Dear Anna,
This is just my $0.02 but I would think that you should be using copes
(i.e. effect sizes) rather than zstats (statistics) in your
correlations. The reason is that zstats reflect both the effect sizes *and
the noise* in a given ROI while copes are effectively just a measure of the
evoked effect according to your contrast of interest.
It may not be very surprising that your RTs don't correlate well with ROI
cope values for a couple of reasons. First, if they are copes, they are
summary statistics across the entire time series per subject so the
correlation is the mean signal in a region across individuals with the
individual's mean RT. Second, The mean RT may not be very meaningful
across subjects, unless it first reflects a mean contrast between relevant
conditions and is also normalized to remove baseline differences in RTs
across subjects. Even so, you're looking for a single brain region to
explain the variance across subjects for a global behavioural measure...
It may be more convincing to enter RTs as a covariate in your individual
subject first level analyses and look for brain regions which correlate
with RTs and then determine whether these are consistent across
subjects. That way, you avoid all of the above issues and simply look for
a consistent brain region which varied with the individual's response times
across trials/blocks.
Hope this is helpful. Good luck!
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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