[FieldTrip] Problem with ft_timelockstatistics, within subject comparison of two conditions (Clara A. Scholl)
barbara.schorr at uni-ulm.de
barbara.schorr at uni-ulm.de
Wed Oct 8 13:31:46 CEST 2014
Dear Clara,
thank you for your comments.
I ran it as an independent samples Test (it is true, that this is the
correct way).
I also changed the design matrix to
cfg.design = [ones(1,size(targetclean_tlt.trial,1))
2*ones(1,size(standardclean_tlt.trial,1))]
It works and there are no more error messages. However, when it
displays the progress of the calculation there is the field: total
number of observations, total number of variables and number of
independent variables. It recognizes correctly that there are 185
trials in total (both conditions together). But it only counts 1
variable and 1 independent variable. Shouldn't it recognize 2
variables as I have 2 conditions?
Best regards,
Barbara
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> 1. Problem with ft_timelockstatistics, within subject comparison
> of two conditions (barbara.schorr at uni-ulm.de)
> 2. Re: Problem with ft_timelockstatistics, within subject
> comparison of two conditions (Clara A. Scholl)
> 3. Re: help for statistics on ERD/ERS (Tzvetan Popov)
> 4. Re: help for statistics on ERD/ERS (Giuly)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 07 Oct 2014 15:42:53 +0200
> From: barbara.schorr at uni-ulm.de
> To: fieldtrip at science.ru.nl
> Subject: [FieldTrip] Problem with ft_timelockstatistics, within
> subject comparison of two conditions
> Message-ID: <20141007154253.1acx2qfvso4k4so4 at imap.uni-ulm.de>
> Content-Type: text/plain; charset=ISO-8859-1; DelSp="Yes";
> format="flowed"
>
> Dear fieldtripers,
>
> I would like to compare to conditions of an auditory oddball paradigm
> (target tones and standard tones).
> For the identification of the electrodes which show the biggest P300,
> I would like to use cluster based permutation test, i.e. I want to use
> ft_timelockstatistics, to identify the clusters with a significant
> difference between the target and the standardtones.
> Important: I don't want to do a group statistic, but I want to compare
> these two conditions within each subject, to identify interesting
> clusters for each subject separately.
>
>
> I wrote the script following the tutorials on the fieldtrip homepage.
>
> I already wrote a code but it does not work:
> %%
>
> for i = 3:10 % subject number
> mypfad = 'G:\BackUp07.07.14_DatenPrepr\Daten1\P300'
> cd(mypfad)
> cd Kontrollen;
> List = dir
> cd (List(i).name);
> for j = 1:4 %session number
> cd (mypfad);
> cd Kontrollen;
> List = dir
> cd (List(i).name);
> eval(['cd M' num2str(j)]);
> load cleandata_tlt; %preprocessed timelocked data
> standardclean_tlt and targetclean_tlt
>
> cfg = []
> cfg.neighbourdist = .09;
> cfg.layout= ulmegilay;
> cfg.method = 'distance';
>
> Neighbours = ft_prepare_neighbours(cfg, standardclean_tlt)
>
> cfg = []
> cfg.method = 'montecarlo' ; %significance probability
> cfg.statistic = 'ft_statfun_depsamplesT'
> cfg.correctm = 'cluster'
> cfg.clusteralpha = 0.05 %alpha level of the sample specific
> test statistic that will
> % be used for thresholding
> cfg.clusterstatistic = 'maxsum'
> cfg.minnbchan = 4
> cfg.latency = [0.25 0.8]
> cfg.neighbours = Neighbours
> cfg.tail = 0
> cfg.clustertail = 0
> cfg.alpha = 0.025
> cfg.numrandomization = 1000
>
> design = [ones(size(targetclean_tlt.trial,1),1);
> 2*ones(size(standardclean_tlt.trial,1),1)]';
> design([1:size(targetclean_tlt.trial)
> 1:size(standardclean_tlt.trial,1)])
>
>
> cfg.design = design
> cfg.ivar = [ones(size(targetclean_tlt.trial,1),1);
> 2*ones(size(standardclean_tlt.trial,1),1)]'
> cfg.uvar = [1:size(targetclean_tlt.trial)
> 1:size(standardclean_tlt.trial,1)]
>
> tlt_statsnew = ft_timelockstatistics(cfg, targetclean_tlt,
> standardclean_tlt )
>
> cd 'G:\BackUp07.07.14_DatenPrepr\Daten1\P300';
> cd Kontrollen;
> List2 = dir
> cd (List2(i).name);
> eval(['cd M' num2str(j)]);
> save statnew tlt_statsnew
>
> end
> end
>
>
> This is what gets displayed while running the script:
>
> selected 245 channels
> selected 139 time bins
> selected 1 frequency bins
> using "ft_statistics_montecarlo" for the statistical testing
> using "ft_statfun_depsamplesT" for the single-sample statistics
> constructing randomized design
> total number of measurements = 189
> total number of variables = 1
> number of independent variables = 189
> number of unit variables = 189
> number of within-cell variables = 0
> number of control variables = 0
> using a permutation resampling approach
>
> Then, this error occurs:
>
> Error using resampledesign (line 168)
> A within-units shuffling requires a at least one unit variable and at least
> one independent variable
>
> Error in ft_statistics_montecarlo (line 241)
> resample = resampledesign(cfg, design);
>
> Error in statistics_wrapper (line 310)
> [stat, cfg] = statmethod(cfg, dat, design);
>
> Error in ft_timelockstatistics (line 113)
> [stat, cfg] = statistics_wrapper(cfg, varargin{:});
>
> I have no clue where I made a mistake. I have unit variables and
> independent variables (189 if I understand it correctly).
> Is there anything I am missing? Any additional information or is the
> design matrix wrong?
>
>
> I really appreciate your help.
>
> Best regards,
> Barbara
>
>
>
>
> Barbara Schorr, MSc
> Clinical and Biological Psychology
> University of Ulm
> Albert-Einstein-Allee 47
> 89069 Ulm
>
>
>
>
>
> ------------------------------
>
> Message: 2
> Date: Tue, 7 Oct 2014 09:55:36 -0400
> From: "Clara A. Scholl" <clara.scholl at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Problem with ft_timelockstatistics, within
> subject comparison of two conditions
> Message-ID:
> <CAAHOyr7MU6npw9U4Wqkoo7OXxthQmsTrjBroWcxLe6qTeSkC=g at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Dear Barbara,
>
> Just three thoughts:
>
> 1) Should cfg.ivar and cfg.uvar both be single values, i.e. the dimension
> of the design matrix that contains the independent and unit variables?
> Then you'd have cfg.ivar=1 and cfg.uvar=2 (or vise versa, depending on the
> design matrix).
>
> 2) I think the design matrix itself might be off, right now it just seems
> to have dimensions of 1 x (# targets+standards). It should have a second
> dimension which counts the # of trials, something like:
>
> design(1,:) = [ones(size(targetclean_tlt.trial,1),1);
> 2*ones(size(standardclean_tlt.trial,1),1)]';
> design(2,:)= ([1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.trial
> ,1)])
>
> 3) Since this is a design where each trial is an observation, I think you
> should be using indepsamplesT for cfg.statistic (the trials aren't paired
> and there aren't necessarily identical #'s of trials for each condition.
>
> What do you think?
> Respectfully,
> Clara
>
>
> On Tue, Oct 7, 2014 at 9:42 AM, <barbara.schorr at uni-ulm.de> wrote:
>
>> Dear fieldtripers,
>>
>> I would like to compare to conditions of an auditory oddball paradigm
>> (target tones and standard tones).
>> For the identification of the electrodes which show the biggest P300, I
>> would like to use cluster based permutation test, i.e. I want to use
>> ft_timelockstatistics, to identify the clusters with a significant
>> difference between the target and the standardtones.
>> Important: I don't want to do a group statistic, but I want to compare
>> these two conditions within each subject, to identify interesting clusters
>> for each subject separately.
>>
>>
>> I wrote the script following the tutorials on the fieldtrip homepage.
>>
>> I already wrote a code but it does not work:
>> %%
>>
>> for i = 3:10 % subject number
>> mypfad = 'G:\BackUp07.07.14_DatenPrepr\Daten1\P300'
>> cd(mypfad)
>> cd Kontrollen;
>> List = dir
>> cd (List(i).name);
>> for j = 1:4 %session number
>> cd (mypfad);
>> cd Kontrollen;
>> List = dir
>> cd (List(i).name);
>> eval(['cd M' num2str(j)]);
>> load cleandata_tlt; %preprocessed timelocked data
>> standardclean_tlt and targetclean_tlt
>>
>> cfg = []
>> cfg.neighbourdist = .09;
>> cfg.layout= ulmegilay;
>> cfg.method = 'distance';
>>
>> Neighbours = ft_prepare_neighbours(cfg, standardclean_tlt)
>>
>> cfg = []
>> cfg.method = 'montecarlo' ; %significance probability
>> cfg.statistic = 'ft_statfun_depsamplesT'
>> cfg.correctm = 'cluster'
>> cfg.clusteralpha = 0.05 %alpha level of the sample specific test
>> statistic that will
>> % be used for thresholding
>> cfg.clusterstatistic = 'maxsum'
>> cfg.minnbchan = 4
>> cfg.latency = [0.25 0.8]
>> cfg.neighbours = Neighbours
>> cfg.tail = 0
>> cfg.clustertail = 0
>> cfg.alpha = 0.025
>> cfg.numrandomization = 1000
>>
>> design = [ones(size(targetclean_tlt.trial,1),1);
>> 2*ones(size(standardclean_tlt.trial,1),1)]';
>> design([1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.
>> trial,1)])
>>
>>
>> cfg.design = design
>> cfg.ivar = [ones(size(targetclean_tlt.trial,1),1);
>> 2*ones(size(standardclean_tlt.trial,1),1)]'
>> cfg.uvar = [1:size(targetclean_tlt.trial) 1:size(standardclean_tlt.
>> trial,1)]
>>
>> tlt_statsnew = ft_timelockstatistics(cfg, targetclean_tlt,
>> standardclean_tlt )
>>
>> cd 'G:\BackUp07.07.14_DatenPrepr\Daten1\P300';
>> cd Kontrollen;
>> List2 = dir
>> cd (List2(i).name);
>> eval(['cd M' num2str(j)]);
>> save statnew tlt_statsnew
>>
>> end
>> end
>>
>>
>> This is what gets displayed while running the script:
>>
>> selected 245 channels
>> selected 139 time bins
>> selected 1 frequency bins
>> using "ft_statistics_montecarlo" for the statistical testing
>> using "ft_statfun_depsamplesT" for the single-sample statistics
>> constructing randomized design
>> total number of measurements = 189
>> total number of variables = 1
>> number of independent variables = 189
>> number of unit variables = 189
>> number of within-cell variables = 0
>> number of control variables = 0
>> using a permutation resampling approach
>>
>> Then, this error occurs:
>>
>> Error using resampledesign (line 168)
>> A within-units shuffling requires a at least one unit variable and at least
>> one independent variable
>>
>> Error in ft_statistics_montecarlo (line 241)
>> resample = resampledesign(cfg, design);
>>
>> Error in statistics_wrapper (line 310)
>> [stat, cfg] = statmethod(cfg, dat, design);
>>
>> Error in ft_timelockstatistics (line 113)
>> [stat, cfg] = statistics_wrapper(cfg, varargin{:});
>>
>> I have no clue where I made a mistake. I have unit variables and
>> independent variables (189 if I understand it correctly).
>> Is there anything I am missing? Any additional information or is the
>> design matrix wrong?
>>
>>
>> I really appreciate your help.
>>
>> Best regards,
>> Barbara
>>
>>
>>
>>
>> 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
>>
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> ------------------------------
>
> Message: 3
> Date: Tue, 7 Oct 2014 21:07:37 +0200
> From: Tzvetan Popov <tzvetan.popov at uni-konstanz.de>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] help for statistics on ERD/ERS
> Message-ID: <D25CE622-A81C-493D-8905-8536BB51023C at uni-konstanz.de>
> Content-Type: text/plain; charset=windows-1252
>
> Hi Giulia,
>
>
>> Dear Fieldtrippers
>> I'm writing to ask you some help on data in a single subject study.
>> I did a time frequency decomposition and I would like to do a
>> statistic to state whether the average TFR has significant ERD/ERS
>> or not.
>> I'm not sure how to proceed
> What you are referring to is a ?between trial experiment? which is
> described in this tutorial:
> http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq
> One possible way to go is to compute the TFR?s with cfg.keeptrials =
> ?yes?. Next you?d treat the baseline and the task interval as two
> conditions by separating them using ft_selectdata. After this you
> can compute the statistical comparison in a similar fashion as
> described in the tutorial.
> Keep in mind that you have to cut the data into equal lengths.
> Please have a look at this post :
> http://mailman.science.ru.nl/pipermail/fieldtrip/2007-July/001303.html
>> , as a first step I compared the single trial baseline with the
>> respective event, with a t-test for each condition and band of
>> interest but I'm not really sure if this is enough and anyway if it
>> is the correct way.
> Also please type ?actvsblT? in the search bar and then click on
> ?Search the FieldTrip mailing list?. There you?ll find some info
> about this.
>
> best
> tzvetan
>
>
>
>
> ------------------------------
>
> Message: 4
> Date: Wed, 08 Oct 2014 10:45:23 +0200
> From: Giuly <giulia.rizza at tiscali.it>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] help for statistics on ERD/ERS
> Message-ID: <eeebb8a2bf90ed8099aea3a3e21a7a38 at tiscali.it>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Tzvetan
> Thank you so much for your reply
> I will try these
> functions keeping in mind your explanation
> Best regards
> Giulia
>
> Il
> 07.10.2014 21:07 Tzvetan Popov ha scritto:
>
>> Hi Giulia,
>>
>>> Dear
> Fieldtrippers I'm writing to ask you some help on data in a single
> subject study. I did a time frequency decomposition and I would like to
> do a statistic to state whether the average TFR has significant ERD/ERS
> or not. I'm not sure how to proceed
>>
>> What you are referring to is a
> "between trial experiment" which is described in this tutorial:
>>
> http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_freq [1]
>>
> One possible way to go is to compute the TFR's with cfg.keeptrials =
> 'yes'. Next you'd treat the baseline and the task interval as two
> conditions by separating them using ft_selectdata. After this you can
> compute the statistical comparison in a similar fashion as described in
> the tutorial.
>> Keep in mind that you have to cut the data into equal
> lengths. Please have a look at this post :
>>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2007-July/001303.html
> [2]
>>
>>> , as a first step I compared the single trial baseline with
> the respective event, with a t-test for each condition and band of
> interest but I'm not really sure if this is enough and anyway if it is
> the correct way.
>>
>> Also please type "actvsblT" in the search bar and
> then click on "Search the FieldTrip mailing list". There you'll find
> some info about this.
>>
>> best
>> tzvetan
>>
>>
> _______________________________________________
>> fieldtrip mailing
> list
>> fieldtrip at donders.ru.nl [3]
>>
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip [4]
>
>
>
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> End of fieldtrip Digest, Vol 47, Issue 6
> ****************************************
>
Barbara Schorr, MSc
Clinical and Biological Psychology
University of Ulm
Albert-Einstein-Allee 47
89069 Ulm
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