<div dir="ltr"><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">Thanks Jan-Mathijs. I have the following questions: </div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small"><br></div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">1. So minnbchan is only for the data in the sensor space, correct? </div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">2. If so, is the 'cluster' method available at all for data in the source space as a means of multiple comparisons correction? </div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small"><br></div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">Basically I was wondering if I can run a cluster-based permutation t-test on the source-level data. For example, I might want to average brain activities across all the vertices within an ROI, get a timeseries, and then do a permutation t-test on it such that a cluster is formed if a t-statistic is above a certain threshold at least for, say, 5 contiguous time samples. (This is a temporal clustering test, and one might want to do a spatio-temporal clustering test where a cluster is formed if an above-threshold statistic is found for N adjacent time samples and M adjacent vertices, etc). </div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small"><br></div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">I hope I explained my question more clearly. Thanks! </div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small"><br></div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">Best,</div><div class="gmail_default" style="font-family:tahoma,sans-serif;font-size:small">Songhee</div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Wed, Nov 24, 2021 at 7:16 AM Schoffelen, J.M. (Jan Mathijs) via fieldtrip <<a href="mailto:fieldtrip@science.ru.nl">fieldtrip@science.ru.nl</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">
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Hi Songhee,
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<div>I don’t know whether I fully understand your question, but I think that such option does not exist. The option minnbchan only exists (and is functional) for channel level data, in order to define the minimum number of suprathreshold neighbouring
channels. Across the time and frequency etc. dimension the spatial neighbourhood is implicit in the consecutive time/freq points, so each sample by definition only has 2 neighbours (one on either side).</div>
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<div>Note that minnbchan will not work for ft_sourcestatistics, as far as I know.</div>
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<div>Best wishes,</div>
<div>Jan-Mathijs</div>
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<div>On 11 Nov 2021, at 01:17, Songhee Kim via fieldtrip <<a href="mailto:fieldtrip@science.ru.nl" target="_blank">fieldtrip@science.ru.nl</a>> wrote:</div>
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Hi folks,</div>
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I wonder if a cluster-based permutation test <b>with respect to the temporal dimension</b> is implemented in Fieldtrip. I can see that there is an option to set a minimal number of channels to form a cluster (i.e., <span style="font-family:Arial,Helvetica,sans-serif">minnbchan)
when running</span> ft_sourcestatistics<span style="font-family:Arial,Helvetica,sans-serif">. Is there a similar option for the temporal dimension? Any help would be appreciated! </span></div>
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<span style="font-family:Arial,Helvetica,sans-serif">Best,</span></div>
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<span style="font-family:Arial,Helvetica,sans-serif">Songhee </span></div>
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<div style="font-size:12.8px"><font color="#444444"><b>Songhee Kim, PhD</b><br>
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<div style="font-size:12.8px"><font color="#444444">Postdoctoral Fellow</font></div>
<div style="font-size:12.8px"><font color="#444444">Department of Neurology</font></div>
<div style="font-size:12.8px"><font color="#444444">Medical College of Wisconsin</font></div>
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</blockquote></div><br clear="all"><div><br></div>-- <br><div dir="ltr" class="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div style="color:rgb(0,0,0);font-size:12.8px"><font color="#676767"><b>Songhee Kim, PhD</b><br></font></div><div style="font-size:12.8px"><font color="#676767">Postdoctoral Fellow</font></div><div style="font-size:12.8px"><font color="#676767">Department of Neurology</font></div><div style="color:rgb(0,0,0);font-size:12.8px">Medical College of Wisconsin</div><div style="color:rgb(0,0,0);font-size:12.8px"></div></div></div></div></div></div></div>