<div dir="ltr"><div><div>Dear Yi-hui<br><br>Decoding is generally not really adapted for mix-designed, as the models are traditionally fit at the single subject level - i.e. your model cannot be easily optimized to look for an across-subject effect. <br></div><div><br></div><div>You can however compare the decoding scores across subjects/conditions as a first approximation, and specify individual subjects' score as your random variable. <br></div><div><br></div><div>For multifactorial within-subject effects, a simple approach can be to implement RSA; we recently added this example in MNE:</div><div><a href="https://mne-tools.github.io/stable/auto_examples/decoding/decoding_rsa.html">https://mne-tools.github.io/stable/auto_examples/decoding/decoding_rsa.html</a></div><div><br></div><div>I will refer you to Kriegoskorte's RSA papers to see how you adapt this analysis to your specific needs,<br></div><div><br></div><div></div>Kindest regards,<br><br></div>Jean-Rémi<br></div><div class="gmail_extra"><br><div class="gmail_quote">On 18 December 2017 at 02:05, Yi-hui Hung <span dir="ltr"><<a href="mailto:vedahung1116@gmail.com" target="_blank">vedahung1116@gmail.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">Hello MNE experts,<div><span style="color:rgb(36,39,41);font-family:Arial,"Helvetica Neue",Helvetica,sans-serif"><br></span></div><div><span style="color:rgb(36,39,41);font-family:Arial,"Helvetica Neue",Helvetica,sans-serif">I have MEG data with two within-subject factors (each having 2 and 3 levels) and one between-subject factor (2 levels).</span><span style="color:rgb(36,39,41);font-family:Arial,"Helvetica Neue",Helvetica,sans-serif"> I </span>performed decoding analysis on my MEG data by using the function " time_decod.fit". The question is how to perform group analysis in subject's decoding data in MNE (or outside MNE) for my mixed design (2 x 3 x 2 factorial design). Besides, I have another dependent variable by using "predict_proba" function to get the predicting probability. I want to test whether the distribution of predicting probability differ according to my design. Whether the difference of the distribution continues in time (e.g., 200-300ms after stimulus onset) does not matter. Suggestions will be appreciated.</div><div> </div></div>
<br>______________________________<wbr>_________________<br>
Mne_analysis mailing list<br>
<a href="mailto:Mne_analysis@nmr.mgh.harvard.edu">Mne_analysis@nmr.mgh.harvard.<wbr>edu</a><br>
<a href="https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis" rel="noreferrer" target="_blank">https://mail.nmr.mgh.harvard.<wbr>edu/mailman/listinfo/mne_<wbr>analysis</a><br>
<br>
<br>
The information in this e-mail is intended only for the person to whom it is<br>
addressed. If you believe this e-mail was sent to you in error and the e-mail<br>
contains patient information, please contact the Partners Compliance HelpLine at<br>
<a href="http://www.partners.org/complianceline" rel="noreferrer" target="_blank">http://www.partners.org/<wbr>complianceline</a> . If the e-mail was sent to you in error<br>
but does not contain patient information, please contact the sender and properly<br>
dispose of the e-mail.<br>
<br></blockquote></div><br></div>