Experimental validation of the free-energy principle with in vitro neural networks.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
07 08 2023
07 08 2023
Historique:
received:
12
10
2022
accepted:
13
07
2023
medline:
9
8
2023
pubmed:
8
8
2023
entrez:
7
8
2023
Statut:
epublish
Résumé
Empirical applications of the free-energy principle are not straightforward because they entail a commitment to a particular process theory, especially at the cellular and synaptic levels. Using a recently established reverse engineering technique, we confirm the quantitative predictions of the free-energy principle using in vitro networks of rat cortical neurons that perform causal inference. Upon receiving electrical stimuli-generated by mixing two hidden sources-neurons self-organised to selectively encode the two sources. Pharmacological up- and downregulation of network excitability disrupted the ensuing inference, consistent with changes in prior beliefs about hidden sources. As predicted, changes in effective synaptic connectivity reduced variational free energy, where the connection strengths encoded parameters of the generative model. In short, we show that variational free energy minimisation can quantitatively predict the self-organisation of neuronal networks, in terms of their responses and plasticity. These results demonstrate the applicability of the free-energy principle to in vitro neural networks and establish its predictive validity in this setting.
Identifiants
pubmed: 37550277
doi: 10.1038/s41467-023-40141-z
pii: 10.1038/s41467-023-40141-z
pmc: PMC10406890
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4547Subventions
Organisme : Wellcome Trust
Pays : United Kingdom
Informations de copyright
© 2023. The Author(s).
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