From anapesquita at gmail.com Fri Feb 1 21:30:03 2019 From: anapesquita at gmail.com (Ana Pesquita) Date: Fri, 1 Feb 2019 20:30:03 +0000 Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) Message-ID: Hello, My name is Ana and I have recently started using Fieldtrip. I am trying to adapt the fieldtrip tutorial - 'Cluster-based permutation tests on time-frequency data' - to my particular case ( http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/). I have data from one MEG subject recorded in an Elekta Neuromag system and would like to do a within trials analysis on that subject (experimental trials vs. control trials). However, my ft_freqstatistics outputs a matrix stat.stat full of NaNs. I am hoping to get some help with identifying the error in my pipeline. These are my steps: *1. I start by loading the two data structures corresponding to the Exp and Ctr trials (selecting only the gradiometer channels).* *Data fields*: data_Exp = struct with fields: label: {202×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] data_Ctr = struct with fields: label: {202×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] *3. Run the frequency analysis on both data structures. * *CFG*: cfg = []; cfg.output = 'pow'; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.taper = 'hanning'; cfg.method = 'mtmconvol'; cfg.foi = 10;%2:2:30;%1:30 numfoi = length(cfg.foi); cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5;%1; cfg.toi = [-1 : 0.05: 3.6]; cfg.keeptrials = 'yes'; tfr_data_Exp = ft_freqanalysis(cfg, data_Exp); cfg = []; cfg.output = 'pow'; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.taper = 'hanning'; cfg.method = 'mtmconvol'; cfg.foi = 10; %2:2:30; numfoi = length(cfg.foi); cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5; cfg.toi = [-1 : 0.05: 3.6]; cfg.keeptrials = 'yes'; tfr_data_Ctr = ft_freqanalysis(cfg, data_Ctr); *Data fields:* e.g. (and similar to the structure of tfr_data_Exp) tfr_data_Ctr = struct with fields: label: {202×1 cell} dimord: 'rpt_chan_freq_time' freq: 10.0000 time: [1×93 double] powspctrm: [90×202×1×93 double] cumtapcnt: [90×1 double] grad: [1×1 struct] trialinfo: [90×1 double] cfg: [1×1 struct] *3. Combine planar gradiometers of the time-frequency data (e.g. tfr_data_Exp)* *CFG*: cfg = []; cfg.method = 'sum'; freqEXP_planar_cmb = ft_combineplanar(cfg,tfr_data_Exp); cfg = []; cfg.method = 'sum'; freqCTR_planar_cmb = ft_combineplanar(cfg,tfr_data_Ctr); *Data fields:* e.g. (and similar to the structure of freqEXP_planar_cm) freqCTR_planar_cmb = struct with fields: label: {102×1 cell} dimord: 'rpt_chan_freq_time' freq: 10.0000 time: [1×93 double] powspctrm: [90×102×1×93 double] cumtapcnt: [90×1 double] grad: [1×1 struct] trialinfo: [90×1 double] cfg: [1×1 struct] *4. Combine planar gradiometers also for the initial data structures (i.e. data_Exp )* *CFG*: cfg = []; cfg.method = 'sum'; data_Exp_cmb = ft_combineplanar(cfg,data_Exp); *Data fields:* data_Exp_cmb = struct with fields: label: {102×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] *5. Prepare neighbours, design, and run ft_freqstatistics* *CFG*: cfg = []; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.latency = 'all'; cfg.frequency = 10; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.minnbchan = 2; cfg.tail = 0; cfg.clustertail = 0; cfg.alpha = 0.025; cfg.numrandomization = 500; % prepare_neighbours determines what sensors may form clusters cfg_neighb.method = 'distance'; cfg_neighb.template = 'neuromag306plan.mat'; cfg.neighbours = ft_prepare_neighbours(cfg_neighb, *data_Exp_cmb*); design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + size(freqEXP_planar_cmb.powspctrm,1)); design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1; design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size(freqCTR_planar_cmb,1)+... size(freqEXP_planar_cmb.powspctrm,1))) = 2; cfg.design = design; cfg.ivar = 1; [stat] = ft_freqstatistics(cfg, *freqCTR_planar_cmb, freqEXP_planar_cmb*); *Data fields:* stat.stat is a matrix full of NaN stat.prob is a matrix of just ones stat = struct with fields: stat: [102×1×93 double] prob: [102×1×93 double] cirange: [102×1×93 double] mask: [102×1×93 logical] ref: [102×1×93 double] dimord: 'chan_freq_time' freq: 10.0000 grad: [1×1 struct] label: {102×1 cell} time: [1×93 double] cfg: [1×1 struct] *Warning:* When running the ft_frestatistics I get the repeated warning: (...) Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computing statistic 498 from 0 Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computing statistic 500 from 0 (...) Many many thanks! Ana -------------- next part -------------- An HTML attachment was scrubbed... URL: From R.Mehraram2 at newcastle.ac.uk Sun Feb 3 18:22:44 2019 From: R.Mehraram2 at newcastle.ac.uk (Ramtin Mehraram (Student)) Date: Sun, 3 Feb 2019 17:22:44 +0000 Subject: [FieldTrip] cfg.channel "ignored" in ft_freqanalysis References: Message-ID: Dear all, I am simply trying to select few channels to run ft_freqanalysis by listing those channels in cfg.channel as a cell array. However, the function keeps selecting all the channels. Any ideas? Many thanks Kind regards Ramtin Mehraram PhD Student @ramtinTVT Biomedical Research Building 3rd floor Institute of Neuroscience Newcastle University NE4 5PL, United Kingdom www.lewybodylab.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From R.Mehraram2 at newcastle.ac.uk Sun Feb 3 19:18:57 2019 From: R.Mehraram2 at newcastle.ac.uk (Ramtin Mehraram (Student)) Date: Sun, 3 Feb 2019 18:18:57 +0000 Subject: [FieldTrip] R: cfg.channel "ignored" in ft_freqanalysis In-Reply-To: References: Message-ID: Please ignore my question. I was confused by Fieldtrip showing in the command window the total number of channels as input as I run the function/script anyways. In fact, the channel selection happens in a subsequent step. Apologies. [signature] Ramtin Mehraram Da: fieldtrip Per conto di Ramtin Mehraram (Student) Inviato: domenica 3 febbraio 2019 17:23 A: fieldtrip at science.ru.nl Oggetto: [FieldTrip] cfg.channel "ignored" in ft_freqanalysis Dear all, I am simply trying to select few channels to run ft_freqanalysis by listing those channels in cfg.channel as a cell array. However, the function keeps selecting all the channels. Any ideas? Many thanks Kind regards Ramtin Mehraram PhD Student @ramtinTVT Biomedical Research Building 3rd floor Institute of Neuroscience Newcastle University NE4 5PL, United Kingdom www.lewybodylab.org -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 8752 bytes Desc: image001.png URL: From bick35 at gmail.com Mon Feb 4 01:52:46 2019 From: bick35 at gmail.com (Steph bick) Date: Mon, 4 Feb 2019 00:52:46 +0000 Subject: [FieldTrip] Postdoc positions in ECoG lab in NY Message-ID: Dear all, Two postdoc positions are available in the ECoG Laboratory for Human Brain Mapping at the Feinstein Institute for Medical Research – Hofstra Northwell School of Medicine, NY USA. The lab works exclusively with patients being evaluated for epilepsy surgery using intracranial electrodes (depth or strips/grids, micro-wires for single unit recordings). The laboratory also uses invasive and non-invasive electrical stimulation, eye tracking, and imaging (MRI, fMRI, DTI) to study the patients. Research topics include the investigation of neuronal dynamics underlying selective attention and active sensing, auditory stream and speech analysis, and neural correlates of object identification. However, one position is geared towards someone with a background in fMRI processing who is interested in investigating electrophysiological correlates of BOLD dynamics. The ideal candidate has a PhD in neuroscience, biomedical engineering, psychology, or a related field. She/he should have a solid background in signal processing (either EEG/MEG, ECoG, or fMRI), programming (Matlab or Python), statistics, and scientific writing. She/he should be comfortable working in a lab where there is interaction with clinical environments. Some supervision and mentoring of research assistants and students is expected. The positions are funded by NIH grants, 2 years guaranteed, with expected start date as soon as possible. The candidate will have ample opportunities to work closely with national and international collaborators. If you would like further information please send your questions to Stephan Bickel, MD PhD (sbickel at northwell.edu) and Ashesh Mehta, MD PhD (amehta at northwell.edu). If you would like to apply, please send your CV, and names and contacts of 2-3 references (ideally researchers). We are looking forward to hearing from you! _________________________________________ Stephan Bickel, MD PhD Assistant Professor of Neurology Donald and Barbara Zucker School of Medicine at Hofstra / Northwell Feinstein Institute for Medical Research Attending Physician Hofstra Northwell Comprehensive Epilepsy Center sbickel at northwell.edu -------------- next part -------------- An HTML attachment was scrubbed... URL: From ksarmuk2 at une.edu.au Mon Feb 4 02:13:02 2019 From: ksarmuk2 at une.edu.au (Kimaya Sarmukadam) Date: Mon, 4 Feb 2019 01:13:02 +0000 Subject: [FieldTrip] Granger Causality - different range of values based on conditions Message-ID: Dear Fiedtrippers, I have been using the following code to calculate Granger Causality, across various conditions (ranging from 2.5 to 3 minutes long, 4 second epochs). cfg = []; cfg.output = 'fourier'; cfg.method = 'mtmfft'; cfg.channel = {'Fp1', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FT7', 'FC3', 'FCz', 'FC4', 'FT8', 'O1', 'Oz', 'O2', 'T7', 'T8', 'TP7', 'TP8'}; cfg.taper = 'dpss'; cfg.tapsmofrq = 5; cfg.pad = 'maxperlen'; cfg.padtype = 'zero'; cfg.foilim = [13 30]; cfg = []; cfg.method = 'granger'; cfg.granger.method = 'bivariate'; %cfg.hasjack = '0'; grangerEC = ft_connectivityanalysis(cfg, freqEC); cfg = []; cfg.parameter = 'grangerspctrm'; cfg.zlim = [0 1]; ft_connectivityplot(cfg, grangerEC); For two conditions, the above code was able to evaluate granger causality between 0 and 1. However, for other conditions I am working on currently, the resulting values range from 0 to 4. Therefore, I was wondering whether there is an error in the code which does not pick up certain data for other conditions. Below is a visual representation: [cid:5b0676da-26fa-4371-9aef-d945d1139572] Any help would be greatly appreciated. Kind regards, Kimaya Sarmukadam -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: pastedImage.png Type: image/png Size: 104803 bytes Desc: pastedImage.png URL: From jan.schoffelen at donders.ru.nl Mon Feb 4 09:13:06 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 4 Feb 2019 08:13:06 +0000 Subject: [FieldTrip] Granger Causality - different range of values based on conditions In-Reply-To: References: Message-ID: <1A99E2FD-830F-4013-AA38-6BB77C2DDC27@donders.ru.nl> Hi Kimaya, In general I would strongly recommend against estimating and interpreting connectivity using channel level EEG data. There is simply too much linear mixing going on that prohibits a clean enough estimate and honest interpretation. If you wish to insist, however, please note that: 1) Granger causality values in principle do not have an upper bound (i.e. mathematically it is possible that GC>1, although in my experience this hardly ever happens in real data). 2) In order to get a mathematically valid estimate of GC using non-parametric spectral factorization, you need to compute the spectrum (in ft_freqanalysis) with the full frequency range, i.e. from 0 Hz to the Nyquist frequency. The frequency range you have used [13 30] is inadequate. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 4 Feb 2019, at 02:13, Kimaya Sarmukadam > wrote: Dear Fiedtrippers, I have been using the following code to calculate Granger Causality, across various conditions (ranging from 2.5 to 3 minutes long, 4 second epochs). cfg = []; cfg.output = 'fourier'; cfg.method = 'mtmfft'; cfg.channel = {'Fp1', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FT7', 'FC3', 'FCz', 'FC4', 'FT8', 'O1', 'Oz', 'O2', 'T7', 'T8', 'TP7', 'TP8'}; cfg.taper = 'dpss'; cfg.tapsmofrq = 5; cfg.pad = 'maxperlen'; cfg.padtype = 'zero'; cfg.foilim = [13 30]; cfg = []; cfg.method = 'granger'; cfg.granger.method = 'bivariate'; %cfg.hasjack = '0'; grangerEC = ft_connectivityanalysis(cfg, freqEC); cfg = []; cfg.parameter = 'grangerspctrm'; cfg.zlim = [0 1]; ft_connectivityplot(cfg, grangerEC); For two conditions, the above code was able to evaluate granger causality between 0 and 1. However, for other conditions I am working on currently, the resulting values range from 0 to 4. Therefore, I was wondering whether there is an error in the code which does not pick up certain data for other conditions. Below is a visual representation: Any help would be greatly appreciated. Kind regards, Kimaya Sarmukadam _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From S.Arana at donders.ru.nl Mon Feb 4 10:46:05 2019 From: S.Arana at donders.ru.nl (Arana, S.L. (Sophie)) Date: Mon, 4 Feb 2019 09:46:05 +0000 Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) In-Reply-To: References: Message-ID: <1549273565463.38825@donders.ru.nl> Hi Ana, I see one small mistake in your code, that might be causing your error message. It is in the way you define your design matrix. It should be design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + size(freqEXP_planar_cmb.powspctrm,1)); design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1;​ design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size(freqCTR_planar_cmb.powspctrm,1)+... size(freqEXP_planar_cmb.powspctrm,1))) = 2; Hope this will fix your issue. Best, Sophie ___________________ M.Sc. Sophie L. Arana Doctoral researcher Neurobiology of Language - MPI for Psycholinguistics Max Planck Institute for Psycholinguistics PO Box 310, 6500 AH Nijmegen Netherlands T +31 24-3610887 E sophie.arana at mpi.nl ________________________________ From: fieldtrip on behalf of Ana Pesquita Sent: Friday, February 1, 2019 9:30 PM To: fieldtrip at science.ru.nl Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) Hello, My name is Ana and I have recently started using Fieldtrip. I am trying to adapt the fieldtrip tutorial - 'Cluster-based permutation tests on time-frequency data' - to my particular case ( http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/). I have data from one MEG subject recorded in an Elekta Neuromag system and would like to do a within trials analysis on that subject (experimental trials vs. control trials). However, my ft_freqstatistics outputs a matrix stat.stat full of NaNs. I am hoping to get some help with identifying the error in my pipeline. These are my steps: 1. I start by loading the two data structures corresponding to the Exp and Ctr trials (selecting only the gradiometer channels). Data fields: data_Exp = struct with fields: label: {202×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] data_Ctr = struct with fields: label: {202×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] 3. Run the frequency analysis on both data structures. CFG: cfg = []; cfg.output = 'pow'; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.taper = 'hanning'; cfg.method = 'mtmconvol'; cfg.foi = 10;%2:2:30;%1:30 numfoi = length(cfg.foi); cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5;%1; cfg.toi = [-1 : 0.05: 3.6]; cfg.keeptrials = 'yes'; tfr_data_Exp = ft_freqanalysis(cfg, data_Exp); cfg = []; cfg.output = 'pow'; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.taper = 'hanning'; cfg.method = 'mtmconvol'; cfg.foi = 10; %2:2:30; numfoi = length(cfg.foi); cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5; cfg.toi = [-1 : 0.05: 3.6]; cfg.keeptrials = 'yes'; tfr_data_Ctr = ft_freqanalysis(cfg, data_Ctr); Data fields: e.g. (and similar to the structure of tfr_data_Exp) tfr_data_Ctr = struct with fields: label: {202×1 cell} dimord: 'rpt_chan_freq_time' freq: 10.0000 time: [1×93 double] powspctrm: [90×202×1×93 double] cumtapcnt: [90×1 double] grad: [1×1 struct] trialinfo: [90×1 double] cfg: [1×1 struct] 3. Combine planar gradiometers of the time-frequency data (e.g. tfr_data_Exp) CFG: cfg = []; cfg.method = 'sum'; freqEXP_planar_cmb = ft_combineplanar(cfg,tfr_data_Exp); cfg = []; cfg.method = 'sum'; freqCTR_planar_cmb = ft_combineplanar(cfg,tfr_data_Ctr); Data fields: e.g. (and similar to the structure of freqEXP_planar_cm) freqCTR_planar_cmb = struct with fields: label: {102×1 cell} dimord: 'rpt_chan_freq_time' freq: 10.0000 time: [1×93 double] powspctrm: [90×102×1×93 double] cumtapcnt: [90×1 double] grad: [1×1 struct] trialinfo: [90×1 double] cfg: [1×1 struct] 4. Combine planar gradiometers also for the initial data structures (i.e. data_Exp ) CFG: cfg = []; cfg.method = 'sum'; data_Exp_cmb = ft_combineplanar(cfg,data_Exp); Data fields: data_Exp_cmb = struct with fields: label: {102×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] 5. Prepare neighbours, design, and run ft_freqstatistics CFG: cfg = []; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.latency = 'all'; cfg.frequency = 10; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.minnbchan = 2; cfg.tail = 0; cfg.clustertail = 0; cfg.alpha = 0.025; cfg.numrandomization = 500; % prepare_neighbours determines what sensors may form clusters cfg_neighb.method = 'distance'; cfg_neighb.template = 'neuromag306plan.mat'; cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_Exp_cmb); design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + size(freqEXP_planar_cmb.powspctrm,1)); design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1; design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size(freqCTR_planar_cmb,1)+... size(freqEXP_planar_cmb.powspctrm,1))) = 2; cfg.design = design; cfg.ivar = 1; [stat] = ft_freqstatistics(cfg, freqCTR_planar_cmb, freqEXP_planar_cmb); Data fields: stat.stat is a matrix full of NaN stat.prob is a matrix of just ones stat = struct with fields: stat: [102×1×93 double] prob: [102×1×93 double] cirange: [102×1×93 double] mask: [102×1×93 logical] ref: [102×1×93 double] dimord: 'chan_freq_time' freq: 10.0000 grad: [1×1 struct] label: {102×1 cell} time: [1×93 double] cfg: [1×1 struct] Warning: When running the ft_frestatistics I get the repeated warning: (...) Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computing statistic 498 from 0 Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computing statistic 500 from 0 (...) Many many thanks! Ana -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Feb 4 11:09:00 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 4 Feb 2019 10:09:00 +0000 Subject: [FieldTrip] Fwd: Granger Causality - different range of values based on conditions References: Message-ID: Begin forwarded message: From: Kimaya Sarmukadam > Subject: Fw: [FieldTrip] Granger Causality - different range of values based on conditions Date: 4 February 2019 at 11:07:55 GMT+1 To: "jan.schoffelen at donders.ru.nl" > Hi Jan-Mathijs, Thank you for your response. After posting, I also realised that frequency range was wrong and extending the frequency range has given me comparable values to the other conditions. For one part of my PhD thesis, I will be comparing functional and effective connectivity measures using the same data set. As I am more interested in comparisons between the methods, in your experience, is it possible to still derive meaningful data from sensor level connectivity? Thank you again! Kind regards, Kimaya ________________________________ From: fieldtrip > on behalf of Schoffelen, J.M. (Jan Mathijs) > Sent: Monday, 4 February 2019 6:13 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] Granger Causality - different range of values based on conditions Hi Kimaya, In general I would strongly recommend against estimating and interpreting connectivity using channel level EEG data. There is simply too much linear mixing going on that prohibits a clean enough estimate and honest interpretation. If you wish to insist, however, please note that: 1) Granger causality values in principle do not have an upper bound (i.e. mathematically it is possible that GC>1, although in my experience this hardly ever happens in real data). 2) In order to get a mathematically valid estimate of GC using non-parametric spectral factorization, you need to compute the spectrum (in ft_freqanalysis) with the full frequency range, i.e. from 0 Hz to the Nyquist frequency. The frequency range you have used [13 30] is inadequate. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 4 Feb 2019, at 02:13, Kimaya Sarmukadam > wrote: Dear Fiedtrippers, I have been using the following code to calculate Granger Causality, across various conditions (ranging from 2.5 to 3 minutes long, 4 second epochs). cfg = []; cfg.output = 'fourier'; cfg.method = 'mtmfft'; cfg.channel = {'Fp1', 'Fp2', 'F7', 'F3', 'Fz', 'F4', 'F8', 'FT7', 'FC3', 'FCz', 'FC4', 'FT8', 'O1', 'Oz', 'O2', 'T7', 'T8', 'TP7', 'TP8'}; cfg.taper = 'dpss'; cfg.tapsmofrq = 5; cfg.pad = 'maxperlen'; cfg.padtype = 'zero'; cfg.foilim = [13 30]; cfg = []; cfg.method = 'granger'; cfg.granger.method = 'bivariate'; %cfg.hasjack = '0'; grangerEC = ft_connectivityanalysis(cfg, freqEC); cfg = []; cfg.parameter = 'grangerspctrm'; cfg.zlim = [0 1]; ft_connectivityplot(cfg, grangerEC); For two conditions, the above code was able to evaluate granger causality between 0 and 1. However, for other conditions I am working on currently, the resulting values range from 0 to 4. Therefore, I was wondering whether there is an error in the code which does not pick up certain data for other conditions. Below is a visual representation: Any help would be greatly appreciated. Kind regards, Kimaya Sarmukadam _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From taravanviegen at gmail.com Mon Feb 4 12:19:08 2019 From: taravanviegen at gmail.com (Tara van Viegen) Date: Mon, 4 Feb 2019 11:19:08 +0000 Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) In-Reply-To: <1549273565463.38825@donders.ru.nl> References: <1549273565463.38825@donders.ru.nl> Message-ID: Hi both, I don't think that causes the problem, because from my understanding the powspctrm fields are the same size for both TFR structures. Ana, are there NaNs in your powspctrm? (Just trying to figure out if there might already be an issue *before *the call to ft_freqstatistics). Best, Tara On Mon, Feb 4, 2019 at 10:35 AM Arana, S.L. (Sophie) wrote: > Hi Ana, > > > I see one small mistake in your code, that might be causing your error > message. It is in the way you define your design matrix. It should be > > design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + > size(freqEXP_planar_cmb.powspctrm,1)); > design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1;​ > > > design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size( > *freqCTR_planar_cmb.powspctrm*,1)+... > size(freqEXP_planar_cmb.powspctrm,1))) = 2; > > > Hope this will fix your issue. > > > Best, > > Sophie > ___________________ > M.Sc. Sophie L. Arana > > Doctoral researcher > Neurobiology of Language - MPI for Psycholinguistics > > Max Planck Institute for Psycholinguistics > PO Box 310, 6500 AH Nijmegen > Netherlands > > T +31 24-3610887 > E sophie.arana at mpi.nl > > > > ------------------------------ > *From:* fieldtrip on behalf of Ana > Pesquita > *Sent:* Friday, February 1, 2019 9:30 PM > *To:* fieldtrip at science.ru.nl > *Subject:* [FieldTrip] Help with between-trials single subject > permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) > > Hello, > > My name is Ana and I have recently started using Fieldtrip. > I am trying to adapt the fieldtrip tutorial - 'Cluster-based permutation > tests on time-frequency data' - to my particular case ( > http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/). > > I have data from one MEG subject recorded in an Elekta Neuromag system and > would like to do a within trials analysis on that subject (experimental > trials vs. control trials). However, my ft_freqstatistics outputs a > matrix stat.stat full of NaNs. > I am hoping to get some help with identifying the error in my pipeline. > > These are my steps: > > *1. I start by loading the two data structures corresponding to the Exp > and Ctr trials (selecting only the gradiometer channels).* > *Data fields*: > data_Exp = > struct with fields: > label: {202×1 cell} > trialinfo: [90×1 double] > sampleinfo: [90×2 double] > trial: {1×90 cell} > time: {1×90 cell} > cfg: [1×1 struct] > fsample: 1.0000e+03 > grad: [1×1 struct] > > data_Ctr = > struct with fields: > label: {202×1 cell} > trialinfo: [90×1 double] > sampleinfo: [90×2 double] > trial: {1×90 cell} > time: {1×90 cell} > cfg: [1×1 struct] > fsample: 1.0000e+03 > grad: [1×1 struct] > > *3. Run the frequency analysis on both data structures. * > *CFG*: > cfg = []; > cfg.output = 'pow'; > cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; > cfg.taper = 'hanning'; > cfg.method = 'mtmconvol'; > cfg.foi = 10;%2:2:30;%1:30 > numfoi = length(cfg.foi); > cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5;%1; > cfg.toi = [-1 : 0.05: 3.6]; > cfg.keeptrials = 'yes'; > tfr_data_Exp = ft_freqanalysis(cfg, data_Exp); > > cfg = []; > cfg.output = 'pow'; > cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; > cfg.taper = 'hanning'; > cfg.method = 'mtmconvol'; > cfg.foi = 10; %2:2:30; > numfoi = length(cfg.foi); > cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5; > cfg.toi = [-1 : 0.05: 3.6]; > cfg.keeptrials = 'yes'; > tfr_data_Ctr = ft_freqanalysis(cfg, data_Ctr); > > *Data fields:* > e.g. (and similar to the structure of tfr_data_Exp) > tfr_data_Ctr = > struct with fields: > label: {202×1 cell} > dimord: 'rpt_chan_freq_time' > freq: 10.0000 > time: [1×93 double] > powspctrm: [90×202×1×93 double] > cumtapcnt: [90×1 double] > grad: [1×1 struct] > trialinfo: [90×1 double] > cfg: [1×1 struct] > > *3. Combine planar gradiometers of the time-frequency data (e.g. > tfr_data_Exp)* > *CFG*: > cfg = []; > cfg.method = 'sum'; > freqEXP_planar_cmb = ft_combineplanar(cfg,tfr_data_Exp); > > cfg = []; > cfg.method = 'sum'; > freqCTR_planar_cmb = ft_combineplanar(cfg,tfr_data_Ctr); > > *Data fields:* > e.g. (and similar to the structure of freqEXP_planar_cm) > freqCTR_planar_cmb = > struct with fields: > label: {102×1 cell} > dimord: 'rpt_chan_freq_time' > freq: 10.0000 > time: [1×93 double] > powspctrm: [90×102×1×93 double] > cumtapcnt: [90×1 double] > grad: [1×1 struct] > trialinfo: [90×1 double] > cfg: [1×1 struct] > > *4. Combine planar gradiometers also for the initial data structures > (i.e. data_Exp )* > *CFG*: > cfg = []; > cfg.method = 'sum'; > data_Exp_cmb = ft_combineplanar(cfg,data_Exp); > > *Data fields:* > data_Exp_cmb = > struct with fields: > label: {102×1 cell} > trialinfo: [90×1 double] > sampleinfo: [90×2 double] > trial: {1×90 cell} > time: {1×90 cell} > cfg: [1×1 struct] > fsample: 1.0000e+03 > grad: [1×1 struct] > > *5. Prepare neighbours, design, and run ft_freqstatistics* > *CFG*: > cfg = []; > cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; > cfg.latency = 'all'; > cfg.frequency = 10; > cfg.method = 'montecarlo'; > cfg.statistic = 'ft_statfun_indepsamplesT'; > cfg.correctm = 'cluster'; > cfg.clusteralpha = 0.05; > cfg.clusterstatistic = 'maxsum'; > cfg.minnbchan = 2; > cfg.tail = 0; > cfg.clustertail = 0; > cfg.alpha = 0.025; > cfg.numrandomization = 500; > % prepare_neighbours determines what sensors may form clusters > cfg_neighb.method = 'distance'; > cfg_neighb.template = 'neuromag306plan.mat'; > cfg.neighbours = ft_prepare_neighbours(cfg_neighb, *data_Exp_cmb*); > > design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + > size(freqEXP_planar_cmb.powspctrm,1)); > design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1; > > design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size(freqCTR_planar_cmb,1)+... > size(freqEXP_planar_cmb.powspctrm,1))) = 2; > > cfg.design = design; > cfg.ivar = 1; > > [stat] = ft_freqstatistics(cfg, *freqCTR_planar_cmb, freqEXP_planar_cmb*); > > *Data fields:* > stat.stat is a matrix full of NaN > > stat.prob is a matrix of just ones > > stat = > struct with fields: > stat: [102×1×93 double] > prob: [102×1×93 double] > cirange: [102×1×93 double] > mask: [102×1×93 logical] > ref: [102×1×93 double] > dimord: 'chan_freq_time' > freq: 10.0000 > grad: [1×1 struct] > label: {102×1 cell} > time: [1×93 double] > cfg: [1×1 struct] > > *Warning:* > When running the ft_frestatistics I get the repeated warning: > > (...) > Warning: Not all replications are used for the computation of the > statistic. > Warning: Not all replications are used for the computation of the > statistic. > Warning: Not all replications are used for the computing statistic 498 > from 0 > Warning: Not all replications are used for the computation of the > statistic. > Warning: Not all replications are used for the computation of the > statistic. > Warning: Not all replications are used for the computing statistic 500 > from 0 > (...) > > > Many many thanks! > > Ana > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: From S.Arana at donders.ru.nl Mon Feb 4 13:16:05 2019 From: S.Arana at donders.ru.nl (Arana, S.L. (Sophie)) Date: Mon, 4 Feb 2019 12:16:05 +0000 Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) In-Reply-To: References: <1549273565463.38825@donders.ru.nl>, Message-ID: <1549282565732.27632@donders.ru.nl> Hi Tara, indeed the powspctrm fields are the same. However, in the code the field 'powspctrm' is missing alltogether so that size(freqCTR_plana_cmb) is simply 1 as that is the size of the structure not the powspctrm field. As Ana is using the ft_statfun_indepsamplesT.m , the design matrix should have the length equivalent to number of trials across both conditions and each trial coded as either 1 or 2 depending on which condition it belongs to. (see http://www.fieldtriptoolbox.org/walkthrough/ for more detailed description of design matrix) Ana's code as far as I can see would lead to an unintended design matrix, containing 0s, which also results in the warning "Not all replications are used ..." Best, Sophie ________________________________ From: fieldtrip on behalf of Tara van Viegen Sent: Monday, February 4, 2019 12:19 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) Hi both, I don't think that causes the problem, because from my understanding the powspctrm fields are the same size for both TFR structures. Ana, are there NaNs in your powspctrm? (Just trying to figure out if there might already be an issue before the call to ft_freqstatistics). Best, Tara On Mon, Feb 4, 2019 at 10:35 AM Arana, S.L. (Sophie) > wrote: Hi Ana, I see one small mistake in your code, that might be causing your error message. It is in the way you define your design matrix. It should be design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + size(freqEXP_planar_cmb.powspctrm,1)); design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1;​ design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size(freqCTR_planar_cmb.powspctrm,1)+... size(freqEXP_planar_cmb.powspctrm,1))) = 2; Hope this will fix your issue. Best, Sophie ___________________ M.Sc. Sophie L. Arana Doctoral researcher Neurobiology of Language - MPI for Psycholinguistics Max Planck Institute for Psycholinguistics PO Box 310, 6500 AH Nijmegen Netherlands T +31 24-3610887 E sophie.arana at mpi.nl ________________________________ From: fieldtrip > on behalf of Ana Pesquita > Sent: Friday, February 1, 2019 9:30 PM To: fieldtrip at science.ru.nl Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) Hello, My name is Ana and I have recently started using Fieldtrip. I am trying to adapt the fieldtrip tutorial - 'Cluster-based permutation tests on time-frequency data' - to my particular case ( http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/). I have data from one MEG subject recorded in an Elekta Neuromag system and would like to do a within trials analysis on that subject (experimental trials vs. control trials). However, my ft_freqstatistics outputs a matrix stat.stat full of NaNs. I am hoping to get some help with identifying the error in my pipeline. These are my steps: 1. I start by loading the two data structures corresponding to the Exp and Ctr trials (selecting only the gradiometer channels). Data fields: data_Exp = struct with fields: label: {202×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] data_Ctr = struct with fields: label: {202×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] 3. Run the frequency analysis on both data structures. CFG: cfg = []; cfg.output = 'pow'; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.taper = 'hanning'; cfg.method = 'mtmconvol'; cfg.foi = 10;%2:2:30;%1:30 numfoi = length(cfg.foi); cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5;%1; cfg.toi = [-1 : 0.05: 3.6]; cfg.keeptrials = 'yes'; tfr_data_Exp = ft_freqanalysis(cfg, data_Exp); cfg = []; cfg.output = 'pow'; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.taper = 'hanning'; cfg.method = 'mtmconvol'; cfg.foi = 10; %2:2:30; numfoi = length(cfg.foi); cfg.t_ftimwin = ones(length(cfg.foi),1).* 0.5; cfg.toi = [-1 : 0.05: 3.6]; cfg.keeptrials = 'yes'; tfr_data_Ctr = ft_freqanalysis(cfg, data_Ctr); Data fields: e.g. (and similar to the structure of tfr_data_Exp) tfr_data_Ctr = struct with fields: label: {202×1 cell} dimord: 'rpt_chan_freq_time' freq: 10.0000 time: [1×93 double] powspctrm: [90×202×1×93 double] cumtapcnt: [90×1 double] grad: [1×1 struct] trialinfo: [90×1 double] cfg: [1×1 struct] 3. Combine planar gradiometers of the time-frequency data (e.g. tfr_data_Exp) CFG: cfg = []; cfg.method = 'sum'; freqEXP_planar_cmb = ft_combineplanar(cfg,tfr_data_Exp); cfg = []; cfg.method = 'sum'; freqCTR_planar_cmb = ft_combineplanar(cfg,tfr_data_Ctr); Data fields: e.g. (and similar to the structure of freqEXP_planar_cm) freqCTR_planar_cmb = struct with fields: label: {102×1 cell} dimord: 'rpt_chan_freq_time' freq: 10.0000 time: [1×93 double] powspctrm: [90×102×1×93 double] cumtapcnt: [90×1 double] grad: [1×1 struct] trialinfo: [90×1 double] cfg: [1×1 struct] 4. Combine planar gradiometers also for the initial data structures (i.e. data_Exp ) CFG: cfg = []; cfg.method = 'sum'; data_Exp_cmb = ft_combineplanar(cfg,data_Exp); Data fields: data_Exp_cmb = struct with fields: label: {102×1 cell} trialinfo: [90×1 double] sampleinfo: [90×2 double] trial: {1×90 cell} time: {1×90 cell} cfg: [1×1 struct] fsample: 1.0000e+03 grad: [1×1 struct] 5. Prepare neighbours, design, and run ft_freqstatistics CFG: cfg = []; cfg.channel = {'MEGGRAD','-MEG1843', '-MEG2122'}; cfg.latency = 'all'; cfg.frequency = 10; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.minnbchan = 2; cfg.tail = 0; cfg.clustertail = 0; cfg.alpha = 0.025; cfg.numrandomization = 500; % prepare_neighbours determines what sensors may form clusters cfg_neighb.method = 'distance'; cfg_neighb.template = 'neuromag306plan.mat'; cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_Exp_cmb); design = zeros(1,size(freqCTR_planar_cmb.powspctrm,1) + size(freqEXP_planar_cmb.powspctrm,1)); design(1,1:size(freqCTR_planar_cmb.powspctrm,1)) = 1; design(1,(size(freqCTR_planar_cmb.powspctrm,1)+1):(size(freqCTR_planar_cmb,1)+... size(freqEXP_planar_cmb.powspctrm,1))) = 2; cfg.design = design; cfg.ivar = 1; [stat] = ft_freqstatistics(cfg, freqCTR_planar_cmb, freqEXP_planar_cmb); Data fields: stat.stat is a matrix full of NaN stat.prob is a matrix of just ones stat = struct with fields: stat: [102×1×93 double] prob: [102×1×93 double] cirange: [102×1×93 double] mask: [102×1×93 logical] ref: [102×1×93 double] dimord: 'chan_freq_time' freq: 10.0000 grad: [1×1 struct] label: {102×1 cell} time: [1×93 double] cfg: [1×1 struct] Warning: When running the ft_frestatistics I get the repeated warning: (...) Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computing statistic 498 from 0 Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computation of the statistic. Warning: Not all replications are used for the computing statistic 500 from 0 (...) Many many thanks! Ana _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From litvak.vladimir at gmail.com Mon Feb 4 13:19:09 2019 From: litvak.vladimir at gmail.com (Vladimir Litvak) Date: Mon, 4 Feb 2019 12:19:09 +0000 Subject: [FieldTrip] SPM M/EEG course 2019: registration is now open! In-Reply-To: <1396587616.4720470.1549278500791@mail.yahoo.com> References: <1396587616.4720470.1549278500791.ref@mail.yahoo.com> <1396587616.4720470.1549278500791@mail.yahoo.com> Message-ID: Dear all, We are pleased to announce that our annual SPM course for MEG/EEG will take place this year from Monday May 20 to Wednesday May 22 2019. Hosted by University College London, the course will be held at Queen Square (UK). The course will present instruction on the analysis of MEG and EEG data. The first two days will combine theoretical presentations with practical demonstrations of the different data analysis methods implemented in SPM. On the last day participants will have the opportunity to work on SPM tutorial data sets under the supervision of the course faculty. We also invite students to bring their own data for analysis. The course is suitable for both beginners and more advanced users. The topics that will be covered range from pre-processing and statistical analysis to source localization and dynamic causal modelling. The program is listed below. Registration is now open. For full details see: https://onlinestore.ucl.ac.uk/conferences-and-events/faculty-of-brain-sciences-c07/ucl-institute-of-neurology-d07/d07-statistical-parametric-mapping-for-megeeg-2019 where you can also register. Available places are limited so please register as early as possible if you would like to attend! For any administrative questions, please contact Ms Kamlyn Ramikssoon (k.ramkissoon at ucl.ac.uk) Monday May 20th (12 Queen square, 4th floor) 9.00 - 9.30 Registration 9.30 - 9.45 SPM introduction and resources 9.45 - 10.30 What are we measuring with M/EEG? 10.30- 11.15 Data pre-processing Coffee 11.45 - 12.30 Data pre-processing – demo 12.30 - 13.15 General linear model and classical inference Lunch 14.15 - 15.00 Multiple comparisons problem and solutions 15.00 - 15.45 Bayesian inference Coffee 16.15 - 17.45 Group M/EEG dataset analysis – demo 17.45 - 18.30 Advanced applications of the GLM Tuesday May 21th (33 Queen square, basement) 9.30 - 10.15 M/EEG source analysis 10.15 - 11.15 M/EEG source analysis – demo Coffee 11.45 - 12.30 The principles of dynamic causal modelling 12.30 - 13.15 DCM for evoked responses Lunch 14.15 - 15.00 DCM for steady state responses 15.00 - 15.45 DCM - demo Coffee 16.15 - 17.00 Bayesian model selection and averaging 17.00 - 18.30 Clinic - questions & answers 19.00 - ... Social Event Wednesday May 22th 9.30 - 17.00 Practical hands-on session will take place in UCL computer classrooms. Participants can either work on SPM tutorial datasets or on their own data with the help of the faculty. There will also be an opportunity to ask questions in small tutorial groups for further discussions on the topics of the lectures. With the very best regards, Amirhossein Jafarian, Ph.D., MSc, BSc, Research Associate Methods Group Wellcome Centre for Human Neuroimaging UCL Queen Square Institute of Neurology University College London 12 Queen Square London, WC 1N 3AR Email: a.jafarian at ucl.ac.uk -------------- next part -------------- An HTML attachment was scrubbed... URL: From michel at cbs.mpg.de Tue Feb 5 20:23:53 2019 From: michel at cbs.mpg.de (Christine Michel) Date: Tue, 5 Feb 2019 20:23:53 +0100 Subject: [FieldTrip] databrowser problem when jumping to next segment in next trial Message-ID: <84f9e5fe-27ba-eddf-e423-21625c3ca04f@cbs.mpg.de> Dear fieldtrip - experts , I am searching for a solution for a problem I have with the databrowser. I want to scroll through my data with a horizontal resolution which is smaller than the trial length and mark my visual artifacts. For instance, I want to scroll through the data showing only 5s of data and my trial is 23s long. This all works fine until I reach the end of the trial. When clicking on the right arrow, the display does not jump to the first segment of the next trail. Instead, I have to increase the horizontal resolution let's say to 25s, go to the next segment, which is the next trial. Then decrease the horizontal resolution again to 5s and continue marking artifacts. This is - for me - inconvenient and takes some time. Is there any possibility to scroll through the data in my 5s resolution even to the next trial? This would be great! Any advice is highly appreciated! All the best Christine -- Dr. Christine Michel Max Planck Research Group on Early Social Cognition Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1A 04103 Leipzig Germany phone: +49 341 9940 2468 From 404164884 at qq.com Wed Feb 6 01:23:00 2019 From: 404164884 at qq.com (=?gb18030?B?s8K/pbrG?=) Date: Wed, 6 Feb 2019 08:23:00 +0800 Subject: [FieldTrip] :Questions about source interpolate and source reconstruction for specific MNI coordinate Message-ID: Dear Fieldtripers, I tried to conduct source reconstruction and extract time series from specific MNI coordinate on MEG data, but I got some problems. I sorted my questions as follow: (1 In the process of constructing sourcemodel, firstly I conducted ‘ft_volumerealign’ (cfg.coordsys='4d') on subject MRI to define the position of LPA, RPA and nasion according to 4d/bti coordinate system. Then I conducted: cfg = []; cfg.output = ‘brain’; segmentedmri=ft_volumesegment(cfg,mri); I checked the segmentedmri but I saw the brain stem and part of spinal cord were also comprised in it (Fig.1 and Fig.2). I think this result may affect source reconstruction. So, is this result normal? Or did I do something incorrectly? (2 Next I used template-sourcemodel and subject-MRI to construct sourcemodel in MNI space. After I got subject headmodel and sourcemodel, I conducted ‘ft_prepare_leadfield’ and then ‘ft_sourceanalysis’. When I conducted ‘ft_soureinterpolate’ to interpolate this source on subject MRI and plot it, I saw some activation outside the brain, especially in brain stem and spinal cord. But the most important thing is when I interpolate the source on template-MRI (spm8-T1.nii), the functional image and anatomical image do not match, the sagittal plane of functional image is plotted on the coronal plane of anatomical image, the transverse plane of functional image is plotted on the sagittal plane of anatomical image (Fig. 3). But if i interpolated the source on subject MRI, then use 'ft_volumenormalise', they will be match. I have not conducted ‘ft_volumelookup’ and ‘ft_volumereslice’ in the process, is this the reason? Or did I do wrong step in the process? (3 I want to extract time series form specific ROI in MNI space according to MNI coordinate. And I prepare to do this by: norm = ft_volumenormalise([],mri); %normalise subject MRI to MNI space mnipos = [x y z]; %define ROI position in MNI space posback=ft_warp_apply(norm.params,mnipos,'sn2individual'); btipos= ft_warp_apply(pinv(norm.initial),posback); % position in individual coordinates Then conducted ‘ft_prepare_leadfield’ again for ROI only, and conducted ‘ft_sourceanalysis’. Can this process work? Thank you very much for your time and consideration. Looking forward to your reply. Best regards, Chen -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig. 1.png Type: application/octet-stream Size: 265329 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig. 2.png Type: application/octet-stream Size: 22899 bytes Desc: not available URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Fig. 3.png Type: application/octet-stream Size: 183732 bytes Desc: not available URL: From craiggrichter at gmail.com Wed Feb 6 11:08:58 2019 From: craiggrichter at gmail.com (Craig Richter) Date: Wed, 6 Feb 2019 11:08:58 +0100 Subject: [FieldTrip] Postdoctoral Position - BCBL - San Sebastian, Spain Message-ID: The Basque Center on Cognition Brain and Language – BCBL- (San Sebastián, Basque Country, Spain) is offering a postdoctoral position focused on the neurobiological basis of predictive processing and statistical learning. The main project will focus on the oscillatory correlates of predictive processing in vision and audition with a special focus on neural entrainment phenomena and top-down control. The project is part of a collaborative research effort of the BCBL with the Hebrew University of Jerusalem funded by the ERC with PIs: Ram Frost (Hebrew U), Craig Richter (BCBL), Nicola Molinaro (BCBL). The expected time frame is one year with a possible extension to another year. The project is based on a set of EEG and MEG experiments that will be designed to uncover the neural mechanisms supporting predictive processing – across sensory modalities and cognitive domains. The long-term goal is to evaluate the role that such predictive skills play in second language learning, and how these are implemented neurobiologically. We are interested in candidates with a high level of independence, familiarity with EEG or MEG, as well as computing tools (Python/Matlab). Candidates should demonstrate a convincing publication record. The successful candidate will join an interdisciplinary team of researchers studying the cognitive and neural mechanisms underlying statistical learning, predictive processing and language learning, and research will be carried out primarily at the BCBL, with stays at the Hebrew U. Deadline: April 15th, 2019. To submit your application please follow this link: http://www.bcbl.eu/calls , applying for EEG/MEG Postdoc 2019_02 and upload: 1. A curriculum vitae. 2. A cover letter/statement describing your research interests (4000 characters max). 3. Two reference letters submitted directly by the referees through the outline system. For more information about the specifics of the position, please contact Ram Frost (ram.frost at mail.huji.ac.il ) and/or Craig Richter at the BCBL (craiggrichter at gmail.com). -------------- next part -------------- An HTML attachment was scrubbed... URL: From malgorzata.wislowska at gmail.com Wed Feb 6 15:49:38 2019 From: malgorzata.wislowska at gmail.com (Malgorzata Wislowska) Date: Wed, 6 Feb 2019 14:49:38 +0000 Subject: [FieldTrip] databrowser problem when jumping to next segment in next trial In-Reply-To: References: Message-ID: Dear Christine, if you specify in your input configuration structure: cfg.continuous = 'yes'; then your trials will be appended and you will be able to scroll through the entire dataset at once. I hope this help. Best regards, Gosia > ---------- Forwarded message ---------- > From: Christine Michel > To: fieldtrip at science.ru.nl > Cc: > Bcc: > Date: Tue, 5 Feb 2019 20:23:53 +0100 > Subject: [FieldTrip] databrowser problem when jumping to next segment in > next trial > Dear fieldtrip - experts , > > I am searching for a solution for a problem I have with the databrowser. > I want to scroll through my data with a horizontal resolution which is > smaller than the trial length and mark my visual artifacts. For > instance, I want to scroll through the data showing only 5s of data and > my trial is 23s long. This all works fine until I reach the end of the > trial. When clicking on the right arrow, the display does not jump to > the first segment of the next trail. Instead, I have to increase the > horizontal resolution let's say to 25s, go to the next segment, which is > the next trial. Then decrease the horizontal resolution again to 5s and > continue marking artifacts. This is - for me - inconvenient and takes > some time. Is there any possibility to scroll through the data in my 5s > resolution even to the next trial? This would be great! Any advice is > highly appreciated! > > All the best > > Christine > > > > -- > Dr. Christine Michel > Max Planck Research Group on Early Social Cognition > > Max Planck Institute for Human Cognitive and Brain Sciences > Stephanstr. 1A > 04103 Leipzig > Germany > > phone: +49 341 9940 2468 > -------------- next part -------------- An HTML attachment was scrubbed... URL: From elam4hcp at gmail.com Wed Feb 6 22:23:28 2019 From: elam4hcp at gmail.com (Jennifer Elam) Date: Wed, 6 Feb 2019 15:23:28 -0600 Subject: [FieldTrip] Announcing HCP Course 2019, July 8-12 in Portland, OR! Message-ID: We are pleased to announce the 2019 HCP Course: "Exploring the Human Connectome" , to be held July 8 – 12, 2019 at the University Place Hotel and Conference Center at Portland State University in Portland, Oregon, USA. This 5-day intensive course will provide training in acquisition, processing, analysis and visualization of whole brain imaging and behavioral data using methods and tools developed by the WU-Minn-Oxford Human Connectome Project (HCP) consortium. The course is designed for those interested in: - using HCP-style data currently available from the young adult HCP and HCP Lifespan (Development and Aging) projects - acquiring and analyzing HCP-style imaging and behavioral data at your own institution - processing your own non-HCP data (including legacy data) using HCP pipelines and methods - using Connectome Workbench tools and sharing data using the BALSA imaging database - learning HCP multi-modal neuroimaging analysis methods, including those that combine MEG and MRI data - positioning yourself to capitalize on HCP-style data forthcoming from large-scale projects currently collecting data (e.g., Lifespan HCP development and aging longitudinal data and Connectomes Related to Human Disease projects) - learning how to obtain data from the NIMH Data Archive (NDA) and setup processing in an Amazon Web Services (AWS) environment Participants will learn how to acquire, analyze, visualize, and interpret data from four major MR modalities (structural MR, resting-state fMRI, diffusion imaging, task-evoked fMRI) plus magnetoencephalography (MEG) and extensive behavioral data. Lectures and labs will provide grounding in neurobiological as well as methodological issues involved in interpreting multimodal data, and will span the range from single-voxel/vertex to brain network analysis approaches. The course is open to students, postdocs, faculty, non-profit and industry participants. The course is aimed at both new and current users of HCP data, methods, and tools, and will cover both basic and advanced topics. Prior experience in human neuroimaging or in computational analysis of brain networks is desirable, preferably including some familiarity with FSL and Freesurfer software. For more info and to register visit the HCP Course 2019 website . If you have any questions, please contact us at: hcpcourse at humanconnectome.org We look forward to seeing you in Portland! Best, 2019 HCP Course Organizers -- Jennifer Elam, Ph.D. Scientific Outreach, Human Connectome Project Washington University School of Medicine Department of Neuroscience, Box 8108 660 South Euclid Avenue St. Louis, MO 63110 314-362-9387 elam at wustl.edu www.humanconnectome.org -------------- next part -------------- An HTML attachment was scrubbed... URL: From pdhami06 at gmail.com Thu Feb 7 04:49:59 2019 From: pdhami06 at gmail.com (Paul Dhami) Date: Wed, 6 Feb 2019 22:49:59 -0500 Subject: [FieldTrip] Question regarding calculation of effect sizes for cluster-based permutation tests Message-ID: Dear Fieldtrip community, According to this thread ( https://mailman.science.ru.nl/pipermail/fieldtrip/2017-September/011773.html), Dr. Eric Maris provides a 3 step way to calculate the effect size for cluster-based permutation tests. 1. Calculate the non-standardised effect sizes by averaging the (sensor, frequency, time)-specific effects within the cluster of interest. Typically, the (sensor, frequency, time)-specific effects are raw differences between the subject averages for the experimental conditions that are being compared. 2. Calculate the standard deviation over the subjects of these non-standardised effect sizes. 3. Calculate Cohen’s d by dividing the grand average of the non-standardised effect sizes by the standard deviation obtained in 2. However, a few other threads have people suggesting it is not possible or not recommended. Can anyone else provide guidance as to whether the method describe above is accurate for getting the effect sizes of cluster-based permutation tests? Thank you, Paul -------------- next part -------------- An HTML attachment was scrubbed... URL: From michel at cbs.mpg.de Thu Feb 7 11:36:43 2019 From: michel at cbs.mpg.de (Christine Michel) Date: Thu, 7 Feb 2019 11:36:43 +0100 Subject: [FieldTrip] databrowser problem when jumping to next segment in next trial Message-ID: <778bb559-921e-65ab-bcb0-99f017ca26a2@cbs.mpg.de> Dear Gosia, thank you for the idea of using cfg. continuous = 'yes'. It works fine and I can now scroll through the data. The problem I have is that we do not have continuous data as we have for example breaks between trials and this data was already set to NaN. When I set cfg.continuous to 'yes' , I have now blank/empty segments which I have to scroll through until the next trial starts. Is there any way I can get of the blank/ empty segments and only scroll continuously through the existing data? Thanks a lot - any advice is highly appreciated, Christine -- Dr. Christine Michel Max Planck Research Group on Early Social Cognition Max Planck Institute for Human Cognitive and Brain Sciences Stephanstr. 1A 04103 Leipzig Germany phone: +49 341 9940 2468 From anapesquita at gmail.com Thu Feb 7 12:00:02 2019 From: anapesquita at gmail.com (Ana Pesquita) Date: Thu, 7 Feb 2019 11:00:02 +0000 Subject: [FieldTrip] Help with between-trials single subject permutation (ft_freqstatistics output is stat.sta NaN NaN NaN ....) Message-ID: Hello all, Thank you so much for all the input. This community is top! : ) When I removed the NaN from the beginning and end of the pwspctrm data field, the "Warning: Not all replications are used for the computing statistic" disappeared. So it seems that ft_freqstatistics prefers to deal with data without any NaN (even the ones that are naturally created at the edges of the data when running the ft_freqanalysis). Thank you again for all the help! A merry fieldtrip day to you all! Ana -------------- next part -------------- An HTML attachment was scrubbed... URL: From afsamani at hst.aau.dk Thu Feb 7 15:32:13 2019 From: afsamani at hst.aau.dk (Afshin Samani) Date: Thu, 7 Feb 2019 14:32:13 +0000 Subject: [FieldTrip] simbio tutorial Message-ID: <2E4AC5E2A691FE4B89DA44B0E70DF70A0175DC86D3@AD-EXCHMBX3-3.aau.dk> Dear all, I am just trying to familiarize myself with the functionalities of Fieldtrip. I was trying to run the tutorial on FEM volume conduction model for EEG http://www.fieldtriptoolbox.org/tutorial/headmodel_eeg_fem/ Apparently, the new versions of fieldtrip do not have a simbio folder in their external sources. I read in an old query that somebody got it from an older version of fieldtrip and it resolved the problem. https://mailman.science.ru.nl/pipermail/fieldtrip/2016-April/010348.html I did the same but apparently, it was not sufficient to add that folder to the external folder. When I did that, I faced with a chunk of error messages about invalid mex files requiring some other dll files like 'MSVCR90.dll', 'svml_dispmd.dll', and many more. I am running MATLAB on a windows platform. Could this be the reason? I did not see any instruction for avoiding windows for this tutorial though. I tried to search for a solution but I did not find any instruction on how to get around this trouble. Could anybody help? Best regards, Afshin -------------- next part -------------- An HTML attachment was scrubbed... URL: From j.vorw01 at gmail.com Thu Feb 7 15:43:39 2019 From: j.vorw01 at gmail.com (Johannes) Date: Thu, 7 Feb 2019 15:43:39 +0100 Subject: [FieldTrip] simbio tutorial In-Reply-To: <2E4AC5E2A691FE4B89DA44B0E70DF70A0175DC86D3@AD-EXCHMBX3-3.aau.dk> References: <2E4AC5E2A691FE4B89DA44B0E70DF70A0175DC86D3@AD-EXCHMBX3-3.aau.dk> Message-ID: Dear Afshin, the simbio mex-files require to have the Microsoft Visual C++ 2008 Redistributables and Intel Visual Fortran Redistributables installed when run on windows. Otherwise dll-files will be missing, as seen in your error message. I hope this helps. Best, Johannes Am Do., 7. Feb. 2019 um 15:35 Uhr schrieb Afshin Samani : > Dear all, > > > > I am just trying to familiarize myself with the functionalities of > Fieldtrip. > > I was trying to run the tutorial on FEM volume conduction model for EEG > > http://www.fieldtriptoolbox.org/tutorial/headmodel_eeg_fem/ > > Apparently, the new versions of fieldtrip do not have a simbio folder in > their external sources. > > I read in an old query that somebody got it from an older version of > fieldtrip and it resolved the problem. > > https://mailman.science.ru.nl/pipermail/fieldtrip/2016-April/010348.html > > > > I did the same but apparently, it was not sufficient to add that folder to > the external folder. When I did that, I faced with a chunk of error > messages about invalid mex files requiring some other dll files like > 'MSVCR90.dll', 'svml_dispmd.dll', and many more. > > I am running MATLAB on a windows platform. Could this be the reason? I did > not see any instruction for avoiding windows for this tutorial though. > > > > I tried to search for a solution but I did not find any instruction on how > to get around this trouble. Could anybody help? > > > > Best regards, > > Afshin > > > > > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: From afsamani at hst.aau.dk Fri Feb 8 10:44:09 2019 From: afsamani at hst.aau.dk (Afshin Samani) Date: Fri, 8 Feb 2019 09:44:09 +0000 Subject: [FieldTrip] simbio tutorial In-Reply-To: References: <2E4AC5E2A691FE4B89DA44B0E70DF70A0175DC86D3@AD-EXCHMBX3-3.aau.dk> Message-ID: <2E4AC5E2A691FE4B89DA44B0E70DF70A0175DC9294@AD-EXCHMBX3-3.aau.dk> Thanks Johannes for the hint. Apparently, I had to setup the compiler in MATLAB too. Best, Afshin From: fieldtrip On Behalf Of Johannes Sent: 7. februar 2019 15:44 To: FieldTrip discussion list Subject: Re: [FieldTrip] simbio tutorial Dear Afshin, the simbio mex-files require to have the Microsoft Visual C++ 2008 Redistributables and Intel Visual Fortran Redistributables installed when run on windows. Otherwise dll-files will be missing, as seen in your error message. I hope this helps. Best, Johannes Am Do., 7. Feb. 2019 um 15:35 Uhr schrieb Afshin Samani >: Dear all, I am just trying to familiarize myself with the functionalities of Fieldtrip. I was trying to run the tutorial on FEM volume conduction model for EEG http://www.fieldtriptoolbox.org/tutorial/headmodel_eeg_fem/ Apparently, the new versions of fieldtrip do not have a simbio folder in their external sources. I read in an old query that somebody got it from an older version of fieldtrip and it resolved the problem. https://mailman.science.ru.nl/pipermail/fieldtrip/2016-April/010348.html I did the same but apparently, it was not sufficient to add that folder to the external folder. When I did that, I faced with a chunk of error messages about invalid mex files requiring some other dll files like 'MSVCR90.dll', 'svml_dispmd.dll', and many more. I am running MATLAB on a windows platform. Could this be the reason? I did not see any instruction for avoiding windows for this tutorial though. I tried to search for a solution but I did not find any instruction on how to get around this trouble. Could anybody help? Best regards, Afshin _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From J.Verhoef at donders.ru.nl Thu Feb 7 11:41:14 2019 From: J.Verhoef at donders.ru.nl (Verhoef, J.P. (Julia)) Date: Thu, 7 Feb 2019 10:41:14 +0000 Subject: [FieldTrip] Postdoc position in Linguistics for Research Consortium 'Language in Interaction' (1, 0 fte) Message-ID: Postdoc position in Linguistics for Research Consortium 'Language in Interaction' (1,0 fte) Dutch Research Consortium 'Language in Interaction' Application deadline: February 17, 2019, 23:59 CET [Logo][Logo NWO] Responsibilities The Language in Interaction research consortium invites applications for a postdoctoral position in Linguistics. We are looking for a candidate with a background in theoretical and/or computational linguistics. You will contribute to the integration of linguistic expertise into the empirical research performed by teams of researchers in our consortium that are collaborating to collectively address the key questions of our field. You will be provided the opportunity to conduct research in one or more research areas relevant to the position. Supervision of BSc, MSc and PhD projects will be part of your responsibilities. You will be provided with budgetary resources for travel, materials and lab-use. This position provides the opportunity for conducting world-class research as a member of an interdisciplinary team. Moreover, it will provide the opportunity to contribute to developing a theoretical framework for our understanding of the human language faculty. Work environment The Netherlands has an outstanding track record in the language sciences. The research consortium 'Language in Interaction', sponsored by a large grant from the Netherlands Organization for Scientific research (NWO), brings together many of the excellent research groups in the Netherlands with a research programme on the foundations of language. In addition to excellence in the domain of language and related relevant fields of cognition, our consortium provides state-of-the-art research facilities and a research team with ample experience in the complex research methods that will be invoked to address the scientific questions at the highest level of methodological sophistication. These include methods from genetics, neuroimaging, computational modelling, and patient-related research. This consortium realizes both quality and critical mass for studying human language at a scale not easily found anywhere else. We have identified five Big Questions (BQ) that are central to our understanding of the human language faculty. These questions are interrelated at multiple levels. Teams of researchers will collaborate to collectively address these key questions of our field. Our five Big Questions are: BQ1: The nature of the mental lexicon: How to bridge neurobiology and psycholinguistic theory by computational modelling? BQ2: What are the characteristics and consequences of internal brain organization for language? BQ3: Creating a shared cognitive space: How is language grounded in and shaped by communicative settings of interacting people? BQ4: Variability in language processing and in language learning: Why does the ability to learn language change with age? How can we characterise and map individual language skills in relation to the population distribution? BQ5: How are other cognitive systems shaped by the presence of a language system in humans? Successful candidates will be appointed at one of the consortium's home institutions, depending on the position applied for. All successful candidates will become members of our Big Question teams. The research is conducted in an international setting at all participating institutions. English is the lingua franca. You will be appointed at the Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands. You will be supervised by Peter Hagoort, programme director of the Language in Interaction consortium. The research is conducted in an international setting at all participating institutions. English is the lingua franca. What we expect from you We are looking for highly motivated candidates to enrich a unique consortium of researchers that aims to unravel the neurocognitive mechanisms of language at multiple levels. The goal is to understand both the universality and the variability of the human language faculty from genes to behaviour. · a PhD in Linguistics; · an integrative mindset; · a theory-driven approach; · good communication skills; · strong motivation; · excellent proficiency in written and spoken English. What we have to offer · Full-time position (39 hours per week) with a term of appointment of 4 years. · The salary is according to the German TVöD (Tarifvertrag für den öffentlichen Dienst) and is classified in salary group E13 (depending on the experience of the applicant between EUR 3.827,03 and EUR 5.683,28 gross per month, based on a full-time employment). · In addition to the salary: an 8% holiday allowance · The Max Planck Institute involved has a number of regulations that make it possible for employees to create a good work-life balance. Other Information The institute involved is an equal opportunity employer, committed to building a culturally diverse intellectual community, and as such encourages applications from women and minorities. Would you like to know more? Further information on: the Language in Interaction Consortium. Further information on: Donders Institute for Brain, Cognition and Behaviour For more information about this vacancy, please contact: Prof. dr. Peter Hagoort, programme director Language in Interaction and director of DCCN and MPI Telephone: +31 24 3610648, +31 24 3521301 E-mail: p.hagoort at donders.ru.nl Are you interested? Please submit your application (attn. of Prof. dr. P. Hagoort) to j.verhoef at donders.ru.nl in electronic form. Your application should include (and be limited to) the following attachments: · a cover letter, · your curriculum vitae, including a list of publications and the names of at least two persons who can provide references. Application deadline: February 17, 2019, 23:59 CET. Kind regards, Julia Verhoef Secretary - Language in Interaction Consortium Radboud University | Donders Centre for Cognitive Neuroimaging (DCCN) Room 0.026 Kapittelweg 29, 6525 EN Nijmegen, The Netherlands P.O. Box 9101, 6500 HB, Nijmegen, The Netherlands |T: +31 (0)24 3666272 E: J.Verhoef at donders.ru.nll|Office hours: 9-14 hr on Mon - Fri Follow Language in Interaction on Twitter Like Language in Interaction on Facebook -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.jpg Type: image/jpeg Size: 40202 bytes Desc: image001.jpg URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image002.jpg Type: image/jpeg Size: 2461 bytes Desc: image002.jpg URL: From pelagietemgoua at yahoo.fr Fri Feb 8 11:51:03 2019 From: pelagietemgoua at yahoo.fr (=?UTF-8?Q?p=C3=A9lagie_Temgoua?=) Date: Fri, 8 Feb 2019 10:51:03 +0000 (UTC) Subject: [FieldTrip] Fw: Problem with ft_connectivityanalysis In-Reply-To: <1426329734.315765.1549621159291@mail.yahoo.com> References: <1426329734.315765.1549621159291.ref@mail.yahoo.com> <1426329734.315765.1549621159291@mail.yahoo.com> Message-ID: <294302191.402652.1549623063856@mail.yahoo.com> Good morning their all. i run ft_connectivityanalysis.m script with the following configuration :[data, header] = edfread("s01.edf")freq = 250cfg = [];cfg.method = 'plv';stat = ft_connectivityanalysis(cfg, data) and i get the following error:Error using ft_checkdata (line 529)This function requires 'freqmvar', 'freq' or 'source' data as input, see ft_datatype_freq or ft_datatype_source. Error in ft_connectivityanalysis (line 271)data = ft_checkdata(data, 'datatype', {'freqmvar' 'freq' 'source'});need your help please. Thank you. Pélagie Flore TEMGOUA NANFACK Tél : (00237) 675 39 66 33/ 696 20 51 02 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Fri Feb 8 12:03:47 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 8 Feb 2019 11:03:47 +0000 Subject: [FieldTrip] Problem with ft_connectivityanalysis In-Reply-To: <294302191.402652.1549623063856@mail.yahoo.com> References: <1426329734.315765.1549621159291.ref@mail.yahoo.com> <1426329734.315765.1549621159291@mail.yahoo.com> <294302191.402652.1549623063856@mail.yahoo.com> Message-ID: <8D485340-8916-4531-808E-85CA11AA3D26@donders.ru.nl> Hi Pélagie, As the error indicates, the data object that goes into ft_connectivityanalysis is not according to the function’s expectations. In general, data objects need to be according to FieldTrip’s definition, and using a low-level reading function, such as edfread in your example, returns only a matrix, and not the associated metadata. If you want the data properly formatted, you should use ft_preprocessing. e.g.: cfg = []; cfg.dataset = ’s01.edf’; data = ft_preprocessing(cfg); Next, if you want to compute the phase locking value (as is suggested by your call to ft_connectivityanalysis), you should first transform your epoched (!) time-domain data into the frequency domain by means of ft_freqanalysis. Note that there’s a wealth of tutorial and getting started documentation on the website: www.fieldtriptoolbox.org, which should get you started. Best wishes, Jan-Mathijs Schoffelen J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 8 Feb 2019, at 11:51, pélagie Temgoua > wrote: Good morning their all. i run ft_connectivityanalysis.m script with the following configuration : [data, header] = edfread("s01.edf") freq = 250 cfg = []; cfg.method = 'plv'; stat = ft_connectivityanalysis(cfg, data) and i get the following error: Error using ft_checkdata (line 529) This function requires 'freqmvar', 'freq' or 'source' data as input, see ft_datatype_freq or ft_datatype_source. Error in ft_connectivityanalysis (line 271) data = ft_checkdata(data, 'datatype', {'freqmvar' 'freq' 'source'}); need your help please. Thank you. Pélagie Flore TEMGOUA NANFACK Tél : (00237) 675 39 66 33/ 696 20 51 02 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From mona at sdsc.edu Sat Feb 9 03:33:29 2019 From: mona at sdsc.edu (Wong-Barnum, Mona) Date: Sat, 9 Feb 2019 02:33:29 +0000 Subject: [FieldTrip] plotting tutorial Message-ID: <8ABE1405-1C8E-40B7-9C5E-AA2AB92618A6@sdsc.edu> Hi: I’m working my way through the plotting tutorial at http://www.fieldtriptoolbox.org/tutorial/plotting/. I would like to use the neuromag306all.lay layout to plot the data. I tried the neuromag306.mat from ftp but that didn’t work; it seems the data read in from neuromag306.mat doesn’t actually contain any data: >> sens sens = struct with fields: chanpos: [2x3 double] elecpos: [2x3 double] label: {2x1 cell} unit: ‘cm' I have my own neuromag .fif file but not sure how to use the layout to plot my data (read in following the instructions at page http://www.fieldtriptoolbox.org/getting_started/neuromag/): >> hdr hdr = struct with fields: label: {389x1 cell} nChans: 389 Fs: 603.1072 grad: [1x1 struct] elec: [1x1 struct] nSamples: 192000 nSamplesPre: 0 nTrials: 1 orig: [1x1 struct] chantype: {389x1 cell} chanunit: {389x1 cell} All tips/help are appreciated. thanks, Mona ********************************************* Mona Wong Web & Mobile Application Developer San Diego Supercomputer Center "I've learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel." --- Maya Angelou ********************************************* From alexandre.chalard at inserm.fr Sun Feb 10 23:58:18 2019 From: alexandre.chalard at inserm.fr (Alexandre Chalard) Date: Sun, 10 Feb 2019 23:58:18 +0100 Subject: [FieldTrip] ft_freqstatistics not working on mac Message-ID: <1F212210-C2EE-4ACF-B4CC-648AEE25FA3A@inserm.fr> Dear all, When I try to perform an analysis with my PC with the following code : cfg.neighbours = ft_prepare_neighbours(cfg_neighb, DataP); cfg.channel = ROI; cfg.latency = [0 100]; cfg.frequency = [13 30]; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.minnbchan = 2; cfg.tail = 0; cfg.clustertail = 0; cfg.alpha = 0.025; cfg.numrandomization = 100; cfg.avgovertime = 'yes'; cfg.avgoverfreq = 'yes'; design = []; design(1:numel(PFiles)) = 1; design(end+1:end+numel(TFiles)) = 2; cfg.design = design; cfg.ivar = 1; stat = ft_freqstatistics(cfg,DataP,DataT); Everything is working, but when I try with my macbook pro, the function doesn’t work. The permutation progress take directly the value 100 on 100, and the matlab status is busy with no return and no possibility to break the code (ctrl-c), I need to close matlab to stop the execution. Does anyone have an idea or have the same problem? Kind regards, Alexandre Chalard -- PhD student -------------- next part -------------- An HTML attachment was scrubbed... URL: From Jane.Tan at murdoch.edu.au Mon Feb 11 03:42:26 2019 From: Jane.Tan at murdoch.edu.au (Jane Tan) Date: Mon, 11 Feb 2019 02:42:26 +0000 Subject: [FieldTrip] Is it normal to have NaNs in source analysis output? Message-ID: Dear Fieldtrippers, My name is Jane, and this is my first time posting a question to this community. First and foremost, I would like to apologise if my question is extremely trivial. I am trying to perform source analysis using the Beamformer DICS approach on EEG data. My data has been preprocessed using the EEGlab toolbox, and in this particular instance I am only interested in 20 Hz source space activity for time periods around event 'SS'. My question is very simple: is it normal to get NaNs in the avg.pow output of the source analysis? It seems to make sense; positions in the grid that do not have 20 Hz reconstructed activity would be represented by NaNs. However, I'm a novice (in all aspects: Matlab, EEG analysis, and Fieldtrip), and for a sanity check, would like to confirm that getting NaNs in my source output is normal. Here is the code I executed: %% Loading data [EEG] = pop_loadset('E:\preprocesseddata.set'); EEG = pop_epoch( EEG, { 'SSstopDIN' }, [-0.5 0.8]); % Epoch to event of interest 'SS' dataSS_epoched = eeglab2fieldtrip(EEG, 'preprocessing'); % Convert eeglab dataset to fieldtrip data %% Calculating the cross spectral density matrix cfg = []; cfg.method = 'mtmfft'; cfg.taper = 'hanning'; cfg.output = 'powandcsd'; cfg.foi = 4:40; cfg.keeptrials = 'no'; TFR_SS = ft_freqanalysis(cfg, dataSS_epoched); %% Computing leadfield cfg = []; cfg.headmodel = vol; %using BEM head model from FT template cfg.reducerank = 3; %default = 3 for EEG cfg.elec = elec_aligned cfg.grid.resolution = 0.5; % use a 3-D grid with a 0.5 cm resolution cfg.grid.unit = 'cm'; [grid] = ft_prepare_leadfield(cfg); %% Source analysis (without contrasts; just testing source reconstruction for one condition first) cfg = []; cfg.method = 'dics'; cfg.frequency = 20; cfg.grid = grid; cfg.headmodel = vol; cfg.elec = elec_aligned; sourceSS_nocon = ft_sourceanalysis(cfg, TFR_SS); % Here, sourceSS_nocon.avg.pow shows NaNs in some cells and not others [cid:a458c15f-7cd8-4957-b19f-49686ec7517a] My sincere thanks in advance! Best regards, Jane Jane Tan, PhD Candidate School of Psychology and Exercise Science | Murdoch University Room 3.001 Social Science Building, 90 South Street, Murdoch WA 6150 | Email: Jane.Tan at murdoch.edu.au [cid:95c33115-83df-4674-9c4c-28935742fc23] -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: pastedImage.png Type: image/png Size: 28967 bytes Desc: pastedImage.png URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: Outlook-3jowpkkg.png Type: image/png Size: 7527 bytes Desc: Outlook-3jowpkkg.png URL: From nathanweisz at me.com Mon Feb 11 07:21:41 2019 From: nathanweisz at me.com (Nathan Weisz) Date: Mon, 11 Feb 2019 07:21:41 +0100 Subject: [FieldTrip] ft_freqstatistics not working on mac In-Reply-To: <1F212210-C2EE-4ACF-B4CC-648AEE25FA3A@inserm.fr> References: <1F212210-C2EE-4ACF-B4CC-648AEE25FA3A@inserm.fr> Message-ID: <3B491A8C-FB59-4DF6-B311-1542F02EA40D@me.com> i had the same issue … first i thought i may not have the image processing toolbox installed. > Am 10.02.2019 um 23:58 schrieb Alexandre Chalard : > > Dear all, > > When I try to perform an analysis with my PC with the following code : > > cfg.neighbours = ft_prepare_neighbours(cfg_neighb, DataP); > cfg.channel = ROI; > cfg.latency = [0 100]; > cfg.frequency = [13 30]; > cfg.method = 'montecarlo'; > cfg.statistic = 'ft_statfun_indepsamplesT'; > cfg.correctm = 'cluster'; > cfg.clusteralpha = 0.05; > cfg.clusterstatistic = 'maxsum'; > cfg.minnbchan = 2; > cfg.tail = 0; > cfg.clustertail = 0; > cfg.alpha = 0.025; > cfg.numrandomization = 100; > cfg.avgovertime = 'yes'; > cfg.avgoverfreq = 'yes'; > > design = []; > design(1:numel(PFiles)) = 1; > design(end+1:end+numel(TFiles)) = 2; > > cfg.design = design; > cfg.ivar = 1; > > stat = ft_freqstatistics(cfg,DataP,DataT); > > Everything is working, but when I try with my macbook pro, the function doesn’t work. > The permutation progress take directly the value 100 on 100, and the matlab status is busy with no return and no possibility to break the code (ctrl-c), I need to close matlab to stop the execution. > > Does anyone have an idea or have the same problem? > > Kind regards, > > Alexandre Chalard > -- > PhD student > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From a.stolk8 at gmail.com Mon Feb 11 07:51:05 2019 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Sun, 10 Feb 2019 22:51:05 -0800 Subject: [FieldTrip] ft_freqstatistics not working on mac In-Reply-To: <3B491A8C-FB59-4DF6-B311-1542F02EA40D@me.com> References: <1F212210-C2EE-4ACF-B4CC-648AEE25FA3A@inserm.fr> <3B491A8C-FB59-4DF6-B311-1542F02EA40D@me.com> Message-ID: <2F650C95-5F69-47D2-9D9E-ECC8313FA761@gmail.com> Is this something that started happening recently? What mac os/matlab/ft version? > On Feb 10, 2019, at 10:21 PM, Nathan Weisz wrote: > > i had the same issue … first i thought i may not have the image processing toolbox installed. > > >> Am 10.02.2019 um 23:58 schrieb Alexandre Chalard : >> >> Dear all, >> >> When I try to perform an analysis with my PC with the following code : >> >> cfg.neighbours = ft_prepare_neighbours(cfg_neighb, DataP); >> cfg.channel = ROI; >> cfg.latency = [0 100]; >> cfg.frequency = [13 30]; >> cfg.method = 'montecarlo'; >> cfg.statistic = 'ft_statfun_indepsamplesT'; >> cfg.correctm = 'cluster'; >> cfg.clusteralpha = 0.05; >> cfg.clusterstatistic = 'maxsum'; >> cfg.minnbchan = 2; >> cfg.tail = 0; >> cfg.clustertail = 0; >> cfg.alpha = 0.025; >> cfg.numrandomization = 100; >> cfg.avgovertime = 'yes'; >> cfg.avgoverfreq = 'yes'; >> >> design = []; >> design(1:numel(PFiles)) = 1; >> design(end+1:end+numel(TFiles)) = 2; >> >> cfg.design = design; >> cfg.ivar = 1; >> >> stat = ft_freqstatistics(cfg,DataP,DataT); >> >> Everything is working, but when I try with my macbook pro, the function doesn’t work. >> The permutation progress take directly the value 100 on 100, and the matlab status is busy with no return and no possibility to break the code (ctrl-c), I need to close matlab to stop the execution. >> >> Does anyone have an idea or have the same problem? >> >> Kind regards, >> >> Alexandre Chalard >> -- >> PhD student >> >> >> _______________________________________________ >> fieldtrip mailing list >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> https://doi.org/10.1371/journal.pcbi.1002202 > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Feb 11 08:39:40 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 11 Feb 2019 07:39:40 +0000 Subject: [FieldTrip] Is it normal to have NaNs in source analysis output? In-Reply-To: References: Message-ID: <9F90E740-AEC6-418A-8070-C2AAD21C243B@donders.ru.nl> Hi Jane, Yes, it is not a problem (and expected) for the outside-of-the-head dipole positions to be represented by NaNs. Best wishes and keep up the good work, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 11 Feb 2019, at 03:42, Jane Tan > wrote: Dear Fieldtrippers, My name is Jane, and this is my first time posting a question to this community. First and foremost, I would like to apologise if my question is extremely trivial. I am trying to perform source analysis using the Beamformer DICS approach on EEG data. My data has been preprocessed using the EEGlab toolbox, and in this particular instance I am only interested in 20 Hz source space activity for time periods around event 'SS'. My question is very simple: is it normal to get NaNs in the avg.pow output of the source analysis? It seems to make sense; positions in the grid that do not have 20 Hz reconstructed activity would be represented by NaNs. However, I'm a novice (in all aspects: Matlab, EEG analysis, and Fieldtrip), and for a sanity check, would like to confirm that getting NaNs in my source output is normal. Here is the code I executed: %% Loading data [EEG] = pop_loadset('E:\preprocesseddata.set'); EEG = pop_epoch( EEG, { 'SSstopDIN' }, [-0.5 0.8]); % Epoch to event of interest 'SS' dataSS_epoched = eeglab2fieldtrip(EEG, 'preprocessing'); % Convert eeglab dataset to fieldtrip data %% Calculating the cross spectral density matrix cfg = []; cfg.method = 'mtmfft'; cfg.taper = 'hanning'; cfg.output = 'powandcsd'; cfg.foi = 4:40; cfg.keeptrials = 'no'; TFR_SS = ft_freqanalysis(cfg, dataSS_epoched); %% Computing leadfield cfg = []; cfg.headmodel = vol; %using BEM head model from FT template cfg.reducerank = 3; %default = 3 for EEG cfg.elec = elec_aligned cfg.grid.resolution = 0.5; % use a 3-D grid with a 0.5 cm resolution cfg.grid.unit = 'cm'; [grid] = ft_prepare_leadfield(cfg); %% Source analysis (without contrasts; just testing source reconstruction for one condition first) cfg = []; cfg.method = 'dics'; cfg.frequency = 20; cfg.grid = grid; cfg.headmodel = vol; cfg.elec = elec_aligned; sourceSS_nocon = ft_sourceanalysis(cfg, TFR_SS); % Here, sourceSS_nocon.avg.pow shows NaNs in some cells and not others My sincere thanks in advance! Best regards, Jane Jane Tan, PhD Candidate School of Psychology and Exercise Science | Murdoch University Room 3.001 Social Science Building, 90 South Street, Murdoch WA 6150 | Email: Jane.Tan at murdoch.edu.au _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From jan.schoffelen at donders.ru.nl Mon Feb 11 08:42:28 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Mon, 11 Feb 2019 07:42:28 +0000 Subject: [FieldTrip] plotting tutorial In-Reply-To: <8ABE1405-1C8E-40B7-9C5E-AA2AB92618A6@sdsc.edu> References: <8ABE1405-1C8E-40B7-9C5E-AA2AB92618A6@sdsc.edu> Message-ID: <6E0506AF-0042-4DE4-B6B7-041D4A1F1F82@donders.ru.nl> Hi Mona, Have you tried the layout files that are contained in fieldtrip/template/layout. I think that there should be a few that would suit your needs. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 9 Feb 2019, at 03:33, Wong-Barnum, Mona > wrote: Hi: I’m working my way through the plotting tutorial at http://www.fieldtriptoolbox.org/tutorial/plotting/. I would like to use the neuromag306all.lay layout to plot the data. I tried the neuromag306.mat from ftp but that didn’t work; it seems the data read in from neuromag306.mat doesn’t actually contain any data: sens sens = struct with fields: chanpos: [2x3 double] elecpos: [2x3 double] label: {2x1 cell} unit: ‘cm' I have my own neuromag .fif file but not sure how to use the layout to plot my data (read in following the instructions at page http://www.fieldtriptoolbox.org/getting_started/neuromag/): hdr hdr = struct with fields: label: {389x1 cell} nChans: 389 Fs: 603.1072 grad: [1x1 struct] elec: [1x1 struct] nSamples: 192000 nSamplesPre: 0 nTrials: 1 orig: [1x1 struct] chantype: {389x1 cell} chanunit: {389x1 cell} All tips/help are appreciated. thanks, Mona ********************************************* Mona Wong Web & Mobile Application Developer San Diego Supercomputer Center "I've learned that people will forget what you said, people will forget what you did, but people will never forget how you made them feel." --- Maya Angelou ********************************************* _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: From Jane.Tan at murdoch.edu.au Mon Feb 11 10:59:37 2019 From: Jane.Tan at murdoch.edu.au (Jane Tan) Date: Mon, 11 Feb 2019 09:59:37 +0000 Subject: [FieldTrip] Is it normal to have NaNs in source analysis output? In-Reply-To: <2980ac930dd14d6598a29529b5671f90@MEXPR01MB1237.ausprd01.prod.outlook.com> References: , <2980ac930dd14d6598a29529b5671f90@MEXPR01MB1237.ausprd01.prod.outlook.com> Message-ID: Hi Jan-Mathjis, What a relief and thank you very much! Cheers, Jane ________________________________ From: fieldtrip on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Monday, 11 February 2019 3:39 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] Is it normal to have NaNs in source analysis output? Hi Jane, Yes, it is not a problem (and expected) for the outside-of-the-head dipole positions to be represented by NaNs. Best wishes and keep up the good work, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 11 Feb 2019, at 03:42, Jane Tan > wrote: Dear Fieldtrippers, My name is Jane, and this is my first time posting a question to this community. First and foremost, I would like to apologise if my question is extremely trivial. I am trying to perform source analysis using the Beamformer DICS approach on EEG data. My data has been preprocessed using the EEGlab toolbox, and in this particular instance I am only interested in 20 Hz source space activity for time periods around event 'SS'. My question is very simple: is it normal to get NaNs in the avg.pow output of the source analysis? It seems to make sense; positions in the grid that do not have 20 Hz reconstructed activity would be represented by NaNs. However, I'm a novice (in all aspects: Matlab, EEG analysis, and Fieldtrip), and for a sanity check, would like to confirm that getting NaNs in my source output is normal. Here is the code I executed: %% Loading data [EEG] = pop_loadset('E:\preprocesseddata.set'); EEG = pop_epoch( EEG, { 'SSstopDIN' }, [-0.5 0.8]); % Epoch to event of interest 'SS' dataSS_epoched = eeglab2fieldtrip(EEG, 'preprocessing'); % Convert eeglab dataset to fieldtrip data %% Calculating the cross spectral density matrix cfg = []; cfg.method = 'mtmfft'; cfg.taper = 'hanning'; cfg.output = 'powandcsd'; cfg.foi = 4:40; cfg.keeptrials = 'no'; TFR_SS = ft_freqanalysis(cfg, dataSS_epoched); %% Computing leadfield cfg = []; cfg.headmodel = vol; %using BEM head model from FT template cfg.reducerank = 3; %default = 3 for EEG cfg.elec = elec_aligned cfg.grid.resolution = 0.5; % use a 3-D grid with a 0.5 cm resolution cfg.grid.unit = 'cm'; [grid] = ft_prepare_leadfield(cfg); %% Source analysis (without contrasts; just testing source reconstruction for one condition first) cfg = []; cfg.method = 'dics'; cfg.frequency = 20; cfg.grid = grid; cfg.headmodel = vol; cfg.elec = elec_aligned; sourceSS_nocon = ft_sourceanalysis(cfg, TFR_SS); % Here, sourceSS_nocon.avg.pow shows NaNs in some cells and not others My sincere thanks in advance! Best regards, Jane Jane Tan, PhD Candidate School of Psychology and Exercise Science | Murdoch University Room 3.001 Social Science Building, 90 South Street, Murdoch WA 6150 | Email: Jane.Tan at murdoch.edu.au _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alexandre.chalard at inserm.fr Mon Feb 11 16:35:09 2019 From: alexandre.chalard at inserm.fr (Alexandre Chalard) Date: Mon, 11 Feb 2019 16:35:09 +0100 Subject: [FieldTrip] ft_freqstatistics not working on mac Message-ID: <70F24501-5E08-4D56-B91F-1AE0989C81AD@inserm.fr> Dear all, My OS is OS X El capitan 10.11.6 I am on matlab R2017a, I download the toolbox on the 31th December 2018. I also have the image processing toolbox. I have no idea where is the issue, because it perfectly works on my PC which is on the same matlab version just the OS is different. When the function run it looks like matlab is on a while loop. Any suggestion ? Thank you Alexandre Chalard -- PhD student Toulouse NeuroImaging Center UMR1214 - Inserm/UPS CHU PURPAN - Pavillon BAUDOT 3ème étage, Bureau 308 31024 TOULOUSE CEDEX 3 Tel: 05.62.74.62.02 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From mona at sdsc.edu Mon Feb 11 20:32:51 2019 From: mona at sdsc.edu (Wong-Barnum, Mona) Date: Mon, 11 Feb 2019 19:32:51 +0000 Subject: [FieldTrip] plotting tutorial In-Reply-To: <6E0506AF-0042-4DE4-B6B7-041D4A1F1F82@donders.ru.nl> References: <8ABE1405-1C8E-40B7-9C5E-AA2AB92618A6@sdsc.edu> <6E0506AF-0042-4DE4-B6B7-041D4A1F1F82@donders.ru.nl> Message-ID: Yes, I have tried the neuromag306all.lay and neuromag306cmb.lay. My issue is I don’t know what format/data structure my data needs to be in order to use these layouts since the example neuromag306.mat was empty so didn’t work with the neuromag layouts. I did read in my neuromag data using the ft_read_header() and ft_read_data() but not sure how to use it with the plotting function ft_multiplotER(), ft_topoplotER() and/or ft_topoplotTFR(). All help/tips are welcome thanks, Mona On Feb 10, 2019, at 11:42 PM, Schoffelen, J.M. (Jan Mathijs) > wrote: Hi Mona, Have you tried the layout files that are contained in fieldtrip/template/layout. I think that there should be a few that would suit your needs. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 9 Feb 2019, at 03:33, Wong-Barnum, Mona > wrote: Hi: I’m working my way through the plotting tutorial at http://www.fieldtriptoolbox.org/tutorial/plotting/. I would like to use the neuromag306all.lay layout to plot the data. I tried the neuromag306.mat from ftp but that didn’t work; it seems the data read in from neuromag306.mat doesn’t actually contain any data: sens sens = struct with fields: chanpos: [2x3 double] elecpos: [2x3 double] label: {2x1 cell} unit: ‘cm' I have my own neuromag .fif file but not sure how to use the layout to plot my data (read in following the instructions at page http://www.fieldtriptoolbox.org/getting_started/neuromag/): hdr hdr = struct with fields: label: {389x1 cell} nChans: 389 Fs: 603.1072 grad: [1x1 struct] elec: [1x1 struct] nSamples: 192000 nSamplesPre: 0 nTrials: 1 orig: [1x1 struct] chantype: {389x1 cell} chanunit: {389x1 cell} All tips/help are appreciated. thanks, Mona _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 ********************************************* Mona Wong Web & iPad Application Developer San Diego Supercomputer Center "I can't change the direction of the wind, but I can adjust my sails to always reach my destination." --- Jimmy Dean ********************************************* -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alexandre.chalard at inserm.fr Mon Feb 11 21:48:51 2019 From: alexandre.chalard at inserm.fr (Alexandre Chalard) Date: Mon, 11 Feb 2019 21:48:51 +0100 Subject: [FieldTrip] Fwd: ft_freqstatistics not working on mac References: <1F212210-C2EE-4ACF-B4CC-648AEE25FA3A@inserm.fr> Message-ID: <09D9C8C6-2A43-4D14-AE18-9839DB148E7D@inserm.fr> Dear all, My OS is OS X El capitan 10.11.6 I am on matlab R2017a, I download the toolbox on the 31th December 2018. I also have the image processing toolbox. I have no idea where is the issue, because it perfectly works on my PC which is on the same matlab version just the OS is different. When the function run it looks like matlab is on a while loop. Any suggestion ? Thank you > Début du message réexpédié : > Is this something that started happening recently? What mac os/matlab/ft version? i had the same issue … first i thought i may not have the image processing toolbox installed. > De: Alexandre Chalard > Objet: ft_freqstatistics not working on mac > Date: 10 février 2019 23:58:18 UTC+1 > À: fieldtrip at science.ru.nl > > Dear all, > > When I try to perform an analysis with my PC with the following code : > > cfg.neighbours = ft_prepare_neighbours(cfg_neighb, DataP); > cfg.channel = ROI; > cfg.latency = [0 100]; > cfg.frequency = [13 30]; > cfg.method = 'montecarlo'; > cfg.statistic = 'ft_statfun_indepsamplesT'; > cfg.correctm = 'cluster'; > cfg.clusteralpha = 0.05; > cfg.clusterstatistic = 'maxsum'; > cfg.minnbchan = 2; > cfg.tail = 0; > cfg.clustertail = 0; > cfg.alpha = 0.025; > cfg.numrandomization = 100; > cfg.avgovertime = 'yes'; > cfg.avgoverfreq = 'yes'; > > design = []; > design(1:numel(PFiles)) = 1; > design(end+1:end+numel(TFiles)) = 2; > > cfg.design = design; > cfg.ivar = 1; > > stat = ft_freqstatistics(cfg,DataP,DataT); > > Everything is working, but when I try with my macbook pro, the function doesn’t work. > The permutation progress take directly the value 100 on 100, and the matlab status is busy with no return and no possibility to break the code (ctrl-c), I need to close matlab to stop the execution. > > Does anyone have an idea or have the same problem? > > Kind regards, > > Alexandre Chalard > -- > PhD student > > Alexandre Chalard -- PhD student Toulouse NeuroImaging Center UMR1214 - Inserm/UPS CHU PURPAN - Pavillon BAUDOT 3ème étage, Bureau 308 31024 TOULOUSE CEDEX 3 Tel: 05.62.74.62.02 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From martin.rosenfelder at uni-ulm.de Mon Feb 11 22:25:14 2019 From: martin.rosenfelder at uni-ulm.de (Martin Rosenfelder) Date: Mon, 11 Feb 2019 22:25:14 +0100 Subject: [FieldTrip] Fwd: ft_freqstatistics not working on mac In-Reply-To: <09D9C8C6-2A43-4D14-AE18-9839DB148E7D@inserm.fr> References: <1F212210-C2EE-4ACF-B4CC-648AEE25FA3A@inserm.fr> <09D9C8C6-2A43-4D14-AE18-9839DB148E7D@inserm.fr> Message-ID: <06c56f7d-5864-5674-2b7a-93233dd0fc6f@uni-ulm.de> Dear Alexandre, I had a similar issue on OS HighSierra using MATLAB R2017a, however with another Fieldtrip version. Eventually, I got rid of the error by installing an older version of the toolbox. Currently, I am working with Fieldtrip - 20180402 and ft_freqstatistics is behaving normally. Best, Martin Am 11.02.19 um 21:48 schrieb Alexandre Chalard: > Dear all, > > My OS is OS X El capitan 10.11.6 I am on matlab R2017a, I download the > toolbox on the 31th December 2018. > I also have the image processing toolbox. > I have no idea where is the issue, because it perfectly works on my PC > which is on the same matlab version just the OS is different. > When the function run it looks like matlab is on a while loop. > > Any suggestion ? > > Thank you > >> Début du message réexpédié : >> > Is this something that started happening recently? What mac os/matlab/ft version? > > i had the same issue … first i thought i may not have the image processing toolbox installed. > >> *De: *Alexandre Chalard > > >> *Objet: **ft_freqstatistics not working on mac* >> *Date: *10 février 2019 23:58:18 UTC+1 >> *À: *fieldtrip at science.ru.nl >> >> Dear all, >> >> When I try to perform an analysis with my PC with the following code : >> >> cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, DataP); >> cfg.channel         = ROI; >> cfg.latency         = [0 100]; >> cfg.frequency       = [13 30]; >> cfg.method         = 'montecarlo'; >> cfg.statistic = 'ft_statfun_indepsamplesT'; >> cfg.correctm         = 'cluster'; >> cfg.clusteralpha     = 0.05; >> cfg.clusterstatistic = 'maxsum'; >> cfg.minnbchan       = 2; >> cfg.tail         = 0; >> cfg.clustertail     = 0; >> cfg.alpha         = 0.025; >> cfg.numrandomization = 100; >> cfg.avgovertime     = 'yes'; >> cfg.avgoverfreq     = 'yes'; >> >> design = []; >> design(1:numel(PFiles))         = 1; >> design(end+1:end+numel(TFiles)) = 2; >> >> cfg.design = design; >> cfg.ivar   = 1; >> >> stat = ft_freqstatistics(cfg,DataP,DataT); >> >> Everything is working, but when I try with my macbook pro, the >> function doesn’t work. >> The permutation progress take directly the value 100 on 100, and the >> matlab status is busy with no return and no possibility to break the >> code (ctrl-c), I need to close matlab to stop the execution. >> >> Does anyone have an idea or have the same problem? >> >> Kind regards, >> >> Alexandre Chalard >> -- >> PhD student >> >> > > Alexandre Chalard > -- > PhD student > Toulouse NeuroImaging Center UMR1214 - Inserm/UPS > CHU PURPAN - Pavillon BAUDOT > 3ème étage, Bureau 308 > 31024 TOULOUSE CEDEX 3 > Tel: 05.62.74.62.02 > > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 -- M.Sc.-Psych. Martin Rosenfelder Research Associate PhD Student Clinical and Biological Psychology Ulm University Room: 47.2.259 Phone: +49 731-50 26592 E-mail: martin.rosenfelder at uni-ulm.de -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From nathanfaivre at gmail.com Tue Feb 12 14:20:17 2019 From: nathanfaivre at gmail.com (Nathan Faivre) Date: Tue, 12 Feb 2019 14:20:17 +0100 Subject: [FieldTrip] postdoc position LPNC Grenoble, France Message-ID: <1549977526.local-5a5b4108-be83-v1.5.5-b7939d38@getmailspring.com> We are seeking a highly motivated postdoc candidate to investigate the neural correlates of perceptual consciousness and metacognition. The position is part of MetAction, an ERC-funded project lead by Nathan Faivre in Grenoble (France), which aims to document the contribution of bodily signals to metacognition, and explore metacognitve deficits in schizophrenia. Contract Period: 18 months (renewable) Expected date of employment: 1 May 2019 Remuneration: 2530€ - 3509€ / month (gross, according to experience) Activities The selected candidate will develop experimental paradigms, collect behavioral and electrophysiological data, analyze and interpret data, and draft manuscripts in close collaboration with Nathan Faivre. The research will involve healthy volunteers as well as individuals with epilepsy and schizophrenia. Skills Applicants should have strong skills in computer programming, statistics, and signal processing (Matlab, R, or Python). Applicants should speak basic French, or be willing to learn rapidly in order to interact with participants. Experience in psychophysics, (intracranial) electroencephalography, signal detection theory, and/or computational modeling is a plus. Applicants with a background in engineering, computer science, or physics are also encouraged to apply. Work context The work will take place at the Laboratoire de Psychologie et Neurogognition in Grenoble (France). The laboratory is associated with the National Centre for Scientific Research (CNRS), and offers state of the art platforms for behavioral, EEG, and fMRI experiments. Part of the research will be performed in collaboration with hospitals in Grenoble, Geneva, and Versailles. All expenses related to the project will be covered by the ERC grant. Constraints and risks Short travels in France and abroad should be expected for conferences and collaborations. The contract is renewable once upon common agreement. Apply here: http://bit.ly/2MWh48k -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From vale.nasato at gmail.com Tue Feb 12 15:37:26 2019 From: vale.nasato at gmail.com (Valentina Nasato) Date: Tue, 12 Feb 2019 15:37:26 +0100 Subject: [FieldTrip] Source Message-ID: <5c62da24.1c69fb81.feff6.dd2b@mx.google.com> Good morning, sir, I'm Valentina, I calculated the sources of the fem model through ft_sourceanalysis with the eloreta method. I would like to put the opition to calculate the inverse kernel. At the moment I have written these parameters for the cfg cfg.keepfilter='yes'; cfg.keepmom='yes'; cfg.method = 'eloreta'; cfg.headmodel = headmodel_fem_eeg_tr; cfg.elec=elec; cfg.grid=sourcemodel_fem; keepmom what does it correspond to? and in struct source.avg.ori what does it mean? also how do I manage cell files {}('mom'',filter','ori')? Thank you very for the help -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From vale.nasato at gmail.com Tue Feb 12 16:43:00 2019 From: vale.nasato at gmail.com (Valentina Nasato) Date: Tue, 12 Feb 2019 16:43:00 +0100 Subject: [FieldTrip] I:Using inverse kernel with EEG to calculate sources In-Reply-To: <5c62da24.1c69fb81.feff6.dd2b@mx.google.com> References: <5c62da24.1c69fb81.feff6.dd2b@mx.google.com> Message-ID: <5c62e981.1c69fb81.95385.1d77@mx.google.com> Good morning, sir, I'm Valentina, I calculated the sources of the fem model through ft_sourceanalysis with the eloreta method. I would like to put the opition to calculate the inverse kernel. At the moment I have written these parameters for the cfg cfg.keepfilter='yes'; cfg.keepmom='yes'; cfg.method = 'eloreta'; cfg.headmodel = headmodel_fem_eeg_tr; cfg.elec=elec; cfg.grid=sourcemodel_fem; keepmom what does it correspond to? and in struct source.avg.ori what does it mean? also how do I manage cell files {}('mom'',filter','ori')? Thank you very for the help -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From vale.nasato at gmail.com Wed Feb 13 11:39:25 2019 From: vale.nasato at gmail.com (Valentina Nasato) Date: Wed, 13 Feb 2019 11:39:25 +0100 Subject: [FieldTrip] I: Using inverse kernel with EEG to calculate sources In-Reply-To: <5c62e981.1c69fb81.95385.1d77@mx.google.com> References: <5c62da24.1c69fb81.feff6.dd2b@mx.google.com> <5c62e981.1c69fb81.95385.1d77@mx.google.com> Message-ID: <5c63f3db.1c69fb81.69b79.6ba4@mx.google.com> Inviato da Posta per Windows 10 Da: Valentina Nasato Inviato: martedì 12 febbraio 2019 16:42 A: fieldtrip at science.ru.nl Oggetto: I:Using inverse kernel with EEG to calculate sources Good morning, sir, I'm Valentina, I calculated the sources of the fem model through ft_sourceanalysis with the eloreta method. I would like to put the opition to calculate the inverse kernel. At the moment I have written these parameters for the cfg cfg.keepfilter='yes'; cfg.keepmom='yes'; cfg.method = 'eloreta'; cfg.headmodel = headmodel_fem_eeg_tr; cfg.elec=elec; cfg.grid=sourcemodel_fem; keepmom what does it correspond to? and in struct source.avg.ori what does it mean? also how do I manage cell files {}('mom'',filter','ori')? Thank you very for the help -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From pelagietemgoua at yahoo.fr Wed Feb 13 14:41:18 2019 From: pelagietemgoua at yahoo.fr (=?UTF-8?Q?p=C3=A9lagie_Temgoua?=) Date: Wed, 13 Feb 2019 13:41:18 +0000 (UTC) Subject: [FieldTrip] Difficulty with ft_connectivityanalysis References: <26068173.4921137.1550065278353.ref@mail.yahoo.com> Message-ID: <26068173.4921137.1550065278353@mail.yahoo.com> Hello!This is a part of my code : TFR_result = ft_freqanalysis(cfg, dataica);%cfg = [];cfg.method      = 'plv';plv = ft_connectivityanalysis(cfg, TFR_result ); I want to have graph and draw adjacency matrix of my phase locked value.I want to use it to compute degree, density and strenght of that matrix. Please i need help. Pélagie Flore TEMGOUA NANFACK Chercheur/ Informaticienne MINRESI/CNDTpelagietemgoua at gmail.com/pelagietemgoua at yahoo.fr Tél : (00237) 675 39 66 33/ 696 20 51 02 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From vabelyaeva94 at gmail.com Wed Feb 13 14:28:55 2019 From: vabelyaeva94 at gmail.com (Valeriya Belyaeva) Date: Wed, 13 Feb 2019 16:28:55 +0300 Subject: [FieldTrip] correlation with behavioural data and cluster statistics Message-ID: Dear fieldtrip developers, I have a question about correlation of neuronal and behavioural data. You have discussed this question here: http://www.fieldtriptoolbox.org/faq/how_can_i_test_for_correlations_between_neuronal_data_and_quantitative_stimulus_and_behavioural_variables/ I have taken the code, which was given as an example and added cluster-based correction method. My goal is to perform correlation between neuronal and behavioural data and then to account for multiple comparisons with cluster statistics. Could you, please, tell me, whether this script does it? Here is the script: % example script cfg = []; cfg.statistic = 'ft_statfun_correlationT'; cfg.method = 'montecarlo'; cfg.numrandomization = 1000; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.025; cfg_neighb.method = 'triangulation'; cfg_neighb.layout = 'acticap_62'; cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_brain{:}); n1 = 42; % n1 is the number of subjects design(1,1:n1) = behav_data(:,1); % mean reaction time by subject cfg.design = design; cfg.ivar = 1; stat = ft_freqstatistics(cfg, data_brain{:}); Thank you a lot in advance! -- Best regards, Valeriya Belyaeva HSE, Cognitive science and technologies -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alejandra.korovaichuk at ctb.upm.es Thu Feb 14 11:29:59 2019 From: alejandra.korovaichuk at ctb.upm.es (=?UTF-8?Q?Mar=C3=ADa_Alejandra_Korovaichuk?=) Date: Thu, 14 Feb 2019 11:29:59 +0100 Subject: [FieldTrip] Error ussingg ft_appendspike Message-ID: Hi, I am trying to append LFP data (from a continous matlab file), with a spike data (from wave_clus), into one large file to do some analysis. I tried many options but I always have the same error (Error using ft_appendspike (line 112) could not find the trial information in the continuous data) I add all the requiered info manually in order to read it but there is something missing I can't find. Any help is welcome, thanks! -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Thu Feb 14 12:14:21 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 14 Feb 2019 11:14:21 +0000 Subject: [FieldTrip] Error ussingg ft_appendspike In-Reply-To: References: Message-ID: Could you please articulate your question with a little bit more detail? See http://www.fieldtriptoolbox.org/faq/how_to_ask_good_questions_to_the_community/ for some inspiration. Best wishes, Jan-Mathijs On 14 Feb 2019, at 11:29, María Alejandra Korovaichuk > wrote: Hi, I am trying to append LFP data (from a continous matlab file), with a spike data (from wave_clus), into one large file to do some analysis. I tried many options but I always have the same error (Error using ft_appendspike (line 112) could not find the trial information in the continuous data) I add all the requiered info manually in order to read it but there is something missing I can't find. Any help is welcome, thanks! _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alejandra.korovaichuk at ctb.upm.es Thu Feb 14 13:57:57 2019 From: alejandra.korovaichuk at ctb.upm.es (=?UTF-8?Q?Mar=C3=ADa_Alejandra_Korovaichuk?=) Date: Thu, 14 Feb 2019 13:57:57 +0100 Subject: [FieldTrip] Error ussingg ft_appendspike In-Reply-To: References: Message-ID: Hi again, This is my question (I hope now would be much clear): I am trying to do a "preprocessing and analysis of spike+local field potential data". I followed the tutorial and everything was nice and clear with your data. However I found some issues with my own data. My LFP data is a .mat file and I tranformed it into a FT data structure. The only thing I don't have is the header (hdr), because the original recording came from a .dat file from Inomed recordings. Anyway, even without the header I am able to plot the data and to see it. The spikes were sorted with wave_clus so here I don't have any issue, FT open it and I can work with them perfectly. The step I am following are: 1) Read the LFP and spikes files with FT. No problem so far except for the header in the LFP file 2) Define trial and preprocessing of both files separately 3) read and select the spike 4)The first problem is here in: construct a cfg.trl matrix to preprocess the LFP. I can preprocess like a continuous data (1 column of voltages and the sampling freq): load(fullfile(data_dir,'lfp.mat')); cfg = []; cfg.continuous = 'yes'; cfg.channel=lfp_FT.label; cfg.padding = 10; cfg.dftfreq = [50-1*(1/10):(1/10):50+1*(1/10) ]; % filter out 50 hz line noise cfg.bsfilter = 'yes'; data_lfp = ft_preprocessing(cfg, lfp_FT); % read in the LFP I tried many ways following the different tutorials and nothing works properly because even when FT let me ADD THE TRIAL INFORMATION "artificially" into my data_lfp, later on it would show me the Error using ft_appendspike (line 112): could not find the trial information in the continuous data" I plot both files and the spikes match perfectly with the lfp data, so Matlab is reading them well, but I am doing something wrong when I try to create the lfp FT structure. Thanks for your help, Maria El jue., 14 feb. 2019 a las 11:29, María Alejandra Korovaichuk (< alejandra.korovaichuk at ctb.upm.es>) escribió: > Hi, > > I am trying to append LFP data (from a continous matlab file), with a > spike data (from wave_clus), into one large file to do some analysis. > > I tried many options but I always have the same error (Error using > ft_appendspike (line 112) > > could not find the trial information in the continuous data) > > I add all the requiered info manually in order to read it but there is > something missing I can't find. > > Any help is welcome, thanks! > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From pelagietemgoua at yahoo.fr Thu Feb 14 13:58:02 2019 From: pelagietemgoua at yahoo.fr (=?UTF-8?Q?p=C3=A9lagie_Temgoua?=) Date: Thu, 14 Feb 2019 12:58:02 +0000 (UTC) Subject: [FieldTrip] Spectral connectivity References: <1154292143.443638.1550149082022.ref@mail.yahoo.com> Message-ID: <1154292143.443638.1550149082022@mail.yahoo.com> Hello!Please how do i compute Phase locked value using spectral connectivity? I have a an EEG (EDF file).Thank you.  Pélagie Flore TEMGOUA NANFACK Chercheur/ Informaticienne MINRESI/CNDTpelagietemgoua at gmail.com/pelagietemgoua at yahoo.fr Tél : (00237) 675 39 66 33/ 696 20 51 02 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Thu Feb 14 14:27:13 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 14 Feb 2019 13:27:13 +0000 Subject: [FieldTrip] Difficulty with ft_connectivityanalysis References: <0C7222ED-35CC-43E7-ADDD-BBCFFD945F5C@donders.ru.nl> Message-ID: <0D378716-826C-4994-8BD8-48C6E780BF0C@donders.ru.nl> Hi Pélagie, Could you please check http://www.fieldtriptoolbox.org/faq/how_to_ask_good_questions_to_the_community/ https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002202 and ask your question in a more constructive way? Also, I think that there is ample documentation on the fieldtrip website that should get you started. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 13 Feb 2019, at 14:41, pélagie Temgoua > wrote: Hello! This is a part of my code : TFR_result = ft_freqanalysis(cfg, dataica); %cfg = []; cfg.method = 'plv'; plv = ft_connectivityanalysis(cfg, TFR_result ); I want to have graph and draw adjacency matrix of my phase locked value. I want to use it to compute degree, density and strenght of that matrix. Please i need help. Pélagie Flore TEMGOUA NANFACK Chercheur/ Informaticienne MINRESI/CNDT pelagietemgoua at gmail.com/pelagietemgoua at yahoo.fr Tél : (00237) 675 39 66 33/ 696 20 51 02 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Thu Feb 14 14:26:20 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 14 Feb 2019 13:26:20 +0000 Subject: [FieldTrip] Error ussingg ft_appendspike In-Reply-To: References: Message-ID: <16FA2EA5-2AE8-4A34-9B7C-D74B4F0D3960@donders.ru.nl> Hi Maria, I am not using combined spike/lfp data myself, but I suggest that you look into the code of ft_appendspike in a little more detail. This will give you some idea about why the error occurs. My initial thought is that ft_appendspike hasn’t matured (in terms of backward compatibility) along with the fieldtrip code base (and more strict internal data representation). Any improvements in the code will therefore be most welcome. I suspect that the current issue results from the fact that the code tries to look into data.cfg. … .trl to extract information about the original sampling. Since your data is coming from somewhere else, this information is not present. Also, current data organization standards actually prohibit to look into data.cfg.previous. … trl, and require this information be represented in a field called .sampleinfo. I suggest that you search in the documentation for ‘sampleinfo’ to get an impression how this information is used throughout the code, and how it is generated if it doesn’t exist (hint: use ft_checkdata(data,'hassampleinfo’, true); Please also, if you have fixed your version of ft_appendspike, do submit a Pull Request on github so that we can incorporate your fixes into the codebase. Best wishes Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 14 Feb 2019, at 13:57, María Alejandra Korovaichuk > wrote: Hi again, This is my question (I hope now would be much clear): I am trying to do a "preprocessing and analysis of spike+local field potential data". I followed the tutorial and everything was nice and clear with your data. However I found some issues with my own data. My LFP data is a .mat file and I tranformed it into a FT data structure. The only thing I don't have is the header (hdr), because the original recording came from a .dat file from Inomed recordings. Anyway, even without the header I am able to plot the data and to see it. The spikes were sorted with wave_clus so here I don't have any issue, FT open it and I can work with them perfectly. The step I am following are: 1) Read the LFP and spikes files with FT. No problem so far except for the header in the LFP file 2) Define trial and preprocessing of both files separately 3) read and select the spike 4)The first problem is here in: construct a cfg.trl matrix to preprocess the LFP. I can preprocess like a continuous data (1 column of voltages and the sampling freq): load(fullfile(data_dir,'lfp.mat')); cfg = []; cfg.continuous = 'yes'; cfg.channel=lfp_FT.label; cfg.padding = 10; cfg.dftfreq = [50-1*(1/10):(1/10):50+1*(1/10) ]; % filter out 50 hz line noise cfg.bsfilter = 'yes'; data_lfp = ft_preprocessing(cfg, lfp_FT); % read in the LFP I tried many ways following the different tutorials and nothing works properly because even when FT let me ADD THE TRIAL INFORMATION "artificially" into my data_lfp, later on it would show me the Error using ft_appendspike (line 112): could not find the trial information in the continuous data" I plot both files and the spikes match perfectly with the lfp data, so Matlab is reading them well, but I am doing something wrong when I try to create the lfp FT structure. Thanks for your help, Maria El jue., 14 feb. 2019 a las 11:29, María Alejandra Korovaichuk (>) escribió: Hi, I am trying to append LFP data (from a continous matlab file), with a spike data (from wave_clus), into one large file to do some analysis. I tried many options but I always have the same error (Error using ft_appendspike (line 112) could not find the trial information in the continuous data) I add all the requiered info manually in order to read it but there is something missing I can't find. Any help is welcome, thanks! _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Thu Feb 14 14:36:25 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 14 Feb 2019 13:36:25 +0000 Subject: [FieldTrip] plotting tutorial In-Reply-To: References: <8ABE1405-1C8E-40B7-9C5E-AA2AB92618A6@sdsc.edu> <6E0506AF-0042-4DE4-B6B7-041D4A1F1F82@donders.ru.nl> Message-ID: Hi Mona, I think that you first need to look into what you actually want to achieve. From the context of this thread it seems that you want to visualise data that has been collected with a ‘neuromag306’ MEG device, which is further supported by the fact that you mentioned having an ‘.fif’ file. However, you don’t mention whether you have read in actual data to-be-plotted. You only mention that you have read in the header information (as per ft_read_header). Using ft_read_data is not going to do the trick. In order to use the higher level plotting functions, you need to create a data object as per ft_preprocessing. Please refer to the tutorial documentation on http://www.fieldtriptoolbox.org/tutorial/natmeg/preprocessing/, for instance. Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands Yes, I have tried the neuromag306all.lay and neuromag306cmb.lay. My issue is I don’t know what format/data structure my data needs to be in order to use these layouts since the example neuromag306.mat was empty so didn’t work with the neuromag layouts. I did read in my neuromag data using the ft_read_header() and ft_read_data() but not sure how to use it with the plotting function ft_multiplotER(), ft_topoplotER() and/or ft_topoplotTFR(). All help/tips are welcome thanks, Mona On Feb 10, 2019, at 11:42 PM, Schoffelen, J.M. (Jan Mathijs) > wrote: Hi Mona, Have you tried the layout files that are contained in fieldtrip/template/layout. I think that there should be a few that would suit your needs. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 9 Feb 2019, at 03:33, Wong-Barnum, Mona > wrote: Hi: I’m working my way through the plotting tutorial at http://www.fieldtriptoolbox.org/tutorial/plotting/. I would like to use the neuromag306all.lay layout to plot the data. I tried the neuromag306.mat from ftp but that didn’t work; it seems the data read in from neuromag306.mat doesn’t actually contain any data: sens sens = struct with fields: chanpos: [2x3 double] elecpos: [2x3 double] label: {2x1 cell} unit: ‘cm' I have my own neuromag .fif file but not sure how to use the layout to plot my data (read in following the instructions at page http://www.fieldtriptoolbox.org/getting_started/neuromag/): hdr hdr = struct with fields: label: {389x1 cell} nChans: 389 Fs: 603.1072 grad: [1x1 struct] elec: [1x1 struct] nSamples: 192000 nSamplesPre: 0 nTrials: 1 orig: [1x1 struct] chantype: {389x1 cell} chanunit: {389x1 cell} All tips/help are appreciated. thanks, Mona _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 ********************************************* Mona Wong Web & iPad Application Developer San Diego Supercomputer Center "I can't change the direction of the wind, but I can adjust my sails to always reach my destination." --- Jimmy Dean ********************************************* _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Thu Feb 14 14:30:11 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 14 Feb 2019 13:30:11 +0000 Subject: [FieldTrip] Using inverse kernel with EEG to calculate sources In-Reply-To: <5c63f3db.1c69fb81.69b79.6ba4@mx.google.com> References: <5c62da24.1c69fb81.feff6.dd2b@mx.google.com> <5c62e981.1c69fb81.95385.1d77@mx.google.com> <5c63f3db.1c69fb81.69b79.6ba4@mx.google.com> Message-ID: <78C05A86-BA70-400D-B884-807EC62F4F63@donders.ru.nl> Hi Valentina, Could you please check http://www.fieldtriptoolbox.org/faq/how_to_ask_good_questions_to_the_community/ https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002202 and ask your question in a more constructive way? Also, I think that there is ample documentation on the fieldtrip website that should get you started. With respect to your question pertaining to ‘managing cell files’, please refer to the basic matlab documentation. Also, please note that there are about 1500 e-mail addresses registered to this list, so in general I think it is not a good idea to keep reposting the same e-mail, even if you are very eager to obtain an answer. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 13 Feb 2019, at 11:39, Valentina Nasato > wrote: Inviato da Posta per Windows 10 Da: Valentina Nasato Inviato: martedì 12 febbraio 2019 16:42 A: fieldtrip at science.ru.nl Oggetto: I:Using inverse kernel with EEG to calculate sources Good morning, sir, I'm Valentina, I calculated the sources of the fem model through ft_sourceanalysis with the eloreta method. I would like to put the opition to calculate the inverse kernel. At the moment I have written these parameters for the cfg cfg.keepfilter='yes'; cfg.keepmom='yes'; cfg.method = 'eloreta'; cfg.headmodel = headmodel_fem_eeg_tr; cfg.elec=elec; cfg.grid=sourcemodel_fem; keepmom what does it correspond to? and in struct source.avg.ori what does it mean? also how do I manage cell files {}('mom'',filter','ori')? Thank you very for the help _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From pelagietemgoua at yahoo.fr Thu Feb 14 14:54:43 2019 From: pelagietemgoua at yahoo.fr (=?UTF-8?Q?p=C3=A9lagie_Temgoua?=) Date: Thu, 14 Feb 2019 13:54:43 +0000 (UTC) Subject: [FieldTrip] manipulation of an EDF file References: <817494199.512186.1550152483853.ref@mail.yahoo.com> Message-ID: <817494199.512186.1550152483853@mail.yahoo.com> Dear community, My name is Pelagie Temgoua I am Phd student inuniversity of Dschang in Cameroon. In Currently I am analysing EEG data (EDFfile). I want to read EDf file, choose reference electrode, removeepoch, filter a specify frequency band, compute phase locked value (PLV), phaselag index (PLI) and directed function transfert (DTF). Draw adjacency matrix and graph of PLV, PLI, DTF.After, I want to compute density, strength and degree of each matrix.   Now, I have this code: %read data begin % cfg = []; % cfg.dataset = 'h01.edf'; % data = ft_preprocessing(cfg); %read data end   %cleaning data begin. Use artifacts % cfg          = []; % cfg.method   = 'trial'; % cfg.alim     = 5e-5;%280e-16; % clean_data        =ft_rejectvisual(cfg,data); %cleaning data end %30s epoch begin.       cfg = []; cfg.dataset                 = 'h01.edf'; cfg.trialfun                = 'ft_trialfun_general'; % this is the default cfg.trialdef.eventtype      = 'backpanel trigger'; % cfg.trialdef.eventvalue     = 3;% the value of the stimulus trigger for fully incongruent (FIC). % cfg.trialdef.prestim        = 1;% in seconds % cfg.trialdef.poststim       = 2;% in seconds cfg.trialdef.triallength = 10; cfg.trialdef.ntrials     = 3; cfg = ft_definetrial(cfg);   cfg.memory = 'high'; cfg.artfctdef.reject = 'complete'; %[cfg, artifact_EOG] = ft_artifact_zvalue(cfg);     %cfg.artfctdef.eog.artifact =artifact_EOG; % cfg.artfctdef.jump.artifact = artifact_jump; % cfg.artfctdef.muscle.artifact = artifact_muscle; cfg = ft_rejectartifact(cfg);     %cfg.trialfun  ='ft_trialfun_general'; % this is the default % cfg.trialdef.eventtype  = '?'; % %cfg.padding      = 30; % cfg.trialdef.triallength = 10; % cfg.trialdef.ntrials     = 3; % cfg = ft_definetrial(cfg); %filter data begin cfg.continuous   = 'yes'; cfg.channel = 'EEG'; cfg.bsfilter      = 'yes'; cfg.bsfreq = [8 12]; data = ft_preprocessing(cfg); %filter data end %plot(data.time{1}, data.trial{1}(10,:))   cfg              = []; cfg.output       = 'pow'; cfg.channel      = 'EEG'; cfg.method       = 'mtmconvol'; cfg.taper        = 'hanning'; cfg.foi          = 8:12; cfg.t_ftimwin    =7./cfg.foi;  % 7 cycles per time window cfg.toi          = -0.5:0.05:1.5; TFRhann7 = ft_freqanalysis(cfg, data);   cfg              = []; cfg.baseline     = [-0.5 -0.1]; cfg.baselinetype = 'absolute'; cfg.maskstyle    = 'saturation'; cfg.zlim         = [-3e-27 3e-27]; cfg.channel      = 'EEG'; cfg.interactive  = 'no'; %figure %ft_singleplotTFR(cfg, TFRhann7);   cfg = []; cfg.method      = 'plv'; plv = ft_connectivityanalysis(cfg, TFRhann7 ); %figure %ft_singleplotTFR(cfg, plv);   And I don’t know how I can continue. I need help please. Best, Pélagie Flore TEMGOUA NANFACK pelagietemgoua at gmail.com/pelagietemgoua at yahoo.fr Tél : (00237) 675 39 66 33/ 696 20 51 02 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From e.spaak at donders.ru.nl Thu Feb 14 15:24:23 2019 From: e.spaak at donders.ru.nl (Eelke Spaak) Date: Thu, 14 Feb 2019 15:24:23 +0100 Subject: [FieldTrip] Spectral connectivity In-Reply-To: <1154292143.443638.1550149082022@mail.yahoo.com> References: <1154292143.443638.1550149082022.ref@mail.yahoo.com> <1154292143.443638.1550149082022@mail.yahoo.com> Message-ID: Hi Pélagie, To get started, you will want to have a look at the tutorials: http://www.fieldtriptoolbox.org/tutorial/ specifically those on connectivity. Furthermore, the following two resources would probably be of value to you: http://www.fieldtriptoolbox.org/faq/how_to_ask_good_questions_to_the_community/ and https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1002202 . Best, Eelke On Thu, 14 Feb 2019 at 13:58, pélagie Temgoua wrote: > > Hello! > Please how do i compute Phase locked value using spectral connectivity? I have a an EEG (EDF file). > Thank you. > > Pélagie Flore TEMGOUA NANFACK > > Chercheur/ Informaticienne > > MINRESI/CNDT > pelagietemgoua at gmail.com/pelagietemgoua at yahoo.fr > > Tél : (00237) 675 39 66 33/ 696 20 51 02 > > > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From nugenta at mail.nih.gov Thu Feb 14 21:50:54 2019 From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E]) Date: Thu, 14 Feb 2019 20:50:54 +0000 Subject: [FieldTrip] MEG Lab Manager job opening at NIH Message-ID: A lab manager/MEG technologist is being recruited to support the NIMH MEG Core Facility: https://capefox.mua.hrdepartment.com/hrdepartment/ats/Posting/view/4226?site_id=247 The NIH campus is in Bethesda, Maryland, just outside Washington DC. The position is open to both EEG or MEG technologists as well as anyone with a bachelor's degree and neuroimaging or neurophysiology experience. Please forward along to anyone who might be interested. Allison C. Nugent, PhD Director, MEG Core Facility NIMH/NIH/DHHS 10 Center Drive, MSC 1059 Building 10 Room 4N242 Bethesda, MD 20892-1059 301-451-8863 nugenta at nih.gov -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From r.oostenveld at donders.ru.nl Fri Feb 15 09:33:58 2019 From: r.oostenveld at donders.ru.nl (Robert Oostenveld) Date: Fri, 15 Feb 2019 09:33:58 +0100 Subject: [FieldTrip] sample size calculations - nonparametric cluster permutation tests. In-Reply-To: References: Message-ID: <35A01FA2-A72A-424C-9930-70C8963231B4@donders.ru.nl> Hi Martin, Let me CC this to the FieldTrip mailing list, since people there might want to chip in. I am not aware of a way to calculate sample sizes for a non-parametric test in general, although for specific tests there are estimates (see e.g. http://www.stat.purdue.edu/~bacraig/notes582/noether.pdf ). The challenge with the cluster-based permutation test is that the effect is not a-priori specified, and hence the effect size is not quantified. If you don’t know the effect size, you cannot estimate the likelihood of observing that effect (given the number of subjects), or number of subjects (given the desired likelihood of observing the effect). Actually, to be more precise: with the non-parametric permutation test you are not even making an inference about a specific effect, but you are making an inference on the data being exchangeable in general (see also this FAQ on the FieldTrip website). If you do know the effect (as you seem to do), then a non-parametric test might actually not be the most optimal. Your follow up study would have a better power if you were not to ask the question "is there a difference in the distribution of the data in general” (i.e. H0: there is no difference, versus H1 there is a difference), but rather “is there a difference in the channel-time-frequency range (ie.. cluster) that I previously identified”. In the 2nd case it might be possible to average over the region of interest. Still, you may have the issue that the distribution of the statistic-of-interest is not according to a known distribution (or cannot be assumed to have normally distributed error terms), so a non-parametric test might still be in place. Pragmatically I think that you can indeed use a resampling strategy to estimate the required sample size from previously acquired data, asssuming that your previous study is sufficiently overpowered (and of course assuming that your previous study is not a false alarm, but a true rejection of the H0). Another approach (although not 100% addressing your question) is to specify in the new study design to specify that a certain number of subjects are going to be set aside to optimize the analysis pipeline and determine the effect of interest, after which that optimized pipeline will be used to evaluate the effect in all other subjects. However, that does not allow a-priori specification of the number of subjects; it just replaces the effect size estimate from the previous study with an effect size estimate from the pilot group. Many studies actually benefit from having specific hypotheses amd being able to specifying the effect of interest prior to testing that effect. E.g. that is also what is done here . In general, initiating new neuroscience studies again-and-again as if we don’t know anything about the data is simply not efficient. So please do use your existing data in the analysis plan of your new study. best Robert > On 15 Feb 2019, at 01:22, Gallagher, Martin J wrote: > > > Hello Dr. Oostenveld, > > Thank you for developing the nonparametric permutation tests in Fieldtrip and your reviews of the subjects. > > For a grant, my study section is asking for sample size calculations. Is there a way to estimate this? I know it’s probably simple-minded, but could I use permutation tests I’ve run in the past and keep scaling back the number of trials until I get to a N value that still has a p value < 0.025? > > Thank you for considering! > > _______________________________ > Martin J. Gallagher MD, PhD > Associate Professor > Dept. of Neurology, Epilepsy Division > Vanderbilt University School of Medicine > The information contained in this message and any attachments is intended solely for the individual or entity to which it is addressed and may contain confidential and/or privileged material. If you have received this email in error, please contact the sender and delete the material from your system. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jorn at artinis.com Fri Feb 15 11:19:13 2019 From: jorn at artinis.com (=?iso-8859-1?Q?J=F6rn_M._Horschig?=) Date: Fri, 15 Feb 2019 11:19:13 +0100 Subject: [FieldTrip] NIRS/fNIRS symposium May 2019: 3rd ArtScientific Message-ID: <006d01d4c517$e6e0d140$b4a273c0$@artinis.com> Dear list, In May 2019, we are organizing the third ARTScientific symposium. We will create an open platform for both experienced and novice researchers to share experiences, discuss NIRS and enjoy hands-on workshops. We are delighted with our key note speakers, Prof. Clare Elwell (UCL), Prof. Bruno Grassi (Univ. of Udine), Prof. Roi Cohen Kadosh (Univ. of Oxford) and Dr. Chris McKnight (Univ. of St. Andrews), who will provide valuable insight into NIRS and brain and muscle research. We are excited to share the program of our symposium ARTscientific with you (see https://www.artinis.com/artscientific-2019)! You can expect three days of NIRS talks, workshops and wining and dining in a beautiful environment on the seaside of the Netherlands. We would like to cordially invite everyone who is interested in NIRS (with only few spaces left). We carefully selected some very interesting topics for our hands-on NIRS workshops. Several topics will be discussed, including but not limited to functional connectivity, correcting for superficial tissue activation and short channels, hands-on analysis workshops, multimodality (combined EEG/NIRS and EMG/NIRS) and much more! We encourage you to submit your abstract(s) for poster and/or oral presentation to symposium at artinis.com . There is an early bird discount until February 28. Registration costs include accommodation, breakfast, lunch and dinner. Should you have any questions, please feel free to also contact me directly. It would be great seeing some of you there! With best regards, Jörn -- Jörn M. Horschig, PhD Software Manager & Project Leader Artinis Medical Systems | +31 481 350 980 A Einsteinweg 17 6662PW Elst The Netherlands T +31 481 350 980 I www.artinis.com The information in this e-mail is confidential and intended solely for the person to whom it is addressed. If this message is not addressed to you, please be aware that you have no authorization to read this e-mail, to copy it, to furnish it to any person other than the addressee, or to use or misuse its content in any way whatsoever. Should you have received this e-mail by mistake, please bring this to the attention of the sender, after which you are kindly requested to destroy the original message. Sign up for our NIRS newsletter Or meet us here: February 12-14, 2019 - 6th Israeli Conference on Cognition Research, Acre, Israel February 14-15, 2019 - 11th Annual Meeting of the Swiss Society of Sport Science, Freiburg, Switzerland February 20-22, 2019 - German Exercise Science and Training (GEST:19), Würzburg, Germany February 24-27, 2019 - 3rd International Brain Stimulation Conference, Vancouver, Canada March 7-9, 2019 - International Convention of Psychological Science (ICPS), Paris, France March 21-23, 2019 - Society for Research in Child Development (SRCD), Baltimore, Maryland, USA May 9-11, 2019 - Artscientific: 3rd Artinis symposium, Egmond aan Zee, The Netherlands May 28-June 1, 2019 - American College of Sports Medicine (ACSM), Orlando, Florida, USA June 9-13, 2019 - Organization for Human Brain Mapping (OHBM), Rome, Italy July 3-6, 2019 - European College on Sport Science (ECSS), Prague, Czech Republic September 19-21, 2019 - Japanese Society of Physical Fitness and Sports Medicine, Tsukuba, Ibaragi, Japan -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: image001.png Type: image/png Size: 9919 bytes Desc: not available URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From x.vrijdag at auckland.ac.nz Mon Feb 18 07:23:33 2019 From: x.vrijdag at auckland.ac.nz (Xavier Vrijdag) Date: Mon, 18 Feb 2019 06:23:33 +0000 Subject: [FieldTrip] Error in source localisation statistics Message-ID: Hello, I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as they helped me tremendously to do this analysis. After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them. %Calculate the channel covariance matric cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'all'; cfg.keeptrials = 'yes'; timelock = ft_timelockanalysis(cfg, data_filt); %Global filter cfg = []; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.grid = grid; cfg.method = 'lcmv'; cfg.lcmv.projectnoise='yes'; %needed for neural activity index cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights cfg.lcmv.lambda = '5%'; %Regularise a little cfg.rawtrial = 'yes'; % project each single trial through the filter. cfg.keeptrials = 'yes'; source = ft_sourceanalysis(cfg, timelock); cfg = []; cfg.dim = source.dim; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.parameter = 'pow'; cfg.correctm = 'cluster'; cfg.numrandomization = 1000; cfg.alpha = 0.05; % note that this only implies single-sided testing cfg.tail = 0; cfg.design(1,:) = [1:nTrials 1:nTrials]; cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2]; cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials) cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions) stat = ft_sourcestatistics(cfg, source); After the source analysis the source statistics script calls the checkdata script and I get the following error: Index exceeds array bounds. Error in ft_datatype_source (line 183) val{indx(k)}(1,:,:,:) = dat{indx(k)}; Error in ft_checkdata (line 278) data = ft_datatype_source(data); Error in ft_sourcestatistics (line 94) varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no'); Error in sourcelocalisation_N2O (line 114) stat = ft_sourcestatistics(cfg, source); The source struct has the following content: time: [1×15360 double] dim: [24 31 25] inside: [18600×1 logical] pos: [18600×3 double] method: 'rawtrial' trial: [1×24 struct] df: 24 cfg: [1×1 struct] With source.trial: 1×24 struct array with fields: ori pow mom noise filter label filterdimord I would like your help to understand the error and how to fix it. Regards, Xavier Vrijdag -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From pdhami06 at gmail.com Mon Feb 18 16:16:21 2019 From: pdhami06 at gmail.com (Paul Dhami) Date: Mon, 18 Feb 2019 10:16:21 -0500 Subject: [FieldTrip] Custom stat_function for intraclass correlation Message-ID: Dear Fieldtrip community, I am interested in using cluster statistics to assess the significance of intraclass correlations, run for every data time/channel point between two runs. I had a couple of questions: 1. Does testing for significant intraclass correlation clusters make sense in the permutation/reshuffling framework? 2. If yes, how can I implement this? I tried following the ft_statfun_diff script as an example, but run into this error: Error using ft_statistics_montecarlo (line 247) could not determine the parametric critical value for clustering Error in ft_timelockstatistics (line 181) [stat, cfg] = statmethod(cfg, dat, design); Thank you very much. Paul -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alejandra.korovaichuk at ctb.upm.es Tue Feb 19 10:19:14 2019 From: alejandra.korovaichuk at ctb.upm.es (=?UTF-8?Q?Mar=C3=ADa_Alejandra_Korovaichuk?=) Date: Tue, 19 Feb 2019 10:19:14 +0100 Subject: [FieldTrip] ft_appendspike create a trialfun for continuos data Message-ID: Hi! Is still impossible to use the appendspike function in my data :( That is way now I am trying to use the ft_definetrial to create my own set. My question is how can I create a trialfun for continuos data (that means I don't want to split my data into segments or events or epochs), I want to define a long and continuos set of data (the LFP), in order to append the spike data afterwards. Thanks! Best, Alex -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From martin.rosenfelder at uni-ulm.de Tue Feb 19 11:00:05 2019 From: martin.rosenfelder at uni-ulm.de (Martin Rosenfelder) Date: Tue, 19 Feb 2019 11:00:05 +0100 Subject: [FieldTrip] =?utf-8?b?Pz09P3V0Zi04P3E/ID89PT91dGYtOD9xPyBmdF9h?= =?utf-8?q?ppendspike__create_a_trialfun_for_continuos_data?= In-Reply-To: Message-ID: <60a7-5c6bd380-b-2d147a00@189380900> Hi Alex, You can use the ft_definetrial function in order to define your data containing continuous data. In order to achieve this, you can specify the cfg like this: cfg = [] cfg.trialdef = (your 1x3 matrix) data_new = ft_definetrial(data) The new variable should now contain your continuous data as one trial. In the new data matrix you can then check the .trl field if it really consists of just one trial from beginning to end of your timeline. Maybe this works. Best, Martin -- M.Sc.-Psych. Martin Rosenfelder Wissenschaftlicher Mitarbeiter Klinische und Biologische Psychologie Universität Ulm Raum 47.2.259 +49 731-50 26592 martin.rosenfelder at uni-ulm.de Am Dienstag, 19. Februar 2019 10:19 CET, María Alejandra Korovaichuk schrieb: > Hi! > > Is still impossible to use the appendspike function in my data :( That is > way now I am trying to use the ft_definetrial to create my own set. > My question is how can I create a trialfun for continuos data (that means I > don't want to split my data into segments or events or epochs), I want to > define a long and continuos set of data (the LFP), in order to append the > spike data afterwards. > > Thanks! > > Best, > > Alex _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alejandra.korovaichuk at ctb.upm.es Tue Feb 19 12:52:12 2019 From: alejandra.korovaichuk at ctb.upm.es (=?UTF-8?Q?Mar=C3=ADa_Alejandra_Korovaichuk?=) Date: Tue, 19 Feb 2019 12:52:12 +0100 Subject: [FieldTrip] ?= =?utf-8?q? ft_appendspike create a trialfun for continuos data In-Reply-To: <60a7-5c6bd380-b-2d147a00@189380900> References: <60a7-5c6bd380-b-2d147a00@189380900> Message-ID: Thanks Martin, but I tried this many times before and is still the same issue. FT is not recognizing mydata (is a matlab file with 3 variables: time (in milliseconds), lfp data (in mV), and sampling freq The message is always the same: evaluating trialfunction 'ft_trialfun_general' reading the header from 'mydata.mat' Error using ft_read_header (line 2581) unsupported header format "matlab" El mar., 19 feb. 2019 a las 11:44, Martin Rosenfelder (< martin.rosenfelder at uni-ulm.de>) escribió: > Hi Alex, > > You can use the ft_definetrial function in order to define your data > containing continuous data. In order to achieve this, you can specify the > cfg like this: > cfg = [] > cfg.trialdef = (your 1x3 matrix) > data_new = ft_definetrial(data) > > The new variable should now contain your continuous data as one trial. > In the new data matrix you can then check the .trl field if it really > consists of just one trial from beginning to end of your timeline. > > Maybe this works. > > Best, > Martin > > > > > -- > M.Sc.-Psych. Martin Rosenfelder > Wissenschaftlicher Mitarbeiter > Klinische und Biologische Psychologie > Universität Ulm > Raum 47.2.259 > +49 731-50 26592 > martin.rosenfelder at uni-ulm.de > > Am Dienstag, 19. Februar 2019 10:19 CET, María Alejandra Korovaichuk < > alejandra.korovaichuk at ctb.upm.es> schrieb: > > > Hi! > > > > Is still impossible to use the appendspike function in my data :( That is > > way now I am trying to use the ft_definetrial to create my own set. > > My question is how can I create a trialfun for continuos data (that > means I > > don't want to split my data into segments or events or epochs), I want to > > define a long and continuos set of data (the LFP), in order to append the > > spike data afterwards. > > > > Thanks! > > > > Best, > > > > Alex > > > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From laura.arendsen at uni-tuebingen.de Tue Feb 19 13:26:37 2019 From: laura.arendsen at uni-tuebingen.de (Laura Arendsen) Date: Tue, 19 Feb 2019 13:26:37 +0100 Subject: [FieldTrip] PhD and Postdoc positions: state-dependent and adaptive neuro-stimulation, University Hospital Tuebingen Message-ID: <20190219132637.Horde.5zisaZETYFHMDkeO0kczxWN@webmail.uni-tuebingen.de> PhD and Postdoc positions: state-dependent and adaptive neuro-stimulation, University Hospital Tuebingen Our group at the Div. Functional and Restorative Neurosurgery, University Hospital Tuebingen, Germany, unites neuroscientists, engineers, computer scientists and physicians following a common goal: To improve the lives of patients with neurological disorders using state-dependent and adaptive stimulation of the nervous system. To achieve this goal, we combine online-analysis of electrophysiology (e.g. EEG, LFP) with non-invasive (TMS, tACS, tDCS, FES, NMES) or invasive (DBS) stimulation. In order to strengthen our team, we are looking for Postdocs and PhD students. As a translational group, we work closely together with biomedical companies to gain access to new tools, combine basic studies on healthy subjects with clinical studies on patient populations, and apply the knowledge gained from these studies to develop and refine these new tools. Representative work from the last months: Naros et al. Mov Disord. 2018, Khademi et al. Cereb Cortex. 2018, Kraus et al. J Neurosci. 2018 and Guggenberger et al. Brain Stimul 2018. What you can expect • Design and evaluate novel brain stimulation paradigms. Investigate the effects of these paradigms using electrophysiological data. Expand the understanding of the human brain. • Opportunity to work with in vivo data. Examine electrophysiological signals from patients and healthy controls. We support your work with a broad range of pre-build analysis tools and assist you in designing your own approaches. • Access to state-of-the-art technologies to generate reliable results. • Join a team that is united by a vision: To enhance the understanding of the human brain in order to invent and implement more effective therapies. • 3-year contract, third-party-funded in accordance with the German public service collective agreement pay scale and your previous experience. Qualifications • Team-player • Solid understanding of statistical data analysis, digital signal processing and/or programming principles • Programming skills in Python or MATLAB and/or experience in applying statistical tools, e.g. machine learning for data analysis. • Experience with relevant techniques, i.e. tDCS, TMS, NMES, M/EEG, and/or EMG. • Master’s degree or PhD in the field of neuroscience, cognitive science, biology, computer science, engineering, data science or related fields. Application • Please send your significant application electronically (pdf-files only) to tanja.mathis at med.uni-tuebingen.de • Motivational letter including CV, publication record, names and email addresses of three professional references, Transcript of Records, TOEFL scores or other evidence of English and/or German proficiency Kind regards, Laura Arendsen _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From martin.rosenfelder at uni-ulm.de Tue Feb 19 13:55:08 2019 From: martin.rosenfelder at uni-ulm.de (Martin Rosenfelder) Date: Tue, 19 Feb 2019 13:55:08 +0100 Subject: [FieldTrip] =?utf-8?b?Pz09P3V0Zi04P3E/ID89PT91dGYtOD9xPyA/PSBm?= =?utf-8?q?t_appendspike_create_a_trialfun_for_continuos_dat?= In-Reply-To: Message-ID: Dear Alex, I suppose that Fieldtrip throws that particular error, since the data is already present in MATLAB structure. Actually, I think there is no need to define the trial using ft_definetrial. Maybe ft_redifinetrial accepts the MATLAB structure of your data. Does reading the data as 'continuous' work using ft_preprocessing? See also the following link to a similar problem which had been discussed in the Fieldtrip community three years ago: https://mailman.science.ru.nl/pipermail/fieldtrip/2016-July/010699.html Best, Martin -- M.Sc.-Psych. Martin Rosenfelder Wissenschaftlicher Mitarbeiter Klinische und Biologische Psychologie Universität Ulm Raum 47.2.259 +49 731-50 26592 martin.rosenfelder at uni-ulm.de Am Dienstag, 19. Februar 2019 12:52 CET, María Alejandra Korovaichuk schrieb: > Thanks Martin, but I tried this many times before and is still the same > issue. > FT is not recognizing mydata (is a matlab file with 3 variables: time (in > milliseconds), lfp data (in mV), and sampling freq > > The message is always the same: > evaluating trialfunction 'ft_trialfun_general' > reading the header from 'mydata.mat' > Error using ft_read_header (line 2581) > unsupported header format "matlab" > > > > El mar., 19 feb. 2019 a las 11:44, Martin Rosenfelder (< > martin.rosenfelder at uni-ulm.de>) escribió: > > > Hi Alex, > > > > You can use the ft_definetrial function in order to define your data > > containing continuous data. In order to achieve this, you can specify the > > cfg like this: > > cfg = [] > > cfg.trialdef = (your 1x3 matrix) > > data_new = ft_definetrial(data) > > > > The new variable should now contain your continuous data as one trial. > > In the new data matrix you can then check the .trl field if it really > > consists of just one trial from beginning to end of your timeline. > > > > Maybe this works. > > > > Best, > > Martin > > > > > > > > > > -- > > M.Sc.-Psych. Martin Rosenfelder > > Wissenschaftlicher Mitarbeiter > > Klinische und Biologische Psychologie > > Universität Ulm > > Raum 47.2.259 > > +49 731-50 26592 > > martin.rosenfelder at uni-ulm.de > > > > Am Dienstag, 19. Februar 2019 10:19 CET, María Alejandra Korovaichuk < > > alejandra.korovaichuk at ctb.upm.es> schrieb: > > > > > Hi! > > > > > > Is still impossible to use the appendspike function in my data :( That is > > > way now I am trying to use the ft_definetrial to create my own set. > > > My question is how can I create a trialfun for continuos data (that > > means I > > > don't want to split my data into segments or events or epochs), I want to > > > define a long and continuos set of data (the LFP), in order to append the > > > spike data afterwards. > > > > > > Thanks! > > > > > > Best, > > > > > > Alex > > > > > > > > > > _______________________________________________ > > fieldtrip mailing list > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > https://doi.org/10.1371/journal.pcbi.1002202 > > _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From Jane.Tan at murdoch.edu.au Tue Feb 19 14:57:12 2019 From: Jane.Tan at murdoch.edu.au (Jane Tan) Date: Tue, 19 Feb 2019 13:57:12 +0000 Subject: [FieldTrip] Strange MNE source reconstruction results Message-ID: Dear community, I am trying to run source reconstruction on EEG data using minimum source estimation, but have gotten very strange-looking results. The ortho view (via ft_sourceplot) shows source activity "shooting" from within the cortex to outside of the head. I have attached a screen capture. I've been trying to find out what's wrong, but I can't seem to find anything amiss. I initially thought it might be an issue with the leadfield, but I use the BEM headmodel and sourcemodel ft templates for the leadfield calculation, and have checked that the sensors (EGI 128) are properly aligned to the headmodel using ft_plot_sens, so I don't think the problem lies with the leadfield. I don't think that it is due to the dataset as well, because previous source reconstructions with beamformers resulted in normal-looking sourceplots.. I'm really at a loss right now, and would really appreciate any suggestions or advice. My code: % Getting noise-covariance cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'prestim' tlckSS = ft_timelockanalysis(cfg, dataSS_epoched); % Leadfield sourcemodel=ft_read_headshape('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template\sourcemodel\cortex_8196.surf.gii'); cfg = []; cfg.elec = elec_aligned; %aligned to BEM headmodel cfg.grid = sourcemodel; % FROM FT TEMPLATES cfg.headmodel = vol; %BEM headmodel from FT templates leadfield = ft_prepare_leadfield(cfg); % Minimum norm estimation cfg = []; cfg.method = 'mne'; cfg.grid = leadfield; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.mne.prewhiten = 'yes'; cfg.mne.lambda = 3; cfg.mne.scalesourcecov = 'yes'; sourceSS = ft_sourceanalysis(cfg,tlckSS); % Loading single_subj_T1 MRI template mri = ft_read_mri('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template \anatomy\single_subj_T1_1mm.nii'); % Reslice the MRI to align voxel axes with the head coordinate axes mri = ft_volumereslice([], mri); %Interpolate the source to the MRI cfg = []; cfg.downsample = 2; cfg.parameter = 'pow'; sourceSSInt = ft_sourceinterpolate(cfg, sourceSS , mri); %Plotting cfg = []; cfg.method = 'ortho'; cfg.funparameter = 'pow'; cfg.latency = [0.2 0.4]; %to specify time range in seconds cfg.avgovertime = 'yes'; % for time range ft_sourceplot(cfg, sourceSSInt); [cid:a826b3b5-b355-4092-842c-00ee696f5e9e] Best regards, Jane -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- A non-text attachment was scrubbed... Name: pastedImage.png Type: image/png Size: 112153 bytes Desc: pastedImage.png URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Tue Feb 19 14:54:56 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 19 Feb 2019 13:54:56 +0000 Subject: [FieldTrip] Error in source localisation statistics In-Reply-To: References: Message-ID: <6DDDA420-50F6-4785-BCF7-3E637114181D@donders.ru.nl> Hi Xavier, My recommendation here would be to use the matlab debugger and inspect the cause of the error. The ‘Index exceeds array bounds’ is quite a clear error message, and suggests that there is a mismatch between the number of elements in dat/val, and the numbers represented in indx(k). Good luck, Jan-Mathijs On 18 Feb 2019, at 07:23, Xavier Vrijdag > wrote: Hello, I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as they helped me tremendously to do this analysis. After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them. %Calculate the channel covariance matric cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'all'; cfg.keeptrials = 'yes'; timelock = ft_timelockanalysis(cfg, data_filt); %Global filter cfg = []; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.grid = grid; cfg.method = 'lcmv'; cfg.lcmv.projectnoise='yes'; %needed for neural activity index cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights cfg.lcmv.lambda = '5%'; %Regularise a little cfg.rawtrial = 'yes'; % project each single trial through the filter. cfg.keeptrials = 'yes'; source = ft_sourceanalysis(cfg, timelock); cfg = []; cfg.dim = source.dim; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.parameter = 'pow'; cfg.correctm = 'cluster'; cfg.numrandomization = 1000; cfg.alpha = 0.05; % note that this only implies single-sided testing cfg.tail = 0; cfg.design(1,:) = [1:nTrials 1:nTrials]; cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2]; cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials) cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions) stat = ft_sourcestatistics(cfg, source); After the source analysis the source statistics script calls the checkdata script and I get the following error: Index exceeds array bounds. Error in ft_datatype_source (line 183) val{indx(k)}(1,:,:,:) = dat{indx(k)}; Error in ft_checkdata (line 278) data = ft_datatype_source(data); Error in ft_sourcestatistics (line 94) varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no'); Error in sourcelocalisation_N2O (line 114) stat = ft_sourcestatistics(cfg, source); The source struct has the following content: time: [1×15360 double] dim: [24 31 25] inside: [18600×1 logical] pos: [18600×3 double] method: 'rawtrial' trial: [1×24 struct] df: 24 cfg: [1×1 struct] With source.trial: 1×24 struct array with fields: ori pow mom noise filter label filterdimord I would like your help to understand the error and how to fix it. Regards, Xavier Vrijdag _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From alejandra.korovaichuk at ctb.upm.es Tue Feb 19 14:47:15 2019 From: alejandra.korovaichuk at ctb.upm.es (=?UTF-8?Q?Mar=C3=ADa_Alejandra_Korovaichuk?=) Date: Tue, 19 Feb 2019 14:47:15 +0100 Subject: [FieldTrip] ?= ft appendspike create a trialfun for continuos dat In-Reply-To: References: Message-ID: Yes, I've been going through that discussion trying to repeat what Rachel did but is not working, maybe my problem is somewhere else. I want to use the ft_appendspike function in order to do a spike-field coherence test. So, to do that the FT tutorial says I need to process the raw spike data such the resulting spike structure has the "same trial definition" as the lfp structure. Al lthe time in the tutorial is asking me for a trl function but the only way to create a trl matrix is using the ft_definitiontria, and to use the ft_definitiontrial I need to read the header. Is a vicious circle and I can't find the way out El mar., 19 feb. 2019 a las 14:29, Martin Rosenfelder (< martin.rosenfelder at uni-ulm.de>) escribió: > Dear Alex, > > I suppose that Fieldtrip throws that particular error, since the data is > already present in MATLAB structure. Actually, I think there is no need to > define the trial using ft_definetrial. Maybe ft_redifinetrial accepts the > MATLAB structure of your data. Does reading the data as 'continuous' work > using ft_preprocessing? > See also the following link to a similar problem which had been discussed > in the Fieldtrip community three years ago: > https://mailman.science.ru.nl/pipermail/fieldtrip/2016-July/010699.html > > Best, > Martin > > > -- > M.Sc.-Psych. Martin Rosenfelder > Wissenschaftlicher Mitarbeiter > Klinische und Biologische Psychologie > Universität Ulm > Raum 47.2.259 > +49 731-50 26592 > martin.rosenfelder at uni-ulm.de > > Am Dienstag, 19. Februar 2019 12:52 CET, María Alejandra Korovaichuk < > alejandra.korovaichuk at ctb.upm.es> schrieb: > > > Thanks Martin, but I tried this many times before and is still the same > > issue. > > FT is not recognizing mydata (is a matlab file with 3 variables: time (in > > milliseconds), lfp data (in mV), and sampling freq > > > > The message is always the same: > > evaluating trialfunction 'ft_trialfun_general' > > reading the header from 'mydata.mat' > > Error using ft_read_header (line 2581) > > unsupported header format "matlab" > > > > > > > > El mar., 19 feb. 2019 a las 11:44, Martin Rosenfelder (< > > martin.rosenfelder at uni-ulm.de>) escribió: > > > > > Hi Alex, > > > > > > You can use the ft_definetrial function in order to define your data > > > containing continuous data. In order to achieve this, you can specify > the > > > cfg like this: > > > cfg = [] > > > cfg.trialdef = (your 1x3 matrix) > > > data_new = ft_definetrial(data) > > > > > > The new variable should now contain your continuous data as one trial. > > > In the new data matrix you can then check the .trl field if it really > > > consists of just one trial from beginning to end of your timeline. > > > > > > Maybe this works. > > > > > > Best, > > > Martin > > > > > > > > > > > > > > > -- > > > M.Sc.-Psych. Martin Rosenfelder > > > Wissenschaftlicher Mitarbeiter > > > Klinische und Biologische Psychologie > > > Universität Ulm > > > Raum 47.2.259 > > > +49 731-50 26592 > > > martin.rosenfelder at uni-ulm.de > > > > > > Am Dienstag, 19. Februar 2019 10:19 CET, María Alejandra Korovaichuk < > > > alejandra.korovaichuk at ctb.upm.es> schrieb: > > > > > > > Hi! > > > > > > > > Is still impossible to use the appendspike function in my data :( > That is > > > > way now I am trying to use the ft_definetrial to create my own set. > > > > My question is how can I create a trialfun for continuos data (that > > > means I > > > > don't want to split my data into segments or events or epochs), I > want to > > > > define a long and continuos set of data (the LFP), in order to > append the > > > > spike data afterwards. > > > > > > > > Thanks! > > > > > > > > Best, > > > > > > > > Alex > > > > > > > > > > > > > > > _______________________________________________ > > > fieldtrip mailing list > > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > > https://doi.org/10.1371/journal.pcbi.1002202 > > > > > > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Tue Feb 19 15:04:51 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 19 Feb 2019 14:04:51 +0000 Subject: [FieldTrip] ?= ft appendspike create a trialfun for continuos dat In-Reply-To: References: Message-ID: Maria, Can I reiterate my suggestion to look into the problem at the level of ft_appendspike (as per the text copied in below), or additionally look into this information: http://www.fieldtriptoolbox.org/faq/how_can_i_import_my_own_dataformat/ Your ‘vicious’ circle is caused by the fact that you try to create a ’trl’-matrix using an underdefined data format, so I don’t think that this is going to work. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands +++++++++++++++++++++++++++++++++++++++++++++++++++++++++ Hi Maria, I am not using combined spike/lfp data myself, but I suggest that you look into the code of ft_appendspike in a little more detail. This will give you some idea about why the error occurs. My initial thought is that ft_appendspike hasn’t matured (in terms of backward compatibility) along with the fieldtrip code base (and more strict internal data representation). Any improvements in the code will therefore be most welcome. I suspect that the current issue results from the fact that the code tries to look into data.cfg. … .trl to extract information about the original sampling. Since your data is coming from somewhere else, this information is not present. Also, current data organization standards actually prohibit to look into data.cfg.previous. … trl, and require this information be represented in a field called .sampleinfo. I suggest that you search in the documentation for ‘sampleinfo’ to get an impression how this information is used throughout the code, and how it is generated if it doesn’t exist (hint: use ft_checkdata(data,'hassampleinfo’, true); Please also, if you have fixed your version of ft_appendspike, do submit a Pull Request on github so that we can incorporate your fixes into the codebase. Best wishes Jan-Mathijs On 19 Feb 2019, at 14:47, María Alejandra Korovaichuk > wrote: Yes, I've been going through that discussion trying to repeat what Rachel did but is not working, maybe my problem is somewhere else. I want to use the ft_appendspike function in order to do a spike-field coherence test. So, to do that the FT tutorial says I need to process the raw spike data such the resulting spike structure has the "same trial definition" as the lfp structure. Al lthe time in the tutorial is asking me for a trl function but the only way to create a trl matrix is using the ft_definitiontria, and to use the ft_definitiontrial I need to read the header. Is a vicious circle and I can't find the way out El mar., 19 feb. 2019 a las 14:29, Martin Rosenfelder (>) escribió: Dear Alex, I suppose that Fieldtrip throws that particular error, since the data is already present in MATLAB structure. Actually, I think there is no need to define the trial using ft_definetrial. Maybe ft_redifinetrial accepts the MATLAB structure of your data. Does reading the data as 'continuous' work using ft_preprocessing? See also the following link to a similar problem which had been discussed in the Fieldtrip community three years ago: https://mailman.science.ru.nl/pipermail/fieldtrip/2016-July/010699.html Best, Martin -- M.Sc.-Psych. Martin Rosenfelder Wissenschaftlicher Mitarbeiter Klinische und Biologische Psychologie Universität Ulm Raum 47.2.259 +49 731-50 26592 martin.rosenfelder at uni-ulm.de Am Dienstag, 19. Februar 2019 12:52 CET, María Alejandra Korovaichuk > schrieb: > Thanks Martin, but I tried this many times before and is still the same > issue. > FT is not recognizing mydata (is a matlab file with 3 variables: time (in > milliseconds), lfp data (in mV), and sampling freq > > The message is always the same: > evaluating trialfunction 'ft_trialfun_general' > reading the header from 'mydata.mat' > Error using ft_read_header (line 2581) > unsupported header format "matlab" > > > > El mar., 19 feb. 2019 a las 11:44, Martin Rosenfelder (< > martin.rosenfelder at uni-ulm.de>) escribió: > > > Hi Alex, > > > > You can use the ft_definetrial function in order to define your data > > containing continuous data. In order to achieve this, you can specify the > > cfg like this: > > cfg = [] > > cfg.trialdef = (your 1x3 matrix) > > data_new = ft_definetrial(data) > > > > The new variable should now contain your continuous data as one trial. > > In the new data matrix you can then check the .trl field if it really > > consists of just one trial from beginning to end of your timeline. > > > > Maybe this works. > > > > Best, > > Martin > > > > > > > > > > -- > > M.Sc.-Psych. Martin Rosenfelder > > Wissenschaftlicher Mitarbeiter > > Klinische und Biologische Psychologie > > Universität Ulm > > Raum 47.2.259 > > +49 731-50 26592 > > martin.rosenfelder at uni-ulm.de > > > > Am Dienstag, 19. Februar 2019 10:19 CET, María Alejandra Korovaichuk < > > alejandra.korovaichuk at ctb.upm.es> schrieb: > > > > > Hi! > > > > > > Is still impossible to use the appendspike function in my data :( That is > > > way now I am trying to use the ft_definetrial to create my own set. > > > My question is how can I create a trialfun for continuos data (that > > means I > > > don't want to split my data into segments or events or epochs), I want to > > > define a long and continuos set of data (the LFP), in order to append the > > > spike data afterwards. > > > > > > Thanks! > > > > > > Best, > > > > > > Alex > > > > > > > > > > _______________________________________________ > > fieldtrip mailing list > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > https://doi.org/10.1371/journal.pcbi.1002202 > > _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Tue Feb 19 15:07:47 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 19 Feb 2019 14:07:47 +0000 Subject: [FieldTrip] Strange MNE source reconstruction results In-Reply-To: References: Message-ID: Hi Jane, You may want to adjust the cfg.interpmethod in your call to ft_sourceinterpolate. Or alternatively, don’t use ft_sourceinterpolate, and use cfg.method = ‘surface’, in ft_sourceplot Happy computing and good luck, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 19 Feb 2019, at 14:57, Jane Tan > wrote: Dear community, I am trying to run source reconstruction on EEG data using minimum source estimation, but have gotten very strange-looking results. The ortho view (via ft_sourceplot) shows source activity "shooting" from within the cortex to outside of the head. I have attached a screen capture. I've been trying to find out what's wrong, but I can't seem to find anything amiss. I initially thought it might be an issue with the leadfield, but I use the BEM headmodel and sourcemodel ft templates for the leadfield calculation, and have checked that the sensors (EGI 128) are properly aligned to the headmodel using ft_plot_sens, so I don't think the problem lies with the leadfield. I don't think that it is due to the dataset as well, because previous source reconstructions with beamformers resulted in normal-looking sourceplots.. I'm really at a loss right now, and would really appreciate any suggestions or advice. My code: % Getting noise-covariance cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'prestim' tlckSS = ft_timelockanalysis(cfg, dataSS_epoched); % Leadfield sourcemodel=ft_read_headshape('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template\sourcemodel\cortex_8196.surf.gii'); cfg = []; cfg.elec = elec_aligned; %aligned to BEM headmodel cfg.grid = sourcemodel; % FROM FT TEMPLATES cfg.headmodel = vol; %BEM headmodel from FT templates leadfield = ft_prepare_leadfield(cfg); % Minimum norm estimation cfg = []; cfg.method = 'mne'; cfg.grid = leadfield; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.mne.prewhiten = 'yes'; cfg.mne.lambda = 3; cfg.mne.scalesourcecov = 'yes'; sourceSS = ft_sourceanalysis(cfg,tlckSS); % Loading single_subj_T1 MRI template mri = ft_read_mri('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template \anatomy\single_subj_T1_1mm.nii'); % Reslice the MRI to align voxel axes with the head coordinate axes mri = ft_volumereslice([], mri); %Interpolate the source to the MRI cfg = []; cfg.downsample = 2; cfg.parameter = 'pow'; sourceSSInt = ft_sourceinterpolate(cfg, sourceSS , mri); %Plotting cfg = []; cfg.method = 'ortho'; cfg.funparameter = 'pow'; cfg.latency = [0.2 0.4]; %to specify time range in seconds cfg.avgovertime = 'yes'; % for time range ft_sourceplot(cfg, sourceSSInt); Best regards, Jane _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From lollo.seme at libero.it Tue Feb 19 15:18:23 2019 From: lollo.seme at libero.it (lollo.seme at libero.it) Date: Tue, 19 Feb 2019 15:18:23 +0100 (CET) Subject: [FieldTrip] PhD and Postdoc positions: state-dependent and adaptive neuro-stimulation, University Hospital Tuebingen In-Reply-To: <20190219132637.Horde.5zisaZETYFHMDkeO0kczxWN@webmail.uni-tuebingen.de> References: <20190219132637.Horde.5zisaZETYFHMDkeO0kczxWN@webmail.uni-tuebingen.de> Message-ID: <49064196.415861.1550585903836@mail.libero.it> Good afternoon, I am Lorenzo Semeia, currently doing a post-degree traineeship at the MEG Center in Tuebingen (The building next to yours). I saw the advertisement for the PhD position, and I would like to ask you some questions if you find 10 minutes for a meeting. Best, Lorenzo > > Il 19 febbraio 2019 alle 13.26 Laura Arendsen ha scritto: > > PhD and Postdoc positions: state-dependent and adaptive > neuro-stimulation, University Hospital Tuebingen > > Our group at the Div. Functional and Restorative Neurosurgery, > University Hospital Tuebingen, Germany, unites neuroscientists, > engineers, computer scientists and physicians following a common goal: > To improve the lives of patients with neurological disorders using > state-dependent and adaptive stimulation of the nervous system. To > achieve this goal, we combine online-analysis of electrophysiology > (e.g. EEG, LFP) with non-invasive (TMS, tACS, tDCS, FES, NMES) or > invasive (DBS) stimulation. In order to strengthen our team, we are > looking for Postdocs and PhD students. > > As a translational group, we work closely together with biomedical > companies to gain access to new tools, combine basic studies on > healthy subjects with clinical studies on patient populations, and > apply the knowledge gained from these studies to develop and refine > these new tools. Representative work from the last months: Naros et > al. Mov Disord. 2018, Khademi et al. Cereb Cortex. 2018, Kraus et al. > J Neurosci. 2018 and Guggenberger et al. Brain Stimul 2018. > > What you can expect > • Design and evaluate novel brain stimulation paradigms. Investigate > the effects of these paradigms using electrophysiological data. Expand > the understanding of the human brain. > • Opportunity to work with in vivo data. Examine electrophysiological > signals from patients and healthy controls. We support your work with > a broad range of pre-build analysis tools and assist you in designing > your own approaches. > • Access to state-of-the-art technologies to generate reliable results. > • Join a team that is united by a vision: To enhance the understanding > of the human brain in order to invent and implement more effective > therapies. > • 3-year contract, third-party-funded in accordance with the German > public service collective agreement pay scale and your previous > experience. > > Qualifications > • Team-player > • Solid understanding of statistical data analysis, digital signal > processing and/or programming principles > • Programming skills in Python or MATLAB and/or experience in applying > statistical tools, e.g. machine learning for data analysis. > • Experience with relevant techniques, i.e. tDCS, TMS, NMES, M/EEG, > and/or EMG. > • Master’s degree or PhD in the field of neuroscience, cognitive > science, biology, computer science, engineering, data science or > related fields. > > Application > • Please send your significant application electronically (pdf-files > only) to tanja.mathis at med.uni-tuebingen.de > • Motivational letter including CV, publication record, names and > email addresses of three professional references, Transcript of > Records, TOEFL scores or other evidence of English and/or German > proficiency > > Kind regards, > Laura Arendsen > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From vabelyaeva94 at gmail.com Tue Feb 19 15:35:45 2019 From: vabelyaeva94 at gmail.com (Valeriya Belyaeva) Date: Tue, 19 Feb 2019 17:35:45 +0300 Subject: [FieldTrip] Fwd: correlation with behavioural data and cluster statistics In-Reply-To: References: Message-ID: ---------- Forwarded message --------- From: Valeriya Belyaeva Date: ср, 13 февр. 2019 г. в 16:28 Subject: correlation with behavioural data and cluster statistics To: Dear fieldtrip developers, I have a question about correlation of neuronal and behavioural data. You have discussed this question here: http://www.fieldtriptoolbox.org/faq/how_can_i_test_for_correlations_between_neuronal_data_and_quantitative_stimulus_and_behavioural_variables/ I have taken the code, which was given as an example and added cluster-based correction method. My goal is to perform correlation between neuronal and behavioural data and then to account for multiple comparisons with cluster statistics. Could you, please, tell me, whether this script does it? Here is the script: % example script cfg = []; cfg.statistic = 'ft_statfun_correlationT'; cfg.method = 'montecarlo'; cfg.numrandomization = 1000; cfg.correctm = 'cluster'; cfg.clusteralpha = 0.025; cfg_neighb.method = 'triangulation'; cfg_neighb.layout = 'acticap_62'; cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_brain{:}); n1 = 42; % n1 is the number of subjects design(1,1:n1) = behav_data(:,1); % mean reaction time by subject cfg.design = design; cfg.ivar = 1; stat = ft_freqstatistics(cfg, data_brain{:}); Thank you a lot in advance! -- Best regards, Valeriya Belyaeva HSE, Cognitive science and technologies -- Best regards, Valeriya Belyaeva HSE, Cognitive science and technologies -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From Jane.Tan at murdoch.edu.au Tue Feb 19 16:24:39 2019 From: Jane.Tan at murdoch.edu.au (Jane Tan) Date: Tue, 19 Feb 2019 15:24:39 +0000 Subject: [FieldTrip] Strange MNE source reconstruction results In-Reply-To: <8909b90fe2244af8bbf50d5d85b28a21@MEXPR01MB1237.ausprd01.prod.outlook.com> References: , <8909b90fe2244af8bbf50d5d85b28a21@MEXPR01MB1237.ausprd01.prod.outlook.com> Message-ID: Hi Jan-Mathijs, Changing the interpmethod was indeed helpful. Thank you! Cheers, Jane ________________________________ From: fieldtrip on behalf of Schoffelen, J.M. (Jan Mathijs) Sent: Tuesday, 19 February 2019 10:07:47 PM To: FieldTrip discussion list Subject: Re: [FieldTrip] Strange MNE source reconstruction results Hi Jane, You may want to adjust the cfg.interpmethod in your call to ft_sourceinterpolate. Or alternatively, don’t use ft_sourceinterpolate, and use cfg.method = ‘surface’, in ft_sourceplot Happy computing and good luck, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 19 Feb 2019, at 14:57, Jane Tan > wrote: Dear community, I am trying to run source reconstruction on EEG data using minimum source estimation, but have gotten very strange-looking results. The ortho view (via ft_sourceplot) shows source activity "shooting" from within the cortex to outside of the head. I have attached a screen capture. I've been trying to find out what's wrong, but I can't seem to find anything amiss. I initially thought it might be an issue with the leadfield, but I use the BEM headmodel and sourcemodel ft templates for the leadfield calculation, and have checked that the sensors (EGI 128) are properly aligned to the headmodel using ft_plot_sens, so I don't think the problem lies with the leadfield. I don't think that it is due to the dataset as well, because previous source reconstructions with beamformers resulted in normal-looking sourceplots.. I'm really at a loss right now, and would really appreciate any suggestions or advice. My code: % Getting noise-covariance cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'prestim' tlckSS = ft_timelockanalysis(cfg, dataSS_epoched); % Leadfield sourcemodel=ft_read_headshape('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template\sourcemodel\cortex_8196.surf.gii'); cfg = []; cfg.elec = elec_aligned; %aligned to BEM headmodel cfg.grid = sourcemodel; % FROM FT TEMPLATES cfg.headmodel = vol; %BEM headmodel from FT templates leadfield = ft_prepare_leadfield(cfg); % Minimum norm estimation cfg = []; cfg.method = 'mne'; cfg.grid = leadfield; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.mne.prewhiten = 'yes'; cfg.mne.lambda = 3; cfg.mne.scalesourcecov = 'yes'; sourceSS = ft_sourceanalysis(cfg,tlckSS); % Loading single_subj_T1 MRI template mri = ft_read_mri('C:\xxxxx\xxxxx\xxxx\MATLAB\fieldtrip-20181109\template \anatomy\single_subj_T1_1mm.nii'); % Reslice the MRI to align voxel axes with the head coordinate axes mri = ft_volumereslice([], mri); %Interpolate the source to the MRI cfg = []; cfg.downsample = 2; cfg.parameter = 'pow'; sourceSSInt = ft_sourceinterpolate(cfg, sourceSS , mri); %Plotting cfg = []; cfg.method = 'ortho'; cfg.funparameter = 'pow'; cfg.latency = [0.2 0.4]; %to specify time range in seconds cfg.avgovertime = 'yes'; % for time range ft_sourceplot(cfg, sourceSSInt); Best regards, Jane _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From a.stolk8 at gmail.com Tue Feb 19 16:33:46 2019 From: a.stolk8 at gmail.com (Arjen Stolk) Date: Tue, 19 Feb 2019 07:33:46 -0800 Subject: [FieldTrip] Fwd: correlation with behavioural data and cluster statistics In-Reply-To: References: Message-ID: <24502A09-8940-4825-83E2-A25B4420775D@gmail.com> Hi Valeriya, That looks to be correct use of the correlationT method. The behavioral data goes into the design matrix, as you did. Best, Arjen > On Feb 19, 2019, at 6:35 AM, Valeriya Belyaeva wrote: > > > > ---------- Forwarded message --------- > From: Valeriya Belyaeva > Date: ср, 13 февр. 2019 г. в 16:28 > Subject: correlation with behavioural data and cluster statistics > To: > > > Dear fieldtrip developers, > > I have a question about correlation of neuronal and behavioural data. You have discussed this question here: http://www.fieldtriptoolbox.org/faq/how_can_i_test_for_correlations_between_neuronal_data_and_quantitative_stimulus_and_behavioural_variables/ > > I have taken the code, which was given as an example and added cluster-based correction method. My goal is to perform correlation between neuronal and behavioural data and then to account for multiple comparisons with cluster statistics. > > Could you, please, tell me, whether this script does it? > > Here is the script: > > % example script > > cfg = []; > > cfg.statistic = 'ft_statfun_correlationT'; > > cfg.method = 'montecarlo'; > > cfg.numrandomization = 1000; > > cfg.correctm = 'cluster'; > > > > cfg.clusteralpha = 0.025; > > cfg_neighb.method = 'triangulation'; > > cfg_neighb.layout = 'acticap_62'; > > cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_brain{:}); > > > > n1 = 42; % n1 is the number of subjects > > design(1,1:n1) = behav_data(:,1); % mean reaction time by subject > > cfg.design = design; > > cfg.ivar = 1; > > stat = ft_freqstatistics(cfg, data_brain{:}); > > > Thank you a lot in advance! > -- > Best regards, > Valeriya Belyaeva > HSE, Cognitive science and technologies > > > > -- > Best regards, > Valeriya Belyaeva > HSE, Cognitive science and technologies > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From lmelloni at gmail.com Tue Feb 19 18:00:28 2019 From: lmelloni at gmail.com (Lucia Melloni) Date: Tue, 19 Feb 2019 18:00:28 +0100 Subject: [FieldTrip] Postdoc in Human Laminar Electrophysiology at NYU (BRAIN Initiative) Message-ID: <50CBA830-39FB-45B4-956A-776042F5B2F6@gmail.com> Postdoc in Human Laminar Electrophysiology at NYU (BRAIN Initiative) A full-time Postdoc position will be available in the NYU Comprehensive Epilepsy Center, to study the electrophysiological basis of laminar functional MRI (fMRI). The position is part of a National Institutes of Health BRAIN Initiative-funded project in collaboration with the Center for Magnetic Resonance Research (CMRR) at the University of Minnesota and Department of Cognitive Neuroscience at Maastricht University. The postdoc will conduct intracranial and laminar electrophysiological recordings, as well as 7T laminar fMRI studies in people with epilepsy, and collaborate closely with a team of leading neuroscientists, physicians, and biomedical engineers. The aim of the project is to understand the neural underpinning of the laminar functional MRI signals by combining in-vivo electrophysiology in humans (NYU), high field MRI (NYU/CMRR/Maastricht) and computational modeling (Maastricht/CMRR). The candidate will benefit from the rich resources of our neuroscience community, which includes researchers at NYU School of Medicine, NYU Langone Health’s Neuroscience Institute , and the Center for Neural Science at NYU. The candidate will work closely with collaborators at the CMRR (Dr. Yacoub), Maastricht (Drs. Formisano, De Martino, Havlicek) and CMRR/Toronto/Suwon (Dr.Uludag). The ideal candidate has a PhD in neuroscience, biomedical engineering, psychology, or a related field. She/he should have a solid background in (human) electrophysiology and signal processing (EEG, MEG and/or ECoG), programming (Matlab or Python), statistics, and scientific writing. The candidate is expected to be able to work independently, to enjoy interacting within an interdisciplinary research environment as well as with a clinical team, and to have a track-record of peer-reviewed publications. Some supervision and mentoring of research assistants and students is expected. Previous experience with human electrophysiology will be an asset. Preferred starting date: August 2019 or as soon as possible. Initial appointment will be for 2 years with the option to renew up to 4 years. Interested individuals should send an email to lucia.melloni at nyulangone.org and sasha.devorea at nyulangone.org including a cover letter describing research experience and qualifications, an academic CV, and contact information of 2-3 referees who have agreed to be contacted, by March 30th, 2019. -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From vabelyaeva94 at gmail.com Tue Feb 19 19:11:34 2019 From: vabelyaeva94 at gmail.com (Valeriya Belyaeva) Date: Tue, 19 Feb 2019 21:11:34 +0300 Subject: [FieldTrip] Fwd: correlation with behavioural data and cluster statistics In-Reply-To: <24502A09-8940-4825-83E2-A25B4420775D@gmail.com> References: <24502A09-8940-4825-83E2-A25B4420775D@gmail.com> Message-ID: Thank you a lot, Arjen. Best regards, Valeriya вт, 19 февр. 2019 г. в 18:44, Arjen Stolk : > Hi Valeriya, > > That looks to be correct use of the correlationT method. The behavioral > data goes into the design matrix, as you did. > > Best, > Arjen > > On Feb 19, 2019, at 6:35 AM, Valeriya Belyaeva > wrote: > > > > ---------- Forwarded message --------- > From: Valeriya Belyaeva > Date: ср, 13 февр. 2019 г. в 16:28 > Subject: correlation with behavioural data and cluster statistics > To: > > > Dear fieldtrip developers, > > I have a question about correlation of neuronal and behavioural data. You > have discussed this question here: > http://www.fieldtriptoolbox.org/faq/how_can_i_test_for_correlations_between_neuronal_data_and_quantitative_stimulus_and_behavioural_variables/ > > I have taken the code, which was given as an example and added > cluster-based correction method. My goal is to perform correlation between > neuronal and behavioural data and then to account for multiple comparisons > with cluster statistics. > > Could you, please, tell me, whether this script does it? > > Here is the script: > > % example script > > cfg = []; > > cfg.statistic = 'ft_statfun_correlationT'; > > cfg.method = 'montecarlo'; > > cfg.numrandomization = 1000; > > cfg.correctm = 'cluster'; > > > cfg.clusteralpha = 0.025; > > cfg_neighb.method = 'triangulation'; > > cfg_neighb.layout = 'acticap_62'; > > cfg.neighbours = ft_prepare_neighbours(cfg_neighb, data_brain{:}); > > > n1 = 42; % n1 is the number of subjects > > design(1,1:n1) = behav_data(:,1); % mean reaction time by subject > > cfg.design = design; > > cfg.ivar = 1; > > stat = ft_freqstatistics(cfg, data_brain{:}); > > Thank you a lot in advance! > -- > Best regards, > Valeriya Belyaeva > HSE, Cognitive science and technologies > > > > -- > Best regards, > Valeriya Belyaeva > HSE, Cognitive science and technologies > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -- Best regards, Valeriya Belyaeva HSE, Cognitive science and technologies -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From x.vrijdag at auckland.ac.nz Wed Feb 20 21:32:50 2019 From: x.vrijdag at auckland.ac.nz (Xavier Vrijdag) Date: Wed, 20 Feb 2019 20:32:50 +0000 Subject: [FieldTrip] Error in source localisation statistics In-Reply-To: <6DDDA420-50F6-4785-BCF7-3E637114181D@donders.ru.nl> References: <6DDDA420-50F6-4785-BCF7-3E637114181D@donders.ru.nl> Message-ID: <2ABDCCE6-5E77-41AE-8A94-4FAE2CDAC551@auckland.ac.nz> Hi Jan-Mathijs, Thank you for your help. I went in to have a look at what is going on inside those loops and found that the error is occurring in iteration 6, when the field source.trial(1).label is concatenated. It uses the indexes for the big data cells (ori, mom & filter) which clearly doesn’t work on the small cell with the labels. This seems to me that this is a bug. I added a piece of code in front of the loop that was giving the error (before line 177 and make the if and elseif. if isequal(fn{i}, 'label') for j=1:nrpt source_new.label(:,j) = source.trial(j).label; end elseif iscell(dat) This worked to circumvent the problem. However, I do get the warning that the dimord of “ori” and “df” could not be determined. When using this cleaned source struct in source statistics I get further errors. It looks like an issue with how the source struct is built by the source analysis function with trials, and lateron needs to be restructured. SO I would like to know what is the needed structure for ft_sourcestatistics, so we can adjust the code correctly. Regards, Xavier From: fieldtrip on behalf of "Schoffelen, J.M. (Jan Mathijs)" Reply-To: FieldTrip discussion list Date: Wednesday, 20 February 2019 at 2:59 AM To: FieldTrip discussion list Subject: Re: [FieldTrip] Error in source localisation statistics Hi Xavier, My recommendation here would be to use the matlab debugger and inspect the cause of the error. The ‘Index exceeds array bounds’ is quite a clear error message, and suggests that there is a mismatch between the number of elements in dat/val, and the numbers represented in indx(k). Good luck, Jan-Mathijs On 18 Feb 2019, at 07:23, Xavier Vrijdag > wrote: Hello, I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as they helped me tremendously to do this analysis. After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them. %Calculate the channel covariance matric cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'all'; cfg.keeptrials = 'yes'; timelock = ft_timelockanalysis(cfg, data_filt); %Global filter cfg = []; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.grid = grid; cfg.method = 'lcmv'; cfg.lcmv.projectnoise='yes'; %needed for neural activity index cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights cfg.lcmv.lambda = '5%'; %Regularise a little cfg.rawtrial = 'yes'; % project each single trial through the filter. cfg.keeptrials = 'yes'; source = ft_sourceanalysis(cfg, timelock); cfg = []; cfg.dim = source.dim; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.parameter = 'pow'; cfg.correctm = 'cluster'; cfg.numrandomization = 1000; cfg.alpha = 0.05; % note that this only implies single-sided testing cfg.tail = 0; cfg.design(1,:) = [1:nTrials 1:nTrials]; cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2]; cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials) cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions) stat = ft_sourcestatistics(cfg, source); After the source analysis the source statistics script calls the checkdata script and I get the following error: Index exceeds array bounds. Error in ft_datatype_source (line 183) val{indx(k)}(1,:,:,:) = dat{indx(k)}; Error in ft_checkdata (line 278) data = ft_datatype_source(data); Error in ft_sourcestatistics (line 94) varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no'); Error in sourcelocalisation_N2O (line 114) stat = ft_sourcestatistics(cfg, source); The source struct has the following content: time: [1×15360 double] dim: [24 31 25] inside: [18600×1 logical] pos: [18600×3 double] method: 'rawtrial' trial: [1×24 struct] df: 24 cfg: [1×1 struct] With source.trial: 1×24 struct array with fields: ori pow mom noise filter label filterdimord I would like your help to understand the error and how to fix it. Regards, Xavier Vrijdag _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jonas at obleser.de Thu Feb 21 14:46:54 2019 From: jonas at obleser.de (Jonas Obleser) Date: Thu, 21 Feb 2019 14:46:54 +0100 Subject: [FieldTrip] =?utf-8?q?Postdoc_opportunity_=28up_to_4_years=29=2C?= =?utf-8?b?IE9ibGVzZXIgbGFiLCBMw7xiZWNrIChHRVIp?= Message-ID: <0866A3D2-FD30-421C-A138-B34E45CE7704@obleser.de> Dear colleagues, sorry for any crossposting: I am hiring a Postdoc to do some exciting Cogn Neuro with my lab and me near the baltic sea in the years to come. This post is not grant-based, so more-than-usual freedom, topicwise, but some modest teaching involvement. Application deadline March 15, starting date any time, full German contract up to 4 years. If interested/in doubt, please talk to me. Contact details below. Thanks for spreading the news, Jonas obleserlab.com uni-luebeck.de Job ad in English: https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf Job ad in German: https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job Jonas Obleser Professor Chair in Physiological Psychology and Research Methods University of Lübeck Department of Psychology MFC 8, Maria-Goeppert-Straße 9a 23562 Lübeck, Germany Phone +49 (0)451 3101 3620 Mobile +49 (0)171 6993337 jonas.obleser at uni-luebeck.de http://jonasobleser.com ---Schedule a meeting with me? https://calendly.com/jonasobleser --- -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Thu Feb 21 16:10:18 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Thu, 21 Feb 2019 15:10:18 +0000 Subject: [FieldTrip] Error in source localisation statistics In-Reply-To: <2ABDCCE6-5E77-41AE-8A94-4FAE2CDAC551@auckland.ac.nz> References: <6DDDA420-50F6-4785-BCF7-3E637114181D@donders.ru.nl> <2ABDCCE6-5E77-41AE-8A94-4FAE2CDAC551@auckland.ac.nz> Message-ID: <21612B35-BED5-4A31-8206-CAC578C72109@donders.ru.nl> Hi Xavier, I see. Unfortunately you happened to end up in a corner of the code that is a bit shaky, and possibly not well tested (although once upon a time it may have worked). This may be due to the fact that you are trying to ‘fool’ fieldtrip into treating a multiple subject design as if it’s a single subject design with multiple trials (where each of the trials represents a single condition estimate for a subject), correct? (as a side note: you would want to use ‘depsamplesT’ rather than ‘indepsamplesT’ as your test statistic). I think that you should not do this. First, as you have noticed this leads to downstream problems (specifically handcrafting combined data could easily lead to a user-error causing the data to deviate according to what FieldTrip can handle, but also using the cfg.rawtrial option of ft_sourceanalaysis historically and notoriously is a dysfunctional (or at least unpredictable in its behavior) option. (nominated to be removed once we find the time). Next to this, even though it seems your geometrical data (i.e. electrode positions, headmodel, sourcemodel) are shared across subjects, the covariance structure of the data will for sure be subject-specific, and I don’t think that it is a good idea to combine data across subjects before sourceanalysis. This is what I would do: for each subject do: ft_timelockanalysis with the subject-specific data combined across conditions ft_timelockanalysis with the subject-specific data for each of the conditions separately ft_sourceanalysis with the subject-specific data combined across conditions AND cfg.lcmv.keepfilter = ‘yes’; (and don’t specify cfg.keeptrials or cfg.rawtrial) input the source.avg.filter from the previous step into the cfg for each condition (in each subject) do: ft_sourceanalysis after this you should have a set of Nsubject times number of conditions source structures then you should be able to use ft_sourcestatistics with cfg.statisti = ‘depsamplesT’: ft_sourcestatistics(cfg, source{:}); % if in the previous for-loop you have stored the individual source-objects into a cell-array this syntax works (and is much cleaner than either ft_sourcestatistics(cfg, source1a, source2a ,…etc), and cleaner than going through ft_sourcegrandaverage). ft_sourcedescriptives should not be needed in this recipe. Good luck, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 20 Feb 2019, at 21:32, Xavier Vrijdag > wrote: Hi Jan-Mathijs, Thank you for your help. I went in to have a look at what is going on inside those loops and found that the error is occurring in iteration 6, when the field source.trial(1).label is concatenated. It uses the indexes for the big data cells (ori, mom & filter) which clearly doesn’t work on the small cell with the labels. This seems to me that this is a bug. I added a piece of code in front of the loop that was giving the error (before line 177 and make the if and elseif. if isequal(fn{i}, 'label') for j=1:nrpt source_new.label(:,j) = source.trial(j).label; end elseif iscell(dat) This worked to circumvent the problem. However, I do get the warning that the dimord of “ori” and “df” could not be determined. When using this cleaned source struct in source statistics I get further errors. It looks like an issue with how the source struct is built by the source analysis function with trials, and lateron needs to be restructured. SO I would like to know what is the needed structure for ft_sourcestatistics, so we can adjust the code correctly. Regards, Xavier From: fieldtrip > on behalf of "Schoffelen, J.M. (Jan Mathijs)" > Reply-To: FieldTrip discussion list > Date: Wednesday, 20 February 2019 at 2:59 AM To: FieldTrip discussion list > Subject: Re: [FieldTrip] Error in source localisation statistics Hi Xavier, My recommendation here would be to use the matlab debugger and inspect the cause of the error. The ‘Index exceeds array bounds’ is quite a clear error message, and suggests that there is a mismatch between the number of elements in dat/val, and the numbers represented in indx(k). Good luck, Jan-Mathijs On 18 Feb 2019, at 07:23, Xavier Vrijdag > wrote: Hello, I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as they helped me tremendously to do this analysis. After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them. %Calculate the channel covariance matric cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'all'; cfg.keeptrials = 'yes'; timelock = ft_timelockanalysis(cfg, data_filt); %Global filter cfg = []; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.grid = grid; cfg.method = 'lcmv'; cfg.lcmv.projectnoise='yes'; %needed for neural activity index cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights cfg.lcmv.lambda = '5%'; %Regularise a little cfg.rawtrial = 'yes'; % project each single trial through the filter. cfg.keeptrials = 'yes'; source = ft_sourceanalysis(cfg, timelock); cfg = []; cfg.dim = source.dim; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.parameter = 'pow'; cfg.correctm = 'cluster'; cfg.numrandomization = 1000; cfg.alpha = 0.05; % note that this only implies single-sided testing cfg.tail = 0; cfg.design(1,:) = [1:nTrials 1:nTrials]; cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2]; cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials) cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions) stat = ft_sourcestatistics(cfg, source); After the source analysis the source statistics script calls the checkdata script and I get the following error: Index exceeds array bounds. Error in ft_datatype_source (line 183) val{indx(k)}(1,:,:,:) = dat{indx(k)}; Error in ft_checkdata (line 278) data = ft_datatype_source(data); Error in ft_sourcestatistics (line 94) varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no'); Error in sourcelocalisation_N2O (line 114) stat = ft_sourcestatistics(cfg, source); The source struct has the following content: time: [1×15360 double] dim: [24 31 25] inside: [18600×1 logical] pos: [18600×3 double] method: 'rawtrial' trial: [1×24 struct] df: 24 cfg: [1×1 struct] With source.trial: 1×24 struct array with fields: ori pow mom noise filter label filterdimord I would like your help to understand the error and how to fix it. Regards, Xavier Vrijdag _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From Pierre.Megevand at unige.ch Thu Feb 21 17:16:47 2019 From: Pierre.Megevand at unige.ch (Pierre Bastien Megevand) Date: Thu, 21 Feb 2019 16:16:47 +0000 Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM forward solution Message-ID: <617c8035ce184327b4ed18a9caa3a033@unige.ch> Dear all, I think I have found an inconsistency in the way Fieldtrip handles the building of a FEM forward solution. I am following the procedure described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline for EEG forward solutions. Biomed Eng Online. 2018 (https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y). This procedure suggests to build the forward solution by calling the following Fieldtrip functions: ft_read_mri ft_volumerealign ft_volumereslice ft_volumesegment ft_prepare_mesh ft_prepare_headmodel ft_read_header (to get electrode data) ft_electroderealign ft_prepare_vol_sens ft_prepare_sourcemodel ft_prepare_leadfield My issue is the following: the FieldTrip-SimBio pipeline explicitly calls ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the case of the published paper, which used about 80 electrodes). However, ft_prepare_leadfield later calls (line 165) prepare_headmodel, which itself calls (line 113) ft_prepare_vol_sens again, with the same parameters as far as I can tell (and again taking ages to run). Is this redundancy intended? If not, can it be circumvented? Thank you in advance, Pierre Pierre Mégevand, MD, PhD Senior research associate, Dept. of basic neurosciences Faculty of medicine, University of Geneva, Switzerland T. +41 76 693 65 22 | pierre.megevand at unige.ch -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From neeraj750kumar at gmail.com Fri Feb 22 11:14:42 2019 From: neeraj750kumar at gmail.com (Neeraj kumar) Date: Fri, 22 Feb 2019 15:44:42 +0530 Subject: [FieldTrip] Parcellate the reconstructed source time series Message-ID: Hello all, I want to parcellate the reconstructed source time series (~ 1000ms). I have moments in source.avg.mom for around 6000 grids. Additionally, do I need to perform some normalization on time series before or after parcellation to perform network analysis? Thanks in advance. Neeraj Kumar, -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From j.vorw01 at gmail.com Fri Feb 22 11:40:28 2019 From: j.vorw01 at gmail.com (Johannes) Date: Fri, 22 Feb 2019 11:40:28 +0100 Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM forward solution In-Reply-To: <617c8035ce184327b4ed18a9caa3a033@unige.ch> References: <617c8035ce184327b4ed18a9caa3a033@unige.ch> Message-ID: Dear Pierre, if you are running a recent version of FieldTrip (newer than Dec 15, 2018), there should be a check included in ft_prepare_vol_sens to avoid this behavior, i.e., if a transfer matrix is detected in the vol-struct provided to ft_prepare_vol_sens, it is checked if whether this fits to the indicated sensor configuration and if this is the case no new transfer matrix is computed. This should also work if a subset of sensors is selected. Thus, it would be great, if you could check whether this behavior remains when using a recent checkout of FieldTrip. Regarding the time requirement for computing the transfer matrix - the calculation in sb_transfer can be easily parallelized by replacing l 35 in sb_transfer with a parfor loop, e.g., parfor(i=2:length(vol.elecnodes),8), if you want to compute on 8 cores. I hope this answer is helpful to you! Best, Johannes Am Do., 21. Feb. 2019 um 17:17 Uhr schrieb Pierre Bastien Megevand < Pierre.Megevand at unige.ch>: > Dear all, > > > I think I have found an inconsistency in the way Fieldtrip handles the > building of a FEM forward solution. I am following the procedure > described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline > for EEG forward solutions. Biomed Eng Online. 2018 ( > https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y). > This procedure suggests to build the forward solution by calling the > following Fieldtrip functions: > > ft_read_mri > > ft_volumerealign > > ft_volumereslice > > ft_volumesegment > > ft_prepare_mesh > > ft_prepare_headmodel > > ft_read_header (to get electrode data) > > ft_electroderealign > > ft_prepare_vol_sens > > ft_prepare_sourcemodel > > ft_prepare_leadfield > > > My issue is the following: the FieldTrip-SimBio pipeline explicitly calls > ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the > case of the published paper, which used about 80 electrodes). However, > ft_prepare_leadfield later calls (line 165) prepare_headmodel, which > itself calls (line 113) ft_prepare_vol_sens again, with the same > parameters as far as I can tell (and again taking ages to run). > > > Is this redundancy intended? If not, can it be circumvented? > > > Thank you in advance, > > > Pierre > > > Pierre Mégevand, MD, PhD > Senior research associate, Dept. of basic neurosciences > Faculty of medicine, University of Geneva, Switzerland > T. +41 76 693 65 22 | pierre.megevand at unige.ch > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Fri Feb 22 12:55:44 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Fri, 22 Feb 2019 11:55:44 +0000 Subject: [FieldTrip] Parcellate the reconstructed source time series In-Reply-To: References: Message-ID: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> I want to parcellate the reconstructed source time series (~ 1000ms). I have moments in source.avg.mom for around 6000 grids. Additionally, do I need to perform some normalization on time series before or after parcellation to perform network analysis? Well, at least you should compute a metric between pairs of time series that can be subjected to a network analysis. Whether or not this needs ‘some normalization’ depends on what you exactly want to achieve. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From Pierre.Megevand at unige.ch Fri Feb 22 13:37:43 2019 From: Pierre.Megevand at unige.ch (Pierre Bastien Megevand) Date: Fri, 22 Feb 2019 12:37:43 +0000 Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM forward solution In-Reply-To: References: Message-ID: Dear Johannes, thank you for your answer. My bad--I was not using an up-to-date version of FieldTrip. Indeed, now that I have updated the code, the transfer matrix is not computed again by ft_prepare_leadfield. I think that a similar check might be necessary for the call to ft_prepare_sourcemodel (line 178 of ft_prepare_leadfield), since the FieldTrip-SimBio pipeline also calls that function explicitly beforehand. In order to parallelize the transfer matrix computation, in sb_transfer, I suggest that the code at line 41, which currently reads "clear vecb;", be replaced by "vecb=[];", because there is a transparency issue when using "clear" within a parfor loop (see https://ch.mathworks.com/help/distcomp/transparency.html). I have also been trying to parallelize ft_prepare_leadfield. Given that ft_compute_leadfield is called once per grid point, I replaced the for loop at line 301 of ft_prepare_leadfield with a parfor loop. The indexing of grid.leadfield{thisindx} poses a "sliced variable" problem to MATLAB though. The workaround I used was to create a temporary variable, grid_leadfield, and to index it with {i} instead of {thisindx}. At the end of the loop, the "grid.leadfield(insideindx)=grid_leadfield;" line reestablishes that variable. I am currently testing this. Pierre ________________________________ De : fieldtrip de la part de fieldtrip-request at science.ru.nl Envoyé : vendredi, 22 février 2019 12:00 À : fieldtrip at science.ru.nl Objet : fieldtrip Digest, Vol 99, Issue 22 Send fieldtrip mailing list submissions to fieldtrip at science.ru.nl To subscribe or unsubscribe via the World Wide Web, visit https://mailman.science.ru.nl/mailman/listinfo/fieldtrip or, via email, send a message with subject or body 'help' to fieldtrip-request at science.ru.nl You can reach the person managing the list at fieldtrip-owner at science.ru.nl When replying, please edit your Subject line so it is more specific than "Re: Contents of fieldtrip digest..." Today's Topics: 1. Postdoc opportunity (up to 4 years), Obleser lab, Lübeck (GER) (Jonas Obleser) 2. Re: Error in source localisation statistics (Schoffelen, J.M. (Jan Mathijs)) 3. issue with FieldTrip-SimBio pipeline for EEG FEM forward solution (Pierre Bastien Megevand) 4. Parcellate the reconstructed source time series (Neeraj kumar) 5. Re: issue with FieldTrip-SimBio pipeline for EEG FEM forward solution (Johannes) ---------------------------------------------------------------------- Message: 1 Date: Thu, 21 Feb 2019 14:46:54 +0100 From: Jonas Obleser To: fieldtrip at science.ru.nl Subject: [FieldTrip] Postdoc opportunity (up to 4 years), Obleser lab, Lübeck (GER) Message-ID: <0866A3D2-FD30-421C-A138-B34E45CE7704 at obleser.de> Content-Type: text/plain; charset="utf-8" Dear colleagues, sorry for any crossposting: I am hiring a Postdoc to do some exciting Cogn Neuro with my lab and me near the baltic sea in the years to come. This post is not grant-based, so more-than-usual freedom, topicwise, but some modest teaching involvement. Application deadline March 15, starting date any time, full German contract up to 4 years. If interested/in doubt, please talk to me. Contact details below. Thanks for spreading the news, Jonas obleserlab.com uni-luebeck.de Job ad in English: https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf Job ad in German: https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job Jonas Obleser Professor Chair in Physiological Psychology and Research Methods University of Lübeck Department of Psychology MFC 8, Maria-Goeppert-Straße 9a 23562 Lübeck, Germany Phone +49 (0)451 3101 3620 Mobile +49 (0)171 6993337 jonas.obleser at uni-luebeck.de http://jonasobleser.com ---Schedule a meeting with me? https://calendly.com/jonasobleser --- -------------- next part -------------- An HTML attachment was scrubbed... URL: ------------------------------ Message: 2 Date: Thu, 21 Feb 2019 15:10:18 +0000 From: "Schoffelen, J.M. (Jan Mathijs)" To: FieldTrip discussion list Subject: Re: [FieldTrip] Error in source localisation statistics Message-ID: <21612B35-BED5-4A31-8206-CAC578C72109 at donders.ru.nl> Content-Type: text/plain; charset="utf-8" Hi Xavier, I see. Unfortunately you happened to end up in a corner of the code that is a bit shaky, and possibly not well tested (although once upon a time it may have worked). This may be due to the fact that you are trying to ‘fool’ fieldtrip into treating a multiple subject design as if it’s a single subject design with multiple trials (where each of the trials represents a single condition estimate for a subject), correct? (as a side note: you would want to use ‘depsamplesT’ rather than ‘indepsamplesT’ as your test statistic). I think that you should not do this. First, as you have noticed this leads to downstream problems (specifically handcrafting combined data could easily lead to a user-error causing the data to deviate according to what FieldTrip can handle, but also using the cfg.rawtrial option of ft_sourceanalaysis historically and notoriously is a dysfunctional (or at least unpredictable in its behavior) option. (nominated to be removed once we find the time). Next to this, even though it seems your geometrical data (i.e. electrode positions, headmodel, sourcemodel) are shared across subjects, the covariance structure of the data will for sure be subject-specific, and I don’t think that it is a good idea to combine data across subjects before sourceanalysis. This is what I would do: for each subject do: ft_timelockanalysis with the subject-specific data combined across conditions ft_timelockanalysis with the subject-specific data for each of the conditions separately ft_sourceanalysis with the subject-specific data combined across conditions AND cfg.lcmv.keepfilter = ‘yes’; (and don’t specify cfg.keeptrials or cfg.rawtrial) input the source.avg.filter from the previous step into the cfg for each condition (in each subject) do: ft_sourceanalysis after this you should have a set of Nsubject times number of conditions source structures then you should be able to use ft_sourcestatistics with cfg.statisti = ‘depsamplesT’: ft_sourcestatistics(cfg, source{:}); % if in the previous for-loop you have stored the individual source-objects into a cell-array this syntax works (and is much cleaner than either ft_sourcestatistics(cfg, source1a, source2a ,…etc), and cleaner than going through ft_sourcegrandaverage). ft_sourcedescriptives should not be needed in this recipe. Good luck, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On 20 Feb 2019, at 21:32, Xavier Vrijdag > wrote: Hi Jan-Mathijs, Thank you for your help. I went in to have a look at what is going on inside those loops and found that the error is occurring in iteration 6, when the field source.trial(1).label is concatenated. It uses the indexes for the big data cells (ori, mom & filter) which clearly doesn’t work on the small cell with the labels. This seems to me that this is a bug. I added a piece of code in front of the loop that was giving the error (before line 177 and make the if and elseif. if isequal(fn{i}, 'label') for j=1:nrpt source_new.label(:,j) = source.trial(j).label; end elseif iscell(dat) This worked to circumvent the problem. However, I do get the warning that the dimord of “ori” and “df” could not be determined. When using this cleaned source struct in source statistics I get further errors. It looks like an issue with how the source struct is built by the source analysis function with trials, and lateron needs to be restructured. SO I would like to know what is the needed structure for ft_sourcestatistics, so we can adjust the code correctly. Regards, Xavier From: fieldtrip > on behalf of "Schoffelen, J.M. (Jan Mathijs)" > Reply-To: FieldTrip discussion list > Date: Wednesday, 20 February 2019 at 2:59 AM To: FieldTrip discussion list > Subject: Re: [FieldTrip] Error in source localisation statistics Hi Xavier, My recommendation here would be to use the matlab debugger and inspect the cause of the error. The ‘Index exceeds array bounds’ is quite a clear error message, and suggests that there is a mismatch between the number of elements in dat/val, and the numbers represented in indx(k). Good luck, Jan-Mathijs On 18 Feb 2019, at 07:23, Xavier Vrijdag > wrote: Hello, I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as they helped me tremendously to do this analysis. After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them. %Calculate the channel covariance matric cfg = []; cfg.covariance = 'yes'; cfg.covariancewindow = 'all'; cfg.keeptrials = 'yes'; timelock = ft_timelockanalysis(cfg, data_filt); %Global filter cfg = []; cfg.headmodel = vol; cfg.elec = elec_aligned; cfg.grid = grid; cfg.method = 'lcmv'; cfg.lcmv.projectnoise='yes'; %needed for neural activity index cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights cfg.lcmv.lambda = '5%'; %Regularise a little cfg.rawtrial = 'yes'; % project each single trial through the filter. cfg.keeptrials = 'yes'; source = ft_sourceanalysis(cfg, timelock); cfg = []; cfg.dim = source.dim; cfg.method = 'montecarlo'; cfg.statistic = 'ft_statfun_indepsamplesT'; cfg.parameter = 'pow'; cfg.correctm = 'cluster'; cfg.numrandomization = 1000; cfg.alpha = 0.05; % note that this only implies single-sided testing cfg.tail = 0; cfg.design(1,:) = [1:nTrials 1:nTrials]; cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2]; cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials) cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions) stat = ft_sourcestatistics(cfg, source); After the source analysis the source statistics script calls the checkdata script and I get the following error: Index exceeds array bounds. Error in ft_datatype_source (line 183) val{indx(k)}(1,:,:,:) = dat{indx(k)}; Error in ft_checkdata (line 278) data = ft_datatype_source(data); Error in ft_sourcestatistics (line 94) varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no'); Error in sourcelocalisation_N2O (line 114) stat = ft_sourcestatistics(cfg, source); The source struct has the following content: time: [1×15360 double] dim: [24 31 25] inside: [18600×1 logical] pos: [18600×3 double] method: 'rawtrial' trial: [1×24 struct] df: 24 cfg: [1×1 struct] With source.trial: 1×24 struct array with fields: ori pow mom noise filter label filterdimord I would like your help to understand the error and how to fix it. Regards, Xavier Vrijdag _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: ------------------------------ Message: 3 Date: Thu, 21 Feb 2019 16:16:47 +0000 From: Pierre Bastien Megevand To: "fieldtrip at science.ru.nl" Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM forward solution Message-ID: <617c8035ce184327b4ed18a9caa3a033 at unige.ch> Content-Type: text/plain; charset="iso-8859-1" Dear all, I think I have found an inconsistency in the way Fieldtrip handles the building of a FEM forward solution. I am following the procedure described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline for EEG forward solutions. Biomed Eng Online. 2018 (https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y). This procedure suggests to build the forward solution by calling the following Fieldtrip functions: ft_read_mri ft_volumerealign ft_volumereslice ft_volumesegment ft_prepare_mesh ft_prepare_headmodel ft_read_header (to get electrode data) ft_electroderealign ft_prepare_vol_sens ft_prepare_sourcemodel ft_prepare_leadfield My issue is the following: the FieldTrip-SimBio pipeline explicitly calls ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the case of the published paper, which used about 80 electrodes). However, ft_prepare_leadfield later calls (line 165) prepare_headmodel, which itself calls (line 113) ft_prepare_vol_sens again, with the same parameters as far as I can tell (and again taking ages to run). Is this redundancy intended? If not, can it be circumvented? Thank you in advance, Pierre Pierre Mégevand, MD, PhD Senior research associate, Dept. of basic neurosciences Faculty of medicine, University of Geneva, Switzerland T. +41 76 693 65 22 | pierre.megevand at unige.ch -------------- next part -------------- An HTML attachment was scrubbed... URL: ------------------------------ Message: 4 Date: Fri, 22 Feb 2019 15:44:42 +0530 From: Neeraj kumar To: fieldtrip at science.ru.nl Subject: [FieldTrip] Parcellate the reconstructed source time series Message-ID: Content-Type: text/plain; charset="utf-8" Hello all, I want to parcellate the reconstructed source time series (~ 1000ms). I have moments in source.avg.mom for around 6000 grids. Additionally, do I need to perform some normalization on time series before or after parcellation to perform network analysis? Thanks in advance. Neeraj Kumar, -------------- next part -------------- An HTML attachment was scrubbed... URL: ------------------------------ Message: 5 Date: Fri, 22 Feb 2019 11:40:28 +0100 From: Johannes To: FieldTrip discussion list Subject: Re: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM forward solution Message-ID: Content-Type: text/plain; charset="utf-8" Dear Pierre, if you are running a recent version of FieldTrip (newer than Dec 15, 2018), there should be a check included in ft_prepare_vol_sens to avoid this behavior, i.e., if a transfer matrix is detected in the vol-struct provided to ft_prepare_vol_sens, it is checked if whether this fits to the indicated sensor configuration and if this is the case no new transfer matrix is computed. This should also work if a subset of sensors is selected. Thus, it would be great, if you could check whether this behavior remains when using a recent checkout of FieldTrip. Regarding the time requirement for computing the transfer matrix - the calculation in sb_transfer can be easily parallelized by replacing l 35 in sb_transfer with a parfor loop, e.g., parfor(i=2:length(vol.elecnodes),8), if you want to compute on 8 cores. I hope this answer is helpful to you! Best, Johannes Am Do., 21. Feb. 2019 um 17:17 Uhr schrieb Pierre Bastien Megevand < Pierre.Megevand at unige.ch>: > Dear all, > > > I think I have found an inconsistency in the way Fieldtrip handles the > building of a FEM forward solution. I am following the procedure > described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline > for EEG forward solutions. Biomed Eng Online. 2018 ( > https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y). > This procedure suggests to build the forward solution by calling the > following Fieldtrip functions: > > ft_read_mri > > ft_volumerealign > > ft_volumereslice > > ft_volumesegment > > ft_prepare_mesh > > ft_prepare_headmodel > > ft_read_header (to get electrode data) > > ft_electroderealign > > ft_prepare_vol_sens > > ft_prepare_sourcemodel > > ft_prepare_leadfield > > > My issue is the following: the FieldTrip-SimBio pipeline explicitly calls > ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the > case of the published paper, which used about 80 electrodes). However, > ft_prepare_leadfield later calls (line 165) prepare_headmodel, which > itself calls (line 113) ft_prepare_vol_sens again, with the same > parameters as far as I can tell (and again taking ages to run). > > > Is this redundancy intended? If not, can it be circumvented? > > > Thank you in advance, > > > Pierre > > > Pierre Mégevand, MD, PhD > Senior research associate, Dept. of basic neurosciences > Faculty of medicine, University of Geneva, Switzerland > T. +41 76 693 65 22 | pierre.megevand at unige.ch > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: ------------------------------ Subject: Digest Footer _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 ------------------------------ End of fieldtrip Digest, Vol 99, Issue 22 ***************************************** -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From j.vorw01 at gmail.com Fri Feb 22 14:39:21 2019 From: j.vorw01 at gmail.com (Johannes Vorwerk) Date: Fri, 22 Feb 2019 14:39:21 +0100 Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM forward solution In-Reply-To: References: Message-ID: <1E07B224-B7DA-420F-95EF-23FF2CC94C1A@gmail.com> Dear Pierre, I am glad it works now. Regarding the call to ft_prepare_sourcemodel I agree with you that this is repetitive at this position. I think you could actually just skip the first call and directly include the definition of the sources in the cfg for the call to ft_prepare_leadfield. I do not think another check is necessary here, since the computation times for ft_prepare_sourcemodel are usually pretty short. Thanks for your correction regarding the parallelization. Indeed, the command „clear vecb“ also needs to be replaced/removed (since vecb is zeroed in l 38 and is only defined inside the loop), I oversaw that when looking up the parallelized version of sb_transfer.m I am using. I haven’t made any tests to parallelize ft_compute_leadfield, your approach sounds promising though. Best, Johannes > Am 22.02.2019 um 13:37 schrieb Pierre Bastien Megevand : > > Dear Johannes, thank you for your answer. My bad--I was not using an up-to-date version of FieldTrip. Indeed, now that I have updated the code, the transfer matrix is not computed again by ft_prepare_leadfield. I think that a similar check might be necessary for the call to ft_prepare_sourcemodel (line 178 of ft_prepare_leadfield), since the FieldTrip-SimBio pipeline also calls that function explicitly beforehand. > > In order to parallelize the transfer matrix computation, in sb_transfer, I suggest that the code at line 41, which currently reads "clear vecb;", be replaced by "vecb=[];", because there is a transparency issue when using "clear" within a parfor loop (see https://ch.mathworks.com/help/distcomp/transparency.html ). > > I have also been trying to parallelize ft_prepare_leadfield. Given that ft_compute_leadfield is called once per grid point, I replaced the for loop at line 301 of ft_prepare_leadfield with a parfor loop. The indexing of grid.leadfield{thisindx} poses a "sliced variable" problem to MATLAB though. The workaround I used was to create a temporary variable, grid_leadfield, and to index it with {i} instead of {thisindx}. At the end of the loop, the "grid.leadfield(insideindx)=grid_leadfield;" line reestablishes that variable. I am currently testing this. > > Pierre > > > > De : fieldtrip > de la part de fieldtrip-request at science.ru.nl > > Envoyé : vendredi, 22 février 2019 12:00 > À : fieldtrip at science.ru.nl > Objet : fieldtrip Digest, Vol 99, Issue 22 > > Send fieldtrip mailing list submissions to > fieldtrip at science.ru.nl > > To subscribe or unsubscribe via the World Wide Web, visit > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > or, via email, send a message with subject or body 'help' to > fieldtrip-request at science.ru.nl > > You can reach the person managing the list at > fieldtrip-owner at science.ru.nl > > When replying, please edit your Subject line so it is more specific > than "Re: Contents of fieldtrip digest..." > > > Today's Topics: > > 1. Postdoc opportunity (up to 4 years), Obleser lab, Lübeck > (GER) (Jonas Obleser) > 2. Re: Error in source localisation statistics > (Schoffelen, J.M. (Jan Mathijs)) > 3. issue with FieldTrip-SimBio pipeline for EEG FEM forward > solution (Pierre Bastien Megevand) > 4. Parcellate the reconstructed source time series (Neeraj kumar) > 5. Re: issue with FieldTrip-SimBio pipeline for EEG FEM forward > solution (Johannes) > > > ---------------------------------------------------------------------- > > Message: 1 > Date: Thu, 21 Feb 2019 14:46:54 +0100 > From: Jonas Obleser > > To: fieldtrip at science.ru.nl > Subject: [FieldTrip] Postdoc opportunity (up to 4 years), Obleser lab, > Lübeck (GER) > Message-ID: <0866A3D2-FD30-421C-A138-B34E45CE7704 at obleser.de > > Content-Type: text/plain; charset="utf-8" > > Dear colleagues, > > sorry for any crossposting: > I am hiring a Postdoc to do some exciting Cogn Neuro with my lab and me near the baltic sea in the years to come. > > This post is not grant-based, so more-than-usual freedom, topicwise, but some modest teaching involvement. Application deadline March 15, starting date any time, full German contract up to 4 years. > > If interested/in doubt, please talk to me. Contact details below. > Thanks for spreading the news, > Jonas > > obleserlab.com > > uni-luebeck.de > > > Job ad in English: > https://auditorycognition.com/docs/Postdoc-Obleserlab-March2019.pdf > > > Job ad in German: > https://www.academics.de/jobs/wissenschaftlicher-mitarbeiter-post-doc-m-w-d-am-institut-fuer-psychologie-universitaet-zu-luebeck-luebeck-1004361?user_token=SFMyNTY.g3QAAAACZAAEZGF0YWIAAG6AZAAGc2lnbmVkbgYAt8Q1EGkB.yJa3d_6Otl3R_0t0GvEOLq-etYWIp13xoZ4MDhwN5m0&utm_campaign=jobnewsletter&utm_medium=nl&utm_source=2019-02-21&wt_zmc=nl.int.aca.jobnewsletter.2019-02-21.acade.textlink.stellenanzeige_supertreffer.job > > > > Jonas Obleser > Professor > Chair in Physiological Psychology and Research Methods > > University of Lübeck > Department of Psychology > MFC 8, Maria-Goeppert-Straße 9a > 23562 Lübeck, Germany > > Phone +49 (0)451 3101 3620 > Mobile +49 (0)171 6993337 > jonas.obleser at uni-luebeck.de > http://jonasobleser.com > > ---Schedule a meeting with me? https://calendly.com/jonasobleser --- > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > > > ------------------------------ > > Message: 2 > Date: Thu, 21 Feb 2019 15:10:18 +0000 > From: "Schoffelen, J.M. (Jan Mathijs)" > > To: FieldTrip discussion list > > Subject: Re: [FieldTrip] Error in source localisation statistics > Message-ID: <21612B35-BED5-4A31-8206-CAC578C72109 at donders.ru.nl > > Content-Type: text/plain; charset="utf-8" > > Hi Xavier, > > I see. Unfortunately you happened to end up in a corner of the code that is a bit shaky, and possibly not well tested (although once upon a time it may have worked). This may be due to the fact that you are trying to ‘fool’ fieldtrip into treating a multiple subject design as if it’s a single subject design with multiple trials (where each of the trials represents a single condition estimate for a subject), correct? (as a side note: you would want to use ‘depsamplesT’ rather than ‘indepsamplesT’ as your test statistic). > > I think that you should not do this. First, as you have noticed this leads to downstream problems (specifically handcrafting combined data could easily lead to a user-error causing the data to deviate according to what FieldTrip can handle, but also using the cfg.rawtrial option of ft_sourceanalaysis historically and notoriously is a dysfunctional (or at least unpredictable in its behavior) option. (nominated to be removed once we find the time). Next to this, even though it seems your geometrical data (i.e. electrode positions, headmodel, sourcemodel) are shared across subjects, the covariance structure of the data will for sure be subject-specific, and I don’t think that it is a good idea to combine data across subjects before sourceanalysis. > > This is what I would do: > > for each subject do: > > ft_timelockanalysis with the subject-specific data combined across conditions > ft_timelockanalysis with the subject-specific data for each of the conditions separately > > ft_sourceanalysis with the subject-specific data combined across conditions AND cfg.lcmv.keepfilter = ‘yes’; (and don’t specify cfg.keeptrials or cfg.rawtrial) > > input the source.avg.filter from the previous step into the cfg > > for each condition (in each subject) do: > ft_sourceanalysis > > > after this you should have a set of Nsubject times number of conditions source structures > > then you should be able to use ft_sourcestatistics with cfg.statisti = ‘depsamplesT’: > > ft_sourcestatistics(cfg, source{:}); % if in the previous for-loop you have stored the individual source-objects into a cell-array this syntax works (and is much cleaner than either ft_sourcestatistics(cfg, source1a, source2a ,…etc), and cleaner than going through ft_sourcegrandaverage). > > ft_sourcedescriptives should not be needed in this recipe. > > Good luck, > Jan-Mathijs > > > J.M.Schoffelen, MD PhD > Senior Researcher, VIDI-fellow - PI, language in interaction > Telephone: +31-24-3614793 > Physical location: room 00.028 > Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands > > > > On 20 Feb 2019, at 21:32, Xavier Vrijdag >> wrote: > > Hi Jan-Mathijs, > > Thank you for your help. I went in to have a look at what is going on inside those loops and found that the error is occurring in iteration 6, when the field source.trial(1).label is concatenated. It uses the indexes for the big data cells (ori, mom & filter) which clearly doesn’t work on the small cell with the labels. This seems to me that this is a bug. > > I added a piece of code in front of the loop that was giving the error (before line 177 and make the if and elseif. > if isequal(fn{i}, 'label') > for j=1:nrpt > source_new.label(:,j) = source.trial(j).label; > end > elseif iscell(dat) > > This worked to circumvent the problem. However, I do get the warning that the dimord of “ori” and “df” could not be determined. When using this cleaned source struct in source statistics I get further errors. > > It looks like an issue with how the source struct is built by the source analysis function with trials, and lateron needs to be restructured. SO I would like to know what is the needed structure for ft_sourcestatistics, so we can adjust the code correctly. > > Regards, > > Xavier > > > From: fieldtrip >> on behalf of "Schoffelen, J.M. (Jan Mathijs)" >> > Reply-To: FieldTrip discussion list >> > Date: Wednesday, 20 February 2019 at 2:59 AM > To: FieldTrip discussion list >> > Subject: Re: [FieldTrip] Error in source localisation statistics > > Hi Xavier, > > My recommendation here would be to use the matlab debugger and inspect the cause of the error. The ‘Index exceeds array bounds’ is quite a clear error message, and suggests that there is a mismatch between the number of elements in dat/val, and the numbers represented in indx(k). > > Good luck, > > Jan-Mathijs > > > On 18 Feb 2019, at 07:23, Xavier Vrijdag >> wrote: > > Hello, > > I have a dataset from an experiment where 12 participants were exposed to 3 levels of nitrous oxide, while I measured their EEG. I also have a baseline recording. I took for each exposure (and baseline) a 1 minute sample for further analysis. I want to do source localization to better understand which parts of the brain are involved. I don’t have MRI scans of my participants, so I used the standard MRI and BEM. I would like to thanks the persons who made the various manuals and analysis examples on the website, as they helped me tremendously to do this analysis. > > After cleaning and preprocessing, I combined the datasets into one for further analysis. I also chose to make 5 sec “trials” for further analysis. For this source analysis I loaded the data of 1 exposure and the baseline data, to compare them. > > %Calculate the channel covariance matric > cfg = []; > cfg.covariance = 'yes'; > cfg.covariancewindow = 'all'; > cfg.keeptrials = 'yes'; > timelock = ft_timelockanalysis(cfg, data_filt); > > %Global filter > cfg = []; > cfg.headmodel = vol; > cfg.elec = elec_aligned; > cfg.grid = grid; > cfg.method = 'lcmv'; > cfg.lcmv.projectnoise='yes'; %needed for neural activity index > cfg.lcmv.fixedori = 'yes'; %Project onto largest variance orientation > cfg.lcmv.keepfilter = 'yes'; %Keep the beamformer weights > cfg.lcmv.lambda = '5%'; %Regularise a little > cfg.rawtrial = 'yes'; % project each single trial through the filter. > cfg.keeptrials = 'yes'; > source = ft_sourceanalysis(cfg, timelock); > > cfg = []; > cfg.dim = source.dim; > cfg.method = 'montecarlo'; > cfg.statistic = 'ft_statfun_indepsamplesT'; > cfg.parameter = 'pow'; > cfg.correctm = 'cluster'; > cfg.numrandomization = 1000; > cfg.alpha = 0.05; % note that this only implies single-sided testing > cfg.tail = 0; > cfg.design(1,:) = [1:nTrials 1:nTrials]; > cfg.design(2,:) = [ones(1,nTrials) ones(1,nTrials).*2]; > cfg.uvar = 1; % row of design matrix that contains unit variable (in this case: trials) > cfg.ivar = 2; % row of design matrix that contains independent variable (the conditions) > stat = ft_sourcestatistics(cfg, source); > > After the source analysis the source statistics script calls the checkdata script and I get the following error: > > Index exceeds array bounds. > > Error in ft_datatype_source (line 183) > val{indx(k)}(1,:,:,:) = dat{indx(k)}; > > Error in ft_checkdata (line 278) > data = ft_datatype_source(data); > > Error in ft_sourcestatistics (line 94) > varargin{i} = ft_checkdata(varargin{i}, 'datatype', 'source', 'feedback', 'no'); > > Error in sourcelocalisation_N2O (line 114) > stat = ft_sourcestatistics(cfg, source); > > The source struct has the following content: > time: [1×15360 double] > dim: [24 31 25] > inside: [18600×1 logical] > pos: [18600×3 double] > method: 'rawtrial' > trial: [1×24 struct] > df: 24 > cfg: [1×1 struct] > > With source.trial: > 1×24 struct array with fields: > ori > pow > mom > noise > filter > label > filterdimord > > I would like your help to understand the error and how to fix it. > > Regards, > > Xavier Vrijdag > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > > > > > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > > > ------------------------------ > > Message: 3 > Date: Thu, 21 Feb 2019 16:16:47 +0000 > From: Pierre Bastien Megevand > > To: "fieldtrip at science.ru.nl " > > Subject: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG FEM > forward solution > Message-ID: <617c8035ce184327b4ed18a9caa3a033 at unige.ch > > Content-Type: text/plain; charset="iso-8859-1" > > Dear all, > > > I think I have found an inconsistency in the way Fieldtrip handles the building of a FEM forward solution. I am following the procedure described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline for EEG forward solutions. Biomed Eng Online. 2018 (https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y ). This procedure suggests to build the forward solution by calling the following Fieldtrip functions: > > ft_read_mri > > ft_volumerealign > > ft_volumereslice > > ft_volumesegment > > ft_prepare_mesh > > ft_prepare_headmodel > > ft_read_header (to get electrode data) > > ft_electroderealign > > ft_prepare_vol_sens > > ft_prepare_sourcemodel > > ft_prepare_leadfield > > > My issue is the following: the FieldTrip-SimBio pipeline explicitly calls ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the case of the published paper, which used about 80 electrodes). However, ft_prepare_leadfield later calls (line 165) prepare_headmodel, which itself calls (line 113) ft_prepare_vol_sens again, with the same parameters as far as I can tell (and again taking ages to run). > > > Is this redundancy intended? If not, can it be circumvented? > > > Thank you in advance, > > > Pierre > > > Pierre Mégevand, MD, PhD > Senior research associate, Dept. of basic neurosciences > Faculty of medicine, University of Geneva, Switzerland > T. +41 76 693 65 22 | pierre.megevand at unige.ch > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > > > ------------------------------ > > Message: 4 > Date: Fri, 22 Feb 2019 15:44:42 +0530 > From: Neeraj kumar > > To: fieldtrip at science.ru.nl > Subject: [FieldTrip] Parcellate the reconstructed source time series > Message-ID: > > > Content-Type: text/plain; charset="utf-8" > > Hello all, > > I want to parcellate the reconstructed source time series (~ 1000ms). > I have moments in source.avg.mom for around 6000 grids. > Additionally, do I need to perform some normalization on time series before > or after parcellation to perform network analysis? > > Thanks in advance. > > Neeraj Kumar, > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > > > ------------------------------ > > Message: 5 > Date: Fri, 22 Feb 2019 11:40:28 +0100 > From: Johannes > > To: FieldTrip discussion list > > Subject: Re: [FieldTrip] issue with FieldTrip-SimBio pipeline for EEG > FEM forward solution > Message-ID: > > > Content-Type: text/plain; charset="utf-8" > > Dear Pierre, > > if you are running a recent version of FieldTrip (newer than Dec 15, 2018), > there should be a check included in ft_prepare_vol_sens to avoid this > behavior, i.e., if a transfer matrix is detected in the vol-struct provided > to ft_prepare_vol_sens, it is checked if whether this fits to the indicated > sensor configuration and if this is the case no new transfer matrix is > computed. This should also work if a subset of sensors is selected. Thus, > it would be great, if you could check whether this behavior remains when > using a recent checkout of FieldTrip. > > Regarding the time requirement for computing the transfer matrix - the > calculation in sb_transfer can be easily parallelized by replacing l 35 in > sb_transfer with a parfor loop, e.g., parfor(i=2:length(vol.elecnodes),8), > if you want to compute on 8 cores. > > I hope this answer is helpful to you! > > Best, > Johannes > > Am Do., 21. Feb. 2019 um 17:17 Uhr schrieb Pierre Bastien Megevand < > Pierre.Megevand at unige.ch >: > > > Dear all, > > > > > > I think I have found an inconsistency in the way Fieldtrip handles the > > building of a FEM forward solution. I am following the procedure > > described in Vorwerk, Oostenveld et al., The FieldTrip-SimBio pipeline > > for EEG forward solutions. Biomed Eng Online. 2018 ( > > https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-018-0463-y ). > > This procedure suggests to build the forward solution by calling the > > following Fieldtrip functions: > > > > ft_read_mri > > > > ft_volumerealign > > > > ft_volumereslice > > > > ft_volumesegment > > > > ft_prepare_mesh > > > > ft_prepare_headmodel > > > > ft_read_header (to get electrode data) > > > > ft_electroderealign > > > > ft_prepare_vol_sens > > > > ft_prepare_sourcemodel > > > > ft_prepare_leadfield > > > > > > My issue is the following: the FieldTrip-SimBio pipeline explicitly calls > > ft_prepare_vol_sens, which takes very long to execute (over 6 hours in the > > case of the published paper, which used about 80 electrodes). However, > > ft_prepare_leadfield later calls (line 165) prepare_headmodel, which > > itself calls (line 113) ft_prepare_vol_sens again, with the same > > parameters as far as I can tell (and again taking ages to run). > > > > > > Is this redundancy intended? If not, can it be circumvented? > > > > > > Thank you in advance, > > > > > > Pierre > > > > > > Pierre Mégevand, MD, PhD > > Senior research associate, Dept. of basic neurosciences > > Faculty of medicine, University of Geneva, Switzerland > > T. +41 76 693 65 22 | pierre.megevand at unige.ch > > > > _______________________________________________ > > fieldtrip mailing list > > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > > https://doi.org/10.1371/journal.pcbi.1002202 > > > -------------- next part -------------- > An HTML attachment was scrubbed... > URL: > > > ------------------------------ > > Subject: Digest Footer > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > > > ------------------------------ > > End of fieldtrip Digest, Vol 99, Issue 22 > ***************************************** > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From neeraj750kumar at gmail.com Fri Feb 22 14:51:56 2019 From: neeraj750kumar at gmail.com (Neeraj kumar) Date: Fri, 22 Feb 2019 19:21:56 +0530 Subject: [FieldTrip] Parcellate the reconstructed source time series In-Reply-To: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> References: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> Message-ID: Dear Schoffelen, Thank you for your answer. But I'm still confused about how to get parcellated source time series in fieldtrip. I have 1sec time series for around 6000 grids. Neeraj On Fri, 22 Feb 2019 at 17:46, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > > I want to parcellate the reconstructed source time series (~ 1000ms). > I have moments in source.avg.mom for around 6000 grids. > > Additionally, do I need to perform some normalization on time series > before or after parcellation to perform network analysis? > > > Well, at least you should compute a metric between pairs of time series > that can be subjected to a network analysis. Whether or not this needs > ‘some normalization’ depends on what you exactly want to achieve. > > Best wishes, > Jan-Mathijs > > > > > > J.M.Schoffelen, MD PhD > Senior Researcher, VIDI-fellow - PI, language in interaction > Telephone: +31-24-3614793 > Physical location: room 00.028 > Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands > > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Sat Feb 23 20:45:16 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Sat, 23 Feb 2019 19:45:16 +0000 Subject: [FieldTrip] Parcellate the reconstructed source time series In-Reply-To: References: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> Message-ID: Could you be a bit more specific in your question? Right now, based on the quality of your question, it seems as if you haven’t spent much time searching the documentation yourself. For instance, http://www.fieldtriptoolbox.org/tutorial/networkanalysis/ would already give you some directions how to ‘parcellate’ your source level data. Also, if you look for ‘ft_sourceparcellate’ you’ll probably be able to sort out how to do it. Jan-Mathijs On 22 Feb 2019, at 14:51, Neeraj kumar > wrote: Dear Schoffelen, Thank you for your answer. But I'm still confused about how to get parcellated source time series in fieldtrip. I have 1sec time series for around 6000 grids. Neeraj On Fri, 22 Feb 2019 at 17:46, Schoffelen, J.M. (Jan Mathijs) > wrote: I want to parcellate the reconstructed source time series (~ 1000ms). I have moments in source.avg.mom for around 6000 grids. Additionally, do I need to perform some normalization on time series before or after parcellation to perform network analysis? Well, at least you should compute a metric between pairs of time series that can be subjected to a network analysis. Whether or not this needs ‘some normalization’ depends on what you exactly want to achieve. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From neeraj750kumar at gmail.com Mon Feb 25 18:44:36 2019 From: neeraj750kumar at gmail.com (Neeraj kumar) Date: Mon, 25 Feb 2019 23:14:36 +0530 Subject: [FieldTrip] Parcellate the reconstructed source time series In-Reply-To: References: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> Message-ID: Dear Schoffelen, Thank you for your reply and sorry for the vague question. I did look for the options you suggested in your last mail. I'm facing following issues with them: 1. For "ft_sourceparcellate" our functional data must be in the same as our atlas. For that, we need to interpolate the functional data to the atlas. However, the problem is that 'ft_sourceinterpolate' is interpolating only "pow" and "coh" not "mom" (source time course ). In the documentation also ( http://www.fieldtriptoolbox.org/tutorial/networkanalysis/#connectivity-analysis-and-parcellation ) they are interpolating 'Coh' only, thus parcellating only coherence. 2. I also tried to use the source model (sourcemodel_4k.mat) and headmodel (hdm.mat) provided at this link ( ftp://ftp.fieldtriptoolbox.org/pub/fieldtrip/tutorial/networkanalysis/) to prepare leadfield but the headmodel is not compatible for EEG. My final goal is to perform 'ft_connectivityanalysis(cfg, data)', where 'data' contains time series of all parcellated roi. It would be very helpful if you can help me with that. Thank you Neeraj On Sun, 24 Feb 2019 at 01:27, Schoffelen, J.M. (Jan Mathijs) < jan.schoffelen at donders.ru.nl> wrote: > Could you be a bit more specific in your question? Right now, based on the > quality of your question, it seems as if you haven’t spent much time > searching the documentation yourself. For instance, > http://www.fieldtriptoolbox.org/tutorial/networkanalysis/ would already > give you some directions how to ‘parcellate’ your source level data. Also, > if you look for ‘ft_sourceparcellate’ you’ll probably be able to sort out > how to do it. > > Jan-Mathijs > > > On 22 Feb 2019, at 14:51, Neeraj kumar wrote: > > Dear Schoffelen, > > Thank you for your answer. But I'm still confused about how to get > parcellated source time series in fieldtrip. I have 1sec time series for > around 6000 grids. > > Neeraj > > On Fri, 22 Feb 2019 at 17:46, Schoffelen, J.M. (Jan Mathijs) < > jan.schoffelen at donders.ru.nl> wrote: > >> >> I want to parcellate the reconstructed source time series (~ 1000ms). >> I have moments in source.avg.mom for around 6000 grids. >> >> Additionally, do I need to perform some normalization on time series >> before or after parcellation to perform network analysis? >> >> >> Well, at least you should compute a metric between pairs of time series >> that can be subjected to a network analysis. Whether or not this needs >> ‘some normalization’ depends on what you exactly want to achieve. >> >> Best wishes, >> Jan-Mathijs >> >> >> >> >> >> J.M.Schoffelen, MD PhD >> Senior Researcher, VIDI-fellow - PI, language in interaction >> Telephone: +31-24-3614793 >> Physical location: room 00.028 >> Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> https://doi.org/10.1371/journal.pcbi.1002202 >> > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From jan.schoffelen at donders.ru.nl Tue Feb 26 09:43:56 2019 From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs)) Date: Tue, 26 Feb 2019 08:43:56 +0000 Subject: [FieldTrip] Parcellate the reconstructed source time series In-Reply-To: References: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> Message-ID: 1. For "ft_sourceparcellate" our functional data must be in the same as our atlas. For that, we need to interpolate the functional data to the atlas. However, the problem is that 'ft_sourceinterpolate' is interpolating only "pow" and "coh" not "mom" (source time course ). In the documentation also ( http://www.fieldtriptoolbox.org/tutorial/networkanalysis/#connectivity-analysis-and-parcellation ) they are interpolating 'Coh' only, thus parcellating only coherence. Why not just follow the suggestion as per the network tutorial, and compute the connectivity metric at the uninterpolated dipole positions? Alternatively, if you need the univariate time courses parcellated, you may want to try and interpolate your atlas onto the source model that you used for source reconstruction, and then use the interpolated atlas for parcellation. Or, as a third option, you may want to create a source model that is based on the equivalent dipole positions as in your atlas so that you don’t need to interpolate your reconstructed sources. Good luck, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands On Sun, 24 Feb 2019 at 01:27, Schoffelen, J.M. (Jan Mathijs) > wrote: Could you be a bit more specific in your question? Right now, based on the quality of your question, it seems as if you haven’t spent much time searching the documentation yourself. For instance, http://www.fieldtriptoolbox.org/tutorial/networkanalysis/ would already give you some directions how to ‘parcellate’ your source level data. Also, if you look for ‘ft_sourceparcellate’ you’ll probably be able to sort out how to do it. Jan-Mathijs On 22 Feb 2019, at 14:51, Neeraj kumar > wrote: Dear Schoffelen, Thank you for your answer. But I'm still confused about how to get parcellated source time series in fieldtrip. I have 1sec time series for around 6000 grids. Neeraj On Fri, 22 Feb 2019 at 17:46, Schoffelen, J.M. (Jan Mathijs) > wrote: I want to parcellate the reconstructed source time series (~ 1000ms). I have moments in source.avg.mom for around 6000 grids. Additionally, do I need to perform some normalization on time series before or after parcellation to perform network analysis? Well, at least you should compute a metric between pairs of time series that can be subjected to a network analysis. Whether or not this needs ‘some normalization’ depends on what you exactly want to achieve. Best wishes, Jan-Mathijs J.M.Schoffelen, MD PhD Senior Researcher, VIDI-fellow - PI, language in interaction Telephone: +31-24-3614793 Physical location: room 00.028 Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From tzvetan.popov at uni-konstanz.de Tue Feb 26 09:43:48 2019 From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov) Date: Tue, 26 Feb 2019 09:43:48 +0100 Subject: [FieldTrip] Parcellate the reconstructed source time series In-Reply-To: References: <87717E17-45FB-4085-8B2E-E612C8FC0C2D@donders.ru.nl> Message-ID: <74949B2F-9FDF-4EBB-99D3-F6B7E132FFFB@uni-konstanz.de> Dear Neeraj, in addition to Jan-Mathijs’ suggestions you should consider the following: Compute the head model suited for EEG analysis. Type ‘EEG head model’ in the search field and browse thru the links that will pop up. Once you have your head model you could compute source model in accordance with some brain atlas. An example is provided here: http://www.fieldtriptoolbox.org/tutorial/salzburg/ In particular, the section http://www.fieldtriptoolbox.org/tutorial/salzburg/#localizing-auditory-evoked-fields-using-beamforming-techniques-in-parceled-brain-space gives you an idea how to approach this. > > My final goal is to perform 'ft_connectivityanalysis(cfg, data)', where 'data' contains time series of all parcellated roi. It would be very helpful if you can help me with that. Example of your final goal is illustrated here: http://www.fieldtriptoolbox.org/tutorial/salzburg/#connectivity-analysis using only 3 brain parcels. Yet, once you understand the pipeline you can easily extend to your preferred number of parcels. Good luck Tzvetan > > Thank you > Neeraj > > > > > On Sun, 24 Feb 2019 at 01:27, Schoffelen, J.M. (Jan Mathijs) > wrote: > Could you be a bit more specific in your question? Right now, based on the quality of your question, it seems as if you haven’t spent much time searching the documentation yourself. For instance, http://www.fieldtriptoolbox.org/tutorial/networkanalysis/ would already give you some directions how to ‘parcellate’ your source level data. Also, if you look for ‘ft_sourceparcellate’ you’ll probably be able to sort out how to do it. > > Jan-Mathijs > > >> On 22 Feb 2019, at 14:51, Neeraj kumar > wrote: >> >> Dear Schoffelen, >> >> Thank you for your answer. But I'm still confused about how to get parcellated source time series in fieldtrip. I have 1sec time series for around 6000 grids. >> >> Neeraj >> >> On Fri, 22 Feb 2019 at 17:46, Schoffelen, J.M. (Jan Mathijs) > wrote: >> >>> I want to parcellate the reconstructed source time series (~ 1000ms). >>> I have moments in source.avg.mom for around 6000 grids. >>> Additionally, do I need to perform some normalization on time series before or after parcellation to perform network analysis? >> >> Well, at least you should compute a metric between pairs of time series that can be subjected to a network analysis. Whether or not this needs ‘some normalization’ depends on what you exactly want to achieve. >> >> Best wishes, >> Jan-Mathijs >> >> >> >> >> >> J.M.Schoffelen, MD PhD >> Senior Researcher, VIDI-fellow - PI, language in interaction >> Telephone: +31-24-3614793 >> Physical location: room 00.028 >> Donders Centre for Cognitive Neuroimaging, Nijmegen, The Netherlands >> >> >> >> _______________________________________________ >> fieldtrip mailing list >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> https://doi.org/10.1371/journal.pcbi.1002202 >> _______________________________________________ >> fieldtrip mailing list >> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip >> https://doi.org/10.1371/journal.pcbi.1002202 > > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 > _______________________________________________ > fieldtrip mailing list > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip > https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From Holger.Krause at med.uni-duesseldorf.de Wed Feb 27 18:35:58 2019 From: Holger.Krause at med.uni-duesseldorf.de (Holger.Krause at med.uni-duesseldorf.de) Date: Wed, 27 Feb 2019 17:35:58 +0000 Subject: [FieldTrip] Latest FT version on ftp-server is from three days ago In-Reply-To: <1C272A6F-9FCD-4F96-AF0A-1CB01AF46C03@donders.ru.nl> References: <404F4AB0E196F54D941EB2469822658AF5BC264E@MAIL3-UKD.VMED.UKD>, <1C272A6F-9FCD-4F96-AF0A-1CB01AF46C03@donders.ru.nl> Message-ID: <404F4AB0E196F54D941EB2469822658AF651CB11@MAIL3-UKD.VMED.UKD> Dear developers, Once again, daily releases to the ftp server seem to got stuck. The newest one is fieldtrip-20190224.zip. Perhaps someone could talk to the cron daemon again? Concerning the suggested switch to obtain fresh versions from github, I'm wondering, if there's a way to extract the exact "daily release" version as to be found on the ftp server from a git repository, given any specific date? Is the released zip file on the ftp server identical to the zip file, which one would download at midnight from github? Thanks for taking care in advance! Holger ________________________________ Von: fieldtrip [fieldtrip-bounces at science.ru.nl]" im Auftrag von "Schoffelen, J.M. (Jan Mathijs) [jan.schoffelen at donders.ru.nl] Gesendet: Mittwoch, 8. August 2018 17:25 An: FieldTrip discussion list Betreff: Re: [FieldTrip] Latest FT version on ftp-server is from three days ago Dear Holger, Indeed the cronjob that takes care of the daily zipping and upload to the ftp-server was not restarted after our TG did some upgrades to the compute cluster early this week. It has now been restarted (by Robert) so a new version should become available tonight. Note that this might be a good moment to look into the possibility of using github to get your local and daily copy of the repository. See http://www.fieldtriptoolbox.org/development/git for more information. With best wishes, and apologies for any inconvenience caused. Jan-Mathijs On 8 Aug 2018, at 15:10, Holger.Krause at med.uni-duesseldorf.de wrote: Dear developers, Last version available on the ftp server seems to be fieldtrip-20180805.zip. Could you please have a look at this? Thanks in advance, Holger _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From andrea.brovelli at univ-amu.fr Thu Feb 28 17:37:07 2019 From: andrea.brovelli at univ-amu.fr (Andrea Brovelli) Date: Thu, 28 Feb 2019 17:37:07 +0100 Subject: [FieldTrip] Group-level analyses of single-subject cluster-based statistics Message-ID: <950cde2d-11b9-f650-956e-b25c478330c8@univ-amu.fr> Dear all, we would like to perform group-level analyses of the results obtained from single-subject cluster-based statistics. In our case, each subject has a statistical map of size (time x channels) thresholded using cluster-based statistics method. Given you expertise in the cluster-based methods, what do you think would be a good way to perform group-level statistics? And could you point me to some tools, codes, papers please? Or simply send a link of previous discussions on the mailing list? I cannot find them.... Thanks a lot. Best, Andrea _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202 From lah at pedneuro.uni-kiel.de Thu Feb 28 21:47:19 2019 From: lah at pedneuro.uni-kiel.de (Laith Hamid) Date: Thu, 28 Feb 2019 21:47:19 +0100 Subject: [FieldTrip] =?utf-8?q?Call_for_Abstracts=3A_CRC_1261=27s_Summer_?= =?utf-8?q?School_2019_=22Magnetic_sensing_and_applications_in_medicine_an?= =?utf-8?q?d_industry_=E2=80=93_state_of_the_art_and_new_prospects=22_in_K?= =?utf-8?q?iel=2C_Germany?= Message-ID: <2944b1825f3eaa9fa91b75370fb194b5@pedneuro.uni-kiel.de> Dear colleagues from the Fieldtrip community, we would like to inform you about the CRC 1261's Summer School 2019 "Magnetic sensing and applications in medicine and industry - state of the art and new prospects" that will be held in August 2019 in Kiel, Germany. Please forward this email to your students and colleagues. Call for Abstracts: CRC 1261's Summer School 2019 "Magnetic sensing and applications in medicine and industry - state of the art and new prospects" Magnetoelectric sensors can be used in both industrial and medical/biological applications. Sensors currently developed within the framework of CRC 1261 (for further information see www.sfb1261.de) aim at the detection of biomagnetic signals from the brain, heart, nerves and magnetically labeled cells. Additional applications, according to the needs of industry, are considered for future funding periods. Topics covered: * Sensor concepts, fabrication, characterization, modeling, benchmarking * Sensor array building and desing * Measurement electronics * Signal processing * Forward/inverse problems and sensor fusion * Medical diagnostics Event The interdisciplinary Collaborative Research Center (CRC) 1261 "Magnetoelectric Sensors: From Composite Materials to Biomagnetic Diagnostics" funded by the German Research Foundation (DFG) at Kiel University (for further information see www.sfb1261.de) will hold an international Summer School on 19-21 August 2019 in Kiel, Germany. Location The Summer School 2019 will take place at Kiel University, founded in 1665. The city is located on the shores of the Baltic Sea. In addition to its scientific prowess, the city of Kiel is renowned for its big sailing events, beautiful beaches and numerous festivals. Additionally, the city offers many opportunities for cultural tours and outdoor activities. The 3-day schedule of the Summer School includes: * Talks by invited speakers, including experts from industry * Laboratory visits within the Faculty of Engineering: Kiel Nanolab, magnetically shielded room, facilities of the Departments of Materials Science and Electrical Engineering * Soft skills courses for improving interdisciplinary and intercultural skills * Participants will be asked to present their work as a poster or in a short talk * Poster award for the best poster * Participants will have the possibility to network with representatives of Kiel University Interested in Participation? The participation fee is 100 EUR. Participants must cover their own travel costs. All applications must include the following documents: * a short CV, * a brief description of maximum one page that describes why you want to attend the summer school * an abstract about your scientific research. Deadline for submissions is April 15th. Please send your application in one pdf document to summerschool at sfb1261.de. There will be 30 places for international participants. If there are more applications, the participants will be selected according to their motivation letter and abstract. Best regards, Laith Hamid -------------- next part -------------- An HTML attachment was scrubbed... URL: -------------- next part -------------- _______________________________________________ fieldtrip mailing list https://mailman.science.ru.nl/mailman/listinfo/fieldtrip https://doi.org/10.1371/journal.pcbi.1002202