Characterizing Network Search Algorithms Developed for Dynamic Causal Modeling

Characterizing Network Search Algorithms Developed for Dynamic Causal Modeling

Dynamic causal modeling (DCM) is a widely used tool to estimate the effective connectivity of specified models of a brain network. Finding the model explaining measured data is one of the most important outstanding problems in Bayesian modeling. Using heuristic model search algorithms enables us to...

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Bibliographic Details
Main Authors: Sándor Csaba Aranyi, Marianna Nagy, Gábor Opposits, Ervin Berényi, Miklós Emri
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Neuroinformatics
Subjects:
fMRI
dynamic causal modeling
search algorithm
network topology
model-space
Online Access:https://www.frontiersin.org/articles/10.3389/fninf.2021.656486/full

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https://www.frontiersin.org/articles/10.3389/fninf.2021.656486/full

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