Wave Generation in Unidirectional Chains of Idealized Neural Oscillators.

IF 2.3 4区 医学 Q1 Neuroscience
Journal of Mathematical Neuroscience Pub Date : 2016-12-01 Epub Date: 2016-04-08 DOI:10.1186/s13408-016-0037-x
Bastien Fernandez, Stanislav M Mintchev
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引用次数: 2

Abstract

We investigate the dynamics of unidirectional semi-infinite chains of type-I oscillators that are periodically forced at their root node, as an archetype of wave generation in neural networks. In previous studies, numerical simulations based on uniform forcing have revealed that trajectories approach a traveling wave in the far-downstream, large time limit. While this phenomenon seems typical, it is hardly anticipated because the system does not exhibit any of the crucial properties employed in available proofs of existence of traveling waves in lattice dynamical systems. Here, we give a full mathematical proof of generation under uniform forcing in a simple piecewise affine setting for which the dynamics can be solved explicitly. In particular, our analysis proves existence, global stability, and robustness with respect to perturbations of the forcing, of families of waves with arbitrary period/wave number in some range, for every value of the parameters in the system.

Abstract Image

Abstract Image

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理想神经振荡器单向链中的波产生。
我们研究了在其根节点周期性强制的i型振荡器的单向半无限链的动力学,作为神经网络中波产生的原型。在之前的研究中,基于均匀强迫的数值模拟表明,轨迹在远下游的大时间限制内接近行波。虽然这种现象看起来很典型,但很难预料到,因为该系统没有表现出晶格动力系统中行波存在的现有证明中所使用的任何关键性质。在此,我们给出了在一个简单的分段仿射设置下均匀强迫下的生成的完整数学证明,该设置下的动力学可以显式求解。特别是,我们的分析证明了在一定范围内具有任意周期/波数的波族的存在性,全局稳定性和关于强迫扰动的鲁棒性,对于系统中的每个参数值。
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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
自引率
0.00%
发文量
0
审稿时长
13 weeks
期刊介绍: The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions. The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition. The aim is to publish work that uses advanced mathematical techniques to illuminate these questions. It publishes full length original papers, rapid communications and review articles. Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged. Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.
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