<div dir="ltr"><div dir="ltr">Hi<div><br></div><div>you should first reconstruct the sources from sensors recordings (EEGlab or other toolboxes can do so). Then for the network part you can use several toolboxes, starting from the Brain Connectivity Toolbox (<a href="https://sites.google.com/site/bctnet/">https://sites.google.com/site/bctnet/</a>) and the Network Based Statistics Toolbox within.</div><div><br></div><div>This for the practical part. But the interpretation is tricky and there are many possible confounders (the mixing from the sources to the scalp, the precision of reconstructing hundred of sources, etc). So please be careful.</div><div><br></div><div>best regards</div></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Feb 6, 2019 at 8:35 AM Sadatnejad <<a href="mailto:sadatnejad@aut.ac.ir">sadatnejad@aut.ac.ir</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"><div dir="" style="font-size:10pt;font-family:"Source Sans Pro",sans-serif;background-image:none;background-repeat:repeat"><div>​Dear all,</div><div><br></div><div>I have a EEG dataset composed of two classes. I should analyze it from Brain networking point of view (DMN, TPN,...) and investigate the difference between its groups. I'm beginner in network analysis of EEG. Do you have any tool box for this purpose under Matlab or Python?</div><div>Thank you in advance!<br></div><div>Regards</div></div><pre>--
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