Donald,

Thanks for your response. From this then, would it be sensible to say that you are only interested in the effects of one condition on the regional response and therefore place variance associated with the other condition in the null space?

Would this work as a way to sort of orthogonalize the extracted time course?

-Drew

From: <MCLAREN>, Donald <[log in to unmask]>
Date: Friday, October 25, 2013 4:47 PM
To: Landrew Sevel <[log in to unmask]>
Cc: SPM <[log in to unmask]>
Subject: Re: [SPM] Eigenvariate--Adjusting for a contrast

Drew,

The point of adjusting is to remove the effect of the null-space effects from the data (e.g the effects of motion and constant term). If you are going to adjust, you want to use the same adjustment for all conditions. You want to use an F-contrast that tests for the effect of any condition as the contrast to adjust for.

Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Thu, Oct 17, 2013 at 6:31 PM, Sevel,Landrew S <[log in to unmask]> wrote:
SPM'ers,

What are the specific effects of adjusting for an F contrast on the eigenvariate values that are produced?

Specifically, we are looking to apply SEM to time series from a protocol with two conditions with the goal of comparing models generated between conditions. Would it be appropriate to create an F contrast for condition 1 and extract a time series from region 1 after adjusting for contrast one and then extracting an eigenvariate from the same region but adjusting for an F contrast of condition two?

I do realize the potential utility of using DCM to address this question but nonetheless would like to know if this would be an appropriate approach for SEM.

Many thanks,

Drew