[pymvpa] Matrices per Searchlight

[Susanne Greiner]

Hi Gavin,

I am no searchlight expert, but one of the BayesConfusionHypothesis team 
:-) It could be that at a certain stage I have already tried to do 
something similar and there could also be (maybe not very beautiful but 
working) code. Could you please let me know which version of PyMVPA you 
are currently using and give a few more details on what you are 
launching (experimental settings) and what kind of results you expect?
What I did in the past was to launch searchlight on a specific ROI in 
combination with the BayesConfusionHypothesis in order to see whether 
subregions of the ROI were more specific for one of the stimulation 
conditions making kind of searchlight maps (one for each stimulation 
condition) and looking on them when overlaid :-)

Susanne

-------------

On 11/25/13 8:36 PM, Hanson, Gavin Keith wrote:
> Hi:
> I am reasonably new to PyMVPA, but have not had any trouble with it so far.
> However, I am interested in running an analysis similar to that performed in Connolly, 2012, where dissimilarity matrices are computed per searchlight. I would like to know if anyone knows of a straightforward way to do with within PyMVPA - that is, get the simple confusion matrix per searchlight. Even better, I would like to be able to look at the results of the BayesConfusionHypothesis node at a per-searchlight level, as our hypothesis has to do with how the specificity of information encoding changes across the brain, and that tool seems perfect for that. Results with ROIs have been promising, but I'd like to see how this plays out across the entire brain, and the ability to use the searchlight tool in conjunction with the Bayes Confusion node would be very helpful. If anyone could help me with this, I'd much appreciate it!
>
> - Gavin Hanson
>
>
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