Hi Doug,
Thanks for your response.  I want to treat it as a nuisance variable.  If so, 
should the #3 is best choice?
Xiaomin

Date: Sun, 3 May 2015 11:06:01 -0400
From: gr...@nmr.mgh.harvard.edu
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] a mkanalysis-sess question


  
    
  
  
    

    #1 and #3 are basically the same. If used as a task regressor, then
    a contrast for it will be created. #2 is a parametric modulation.
    Probably not what you want but see
    http://freesurfer.net/fswiki/FsFastParametricModulation

    

    Do you want to treat it as  a nuisance variable or task? In any
    event, I would probably recode it to make fixation=0 and
    non-fixation something else

    

    

    On 5/2/15 5:34 PM, Xiaomin Yue wrote:

    
    
      
      
        
        
        
        
        Hi, 
         
        I have a question related to how to make an
          appropriate design
          matrix using fs-fast 5.3.   Subjects’ eye
          movement was collected during an experiment.  Then, the data
          has been transformed to a continuous
          variable with a number for each TR.  The
          better fixation performance has higher number. 
          For example, a number would be 0 if subjects look away from a
          target
          within a TR.  In ideal situation,
          subjects should keep his eyes on target all the time, so the
          variable should be
          1 for all TR.  According to
          mkanalysis-sess documents, it seems that there are three
          different ways to take
          into account of eye fixation performance: 1) use it as an
          external task regressor;
          2) use it as a weight in the paradigm file (the fourth
          column); 3) use it as a
          nuisance regressor.  My question is what’s
          the difference between the three methods? 
          In my situation, which one is the best choice in my situation?
        

        
        I hope the question is clear.  Thanks so
          much for your help.
        

        
        Xiaomin
        
         
      

      
      

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