Hi Paige,
THe short answer is yes, you need to correct for multiple comparisons if
you want to characterise your results in terms of "activations". As I
understand these things, you have the option of of simply describing the
patterns as probably greater than 0 with a given confidence, but in
practice this is not generally what one wants to say. Instead, we normally
are asking what is "activated" by a given contrast (e.g. more activated in
condition A than B) and for that you need to control the risk of family
wise error.
From what I can tell, this issue of not correcting posterior probability
maps (PPMs) is a bit of semantic trickery and not generally useful given
the types of questions one normally tries to answer using fMRI... but I'd
be interested in hearing other's (more educated!) opinions.
> Since FLAME uses Bayesian inferences techniques, is it necessary
> to correct for multiple comparisons when thresholding
> for voxel-wise activation? The SPM info pages explicitly state
> that it is not necessary to do so when using its Bayesian
> estimation and inference packages; I was wondering if the same
> held true for the estimation and inference techniques used by
> FLAME? Also, if you could provide me with a "dummy's" explanation
> for why this is or is not the case, I'd be most grateful.
Joe
--------------------
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]
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