<html><head></head><body>I would say it all depends on many factors, such as problem at hand, classifier, etc. So not sure if anything systematic and actually generically useful could be done/stated. But have a look may be at Jo's paper.<br><br>Etzel JA, Zacks JM, Braver TS. Searchlight analysis: Promise, pitfalls, and potential. Neuroimage. 2013. PMCID: PMC3988828<br><br><div class="gmail_quote">On October 8, 2018 7:55:43 AM EDT, Alyson Saenz <neuro.alyson@gmail.com> wrote:<blockquote class="gmail_quote" style="margin: 0pt 0pt 0pt 0.8ex; border-left: 1px solid rgb(204, 204, 204); padding-left: 1ex;">
<div dir="ltr">Dear PyMVPA community,<div><br></div><div>Does anyone know a paper in which someone has explored the effect of different searchlight radius?</div><div><br></div><div>I know that a bigger radius increases performance but also processing time, and that at some point you will get bad performances, but, has anyone systematically explored this?</div><div><br></div><div>Thanks for your help</div><div><br></div><div>Alyson</div><div><br></div><div><br></div><div><div><br></div><div><br></div></div></div>
</blockquote></div><br>-- <br>Yaroslav O. Halchenko (mobile version)<br>Center for Open Neuroscience <a href="http://centerforopenneuroscience.org">http://centerforopenneuroscience.org</a><br>Dartmouth College, NH, USA<br></body></html>