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
Published in:	Frontiers in neuroinformatics Vol. 15; p. 656486
Main Authors:	Aranyi, Sándor Csaba, Nagy, Marianna, Opposits, Gábor, Berényi, Ervin, Emri, Miklós
Format:	Journal Article
Language:	English
Published:	Lausanne Frontiers Research Foundation 10.06.2021 Frontiers Media S.A
Subjects:	Algorithms Approximation Bayesian analysis Brain mapping Computational neuroscience dynamic causal modeling Efficiency fMRI Functional magnetic resonance imaging Hypotheses Mathematical models Methods model-space Nervous system Network management systems network topology Neural networks Neuroscience Performance evaluation Physiology search algorithm Statistical analysis
ISSN:	1662-5196, 1662-5196
Online Access:	Get full text
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