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Thank you, Paolo! This is very helpful!</div>
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Best,</div>
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Eniko</div>
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<p style="margin-top: 0px; margin-bottom: 0px;margin-top:0; margin-bottom:0"><span style="font-size:12pt">Eniko Ladanyi, Ph.D.<span style="color:rgb(114,50,173)"></span></span></p>
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<div id="divRplyFwdMsg" dir="ltr"><font face="Calibri, sans-serif" color="#000000" style="font-size:11pt"><b>From:</b> fieldtrip <fieldtrip-bounces@science.ru.nl> on behalf of Paolo Belardinelli <paolo.belardinelli@gmail.com><br>
<b>Sent:</b> Thursday, March 4, 2021 2:02 PM<br>
<b>To:</b> FieldTrip discussion list <fieldtrip@science.ru.nl><br>
<b>Subject:</b> Re: [FieldTrip] source-level cluster analysis?</font>
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<div class="x_gmail_default" style="font-size:large">Hi Eniko.</div>
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<div class="x_gmail_default" style="font-size:large">You might check this out:</div>
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<div class="x_gmail_default" style="font-size:large"><a href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.fieldtriptoolbox.org%2Fexample%2Fsource_statistics%2F&data=04%7C01%7Ceniko.ladanyi%40vumc.org%7C7ca941d103a64bf0927108d8df4894c0%7Cef57503014244ed8b83c12c533d879ab%7C0%7C1%7C637504850130270558%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=L5FRsfjl29oIrmwRFat9KKi39qRYTXgQ4%2F3HvZrIEuU%3D&reserved=0" originalsrc="https://www.fieldtriptoolbox.org/example/source_statistics/" shash="Ec+4/tX5MBcTZ0WXMFlySJbIKKVIxo9G0yV6V+uVDf+oNtY9uJYUSO5cXf80BDhMj6EhQFevkRH3D8M0GHe20Ce9B36xqUIFoAtcglqPcydIGb2yaL4r5QX8jMuL06e6NQ2ghZgBVU63SoDZ9GhRWG9bekZogVPyvRS193MvEzI=">https://www.fieldtriptoolbox.org/example/source_statistics/</a><br>
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<div class="x_gmail_default" style="font-size:large">I would add that in my experience a strong significance at sensor does not imply a significance at source. </div>
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<div class="x_gmail_default" style="font-size:large">Best wishes,</div>
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<div class="x_gmail_default" style="font-size:large">Paolo</div>
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<div dir="ltr" class="x_gmail_attr">On Thu, Mar 4, 2021 at 8:13 PM Ladanyi, Eniko <<a href="mailto:eniko.ladanyi@vumc.org">eniko.ladanyi@vumc.org</a>> wrote:<br>
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Hi all,<u></u> <u></u></p>
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<u></u> <u></u></p>
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I am analyzing an MEG dataset in which I only have access to source-level data. I ran cluster-based permutation tests on the data with pre-defined ROI-s but I was wondering if it would make sense not to pre-define ROI-s but search for spatial clusters with
a cluster-based permutation test. I’m not familiar enough with MEG, so I can’t decide if the features of source-level data would allow me to run the cluster analysis the same way described here for sensor-level data<span style="background-color:rgb(255,255,255); display:inline">: </span><a href="https://nam12.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.fieldtriptoolbox.org%2Ftutorial%2Fcluster_permutation_freq%2F&data=04%7C01%7Ceniko.ladanyi%40vumc.org%7C7ca941d103a64bf0927108d8df4894c0%7Cef57503014244ed8b83c12c533d879ab%7C0%7C1%7C637504850130280553%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000&sdata=Jm36KzjU6sa3kvQApqvd%2FZXW2iKK%2FN6Fz1jaIOiQyfQ%3D&reserved=0" originalsrc="https://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/" shash="F8whmOvGMzBYTzuXbzQ7nc2fR06iky+6kffO+fh4I9WhKcAdfD+yg24drw80ehOaka7tI8ZXm5ANIApXrLb757p3v1c8u1CXZmr0RbNWyD6+1QzA/z1BfvKCUrGh/CpdREHTspeSXjRkzixUodWTs0mxDQDTx4vUZ2/NHQPGgpY=" target="_blank">https://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq/</a>.<u></u> <u></u></p>
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Would cluster-based permutation test work as well with source-level data as with sensor-level data? If so, what kind of layout file should I use? Positions of sensors/electrodes can be defined with two coordinates but sources can be only defined with three
coordinates.<u></u> <u></u></p>
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<u></u> <u></u></p>
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Thanks so much in advance for any advice!<u></u> <u></u></p>
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<u></u> <u></u></p>
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Best,<u></u> <u></u></p>
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<u></u> <u></u></p>
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Eniko<u></u> <u></u></p>
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<p style="margin-top:0px; margin-bottom:0px"><span style="color:rgb(117,123,128)">*********************</span></p>
<p style="margin-top:0px; margin-bottom:0px"><span style="font-size:12pt">Eniko Ladanyi, Ph.D.<span style="color:rgb(114,50,173)"></span></span></p>
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