Article

Dynamics of Functional Network Organization Through Graph Mixture Learning

2021-05-26

Abstract excerpt

Understanding the organizational principles of human brain activity at the systems level remains a major challenge in network neuroscience. Here, we introduce a fully data-driven approach based on graph learning to extract meaningful repeating network patterns from regionally-averaged time-courses. We use the Graph Laplacian Mixture Model (GLMM), a generative model that treats functional data as a collection of si...

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Literature Corpus work: b2a74904-e50d-55b7-8315-ca9e8bbd53ef
DOI: 10.1101/2021.05.25.445303

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