[FieldTrip] fieldtrip Digest, Vol 107, Issue 4 Re: baseline correction - Cluster Based Permutation Test (Tara van Viegen)
eleonora parrotta
eleonora_p at hotmail.it
Tue Oct 8 13:01:52 CEST 2019
Dear Tara,
Thank you very much for your suggestion, but I already tried to run the Cluster-based on raw power in the baseline time-interval and no significant cluster has been detected.
So, it seems that this difference between raw power and baseline-corrected one can't be explained by existing differences in the baseline period.
Hope that you have other suggestions,
Thank you in advance,
Eleonora
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Subject: fieldtrip Digest, Vol 107, Issue 4
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Today's Topics:
1. Re: Small Issues with the 15684 Mesh Creation Procedure
(Schoffelen, J.M. (Jan Mathijs))
2. baseline correction - Cluster Based Permutation Test
(eleonora parrotta)
3. Re: baseline correction - Cluster Based Permutation Test
(Tara van Viegen)
----------------------------------------------------------------------
Message: 1
Date: Mon, 7 Oct 2019 12:33:27 +0000
From: "Schoffelen, J.M. (Jan Mathijs)" <jan.schoffelen at donders.ru.nl>
To: FieldTrip discussion list <fieldtrip at science.ru.nl>
Subject: Re: [FieldTrip] Small Issues with the 15684 Mesh Creation
Procedure
Message-ID: <C7A4D2E1-171C-4D79-A398-99EF2126A762 at donders.ru.nl>
Content-Type: text/plain; charset="utf-8"
Dear Paolo,
@1: I have not encountered the issue you describe. Probably it is the consequence of the fact that the anatomical images you use are different as compared to ours, e.g. in terms of voxel sizes, field-of-view, acquisition sequence. I am no expert in mri_convert, but this function has some options that might tweak its behavior such that it does justice to your anatomical images.
@2: If you run the post processing script (which relies on hcp-workbench) the meshes will be surface-registered to a template, which allows for direct vertex-wise comparison across subjects (as well as across hemispheres).
Best,
Jan-Mathijs
On 2 Oct 2019, at 11:35, Paolo Belardinelli <paolo.belardinelli at gmail.com<mailto:paolo.belardinelli at gmail.com>> wrote:
Dear all,
I would first like to thank Jan-Mathijs for the massive work on the mesh sourcemodel.
I encountered a couple of minor issues while implementing the whole process:
1. In some subjects, after saving the .mgz file with Fieldtrip (including acpc coordinates and reference point), the image is slightly shifted towards the superior side of the frame by mriconvert (mri_convert -c -oc 0 0 0 $SUBJECTNAME.mgz orig.mgz). This implies that the upper part of the brain is being chopped and the further segmentation process with recon -all makes no sense anymore. Has anyone the same issue?
2. As far as I understand, an average, atlas-mapped mesh where to visualize pooled results is not generated. What would be a straightforward way of visualizing group results in standard coordinates?
Best wishes,
Paolo
--
--
Paolo Belardinelli, PhD
Neurology Department
University Hospital Tuebingen
Eberhard Karls University Tuebingen
Hoppe-Seyler Str. 3
D-72076 Tuebingen
Tel: +49 7071 / 29 80478
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https://doi.org/10.1371/journal.pcbi.1002202
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Message: 2
Date: Mon, 7 Oct 2019 16:12:30 +0000
From: eleonora parrotta <eleonora_p at hotmail.it>
To: "fieldtrip at science.ru.nl" <fieldtrip at science.ru.nl>
Subject: [FieldTrip] baseline correction - Cluster Based Permutation
Test
Message-ID:
<DB8PR10MB31155EC46EAD26EFB120F7A18D9B0 at DB8PR10MB3115.EURPRD10.PROD.OUTLOOK.COM>
Content-Type: text/plain; charset="windows-1252"
Dear Fieldtrippers,
I am performing analysis of EEG data. I have two conditions of interest: A and B, and I have performed spectral decomposition with the wavelet method to obtain the power (frequencies from 1 to 50 Hz).
I performed a cluster-based permutation test to assess whether there are significant power differences between the two conditions of interest in the time-interval from the onset of the stimulus to 1 sec after:
%% clusterbased analysis
cfg = [];
cfg.latency = [0 1]; % Time of Interest
cfg.frequency = [8 12]; % Frequency of interest
cfg.channel = {'PO3', 'P3', 'O1', 'P7','O2','P8','PO4','P4'};
cfg.neighbours = neighbours;
cfg.avgoverfreq = 'yes';
cfg.avgovertime = 'no';
cfg.avgoverchannel = 'no';
cfg.method = 'montecarlo';
cfg.statistic = 'ft_statfun_depsamplesT';
subj = 18;
design = zeros(2,2*subj);
for i = 1:subj
design(1,i) = i;
end
for i = 1:subj
design(1,subj+i) = i;
end
design(2,1:subj)= 1;design(2,subj+1:2*subj) = 2;
cfg.design = design;
cfg.uvar = 1;
cfg.ivar = 2;
cfg.correctm = 'cluster';
cfg.clusteralpha = 0.05;
cfg.clusterstatistic = 'maxsum';
cfg.minnbchan = 2;% specifies with which sensors other sensors can form clusters
cfg.tail = 0;
cfg.clustertail = 0;
cfg.alpha = 0.05;
cfg.numrandomization = 1000;
[alpha] = ft_freqstatistics(cfg, avg_pred, avg_ran);
When I perform the cluster-based analysis on raw power I obtain more than one negative cluster, with highly significant differences between my two condition (p=0.01). The problem is that when I run the cluster-based analysis on baseline-corrected power the analysis is not even able to find any cluster of electrodes that behave differently in one condition compared to the other one (no matter which kind of baseline I applied, I tried with both ‘absolute’ and ‘relchange’ and even different time-window).
I am aware of the potential loss of power that can occur when we use baseline-correction (http://datacolada.org/39)
At the same time I am not sure how correct is to perform stats on non-baseline corrected power, as without applying this procedure drifts and offsets potentially present in the signal could affect the statistical test, executed on two non-normalized datasets.
I was wondering whether I am not aware of potential ways to specify that a baseline-correction has been applied to the data, or if there is a correct way of doing it.
So far I couldn’t find any reference that explains it clearly, but if anyone has an explanation I would really appreciate.
Thanks in advance,
Eleonora
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Message: 3
Date: Mon, 7 Oct 2019 13:49:04 -0400
From: Tara van Viegen <taravanviegen at gmail.com>
To: FieldTrip discussion list <fieldtrip at science.ru.nl>
Subject: Re: [FieldTrip] baseline correction - Cluster Based
Permutation Test
Message-ID:
<CAFBE+2n0yaCFpxijCN7LrCtStxmKaKUv8gEZ5v-X3iGTfGCb6g at mail.gmail.com>
Content-Type: text/plain; charset="utf-8"
Hi Eleonora,
A likely explanation of what you describe is that there are baseline
differences between your conditions of interest. You could check this by
running the statistics you used previously on the raw power in the time
window that you select as a baseline (e.g. cfg.latency = [-0.5 -0.1];
cfg.avgovertime = 'yes';). The difference you are observing between your
conditions are then explained by differences that already exist in the
baseline. If you apply a baseline correction you get rid of this effect.
Best,
Tara van Viegen
Senior-RA (aspiring post-doc)
Neuroscience of Attention & Perception Lab
Princeton University
tviegen at princeton.edu
On Mon, Oct 7, 2019 at 12:34 PM eleonora parrotta <eleonora_p at hotmail.it>
wrote:
> Dear Fieldtrippers,
>
> I am performing analysis of EEG data. I have two conditions of interest: A
> and B, and I have performed spectral decomposition with the wavelet method
> to obtain the power (frequencies from 1 to 50 Hz).
>
> I performed a cluster-based permutation test to assess whether there are
> significant power differences between the two conditions of interest in the
> time-interval from the onset of the stimulus to 1 sec after:
>
> %% clusterbased analysis
>
> cfg = [];
>
> cfg.latency = [0 1]; % Time of Interest
>
> cfg.frequency = [8 12]; % Frequency of interest
>
> cfg.channel = {'PO3', 'P3', 'O1', 'P7','O2','P8','PO4','P4'};
>
> cfg.neighbours = neighbours;
>
> cfg.avgoverfreq = 'yes';
>
> cfg.avgovertime = 'no';
>
> cfg.avgoverchannel = 'no';
>
> cfg.method = 'montecarlo';
>
> cfg.statistic = 'ft_statfun_depsamplesT';
>
> subj = 18;
>
> design = zeros(2,2*subj);
>
> for i = 1:subj
>
> design(1,i) = i;
>
> end
>
> for i = 1:subj
>
> design(1,subj+i) = i;
>
> end
>
> design(2,1:subj)= 1;design(2,subj+1:2*subj) = 2;
>
> cfg.design = design;
>
> cfg.uvar = 1;
>
> cfg.ivar = 2;
>
> cfg.correctm = 'cluster';
>
> cfg.clusteralpha = 0.05;
>
> cfg.clusterstatistic = 'maxsum';
>
> cfg.minnbchan = 2;% specifies with which sensors other sensors can
> form clusters
>
> cfg.tail = 0;
>
> cfg.clustertail = 0;
>
> cfg.alpha = 0.05;
>
> cfg.numrandomization = 1000;
>
> [alpha] = ft_freqstatistics(cfg, avg_pred, avg_ran);
>
>
>
> When I perform the cluster-based analysis on raw power I obtain more than
> one negative cluster, with highly significant differences between my two
> condition (p=0.01). The problem is that when I run the cluster-based
> analysis on baseline-corrected power the analysis is not even able to find
> any cluster of electrodes that behave differently in one condition compared
> to the other one (no matter which kind of baseline I applied, I tried with
> both ‘absolute’ and ‘relchange’ and even different time-window).
>
> I am aware of the potential loss of power that can occur when we use
> baseline-correction (http://datacolada.org/39)
>
> At the same time I am not sure how correct is to perform stats on
> non-baseline corrected power, as without applying this procedure drifts and
> offsets potentially present in the signal could affect the statistical
> test, executed on two non-normalized datasets.
>
> I was wondering whether I am not aware of potential ways to specify that a
> baseline-correction has been applied to the data, or if there is a correct
> way of doing it.
>
> So far I couldn’t find any reference that explains it clearly, but if anyone has an explanation I would really appreciate.
>
>
>
> Thanks in advance,
>
>
>
> Eleonora
>
>
>
> _______________________________________________
> fieldtrip mailing list
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> https://doi.org/10.1371/journal.pcbi.1002202
>
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