[pymvpa] question about cross-subject analysis

John Magnotti john.magnotti at gmail.com
Wed Jan 18 15:30:24 UTC 2012

Hi All,

I'm trying to work build a cross-subject analysis using the Haxby et
al data (http://data.pymvpa.org/datasets/haxby2001/). The problem is
that the masks for each subject don't necessarily cover the same
voxels. Poldrack et al. [1] mention using an intersection mask to
ensure they were looking at the same voxels across subjects. Is there
a way to do this in PyMVPA, and should I do something like convert to
standard space beforehand? I could also just use the whole timeseries,
but I think there is still the issue of ensuring that the voxels
"match" across subjects, right?

Any hints or tips would be much appreciated.



1. Poldrack, R. A., Halchenko, Y. O., & Hanson, S. J. (2009). Decoding
the large-scale structure of brain function by classifying mental
states across individuals. Psychological Science, 20(11), 1364-72.

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