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posted on 2016-12-21, 18:53 authored by Jun-ichiro Hirayama, Aapo Hyvärinen, Vesa Kiviniemi, Motoaki Kawanabe, Okito Yamashita(a) Root mean squared error (RMSE) between true and estimated B of first component versus sample size N (in log scale). Left panel: only inter-module connectivity between two modules varied. Right panel: both intra-module and inter-module connectivities varied. Each plot shows mean RMSE of 100 runs, where error bars indicate sample standard deviations in each side. Four methods are shown with different colors and marker symbols. (b) Identical as above but for second component.
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results show986 subjectseigenconnectivity matricesConstrained Principal Component Analysisconnectivity MRI datasetdata-driven mannerinter-module connectivitiesmodule-based visualization schemeconnectivity matriceseigenconnectivity patternshigh-dimensional connectivity matrices yieldsPrincipal component analysisconnectivity factorizationbrain connectivityoptimization algorithmPCA problemMCF methodorthogonal connectivity factorization methodnetwork modulesbrain networksPCA methodsimulation studiesModular Brain Connectivity