AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

History of AFNI updates  

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January 05, 2018 11:50AM
Unfortunately, the article referenced does not give the formula for the HRF they used, they just say it is implemented in BrainVoyager. So it is a little difficult to fully address your question.

There are a couple ways you can proceed, from easy to hard.

FIRST method: GAM(p,q) is described in detail in the output of 3dDeconvolve -help:
https://afni.nimh.nih.gov/pub/dist/doc/program_help/3dDeconvolve.html
     'GAM(p,q)'    = 1 parameter gamma variate                         
                               (t/(p*q))^p * exp(p-t/q)                      
                             Defaults: p=8.6 q=0.547 if only 'GAM' is used   
                          ** The peak of 'GAM(p,q)' is at time p*q after    
                             the stimulus.  The FWHM is about 2.3*sqrt(p)*q.
                   ==> ** If you add a third argument 'd', then the GAM  
                              function is convolved with a square wave of    
                              duration 'd' seconds; for example:             
                                'GAM(8.6,.547,17)'                           
                              for a 17 second stimulus.
So if you want a peak to occur at D s, then p*q=D should be chosen. If you want a (full) width of W s, then 2.3*sqrt(p)*q=W should be chosen. So D/W=sqrt(p)/2.3 or p=(2.3*D/W)^2 and then q=D/p. For example, D=4 and W=6 gives p=2.35 q=1.70. You can visualize this function in AFNI commands via
1deval -num 200 -del 0.1 -expr 't^2.35*exp(-t/1.7)' | 1dplot -stdin -del 0.1
If you have a stimulus of duration 3 s (as in the cited paper), then using 'GAM(2.35,1.7,3)' would be appropriate for this model.

The drawback of this method, relative to the method of the cited paper, is that there is only one gamma variate (please do NOT call these gamma functions, as is commonly done, since those are something else entirely), and if you want to duplicate the analysis of the paper, you need two such functions added together appropriately.

At this point, I'm tired of typing, so will respond to this posting later when I gather my thoughts and rest my fingers.
Subject Author Posted

How to use HRF with shorter latency for deconvolving in afni?

Zhang Yu January 04, 2018 04:15PM

Re: How to use HRF with shorter latency for deconvolving in afni?

Bob Cox January 05, 2018 11:50AM

Re: How to use HRF with shorter latency for deconvolving in afni?

Bob Cox January 08, 2018 11:01AM

Re: How to use HRF with shorter latency for deconvolving in afni?

Zhang Yu January 10, 2018 01:24PM

Re: How to use HRF with shorter latency for deconvolving in afni?

Bob Cox January 10, 2018 01:41PM

Re: How to use HRF with shorter latency for deconvolving in afni?

Zhang Yu January 11, 2018 01:21AM

Re: How to use HRF with shorter latency for deconvolving in afni?

rick reynolds January 11, 2018 08:52AM

Re: How to use HRF with shorter latency for deconvolving in afni?

rick reynolds January 11, 2018 09:52AM