[pymvpa] Across-subjects surface query engine?

[Beau R. Sievers]

Hi there,

How does one perform across-subjects analysis on the surface using PyMVPA?

I am currently estimating the noise ceiling on my data (as described by Nili et al., 2014). This requires anatomically-aligned data from all of the subjects in the experiment. I'm using the following approach: create a single large PyMVPA dataset including data from all template-aligned subjects, and assign a chunks sample attribute corresponding to subject ID, then use a searchlight with a custom noise ceiling estimation measure (that uses the chunks sample attribute to split the samples appropriately).

This works great, but I would like to move my analysis to the surface. So for each searchlight center _on the surface template_ I would need to get surrounding voxels _from all individual subjects._

It is difficult for me to tell whether this is possible based on reading the query engine documentation and the surface searchlight example.

Thanks!

Bests,
Beau Sievers

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Refs:

Nili, H., Wingfield, C., Walther, A., Su, L., Marslen-Wilson, W., & Kriegeskorte, N. (2014). A toolbox for representational similarity analysis. PLoS Comput Biol, 10(4), e1003553.