So I created a weighted regression analysis to look at the effect of memory load in a particular brain region. Basically, I weighted the paradigms by a behavioral measure that reflected the number of items actually remembered (as set size was increased). As far as Doug told me there are basically 2 ways to weight your paradigm files.
Version 1: Have 2 conditions, baseline (condition 0) and all the set sizes (condition 1). Condition 1 would then be weighted by the behavioral measure. Version 2: Have 3 conditions, baseline (condition 0), and then I represented each presentation as two different conditions, one with a weight that is always 1 (condition 1), the other weighted according to the behavioral measure (condition 2). The difference, as far as I understand it, in version 1, it is assumed that the response amplitude is ) when the weight is 0 (ie. that when you are attending to 0 items, brain activity = 0). Whereas, version 2, tests the slope of the HRF amplitude vs weight without the assumption above. However, I'm a bit confused as to the results I got. When I looked at the data from both versions, version 1 provided a much higher amount of activation and more areas activated than version 2. However, I believe version 2 better fits with the multiple regression analysis that is done in Brain Voyager. Can anyone give me a better explanation of what the difference between these analysis models is? Katie
_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine at http://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.
