时滞耦合可激单元网络中的随机爆破。

IF 1.7 4区 工程技术 Q3 COMPUTER SCIENCE, CYBERNETICS
Biological Cybernetics Pub Date : 2022-04-01 Epub Date: 2021-06-28 DOI:10.1007/s00422-021-00883-9
Chunming Zheng, Arkady Pikovsky
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引用次数: 0

摘要

利用有向树格模型研究了具有多个弱延迟反馈的噪声可激单元的随机爆破现象。我们找到了峰值出现序列的统计性质和功率谱密度的表达式。将该简单模型推广到具有星型延迟耦合的三单元网络。我们求出每个单元的功率谱密度和任意两个单元之间的交叉谱密度。分析方法背后的基本假设是时间尺度的分离,允许将尖峰序列描述为一个点过程,以及耦合的弱点,允许通过单尖峰激励概率的总和来表示重叠尖峰的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Stochastic bursting in networks of excitable units with delayed coupling.

Stochastic bursting in networks of excitable units with delayed coupling.

Stochastic bursting in networks of excitable units with delayed coupling.

Stochastic bursting in networks of excitable units with delayed coupling.

We investigate the phenomenon of stochastic bursting in a noisy excitable unit with multiple weak delay feedbacks, by virtue of a directed tree lattice model. We find statistical properties of the appearing sequence of spikes and expressions for the power spectral density. This simple model is extended to a network of three units with delayed coupling of a star type. We find the power spectral density of each unit and the cross-spectral density between any two units. The basic assumptions behind the analytical approach are the separation of timescales, allowing for a description of the spike train as a point process, and weakness of coupling, allowing for a representation of the action of overlapped spikes via the sum of the one-spike excitation probabilities.

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来源期刊
Biological Cybernetics
Biological Cybernetics 工程技术-计算机:控制论
CiteScore
3.50
自引率
5.30%
发文量
38
审稿时长
6-12 weeks
期刊介绍: Biological Cybernetics is an interdisciplinary medium for theoretical and application-oriented aspects of information processing in organisms, including sensory, motor, cognitive, and ecological phenomena. Topics covered include: mathematical modeling of biological systems; computational, theoretical or engineering studies with relevance for understanding biological information processing; and artificial implementation of biological information processing and self-organizing principles. Under the main aspects of performance and function of systems, emphasis is laid on communication between life sciences and technical/theoretical disciplines.
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