Inferring structural connectivity using Ising couplings in models of neuronal networks
Abstract Functional connectivity metrics have been widely used to infer the underlying structural connectivity in neuronal networks. Maximum entropy based Ising models have been suggested to discount the effect of indirect interactions and give good results in inferring the true anatomical connectio...
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Auteurs principaux: | Balasundaram Kadirvelu, Yoshikatsu Hayashi, Slawomir J. Nasuto |
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Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2017
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Accès en ligne: | https://doaj.org/article/b195e15f002a4a339ee62c6324e0909c |
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