[Eeglablist] how to do group analysis using SIFT?

[Hui-bin Jia]

Hi, everyone
 
   SIFT doesn’t have Group Analysis module in current version. 
   But I want to use this toolbox to do the granger-causal connectivity analysis of channel data. 
   To achieve this goal, I thought out this method. But I don’t know whether it right or not.
 
 
   I will make use of the experiment in the SIFT manual to illustrate my method.
   Assuming I have got the data of 10 subjects in two conditions (RespWrong and RespCorrect). 
   So there are 20 datasets in total. Independent component analysis has been conducted on all of the 20 datasets.
   In each dataset, the number of channels and independent components both are 152(nbchan = 152 ), and the      number of epochs is 123. In every epoch, there are 1024 data points(ie. pnts = 1024).
 
   Then I collected the EEG data of the eleventh subject in the two conditions (RespWrong and RespCorrect).
   And these two dataset are called ‘datasetwrong’ and ‘datasetcorrect’. Independent component analysis has
   been conducted on all of the 2 datasets. In each dataset, the number of channels and independent components
   both are 152(nbchan = 152 ), and the number of epochs is 1030. In every epoch, there are 1024 data
   points(ie. pnts = 1024).
 
   Now I want to do granger-causal connectivity analysis of the RespWrong condition. 
   The No. of channels for analysis are 11, 12, and 13. For the first ten subjects, I get 1230(123*10) epochs 
   at each channel. 
   1. I get 1000 epochs which are free from artifacts from all the 1230 epochs(123*10) in channel 11, 12 and 13.  
   Then using these data, I get 3 1024*1000 matrices. 
   They are called a, b, and c. And I assume these three matrices represent the data from all of the first ten 
   subjects. 
   2.'datasewrong' is loaded in MATLAB, and 30 epochs in this dataset are deleted, which means 
   the number of the remaining epochs is 1000. 
   3, in the command line, 
   I type EEG.data(1,:,: ) = a ; EEG.data(2,:,: ) = b; EEG.data(3,:,: ) = c.  EEG.data is a 152*1024*1000 matrix. 
   4. In the command line, I type EEG.data = EEG.icaact; EEG.icawinv = EEG.icaweights = ones(152,152).
   5, I select the eleventh, twelfth, and thirteenth independent components and do granger-causal connectivity
   analysis according to the Data processing pipeline illustrated by the SIFT manual.
 
 
   I’m asking my method is right or not? Can it be considered as an alternative for group analysis?
 
   Can I do bootstrap sample and phase randomization with the current version of SIFT?
 
   Thanks!
  
  
 Sincerely,
 Hui-bin Jia
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