Simulations approaching data: cortical slow waves in inferred models of the whole hemisphere of mouse.
Journal
Communications biology
ISSN: 2399-3642
Titre abrégé: Commun Biol
Pays: England
ID NLM: 101719179
Informations de publication
Date de publication:
13 03 2023
13 03 2023
Historique:
received:
16
06
2022
accepted:
10
02
2023
entrez:
14
3
2023
pubmed:
15
3
2023
medline:
16
3
2023
Statut:
epublish
Résumé
The development of novel techniques to record wide-field brain activity enables estimation of data-driven models from thousands of recording channels and hence across large regions of cortex. These in turn improve our understanding of the modulation of brain states and the richness of traveling waves dynamics. Here, we infer data-driven models from high-resolution in-vivo recordings of mouse brain obtained from wide-field calcium imaging. We then assimilate experimental and simulated data through the characterization of the spatio-temporal features of cortical waves in experimental recordings. Inference is built in two steps: an inner loop that optimizes a mean-field model by likelihood maximization, and an outer loop that optimizes a periodic neuro-modulation via direct comparison of observables that characterize cortical slow waves. The model reproduces most of the features of the non-stationary and non-linear dynamics present in the high-resolution in-vivo recordings of the mouse brain. The proposed approach offers new methods of characterizing and understanding cortical waves for experimental and computational neuroscientists.
Identifiants
pubmed: 36914748
doi: 10.1038/s42003-023-04580-0
pii: 10.1038/s42003-023-04580-0
pmc: PMC10011502
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
266Informations de copyright
© 2023. The Author(s).
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