Predicting Functional Connectivity From Observed and Latent Structural Connectivity via Eigenvalue Mapping

Understanding how complex dynamic activity propagates over a static structural network is an overarching question in the field of neuroscience. Previous work has demonstrated that linear graph-theoretic models perform as well as non-linear neural simulations in predicting functional connectivity wit...

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Autori principali:	Jennifer A. Cummings, Benjamin Sipes, Daniel H. Mathalon, Ashish Raj
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	Frontiers Media S.A. 2022-03-01
Serie:	Frontiers in Neuroscience
Soggetti:	BOLD fMRI functional connectivity structural connectivity spectral graph theory eigenvalue decomposition network diffusion model
Accesso online:	https://www.frontiersin.org/articles/10.3389/fnins.2022.810111/full
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