[FieldTrip] ft_globalmeanfield : Undefined function of variable 'abort'

[Jing Fan]

Hi Jim,

I download the latest .zip file from FTP.
I received the same error message when calling function ft_definetrial(cfg).
It seems to me that ft_preamble init command will go to script ft_preamble.m
instead of ft_preamble_init.m.
Any help to resolve this issue will be appreciated.

Best,
Jing



-----Original Message-----
From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Herring, J.D. (Jim)
Sent: Monday, September 15, 2014 5:01 AM
To: FieldTrip discussion list
Subject: Re: [FieldTrip] ft_globalmeanfield : Undefined function of variable
'abort'

Dear Barbara,

The error seems to be related to a bug that pops up now and then
(http://bugzilla.fcdonders.nl/show_bug.cgi?id=2580) which could be due to a
corrupt installation of fieldtrip and/or the need to update fieldtrip. 

Could you please try downloading the most recent version of fieldtrip and
see if the problem persists?

For an example of what can be expected from this function see: Esser SK,
Huber R, Massimini M, Peterson MJ, Ferrarelli F, Tononi G. A direct
demonstration of cortical LTP in humans: a combined TMS/EEG study. Brain Res
Bull. 2006 Mar 15;69(1):86-94. Epub 2005 Dec 1. PubMed PMID: 16464689.

Best,

Jim 


----- Oorspronkelijk bericht -----
> Van: "barbara schorr" <barbara.schorr at uni-ulm.de>
> Aan: fieldtrip at science.ru.nl
> Verzonden: Woensdag 10 september 2014 14:07:14
> Onderwerp: [FieldTrip] ft_globalmeanfield : Undefined function of variable
'abort'
> Dear fieldtripers.
> 
> as mentioned in the subject line I would like to anaylse my timelocked
> ERP Data with the function ft_globalmeanfield.
> 
> I get the Error: Undefined function or variable 'abort'
> Error in ft_globalmeanfield (line84)
> if abort
> 
> in the function it says:
> 
> %the abort variable is set to true or false in ft_preamble_inti
> if abort
> % do not continue function execution in case the outputfile is
> present and the user indicated to keep it
> return
> end
> 
> 
> I don't understand what this means. I would really appreciate your
> help to get this running.
> 
> Also, what is the result when I run this function on my data? (This
> method was proposed from a reviewer. I never used it before, so I
> don't exactly know what it does and what the result will look like).
> 
> Thank you very much in advance!
> 
> Best,
> 
> Barbara Schorr
> 
> 
> 
> 
> Zitat von fieldtrip-request at science.ru.nl:
> 
> > Send fieldtrip mailing list submissions to
> > 	fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> > 	http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > 	fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> > 	fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. Re: Question regarding nonparametric testing for coherence
> >       differences (Eric Maris)
> >    2. Re: Problem with Geodesic 129 layout!! (KatrinH Heimann)
> >    3. Re: Problem with Geodesic 129 layout!! (Joseph Dien)
> >    4. Re: ft_rejectvisual: removing trials marked as bad
> >       (Caspar, Emilie)
> >    5. Re: TRENTOOL pipeline help (Patricia Wollstadt)
> >    6. Latest FT version on ftp-server is from three days ago
> >       (Holger Krause)
> >    7. Re: TRENTOOL pipeline help (Max Cantor)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Mon, 8 Sep 2014 15:46:11 +0200 (CEST)
> > From: "Eric Maris" <e.maris at psych.ru.nl>
> > To: <hweeling.lee at gmail.com>, "'FieldTrip discussion list'"
> > 	<fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] Question regarding nonparametric testing
> > for
> > 	coherence differences
> > Message-ID: <015901cfcb6b$3fdf1f00$bf9d5d00$@maris at psych.ru.nl>
> > Content-Type: text/plain; charset="utf-8"
> >
> > Dear Hwee Ling,
> >
> >
> >
> > In the paper you refer to (Maris et al, JNM, 2007), I did not
> > perform a
> > cluster-based permutation test at the level of the channel pairs.
> > Instead,
> > all coherences mentioned in the paper are coherence between a single
> > EMG
> > channel (2 electrodes mounted on the forearm) and all MEG
> > electrodes. Thus,
> > there are as many EMG-MEG coherences as there are MEG channels (275
> > in our
> > lab), and the clustering of these coherences involves the same
> > neighbourhood
> > structure as the clustering of channel-specific statistics on power
> > or
> > evoked response. The analysis you propose involves clustering in a
> > much more
> > complex space, namely the formed by all (MEG,MEG) channel pairs
> > (275*275=75625 pairs). In the early days of cluster-based
> > permutation
> > statistics, I have worked on this problem but did not pursue it
> > because the
> > resulting clusters are very hard to interpret.
> >
> >
> >
> > Best,
> >
> >
> >
> > Eric Maris
> >
> >
> >
> >
> >
> > Dear all and Prof Maris,
> >
> > I'm re-posting this question again, as I didn't get any replies
> > previously.
> >
> > I?m interested to investigate if there are any differences in phase
> > synchronization in resting state data at timepoint 2 versus
> > timepoint 1. The
> > EEG data was collected using 64 EEG channels, resting state, eyes
> > opened and
> > eyes closed. I?ve arbitrarily segmented the resting state data into
> > epochs
> > of 2s each, and the epochs with artifacts are excluded completely
> > from
> > further analyses. I then performed mtmfft to get the fourier
> > representation
> > of the data, extracted the coherence, and compared the coherence
> > difference
> > of timepoint 2 versus timepoint 1 of all channels paired with all
> > other
> > channels.
> >
> > I figured that if I extract the connectivity analyses without
> > specifying the
> > channelcmb, I get a 'chan_chan_freq' dimord variable that would
> > allow me to
> > perform cluster-based statistical analyses. I get an output with
> > ?chan_chan?
> > dimord variable. However, I was not 100% sure that this is correct,
> > hence, I?ve
> > inserted my code (see below). It?ll be great if you could tell me if
> > what I?m
> > doing makes any sense at all. Also, I don?t know how I can plot the
> > results
> > to see if it make any sense at all.
> >
> > Also, I checked the values obtained from when I specified
> > "cfg.channelcmb"
> > and when I did not specify "cfg.channelcmb", I noticed that the
> > values were
> > somehow different. I would assume that the values to be similar,
> > although
> > I'm not sure why they would have differences in the values obtained
> > from
> > specifying "cfg.channelcmb".
> >
> > This is my code that I've used thus far:
> >
> > for sub = 1:5
> >
> >     cfg = [];
> >
> >     cfg.output = 'fourier';
> >
> >     cfg.channel = {'all'};
> >
> >     cfg.method = 'mtmfft';
> >
> >     cfg.keeptrials = 'yes';
> >
> >     cfg.tapsmofrq = 5;
> >
> >        cfg.foilim = [0 100];
> >
> >     cfg.taper = 'dpss';
> >
> >     % find the index for the c200 condition
> >
> >    pre_c200_idx = find(data5.trialinfo == 201);
> >
> >     cfg.trials = pre_c200_idx;
> >
> >     HLF_pre_c200 = ft_freqanalysis(cfg, data5);
> >
> > post_c200_idx = find(data5.trialinfo == 200);
> >
> >     cfg.trials = post_c200_idx;
> >
> >     HLF_post_c200 = ft_freqanalysis(cfg, data5);
> >
> >
> >
> > cfg = [];
> >
> >     cfg.keeptrials = 'no';
> >
> >     cfg.channel = {'all'};
> >
> >     cfg.removemean = 'yes';
> >
> >     cfg.method = 'coh';
> >
> >     HLF_pre_c200coh{sub} = ft_connectivityanalysis(cfg,
> >     HLF_pre_c200);
> >
> >     HLF_post_c200coh{sub} = ft_connectivityanalysis(cfg,
> > HLF_post_c200);
> >
> > end
> >
> >
> >
> >
load('D:\Hweeling_Programs\fieldtrip-20140330\template\layout\easycapM11.mat
');
> >
> > cfg_neighb.method = 'template';
> >
> > cfg_neighb.layout = lay;
> >
> > cfg_neighb.channel = 'all';
> >
> > neighbours = ft_prepare_neighbours(cfg_neighb,
> > sub_HLF_pre_c200coh{1});
> >
> >
> >
> > cfg = [];
> >
> > cfg.layout = lay;
> >
> > cfg.neighbours = neighbours;
> >
> > cfg.channel = 'all';
> >
> > cfg.channelcmb = {cfg.channel, cfg.channel};
> >
> > cfg.latency = 'all';
> >
> > cfg.avgovertime = 'no';
> >
> > cfg.avgoverchan = 'no';
> >
> > cfg.parameter = 'cohspctrm';
> >
> > cfg.method = 'montecarlo';
> >
> > cfg.statistic = 'depsamplesT';
> >
> > cfg.correctm = 'cluster';
> >
> > cfg.tail = 0;
> >
> > % cfg.clustertail = 0;
> >
> > cfg.alpha = 0.05/8; % to correct for multiple comparisons across 8
> > frequency
> > bands.
> >
> > cfg.numrandomization = 10000;
> >
> > cfg.ivar = 2;
> >
> > cfg.uvar = 1;
> >
> >
> >
> > % design matrices
> >
> > clear design;
> >
> > design(1,:) = [1:5, 1:5];
> >
> > design(2,:) = [ones(1,5), ones(1,5) * 2];
> >
> > cfg.design = design;
> >
> > % for theta band
> >
> > cfg.avgoverfreq = 'yes';
> >
> > cfg.frequency = [4 8]; % I also performed the statistics for delta
> > (2-4),
> > alpha (8-10.5), alpha (10.5-13), beta (13-20), beta (20-30), gamma
> > (30-40),
> > and gamma (40-100).
> >
> > [diffc200_theta_stat] = ft_freqstatistics(cfg,
> > sub_HLF_post_c200coh{:},
> > sub_HLF_pre_c200coh{:});
> >
> >
> >
> > When I tried to plot the results, I used this code:
> >
> > cfg = [];
> >
> > cfg.channel = 'all';
> >
> > cfg.layout = 'lay';
> >
> > cfg.zlim = [-1 1];
> >
> > cfg.alpha = 0.05;
> >
> > cfg.refchannel = 'all';
> >
> > ft_clusterplot(cfg, diffc200_theta_stat);
> >
> > However, I was not sure how I could plot the results. I get an error
> > message
> > from Fieldtrip when using ft_clusterplot:
> >
> > Error using topoplot_common (line 366)
> >
> > no reference channel is specified
> >
> > Error in ft_topoplotTFR (line 192)
> >
> > [cfg] = topoplot_common(cfg, varargin{:});
> >
> > Error in ft_clusterplot (line 372)
> >
> >       ft_topoplotTFR(cfgtopo, stat);
> >
> >
> >
> > According to your paper in 2007, the topoplot of the results were
> > masked by
> > the spatio-spectral pattern of the significant clusters. I don't
> > know how to
> > do this, and I would really appreciate if you can show me how to
> > make such a
> > plot.
> >
> > Thank you very much.
> >
> > Kind regards,
> >
> > Hweeling
> >
> >
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL:
> >
<http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20140908/98b85
280/attachment-0001.html>
> >
> > ------------------------------
> >
> > Message: 2
> > Date: Mon, 8 Sep 2014 21:38:01 +0200
> > From: KatrinH Heimann <katrinheimann at gmail.com>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] Problem with Geodesic 129 layout!!
> > Message-ID:
> > 	<CACnHcBeqEoQMirfZ-hCKK8rSmbfcNYzxFQH1mmSaeGCuKMN-uA at mail.gmail.com>
> > Content-Type: text/plain; charset="utf-8"
> >
> > Dear Joseph, thanks so much, I really appreciate your help. I was
> > also
> > wandering, if maybe there is another bug in my code.
> > Our nets are 128 channels, Hydrocel, but as a colleague of me
> > adviced me to
> > do so, I also tried the 129 layout.
> > My code you find below (without selection of bad channels etc.)
> > If you need also the data of two subjects to have a look, let me
> > know!!!
> > Best and thanks really!
> >  Katrin
> >
> >
> > subject=input('Which subject do you want to analyse? ','s');
> >
> > name = strcat(subject,'.raw');
> >
> > subjectnumber=input('Which is the subjectnumber?', 's');
> >
> > sb=subjectnumber
> >
> > %subjectnumber = strcat(subjectnumber, '.txt')
> >
> > %%
> >
> >
> > cfg = [];
> >
> > cfg.dataset = name;
> >
> > cfg.trialfun = 'ft_trialfun_general'; % this is the default
> >
> > cfg.trialdef.eventtype = 'trigger';
> >
> > cfg.trialdef.eventvalue = 'stim'; % the value of the stimulus
> > trigger
> >
> > cfg.trialdef.prestim = 0.234; % in seconds
> >
> > cfg.trialdef.poststim = 7.266; % in seconds (whole time of video
> > observation, but maybe we need less)
> >
> > cfg = ft_definetrial(cfg);
> >
> >
> > cfg.trl([1:7],:) = [];
> >
> >
> > %change timeline according to constant offset of 16 ms = 8 samples
> > (because
> > recorded with 500 hz)in
> >
> > %structure trial
> >
> > cfg.trl(:,3)=cfg.trl(:,3)-8
> >
> >
> > %change timeline to make the cut the zeropoint
> >
> >
> > cfg.trl(:,3)=cfg.trl(:,3)- 1000;
> >
> >
> >
> > %% preprocess data
> >
> > cfg.channel = 'all';
> >
> > cfg.preproc.detrend = 'yes';
> >
> > cfg.preproc.demean = 'yes';
> >
> > cfg.preproc.baselinewindow = [-2.1 -2.0]
> >
> > %cfg.preproc.bpfilter = 'yes'; - the data here has to be already
> > filtered
> >
> > %(0.1-45) and bad channels have to be replaced!!!!
> >
> > %cfg.preproc.bpfreq = [6 32];
> >
> > %
> >
> > %
> >
> > obs_data = ft_preprocessing(cfg);
> >
> > %
> >
> > save (strcat(sb,'obs_data') , 'obs_data')
> >
> >
> > %% determining channel neighbours (necessary for Artifact detection)
> >
> > cfg = [];
> >
> > cfg.channel = obs_data.label;
> >
> > cfg.layout = 'GSN128.sfp';
> >
> > cfg.feedback = 'yes';
> >
> > lay = ft_prepare_layout(cfg);
> >
> >
> >
> > cfg_neighb = [];
> >
> > cfg_neighb.feedback = 'yes';
> >
> >
> > cfg_neighb.method = 'triangulation';
> >
> > cfg_neighb.layout = 'GSN128.sfp';
> >
> > neighbours = ft_prepare_neighbours(cfg_neighb, obs_data);
> >
> >
> > obs_data.elec = ft_read_sens('GSN128.sfp');
> >
> >
> > %% Artifacts - to detect bad channels - is not saved!!!
> >
> >
> >
> > cfg.method = 'summary';
> >
> > cfg.latency=[0 1];
> >
> > cfg.layout = 'GSN128.sfp'; % this allows for plotting
> >
> > obs_data_try = ft_rejectvisual(cfg, obs_data);
> >
> >
> > cfg = [];
> >
> > cfg.viewmode = 'vertical';
> >
> > cfg.latency=[0 1];
> >
> > cfg.continuous = 'no';
> >
> > cfg.plotlabels='yes'
> >
> > cfg = ft_databrowser(cfg,obs_data);
> >
> > %cfg.artfctdef.reject = 'complete';
> >
> > obs_data_try = ft_rejectartifact (cfg,obs_data);
> >
> >
> >
> > %% Preparing neighbours for channel repair - but bad channel info
> > in!!!
> >
> >
> > % cfg_neighb = [];
> >
> > % cfg_neighb.feedback = 'yes';
> >
> > % cfg_neighb.method = 'triangulation';
> >
> > % cfg_neighb.layout = 'GSN-HydroCel-128.sfp';
> >
> > % neighbours = ft_prepare_neighbours(cfg_neighb, obs_data);
> >
> >
> > % Interpolate and put into new data structure
> >
> >  cfg = [];
> >
> >  cfg.badchannel = {};
> >
> >  cfg.layout = 'GSN128.sfp';
> >
> >  cfg.method = 'nearest';
> >
> >  cfg.neighbours = neighbours;
> >
> >  obs_data_channelrepaired = ft_channelrepair(cfg,obs_data)
> >
> >
> >  % Check reconstruction
> >
> > cfg = [];
> >
> > cfg.viewmode = 'vertical';
> >
> > cfg.continuous = 'no';
> >
> > cfg.plotlabels='yes'
> >
> > cfg = ft_databrowser(cfg,obs_data_channelrepaired);
> >
> > %cfg.artfctdef.reject = 'complete';
> >
> > obs_data_clean1 = ft_rejectartifact (cfg,obs_data_channelrepaired);
> >
> >
> > % dat1=obs_data;
> >
> > % dat2=obs_data_channelrepaired;
> >
> > %
> >
> > % x=dat1.trial{1}(62,:); % 68 is channel index of E68
> >
> > % y=dat2.trial{1}(62,:);
> >
> > % plot(x);hold on;plot(y,'r');
> >
> > %
> >
> > % x=dat1.trial{1}(72,:);
> >
> > % y=dat2.trial{1}(75,:);
> >
> > % figure;
> >
> > % plot(x);hold on;plot(y,'r')
> >
> > %
> >
> > % x=dat1.trial{1}(75,:);
> >
> > % y=dat2.trial{1}(75,:);
> >
> > % figure;
> >
> > % plot(x);hold on;plot(y,'r')
> >
> > %% artifact rejection/trial inspection - throw out electrode jumps
> > etc.
> >
> >
> >
> > cfg = [];
> >
> > cfg.viewmode = 'vertical';
> >
> > cfg.continuous = 'no';
> >
> > cfg.plotlabels='yes'
> >
> > cfg = ft_databrowser(cfg,obs_data_channelrepaired);
> >
> > %cfg.artfctdef.reject = 'complete';
> >
> > obs_data_clean1 = ft_rejectartifact (cfg,obs_data_channelrepaired);
> >
> >
> > %% ICA - Anzahl der Komponenten anpassen!- adapt numcomponent
> > according to
> > channels interpolated %% 128-number of interp. channels)
> >
> >
> >
> > cfg = [];
> >
> > cfg.channel = {'all'};
> >
> > cfg.numcomponent = 128
> >
> > comp = ft_componentanalysis(cfg,obs_data_clean1);
> >
> > save (strcat(sb,'comp_all') , 'comp')
> >
> >
> > %%
> >
> > cfg = [];
> >
> > cfg.viewmode = 'component';
> >
> > cfg.continuous = 'no';
> >
> > cfg.plotlabels='some';
> >
> > cfg.layout = 'GSN128.sfp';
> >
> > ft_databrowser(cfg,comp);
> >
> >
> > %% poweranalysis components
> >
> > cfg = [];
> >
> > cfg.output = 'pow';
> >
> > cfg.channel = 'all';%compute the power spectrum in all ICs
> >
> > cfg.method = 'mtmfft';
> >
> > cfg.taper = 'hanning';
> >
> > cfg.foi = 0:0.2:50;
> >
> > obs_freq = ft_freqanalysis(cfg, comp);
> >
> >
> > %And you can plot the spectra:
> >
> >
> > %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> >
> > nsubplots = 16;
> >
> > nbyn = sqrt(nsubplots);% sqrt(nsubplots) should not contain
> > decimals, type
> > doc subplot
> >
> >
> > Nfigs = ceil(size(comp.topo,1)/nsubplots);
> >
> > tot = Nfigs*nsubplots;
> >
> >
> > rptvect = 1:size(comp.topo,1);
> >
> > rptvect = padarray(rptvect, [0 tot-size(comp.topo,1)], 0,'post');
> >
> > rptvect = reshape(rptvect,nsubplots,Nfigs)';
> >
> >
> > for r=1:size(rptvect,1);
> >
> >   figure;set(gcf,'units','normalized','outerposition',[0 0 1
> >   1]);%full
> > screen
> >
> >   k=0;
> >
> >   for j=1:size(rptvect,2);
> >
> >     if~(rptvect(r,j)==0);
> >
> >       k=k+1;
> >
> >       cfg=[];
> >
> >       cfg.channel = rptvect(r,j);
> >
> >       cfg.ylim =[0 500]
> >
> >       cfg.xlim =[0 50]
> >
> >       subplot(nbyn,nbyn,k);ft_singleplotER(cfg,obs_freq);
> >
> >     end
> >
> >   end
> >
> > end
> >
> >
> > %For the IC topos you'll follow the same logic as above but with:
> >
> >
> > figure
> >
> > cfg = [];
> >
> > cfg.component = [1:20]; % specify the component(s) that should be
> > plotted
> >
> > cfg.layout = 'GSN128.sfp';
> >
> > cfg.comment = 'no';
> >
> > ft_topoplotIC(cfg, comp)
> >
> >
> > figure
> >
> > cfg = [];
> >
> > cfg.component = [21:40]; % specify the component(s) that should be
> > plotted
> >
> > cfg.layout = 'GSN128.sfp';
> >
> > cfg.comment = 'no';
> >
> > ft_topoplotIC(cfg, comp)
> >
> >
> > figure
> >
> > cfg = [];
> >
> > cfg.component = [41:60]; % specify the component(s) that should be
> > plotted
> >
> > cfg.layout = 'GSN128.sfp';
> >
> > cfg.comment = 'no';
> >
> > ft_topoplotIC(cfg, comp)
> >
> >
> > figure
> >
> > cfg = [];
> >
> > cfg.component = [61:80]; % specify the component(s) that should be
> > plotted
> >
> > cfg.layout = 'GSN128.sfp';
> >
> > cfg.comment = 'no';
> >
> > ft_topoplotIC(cfg, comp)
> >
> >
> >
> >
> >
> >
> > %% Seperate observation conditions
> >
> >
> > name1= strcat(num2str(sb),'_90.xls');
> >
> >     list1=xlsread (name1)
> >
> >
> >
> >
> >
> > name2= strcat(num2str(sb),'_180.xls');
> >
> >     list2=xlsread (name2)
> >
> >
> >
> > %
> >
> >
> > cfg = []
> >
> > cfg.trials = [list1]
> >
> > obs90_data = ft_redefinetrial(cfg,obs_data_channelrepaired)
> >
> >
> > cfg = []
> >
> > cfg.trials = [list2]
> >
> > obs180_data = ft_redefinetrial(cfg,obs_data_channelrepaired)
> >
> >
> > %%PIPELINE FOR obs90
> >
> >
> > %% Decompose original data according to the components found before
> >
> > load (strcat(sb,'comp_all'))
> >
> >
> > cfg = [];
> >
> > cfg.numcomponent = 128;
> >
> > cfg.unmixing = comp.unmixing;
> >
> > cfg.topolabel = comp.topolabel;
> >
> >
> > comp_1 = ft_componentanalysis(cfg, obs90_data);
> >
> >
> >
> > %% Reject component
> >
> > cfg = [];
> >
> >     cfg.component = [];
> >
> >     obs90_data_ica_cleaned = ft_rejectcomponent(cfg, comp_1,
> >     obs90_data);
> >
> >
> >
> >
> >  save (strcat(sb,'obs90_ica_cleaned') , 'obs90_data_ica_cleaned')
> >
> >
> >
> >
> > %% Artifacts - final detection
> >
> >
> >
> > cfg.method = 'summary';
> >
> > cfg.latency=[0 1];
> >
> > cfg.layout = 'GSN128.sfp'; % this allows for plotting
> >
> > obs90_data_clean3 = ft_rejectvisual(cfg, obs90_data_ica_cleaned);
> >
> >
> > cfg = [];
> >
> > cfg.viewmode = 'vertical';
> >
> > cfg.latency=[0 1];
> >
> > cfg.continuous = 'no';
> >
> > cfg.plotlabels='yes'
> >
> > cfg = ft_databrowser(cfg,obs90_data_clean3);
> >
> > %cfg.artfctdef.reject = 'complete';
> >
> > obs90_data_clean2 = ft_rejectartifact (cfg,obs90_data_clean3);
> >
> >
> >
> > % Save clean data
> >
> >
> > save (strcat(subject,'obs90_clean') , 'obs90_data_clean2')
> >
> >
> >
> > %% Rereferencing data
> >
> > cfg = [];
> >
> >
> > cfg.channel = 'all';
> >
> > cfg.preproc.reref = 'yes';
> >
> > cfg.preproc.refchannel = 'all';
> >
> > obs90_data_ref= ft_preprocessing(cfg,obs90_data_clean2)
> >
> >
> > save (strcat(subject,'obs90_ref') , 'obs90_data_ref')
> >
> > %% Snap out smaller pieces (the third second)
> >
> >
> > cfg = []
> >
> > cfg.toilim = [0 1]
> >
> >
> > obs90_data_small = ft_redefinetrial(cfg,obs90_data_ref)
> >
> >
> > %% TIMELOCK ERP
> >
> > obs90_data_ERP = ft_timelockanalysis(cfg, obs90_data_small);
> >
> >
> > save (strcat(subject,'obs90_ERP') , 'obs90_data_ERP')
> >
> >
> > %% plot it
> >
> > cfg = [];
> >
> > cfg.layout = lay ;
> >
> > cfg.interactive = 'yes';
> >
> > ft_multiplotER(cfg, obs90_data_ERP)
> >
> >
> >
> >
> >
> >
> >
> > %% PIPELINE FOR obs180
> >
> >
> >
> > %% Decompose original data according to the components found before
> >
> > load (strcat(sb,'comp_all'))
> >
> >
> > cfg = [];
> >
> > cfg.numcomponent = 128
> >
> > cfg.unmixing = comp.unmixing;
> >
> > cfg.topolabel = comp.topolabel;
> >
> > comp_2 = ft_componentanalysis(cfg, obs180_data);
> >
> >
> >
> > %% Reject component
> >
> > cfg = [];
> >
> >     cfg.component = [];
> >
> >     obs180_data_ica_cleaned = ft_rejectcomponent(cfg, comp_2,
> >     obs180_data);
> >
> >
> >
> >
> >  save (strcat(sb,'obs180_ica_cleaned') , 'obs180_data_ica_cleaned')
> >
> >
> >
> >
> > %% Artifacts final 180
> >
> >
> >
> > cfg.method = 'summary';
> >
> > cfg.latency=[0 1];
> >
> > cfg.layout = 'GSN128.sfp'; % this allows for plotting
> >
> > obs180_data_clean3 = ft_rejectvisual(cfg, obs180_data_ica_cleaned);
> >
> >
> > cfg = [];
> >
> > cfg.viewmode = 'vertical';
> >
> > cfg.latency=[0 1];
> >
> > cfg.continuous = 'no';
> >
> > cfg.plotlabels='yes'
> >
> > cfg = ft_databrowser(cfg,obs180_data_clean3);
> >
> > %cfg.artfctdef.reject = 'complete';
> >
> > obs180_data_clean2 = ft_rejectartifact (cfg,obs180_data_clean3);
> >
> >
> >
> > % Save clean data
> >
> >
> > save (strcat(subject,'obs180_clean') , 'obs180_data_clean2')
> >
> >
> >
> > %% Rereferencing data
> >
> > cfg = [];
> >
> > cfg.channel = 'all';
> >
> > cfg.preproc.reref = 'yes';
> >
> > cfg.preproc.refchannel = 'all';
> >
> > obs180_data_ref= ft_preprocessing(cfg,obs180_data_clean2)
> >
> >
> > save (strcat(subject,'obs180_ref') , 'obs180_data_ref')
> >
> > %% Snap out smaller pieces (the third second)
> >
> >
> > cfg = []
> >
> > cfg.toilim = [0 1]
> >
> >
> > obs180_data_small = ft_redefinetrial(cfg,obs180_data_ref)
> >
> >
> > %% TIMELOCK ERP
> >
> > obs180_data_ERP = ft_timelockanalysis(cfg, obs180_data_small);
> >
> >
> > save (strcat(subject,'obs180_ERP') , 'obs180_data_ERP')
> >
> >
> > %% plot 180 ERP
> >
> >
> > cfg = [];
> >
> > cfg.layout = lay ;
> >
> > cfg.interactive = 'yes';
> >
> > ft_multiplotER(cfg, obs180_data_ERP)
> >
> >
> > %% plot both ERPs
> >
> >
> > cfg = [];
> >
> > cfg.layout = lay ;
> >
> > cfg.interactive = 'yes';
> >
> > cfg.showlabels = 'yes';
> >
> > ft_multiplotER(cfg, obs90_data_ERP, obs180_data_ERP)
> >
> >
> > %% plot difference wave
> >
> >
> > difference = obs180_data_ERP; % copy one of the
> > structures
> >
> > difference.avg = obs180_data_ERP.avg - obs90_data_ERP.avg; % compute
> > the
> > difference ERP
> >
> >
> >
> > cfg = [];
> >
> > cfg.layout = lay;
> >
> > cfg.interactive = 'yes';
> >
> > ft_multiplotER(cfg, difference)
> >
> > 2014-09-07 7:53 GMT+02:00 Joseph Dien <jdien07 at mac.com>:
> >
> >> Hi,
> >>    I?m one of the main Fieldtrip contributors working on supporting
> >>    EGI
> >> data. A couple things. First of all, exactly which net do you use?
> >> If
> >> they are 129-channel, there is still the question of whether they
> >> are the
> >> Hydrocel or the older geodesic nets. Regardless, that shouldn't
> >> cause an
> >> error like this. Could you send me the file you are trying to
> >> process and
> >> the script you are using and I?ll try troubleshooting it.
> >>
> >> Joe
> >>
> >>
> >> On Aug 26, 2014, at 12:53 AM, Ana Laura Diez Martini <
> >> diezmartini at gmail.com> wrote:
> >>
> >> Which nets do you use? I use EGI. I tried both the ones you mention
> >> and
> >> they didn't work. It was hard to find that exact one online but it
> >> was the
> >> only file that actually worked.
> >>
> >>
> >> On Mon, Aug 25, 2014 at 7:52 AM, KatrinH Heimann
> >> <katrinheimann at gmail.com>
> >> wrote:
> >>
> >>> Dear Ana, dear all,
> >>> the layout you used does not correspond to our nets. I tried the
> >>>    GSN-HydroCel-128.sfp and the GSN-HydroCel-129.sfp. Both don't
> >>>    work.
> >>> Please can anybody help?
> >>> Cheers
> >>> Katrin
> >>>
> >>>
> >>> 2014-08-24 5:40 GMT+02:00 Ana Laura Diez Martini
> >>> <diezmartini at gmail.com>:
> >>>
> >>> Try this one
> >>> <https://www.dropbox.com/s/58zv658rtdant2c/GSN129.sfp?dl=0>
> >>>> I use
> >>>>
> >>>>
> >>>> On Sun, Aug 24, 2014 at 4:08 AM, KatrinH Heimann <
> >>>> katrinheimann at gmail.com> wrote:
> >>>>
> >>>>> Dear all, my problems seem neverending. This time however i
> >>>>> really need
> >>>>> help.
> >>>>> I implemented a pipeline for ERPs. All works now,
> >>>>> trialdefinition,
> >>>>> preprocessing, channelreplacement, ica, componentrejection,
> >>>>> final
> >>>>> artifactdetection, timelock of the single subject data. However,
> >>>>> when I
> >>>>> wanna compute the grandaverage of the single subjects I get the
> >>>>> following
> >>>>> error message:
> >>>>>
> >>>>> computing average of avg over 19 subjects
> >>>>> Warning: discarding electrode information because it cannot be
> >>>>> averaged
> >>>>> > In ft_timelockgrandaverage at 249
> >>>>> the call to "ft_timelockgrandaverage" took 0 seconds and
> >>>>> required the
> >>>>> additional allocation of an estimated 3 MB
> >>>>> computing average of avg over 2 subjects
> >>>>> Warning: discarding electrode information because it cannot be
> >>>>> averaged
> >>>>> > In ft_timelockgrandaverage at 249
> >>>>> the call to "ft_timelockgrandaverage" took 0 seconds and
> >>>>> required the
> >>>>> additional allocation of an estimated 0 MB
> >>>>> the call to "ft_prepare_layout" took 0 seconds and required the
> >>>>> additional allocation of an estimated 0 MB
> >>>>> the call to "ft_topoplotER" took 0 seconds and required the
> >>>>> additional
> >>>>> allocation of an estimated 0 MB
> >>>>>
> >>>>> Furthermore in the plot of the significant clusters, the
> >>>>> channelnames
> >>>>> are mixed up (do not correspond to my net)
> >>>>>
> >>>>>
> >>>>> I guess that there is a problem with the layout I use.
> >>>>> Here the code that I use
> >>>>>
> >>>>> %For generating the layout (also in the single subjects):
> >>>>>
> >>>>> cfg = [];
> >>>>>
> >>>>> cfg.channel = obs_data.label;
> >>>>>
> >>>>> cfg.layout = 'GSN-HydroCel-129.sfp';
> >>>>>
> >>>>> cfg.feedback = 'yes';
> >>>>>
> >>>>> lay = ft_prepare_layout(cfg);
> >>>>>
> >>>>>
> >>>>> cfg_neighb = [];
> >>>>>
> >>>>> cfg_neighb.feedback = 'yes';
> >>>>>
> >>>>> cfg_neighb.method = 'triangulation';
> >>>>>
> >>>>> cfg_neighb.layout = lay;
> >>>>>
> >>>>> neighbours = ft_prepare_neighbours(cfg_neighb, obs_data);
> >>>>>
> >>>>>
> >>>>> obs_data.elec = ft_read_sens('GSN-HydroCel-129.sfp');
> >>>>>
> >>>>>
> >>>>> %For computing the grand average
> >>>>>
> >>>>> cfg = [];
> >>>>>
> >>>>> cfg.channel = 'all';
> >>>>>
> >>>>> cfg.latency = 'all';
> >>>>>
> >>>>> cfg.parameter = 'avg';
> >>>>>
> >>>>> cfg.keepindividual = 'no'
> >>>>>
> >>>>> GA_90 = ft_timelockgrandaverage(cfg,all90{:});
> >>>>>
> >>>>> GA_180 = ft_timelockgrandaverage(cfg,all180{:});
> >>>>>
> >>>>> % "{:}" means to use data from all elements of the variable
> >>>>>
> >>>>>
> >>>>> For plotting the significant clusters
> >>>>>
> >>>>> cfg = [];
> >>>>>
> >>>>> cfg.style = 'blank';
> >>>>>
> >>>>> cfg.layout = lay;
> >>>>>
> >>>>> cfg.channellabels = 'yes';
> >>>>>
> >>>>> cfg.highlight = 'labels';
> >>>>>
> >>>>> cfg.highlightchannel = find(stat.mask);
> >>>>>
> >>>>> cfg.comment = 'no';
> >>>>>
> >>>>> figure; ft_topoplotER(cfg, GA_90)
> >>>>>
> >>>>> title('Nonparametric: significant with cluster multiple
> >>>>> comparison
> >>>>> correction')
> >>>>>
> >>>>>
> >>>>> Do you have ANY idea to this? I am really completely
> >>>>> helpless....
> >>>>>
> >>>>> thanks and best
> >>>>>
> >>>>> Katrin
> >>>>>
> >>>>> _______________________________________________
> >>>>> fieldtrip mailing list
> >>>>> fieldtrip at donders.ru.nl
> >>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>>>
> >>>>
> >>>>
> >>>> _______________________________________________
> >>>> fieldtrip mailing list
> >>>> fieldtrip at donders.ru.nl
> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>>
> >>>
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >>
> >>
> >>
----------------------------------------------------------------------------
----
> >>
> >> Joseph Dien, PhD
> >> Research Associate
> >> Cognitive Neurology
> >> The Johns Hopkins University School of Medicine
> >>
> >> Lab E-mail: jdien1 at jhmi.edu
> >> Private E-mail: jdien07 at mac.com
> >> Office Phone: 410-614-3115
> >> Cell Phone: 202-297-8117
> >> Fax: 410-955-0188
> >> http://joedien.com
> >>
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL:
> >
<http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20140908/e8846
b61/attachment-0001.html>
> >
> > ------------------------------
> >
> > Message: 3
> > Date: Mon, 08 Sep 2014 21:55:44 -0400
> > From: Joseph Dien <jdien07 at mac.com>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] Problem with Geodesic 129 layout!!
> > Message-ID: <148A801A-8CEA-4F88-A7D0-130637BDAC03 at mac.com>
> > Content-Type: text/plain; charset="windows-1252"
> >
> > yes, please do send me the data.
> >
> > Thanks!
> >
> > Joe
> >
> > On Sep 8, 2014, at 3:38 PM, KatrinH Heimann
> > <katrinheimann at gmail.com> wrote:
> >
> >> Dear Joseph, thanks so much, I really appreciate your help. I was
> >> also wandering, if maybe there is another bug in my code.
> >> Our nets are 128 channels, Hydrocel, but as a colleague of me
> >> adviced me to do so, I also tried the 129 layout.
> >> My code you find below (without selection of bad channels etc.)
> >> If you need also the data of two subjects to have a look, let me
> >> know!!!
> >> Best and thanks really!
> >>  Katrin
> >>
> >>
> >>
> >> subject=input('Which subject do you want to analyse? ','s');
> >>
> >> name = strcat(subject,'.raw');
> >>
> >> subjectnumber=input('Which is the subjectnumber?', 's');
> >>
> >> sb=subjectnumber
> >>
> >> %subjectnumber = strcat(subjectnumber, '.txt')
> >>
> >> %%
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.dataset = name;
> >>
> >> cfg.trialfun = 'ft_trialfun_general'; % this is the default
> >>
> >> cfg.trialdef.eventtype = 'trigger';
> >>
> >> cfg.trialdef.eventvalue = 'stim'; % the value of the stimulus
> >> trigger
> >>
> >> cfg.trialdef.prestim = 0.234; % in seconds
> >>
> >> cfg.trialdef.poststim = 7.266; % in seconds (whole time of video
> >> observation, but maybe we need less)
> >>
> >> cfg = ft_definetrial(cfg);
> >>
> >>
> >>
> >> cfg.trl([1:7],:) = [];
> >>
> >>
> >>
> >> %change timeline according to constant offset of 16 ms = 8 samples
> >> (because recorded with 500 hz)in
> >>
> >> %structure trial
> >>
> >> cfg.trl(:,3)=cfg.trl(:,3)-8
> >>
> >>
> >>
> >> %change timeline to make the cut the zeropoint
> >>
> >>
> >>
> >> cfg.trl(:,3)=cfg.trl(:,3)- 1000;
> >>
> >>
> >>
> >>
> >>
> >> %% preprocess data
> >>
> >> cfg.channel = 'all';
> >>
> >> cfg.preproc.detrend = 'yes';
> >>
> >> cfg.preproc.demean = 'yes';
> >>
> >> cfg.preproc.baselinewindow = [-2.1 -2.0]
> >>
> >> %cfg.preproc.bpfilter = 'yes'; - the data here has to be already
> >> filtered
> >>
> >> %(0.1-45) and bad channels have to be replaced!!!!
> >>
> >> %cfg.preproc.bpfreq = [6 32];
> >>
> >> %
> >>
> >> %
> >>
> >> obs_data = ft_preprocessing(cfg);
> >>
> >> %
> >>
> >> save (strcat(sb,'obs_data') , 'obs_data')
> >>
> >>
> >>
> >> %% determining channel neighbours (necessary for Artifact
> >> detection)
> >>
> >> cfg = [];
> >>
> >> cfg.channel = obs_data.label;
> >>
> >> cfg.layout = 'GSN128.sfp';
> >>
> >> cfg.feedback = 'yes';
> >>
> >> lay = ft_prepare_layout(cfg);
> >>
> >>
> >> cfg_neighb = [];
> >>
> >> cfg_neighb.feedback = 'yes';
> >>
> >>
> >>
> >> cfg_neighb.method = 'triangulation';
> >>
> >> cfg_neighb.layout = 'GSN128.sfp';
> >>
> >> neighbours = ft_prepare_neighbours(cfg_neighb, obs_data);
> >>
> >>
> >>
> >> obs_data.elec = ft_read_sens('GSN128.sfp');
> >>
> >>
> >>
> >> %% Artifacts - to detect bad channels - is not saved!!!
> >>
> >>
> >>
> >>
> >>
> >> cfg.method = 'summary';
> >>
> >> cfg.latency=[0 1];
> >>
> >> cfg.layout = 'GSN128.sfp'; % this allows for plotting
> >>
> >> obs_data_try = ft_rejectvisual(cfg, obs_data);
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.viewmode = 'vertical';
> >>
> >> cfg.latency=[0 1];
> >>
> >> cfg.continuous = 'no';
> >>
> >> cfg.plotlabels='yes'
> >>
> >> cfg = ft_databrowser(cfg,obs_data);
> >>
> >> %cfg.artfctdef.reject = 'complete';
> >>
> >> obs_data_try = ft_rejectartifact (cfg,obs_data);
> >>
> >>
> >>
> >>
> >>
> >> %% Preparing neighbours for channel repair - but bad channel info
> >> in!!!
> >>
> >>
> >>
> >> % cfg_neighb = [];
> >>
> >> % cfg_neighb.feedback = 'yes';
> >>
> >> % cfg_neighb.method = 'triangulation';
> >>
> >> % cfg_neighb.layout = 'GSN-HydroCel-128.sfp';
> >>
> >> % neighbours = ft_prepare_neighbours(cfg_neighb, obs_data);
> >>
> >>
> >>
> >> % Interpolate and put into new data structure
> >>
> >>  cfg = [];
> >>
> >>  cfg.badchannel = {};
> >>
> >>  cfg.layout = 'GSN128.sfp';
> >>
> >>  cfg.method = 'nearest';
> >>
> >>  cfg.neighbours = neighbours;
> >>
> >>  obs_data_channelrepaired = ft_channelrepair(cfg,obs_data)
> >>
> >>
> >>
> >>  % Check reconstruction
> >>
> >> cfg = [];
> >>
> >> cfg.viewmode = 'vertical';
> >>
> >> cfg.continuous = 'no';
> >>
> >> cfg.plotlabels='yes'
> >>
> >> cfg = ft_databrowser(cfg,obs_data_channelrepaired);
> >>
> >> %cfg.artfctdef.reject = 'complete';
> >>
> >> obs_data_clean1 = ft_rejectartifact (cfg,obs_data_channelrepaired);
> >>
> >>
> >>
> >> % dat1=obs_data;
> >>
> >> % dat2=obs_data_channelrepaired;
> >>
> >> %
> >>
> >> % x=dat1.trial{1}(62,:); % 68 is channel index of E68
> >>
> >> % y=dat2.trial{1}(62,:);
> >>
> >> % plot(x);hold on;plot(y,'r');
> >>
> >> %
> >>
> >> % x=dat1.trial{1}(72,:);
> >>
> >> % y=dat2.trial{1}(75,:);
> >>
> >> % figure;
> >>
> >> % plot(x);hold on;plot(y,'r')
> >>
> >> %
> >>
> >> % x=dat1.trial{1}(75,:);
> >>
> >> % y=dat2.trial{1}(75,:);
> >>
> >> % figure;
> >>
> >> % plot(x);hold on;plot(y,'r')
> >>
> >> %% artifact rejection/trial inspection - throw out electrode jumps
> >> etc.
> >>
> >>
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.viewmode = 'vertical';
> >>
> >> cfg.continuous = 'no';
> >>
> >> cfg.plotlabels='yes'
> >>
> >> cfg = ft_databrowser(cfg,obs_data_channelrepaired);
> >>
> >> %cfg.artfctdef.reject = 'complete';
> >>
> >> obs_data_clean1 = ft_rejectartifact (cfg,obs_data_channelrepaired);
> >>
> >>
> >>
> >> %% ICA - Anzahl der Komponenten anpassen!- adapt numcomponent
> >> according to channels interpolated %% 128-number of interp.
> >> channels)
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.channel = {'all'};
> >>
> >> cfg.numcomponent = 128
> >>
> >> comp = ft_componentanalysis(cfg,obs_data_clean1);
> >>
> >> save (strcat(sb,'comp_all') , 'comp')
> >>
> >>
> >>
> >> %%
> >>
> >> cfg = [];
> >>
> >> cfg.viewmode = 'component';
> >>
> >> cfg.continuous = 'no';
> >>
> >> cfg.plotlabels='some';
> >>
> >> cfg.layout = 'GSN128.sfp';
> >>
> >> ft_databrowser(cfg,comp);
> >>
> >>
> >>
> >> %% poweranalysis components
> >>
> >> cfg = [];
> >>
> >> cfg.output = 'pow';
> >>
> >> cfg.channel = 'all';%compute the power spectrum in all ICs
> >>
> >> cfg.method = 'mtmfft';
> >>
> >> cfg.taper = 'hanning';
> >>
> >> cfg.foi = 0:0.2:50;
> >>
> >> obs_freq = ft_freqanalysis(cfg, comp);
> >>
> >>
> >>
> >> %And you can plot the spectra:
> >>
> >>
> >>
> >> %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
> >>
> >> nsubplots = 16;
> >>
> >> nbyn = sqrt(nsubplots);% sqrt(nsubplots) should not contain
> >> decimals, type doc subplot
> >>
> >>
> >>
> >> Nfigs = ceil(size(comp.topo,1)/nsubplots);
> >>
> >> tot = Nfigs*nsubplots;
> >>
> >>
> >>
> >> rptvect = 1:size(comp.topo,1);
> >>
> >> rptvect = padarray(rptvect, [0 tot-size(comp.topo,1)], 0,'post');
> >>
> >> rptvect = reshape(rptvect,nsubplots,Nfigs)';
> >>
> >>
> >>
> >> for r=1:size(rptvect,1);
> >>
> >>   figure;set(gcf,'units','normalized','outerposition',[0 0 1
> >> 1]);%full screen
> >>
> >>   k=0;
> >>
> >>   for j=1:size(rptvect,2);
> >>
> >>     if~(rptvect(r,j)==0);
> >>
> >>       k=k+1;
> >>
> >>       cfg=[];
> >>
> >>       cfg.channel = rptvect(r,j);
> >>
> >>       cfg.ylim =[0 500]
> >>
> >>       cfg.xlim =[0 50]
> >>
> >>       subplot(nbyn,nbyn,k);ft_singleplotER(cfg,obs_freq);
> >>
> >>     end
> >>
> >>   end
> >>
> >> end
> >>
> >>
> >>
> >> %For the IC topos you'll follow the same logic as above but with:
> >>
> >>
> >>
> >> figure
> >>
> >> cfg = [];
> >>
> >> cfg.component = [1:20]; % specify the component(s) that
> >> should be plotted
> >>
> >> cfg.layout = 'GSN128.sfp';
> >>
> >> cfg.comment = 'no';
> >>
> >> ft_topoplotIC(cfg, comp)
> >>
> >>
> >>
> >> figure
> >>
> >> cfg = [];
> >>
> >> cfg.component = [21:40]; % specify the component(s) that
> >> should be plotted
> >>
> >> cfg.layout = 'GSN128.sfp';
> >>
> >> cfg.comment = 'no';
> >>
> >> ft_topoplotIC(cfg, comp)
> >>
> >>
> >>
> >> figure
> >>
> >> cfg = [];
> >>
> >> cfg.component = [41:60]; % specify the component(s) that
> >> should be plotted
> >>
> >> cfg.layout = 'GSN128.sfp';
> >>
> >> cfg.comment = 'no';
> >>
> >> ft_topoplotIC(cfg, comp)
> >>
> >>
> >>
> >> figure
> >>
> >> cfg = [];
> >>
> >> cfg.component = [61:80]; % specify the component(s) that
> >> should be plotted
> >>
> >> cfg.layout = 'GSN128.sfp';
> >>
> >> cfg.comment = 'no';
> >>
> >> ft_topoplotIC(cfg, comp)
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >> %% Seperate observation conditions
> >>
> >>
> >>
> >> name1= strcat(num2str(sb),'_90.xls');
> >>
> >>     list1=xlsread (name1)
> >>
> >>
> >>
> >> name2= strcat(num2str(sb),'_180.xls');
> >>
> >>     list2=xlsread (name2)
> >>
> >>
> >> %
> >>
> >>
> >>
> >> cfg = []
> >>
> >> cfg.trials = [list1]
> >>
> >> obs90_data = ft_redefinetrial(cfg,obs_data_channelrepaired)
> >>
> >>
> >>
> >> cfg = []
> >>
> >> cfg.trials = [list2]
> >>
> >> obs180_data = ft_redefinetrial(cfg,obs_data_channelrepaired)
> >>
> >>
> >>
> >> %%PIPELINE FOR obs90
> >>
> >>
> >>
> >> %% Decompose original data according to the components found before
> >>
> >> load (strcat(sb,'comp_all'))
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.numcomponent = 128;
> >>
> >> cfg.unmixing = comp.unmixing;
> >>
> >> cfg.topolabel = comp.topolabel;
> >>
> >>
> >>
> >> comp_1 = ft_componentanalysis(cfg, obs90_data);
> >>
> >>
> >>
> >>
> >>
> >> %% Reject component
> >>
> >> cfg = [];
> >>
> >>     cfg.component = [];
> >>
> >>     obs90_data_ica_cleaned = ft_rejectcomponent(cfg, comp_1,
> >>     obs90_data);
> >>
> >>
> >>
> >>
> >>  save (strcat(sb,'obs90_ica_cleaned') , 'obs90_data_ica_cleaned')
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >> %% Artifacts - final detection
> >>
> >>
> >>
> >>
> >>
> >> cfg.method = 'summary';
> >>
> >> cfg.latency=[0 1];
> >>
> >> cfg.layout = 'GSN128.sfp'; % this allows for plotting
> >>
> >> obs90_data_clean3 = ft_rejectvisual(cfg, obs90_data_ica_cleaned);
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.viewmode = 'vertical';
> >>
> >> cfg.latency=[0 1];
> >>
> >> cfg.continuous = 'no';
> >>
> >> cfg.plotlabels='yes'
> >>
> >> cfg = ft_databrowser(cfg,obs90_data_clean3);
> >>
> >> %cfg.artfctdef.reject = 'complete';
> >>
> >> obs90_data_clean2 = ft_rejectartifact (cfg,obs90_data_clean3);
> >>
> >>
> >>
> >>
> >>
> >> % Save clean data
> >>
> >>
> >>
> >> save (strcat(subject,'obs90_clean') , 'obs90_data_clean2')
> >>
> >>
> >>
> >>
> >>
> >> %% Rereferencing data
> >>
> >> cfg = [];
> >>
> >>
> >>
> >> cfg.channel = 'all';
> >>
> >> cfg.preproc.reref = 'yes';
> >>
> >> cfg.preproc.refchannel = 'all';
> >>
> >> obs90_data_ref= ft_preprocessing(cfg,obs90_data_clean2)
> >>
> >>
> >>
> >> save (strcat(subject,'obs90_ref') , 'obs90_data_ref')
> >>
> >> %% Snap out smaller pieces (the third second)
> >>
> >>
> >>
> >> cfg = []
> >>
> >> cfg.toilim = [0 1]
> >>
> >>
> >>
> >> obs90_data_small = ft_redefinetrial(cfg,obs90_data_ref)
> >>
> >>
> >>
> >> %% TIMELOCK ERP
> >>
> >> obs90_data_ERP = ft_timelockanalysis(cfg, obs90_data_small);
> >>
> >>
> >>
> >> save (strcat(subject,'obs90_ERP') , 'obs90_data_ERP')
> >>
> >>
> >>
> >> %% plot it
> >>
> >> cfg = [];
> >>
> >> cfg.layout = lay ;
> >>
> >> cfg.interactive = 'yes';
> >>
> >> ft_multiplotER(cfg, obs90_data_ERP)
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >> %% PIPELINE FOR obs180
> >>
> >>
> >>
> >>
> >>
> >> %% Decompose original data according to the components found before
> >>
> >> load (strcat(sb,'comp_all'))
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.numcomponent = 128
> >>
> >> cfg.unmixing = comp.unmixing;
> >>
> >> cfg.topolabel = comp.topolabel;
> >>
> >> comp_2 = ft_componentanalysis(cfg, obs180_data);
> >>
> >>
> >>
> >>
> >>
> >> %% Reject component
> >>
> >> cfg = [];
> >>
> >>     cfg.component = [];
> >>
> >>     obs180_data_ica_cleaned = ft_rejectcomponent(cfg, comp_2,
> >>     obs180_data);
> >>
> >>
> >>
> >>
> >>  save (strcat(sb,'obs180_ica_cleaned') , 'obs180_data_ica_cleaned')
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >> %% Artifacts final 180
> >>
> >>
> >>
> >>
> >>
> >> cfg.method = 'summary';
> >>
> >> cfg.latency=[0 1];
> >>
> >> cfg.layout = 'GSN128.sfp'; % this allows for plotting
> >>
> >> obs180_data_clean3 = ft_rejectvisual(cfg, obs180_data_ica_cleaned);
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.viewmode = 'vertical';
> >>
> >> cfg.latency=[0 1];
> >>
> >> cfg.continuous = 'no';
> >>
> >> cfg.plotlabels='yes'
> >>
> >> cfg = ft_databrowser(cfg,obs180_data_clean3);
> >>
> >> %cfg.artfctdef.reject = 'complete';
> >>
> >> obs180_data_clean2 = ft_rejectartifact (cfg,obs180_data_clean3);
> >>
> >>
> >>
> >>
> >>
> >> % Save clean data
> >>
> >>
> >>
> >> save (strcat(subject,'obs180_clean') , 'obs180_data_clean2')
> >>
> >>
> >>
> >>
> >>
> >> %% Rereferencing data
> >>
> >> cfg = [];
> >>
> >> cfg.channel = 'all';
> >>
> >> cfg.preproc.reref = 'yes';
> >>
> >> cfg.preproc.refchannel = 'all';
> >>
> >> obs180_data_ref= ft_preprocessing(cfg,obs180_data_clean2)
> >>
> >>
> >>
> >> save (strcat(subject,'obs180_ref') , 'obs180_data_ref')
> >>
> >> %% Snap out smaller pieces (the third second)
> >>
> >>
> >>
> >> cfg = []
> >>
> >> cfg.toilim = [0 1]
> >>
> >>
> >>
> >> obs180_data_small = ft_redefinetrial(cfg,obs180_data_ref)
> >>
> >>
> >>
> >> %% TIMELOCK ERP
> >>
> >> obs180_data_ERP = ft_timelockanalysis(cfg, obs180_data_small);
> >>
> >>
> >>
> >> save (strcat(subject,'obs180_ERP') , 'obs180_data_ERP')
> >>
> >>
> >>
> >> %% plot 180 ERP
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.layout = lay ;
> >>
> >> cfg.interactive = 'yes';
> >>
> >> ft_multiplotER(cfg, obs180_data_ERP)
> >>
> >>
> >>
> >> %% plot both ERPs
> >>
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.layout = lay ;
> >>
> >> cfg.interactive = 'yes';
> >>
> >> cfg.showlabels = 'yes';
> >>
> >> ft_multiplotER(cfg, obs90_data_ERP, obs180_data_ERP)
> >>
> >>
> >>
> >> %% plot difference wave
> >>
> >>
> >>
> >> difference = obs180_data_ERP; % copy one of
> >> the structures
> >>
> >> difference.avg = obs180_data_ERP.avg - obs90_data_ERP.avg; %
> >> compute the difference ERP
> >>
> >>
> >> cfg = [];
> >>
> >> cfg.layout = lay;
> >>
> >> cfg.interactive = 'yes';
> >>
> >> ft_multiplotER(cfg, difference)
> >>
> >>
> >> 2014-09-07 7:53 GMT+02:00 Joseph Dien <jdien07 at mac.com>:
> >> Hi,
> >>    I?m one of the main Fieldtrip contributors working on supporting
> >>  EGI data. A couple things. First of all, exactly which net do
> >> you use? If they are 129-channel, there is still the question of
> >> whether they are the Hydrocel or the older geodesic nets.
> >> Regardless, that shouldn't cause an error like this. Could you
> >> send me the file you are trying to process and the script you are
> >> using and I?ll try troubleshooting it.
> >>
> >> Joe
> >>
> >>
> >> On Aug 26, 2014, at 12:53 AM, Ana Laura Diez Martini
> >> <diezmartini at gmail.com> wrote:
> >>
> >>> Which nets do you use? I use EGI. I tried both the ones you
> >>> mention and they didn't work. It was hard to find that exact one
> >>> online but it was the only file that actually worked.
> >>>
> >>>
> >>> On Mon, Aug 25, 2014 at 7:52 AM, KatrinH Heimann
> >>> <katrinheimann at gmail.com> wrote:
> >>> Dear Ana, dear all,
> >>> the layout you used does not correspond to our nets. I tried the
> >>>    GSN-HydroCel-128.sfp and the GSN-HydroCel-129.sfp. Both don't
> >>> work. Please can anybody help?
> >>> Cheers
> >>> Katrin
> >>>
> >>>
> >>> 2014-08-24 5:40 GMT+02:00 Ana Laura Diez Martini
> >>> <diezmartini at gmail.com>:
> >>>
> >>> Try this one I use
> >>>
> >>>
> >>> On Sun, Aug 24, 2014 at 4:08 AM, KatrinH Heimann
> >>> <katrinheimann at gmail.com> wrote:
> >>> Dear all, my problems seem neverending. This time however i really
> >>>  need help.
> >>> I implemented a pipeline for ERPs. All works now, trialdefinition,
> >>>  preprocessing, channelreplacement, ica, componentrejection, final
> >>>  artifactdetection, timelock of the single subject data. However,
> >>> when I wanna compute the grandaverage of the single subjects I get
> >>>  the following error message:
> >>>
> >>> computing average of avg over 19 subjects
> >>> Warning: discarding electrode information because it cannot be
> >>> averaged
> >>> > In ft_timelockgrandaverage at 249
> >>> the call to "ft_timelockgrandaverage" took 0 seconds and required
> >>> the additional allocation of an estimated 3 MB
> >>> computing average of avg over 2 subjects
> >>> Warning: discarding electrode information because it cannot be
> >>> averaged
> >>> > In ft_timelockgrandaverage at 249
> >>> the call to "ft_timelockgrandaverage" took 0 seconds and required
> >>> the additional allocation of an estimated 0 MB
> >>> the call to "ft_prepare_layout" took 0 seconds and required the
> >>> additional allocation of an estimated 0 MB
> >>> the call to "ft_topoplotER" took 0 seconds and required the
> >>> additional allocation of an estimated 0 MB
> >>>
> >>> Furthermore in the plot of the significant clusters, the
> >>> channelnames are mixed up (do not correspond to my net)
> >>>
> >>>
> >>> I guess that there is a problem with the layout I use.
> >>> Here the code that I use
> >>>
> >>> %For generating the layout (also in the single subjects):
> >>> cfg = [];
> >>>
> >>> cfg.channel = obs_data.label;
> >>>
> >>> cfg.layout = 'GSN-HydroCel-129.sfp';
> >>>
> >>> cfg.feedback = 'yes';
> >>>
> >>> lay = ft_prepare_layout(cfg);
> >>>
> >>>
> >>> cfg_neighb = [];
> >>>
> >>> cfg_neighb.feedback = 'yes';
> >>>
> >>> cfg_neighb.method = 'triangulation';
> >>>
> >>> cfg_neighb.layout = lay;
> >>>
> >>> neighbours = ft_prepare_neighbours(cfg_neighb, obs_data);
> >>>
> >>>
> >>> obs_data.elec = ft_read_sens('GSN-HydroCel-129.sfp');
> >>>
> >>>
> >>>
> >>> %For computing the grand average
> >>>
> >>> cfg = [];
> >>>
> >>> cfg.channel = 'all';
> >>>
> >>> cfg.latency = 'all';
> >>>
> >>> cfg.parameter = 'avg';
> >>>
> >>> cfg.keepindividual = 'no'
> >>>
> >>> GA_90 = ft_timelockgrandaverage(cfg,all90{:});
> >>>
> >>> GA_180 = ft_timelockgrandaverage(cfg,all180{:});
> >>>
> >>> % "{:}" means to use data from all elements of the variable
> >>>
> >>>
> >>> For plotting the significant clusters
> >>>
> >>> cfg = [];
> >>>
> >>> cfg.style = 'blank';
> >>>
> >>> cfg.layout = lay;
> >>>
> >>> cfg.channellabels = 'yes';
> >>>
> >>> cfg.highlight = 'labels';
> >>>
> >>> cfg.highlightchannel = find(stat.mask);
> >>>
> >>> cfg.comment = 'no';
> >>>
> >>> figure; ft_topoplotER(cfg, GA_90)
> >>>
> >>> title('Nonparametric: significant with cluster multiple comparison
> >>>  correction')
> >>>
> >>>
> >>>
> >>> Do you have ANY idea to this? I am really completely helpless....
> >>>
> >>> thanks and best
> >>>
> >>> Katrin
> >>>
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >>
----------------------------------------------------------------------------
----
> >>
> >> Joseph Dien, PhD
> >> Research Associate
> >> Cognitive Neurology
> >> The Johns Hopkins University School of Medicine
> >>
> >> Lab E-mail: jdien1 at jhmi.edu
> >> Private E-mail: jdien07 at mac.com
> >> Office Phone: 410-614-3115
> >> Cell Phone: 202-297-8117
> >> Fax: 410-955-0188
> >> http://joedien.com
> >>
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> >
----------------------------------------------------------------------------
----
> >
> > Joseph Dien, PhD
> > Research Associate
> > Cognitive Neurology
> > The Johns Hopkins University School of Medicine
> >
> > Lab E-mail: jdien1 at jhmi.edu
> > Private E-mail: jdien07 at mac.com
> > Office Phone: 410-614-3115
> > Cell Phone: 202-297-8117
> > Fax: 410-955-0188
> > http://joedien.com
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL:
> >
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> >
> > ------------------------------
> >
> > Message: 4
> > Date: Tue, 9 Sep 2014 06:37:13 +0000
> > From: "Caspar, Emilie" <e.caspar at ucl.ac.uk>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] ft_rejectvisual: removing trials marked as
> > 	bad
> > Message-ID: <3C365782-4B07-4EFE-A921-99489BDD5DA6 at live.ucl.ac.uk>
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Hi Ashley,
> >
> > Maybe the mistake is you did not integrate in your script the
> > command to save the rejection. Normally, with the following command,
> >  you will see in the Matlab Window that artifacts are correctly
> > rejected after the "quit" button.
> >
> > clean_data = ft_rejectvisual(cfg, interpoldata);
> > cfg.artfctdef.reject = 'complete';
> > cfg.artfctdef.feedback = 'yes';
> > cleandata = ft_rejectartifact(cfg,clean_data);
> >
> > Emilie
> >
> >
> >
> >
> >
> > Le 3 sept. 2014 ? 11:58, Ashley Greene
> > <agreene24 at gmail.com<mailto:agreene24 at gmail.com>> a ?crit :
> >
> > Hello,
> >
> > I have used the rejectvisual function in attempt to remove bad
> > trials, but after marking them and pressing the quit button,
> > although the command window states that the selected trials have
> > been removed, there is no obvious change in the data; all of the
> > trials are still intact. Have I overlooked something?
> >
> > Thanks,
> >
> > Ashley
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
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> >
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985/attachment-0001.html>
> >
> > ------------------------------
> >
> > Message: 5
> > Date: Tue, 09 Sep 2014 14:16:20 +0200
> > From: Patricia Wollstadt <Patricia.Wollstadt at gmx.de>
> > To: fieldtrip at science.ru.nl
> > Subject: Re: [FieldTrip] TRENTOOL pipeline help
> > Message-ID: <540EEF94.9080601 at gmx.de>
> > Content-Type: text/plain; charset="windows-1252"
> >
> > Hello Max,
> >
> > I added a few comments to the questions regarding individual
> > parameters
> > below. To address the general problem of TRENTOOL telling you, that
> > there are not enough sample points in your data: From what I can see
> > in
> > your script, you probably don't have enough data points in each time
> > series to robustly estimate TE. You analyze 800 ms of data sampled
> > at
> > 300 Hz, which gives you 240 samples per time series. Can you maybe
> > avoid
> > downsampling to 300 Hz and downsample to 600 Hz instead? Or could
> > you
> > analyze a longer time window of interest?
> > Note that you also 'lose' data to embedding and the interaction
> > delay:
> > The first point that can be used for TE estimation is at max.
> > embedding
> > length + max. interaction delay in samples. For example: max.
> > embedding
> > length = dim * tau_factor * ACT = 10 * 0.4 * 5 = 20 samples plus the
> > max
> > interaction delay of 30 ms = 9 samples. In this example, you would
> > be
> > left with 240 - 29 samples for TE estimation per trial. There is
> > also
> > the possibility to estimate time resolved TE/TE for shorter time
> > windows
> > of interest (see section 4.4 in the manual); however, this method
> > requires the use of a GPU for TE estimation.
> >
> > I would further recommend to use the new pipeline for group
> > statistics
> > described in the manual in section 4.5 (the function
> > 'TEgroup_calculate'
> > is deprecated). The new pipeline allows you to reconstruct the
> > interaction delay and uses the following functions (see also
> > comments in
> > the script):
> >
> > TEgroup_prepare -> prepares all data sets (all subjects/all
> > conditions) for group analysis (this means finding common embedding
> > parameters such that estimates are not biased between groups)
> > InteractionDelayReconstruction_calculate -> estimates TE for
> > individual data sets and all assumed interaction delays u
> > InteractionDelayReconstruction_analyze -> reconstructs the
> > interaction delay by selecting the u that maximizes TE for each
> > channel
> > TEgroup_stats -> calculate group statistics using a permutation test
> >
> > I can send you an example script for group TE analysis using this
> > pipeline to get you started. I hope this helps you to get the group
> > analysis running. Just write again if you're having trouble setting
> > up
> > the pipeline or something is not clear about the parameters/my
> > comments.
> >
> > Best,
> > Patricia
> >
> >
> >
> >
> > On 09/04/2014 08:30 PM, Max Cantor wrote:
> >> Hi fieldtrippers,
> >>
> >> I know trentool is not produced by the Donders Institute, so I'm
> >> not
> >> 100% sure if it is appropriate to ask questions about it here, but
> >> to
> >> the best of my knowledge they do not have a mailing list and I saw
> >> a
> >> few trentool questions in the archives, so I'm going to assume it's
> >> ok...
> >>
> >> In any case, below is my current pipeline (slightly modified for
> >> comprehensibility):
> >>
> >> (notes in bold are comments/questions made in this email, not
> >> present
> >> in the pipeline. Sorry in advance for the long post! Any help would
> >> be
> >> greatly appreciated as I'm a bit over my head on this but I think
> >> I'm
> >> close!)
> >>
> >> *****
> >>
> >> % Prepare group TE data
> >>
> >> cfgP = [];
> >> cfgP.Path2TSTOOL = *TSTOOLPATH*
> >> cfgP.TEcalctype = 'VW_ds';
> >> cfgP.channel = {'ctfdip_LAC' 'ctfdip_RAC'};
> >>
> >> *I'm trying to find the transfer entropy between the left and right
> >> auditory cortices in my experiment. The input is virtual sensor
> >> data
> >> that was produced using SAM in fieldtrip on real MEG data. *
> >>
> >> % specify u to be scanned
> >>
> >> cfgP.predicttime_u = 30;
> >> cfgP.toi = [-0.4 0.4];
> >>
> >> *For clarification, the predicttime_u is in seconds but the toi is
> >> in
> >> milliseconds. If I understand correctly, the predicttime_u must fit
> >> within the toi, but beyond that are there any benefits to it being
> >> earlier or later?* PW: The predictiontime_u is in milliseconds and
> >> the
> >> toi is in seconds. The prediction time is the assumed interaction
> >> delay between your two sources and should fit within your toi. In
> >> general it is preferable to use the method for interaction delay
> >> reconstruction for TE estimation, because it allows you to
> >> reconstruct
> >> the actual delay between your source and target times series. A
> >> non-optimal u/interaction delay may cause an underestimation of TE,
> >> so
> >> it is recommended to use the pipeline for interaction delay
> >> reconstruction whenever estimating TE for unknown delays.
> >> If you use the methods for interaction delay reconstruction
> >> 'predicttime_u' is replaced by
> >> cfgTEP.predicttimemin_u % minimum u to be scanned
> >> cfgTEP.predicttimemax_u % maximum u to be scanned
> >> cfgTEP.predicttimestepsize % time steps between u to be scanned
> >> A large range for u values to be scanned increases computing time a
> >> lot, so it is best to limit the u range to values that are
> >> physiologically plausible.
> >>
> >> % ACT (Autocorrelation Time) estimation and constraints
> >>
> >> cfgP.maxlag = 150;
> >> cfgP.actthrvalue = 7.5;
> >> cfgP.minnrtrials = 5;
> >>
> >> *My understanding is maxlag should be 1/2 the sampling rate, so
> >> since
> >> the data are downsampled to 300hz, it should be 150. I know that
> >> the
> >> sample rate and filters are used to determine the actthrvalue, but
> >> I
> >> don't actually know the calculation. 7.5 was a rough guess just to
> >> test the pipeline. I'm also uncertain of what minnrtrials should
> >> be.*
> >> PW: You can set the actthrvalue based on the filtering you did
> >> prior
> >> to TE analysis. If you for example highpass filtered at 10 Hz, you
> >> shouldn't find an ACT higher than 30 samples, because you filtered
> >> out
> >> any components of the signal slower than 10 Hz/30 samples (given
> >> your
> >> sampling frequency of 300 Hz). So in this scenario the actthrvalue
> >> would be 30.
> >> A good value for cfgP.minnrtrials is 12 (a minimum number of trials
> >> is
> >> needed to realize the permutation test for estimated TE values).
> >>
> >> % Optimization
> >>
> >> cfgP.optimizemethod = 'ragwitz';
> >> cfgP.ragdim = 4:8;
> >> cfgP.ragtaurange = [0.2 0.4];
> >> cfgP.ragtausteps = 15;
> >> cfgP.repPred = 100;
> >> *
> >> *
> >> *I am completely at a loss for this. I've done some reading into
> >> transfer entropy, mutual information, etc., cited in trentool, but
> >> I'm
> >> yet to understand how exactly this optimization works and what the
> >> configuration should be, given my data and experimental
> >> intentions.*
> >> PW: The Ragwitz criterion tries to find optimal embedding
> >> parameters
> >> dim and tau for the data. To do that, the method iteratively takes
> >> all
> >> possible combinations of dim and tau values that are provided in
> >> cfgP.ragdim and cfgP.ragtaurange/.ragtausteps and tests how well
> >> these
> >> combinations embed the data. To test an embedding, the method
> >> builds
> >> the embedding vectors from the data; it then tests for each point
> >> how
> >> well the next point in time can be predicted from the reference
> >> point's nearest neighbours. So for each embedded point, the method
> >> searches for the nearest neighbours and calculates the average of
> >> those nearest neighbours. The difference between the
> >> averaged/predicted point and the actual next point is the error of
> >> the
> >> local predictor. The Ragwitz criterion will then return the
> >> parameter
> >> combination for which this error over all points is minimal.
> >> The parameters set the following: 'ragdim' are dimensions to be
> >> tested
> >> by the method (I would reccomend to start with 2:10), 'ragtaurange'
> >> together with 'ragtausteps' specifies the tau values to be tested
> >> (TRENTOOL will build a vector from 0.2 to 0.4 in 15 steps). Note,
> >> that
> >> the values here are factors that are later multiplied with the ACT
> >> to
> >> obtain the actual tau. 'repPred' is the number of points that will
> >> be
> >> used for the local prediction, i.e. the Ragwitz criterion will test
> >> the local prediction and calculate the error for the first 100
> >> points
> >> in your time series. The two parameters 'flagNei' ans 'sizeNei'
> >> below
> >> specify the type of neighbour search conducted by the Ragwitz
> >> criterion: 'flagNei' tells the method to either conduct a kNN or
> >> range
> >> search; 'sizeNei' specifies the number of neighbours or the radius
> >> to
> >> be searched by a range search.
> >>
> >>
> >> % Kernel-based TE estimation
> >>
> >> cfgP.flagNei = 'Mass';
> >> cfgP.sizeNei = 4; % Default
> >>
> >> cfgP.ensemblemethod = 'no';
> >> cfgP.outputpath = *OUTPUT PATH*;
> >>
> >> if ~exist(*Path for TEprepare data object*)
> >>     load VSdat;
> >>     TE_Wrd = {};
> >>     for i = 1:nConds
> >>         for j = 1:Nsub
> >>             TE_Wrd{i}{j} = TEprepare(cfgP, VSdat{i}{j});
> >>         end
> >>     end
> >>     clear VSdat;
> >>     save('TE_Wrd', 'TE_Wrd');
> >> end
> >> *
> >> *
> >> *The configuration and virtual sensor data, organized in a 3 x 15
> >> cell
> >> of structures (condition by subject) are the input. The TEprepare
> >> substructure is added to each individual condition x subject .mat
> >> files' data structure which are stored on disk independently.*
> >>
> >> % Use object_to_mat_conversion.m to replace individual condition x
> >> subject virtual sensor data
> >> % .mat files with their TE_Wrd equivalent
> >> *
> >> *
> >> *I'm using a separate script to make some manipulations to the
> >> objects
> >> from disk; this will all eventually be integrated into the main
> >> pipeline*.*TRENTOOL seems to handle data output very differently
> >> from
> >> fieldtrip and I've had trouble thinking through the most logical
> >> way
> >> to handle the data so it's a bit haphazard right now.*
> >>
> >> load cond080sub01.mat
> >>
> >> cfgG = [];
> >> cfgG.dim = cond080sub01.TEprepare.optdim;
> >> cfgG.tau = cond080sub01.TEprepare.opttau;
> >>
> >> if isfield(cond080sub01, 'TEprepare')
> >>                               TEgroup_prepare(cfgG, fileCell);
> >> else
> >>     error('Need to run TEprepare before TEgroup_prepare');
> >> end
> >> *
> >> *
> >> *For clarification, fileCell is a cell with the name of each
> >> condition
> >> x subject .mat file, which as I said before is collectively the
> >> same
> >> as the 3 x 15 VSdat structure (condition x subject).*
> >>
> >> % Replace .mat files with '_for_TEgroup_calculate' version in
> >> % object_to_mat_conversion.m
> >>
> >> % TE Group Calculate
> >>
> >> load cond080sub01.mat
> >> if isfield(cond080sub01, 'TEgroupprepare')
> >>     for i = 1:length(fileCell)
> >>                               TEgroup_calculate(fileCell{i});
> >>     end
> >> else
> >>     error('Need to run TEgroup_prepare before TEgroup_calculate');
> >> end
> >> *
> >> *
> >> *At this step I get the following error:
> >>
> >> Error using transferentropy (line 337)
> >> \nTRENTOOL ERROR: not enough data points left after embedding
> >>
> >> Error in TEgroup_calculate (line 133)
> >> [TEresult] = transferentropy(cfg,data);*
> >>
> >> % TE Group Stats
> >>
> >> cfgGSTAT = [];
> >> cfgGSTAT.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)];
> >> cfgGSTAT.design(2,1:2*Nsub) = [1:Nsub 1:Nsub];
> >>
> >> cfgGSTAT.uvar = 1;
> >> cfgGSTAT.ivar = 2;
> >> cfgGSTAT.fileidout = 'test_groupstats';
> >>
> >>                               TEgroup_stats(cfgGSTAT, fileCell);
> >>
> >> *Given the error above, I am yet to get to this step, but it does
> >> not
> >> seem fundamentally different from normal fieldtrip stats.*
> >>
> >> *****
> >>
> >> In case my notes were not clear or you skipped to the bottom, *my
> >> primary concern is whether the error I'm getting in
> >> TEgroup_calculate
> >> is a pipeline issue* (I noticed the example pipeline in trentool,
> >> the
> >> manual, and published methods articles all seem to have slightly or
> >> significantly different pipeline compositions), *or if the error
> >> is*
> >> due to ACT, ragwitz optimization, or some other faulty
> >> parameterization *on my part due to a lack of understanding of how
> >> transfer entropy works on a more theoretical/mathematical level*.
> >> If
> >> the latter is the case, is there any relatively straightforward way
> >> to
> >> conceptualize this, or is this something where I'm just going to
> >> have
> >> to keep reading and rereading until it eventually makes sense? I've
> >> already done quite a bit of that and it hasn't pierced my thick
> >> skull
> >> yet but I'm sure it will eventually!
> >>
> >> Thank you so much,
> >>
> >> Max Cantor
> >>
> >>
> >> --
> >> Max Cantor
> >> Lab Manager
> >> Computational Neurolinguistics Lab
> >> University of Michigan
> >>
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > --
> > ------------------------------------------------------------
> >
> > Patricia Wollstadt, PhD Student
> >
> > MEG Unit, Brain Imaging Center
> >
> > Goethe University, Frankfurt, Germany
> >
> > Heinrich Hoffmann Strasse 10, Haus 93 B
> >
> > D - 60528 Frankfurt am Main
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL:
> >
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> >
> > ------------------------------
> >
> > Message: 6
> > Date: Tue, 9 Sep 2014 15:21:20 +0200
> > From: Holger Krause <Holger.Krause at med.uni-duesseldorf.de>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: [FieldTrip] Latest FT version on ftp-server is from three
> > 	days ago
> > Message-ID:
> > <201409091521.22589.Holger.Krause at med.uni-duesseldorf.de>
> > Content-Type: text/plain; charset="us-ascii"
> >
> > Dear developers,
> >
> > Could you please check the process for creation/publication of
> > zip-files on
> > the FTP server? The latest file I can find there is
> > fieldtrip-20140906.zip.
> >
> > Thanks in advance,
> >
> > Holger
> >
> >
> > ------------------------------
> >
> > Message: 7
> > Date: Tue, 9 Sep 2014 09:19:55 -0400
> > From: Max Cantor <mcantor at umich.edu>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] TRENTOOL pipeline help
> > Message-ID:
> > 	<CAFTjRaUXzwca7rR3sm8iPLLyUxqHO9kkm++=zAU4LUW=r7NRBw at mail.gmail.com>
> > Content-Type: text/plain; charset="utf-8"
> >
> > This is immensely helpful, thank you. I was very confused about why
> > some
> > versions of the pipeline I saw were using group calculate and others
> > were
> > using interaction delay reconstruction and what that meant, and I
> > think I
> > have a more clear idea of what the different steps of the pipeline
> > are
> > doing. There are still a few things I'm a bit confused about though
> > in
> > terms of the pipeline. For instance, whether or not I need to do
> > TEprepare
> > before group prepare, and if I need to do graph analysis (which I'm
> > not
> > sure I fully understand but also haven't looked deeply into) before
> > group
> > stats.
> >
> > If you don't mind me taking you up on your offer, I think seeing
> > your
> > example script might help clarify some of these issues.
> >
> > Thank you!
> >
> > On Tue, Sep 9, 2014 at 8:16 AM, Patricia Wollstadt <
> > Patricia.Wollstadt at gmx.de> wrote:
> >
> >>  Hello Max,
> >>
> >> I added a few comments to the questions regarding individual
> >> parameters
> >> below. To address the general problem of TRENTOOL telling you, that
> >> there
> >> are not enough sample points in your data: From what I can see in
> >> your
> >> script, you probably don't have enough data points in each time
> >> series to
> >> robustly estimate TE. You analyze 800 ms of data sampled at 300 Hz,
> >> which
> >> gives you 240 samples per time series. Can you maybe avoid
> >> downsampling to
> >> 300 Hz and downsample to 600 Hz instead? Or could you analyze a
> >> longer time
> >> window of interest?
> >> Note that you also 'lose' data to embedding and the interaction
> >> delay: The
> >> first point that can be used for TE estimation is at max. embedding
> >> length
> >> + max. interaction delay in samples. For example: max. embedding
> >> length =
> >> dim * tau_factor * ACT = 10 * 0.4 * 5 = 20 samples plus the max
> >> interaction
> >> delay of 30 ms = 9 samples. In this example, you would be left with
> >> 240 -
> >> 29 samples for TE estimation per trial. There is also the
> >> possibility to
> >> estimate time resolved TE/TE for shorter time windows of interest
> >> (see
> >> section 4.4 in the manual); however, this method requires the use
> >> of a GPU
> >> for TE estimation.
> >>
> >> I would further recommend to use the new pipeline for group
> >> statistics
> >> described in the manual in section 4.5 (the function
> >> 'TEgroup_calculate' is
> >> deprecated). The new pipeline allows you to reconstruct the
> >> interaction
> >> delay and uses the following functions (see also comments in the
> >> script):
> >>
> >> TEgroup_prepare -> prepares all data sets (all subjects/all
> >> conditions)
> >> for group analysis (this means finding common embedding parameters
> >> such
> >> that estimates are not biased between groups)
> >> InteractionDelayReconstruction_calculate -> estimates TE for
> >> individual data sets and all assumed interaction delays u
> >> InteractionDelayReconstruction_analyze -> reconstructs the
> >> interaction delay by selecting the u that maximizes TE for each
> >> channel
> >> TEgroup_stats -> calculate group statistics using a permutation
> >> test
> >>
> >> I can send you an example script for group TE analysis using this
> >> pipeline
> >> to get you started. I hope this helps you to get the group analysis
> >> running. Just write again if you're having trouble setting up the
> >> pipeline
> >> or something is not clear about the parameters/my comments.
> >>
> >> Best,
> >> Patricia
> >>
> >>
> >>
> >>
> >> On 09/04/2014 08:30 PM, Max Cantor wrote:
> >>
> >>   Hi fieldtrippers,
> >>
> >>  I know trentool is not produced by the Donders Institute, so I'm
> >>  not 100%
> >> sure if it is appropriate to ask questions about it here, but to
> >> the best
> >> of my knowledge they do not have a mailing list and I saw a few
> >> trentool
> >> questions in the archives, so I'm going to assume it's ok...
> >>
> >>  In any case, below is my current pipeline (slightly modified for
> >> comprehensibility):
> >>
> >>  (notes in bold are comments/questions made in this email, not
> >>  present in
> >> the pipeline. Sorry in advance for the long post! Any help would be
> >> greatly
> >> appreciated as I'm a bit over my head on this but I think I'm
> >> close!)
> >>
> >> *****
> >>
> >> % Prepare group TE data
> >>
> >> cfgP = [];
> >> cfgP.Path2TSTOOL = *TSTOOLPATH*
> >> cfgP.TEcalctype = 'VW_ds';
> >> cfgP.channel = {'ctfdip_LAC' 'ctfdip_RAC'};
> >>
> >> *I'm trying to find the transfer entropy between the left and right
> >> auditory cortices in my experiment. The input is virtual sensor
> >> data that
> >> was produced using SAM in fieldtrip on real MEG data. *
> >>
> >> % specify u to be scanned
> >>
> >> cfgP.predicttime_u = 30;
> >> cfgP.toi = [-0.4 0.4];
> >>
> >>    *For clarification, the predicttime_u is in seconds but the toi
> >>    is in
> >> milliseconds. If I understand correctly, the predicttime_u must fit
> >> within
> >> the toi, but beyond that are there any benefits to it being earlier
> >> or
> >> later?* PW: The predictiontime_u is in milliseconds and the toi is
> >> in
> >> seconds. The prediction time is the assumed interaction delay
> >> between your
> >> two sources and should fit within your toi. In general it is
> >> preferable to
> >> use the method for interaction delay reconstruction for TE
> >> estimation,
> >> because it allows you to reconstruct the actual delay between your
> >> source
> >> and target times series. A non-optimal u/interaction delay may
> >> cause an
> >> underestimation of TE, so it is recommended to use the pipeline for
> >> interaction delay reconstruction whenever estimating TE for unknown
> >> delays.
> >> If you use the methods for interaction delay reconstruction
> >> 'predicttime_u' is replaced by
> >> cfgTEP.predicttimemin_u % minimum u to be scanned
> >> cfgTEP.predicttimemax_u % maximum u to be scanned
> >> cfgTEP.predicttimestepsize % time steps between u to be scanned
> >> A large range for u values to be scanned increases computing time a
> >> lot,
> >> so it is best to limit the u range to values that are
> >> physiologically
> >> plausible.
> >>
> >>
> >>  % ACT (Autocorrelation Time) estimation and constraints
> >>
> >> cfgP.maxlag = 150;
> >> cfgP.actthrvalue = 7.5;
> >> cfgP.minnrtrials = 5;
> >>
> >>  *My understanding is maxlag should be 1/2 the sampling rate, so
> >>  since
> >> the data are downsampled to 300hz, it should be 150. I know that
> >> the sample
> >> rate and filters are used to determine the actthrvalue, but I don't
> >> actually know the calculation. 7.5 was a rough guess just to test
> >> the
> >> pipeline. I'm also uncertain of what minnrtrials should be.* PW:
> >> You can
> >> set the actthrvalue based on the filtering you did prior to TE
> >> analysis. If
> >> you for example highpass filtered at 10 Hz, you shouldn't find an
> >> ACT
> >> higher than 30 samples, because you filtered out any components of
> >> the
> >> signal slower than 10 Hz/30 samples (given your sampling frequency
> >> of 300
> >> Hz). So in this scenario the actthrvalue would be 30.
> >> A good value for cfgP.minnrtrials is 12 (a minimum number of trials
> >> is
> >> needed to realize the permutation test for estimated TE values).
> >>
> >>
> >> % Optimization
> >>
> >> cfgP.optimizemethod = 'ragwitz';
> >> cfgP.ragdim = 4:8;
> >> cfgP.ragtaurange = [0.2 0.4];
> >> cfgP.ragtausteps = 15;
> >> cfgP.repPred = 100;
> >>
> >>  *I am completely at a loss for this. I've done some reading into
> >> transfer entropy, mutual information, etc., cited in trentool, but
> >> I'm yet
> >> to understand how exactly this optimization works and what the
> >> configuration should be, given my data and experimental
> >> intentions.* PW:
> >> The Ragwitz criterion tries to find optimal embedding parameters
> >> dim and
> >> tau for the data. To do that, the method iteratively takes all
> >> possible
> >> combinations of dim and tau values that are provided in cfgP.ragdim
> >> and
> >> cfgP.ragtaurange/.ragtausteps and tests how well these combinations
> >> embed
> >> the data. To test an embedding, the method builds the embedding
> >> vectors
> >> from the data; it then tests for each point how well the next point
> >> in time
> >> can be predicted from the reference point's nearest neighbours. So
> >> for each
> >> embedded point, the method searches for the nearest neighbours and
> >> calculates the average of those nearest neighbours. The difference
> >> between
> >> the averaged/predicted point and the actual next point is the error
> >> of the
> >> local predictor. The Ragwitz criterion will then return the
> >> parameter
> >> combination for which this error over all points is minimal.
> >> The parameters set the following: 'ragdim' are dimensions to be
> >> tested by
> >> the method (I would reccomend to start with 2:10), 'ragtaurange'
> >> together
> >> with 'ragtausteps' specifies the tau values to be tested (TRENTOOL
> >> will
> >> build a vector from 0.2 to 0.4 in 15 steps). Note, that the values
> >> here are
> >> factors that are later multiplied with the ACT to obtain the actual
> >> tau.
> >> 'repPred' is the number of points that will be used for the local
> >> prediction, i.e. the Ragwitz criterion will test the local
> >> prediction and
> >> calculate the error for the first 100 points in your time series.
> >> The two
> >> parameters 'flagNei' ans 'sizeNei' below specify the type of
> >> neighbour
> >> search conducted by the Ragwitz criterion: 'flagNei' tells the
> >> method to
> >> either conduct a kNN or range search; 'sizeNei' specifies the
> >> number of
> >> neighbours or the radius to be searched by a range search.
> >>
> >>
> >> % Kernel-based TE estimation
> >>
> >> cfgP.flagNei = 'Mass';
> >> cfgP.sizeNei = 4; % Default
> >>
> >> cfgP.ensemblemethod = 'no';
> >> cfgP.outputpath = *OUTPUT PATH*;
> >>
> >> if ~exist(*Path for TEprepare data object*)
> >>     load VSdat;
> >>     TE_Wrd = {};
> >>     for i = 1:nConds
> >>         for j = 1:Nsub
> >>             TE_Wrd{i}{j} = TEprepare(cfgP, VSdat{i}{j});
> >>         end
> >>     end
> >>     clear VSdat;
> >>     save('TE_Wrd', 'TE_Wrd');
> >> end
> >>
> >>  *The configuration and virtual sensor data, organized in a 3 x 15
> >>  cell
> >> of structures (condition by subject) are the input. The TEprepare
> >> substructure is added to each individual condition x subject .mat
> >> files'
> >> data structure which are stored on disk independently.*
> >>
> >> % Use object_to_mat_conversion.m to replace individual condition x
> >> subject
> >> virtual sensor data
> >> % .mat files with their TE_Wrd equivalent
> >>
> >>  *I'm using a separate script to make some manipulations to the
> >>  objects
> >> from disk; this will all eventually be integrated into the main
> >> pipeline*.*
> >> TRENTOOL seems to handle data output very differently from
> >> fieldtrip and
> >> I've had trouble thinking through the most logical way to handle
> >> the data
> >> so it's a bit haphazard right now.*
> >>
> >> load cond080sub01.mat
> >>
> >> cfgG = [];
> >> cfgG.dim = cond080sub01.TEprepare.optdim;
> >> cfgG.tau = cond080sub01.TEprepare.opttau;
> >>
> >> if isfield(cond080sub01, 'TEprepare')
> >>                               TEgroup_prepare(cfgG, fileCell);
> >> else
> >>     error('Need to run TEprepare before TEgroup_prepare');
> >> end
> >>
> >>  *For clarification, fileCell is a cell with the name of each
> >>  condition x
> >> subject .mat file, which as I said before is collectively the same
> >> as the 3
> >> x 15 VSdat structure (condition x subject).*
> >>
> >> % Replace .mat files with '_for_TEgroup_calculate' version in
> >> % object_to_mat_conversion.m
> >>
> >> % TE Group Calculate
> >>
> >> load cond080sub01.mat
> >> if isfield(cond080sub01, 'TEgroupprepare')
> >>     for i = 1:length(fileCell)
> >>                               TEgroup_calculate(fileCell{i});
> >>     end
> >> else
> >>     error('Need to run TEgroup_prepare before TEgroup_calculate');
> >> end
> >>
> >>
> >>
> >>
> >>
> >>
> >>
> >> *At this step I get the following error: Error using
> >> transferentropy (line
> >> 337) \nTRENTOOL ERROR: not enough data points left after embedding
> >> Error in
> >> TEgroup_calculate (line 133) [TEresult] =
> >> transferentropy(cfg,data);*
> >>
> >> % TE Group Stats
> >>
> >> cfgGSTAT = [];
> >> cfgGSTAT.design(1,1:2*Nsub) = [ones(1,Nsub) 2*ones(1,Nsub)];
> >> cfgGSTAT.design(2,1:2*Nsub) = [1:Nsub 1:Nsub];
> >>
> >> cfgGSTAT.uvar = 1;
> >> cfgGSTAT.ivar = 2;
> >> cfgGSTAT.fileidout = 'test_groupstats';
> >>
> >>                               TEgroup_stats(cfgGSTAT, fileCell);
> >>
> >>  *Given the error above, I am yet to get to this step, but it does
> >>  not
> >> seem fundamentally different from normal fieldtrip stats.*
> >>
> >> *****
> >>
> >>  In case my notes were not clear or you skipped to the bottom, *my
> >> primary concern is whether the error I'm getting in
> >> TEgroup_calculate is a
> >> pipeline issue* (I noticed the example pipeline in trentool, the
> >> manual,
> >> and published methods articles all seem to have slightly or
> >> significantly
> >> different pipeline compositions), *or if the error is* due to ACT,
> >> ragwitz optimization, or some other faulty parameterization *on my
> >> part
> >> due to a lack of understanding of how transfer entropy works on a
> >> more
> >> theoretical/mathematical level*. If the latter is the case, is
> >> there any
> >> relatively straightforward way to conceptualize this, or is this
> >> something
> >> where I'm just going to have to keep reading and rereading until it
> >> eventually makes sense? I've already done quite a bit of that and
> >> it hasn't
> >> pierced my thick skull yet but I'm sure it will eventually!
> >>
> >>  Thank you so much,
> >>
> >>  Max Cantor
> >>
> >>
> >> --
> >> Max Cantor
> >> Lab Manager
> >> Computational Neurolinguistics Lab
> >> University of Michigan
> >>
> >>
> >> _______________________________________________
> >> fieldtrip mailing
> >>
listfieldtrip at donders.ru.nlhttp://mailman.science.ru.nl/mailman/listinfo/fie
ldtrip
> >>
> >>
> >> --
> >> ------------------------------------------------------------
> >>
> >>  Patricia Wollstadt, PhD Student
> >>
> >>   MEG Unit, Brain Imaging Center Goethe University, Frankfurt,
> >>   Germany
> >>
> >>  Heinrich Hoffmann Strasse 10, Haus 93 B D - 60528 Frankfurt am
> >>  Main
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >
> >
> >
> > --
> > Max Cantor
> > Lab Manager
> > Computational Neurolinguistics Lab
> > University of Michigan
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> > ------------------------------
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > End of fieldtrip Digest, Vol 46, Issue 3
> > ****************************************
> >
> 
> 
> 
> Barbara Schorr, MSc
> Clinical and Biological Psychology
> University of Ulm
> Albert-Einstein-Allee 47
> 89069 Ulm
> 
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Jim Herring, MSc.
Neuronal Oscillations Group
Centre for Cognitive Neuroimaging
Donders Institute for Brain, Cognition and Behaviour
Radboud University Nijmegen
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