 negative clusters in observed data > using a cluster-based method for multiple comparison correction > the returned probabilities and the thresholded mask are corrected for > multiple comparisons > ??? Assignment has more non-singleton rhs dimensions than non-singleton > subscripts > > Error in ==> clusterplot at 91 > sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); > > Error in ==> CMCWM2_std81_junk_with at 153 > clusterplot (cfg, stat); > > ============================================ > > Should our cfg.neighbourdist have a higher number if we are using a > Standard-81 layout? We've tried a few different variations with that > number > and still ended up with the same error. > > Cheers, > > Charles > > On Mon, 8 Jun 2009 17:00:22 +0200, Eric Maris > wrote: > > >Hi Charles, > > > >83.0 neighbours per channel does not make sense. For EEG-channels this > >number typically is 4 and for MEG-channels it is typically 6. Have a look > at > >the neighbourhood geometry structure that is constructed by > freqstatistics. > >I guess this structure is far too wide (a channel is considered a > neighbour > >of almost every other channel). > > > > > >Best, > > > >Eric > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the > FieldTrip toolbox, to share experiences and to discuss new ideas for MEG > and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From wibral at BIC.UNI-FRANKFURT.DE Tue Jun 9 15:05:11 2009 From: wibral at BIC.UNI-FRANKFURT.DE (Michael Wibral) Date: Tue, 9 Jun 2009 15:05:11 +0200 Subject: Freqstatistics Yields Zero Significant Clusters? Message-ID: Hi Charles, I agree with Eric. You might try to define a much smaller neighbour distance. The reason for this may be that BESA sometimes uses [cm] and sometimes [m] - so if all your neighbour positions are given im [m] aand you specify the maximum distance in [cm], the all channels are neighbours of all other channels. I remeber that some of the fieldtrip scripts in the wiki multiplied the .pnt field by 10 or 100 after import from BESA and before proceeding. A note on the side: beware of a "ms" and "s" problem as well. That means check all .time fields in your fieldtrip structures for plausibility. Hope this helps, Michael > -----Ursprüngliche Nachricht----- > Von: "Eric Maris" > Gesendet: 08.06.09 17:03:03 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: Re: [FIELDTRIP] Freqstatistics Yields Zero Significant Clusters? > Hi Charles, > > > > We have modified the code based on your suggestions and I think we're very > > close now. This is our most recent output: > > > > ------------------------------------- > > reading power on 81 channels > > not computing grand average, but keeping individual power for 11 subjects > > not computing grand average, but keeping individual power for 11 subjects > > selected 81 channels > > selected 6 time bins > > selected 4 frequency bins > > Warning: PACK can only be used from the MATLAB command line. > > > In fieldtrip\private\prepare_timefreq_data at 310 > > In fieldtrip\private\statistics_wrapper at 206 > > In freqstatistics at 132 > > In CMCWM2_std81_junk_with at 144 > > Obtaining the electrode configuration from the configuration. > > there are on average 83.0 neighbours per channel > > 83.0 neighbours per channel does not make sense. For EEG-channels this > number typically is 4 and for MEG-channels it is typically 6. Have a look at > the neighbourhood geometry structure that is constructed by freqstatistics. > I guess this structure is far too wide (a channel is considered a neighbour > of almost every other channel). > > > Best, > > Eric > > > > > > > > > using "statistics_montecarlo" for the statistical testing > > using "statfun_indepsamplesT" for the single-sample statistics > > constructing randomized design > > total number of measurements = 22 > > total number of variables = 2 > > number of independent variables = 1 > > number of unit variables = 1 > > number of within-cell variables = 0 > > number of control variables = 0 > > using a permutation resampling approach > > repeated measurement in variable 1 over 22 levels > > number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 > 1 > > 1 1 1 1 1 1 1 1 > > computing a parmetric threshold for clustering > > estimated time per randomization is 0 seconds > > found 2 positive clusters in observed data > > found 1 negative clusters in observed data > > using a cluster-based method for multiple comparison correction > > the returned probabilities and the thresholded mask are corrected for > > multiple comparisons > > ??? Assignment has more non-singleton rhs dimensions than non-singleton > > subscripts > > > > Error in ==> clusterplot at 91 > > sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos)); > > > > Error in ==> CMCWM2_std81_junk_with at 153 > > clusterplot (cfg, stat); > > > > ----------------- > > > > We do keep running into this error with clusterplot. Which we have as > follows: > > > > cfg = []; > > cfg.zlim = [-6 6]; > > cfg.alpha = 0.05; > > clusterplot(cfg, stat); > > > > It crashes on the last line. Does anyone have any ideas where we might be > > going wrong here? > > > > Cheers, > > > > Charles > > > > On Sat, 6 Jun 2009 09:04:43 +0200, Eric Maris > > wrote: > > > > >Hi Charles, > > > > > > > > > > > >Although I'm not 100 percent sure that this is the cause of your > problems, > > >the way you specify the unit of observation is definitely wrong. You have > 22 > > >units of observations (i.c., subjects) so the first row of cfg.design > must > > >be [1 2 ... 22; ... ] > > > > > >Also, did you check whether cfg.design is a 2-by-22 array? In the lines > > >below, a semicolon seems to be missing. > > > > > >> cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11 > % > > >> subject number is 1-11 males and 1-11 females > > >> 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 > 2]; % > > >> condition number with 1 being males and 2 being females > > >> > > >> cfg.uvar = 1; % "subject" is unit of > > >> observation > > >> cfg.ivar = 2; % "condition" is the > > >> independent variable > > > > > > > > >Good luck, > > > > > > > > >dr. Eric Maris > > >Donders Institute for Brain, Cognition and Behavior > > >Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging > > >Radboud University > > >P.O. Box 9104 > > >6500 HE Nijmegen > > >The Netherlands > > >T:+31 24 3612651 > > >F:+31 24 3616066 > > >E: e.maris at donders.ru.nl > > > > > >MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > > > > > > > ---------------------------------- > > The aim of this list is to facilitate the discussion between users of the > FieldTrip > > toolbox, to share experiences and to discuss new ideas for MEG and EEG > analysis. > > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > > http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 344 bytes Desc: not available URL: From wibral at BIC.UNI-FRANKFURT.DE Tue Jun 9 15:19:04 2009 From: wibral at BIC.UNI-FRANKFURT.DE (Michael Wibral) Date: Tue, 9 Jun 2009 15:19:04 +0200 Subject: Open Positions at the Brain Imaging Center Frankfurt Message-ID: Dear Fieldtrip list users, Dr. Peter Uhlhaas from the Max Planck Institute for Brain Research, Dept. Neurophysiology asked me to post these positions related to MEG research in patients with Schizophrenia and Autism spectrum disorder. Michael Wibral --------------------------------------------------- (1) *Postdoctoral Position in Brain Imaging* A postdoctoral position in brain imaging is available at the Max Planck Institute for Brain Research, Department of Neurophysiology (Director: Professor W. Singer) in the group of Dr. Peter J. Uhlhaas. The successful applicant will work on projects examining neural oscillations in schizophrenia with magnetoencephalography (MEG) with advanced signal-processing analyses (Beamforming, Transfer Entropy). Several data sets from unmedicated first-episode and chronic patients with schizophrenia as well autism spectrum disorders are already available. There is also opportunity to design novel experiments. The position is in collaboration with Dr. Michael Wibral (Head: MEG-Unit, Brain Imaging Center Frankfurt). The ideal candidate should have a PhD in neuroimaging and expertise with a neuroimaging technique (EEG, MEG, fMRI/MRI). Excellent research opportunities are available at the nearby Brain Imaging Center (2 x 3T MRI Scanners, MRI-compatible EEG and TMS). Applications from a physics or engineering background are welcome as well. Expertise in Matlab or C++ programming is desirable. The position will run for two years. The successful applicant will receive a stipend, depending on qualification and years of working experience. The position will start on the 1st of January 2010. Informal inquiries can be directed to Peter Uhlhaas (uhlhaas at mpih-frankfurt.mpg.de). To apply, please send curriculum vitae, letter of interest, names and contact information of two references to: Peter Uhlhaas Max Planck Institute for Brain Research Department of Neurophysiology Deutschordenstr. 46 60528 Frankfurt am Main GERMANY ----------------------------------------------- (2) *Doctoral Position in Brain Imaging* A doctoral position in brain imaging is available at the Max Planck Institute for Brain Research, Department of Neurophysiology (Director: Professor W. Singer) in the group of Dr. Peter J. Uhlhaas. The successful applicant will work on projects examining neural oscillations in schizophrenia with magnetoencephalography (MEG). The position is in collaboration with Dr. Michael Wibral (Head: MEG-Unit, Brain Imaging Center Frankfurt). The successful candidate should have a strong background in neuroscience and psychology. Applications from a physics or engineering background are welcome as well. Expertise in Matlab or C++ programming is desirable. The position will start on the 1st of November 2009 and will be paid according to the TVöD E13 (50 %) salary sale. Informal inquiries can be directed to Peter Uhlhaas (uhlhaas at mpih-frankfurt.mpg.de). To apply, please send curriculum vitae, letter of interest, names and contact information of two references to: Peter Uhlhaas Max Planck Institute for Brain Research Department of Neurophysiology Deutschordenstr. 46 60528 Frankfurt am Main GERMANY ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 344 bytes Desc: not available URL: From ole.jensen at DONDERS.RU.NL Wed Jun 10 22:17:29 2009 From: ole.jensen at DONDERS.RU.NL (Ole Jensen) Date: Wed, 10 Jun 2009 22:17:29 +0200 Subject: MEG lunch at HBM: Sunday June 21 (not Friday!) Message-ID: Dear MEG researcher, We would like to invite you to a lunch meeting at HBM2009/San Francisco: Sunday June 31, 12:30 - 1:45 pm. Yerba Buena Ballroom, Salons 1-6 (Lower B2 Level) We hope to explore ways to strengthen the MEG community. We find it particularly important given that the increase of MEG groups warrants more initiatives for improving communication. Points to discuss: - Practical initiatives for strengthening communication between MEG groups * mailing lists/websites * satellite meetings in connection with conferences (e.g. HBM, FENS,...) - Improve education on MEG analysis (summer schools, boot camps, student exchanges,..) - How to promote an increase of the scientific quality/standard of MEG research. *Please forward this message to other MEG researchers (we do not have a complete list).* Best regards, Ole Jensen, Joachim Gross and Srikantan Nagarajan P.S. Please bring your own lunch -- Ole Jensen Principal Investigator Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Office : +31 24 36 10884 MEG lab : +31 24 36 10988 Fax : +31 24 36 10989 e-mail : ole.jensen at donders.ru.nl URL : http://ojensen.ruhosting.nl/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From Douglas.Rose at CCHMC.ORG Thu Jun 11 18:05:05 2009 From: Douglas.Rose at CCHMC.ORG (Douglas Rose) Date: Thu, 11 Jun 2009 12:05:05 -0400 Subject: MEG lunch at HBM: Sunday June 21 (not Friday!) In-Reply-To: <4A3014D9.7010709@donders.ru.nl> Message-ID: Dear Ole, Sri, and Joachim, So sorry will not be at HBM this year. This sounds very good. Please keep me advised of how the meeting goes and how I may help. Best regards, Doug **************************************************** Douglas F. Rose, M.D. Medical Director, CCHMC MEG Center Professor of Pediatrics and Neurology Cincinnati Children's Hospital Medical Center 3333 Burnet Ave, ML #11006 Cincinnati, OH 45229, USA Phone 513-636-4222 Fax 513-636-3980 Email douglas.rose at cchmc.org **************************************************** >>> Ole Jensen 6/10/2009 4:17 PM >>> Dear MEG researcher, We would like to invite you to a lunch meeting at HBM2009/San Francisco: Sunday June 31, 12:30 - 1:45 pm. Yerba Buena Ballroom, Salons 1-6 (Lower B2 Level) We hope to explore ways to strengthen the MEG community. We find it particularly important given that the increase of MEG groups warrants more initiatives for improving communication. Points to discuss: - Practical initiatives for strengthening communication between MEG groups * mailing lists/websites * satellite meetings in connection with conferences (e.g. HBM, FENS,...) - Improve education on MEG analysis (summer schools, boot camps, student exchanges,..) - How to promote an increase of the scientific quality/standard of MEG research. *Please forward this message to other MEG researchers (we do not have a complete list).* Best regards, Ole Jensen, Joachim Gross and Srikantan Nagarajan P.S. Please bring your own lunch -- Ole Jensen Principal Investigator Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Office : +31 24 36 10884 MEG lab : +31 24 36 10988 Fax : +31 24 36 10989 e-mail : ole.jensen at donders.ru.nl URL : http://ojensen.ruhosting.nl/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From santoro.rob at GMAIL.COM Fri Jun 12 12:51:50 2009 From: santoro.rob at GMAIL.COM (Roberta Santoro) Date: Fri, 12 Jun 2009 12:51:50 +0200 Subject: LCMV- Removemean Message-ID: Dear all, I have a question about lcmv beamforming in time domain. I saw in the example "Analysing sources of evoked fields using an LCMV-beamformer" that you don't remove the mean before calculating the covariance matrix and I would like to know why. I tried to estimate the sources both removing and don't removing the mean value in the latency window of interest and the results obtained by removing the mean seem to be less noisy. Thanks, Roberta ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From gsudre at POBOX.COM Fri Jun 12 20:23:07 2009 From: gsudre at POBOX.COM (Gustavo Sudre) Date: Fri, 12 Jun 2009 14:23:07 -0400 Subject: loading BEMs and segmented images Message-ID: Hi, I was wondering if it's possible to load into fieldtrip BEMs computed with external programs (saved as .fif files). Or, is it possible to load MRI images that have been previously segmented? Thanks, Gus ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From megjim1 at GMAIL.COM Fri Jun 12 22:35:56 2009 From: megjim1 at GMAIL.COM (Jim Li) Date: Fri, 12 Jun 2009 22:35:56 +0200 Subject: Can I view the wavelets as well? Message-ID: Dear FTers, I wonder if there's a way to directly view the wavelets which are used for freqanalysis_wltconvol? If so, could you tell me? I'm especially interested in viewing the wavelets designed for the low frequency components (say 3-6Hz) in the theta/delta range when the wavelet temporal resolution is lousy and my inter-trigger-interval is not too long. BTW, is it I true that "cfg.width" should never stay below 5? If so, why? Thanks a lot, Jim ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From sabine.frank at MED.UNI-TUEBINGEN.DE Mon Jun 15 14:03:42 2009 From: sabine.frank at MED.UNI-TUEBINGEN.DE (Sabine Frank) Date: Mon, 15 Jun 2009 14:03:42 +0200 Subject: Autumn School Tuebingen 16.-18. September 2009 Message-ID: "Wiring the Brain: Anatomical and Functional Connectivity" Autumn School, University of Tübingen: 2009/09/16-2009/09/18 The “Autumn School 2009: Wiring the Brain: Anatomical and Functional Connectivity” is organized by the MEG-Center Tübingen and supported by the Graduate School of Neural & Behavioural Sciences / International Max Planck Research School Tübingen, the Werner Reichardt Center for Integrative Neuroscience and the Neurowissenschaftliche Gesellschaft. This year's focus is on connectivity assessed with different neuroimaging methods (MEG, fetal MEG, fMRI, TMS). One crucial point is the comparison and combination of these approaches to increase the mutual benefit. Additionally, the course offers the opportunity to gain experience in hands-on sessions using state-of-the-art equipment as well as educational sessions related to the usage of software packages. All speakers and instructors are leading specialists in their field. The participants will have the opportunity to present their own work in a poster session and discuss their work with the experts. The school is open for master and PhD students and Postdocs working in the field of Neuroscience. Please find the detailed program, application form and further information on our homepage. http://www.mp.uni-tuebingen.de/mp/index.php?id=281 We are looking forward to seeing you in Tübingen. The organizers ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From ole.jensen at DONDERS.RU.NL Tue Jun 16 15:41:32 2009 From: ole.jensen at DONDERS.RU.NL (Ole Jensen) Date: Tue, 16 Jun 2009 15:41:32 +0200 Subject: MEG lunch at HBM: Sunday June 21 Message-ID: There was a mistake in the previous mail (its June 21, not 31). Excuses... ------------------ Dear MEG researcher, We would like to invite you to a lunch meeting at HBM2009/San Francisco: * Sunday June 21*, 12:30 - 1:45 pm. Yerba Buena Ballroom, Salons 1-6 (Lower B2 Level) We hope to explore ways to strengthen the MEG community. We find it particularly important given that the increase of MEG groups warrants more initiatives for improving communication. Points to discuss: - Practical initiatives for strengthening communication between MEG groups * mailing lists/websites * satellite meetings in connection with conferences (e.g. HBM, FENS,...) - Improve education on MEG analysis (summer schools, boot camps, student exchanges,.. ) - How to promote an increase of the scientific quality/standard of MEG research. *Please forward this message to other MEG researchers (we do not have a complete list).* Best regards, Ole Jensen, Joachim Gross and Srikantan Nagarajan -- Ole Jensen Principal Investigator Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Office : +31 24 36 10884 MEG lab : +31 24 36 10988 Fax : +31 24 36 10989 e-mail : ole.jensen at donders.ru.nl URL : http://ojensen.ruhosting.nl/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- An HTML attachment was scrubbed... URL: From charles.cook at ULETH.CA Tue Jun 16 22:44:44 2009 From: charles.cook at ULETH.CA (Charles Cook) Date: Tue, 16 Jun 2009 22:44:44 +0200 Subject: Update: Freqstatistics Now Yields Significant Clusters Message-ID: Hi all, I just wanted to post a follow-up to my previous posted problem of being unable to obtain significant clusters using freqstats. I've included my code for what I believe (and hope...) is our success at obtaining clusters in our analysis, and acknowledge the help we received from the FieldTrip board users, in particular Michael and Eric whose suggestions were immensely helpful. Thanks again! Here's our code below. Our study has both between (sex) and within group components (task1 vs. task2). ===================================================================== % this is the list of BESA datafiles in the Female Feature condition filename_femfeat = { . . . }; nsubj = length(filename_femfeat); for i=1:nsubj femfeat{i} = besa2fieldtrip(filename_femfeat{i}); end % this is the list of BESA datafiles in the Female Location condition filename_femloc = { . . . }; for i=11 nsubj = length(filename_femloc); end for i=1:nsubj femloc{i} = besa2fieldtrip(filename_femloc{i}); end % this is the list of BESA datafiles in the Male Feature condition filename_malefeat = { . . . }; for i=11 nsubj = length(filename_malefeat); end % this is the list of BESA datafiles in the Male Location condition filename_maleloc = { . . . }; for i=11 nsubj = length(filename_maleloc); end %} % collect all single subject data in a convenient cell-array for i=1:nsubj femfeat{i} = besa2fieldtrip(filename_femfeat{i}); femloc{i} = besa2fieldtrip(filename_femloc{i}); malefeat{i} = besa2fieldtrip(filename_malefeat{i}); maleloc{i} = besa2fieldtrip(filename_maleloc{i}); end %Read in the electrode locations for the Std81 montage cfg = []; elec = read_fcdc_elec('EGI-BESA_Standard_81_prime.sfp'); elec.pnt = 1000*elec.pnt; % recompute the average, except do _not_ average but keepindividual % this collects all identical time/frequency/channel samples over all % subjects into a single data structure cfg = []; cfg.keepindividual = 'yes'; maleloc_all = freqgrandaverage(cfg, maleloc{:}); femloc_all = freqgrandaverage(cfg, femloc{:}); malefeat_all = freqgrandaverage(cfg, malefeat{:}); femfeat_all = freqgrandaverage(cfg, femfeat{:}); % perform the statistical test using randomization and a clustering approach % using the NEW freqstatistics function cfg = []; cfg.neighbourdist = 45; cfg.elec = elec; cfg.statistic = 'indepsamplesT'; cfg.minnbchan = 0; cfg.clusteralpha = 0.05; cfg.alpha = 0.05; cfg.clustertail = 0; cfg.numrandomization = 5000; cfg.latency = [0 1000]; cfg.frequency = [4 7]; cfg.avgovertime = 'no'; cfg.avgoverfreq = 'yes'; cfg.avgoverchan = 'no'; cfg.correctm = 'cluster'; cfg.method = 'montecarlo'; cfg.feedback = 'gui'; cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22; % subject number 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % condition number %cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11; % subject number %1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % condition number cfg.uvar = 1; % "subject" is unit of observation cfg.ivar = 2; % "condition" is the independent variable stat = freqstatistics(cfg, maleloc_all, femloc_all); %stat = freqstatistics(cfg, femfeat_all, malefeat_all); %stat = freqstatistics(cfg, maleloc_all, malefeat_all); %stat = freqstatistics(cfg, femfeat_all, femloc_all); cfg = []; cfg.elec = elec; cfg.rotate = 0; %cfg.zlim = [-6 6]; cfg.alpha = 0.05; cfg.label = stat.label; cfg.electrodes = 'labels'; cfg.showxlim = 'yes'; cfg.showzlim = 'yes'; cfg.showylim = 'yes'; clusterplot (cfg, stat); ===================================================================== Our results indicated the following: . . . reading time-frequency representation using BESA toolbox reading power on 81 channels not computing grand average, but keeping individual power for 11 subjects not computing grand average, but keeping individual power for 11 subjects not computing grand average, but keeping individual power for 11 subjects not computing grand average, but keeping individual power for 11 subjects selected 81 channels selected 21 time bins averaging over 4 frequency bins Warning: PACK can only be used from the MATLAB command line. > In fieldtrip\private\prepare_timefreq_data at 310 In fieldtrip\private\statistics_wrapper at 206 In freqstatistics at 132 In CMCWM2_std81 at 139 Obtaining the electrode configuration from the configuration. there are on average 4.7 neighbours per channel using "statistics_montecarlo" for the statistical testing using "statfun_indepsamplesT" for the single-sample statistics constructing randomized design total number of measurements = 22 total number of variables = 2 number of independent variables = 1 number of unit variables = 1 number of within-cell variables = 0 number of control variables = 0 using a permutation resampling approach repeated measurement in variable 1 over 22 levels number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 computing a parmetric threshold for clustering estimated time per randomization is 0 seconds found 4 positive clusters in observed data found 7 negative clusters in observed data using a cluster-based method for multiple comparison correction the returned probabilities and the thresholded mask are corrected for multiple comparisons There are 2 clusters smaller than alpha (0.05) Positive cluster: 1, pvalue: 0 (*), t = 100 to 450 Negative cluster: 1, pvalue: 0 (*), t = 0 to 100 creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec creating layout from cfg.elec ===================================================================== I've also attached a jpg of the above result and our .sfp file if anyone is interested in further information. Thanks once again for the help! Cheers, Charles Cook ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: 4-7Hz.jpg Type: image/jpeg Size: 193169 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: EGI-BESA_Standard_81_prime.sfp Type: application/octet-stream Size: 3513 bytes Desc: not available URL: From wibral at BIC.UNI-FRANKFURT.DE Wed Jun 17 09:24:41 2009 From: wibral at BIC.UNI-FRANKFURT.DE (Michael Wibral) Date: Wed, 17 Jun 2009 09:24:41 +0200 Subject: Update: Freqstatistics Now Yields Sign ificant Clusters Message-ID: Hi Charles, the plots look OK to me. Could you let us know what finally made your analysis work (if there was a single most important thing) - that would be most helpful. Thanks, Michael > -----Ursprüngliche Nachricht----- > Von: "Charles Cook" > Gesendet: 16.06.09 22:46:18 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: [FIELDTRIP] Update: Freqstatistics Now Yields Significant Clusters > Hi all, > > I just wanted to post a follow-up to my previous posted problem of being > unable to obtain significant clusters using freqstats. I've included my code > for what I believe (and hope...) is our success at obtaining clusters in our > analysis, and acknowledge the help we received from the FieldTrip board > users, in particular Michael and Eric whose suggestions were immensely > helpful. Thanks again! > > Here's our code below. Our study has both between (sex) and within group > components (task1 vs. task2). > > ===================================================================== > > % this is the list of BESA datafiles in the Female Feature condition > filename_femfeat = { > . > . > . > }; > > nsubj = length(filename_femfeat); > > for i=1:nsubj > femfeat{i} = besa2fieldtrip(filename_femfeat{i}); > end > > % this is the list of BESA datafiles in the Female Location condition > filename_femloc = { > . > . > . > }; > > for i=11 > nsubj = length(filename_femloc); > end > > for i=1:nsubj > femloc{i} = besa2fieldtrip(filename_femloc{i}); > end > > % this is the list of BESA datafiles in the Male Feature condition > filename_malefeat = { > . > . > . > }; > for i=11 > nsubj = length(filename_malefeat); > end > > > % this is the list of BESA datafiles in the Male Location condition > filename_maleloc = { > . > . > . > }; > for i=11 > nsubj = length(filename_maleloc); > end > %} > > % collect all single subject data in a convenient cell-array > for i=1:nsubj > femfeat{i} = besa2fieldtrip(filename_femfeat{i}); > femloc{i} = besa2fieldtrip(filename_femloc{i}); > malefeat{i} = besa2fieldtrip(filename_malefeat{i}); > maleloc{i} = besa2fieldtrip(filename_maleloc{i}); > end > > > %Read in the electrode locations for the Std81 montage > cfg = []; > elec = read_fcdc_elec('EGI-BESA_Standard_81_prime.sfp'); > elec.pnt = 1000*elec.pnt; > > % recompute the average, except do _not_ average but keepindividual > % this collects all identical time/frequency/channel samples over all > % subjects into a single data structure > cfg = []; > cfg.keepindividual = 'yes'; > maleloc_all = freqgrandaverage(cfg, maleloc{:}); > femloc_all = freqgrandaverage(cfg, femloc{:}); > malefeat_all = freqgrandaverage(cfg, malefeat{:}); > femfeat_all = freqgrandaverage(cfg, femfeat{:}); > > > % perform the statistical test using randomization and a clustering approach > % using the NEW freqstatistics function > cfg = []; > cfg.neighbourdist = 45; > cfg.elec = elec; > cfg.statistic = 'indepsamplesT'; > cfg.minnbchan = 0; > cfg.clusteralpha = 0.05; > cfg.alpha = 0.05; > cfg.clustertail = 0; > cfg.numrandomization = 5000; > > cfg.latency = [0 1000]; > cfg.frequency = [4 7]; > cfg.avgovertime = 'no'; > cfg.avgoverfreq = 'yes'; > cfg.avgoverchan = 'no'; > > cfg.correctm = 'cluster'; > cfg.method = 'montecarlo'; > cfg.feedback = 'gui'; > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > 21 22; % subject number > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 > 2]; % condition number > > %cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 > 10 11; % subject number > %1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 > 2 2]; % condition number > > > cfg.uvar = 1; % "subject" is unit of > observation > cfg.ivar = 2; % "condition" is the > independent variable > stat = freqstatistics(cfg, maleloc_all, femloc_all); > %stat = freqstatistics(cfg, femfeat_all, malefeat_all); > %stat = freqstatistics(cfg, maleloc_all, malefeat_all); > %stat = freqstatistics(cfg, femfeat_all, femloc_all); > > cfg = []; > cfg.elec = elec; > cfg.rotate = 0; > %cfg.zlim = [-6 6]; > cfg.alpha = 0.05; > cfg.label = stat.label; > cfg.electrodes = 'labels'; > cfg.showxlim = 'yes'; > cfg.showzlim = 'yes'; > cfg.showylim = 'yes'; > clusterplot (cfg, stat); > ===================================================================== > > Our results indicated the following: > . > . > . > reading time-frequency representation using BESA toolbox > reading power on 81 channels > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > not computing grand average, but keeping individual power for 11 subjects > > selected 81 channels > selected 21 time bins > averaging over 4 frequency bins > > Warning: PACK can only be used from the MATLAB command line. > > In fieldtrip\private\prepare_timefreq_data at 310 > In fieldtrip\private\statistics_wrapper at 206 > In freqstatistics at 132 > In CMCWM2_std81 at 139 > > Obtaining the electrode configuration from the configuration. > there are on average 4.7 neighbours per channel > using "statistics_montecarlo" for the statistical testing > using "statfun_indepsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 22 levels > number of repeated measurements in each level is 1 1 1 1 1 1 1 1 1 1 1 1 1 1 > 1 1 1 1 1 1 1 1 > computing a parmetric threshold for clustering > estimated time per randomization is 0 seconds > found 4 positive clusters in observed data > found 7 negative clusters in observed data > using a cluster-based method for multiple comparison correction > the returned probabilities and the thresholded mask are corrected for > multiple comparisons > > There are 2 clusters smaller than alpha (0.05) > Positive cluster: 1, pvalue: 0 (*), t = 100 to 450 > Negative cluster: 1, pvalue: 0 (*), t = 0 to 100 > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > creating layout from cfg.elec > > ===================================================================== > > I've also attached a jpg of the above result and our .sfp file if anyone is > interested in further information. Thanks once again for the help! > > Cheers, > > Charles Cook > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 344 bytes Desc: not available URL: From spike377 at KOREA.COM Thu Jun 18 05:06:02 2009 From: spike377 at KOREA.COM (=?EUC-KR?B?aHlvdW5nZG9uZy5wYXJr?=) Date: Thu, 18 Jun 2009 12:06:02 +0900 Subject: questions about freqstatistics. Message-ID: An HTML attachment was scrubbed... URL: From ole.jensen at DONDERS.RU.NL Sun Jun 21 04:16:07 2009 From: ole.jensen at DONDERS.RU.NL (Ole Jensen) Date: Sun, 21 Jun 2009 04:16:07 +0200 Subject: HBM MEG lunch Sunday Message-ID: Dear all, The lunch for MEG researchers at HBM2009/San Francisco is tomorrow (Sunday) 12:30-1:45 Yerba Buena Ballroom, Salons 1-6. All the best, Ole -- Ole Jensen Principal Investigator Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Office : +31 24 36 10884 MEG lab : +31 24 36 10988 Fax : +31 24 36 10989 e-mail : ole.jensen at donders.ru.nl URL : http://ojensen.ruhosting.nl/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From gordon at CCS.FAU.EDU Mon Jun 22 20:13:35 2009 From: gordon at CCS.FAU.EDU (Reyna L. Gordon) Date: Mon, 22 Jun 2009 13:13:35 -0500 Subject: baseline and normalization question Message-ID: Dear FieldTrip list, I am a new user of the toolbox and am currently using it for Wavelet analysis of my EEG data, in preparation for the cluster randomization analysis. My question concerns normalization: my understanding of normalization is that it serves to either preserve or eliminate differences, depending on what parameters you choose. So if I want to put individual subjects on equal footing (de-emphasizing their individual differences in spectral power, in the case of this time frequency analysis), as well as different frequencies (to control for the fact that the different bands tend to have different power), I would normalize across subjects (by, for instance, using the change in power instead of their raw power) and do this separately for each frequency of interest. The freqbaseline function in the FieldTrip toolbox seems to calculate a separate baseline for each electrode channel (in addition to each frequency), whereas our thinking was that in order to find out where (i.e. in which channel) the power is more prominent, it would be preferable to obtain one baseline power value (for each frequency) from averaging together the power from all the channels. I have prepared some code to accomplish this on my FieldTrip data, but I am unsure about the theoretical implications of performing frequency baseline correction in this manner. Already I can see one downside of what I am trying in my data, which is that ambient noise in certain frequency bands shows up more on certain channels than others. Does anyone have insight on whether there are other disadvantages or violations of assumptions associated with "our" normalization method? Likewise, if I instead use the freqbaseline tool and normalize separately for each channel, [how] does the cluster randomization statistical analysis compensate for the (de-emphasized intrinsic) differences between channels? Thank you very much for any all input. Regards, Reyna ----------------------- Reyna L. Gordon PhD Candidate Center for Complex Systems & Brain Sciences Florida Atlantic University gordon at ccs.fau.edu ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From Ingmar.Schneider at BIO.UNI-GIESSEN.DE Tue Jun 23 12:35:45 2009 From: Ingmar.Schneider at BIO.UNI-GIESSEN.DE (Ingmar Schneider) Date: Tue, 23 Jun 2009 12:35:45 +0200 Subject: Freqstatistics actvsblT vs. depsamplesT Message-ID: Dear fieldtrip community, I am currently working on an activation vs. baseline comparison script (attached below) using the 'freqstatistics' function provided by fieldtrip. According to the instructions given in the fieldtrip tutorial, I used the 'actvsblT'-statfun for the comparison of 2s long data segments over a frequency range from 6Hz to 100Hz. However, this turned out to be almost impossible due to huge RAM requirements and frequently led to an 'Out of memory-error' even on a machine with 32GB of RAM. In order to make it work, I had to narrow the frequency range and number of randomizations. When I used the 'depsamplesT'-statfun for the comparison instead of 'actvsblT', a comparison across the whole frequency-range was possible requiring much less RAM (~2GB). The resulting statistics, however, slightly varied from those obtained using the 'actvsblT'-statfun (Topoplots attached); the localisation seems to be the same, but the t-values are a little lower. As far as I could find out using the documentation both statfuns calculate dependent samples T-statistics. Is there an essential difference between them causing the differences in the statistics? With best regards, Ingmar % Preparation of the statistical design nsubjects = size(TFact, 2); statdesign = zeros(2,2*nsubjects); statdesign(1,1:nsubjects) = 1; statdesign(1,nsubjects+1:2*nsubjects) = 2; statdesign(2,1:nsubjects) = [1:nsubjects]; statdesign(2,nsubjects+1:2*nsubjects) = [1:nsubjects]; % Realigning time TFblavg.time = TFactavg.time; % Freqstatistics cfg = []; cfg.frequency = [9 11]; cfg.channel = {'MEG', '-MLP12', '-MRC14', '-MLT41', '-MRC25', '-MRP56', '-MRT21', '-MLO21'}; cfg.latency = [0.5 2.5]; cfg.parameter = 'powspctrm'; cfg.method = 'montecarlo'; cfg.statistic = 'depsamplesT' / 'actvsblT' % respectively cfg.correctm = 'fdr'; cfg.alpha = 0.05; cfg.numrandomization = 1500; cfg.grad = grad; cfg.design = statdesign; cfg.uvar = 2; cfg.ivar = 1; freqstatACTvsBL = freqstatistics(cfg, TFactavg, TFblavg); -- Ingmar Schneider Max-Planck-Institut für Hirnforschung Deutschordenstraße 46 D-60528 Frankfurt/Main Tel.: 069/6301-83221 Fax: 069/96769-327 Mail1: schneider at mpih-frankfurt.mpg.de Mail2: ingmar.schneider at bio.uni-giessen.de ---------------------------------------------------------------- This message was sent using IMP, the Internet Messaging Program. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: FS_actvsblT_9-11Hz.jpg Type: image/jpeg Size: 145789 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: FS_depsamplesT_9-11Hz.jpg Type: image/jpeg Size: 144553 bytes Desc: not available URL: From marco.rotonda at GMAIL.COM Tue Jun 23 13:59:49 2009 From: marco.rotonda at GMAIL.COM (Marco Rotonda) Date: Tue, 23 Jun 2009 13:59:49 +0200 Subject: preprocessing without trigger... Message-ID: Hi there, it could be a stupid question but I don't know how to solve it. I wish to analyze some data files I have (continuous signal, without any trigger). These data sets are 3 minutes of neurofeedback training and there are no trigger. I just want take all the 3 minutes and take each second overlapping 500ms. The point is that there are no trigger so I don't know how to do the preprocessing (where I have to specify the trigger, isn't it?). Thanks in advance ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From t.b.dijkman at STUDENT.UTWENTE.NL Tue Jun 23 14:03:44 2009 From: t.b.dijkman at STUDENT.UTWENTE.NL (Thomas Dijkman) Date: Tue, 23 Jun 2009 14:03:44 +0200 Subject: preprocessing without trigger... Message-ID: Hi, Check out this page in the documentation: http://fieldtrip.fcdonders.nl/faq/reading_is_slow_can_i_write_my_raw_data_to_a_more_efficient_file_format This will probably help you further. Regards, Thomas -----Oorspronkelijk bericht----- Van: FieldTrip discussion list namens Marco Rotonda Verzonden: di 23-6-2009 13:59 Aan: FIELDTRIP at NIC.SURFNET.NL Onderwerp: [FIELDTRIP] preprocessing without trigger... Hi there, it could be a stupid question but I don't know how to solve it. I wish to analyze some data files I have (continuous signal, without any trigger). These data sets are 3 minutes of neurofeedback training and there are no trigger. I just want take all the 3 minutes and take each second overlapping 500ms. The point is that there are no trigger so I don't know how to do the preprocessing (where I have to specify the trigger, isn't it?). Thanks in advance ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From marco.rotonda at GMAIL.COM Tue Jun 23 14:20:37 2009 From: marco.rotonda at GMAIL.COM (Marco Rotonda) Date: Tue, 23 Jun 2009 14:20:37 +0200 Subject: preprocessing without trigger... In-Reply-To: Message-ID: thanks! it's very useful because I'm using bci2000 either! On 23/giu/09, at 14:03, Thomas Dijkman wrote: > Hi, > > Check out this page in the documentation: > > http://fieldtrip.fcdonders.nl/faq/reading_is_slow_can_i_write_my_raw_data_to_a_more_efficient_file_format > > This will probably help you further. > > Regards, > > Thomas > > > -----Oorspronkelijk bericht----- > Van: FieldTrip discussion list namens Marco Rotonda > Verzonden: di 23-6-2009 13:59 > Aan: FIELDTRIP at NIC.SURFNET.NL > Onderwerp: [FIELDTRIP] preprocessing without trigger... > > Hi there, > it could be a stupid question but I don't know how to solve it. > I wish to analyze some data files I have (continuous signal, without > any > trigger). > These data sets are 3 minutes of neurofeedback training and there > are no > trigger. > I just want take all the 3 minutes and take each second overlapping > 500ms. > The point is that there are no trigger so I don't know how to do the > preprocessing (where I have to specify the trigger, isn't it?). > > Thanks in advance > > ---------------------------------- > The aim of this list is to facilitate the discussion between users > of the FieldTrip toolbox, to share experiences and to discuss new > ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html > and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- > The aim of this list is to facilitate the discussion between users > of the FieldTrip toolbox, to share experiences and to discuss new > ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html > and http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From A.Stolk at EWI.UTWENTE.NL Tue Jun 23 16:09:06 2009 From: A.Stolk at EWI.UTWENTE.NL (A. Stolk) Date: Tue, 23 Jun 2009 16:09:06 +0200 Subject: Failed to create socket while using the Fieldtrip buffer Message-ID: Dear fieldtrip users, When using the realtime functions I have difficulties using the fieldtrip buffer continuously. For example, putting data in the buffer with rt_signalproxy seems to be a smooth and stable operation when performed alone. But when I subsequently try to access and plot that same data (e.g. with t_signalviewer) with another matlab session, matlab gives an error after some time. This 'some time' seems to be steady in length everytime I try; about 60 seconds on my laptop. ??? Error using ==> buffer ERROR: failed to create socket Error in ==> read_header at 939 orig = buffer('get_hdr', [], host, port); Error in ==> rt_signalviewer at 75 hdr = read_header(cfg.headerfile, 'headerformat', cfg.headerformat, 'cache', true); I have had this problem on multiple pc's now. All are using Windows XP 32-bit, Fieldtrip version 20090610. Can anyone help me resolve this issue? Friendly regards, Arjen ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From r.oostenveld at FCDONDERS.RU.NL Tue Jun 23 19:06:02 2009 From: r.oostenveld at FCDONDERS.RU.NL (Robert Oostenveld) Date: Tue, 23 Jun 2009 19:06:02 +0200 Subject: Failed to create socket while using the Fieldtrip buffer In-Reply-To: Message-ID: Hi Arjan, The same problem has recently been reported to me by Marco Rontado (see CC). Perhaps it would be usefull if you and Marco get in touch directly to exchange experiences, since sofar there are only few users of fieldtrip for realtime. I have done most of the testing of the buffer on Linux and OSX, and there I have not observed the problem. But given that the problem not always occurs, it might be that the problem is not only windows specific. I am not an expert on TCP/IP networking, but what I suspect is that simultaneous access to the buffer for writing (rt_signalproxy) and reading (rt_signalviewer) causes the problem. Simultaneous access should be possible, because each request is handled by a separate thread. But opening the connection and starting the thread still takes some time, and if during that time the other connection request comes in, the two might collide. At least that is what I currently think is the problem. The solution (not yet implemented) is to have the buffer access function detect that the read or write request has failed and then retry. The fastest (CPU-wise) is to implement the retry at the level of the c-code. Alternative, it would be possible to detect the problem at the level of the matlab code. Extending the matlab wrapper around the buffer request is simpler, but the first is cleaner. It requires a change to the open_connection function in realtime/buffer/src/util.c. At the moment I have limited time (due to traveling), so you could try to fix it yourself. The code around line 258 reads if (connect(s, (struct sockaddr *)&sa, sizeof sa)<0) { perror("open_connection"); return -2; } /* while (connect(s, (struct sockaddr *)&sa, sizeof sa) < 0) { perror("open_connection connect"); usleep(1000000); } */ If you comment out the first section and use the second code snippet instead, then probably it will be solved. Better would be to retry only a few times and not infinitely. Also the usleep could be changed to reduce the delay in the retry. I hope this helps. If you cannot get it to work, please let me know. I'll probably be able to fix it in the official fieldtrip release version somewhere next week. best regards, Robert ----- A. Stolk wrote: > Dear fieldtrip users, > > When using the realtime functions I have difficulties using the > fieldtrip buffer continuously. For example, putting data in the > buffer with rt_signalproxy seems to be a smooth and stable operation > when performed alone. > > But when I subsequently try to access and plot that same data (e.g. > with t_signalviewer) with another matlab session, matlab gives an > error after some time. This 'some time' seems to be steady in length > everytime I try; about 60 seconds on my laptop. > > ??? Error using ==> buffer > ERROR: failed to create socket > > Error in ==> read_header at 939 > orig = buffer('get_hdr', [], host, port); > Error in ==> rt_signalviewer at 75 > hdr = read_header(cfg.headerfile, 'headerformat', cfg.headerformat, > 'cache', true); > > I have had this problem on multiple pc's now. All are using Windows > XP 32-bit, Fieldtrip version 20090610. Can anyone help me resolve > this issue? > > Friendly regards, > > Arjen > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users > of the FieldTrip toolbox, to share experiences and to discuss new > ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html > and http://www.ru.nl/neuroimaging/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From prion.w at GMAIL.COM Tue Jun 23 21:03:07 2009 From: prion.w at GMAIL.COM (peng wang) Date: Tue, 23 Jun 2009 21:03:07 +0200 Subject: channel locations Message-ID: Dear list members, I am a new user of fieldtrip. I have some data preprocessed by fieldtrip. I want to find the channel location information from the field 'grad' in the dataset after this procedure. The original channel number should be 303, but in this field , it looks like this: pnt: [597*3]; ori: [597*3]; tra: [303*597]; label: {303*1 cell} unit: 'cm' balance: {1*1 struct} It seemed there were some transformations(303->597). How did this happen? How can I retrieve the real location information of the sensors?Thank you very much for help! peng ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From v.litvak at ION.UCL.AC.UK Tue Jun 23 21:50:04 2009 From: v.litvak at ION.UCL.AC.UK (Vladimir Litvak) Date: Tue, 23 Jun 2009 20:50:04 +0100 Subject: channel locations In-Reply-To: <4a4126ea.0c58560a.7d96.6cd7@mx.google.com> Message-ID: Dear Peng, These are the real locations. Each channel in your MEG data is computed by combining signals from several magnetometer coils (usually two). The locations of these coils are given in grad.pnt and the way they are combined is described by grad.tra. Best, Vladimir On Tue, Jun 23, 2009 at 8:03 PM, peng wang wrote: > Dear list members, > >        I am a new user of fieldtrip. I have some data preprocessed by fieldtrip. I want to find the channel location information from the field 'grad' in the dataset after this procedure. The original channel number should be 303, but in this field , it looks like this: >          pnt:  [597*3]; >          ori:  [597*3]; >          tra:  [303*597]; >        label:  {303*1 cell} >         unit:  'cm' >  balance:  {1*1 struct} > > It seemed there were some transformations(303->597). How did this happen? How can I retrieve the real location information of the sensors?Thank you very much for help! > > peng > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip  toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From A.Stolk at EWI.UTWENTE.NL Tue Jun 23 22:50:16 2009 From: A.Stolk at EWI.UTWENTE.NL (A. Stolk) Date: Tue, 23 Jun 2009 22:50:16 +0200 Subject: Failed to create socket while using the Fieldtrip buffer Message-ID: Hi Robert, Thank you for your quick reply. I altered util.c, however without any luck so far. Have not tried playing with the usleep setting (yet). Let you know when I know more. Arjen ________________________________ Van: FieldTrip discussion list namens Robert Oostenveld Verzonden: di 6/23/2009 7:06 Aan: FIELDTRIP at NIC.SURFNET.NL Onderwerp: Re: [FIELDTRIP] Failed to create socket while using the Fieldtrip buffer Hi Arjan, The same problem has recently been reported to me by Marco Rontado (see CC). Perhaps it would be usefull if you and Marco get in touch directly to exchange experiences, since sofar there are only few users of fieldtrip for realtime. I have done most of the testing of the buffer on Linux and OSX, and there I have not observed the problem. But given that the problem not always occurs, it might be that the problem is not only windows specific. I am not an expert on TCP/IP networking, but what I suspect is that simultaneous access to the buffer for writing (rt_signalproxy) and reading (rt_signalviewer) causes the problem. Simultaneous access should be possible, because each request is handled by a separate thread. But opening the connection and starting the thread still takes some time, and if during that time the other connection request comes in, the two might collide. At least that is what I currently think is the problem. The solution (not yet implemented) is to have the buffer access function detect that the read or write request has failed and then retry. The fastest (CPU-wise) is to implement the retry at the level of the c-code. Alternative, it would be possible to detect the problem at the level of the matlab code. Extending the matlab wrapper around the buffer request is simpler, but the first is cleaner. It requires a change to the open_connection function in realtime/buffer/src/util.c. At the moment I have limited time (due to traveling), so you could try to fix it yourself. The code around line 258 reads if (connect(s, (struct sockaddr *)&sa, sizeof sa)<0) { perror("open_connection"); return -2; } /* while (connect(s, (struct sockaddr *)&sa, sizeof sa) < 0) { perror("open_connection connect"); usleep(1000000); } */ If you comment out the first section and use the second code snippet instead, then probably it will be solved. Better would be to retry only a few times and not infinitely. Also the usleep could be changed to reduce the delay in the retry. I hope this helps. If you cannot get it to work, please let me know. I'll probably be able to fix it in the official fieldtrip release version somewhere next week. best regards, Robert ----- A. Stolk wrote: > Dear fieldtrip users, > > When using the realtime functions I have difficulties using the > fieldtrip buffer continuously. For example, putting data in the > buffer with rt_signalproxy seems to be a smooth and stable operation > when performed alone. > > But when I subsequently try to access and plot that same data (e.g. > with t_signalviewer) with another matlab session, matlab gives an > error after some time. This 'some time' seems to be steady in length > everytime I try; about 60 seconds on my laptop. > > ??? Error using ==> buffer > ERROR: failed to create socket > > Error in ==> read_header at 939 > orig = buffer('get_hdr', [], host, port); > Error in ==> rt_signalviewer at 75 > hdr = read_header(cfg.headerfile, 'headerformat', cfg.headerformat, > 'cache', true); > > I have had this problem on multiple pc's now. All are using Windows > XP 32-bit, Fieldtrip version 20090610. Can anyone help me resolve > this issue? > > Friendly regards, > > Arjen > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users > of the FieldTrip toolbox, to share experiences and to discuss new > ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html > and http://www.ru.nl/neuroimaging/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From prion.w at GMAIL.COM Wed Jun 24 09:42:30 2009 From: prion.w at GMAIL.COM (peng wang) Date: Wed, 24 Jun 2009 09:42:30 +0200 Subject: channel locations Message-ID: Thank you, Vladimir. Does that mean I can get the coil position by the equation below; and ignore the "ori" information? position = data.grad.tra*data.grad. pnt; Best Peng ========= Dear Peng, These are the real locations. Each channel in your MEG data is computed by combining signals from several magnetometer coils (usually two). The locations of these coils are given in grad.pnt and the way they are combined is described by grad.tra. Best, Vladimir On Tue, Jun 23, 2009 at 8:03 PM, peng wang wrote: > Dear list members, > > I am a new user of fieldtrip. I have some data preprocessed by fieldtrip. I want to find the channel location information from the field 'grad' in the dataset after this procedure. The original channel number should be 303, but in this field , it looks like this: > pnt: [597*3]; > ori: [597*3]; > tra: [303*597]; > label: {303*1 cell} > unit: 'cm' > balance: {1*1 struct} > > It seemed there were some transformations(303->597). How did this happen? How can I retrieve the real location information of the sensors?Thank you very much for help! > > peng > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From v.litvak at ION.UCL.AC.UK Wed Jun 24 10:36:45 2009 From: v.litvak at ION.UCL.AC.UK (Vladimir Litvak) Date: Wed, 24 Jun 2009 09:36:45 +0100 Subject: channel locations In-Reply-To: <4a41d8e6.1358560a.1de9.ffffe324@mx.google.com> Message-ID: On Wed, Jun 24, 2009 at 8:42 AM, peng wang wrote: > Thank you, Vladimir. > Does that mean I can get the coil position by the equation below; and ignore the "ori" information? > position = data.grad.tra*data.grad. pnt; No. grad.tra is about combining sensor signals to get channel signals, not about combining positions. If you want to get a single locations per channel (for instance for topoplotting) you can use the function 'channelposition'. 'ori' is a different way to represent the same information as in grad.tra. It is used for some MEG systems. Best, Vladimir > > Best > Peng > ========= > Dear Peng, > > These are the real locations. Each channel in your MEG data is > computed by combining signals from several magnetometer coils (usually > two). The locations of these coils are given in grad.pnt and the way > they are combined is described by grad.tra. > > Best, > > Vladimir > > On Tue, Jun 23, 2009 at 8:03 PM, peng wang wrote: >> Dear list members, >> >>        I am a new user of fieldtrip. I have some data preprocessed by fieldtrip. I want to find the channel location information from the field 'grad' in the dataset after this procedure. The original channel number should be 303, but in this field , it looks like this: >>          pnt:  [597*3]; >>          ori:  [597*3]; >>          tra:  [303*597]; >>        label:  {303*1 cell} >>         unit:  'cm' >>  balance:  {1*1 struct} >> >> It seemed there were some transformations(303->597). How did this happen? How can I retrieve the real location information of the sensors?Thank you very much for help! >> >> peng >> >> ---------------------------------- >> The aim of this list is to facilitate the discussion between users of the FieldTrip  toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. >> >> > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip  toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From charles.cook at ULETH.CA Wed Jun 24 16:22:04 2009 From: charles.cook at ULETH.CA (Charles Cook) Date: Wed, 24 Jun 2009 16:22:04 +0200 Subject: Update: Freqstatistics Now Yields (Some) Significant Clusters Message-ID: Hi Michael, I would say the single most important variable was getting the scale correct, something you suggested in your last post. Thus, getting this correct in our code: %Read in the electrode locations for the Std81 montage cfg = []; elec = read_fcdc_elec('EGI-BESA_Standard_81_prime.sfp'); elec.pnt = 1000*elec.pnt; This really set us on the right track. Also, having the correct neighbour distance was quite important. That took a little bit of tweaking to get right. Having said all of this, the cluster analysis is proceeding on our data. One point we're not completely satisfied with is the within subjects analysis using the dependent t-test. In our study, we are interested in how male participants were performing in task1 vs. task2. Behaviourally we do see a significant RT difference between task1 vs. task2, but when we run the analysis, we are unable to find any significant clusters (<0.05). It may be possible that this method simply might be too conservative, so if anyone has any suggestions, I'd be very interested and appreciative in some feedback. Cheers, Charles Cook ============================================== % perform the statistical test using randomization and a clustering approach % using the NEW freqstatistics function cfg = []; cfg.neighbourdist = 45; cfg.elec = elec; cfg.statistic = 'depsamplesT'; cfg.minnbchan = 0; cfg.clusteralpha = 0.05; cfg.alpha = 0.05; cfg.clustertail = 0; cfg.numrandomization = 10000; cfg.latency = [0 1000]; cfg.frequency = [8 10]; cfg.avgovertime = 'no'; cfg.avgoverfreq = 'yes'; cfg.avgoverchan = 'no'; cfg.correctm = 'cluster'; cfg.method = 'montecarlo'; cfg.feedback = 'gui'; %cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22; % subject number %1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % condition number cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 10 11; % subject number 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2]; % condition number cfg.uvar = 1; % "subject" is unit of observation cfg.ivar = 2; % "condition" is the independent variable %stat = freqstatistics(cfg, maleloc_all, femloc_all); %stat = freqstatistics(cfg, femfeat_all, malefeat_all); stat = freqstatistics(cfg, maleloc_all, malefeat_all); %stat = freqstatistics(cfg, femfeat_all, femloc_all); cfg = []; cfg.elec = elec; cfg.rotate = 0; %cfg.zlim = [-6 6]; cfg.alpha = 0.05; cfg.label = stat.label; cfg.electrodes = 'labels'; cfg.showxlim = 'yes'; cfg.showzlim = 'yes'; cfg.showylim = 'yes'; clusterplot (cfg, stat); =========================== Obtaining the electrode configuration from the configuration. there are on average 4.7 neighbours per channel using "statistics_montecarlo" for the statistical testing using "statfun_depsamplesT" for the single-sample statistics constructing randomized design total number of measurements = 22 total number of variables = 2 number of independent variables = 1 number of unit variables = 1 number of within-cell variables = 0 number of control variables = 0 using a permutation resampling approach repeated measurement in variable 1 over 11 levels number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 computing a parmetric threshold for clustering estimated time per randomization is 0 seconds found 5 positive clusters in observed data found 12 negative clusters in observed data using a cluster-based method for multiple comparison correction the returned probabilities and the thresholded mask are corrected for multiple comparisons There are 0 clusters smaller than alpha (0.05) On Wed, 17 Jun 2009 09:24:41 +0200, Michael Wibral wrote: >Hi Charles, > >the plots look OK to me. Could you let us know what finally made your analysis work (if there was a single most important thing) >- that would be most helpful. > >Thanks, >Michael > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From prion.w at GMAIL.COM Wed Jun 24 16:50:54 2009 From: prion.w at GMAIL.COM (peng wang) Date: Wed, 24 Jun 2009 16:50:54 +0200 Subject: channel locations Message-ID: Thank you, Vladimir. I made it with the ways you suggested. ========= On Wed, Jun 24, 2009 at 8:42 AM, peng wang wrote: > Thank you, Vladimir. > Does that mean I can get the coil position by the equation below; and ignore the "ori" information? > position = data.grad.tra*data.grad. pnt; No. grad.tra is about combining sensor signals to get channel signals, not about combining positions. If you want to get a single locations per channel (for instance for topoplotting) you can use the function 'channelposition'. 'ori' is a different way to represent the same information as in grad.tra. It is used for some MEG systems. Best, Vladimir > > Best > Peng > ========= > Dear Peng, > > These are the real locations. Each channel in your MEG data is > computed by combining signals from several magnetometer coils (usually > two). The locations of these coils are given in grad.pnt and the way > they are combined is described by grad.tra. > > Best, > > Vladimir > > On Tue, Jun 23, 2009 at 8:03 PM, peng wang wrote: >> Dear list members, >> >> I am a new user of fieldtrip. I have some data preprocessed by fieldtrip. I want to find the channel location information from the field 'grad' in the dataset after this procedure. The original channel number should be 303, but in this field , it looks like this: >> pnt: [597*3]; >> ori: [597*3]; >> tra: [303*597]; >> label: {303*1 cell} >> unit: 'cm' >> balance: {1*1 struct} >> >> It seemed there were some transformations(303->597). How did this happen? How can I retrieve the real location information of the sensors?Thank you very much for help! >> >> peng >> >> ---------------------------------- >> The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. >> >> > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From wibral at BIC.UNI-FRANKFURT.DE Thu Jun 25 12:00:31 2009 From: wibral at BIC.UNI-FRANKFURT.DE (Michael Wibral) Date: Thu, 25 Jun 2009 12:00:31 +0200 Subject: Update: Freqstatistics Now Yields (Som e) Significant Clusters Message-ID: Hi Charles, thanks for the update. Cluster based statistics is exactly what the name says: A statistics telling you whether you have spatially and temporally contiguous effects that cross a certain threshold - in sum over the cluster. It is sometimes worth considering, whether this is what you want to test after all. E.g. extended effects of small effect size per electrode but large time/frequency extent and effects of large effect size but small time/frequency extent may have similar cluster statistics. The even compete in the sense that randomizations of the larger of the two (in total cluster sum) may still have larger cluster statistics thatn the smaller of the two, thus effectively rendering in non-significant. Bear in mind that the only thing really tested is the exchangeability of the data (which is the null hypothesis). That may sometimes make your results more difficult to interpret. You clould also try cfg.correctm = 'fdr', to get classical FDR correction, but you may loose sensitivity in some cases. One last thing: Check carefully that there is no factor that has been balanced over subjects (e.g. response hand) that may be resorted in the randomizations. For example: half of the subjects report match with the right hand and non-match with the left hand, the other half responding with an inverted assignment. This analysis setup: 1. violates the exchangeability hypothesis from the start (and you know!), but not in the way you wanted to test it - this is a serious error in applying randomization testing... 2. Consequentaly, it renders all other effects insignificant because the sorted response hand effects in the randomizations most likely exceed any other effect in the unrandomized data. Michael > -----Ursprüngliche Nachricht----- > Von: "Charles Cook" > Gesendet: 24.06.09 16:23:39 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: Re: [FIELDTRIP] Update: Freqstatistics Now Yields (Some) Significant Clusters > Hi Michael, > > I would say the single most important variable was getting the scale > correct, something you suggested in your last post. Thus, getting this > correct in our code: > > %Read in the electrode locations for the Std81 montage > cfg = []; > elec = read_fcdc_elec('EGI-BESA_Standard_81_prime.sfp'); > elec.pnt = 1000*elec.pnt; > > This really set us on the right track. Also, having the correct neighbour > distance was quite important. That took a little bit of tweaking to get right. > > Having said all of this, the cluster analysis is proceeding on our data. One > point we're not completely satisfied with is the within subjects analysis > using the dependent t-test. In our study, we are interested in how male > participants were performing in task1 vs. task2. Behaviourally we do see a > significant RT difference between task1 vs. task2, but when we run the > analysis, we are unable to find any significant clusters (<0.05). It may be > possible that this method simply might be too conservative, so if anyone has > any suggestions, I'd be very interested and appreciative in some feedback. > > Cheers, > > Charles Cook > ============================================== > > % perform the statistical test using randomization and a clustering approach > % using the NEW freqstatistics function > cfg = []; > cfg.neighbourdist = 45; > cfg.elec = elec; > cfg.statistic = 'depsamplesT'; > cfg.minnbchan = 0; > cfg.clusteralpha = 0.05; > cfg.alpha = 0.05; > cfg.clustertail = 0; > cfg.numrandomization = 10000; > > cfg.latency = [0 1000]; > cfg.frequency = [8 10]; > cfg.avgovertime = 'no'; > cfg.avgoverfreq = 'yes'; > cfg.avgoverchan = 'no'; > > cfg.correctm = 'cluster'; > cfg.method = 'montecarlo'; > cfg.feedback = 'gui'; > %cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > 21 22; % subject number > %1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 > 2 2]; % condition number > > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 > 10 11; % subject number > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 > 2]; % condition number > > > cfg.uvar = 1; % "subject" is unit of > observation > cfg.ivar = 2; % "condition" is the > independent variable > %stat = freqstatistics(cfg, maleloc_all, femloc_all); > %stat = freqstatistics(cfg, femfeat_all, malefeat_all); > stat = freqstatistics(cfg, maleloc_all, malefeat_all); > %stat = freqstatistics(cfg, femfeat_all, femloc_all); > > cfg = []; > cfg.elec = elec; > cfg.rotate = 0; > %cfg.zlim = [-6 6]; > cfg.alpha = 0.05; > cfg.label = stat.label; > cfg.electrodes = 'labels'; > cfg.showxlim = 'yes'; > cfg.showzlim = 'yes'; > cfg.showylim = 'yes'; > clusterplot (cfg, stat); > =========================== > Obtaining the electrode configuration from the configuration. > there are on average 4.7 neighbours per channel > using "statistics_montecarlo" for the statistical testing > using "statfun_depsamplesT" for the single-sample statistics > constructing randomized design > total number of measurements = 22 > total number of variables = 2 > number of independent variables = 1 > number of unit variables = 1 > number of within-cell variables = 0 > number of control variables = 0 > using a permutation resampling approach > repeated measurement in variable 1 over 11 levels > number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 > computing a parmetric threshold for clustering > estimated time per randomization is 0 seconds > found 5 positive clusters in observed data > found 12 negative clusters in observed data > using a cluster-based method for multiple comparison correction > the returned probabilities and the thresholded mask are corrected for > multiple comparisons > There are 0 clusters smaller than alpha (0.05) > > On Wed, 17 Jun 2009 09:24:41 +0200, Michael Wibral > wrote: > > >Hi Charles, > > > >the plots look OK to me. Could you let us know what finally made your > analysis work (if there was a single most important thing) > >- that would be most helpful. > > > >Thanks, > >Michael > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 344 bytes Desc: not available URL: From susannah.murphy at PSYCH.OX.AC.UK Thu Jun 25 12:00:37 2009 From: susannah.murphy at PSYCH.OX.AC.UK (Susannah Murphy) Date: Thu, 25 Jun 2009 11:00:37 +0100 Subject: Update: Freqstatistics Now Yields (Som e) Significant Clusters In-Reply-To: <999611076@web.de> Message-ID: Thanks for your message. I am out of the office until Wednesday 1st July. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From e.maris at DONDERS.RU.NL Thu Jun 25 21:27:43 2009 From: e.maris at DONDERS.RU.NL (Eric Maris) Date: Thu, 25 Jun 2009 21:27:43 +0200 Subject: Update: Freqstatistics Now Yields (Som e) Significant Clusters In-Reply-To: <999611076@web.de> Message-ID: Hi Michael, > thanks for the update. Cluster based statistics is exactly what the name says: A > statistics telling you whether you have spatially and temporally contiguous effects > that cross a certain threshold - in sum over the cluster. It is sometimes worth > considering, whether this is what you want to test after all. E.g. extended effects of > small effect size per electrode but large time/frequency extent and effects of large > effect size but small time/frequency extent may have similar cluster statistics. The > even compete in the sense that randomizations of the larger of the two (in total > cluster sum) may still have larger cluster statistics thatn the smaller of the two, > thus effectively rendering in non-significant. Bear in mind that the only thing really > tested is the exchangeability of the data (which is the null hypothesis). That may > sometimes make your results more difficult to interpret. You clould also try > cfg.correctm = 'fdr', to get classical FDR correction, but you may loose sensitivity in > some cases. This is a fair assessment of cluster-based statistics. > > One last thing: Check carefully that there is no factor that has been balanced over > subjects (e.g. response hand) that may be resorted in the randomizations. For > example: half of the subjects report match with the right hand and non-match with > the left hand, the other half responding with an inverted assignment. This analysis > setup: > 1. violates the exchangeability hypothesis from the start (and you know!), but not in > the way you wanted to test it - this is a serious error in applying randomization > testing... > 2. Consequentaly, it renders all other effects insignificant because the sorted > response hand effects in the randomizations most likely exceed any other effect in > the unrandomized data. The theory of permutation tests also applies to statistical testing problems that involve control variables (e.g., response hand). In this case, the mechanics of the permutation test involves randomly permuting the data sets (single trials or subject averages) within each of the levels of the control variable (conditional permutation). To increase statistical sensitivity in the presence of control variable, it also is good to use a special test statistic that partials out the variance explained by the control variable. This is implemented in Fieldtrip for a couple of statfuns, but not for all of them. Conditional permutation is implemented via cfg.cvar. dr. Eric Maris Donders Institute for Brain, Cognition and Behavior Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging Radboud University P.O. Box 9104 6500 HE Nijmegen The Netherlands T:+31 24 3612651 F:+31 24 3616066 E: e.maris at donders.ru.nl MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > > > Michael > > > > > -----Ursprüngliche Nachricht----- > > Von: "Charles Cook" > > Gesendet: 24.06.09 16:23:39 > > An: FIELDTRIP at NIC.SURFNET.NL > > Betreff: Re: [FIELDTRIP] Update: Freqstatistics Now Yields (Some) Significant > Clusters > > > > Hi Michael, > > > > I would say the single most important variable was getting the scale > > correct, something you suggested in your last post. Thus, getting this > > correct in our code: > > > > %Read in the electrode locations for the Std81 montage > > cfg = []; > > elec = read_fcdc_elec('EGI-BESA_Standard_81_prime.sfp'); > > elec.pnt = 1000*elec.pnt; > > > > This really set us on the right track. Also, having the correct neighbour > > distance was quite important. That took a little bit of tweaking to get right. > > > > Having said all of this, the cluster analysis is proceeding on our data. One > > point we're not completely satisfied with is the within subjects analysis > > using the dependent t-test. In our study, we are interested in how male > > participants were performing in task1 vs. task2. Behaviourally we do see a > > significant RT difference between task1 vs. task2, but when we run the > > analysis, we are unable to find any significant clusters (<0.05). It may be > > possible that this method simply might be too conservative, so if anyone has > > any suggestions, I'd be very interested and appreciative in some feedback. > > > > Cheers, > > > > Charles Cook > > ============================================== > > > > % perform the statistical test using randomization and a clustering approach > > % using the NEW freqstatistics function > > cfg = []; > > cfg.neighbourdist = 45; > > cfg.elec = elec; > > cfg.statistic = 'depsamplesT'; > > cfg.minnbchan = 0; > > cfg.clusteralpha = 0.05; > > cfg.alpha = 0.05; > > cfg.clustertail = 0; > > cfg.numrandomization = 10000; > > > > cfg.latency = [0 1000]; > > cfg.frequency = [8 10]; > > cfg.avgovertime = 'no'; > > cfg.avgoverfreq = 'yes'; > > cfg.avgoverchan = 'no'; > > > > cfg.correctm = 'cluster'; > > cfg.method = 'montecarlo'; > > cfg.feedback = 'gui'; > > %cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 > > 21 22; % subject number > > %1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 > > 2 2]; % condition number > > > > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 9 > > 10 11; % subject number > > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 > > 2]; % condition number > > > > > > cfg.uvar = 1; % "subject" is unit of > > observation > > cfg.ivar = 2; % "condition" is the > > independent variable > > %stat = freqstatistics(cfg, maleloc_all, femloc_all); > > %stat = freqstatistics(cfg, femfeat_all, malefeat_all); > > stat = freqstatistics(cfg, maleloc_all, malefeat_all); > > %stat = freqstatistics(cfg, femfeat_all, femloc_all); > > > > cfg = []; > > cfg.elec = elec; > > cfg.rotate = 0; > > %cfg.zlim = [-6 6]; > > cfg.alpha = 0.05; > > cfg.label = stat.label; > > cfg.electrodes = 'labels'; > > cfg.showxlim = 'yes'; > > cfg.showzlim = 'yes'; > > cfg.showylim = 'yes'; > > clusterplot (cfg, stat); > > =========================== > > Obtaining the electrode configuration from the configuration. > > there are on average 4.7 neighbours per channel > > using "statistics_montecarlo" for the statistical testing > > using "statfun_depsamplesT" for the single-sample statistics > > constructing randomized design > > total number of measurements = 22 > > total number of variables = 2 > > number of independent variables = 1 > > number of unit variables = 1 > > number of within-cell variables = 0 > > number of control variables = 0 > > using a permutation resampling approach > > repeated measurement in variable 1 over 11 levels > > number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 > > computing a parmetric threshold for clustering > > estimated time per randomization is 0 seconds > > found 5 positive clusters in observed data > > found 12 negative clusters in observed data > > using a cluster-based method for multiple comparison correction > > the returned probabilities and the thresholded mask are corrected for > > multiple comparisons > > There are 0 clusters smaller than alpha (0.05) > > > > On Wed, 17 Jun 2009 09:24:41 +0200, Michael Wibral > > wrote: > > > > >Hi Charles, > > > > > >the plots look OK to me. Could you let us know what finally made your > > analysis work (if there was a single most important thing) > > >- that would be most helpful. > > > > > >Thanks, > > >Michael > > > > > > > ---------------------------------- > > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. > > > > > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip > toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From nathanweisz at MAC.COM Mon Jun 29 09:34:22 2009 From: nathanweisz at MAC.COM (Nathan Weisz) Date: Mon, 29 Jun 2009 09:34:22 +0200 Subject: preprocessing without trigger... In-Reply-To: Message-ID: hi, if i understand you correctly you want to analyse your sponatneous data. you need a "trial-function" that you run before calling preprocessing (see help definetrial). below some code for *non-overlapping* 2s windows. but it should be easy to adapt. good luck, n function trl=tzvetan_trialf(cfg) %cuts data into 2 second windows hdr = read_fcdc_header(cfg.dataset); win=2*hdr.Fs; trl=[]; i=1; k=1; while i < (hdr.nSamples-win-1) trl(k,:)=round([i (i+win-1) 0]); i=i+win; k=k+1; end%i On 23.06.2009, at 14:20, Marco Rotonda wrote: > thanks! > it's very useful because I'm using bci2000 either! > > > On 23/giu/09, at 14:03, Thomas Dijkman wrote: > >> Hi, >> >> Check out this page in the documentation: >> >> http://fieldtrip.fcdonders.nl/faq/reading_is_slow_can_i_write_my_raw_data_to_a_more_efficient_file_format >> >> This will probably help you further. >> >> Regards, >> >> Thomas >> >> >> -----Oorspronkelijk bericht----- >> Van: FieldTrip discussion list namens Marco Rotonda >> Verzonden: di 23-6-2009 13:59 >> Aan: FIELDTRIP at NIC.SURFNET.NL >> Onderwerp: [FIELDTRIP] preprocessing without trigger... >> >> Hi there, >> it could be a stupid question but I don't know how to solve it. >> I wish to analyze some data files I have (continuous signal, >> without any >> trigger). >> These data sets are 3 minutes of neurofeedback training and there >> are no >> trigger. >> I just want take all the 3 minutes and take each second overlapping >> 500ms. >> The point is that there are no trigger so I don't know how to do the >> preprocessing (where I have to specify the trigger, isn't it?). >> >> Thanks in advance >> >> ---------------------------------- >> The aim of this list is to facilitate the discussion between users >> of the FieldTrip toolbox, to share experiences and to discuss new >> ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html >> and http://www.ru.nl/neuroimaging/fieldtrip. >> >> ---------------------------------- >> The aim of this list is to facilitate the discussion between users >> of the FieldTrip toolbox, to share experiences and to discuss new >> ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html >> and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- > The aim of this list is to facilitate the discussion between users > of the FieldTrip toolbox, to share experiences and to discuss new > ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html > and http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From wibral at BIC.UNI-FRANKFURT.DE Mon Jun 29 10:44:13 2009 From: wibral at BIC.UNI-FRANKFURT.DE (Michael Wibral) Date: Mon, 29 Jun 2009 10:44:13 +0200 Subject: Update: Freqstatistics Now Yields (Som e) Significant Clusters Message-ID: Hi Eric, thanks for the update on the statfuns. "cfg.cvar" is indeed very helpful. Again I see it always pays to update to the latest version :-). Michael > -----Ursprüngliche Nachricht----- > Von: "Eric Maris" > Gesendet: 25.06.09 21:30:40 > An: FIELDTRIP at NIC.SURFNET.NL > Betreff: Re: [FIELDTRIP] Update: Freqstatistics Now Yields (Som e) Significant Clusters > Hi Michael, > > > thanks for the update. Cluster based statistics is exactly what the name > says: A > > statistics telling you whether you have spatially and temporally > contiguous effects > > that cross a certain threshold - in sum over the cluster. It is sometimes > worth > > considering, whether this is what you want to test after all. E.g. > extended effects of > > small effect size per electrode but large time/frequency extent and > effects of large > > effect size but small time/frequency extent may have similar cluster > statistics. The > > even compete in the sense that randomizations of the larger of the two (in > total > > cluster sum) may still have larger cluster statistics thatn the smaller of > the two, > > thus effectively rendering in non-significant. Bear in mind that the only > thing really > > tested is the exchangeability of the data (which is the null hypothesis). > That may > > sometimes make your results more difficult to interpret. You clould also > try > > cfg.correctm = 'fdr', to get classical FDR correction, but you may loose > sensitivity in > > some cases. > > This is a fair assessment of cluster-based statistics. > > > > > One last thing: Check carefully that there is no factor that has been > balanced over > > subjects (e.g. response hand) that may be resorted in the randomizations. > For > > example: half of the subjects report match with the right hand and > non-match with > > the left hand, the other half responding with an inverted assignment. This > analysis > > setup: > > 1. violates the exchangeability hypothesis from the start (and you know!), > but not in > > the way you wanted to test it - this is a serious error in applying > randomization > > testing... > > 2. Consequentaly, it renders all other effects insignificant because the > sorted > > response hand effects in the randomizations most likely exceed any other > effect in > > the unrandomized data. > > The theory of permutation tests also applies to statistical testing problems > that involve control variables (e.g., response hand). In this case, the > mechanics of the permutation test involves randomly permuting the data sets > (single trials or subject averages) within each of the levels of the control > variable (conditional permutation). To increase statistical sensitivity in > the presence of control variable, it also is good to use a special test > statistic that partials out the variance explained by the control variable. > This is implemented in Fieldtrip for a couple of statfuns, but not for all > of them. Conditional permutation is implemented via cfg.cvar. > > > dr. Eric Maris > Donders Institute for Brain, Cognition and Behavior > > Center for Cognition and F.C. Donders Center for Cognitive Neuroimaging > > Radboud University > P.O. Box 9104 > 6500 HE Nijmegen > The Netherlands > T:+31 24 3612651 > F:+31 24 3616066 > E: e.maris at donders.ru.nl > > > > MSc Cognitive Neuroscience: www.ru.nl/master/cns/ > > > > > > > > > Michael > > > > > > > > > -----Ursprüngliche Nachricht----- > > > Von: "Charles Cook" > > > Gesendet: 24.06.09 16:23:39 > > > An: FIELDTRIP at NIC.SURFNET.NL > > > Betreff: Re: [FIELDTRIP] Update: Freqstatistics Now Yields (Some) > Significant > > Clusters > > > > > > > Hi Michael, > > > > > > I would say the single most important variable was getting the scale > > > correct, something you suggested in your last post. Thus, getting this > > > correct in our code: > > > > > > %Read in the electrode locations for the Std81 montage > > > cfg = []; > > > elec = read_fcdc_elec('EGI-BESA_Standard_81_prime.sfp'); > > > elec.pnt = 1000*elec.pnt; > > > > > > This really set us on the right track. Also, having the correct > neighbour > > > distance was quite important. That took a little bit of tweaking to get > right. > > > > > > Having said all of this, the cluster analysis is proceeding on our data. > One > > > point we're not completely satisfied with is the within subjects > analysis > > > using the dependent t-test. In our study, we are interested in how male > > > participants were performing in task1 vs. task2. Behaviourally we do see > a > > > significant RT difference between task1 vs. task2, but when we run the > > > analysis, we are unable to find any significant clusters (<0.05). It may > be > > > possible that this method simply might be too conservative, so if anyone > has > > > any suggestions, I'd be very interested and appreciative in some > feedback. > > > > > > Cheers, > > > > > > Charles Cook > > > ============================================== > > > > > > % perform the statistical test using randomization and a clustering > approach > > > % using the NEW freqstatistics function > > > cfg = []; > > > cfg.neighbourdist = 45; > > > cfg.elec = elec; > > > cfg.statistic = 'depsamplesT'; > > > cfg.minnbchan = 0; > > > cfg.clusteralpha = 0.05; > > > cfg.alpha = 0.05; > > > cfg.clustertail = 0; > > > cfg.numrandomization = 10000; > > > > > > cfg.latency = [0 1000]; > > > cfg.frequency = [8 10]; > > > cfg.avgovertime = 'no'; > > > cfg.avgoverfreq = 'yes'; > > > cfg.avgoverchan = 'no'; > > > > > > cfg.correctm = 'cluster'; > > > cfg.method = 'montecarlo'; > > > cfg.feedback = 'gui'; > > > %cfg.design = [1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 > 20 > > > 21 22; % subject number > > > %1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 > 2 > > > 2 2]; % condition number > > > > > > cfg.design = [1 2 3 4 5 6 7 8 9 10 11 1 2 3 4 5 6 7 8 > 9 > > > 10 11; % subject number > > > 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 > 2 2 > > > 2]; % condition number > > > > > > > > > cfg.uvar = 1; % "subject" is unit of > > > observation > > > cfg.ivar = 2; % "condition" is the > > > independent variable > > > %stat = freqstatistics(cfg, maleloc_all, femloc_all); > > > %stat = freqstatistics(cfg, femfeat_all, malefeat_all); > > > stat = freqstatistics(cfg, maleloc_all, malefeat_all); > > > %stat = freqstatistics(cfg, femfeat_all, femloc_all); > > > > > > cfg = []; > > > cfg.elec = elec; > > > cfg.rotate = 0; > > > %cfg.zlim = [-6 6]; > > > cfg.alpha = 0.05; > > > cfg.label = stat.label; > > > cfg.electrodes = 'labels'; > > > cfg.showxlim = 'yes'; > > > cfg.showzlim = 'yes'; > > > cfg.showylim = 'yes'; > > > clusterplot (cfg, stat); > > > =========================== > > > Obtaining the electrode configuration from the configuration. > > > there are on average 4.7 neighbours per channel > > > using "statistics_montecarlo" for the statistical testing > > > using "statfun_depsamplesT" for the single-sample statistics > > > constructing randomized design > > > total number of measurements = 22 > > > total number of variables = 2 > > > number of independent variables = 1 > > > number of unit variables = 1 > > > number of within-cell variables = 0 > > > number of control variables = 0 > > > using a permutation resampling approach > > > repeated measurement in variable 1 over 11 levels > > > number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 > > > computing a parmetric threshold for clustering > > > estimated time per randomization is 0 seconds > > > found 5 positive clusters in observed data > > > found 12 negative clusters in observed data > > > using a cluster-based method for multiple comparison correction > > > the returned probabilities and the thresholded mask are corrected for > > > multiple comparisons > > > There are 0 clusters smaller than alpha (0.05) > > > > > > On Wed, 17 Jun 2009 09:24:41 +0200, Michael Wibral > > > wrote: > > > > > > >Hi Charles, > > > > > > > >the plots look OK to me. Could you let us know what finally made your > > > analysis work (if there was a single most important thing) > > > >- that would be most helpful. > > > > > > > >Thanks, > > > >Michael > > > > > > > > > > ---------------------------------- > > > The aim of this list is to facilitate the discussion between users of > the FieldTrip > > toolbox, to share experiences and to discuss new ideas for MEG and EEG > analysis. > > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > > http://www.ru.nl/neuroimaging/fieldtrip. > > > > > > > > > > > ---------------------------------- > > The aim of this list is to facilitate the discussion between users of the > FieldTrip > > toolbox, to share experiences and to discuss new ideas for MEG and EEG > analysis. > > See also http://listserv.surfnet.nl/archives/fieldtrip.html and > > http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: Michael Wibral.vcf Type: text/x-vcard Size: 344 bytes Desc: not available URL: From ingrid.nieuwenhuis at DONDERS.RU.NL Mon Jun 29 22:09:19 2009 From: ingrid.nieuwenhuis at DONDERS.RU.NL (Ingrid Nieuwenhuis) Date: Mon, 29 Jun 2009 22:09:19 +0200 Subject: Clusterplot not highlighting clusters & average layout file In-Reply-To: Message-ID: Dear Manish, (I reply to the list again, than everyone can benefit). That depends on what you want to test. If you have multiple frequencies in your freq-data, and you just call freqanalysis, and you do not average over specific frequency range, then clusterplot will look for clusters in the time-frequency-place domain. This does not always make sense, for instance in the lower frequencies we know that there are different frequency bands that behave totally different (theta and alpha for instance). Then you can better run freqanalysis for these frequencies separately (choose only 10Hz for alpha, or choose 8:12 Hz and cfg.avgoverfreq = 'yes'). In this case you can use clusterplot to visualize. If you have no idea which frequencies behave the same, or that is something you are actually interested in (for instance you have a broadbanded high gamma in your TFR) you can put freq-data with multiple frequencies in freqanalysis and look at the cluster that comes out. This is a valid thing to do, but you can only not use clusterplot to visualize then. What you can do is plot with multiplotTFR with mask settings (cfg.zparam = 'stat', cfg.maskparam = 'mask'). Best Ingrid > -----Original Message----- > From: Manish Saggar [mailto:manish.saggar at gmail.com] > Sent: Monday, June 29, 2009 7:49 PM > To: ingrid.nieuwenhuis at donders.ru.nl > Subject: Re: [FIELDTRIP] Clusterplot not highlighting clusters & average > layout file > > Dear Ingrid, > > Thanks for your reply. Sorry I was out and didn't get a chance to reply > back. > > Last question regarding your reply, can I simply run freqstats and > clusterplot for each frequency separately? > > Regards, > Manish > > On Fri, May 22, 2009 at 9:39 AM, Ingrid > Nieuwenhuis wrote: > > Dear Manish, > > > > If I understand correctly you have multiple frequencies over which you > > cluster. Is that correct? (so cfg.avgoverfreq = 'no' when you called > > freqstatistics?) In that case you should not call clusterplot because > for > > different frequencies there can be different channels part of the > cluster. > > Instead you can call multiplotER or multiplotTFR and use > cfg.maskparameter = > > 'mask' to plot the significant cluster. > > > > Hope this helps, > > Ingrid > > > > > >> -----Original Message----- > >> From: Manish Saggar [mailto:manish.saggar at gmail.com] > >> Sent: Friday, May 15, 2009 8:26 AM > >> To: ingrid.nieuwenhuis at donders.ru.nl > >> Cc: FIELDTRIP at NIC.SURFNET.NL > >> Subject: Re: [FIELDTRIP] Clusterplot not highlighting clusters & > average > >> layout file > >> > >> Ingrid, thanks for replying back. > >> > >> Apologies for lack of information. > >> > >> Clusterplot is plotting clusters fine most of the times, but in some > >> cases it doesn't choose to highlight markers. I have attached two such > >> images with this email. > >> > >> I do not get any errors or warnings. In fact the command window in > >> matlab says, cluster found (with some prob and highlighter sign) and > >> then the plot doesn't contain any highlighting. > >> Initially I thought that my layout file might be messing it up or > >> something, or may be I need to take an average layout file for group > >> analysis (since cap size and electrode digitization varies for each > >> subject). > >> > >> Then I put debug points in the code and found out that at line 235 the > >> list cell (used to denote highlighted points) is empty. I am a novice > >> so please forgive if what I am suggesting is dumb here, but I think > >> when cluster plot is searching for significant clusters it is only > >> looking into first column (which could correspond to first frequency > >> in band) if one cluster is found by freqstats. It might be that in the > >> code you guys are sorting columns and I might have missed it. But I > >> thought I should clear this with you. > >> > >> In another thread you have mentioned to someone that their time limits > >> might not be precise enough to get the clusers highlighted > >> > (https://listserv.surfnet.nl/scripts/wa.cgi?A2=ind0709&L=FIELDTRIP&P=R680 > >> ). But they were doing time-freq analysis and I am just doing freq- > >> representations. So should I use freqstats on each freq separately ? > >> > >> On a side note, when I run freqstats on my data (with 88 channels) > >> command line says '89 neighbors per channel found'. I am a little > >> confused with this. First since I only have less than 88 channels in > >> the data and second since it should only consider a lower number for > >> neighbor distance, right? and how can I change it? > >> > >> Thanks a ton in advance, > >> Manish > >> > >> On May 13, 2009, at 2:10 AM, Ingrid Nieuwenhuis wrote: > >> > >> > Dear Manish, > >> > > >> > You give a bit too few information to be able to figure out what > >> > could be > >> > the problem with clusterplot. After calling clusterplot, clusterplot > >> > gives > >> > information on which clusters it finds. Does the function find any > >> > clusters? > >> > Does the .mask field of the structure that comes out of > freqstatistics > >> > contain any ones? Is everything else plotted normally? Do you get > >> > any errors > >> > or warnings? > >> > > >> > I'm not familiar with BESA layout files, but assuming that all > >> > layout files > >> > are similar over subjects, I think it is fine to just use an > >> > individual > >> > subject's layout file. > >> > > >> > Hope this helps, > >> > Best Ingrid > >> > > >> > > >> >>  ---Original Message----- > >> >> From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On > >> >> Behalf Of Manish Saggar > >> >> Sent: Tuesday, May 12, 2009 10:17 AM > >> >> To: FIELDTRIP at NIC.SURFNET.NL > >> >> Subject: [FIELDTRIP] Clusterplot not highlighting clusters & average > >> >> layout file > >> >> > >> >> All, > >> >> > >> >> I have a question regarding clusterplot function. I am doing a > >> >> within-subject analysis. > >> >> The experimental design that I have is as follows, there are three > >> >> conditions C1, C2 and C3. Each condition is of 1 min duration (e.g. > >> >> rest with eyes open for 1 min). > >> >> > >> >> Now I am comparing grandaverage of freq representation of a set of > >> >> subjects for C2 with C1 etc. FreqStatistics is running just fine > >> >> creating significant (<0.025 alpha, for 2-tailed test) clusters > >> >> (positive). Now the problem is that when I try to plot the location > >> >> of > >> >> this cluster using clusterplot it doesn't show any highlighted > >> >> channels. Any ideas why that is happening? > >> >> > >> >> Another question is that since I am using grandaverages of freq > >> >> representation, what should I use for layout file (using BESA sfp > >> >> file > >> >> here). I have individual subject layout files. Currently I am just > >> >> giving any file from one of the subjects. Since, I noticed that > >> >> FreqStatistics finds a common minimum set of channels and then apply > >> >> statistics on it. So do I need to average layout files for the > >> >> subject > >> >> group or is there any other way? > >> >> > >> >> Any help is much appreciated. > >> >> > >> >> Regards, > >> >> Manish > >> >> > >> >> ---------------------------------- > >> >> The aim of this list is to facilitate the discussion between users > >> >> of the > >> >> FieldTrip  toolbox, to share experiences and to discuss new ideas > >> >> for MEG > >> >> and EEG analysis. See also > >> >> http://listserv.surfnet.nl/archives/fieldtrip.html and > >> >> http://www.ru.nl/neuroimaging/fieldtrip. > >> > > >> > ---------------------------------- > >> > The aim of this list is to facilitate the discussion between users > >> > of the FieldTrip  toolbox, to share experiences and to discuss new > >> > ideas for MEG and EEG analysis. See also > >> http://listserv.surfnet.nl/archives/fieldtrip.html > >> >  and http://www.ru.nl/neuroimaging/fieldtrip. > >> > > > > > > > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From ingrid.nieuwenhuis at DONDERS.RU.NL Mon Jun 29 22:15:40 2009 From: ingrid.nieuwenhuis at DONDERS.RU.NL (Ingrid Nieuwenhuis) Date: Mon, 29 Jun 2009 22:15:40 +0200 Subject: preprocessing without trigger... In-Reply-To: <3D5A4DC7-1B7D-4B26-8164-84B97A717549@mac.com> Message-ID: Hi, There is actually a trial-function implemented in fieldtrip that you can use during definetrial, it is called trialfun_general. cfg.trialfun = 'trialfun_general'; cfg.trialdef.triallength = 2; cfg.trialdef.ntrials = inf; And it will cut the data in 2 sec nonoverlapping timewindows. Nice and easy :) Best Ingrid > -----Original Message----- > From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On > Behalf Of Nathan Weisz > Sent: Monday, June 29, 2009 9:34 AM > To: FIELDTRIP at NIC.SURFNET.NL > Subject: Re: [FIELDTRIP] preprocessing without trigger... > > hi, > > if i understand you correctly you want to analyse your sponatneous data. > you need a "trial-function" that you run before calling preprocessing > (see help definetrial). > > below some code for *non-overlapping* 2s windows. but it should be > easy to adapt. > > good luck, > n > > function trl=tzvetan_trialf(cfg) > %cuts data into 2 second windows > > hdr = read_fcdc_header(cfg.dataset); > win=2*hdr.Fs; > > trl=[]; > > i=1; > k=1; > while i < (hdr.nSamples-win-1) > > trl(k,:)=round([i (i+win-1) 0]); > i=i+win; > k=k+1; > > end%i > > On 23.06.2009, at 14:20, Marco Rotonda wrote: > > > thanks! > > it's very useful because I'm using bci2000 either! > > > > > > On 23/giu/09, at 14:03, Thomas Dijkman wrote: > > > >> Hi, > >> > >> Check out this page in the documentation: > >> > >> > http://fieldtrip.fcdonders.nl/faq/reading_is_slow_can_i_write_my_raw_data_ > to_a_more_efficient_file_format > >> > >> This will probably help you further. > >> > >> Regards, > >> > >> Thomas > >> > >> > >> -----Oorspronkelijk bericht----- > >> Van: FieldTrip discussion list namens Marco Rotonda > >> Verzonden: di 23-6-2009 13:59 > >> Aan: FIELDTRIP at NIC.SURFNET.NL > >> Onderwerp: [FIELDTRIP] preprocessing without trigger... > >> > >> Hi there, > >> it could be a stupid question but I don't know how to solve it. > >> I wish to analyze some data files I have (continuous signal, > >> without any > >> trigger). > >> These data sets are 3 minutes of neurofeedback training and there > >> are no > >> trigger. > >> I just want take all the 3 minutes and take each second overlapping > >> 500ms. > >> The point is that there are no trigger so I don't know how to do the > >> preprocessing (where I have to specify the trigger, isn't it?). > >> > >> Thanks in advance > >> > >> ---------------------------------- > >> The aim of this list is to facilitate the discussion between users > >> of the FieldTrip toolbox, to share experiences and to discuss new > >> ideas for MEG and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html > >> and http://www.ru.nl/neuroimaging/fieldtrip. > >> > >> ---------------------------------- > >> The aim of this list is to facilitate the discussion between users > >> of the FieldTrip toolbox, to share experiences and to discuss new > >> ideas for MEG and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html > >> and http://www.ru.nl/neuroimaging/fieldtrip. > > > > ---------------------------------- > > The aim of this list is to facilitate the discussion between users > > of the FieldTrip toolbox, to share experiences and to discuss new > > ideas for MEG and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html > > and http://www.ru.nl/neuroimaging/fieldtrip. > > ---------------------------------- > The aim of this list is to facilitate the discussion between users of the > FieldTrip toolbox, to share experiences and to discuss new ideas for MEG > and EEG analysis. See also > http://listserv.surfnet.nl/archives/fieldtrip.html and > http://www.ru.nl/neuroimaging/fieldtrip. ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From manish.saggar at GMAIL.COM Tue Jun 30 06:39:52 2009 From: manish.saggar at GMAIL.COM (Manish Saggar) Date: Mon, 29 Jun 2009 23:39:52 -0500 Subject: Clusterplot not highlighting clusters & average layout file In-Reply-To: <005201c9f8f5$7ccee6a0$642dae83@fcdonders.nl> Message-ID: Thanks for your quick reply. I wanted to run freqstats separately on each frequency, since I don't have precise temporal resolution in my data (no events). Hence I need to run stats on Freq-Space representations and not on TFR. Since clusterplot was not handling this case, probably because it is made to search across time and space for a given frequency, I ran freqstats/clusterplot separately for each frequency. So just to make sure I understood correctly, you are saying either I use 'cfg.avgoverfreq=yes' especially for lower frequencies and then use clusterplot OR do it separately for each frequency but use multiplotTFR instead. But it seems like I can also use clusterplot separately for each frequency, right? It seemed to work fine. May be I am missing some obvious point here. Please let me know. Another thing that might be of interest to other people that I noticed recently is that neighbourdist measures distance in meters when the ELP (sensor location) file is created using BESA for EEG data. Thus a default value of 4 cm is considered as 4 m and hence all the available channels become neighbors for each channel. Thus I had to use a value of 0.1 for neighbourdist, which takes 6 neighbour channels into account. I think that is roughly equivalent to the default value of 4 cm. Regards, Manish On Mon, Jun 29, 2009 at 3:09 PM, Ingrid Nieuwenhuis wrote: > Dear Manish, > > (I reply to the list again, than everyone can benefit). > That depends on what you want to test. If you have multiple frequencies in > your freq-data, and you just call freqanalysis, and you do not average over > specific frequency range, then clusterplot will look for clusters in the > time-frequency-place domain. This does not always make sense, for instance > in the lower frequencies we know that there are different frequency bands > that behave totally different (theta and alpha for instance). Then you can > better run freqanalysis for these frequencies separately (choose only 10Hz > for alpha, or choose 8:12 Hz and cfg.avgoverfreq = 'yes'). In this case you > can use clusterplot to visualize. > > If you have no idea which frequencies behave the same, or that is something > you are actually interested in (for instance you have a broadbanded high > gamma in your TFR) you can put freq-data with multiple frequencies in > freqanalysis and look at the cluster that comes out. This is a valid thing > to do, but you can only not use clusterplot to visualize then. What you can > do is plot with multiplotTFR with mask settings (cfg.zparam = 'stat', > cfg.maskparam = 'mask'). > > Best Ingrid > >> -----Original Message----- >> From: Manish Saggar [mailto:manish.saggar at gmail.com] >> Sent: Monday, June 29, 2009 7:49 PM >> To: ingrid.nieuwenhuis at donders.ru.nl >> Subject: Re: [FIELDTRIP] Clusterplot not highlighting clusters & average >> layout file >> >> Dear Ingrid, >> >> Thanks for your reply. Sorry I was out and didn't get a chance to reply >> back. >> >> Last question regarding your reply, can I simply run freqstats and >> clusterplot for each frequency separately? >> >> Regards, >> Manish >> >> On Fri, May 22, 2009 at 9:39 AM, Ingrid >> Nieuwenhuis wrote: >> > Dear Manish, >> > >> > If I understand correctly you have multiple frequencies over which you >> > cluster. Is that correct? (so cfg.avgoverfreq = 'no' when you called >> > freqstatistics?) In that case you should not call clusterplot because >> for >> > different frequencies there can be different channels part of the >> cluster. >> > Instead you can call multiplotER or multiplotTFR and use >> cfg.maskparameter = >> > 'mask' to plot the significant cluster. >> > >> > Hope this helps, >> > Ingrid >> > >> > >> >> -----Original Message----- >> >> From: Manish Saggar [mailto:manish.saggar at gmail.com] >> >> Sent: Friday, May 15, 2009 8:26 AM >> >> To: ingrid.nieuwenhuis at donders.ru.nl >> >> Cc: FIELDTRIP at NIC.SURFNET.NL >> >> Subject: Re: [FIELDTRIP] Clusterplot not highlighting clusters & >> average >> >> layout file >> >> >> >> Ingrid, thanks for replying back. >> >> >> >> Apologies for lack of information. >> >> >> >> Clusterplot is plotting clusters fine most of the times, but in some >> >> cases it doesn't choose to highlight markers. I have attached two such >> >> images with this email. >> >> >> >> I do not get any errors or warnings. In fact the command window in >> >> matlab says, cluster found (with some prob and highlighter sign) and >> >> then the plot doesn't contain any highlighting. >> >> Initially I thought that my layout file might be messing it up or >> >> something, or may be I need to take an average layout file for group >> >> analysis (since cap size and electrode digitization varies for each >> >> subject). >> >> >> >> Then I put debug points in the code and found out that at line 235 the >> >> list cell (used to denote highlighted points) is empty. I am a novice >> >> so please forgive if what I am suggesting is dumb here, but I think >> >> when cluster plot is searching for significant clusters it is only >> >> looking into first column (which could correspond to first frequency >> >> in band) if one cluster is found by freqstats. It might be that in the >> >> code you guys are sorting columns and I might have missed it. But I >> >> thought I should clear this with you. >> >> >> >> In another thread you have mentioned to someone that their time limits >> >> might not be precise enough to get the clusers highlighted >> >> >> (https://listserv.surfnet.nl/scripts/wa.cgi?A2=ind0709&L=FIELDTRIP&P=R680 >> >> ). But they were doing time-freq analysis and I am just doing freq- >> >> representations. So should I use freqstats on each freq separately ? >> >> >> >> On a side note, when I run freqstats on my data (with 88 channels) >> >> command line says '89 neighbors per channel found'. I am a little >> >> confused with this. First since I only have less than 88 channels in >> >> the data and second since it should only consider a lower number for >> >> neighbor distance, right? and how can I change it? >> >> >> >> Thanks a ton in advance, >> >> Manish >> >> >> >> On May 13, 2009, at 2:10 AM, Ingrid Nieuwenhuis wrote: >> >> >> >> > Dear Manish, >> >> > >> >> > You give a bit too few information to be able to figure out what >> >> > could be >> >> > the problem with clusterplot. After calling clusterplot, clusterplot >> >> > gives >> >> > information on which clusters it finds. Does the function find any >> >> > clusters? >> >> > Does the .mask field of the structure that comes out of >> freqstatistics >> >> > contain any ones? Is everything else plotted normally? Do you get >> >> > any errors >> >> > or warnings? >> >> > >> >> > I'm not familiar with BESA layout files, but assuming that all >> >> > layout files >> >> > are similar over subjects, I think it is fine to just use an >> >> > individual >> >> > subject's layout file. >> >> > >> >> > Hope this helps, >> >> > Best Ingrid >> >> > >> >> > >> >> >>  ---Original Message----- >> >> >> From: FieldTrip discussion list [mailto:FIELDTRIP at NIC.SURFNET.NL] On >> >> >> Behalf Of Manish Saggar >> >> >> Sent: Tuesday, May 12, 2009 10:17 AM >> >> >> To: FIELDTRIP at NIC.SURFNET.NL >> >> >> Subject: [FIELDTRIP] Clusterplot not highlighting clusters & average >> >> >> layout file >> >> >> >> >> >> All, >> >> >> >> >> >> I have a question regarding clusterplot function. I am doing a >> >> >> within-subject analysis. >> >> >> The experimental design that I have is as follows, there are three >> >> >> conditions C1, C2 and C3. Each condition is of 1 min duration (e.g. >> >> >> rest with eyes open for 1 min). >> >> >> >> >> >> Now I am comparing grandaverage of freq representation of a set of >> >> >> subjects for C2 with C1 etc. FreqStatistics is running just fine >> >> >> creating significant (<0.025 alpha, for 2-tailed test) clusters >> >> >> (positive). Now the problem is that when I try to plot the location >> >> >> of >> >> >> this cluster using clusterplot it doesn't show any highlighted >> >> >> channels. Any ideas why that is happening? >> >> >> >> >> >> Another question is that since I am using grandaverages of freq >> >> >> representation, what should I use for layout file (using BESA sfp >> >> >> file >> >> >> here). I have individual subject layout files. Currently I am just >> >> >> giving any file from one of the subjects. Since, I noticed that >> >> >> FreqStatistics finds a common minimum set of channels and then apply >> >> >> statistics on it. So do I need to average layout files for the >> >> >> subject >> >> >> group or is there any other way? >> >> >> >> >> >> Any help is much appreciated. >> >> >> >> >> >> Regards, >> >> >> Manish >> >> >> >> >> >> ---------------------------------- >> >> >> The aim of this list is to facilitate the discussion between users >> >> >> of the >> >> >> FieldTrip  toolbox, to share experiences and to discuss new ideas >> >> >> for MEG >> >> >> and EEG analysis. See also >> >> >> http://listserv.surfnet.nl/archives/fieldtrip.html and >> >> >> http://www.ru.nl/neuroimaging/fieldtrip. >> >> > >> >> > ---------------------------------- >> >> > The aim of this list is to facilitate the discussion between users >> >> > of the FieldTrip  toolbox, to share experiences and to discuss new >> >> > ideas for MEG and EEG analysis. See also >> >> http://listserv.surfnet.nl/archives/fieldtrip.html >> >> >  and http://www.ru.nl/neuroimaging/fieldtrip. >> >> >> > >> > >> > >> > > > > > ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From r.oostenveld at FCDONDERS.RU.NL Tue Jun 30 13:09:59 2009 From: r.oostenveld at FCDONDERS.RU.NL (Robert Oostenveld) Date: Tue, 30 Jun 2009 13:09:59 +0200 Subject: job opportunity in Oxford: (postdoctoral) research assistants Message-ID: ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Current Job Vacancies Personnel Services Postdoctoral Research Assistants in Biomedical Engineering (eight posts) DEPARTMENT OF ENGINEERING SCIENCE Grade 7: Salary £28,839 p.a. We are seeking to appoint eight Postdoctoral Research Assistants in the following areas: Monitoring for health (fetal/neonatal imaging, deep brain stimulation); targeting drug delivery for cancer (which includes both imaging and ultrasound activation of nanoparticles); and treating cerebrovascular disease (physiological modelling in stroke and stent design for aneurysms). Based at the department’s Institute of Biomedical Engineering, Headington, Oxford, you will be part of a programme of expansion to increase the institute’s ability to develop novel medical devices, technology and systems capable of delivering substantial healthcare benefits through personalised monitoring and/or treatment. Appointments will be for three years initially, with the possibility of renewal for two further years. You will hold a doctorate (or equivalent) in engineering, physics, computer science, or mathematics and have experience in the relevant area of research (biomedical engineering), ideally at the postgraduate level. Details of the individual posts available and their selection criteria, including details of how to apply, are available from our website: http://www.eng.ox.ac.uk/jobs/, or by emailing: administrator at eng.ox.ac.uk . The closing date for applications is midday on Wednesday 15 July 2009. University of Oxford > University Administration and Services > Personnel Services Maintained by: Personnel Services webmaster Last modified: 25 June 2009 © 2009, University of Oxford. Enquiries to Webmaster ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Current Job Vacancies Personnel Services Research Assistants in Biomedical Engieering (five posts) DEPARTMENT OF ENGINEERING SCIENCE Grade 6: Salary £25,623 p.a. We are seeking to appoint five Research Assistants to work in the following areas: Monitoring for health (fetal/neonatal imaging, deep brain stimulation); targeting drug delivery for cancer (which includes both imaging and ultrasound activation of nanoparticles); and treating cerebrovascular disease (physiological modelling in stroke and stent design for aneurysms). Based at the department’s Institute of Biomedical Engineering, Headington, Oxford, you will be part of a programme of expansion to increase the institute’s ability to develop novel medical devices, technology and systems capable of delivering substantial healthcare benefits through personalised monitoring and/or treatment. Appointments will be for two years, with the possibility of renewal for one further year. You will hold a good honours degree (2:1 or above, or equivalent) in engineering, physics, computer science or mathematics and have sufficient postgraduate experience to be able to work within an established biomedical engineering research programme. Details of the individual posts available and their selection criteria, including details of how to apply, are available from our website: http://www.eng.ox.ac.uk/jobs/, or by emailing: administrator at eng.ox.ac.uk . The closing date for applications is midday on Wednesday 15 July 2009. University of Oxford > University Administration and Services > Personnel Services Maintained by: Personnel Services webmaster Last modified: 25 June 2009 © 2009, University of Oxford. Enquiries to Webmaster ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: DF09035fps.pdf Type: application/pdf Size: 217695 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: DF09036fps.pdf Type: application/pdf Size: 220080 bytes Desc: not available URL: -------------- next part -------------- ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. From ole.jensen at DONDERS.RU.NL Tue Jun 30 21:55:52 2009 From: ole.jensen at DONDERS.RU.NL (Ole Jensen) Date: Tue, 30 Jun 2009 21:55:52 +0200 Subject: MEG lunch at HBM2009/minutes Message-ID: Dear all, Attached please find the minutes from the MEG lunch at the HBM2009 meeting. All the best, Ole -- Ole Jensen Principal Investigator Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging P.O. Box 9101 NL-6500 HB Nijmegen The Netherlands Office : +31 24 36 10884 MEG lab : +31 24 36 10988 Fax : +31 24 36 10989 e-mail : ole.jensen at donders.ru.nl URL : http://ojensen.ruhosting.nl/ ---------------------------------- The aim of this list is to facilitate the discussion between users of the FieldTrip toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip. -------------- next part -------------- A non-text attachment was scrubbed... Name: minutesMEGlunch.pdf Type: application/pdf Size: 14819 bytes Desc: not available URL: