Coexistence of asynchronous and clustered dynamics in noisy inhibitory neural networks

Fuente: arXiv
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Hauptverfasser: Feld, Yannick, Hartmann, Alexander K., Torcini, Alessandro
Format: Preprint
Veröffentlicht: 2024
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author Feld, Yannick
Hartmann, Alexander K.
Torcini, Alessandro
author_facet Feld, Yannick
Hartmann, Alexander K.
Torcini, Alessandro
contents A regime of coexistence of asynchronous and clustered dynamics is analyzed for globally coupled homogeneous and heterogeneous inhibitory networks of quadratic integrate-and-fire (QIF) neurons subject to Gaussian noise. The analysis is based on accurate extensive simulations and complemented by a mean-field description in terms of low-dimensional next generation neural mass models for heterogeneously distributed synaptic couplings. The asynchronous regime is observable at low noise and becomes unstable via a sub-critical Hopf bifurcation at sufficiently large noise. This gives rise to a coexistence region between the asynchronous and the clustered regime. The clustered phase is characterized by population bursts in the γ-range (30-120 Hz), where neurons are split in two equally populated clusters firing in alternation. This clustering behaviour is quite peculiar: despite the global activity being essentially periodic, single neurons display switching between the two clusters due to heterogeneity and/or noise.
format Preprint
id arxiv_https___arxiv_org_abs_2402_06548
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Coexistence of asynchronous and clustered dynamics in noisy inhibitory neural networks
Feld, Yannick
Hartmann, Alexander K.
Torcini, Alessandro
Disordered Systems and Neural Networks
Neurons and Cognition
A regime of coexistence of asynchronous and clustered dynamics is analyzed for globally coupled homogeneous and heterogeneous inhibitory networks of quadratic integrate-and-fire (QIF) neurons subject to Gaussian noise. The analysis is based on accurate extensive simulations and complemented by a mean-field description in terms of low-dimensional next generation neural mass models for heterogeneously distributed synaptic couplings. The asynchronous regime is observable at low noise and becomes unstable via a sub-critical Hopf bifurcation at sufficiently large noise. This gives rise to a coexistence region between the asynchronous and the clustered regime. The clustered phase is characterized by population bursts in the γ-range (30-120 Hz), where neurons are split in two equally populated clusters firing in alternation. This clustering behaviour is quite peculiar: despite the global activity being essentially periodic, single neurons display switching between the two clusters due to heterogeneity and/or noise.
title Coexistence of asynchronous and clustered dynamics in noisy inhibitory neural networks
topic Disordered Systems and Neural Networks
Neurons and Cognition
url https://arxiv.org/abs/2402.06548