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Hi,

However this isn't
terribly important because the same spatial regressors are used
against all subjects in stage one of the dual regression, so the
relative amplitudes (etc) of the outputs from stage 1 (the timeseries)
are unaffected by the scaling of the spatial regressors.

But isn't this true only if  "relative amplitudes" refers to a
between-subject comparison of the time series corresponding to a given
spatial mode? On the other hand,  if the comparison of interest is between
the time series corresponding to *different* spatial regressors (e.g., if
one is interested in comparing the amplitude or the spectrum of the time
signal fluctuations associated with different spatial modes), then wouldn't
a standardization of the spatial regressors make the interpretation of the
results clearer?

That's correct - however from my previous reply - I think that the standardisation that is done is a reasonable one.   However, you might argue that a possibly better way of scaling the spatial regressors is to set the _maximum_ voxel to (say) 1 (in each spatial regressor), whilst keeping the best zero-centering.  This might give you what you want - though might be a 'noisy' kind of standardisation as it would depend on the value in just one voxel........it's something that we're currently looking into the practicalities of.

Cheers, Steve.

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Stephen M. Smith, Professor of Biomedical Engineering
Associate Director,  Oxford University FMRIB Centre

FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 222726  (fax 222717)
[log in to unmask]    http://www.fmrib.ox.ac.uk/~steve
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