<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><meta http-equiv="Content-Type" content="text/html; charset=utf-8" class=""><div style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">Dear Yijun, also CC to the FieldTrip mailing list<div class=""><br class=""></div><div class="">The FieldTrip plotting functions - but also the way we prefer to plot the results - have changed over the years. The ft_clusterplot function is limited in how it can plot the data: the sequence of topographies have to be averaged either over time, or over frequency. And if you have channel*time*frequency data, averaging over time or frequency collapses the cluster in that dimension. In that case the details of the cluster in that dimension get lost, e.g. when averaging over frequencies you would loose information that for low frequencies the cluster might span different channels than for high frequencies. </div><div class=""><br class=""></div><div class="">Rather than ft_clusterplot, I recommend that you write your own for-loop, and use ft_selectdata with avgovertime or avgoverfreq (and keeptimedim=no or keepfreqdim=no, please see the code for that) to average your selections and plot those using ft_topoplotER. After averaging over a dimension, you will see that stat.mask is not 0 or 1 any more, but also can be a number in between if it is not part of the cluster all the time (or for all ferquencies). </div><div class=""><br class=""></div><div class="">But also please note this FAQ <a href="http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test/" class="">http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test/</a> and don’t overinterpret the clusters.</div><div class=""><br class=""></div><div class="">best regards,</div><div class="">Robert </div><div class=""><br class=""></div><div class="">PS please address folow-up questions regarding the use of FieldTrip on its <a href="http://www.fieldtriptoolbox.org/discussion_list/" class="">http://www.fieldtriptoolbox.org/discussion_list/</a>. There are a lot of knowledgeable people on it that can help.</div><div class=""><br class=""><div class=""><br class=""><blockquote type="cite" class=""><div class="">On 30 Jan 2020, at 00:31, Yijun Ge <xxx> wrote:</div><br class="Apple-interchange-newline"><div class=""><meta http-equiv="Content-Type" content="text/html; charset=utf-8" class=""><div dir="ltr" class="">Hi Eric and Robert,<div class=""> I hope this email finds you well! </div><div class=""> My name is Yijun, a PhD student in the University of Minnesota. I have recently read your 2007 Journal of Neuroscience paper "Nonparametric statistical testing of EEG- and MEG- data". This paper is wonderful and helps me a lot! I am kind of new to this field and recently working on my own MEG project and try to do the permutation test using Fieldtrip. </div><div class=""> There is one question about the permutation test results on (sensor, freq, time)-samples. In the paper, you did the permutation test across different frequencies and found the clusters were in the 15-30Hz. And Fig4 showed the topography of significant cluster averaged over 15-30Hz. </div><div class=""> But when I tried similar procedure and got stats results, functions like ft_clusterplot only allows singleton dimension of frequency. Should I average the stats result across frequency band? (The significant cluster were shown as 0/1 in a 3D matrix).</div><div class=""> I would appreciate it a lot if you could give me some guidance! Many thanks.</div><div class="">Best,</div><div class="">Yijun Ge</div><div class="">Department of Psychology</div><div class="">University of Minnesota</div><div class="">6514408588</div></div>
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