[Eeglablist] Extracting ERP values after MPT clustering

[Mohammed Jarjees]

Dear Makoto,

Thank you very much for your quick response.

Sure, I am going to report this problem in Bugzilla.

Is there any alternative method to extract the ERP values after MPT clustering or to extract the P values after run statistics by MPT GUI?

About the anatomical regions, do you know how can I do that?

Many Thanks
Mohammed

From: Makoto Miyakoshi [mailto:mmiyakoshi at ucsd.edu]
Sent: 21 April 2016 03:38
To: Mohammed Jarjees
Cc: eeglablist at sccn.ucsd.edu
Subject: Re: [Eeglablist] Extracting ERP values after MPT clustering

Dear Mohammed,

Sorry to hear the inconvenience. This is a good detailed question. I believe this should be posted for eeglab Bugzilla to be officially registered. Would you mind filing the report here? I appreciate your cooperation and patience.
https://sccn.ucsd.edu/bugzilla/enter_bug.cgi

That being said, I recently noticed that Measure Projection could have a potential problem of double dipping (because you cluster data using ERP, for example, and run statistics on that later). It's probably safer to use anatomical regions, not domains (but that may not be supported by GUI).

Makoto

On Mon, Apr 18, 2016 at 10:49 AM, Mohammed Jarjees <m.jarjees.1 at research.gla.ac.uk<mailto:m.jarjees.1 at research.gla.ac.uk>> wrote:
Dear All,

I am using  Measure projection toolbox (MPT) to cluster my EEG (ERP) data. In this study I have 3 groups of subjects ( First group has 10 subjects, second group has 9 subjects and third group has 10 subjects) and I have 3 conditions per group. I got 3 domains after MPT clustering. I extracted the ERP values from “sessionConditionCell” for each domains. The size of “sessionConditionCell” is 29*3 (subjects*conditions). I have used the following codes to extract the ERP values and to separate these values for each group and each condition.

domainNumber = 1; % this should be 1,2 or 3%
dipoleAndMeasure = STUDY.measureProjection.erp.object;
domain                         = STUDY.measureProjection.erp.projection.domain(domainNumber);
projection                   = STUDY.measureProjection.erp.projection;
headGrid                     = STUDY.measureProjection.erp.headGrid;
[linearProjectedMeasure sessionConditionCell groupId uniqeDatasetId dipoleDensity]  = dipoleAndMeasure.getMeanProjectedMeasureForEachSession(headGrid, domain.membershipCube, projection.projectionParameter);

for i =1 : 29 ;
Condition_1 ( i , : )= sessionConditionCell { i, 1};
Condition_2 ( i , : )= sessionConditionCell { i, 2};
Condition_3 ( i , : )= sessionConditionCell { i, 3};
end

Group_1_Condition_1= Condition_1 ( 1:10, : );     Group_2_Condition_1= Condition_1 ( 11:19, : );     Group_3_Condition_1= Condition_1 ( 20:29, : );
Group_1_Condition_2= Condition_2 ( 1:10, : );     Group_2_Condition_2= Condition_2 ( 11:19, : );     Group_3_Condition_2= Condition_2 ( 20:29, : );
Group_1_Condition_3= Condition_3 ( 1:10, : );     Group_2_Condition_3= Condition_3 ( 11:19, : );     Group_3_Condition_3= Condition_3 ( 20:29, : );

When I plotted the average ERP for each condition, each group and each domain, I got different in some results from the results that I got from MPT GUI. For example the results for group 1 at Domain 1 for 3 conditions are same as the results from MPT GUI as well as the result for domain 2 and all three group and three condition are same as the MPT GUI. However, there are big different for group 2 & 3 at domain 1 as well as group 2 & 3 at domain 3 for all three conditions.

Any Suggestion to solve this problem

Best Regards
Mohammed

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--
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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