The MATLAB code we used to run the standard community-detection algorithm [14, 21] to quantify phase modularity (at each time point per frequency per condition per participant) as the index q (maximized modularity; 0 ≤ q ≤ 1).
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posted on 2024-02-12, 18:24 authored by Melisa Menceloglu, Marcia Grabowecky, Satoru SuzukiThe MATLAB code we used to run the standard community-detection algorithm [14, 21] to quantify phase modularity (at each time point per frequency per condition per participant) as the index q (maximized modularity; 0 ≤ q ≤ 1).
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silent nature videodifferent behavioral conditionsdespite ample knowledgeangles (| δθfundamental functional rolelarge phase lagsglobal phase relationsdiv >< pspecific functional networksnetwork comprising anteriorfunctional rolesspecific behaviorsposterior networkdependent networksregional phasephase modularitytop 5synchronized clustersstandard communityshifting anteriorremarkably simpleq prior researchpower correlationsposterior longoscillatory activityone anotherneural interactionsneural correlatesmodularity statesgeneral rulesgamma bandseyes closeddetection algorithmconsistently elevatedbroad rangebottom 5>), accounting
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