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与资源池自适应耦合的一群可兴奋单元中的集体活动爆发。

Collective Activity Bursting in a Population of Excitable Units Adaptively Coupled to a Pool of Resources.

作者信息

Franović Igor, Eydam Sebastian, Yanchuk Serhiy, Berner Rico

机构信息

Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Belgrade, Serbia.

Neural Circuits and Computations Unit, RIKEN Center for Brain Science, Wako, Japan.

出版信息

Front Netw Physiol. 2022 Mar 28;2:841829. doi: 10.3389/fnetp.2022.841829. eCollection 2022.

Abstract

We study the collective dynamics in a population of excitable units (neurons) adaptively interacting with a pool of resources. The resource pool is influenced by the average activity of the population, whereas the feedback from the resources to the population is comprised of components acting homogeneously or inhomogeneously on individual units of the population. Moreover, the resource pool dynamics is assumed to be slow and has an oscillatory degree of freedom. We show that the feedback loop between the population and the resources can give rise to collective activity bursting in the population. To explain the mechanisms behind this emergent phenomenon, we combine the Ott-Antonsen reduction for the collective dynamics of the population and singular perturbation theory to obtain a reduced system describing the interaction between the population mean field and the resources.

摘要

我们研究了一群可兴奋单元(神经元)与一组资源进行自适应相互作用时的集体动力学。资源池受群体平均活动的影响,而从资源到群体的反馈由对群体中各个单元均匀或非均匀作用的成分组成。此外,假设资源池动力学是缓慢的且具有振荡自由度。我们表明,群体与资源之间的反馈回路可导致群体中出现集体活动爆发。为了解释这一涌现现象背后的机制,我们将群体集体动力学的奥特 - 安东森约化与奇异摄动理论相结合,以获得一个描述群体平均场与资源之间相互作用的约化系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b06c/10013072/bd1ce9a26bdb/fnetp-02-841829-g001.jpg

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