<div dir="ltr">Many thanks, very useful indeed. A related question: So the input to the groupwise calculations are the permutated searchlight maps from single subjects - and computation-wise this seems to me to be quite a bottleneck, given that one whole brain searchlight already takes several hours. Is there any way to speed up this part?</div><div class="gmail_extra"><br><div class="gmail_quote">On Fri, Oct 20, 2017 at 5:13 PM, Nick Oosterhof <span dir="ltr"><<a href="mailto:n.n.oosterhof@googlemail.com" target="_blank">n.n.oosterhof@googlemail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><br><div class="gmail_extra"><br><div class="gmail_quote"><span class="">On 20 October 2017 at 16:48, Pegah Kassraian Fard <span dir="ltr"><<a href="mailto:pegahkf@gmail.com" target="_blank">pegahkf@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left-width:1px;border-left-color:rgb(204,204,204);border-left-style:solid;padding-left:1ex"><div dir="ltr">More concretely, I would be very interested in a non-parameteric test: Permutation of train labels followed by cluster size correction, as for instance presented in the paper <a href="https://www.ncbi.nlm.nih.gov/pubmed/23041526" target="_blank">"Statistical inference and multiple testing correction in classification-based multi-voxel pattern analysis (MVPA): random permutations and cluster size control":</a><br><br></div></blockquote><div><br></div></span><div>Something along these lines in provided in the GroupClusterThreshold class.</div><div><br></div><div>See <a href="http://www.pymvpa.org/generated/mvpa2.algorithms.group_clusterthr.GroupClusterThreshold.html" target="_blank">http://www.pymvpa.org/<wbr>generated/mvpa2.algorithms.<wbr>group_clusterthr.<wbr>GroupClusterThreshold.html</a> </div></div></div></div>
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