Network structure and time delays shape synchronization patterns in brain network models

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Pinder, I ORCID: https://orcid.org/0009-0006-3009-5751, Nelson, MR ORCID: https://orcid.org/0000-0001-5320-2464 and Crofts, JJ ORCID: https://orcid.org/0000-0001-7751-9984, 2024. Network structure and time delays shape synchronization patterns in brain network models. Chaos: an Interdisciplinary Journal of Nonlinear Science, 34 (12): 123123. ISSN 1054-1500

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Official URL: https://doi.org/10.1063/5.0228813

Abstract

In this paper, we investigate synchronization patterns and coherence for a network of delayed Wilson–Cowan nodes. To capture information processing across different brain regions, our model incorporates two distinct delays: an intra-nodal delay that reflects the time signals take to travel within a cortical region due to local circuitry and an inter-nodal delay representing the longer communication times associated with white matter connections between brain areas. To investigate the role of network topology, we consider a range of toy network structures as well as the known (macro-scale) cortical structure of the Macaque monkey. We examine how global network dynamics are shaped by a combination of network configuration, coupling strength, and time delays. Our focus lies on two dynamic measures: synchrony and metastability, the latter reflecting the temporal variation of the former, both crucial for the brain’s real-time functionality. Our investigation identifies extensive regions within the system’s parameter space where the synchronized state exhibits transverse instabilities. These instabilities give rise to diverse dynamical behaviors contingent upon the network architecture and the interplay between coupling strength and time delay. While similar complex partially synchronized states existed for all network topologies considered, the cortical network demonstrated time-dependent behaviors, such as phase cluster dynamics, which were absent in the toy network architectures, and which are considered crucial in its ability to orchestrate complex information processing and behavior. Additionally, we illustrate how delays can regulate a cortical network with chaotic local dynamics, thus emphasizing the potential importance of delays in suppressing pathological spreading dynamics.

Item Type:	Journal article
Publication Title:	Chaos: an Interdisciplinary Journal of Nonlinear Science
Creators:	Pinder, I., Nelson, M.R. and Crofts, J.J.
Publisher:	AIP Publishing
Date:	1 December 2024
Volume:	34
Number:	12
ISSN:	1054-1500
Identifiers:	Number Type 10.1063/5.0228813 DOI 2312527 Other
Rights:	This article may be downloaded for personal use only. Any other use requires prior permission of the author and AIP Publishing. This article appeared in PINDER, I. , NELSON, M.R. and CROFTS, J.J. , 2024. Network structure and time delays shape synchronization patterns in brain network models. Chaos: an Interdisciplinary Journal of Nonlinear Science, 34 (12): 123123) and may be found at https://doi.org/10.1063/5.0228813
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	04 Dec 2024 16:22
Last Modified:	04 Dec 2024 16:22
URI:	https://irep.ntu.ac.uk/id/eprint/52699