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Dynamics of a large system of spiking neurons with synaptic delay

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Dynamics of a large system of spiking neurons with synaptic delay. / Devalle, Federico; Montbrió, Ernest; Pazó, Diego.
In: Physical Review E, Vol. 98, No. 4, 042214, 22.10.2018.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Devalle, F, Montbrió, E & Pazó, D 2018, 'Dynamics of a large system of spiking neurons with synaptic delay', Physical Review E, vol. 98, no. 4, 042214. https://doi.org/10.1103/PhysRevE.98.042214

APA

Devalle, F., Montbrió, E., & Pazó, D. (2018). Dynamics of a large system of spiking neurons with synaptic delay. Physical Review E, 98(4), Article 042214. https://doi.org/10.1103/PhysRevE.98.042214

Vancouver

Devalle F, Montbrió E, Pazó D. Dynamics of a large system of spiking neurons with synaptic delay. Physical Review E. 2018 Oct 22;98(4):042214. doi: 10.1103/PhysRevE.98.042214

Author

Devalle, Federico ; Montbrió, Ernest ; Pazó, Diego. / Dynamics of a large system of spiking neurons with synaptic delay. In: Physical Review E. 2018 ; Vol. 98, No. 4.

Bibtex

@article{8ffba897a6e2444e9b7725467dc83121,
title = "Dynamics of a large system of spiking neurons with synaptic delay",
abstract = "We analyze a large system of heterogeneous quadratic integrate-and-fire (QIF) neurons with time delayed, all-to-all synaptic coupling. The model is exactly reduced to a system of firing rate equations that is exploited to investigate the existence, stability, and bifurcations of fully synchronous, partially synchronous, and incoherent states. In conjunction with this analysis we perform extensive numerical simulations of the original network of QIF neurons, and determine the relation between the macroscopic and microscopic states for partially synchronous states. The results are summarized in two phase diagrams, for homogeneous and heterogeneous populations, which are obtained analytically to a large extent. For excitatory coupling, the phase diagram is remarkably similar to that of the Kuramoto model with time delays, although here the stability boundaries extend to regions in parameter space where the neurons are not self-sustained oscillators. In contrast, the structure of the boundaries for inhibitory coupling is different, and already for homogeneous networks unveils the presence of various partially synchronized states not present in the Kuramoto model: Collective chaos, quasiperiodic partial synchronization (QPS), and a novel state which we call modulated-QPS (M-QPS). In the presence of heterogeneity partially synchronized states reminiscent to collective chaos, QPS and M-QPS persist. In addition, the presence of heterogeneity greatly amplifies the differences between the incoherence stability boundaries of excitation and inhibition. Finally, we compare our results with those of a traditional (Wilson Cowan-type) firing rate model with time delays. The oscillatory instabilities of the traditional firing rate model qualitatively agree with our results only for the case of inhibitory coupling with strong heterogeneity. {\textcopyright} 2018 American Physical Society.",
keywords = "Neurons, Phase diagrams, Time delay, Heterogeneous populations, Homogeneous network, Macroscopic and microscopic, Oscillatory instability, Partial synchronization, Self-sustained oscillators, Stability boundaries, Strong heterogeneities, Synchronization",
author = "Federico Devalle and Ernest Montbri{\'o} and Diego Paz{\'o}",
year = "2018",
month = oct,
day = "22",
doi = "10.1103/PhysRevE.98.042214",
language = "English",
volume = "98",
journal = "Physical Review E",
issn = "2470-0045",
publisher = "American Physical Society",
number = "4",

}

RIS

TY - JOUR

T1 - Dynamics of a large system of spiking neurons with synaptic delay

AU - Devalle, Federico

AU - Montbrió, Ernest

AU - Pazó, Diego

PY - 2018/10/22

Y1 - 2018/10/22

N2 - We analyze a large system of heterogeneous quadratic integrate-and-fire (QIF) neurons with time delayed, all-to-all synaptic coupling. The model is exactly reduced to a system of firing rate equations that is exploited to investigate the existence, stability, and bifurcations of fully synchronous, partially synchronous, and incoherent states. In conjunction with this analysis we perform extensive numerical simulations of the original network of QIF neurons, and determine the relation between the macroscopic and microscopic states for partially synchronous states. The results are summarized in two phase diagrams, for homogeneous and heterogeneous populations, which are obtained analytically to a large extent. For excitatory coupling, the phase diagram is remarkably similar to that of the Kuramoto model with time delays, although here the stability boundaries extend to regions in parameter space where the neurons are not self-sustained oscillators. In contrast, the structure of the boundaries for inhibitory coupling is different, and already for homogeneous networks unveils the presence of various partially synchronized states not present in the Kuramoto model: Collective chaos, quasiperiodic partial synchronization (QPS), and a novel state which we call modulated-QPS (M-QPS). In the presence of heterogeneity partially synchronized states reminiscent to collective chaos, QPS and M-QPS persist. In addition, the presence of heterogeneity greatly amplifies the differences between the incoherence stability boundaries of excitation and inhibition. Finally, we compare our results with those of a traditional (Wilson Cowan-type) firing rate model with time delays. The oscillatory instabilities of the traditional firing rate model qualitatively agree with our results only for the case of inhibitory coupling with strong heterogeneity. © 2018 American Physical Society.

AB - We analyze a large system of heterogeneous quadratic integrate-and-fire (QIF) neurons with time delayed, all-to-all synaptic coupling. The model is exactly reduced to a system of firing rate equations that is exploited to investigate the existence, stability, and bifurcations of fully synchronous, partially synchronous, and incoherent states. In conjunction with this analysis we perform extensive numerical simulations of the original network of QIF neurons, and determine the relation between the macroscopic and microscopic states for partially synchronous states. The results are summarized in two phase diagrams, for homogeneous and heterogeneous populations, which are obtained analytically to a large extent. For excitatory coupling, the phase diagram is remarkably similar to that of the Kuramoto model with time delays, although here the stability boundaries extend to regions in parameter space where the neurons are not self-sustained oscillators. In contrast, the structure of the boundaries for inhibitory coupling is different, and already for homogeneous networks unveils the presence of various partially synchronized states not present in the Kuramoto model: Collective chaos, quasiperiodic partial synchronization (QPS), and a novel state which we call modulated-QPS (M-QPS). In the presence of heterogeneity partially synchronized states reminiscent to collective chaos, QPS and M-QPS persist. In addition, the presence of heterogeneity greatly amplifies the differences between the incoherence stability boundaries of excitation and inhibition. Finally, we compare our results with those of a traditional (Wilson Cowan-type) firing rate model with time delays. The oscillatory instabilities of the traditional firing rate model qualitatively agree with our results only for the case of inhibitory coupling with strong heterogeneity. © 2018 American Physical Society.

KW - Neurons

KW - Phase diagrams

KW - Time delay

KW - Heterogeneous populations

KW - Homogeneous network

KW - Macroscopic and microscopic

KW - Oscillatory instability

KW - Partial synchronization

KW - Self-sustained oscillators

KW - Stability boundaries

KW - Strong heterogeneities

KW - Synchronization

U2 - 10.1103/PhysRevE.98.042214

DO - 10.1103/PhysRevE.98.042214

M3 - Journal article

VL - 98

JO - Physical Review E

JF - Physical Review E

SN - 2470-0045

IS - 4

M1 - 042214

ER -