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 — 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. _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list Pkg-ExpPsy-PyMVPA@lists.alioth.debian.org http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
