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Spatial distribution of heterogeneity as a modulator of collective dynamics in pancreatic beta-cell networks and beyond

Abstract:
We study the impact of spatial distribution of heterogeneity on collective dynamics in gap-junction coupled beta-cell networks comprised on cells from two populations that differ in their intrinsic excitability. Initially, these populations are uniformly and randomly distributed throughout the networks. We develop and apply an iterative algorithm for perturbing the arrangement of the network such that cells from the same population are increasingly likely to be adjacent to one another. We find that the global input strength, or network drive, necessary to transition the network from a state of quiescence to a state of synchronised and oscillatory activity decreases as network sortedness increases. Moreover, for weak coupling, we find that regimes of partial synchronisation and wave propagation arise, which depend both on network drive and network sortedness. We then demonstrate the utility of this algorithm for studying the distribution of heterogeneity in general networks, for which we use Watts–Strogatz networks as a case study. This work highlights the importance of heterogeneity in node dynamics in establishing collective rhythms in complex, excitable networks and has implications for a wide range of real-world systems that exhibit such heterogeneity.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.3389/fnetp.2023.1170930

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Institution:
University of Oxford
Division:
MSD
Department:
Radcliffe Department of Medicine
Sub department:
RDM-Oxford Centre for Diabetes, Endocrinology and Metabolism
Oxford college:
Green Templeton College
Role:
Author
ORCID:
0000-0002-8641-8568
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Role:
Author
ORCID:
0000-0002-8109-2765


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Funder identifier:
https://ror.org/050rgn017
Grant:
22/0006389
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Funder identifier:
https://ror.org/001aqnf71
Grant:
EP/X026833/1
More from this funder
Funder identifier:
https://ror.org/0439y7842
Grant:
EP/N014391/2


Publisher:
Frontiers Media
Journal:
Frontiers in Network Physiology More from this journal
Volume:
3
Article number:
1170930
Place of publication:
Switzerland
Publication date:
2023-03-24
Acceptance date:
2023-03-17
DOI:
EISSN:
2674-0109
Pmid:
36987428


Language:
English
Keywords:
Pubs id:
1585273
Local pid:
pubs:1585273
Deposit date:
2024-12-13
ARK identifier:

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