Hello,
I recently conducted an analysis of a dataset in SPM5 that I had previously
analyzed in SPM99 (with standard random effect GLMs). On the plus side, the
pattern of SPM activity was identical, the only difference being slightly
more robust responses with SPM5. On the minus side (figuratively and
literally), the SPM5 beta-weight values extracted from visual activity
evoked by left and right hemifield stimuli were almost all negative in
amplitude (the same beta-weight values were almost all positive in SPM99, as
would be expected from retinotopic increases in neural activity). To
follow-up on this, I plotted a histogram of each beta-weight set
(beta_0001.img, beta_0002.img, etc.) resulting from the analyses. Values of
most SPM5 beta-weight sets had a relatively large baseline shift (some
positive, some negative, often skewed in distribution), while values of all
SPM99 beta-weight sets were centered at 0 with far less variance and no skew
(as would be expected, given that only a small fraction of voxels should be
associated with a given event type). What is interesting is that the
relative difference in magnitude between beta-weights seems to be intact,
explaining why the overall activation pattern for both analyses is the same.
For instance, in left extrastriate cortex the beta-weight value
corresponding to right visual field stimulation is greater than the value
associated with left visual field stimulation for both analyses, but the
mean beta-weight value is significantly positive for the SPM99 analysis and
significantly negative for the SPM5 analysis. Finally, I should also mention
that I’m interested in this because I have written a function that extracts
beta-weights from ROIs to reveal the sign of event-related activity, and
while it had been useful in SPM 99, it is currently useless in SPM5 for the
above reasons. Any ideas would be greatly appreciated.
Thanks,
Scott
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