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刺猬爆发神经元中的噪声调谐爆发

Noise-tuned bursting in a Hedgehog burster.

作者信息

Zhu Jinjie, Nakao Hiroya

机构信息

School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, China.

Department of Systems and Control Engineering, Tokyo Institute of Technology, Tokyo, Japan.

出版信息

Front Comput Neurosci. 2022 Jul 28;16:970643. doi: 10.3389/fncom.2022.970643. eCollection 2022.

Abstract

Noise can shape the firing behaviors of neurons. Here, we show that noise acting on the fast variable of the Hedgehog burster can tune the spike counts of bursts the self-induced stochastic resonance (SISR) phenomenon. Using the distance matching condition, the critical transition positions on the slow manifolds can be predicted and the stochastic periodic orbits for various noise strengths are obtained. The critical transition positions on the slow manifold with non-monotonic potential differences exhibit a staircase-like dependence on the noise strength, which is also revealed by the stepwise change in the period of the stochastic periodic orbit. The noise-tuned bursting is more coherent within each step while displaying mixed-mode oscillations near the boundaries between the steps. When noise is large enough, noise-induced trapping of the slow variable can be observed, where the number of coexisting traps increases with the noise strength. It is argued that the robustness of SISR underlies the generality of the results discovered in this paper.

摘要

噪声能够塑造神经元的放电行为。在此,我们表明作用于刺猬爆发神经元快速变量的噪声可通过自诱导随机共振(SISR)现象调节爆发的尖峰计数。利用距离匹配条件,可预测慢流形上的临界转变位置,并获得不同噪声强度下的随机周期轨道。具有非单调势差的慢流形上的临界转变位置对噪声强度呈现出阶梯状依赖关系,这也通过随机周期轨道周期的逐步变化得以揭示。在每个步骤内,噪声调节的爆发更加相干,而在步骤之间的边界附近则表现出混合模式振荡。当噪声足够大时,可观察到噪声诱导的慢变量捕获现象,其中共存陷阱的数量随噪声强度增加。有人认为,SISR的稳健性是本文所发现结果具有普遍性的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f109/9366049/f7b64366c2c7/fncom-16-970643-g0001.jpg

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