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Hi Joe, About negative PE values as a result of Featquery: - Looking at the covariance matrix, my design does not appear rank deficient, so I would like to use the PEs reported by Featquery to further understand patterns in my ROI. As a reminder, I have 5 conditions and Featquery gives me negative numbers for PEs and tstats for all 5 in my ROI (though I have positive COPEs of interest). - Doesn't the PE represent beta from the GLM? Is it possible that PEs would be negative because the blood flow changes are the opposite of what I modeled? - In my dataset, one group has consistently MORE negative PEs than the other (both have all negative PEs). Is this related to lower overall levels of blood flow in my ROI in one group, or to worse fit of BF changes to my model? Thanks, Dost On Thu, 23 Sep 2004 19:53:21 +0100, Joseph Devlin <[log in to unmask]> wrote: >The effect size can be consistently negative across conditions if the BOLD >signal in the ROI is less than that of the whole brain mean. If you've >modeled the fixation separately, then you may have a rank-deficient design >matrix in which case the individual PE values aren't entirely meaningful -- >what is important is the relative differences between PEs. It sounds like >your contrast is giving you meaningful results consistent with your >expectations, so I wouldn't worry about the absolute value of the >individual PEs. >-------------------- >Joseph T. Devlin, Ph. D. >FMRIB Centre, Dept. of Clinical Neurology >University of Oxford >John Radcliffe Hospital >Headley Way, Headington >Oxford OX3 9DU >Phone: 01865 222 738 >Email: [log in to unmask]