Heteroclinic networks for brain dynamics.
binding problem
brain dynamics
chunking dynamics
cognitive processes
generalized Lotka–Volterra equations
heteroclinic networks
information processing
metastable states
Journal
Frontiers in network physiology
ISSN: 2674-0109
Titre abrégé: Front Netw Physiol
Pays: Switzerland
ID NLM: 9918334487406676
Informations de publication
Date de publication:
2023
2023
Historique:
received:
11
08
2023
accepted:
16
10
2023
medline:
29
11
2023
pubmed:
29
11
2023
entrez:
29
11
2023
Statut:
epublish
Résumé
Heteroclinic networks are a mathematical concept in dynamic systems theory that is suited to describe metastable states and switching events in brain dynamics. The framework is sensitive to external input and, at the same time, reproducible and robust against perturbations. Solutions of the corresponding differential equations are spatiotemporal patterns that are supposed to encode information both in space and time coordinates. We focus on the concept of winnerless competition as realized in generalized Lotka-Volterra equations and report on results for binding and chunking dynamics, synchronization on spatial grids, and entrainment to heteroclinic motion. We summarize proposals of how to design heteroclinic networks as desired in view of reproducing experimental observations from neuronal networks and discuss the subtle role of noise. The review is on a phenomenological level with possible applications to brain dynamics, while we refer to the literature for a rigorous mathematical treatment. We conclude with promising perspectives for future research.
Identifiants
pubmed: 38020242
doi: 10.3389/fnetp.2023.1276401
pii: 1276401
pmc: PMC10663269
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
1276401Informations de copyright
Copyright © 2023 Meyer-Ortmanns.
Déclaration de conflit d'intérêts
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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