[pymvpa] question about cross-subject analysis

John Magnotti john.magnotti at gmail.com
Wed Jan 18 16:51:26 UTC 2012

Thanks for the citation, I'll definitely take a look. Regarding the
paper you worked on with Russ P., was there any extra effort to ensure
the Z-score maps were in some kind of standard space?


On Wed, Jan 18, 2012 at 9:37 AM, Yaroslav Halchenko
<debian at onerussian.com> wrote:
> I you only care about classification performances I bet you might soon
> hear from Raj...
>> ... the masks for each subject don't necessarily cover the same
>> voxels.
> like snowflakes -- neither of two voxels are "the same" ;) they might be alike
> though...  Therefore you could also have a look at the recent regarding
> either that is closer to your goals:
>    Haxby, J. V. , Guntupalli, J. S. , Connolly, A. C. , Halchenko, Y. O. ,
> Conroy, B. R., Gobbini, M. I. , Hanke, M. and Ramadge, P. J. (2011). A Common,
> High-Dimensional Model of the Representational Space in Human Ventral Temporal
> Cortex. Neuron, 72, 404–416. [PDF] [PDF:Supp] DOI:
> 10.1016/j.neuron.2011.08.026,
>  http://haxbylab.dartmouth.edu/publications/HGC+11.pdf
>  http://haxbylab.dartmouth.edu/publications/HGC+11_Supplementals.pdf
>  Hyperalignment is available as a part of mvpa2
> On Wed, 18 Jan 2012, John Magnotti wrote:
>> 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.
> --
> =------------------------------------------------------------------=
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