<p><span style="padding: 3px 10px; border-radius: 5px; color: #ffffff; font-weight: bold; display: inline-block; background-color: #ff0000;"> External Email - Use Caution </span></p><p></p><div dir="ltr"><div>Hi,</div><div>Thank you very much for your reply,</div><div>Yes, I need
to reconstruct the average from 80 to 120ms (to average the whole-head source estimates over time - in this example, 40 time points at sampling rate of 1000 Hz).</div><div>Irina.<br>
</div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Mon, Oct 21, 2019 at 4:08 PM Alexandre Gramfort <<a href="mailto:alexandre.gramfort@inria.fr">alexandre.gramfort@inria.fr</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><p><span style="padding:3px 10px;border-radius:5px;color:rgb(255,255,255);font-weight:bold;display:inline-block;background-color:rgb(255,0,0)"> External Email - Use Caution </span></p><p></p><div dir="ltr"><div dir="ltr">hi,</div><br><div class="gmail_quote"><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div>I am a new MNE Python user, so excuse me for trivial questions.</div><div>1. Is it possible to reconstruct the source for an integrated time window (e.g., for the auditory N1, from 80 to 120 ms), in order to use the same time window for the comparison among experimental conditions (e.g., attention vs. no attention)?</div></div></blockquote><div><br></div><div>what do you mean by this? reconstruct the average from 80 to 120ms?</div><div>if you just want to limit what you reconstruct you can use Evoked.crop method.</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div>2. If yes, how to extract the time course of this source, and then to obtain peak latency and coordinates of a peak vertex, and the amplitude value for the estimated time window?</div></div></blockquote><div><br></div><div>stc have data (time courses) and vertnos to know to which cortical vertex it corresponds to.</div><div> </div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex"><div dir="ltr"><div>3. How to get a grand average for these source estimates?</div></div></blockquote><div><br></div><div>grand average over subject? you need to morph the stcs to fsaverage.</div><div><br></div><div>these tutorials should help : <a href="https://mne.tools/stable/auto_tutorials/index.html#source-modeling" target="_blank">https://mne.tools/stable/auto_tutorials/index.html#source-modeling</a></div><div><br></div><div>HTH</div><div>Alex</div><div> </div></div></div>
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