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arXiv q-bio.NC 预印本· Martin R Nelson, Jonathan J Crofts·· 9 小时前AI 评分51

用时间延迟探索神经动力学:数值与分岔分析方法

Exploring Neural Dynamics with Time Delays: A Numerical and Bifurcation Analysis Approach

AI 导读

神经群体模型中的信号传导延迟会改变网络动力学。本文以经典的 Wilson-Cowan 模型为对象,梳理时滞如何影响其行为,介绍针对时滞微分方程的数值分析技术,并给出使用 DDE-BIFTOOL 做延拓分析的操作教程,附带 MATLAB 计算代码与 Python 模拟代码供复现。

摘要

arXiv:2610.36920v1 Announce Type: new Abstract: The Wilson-Cowan model is a classic example of a ``neural mass model'' - a simplified yet powerful way to describe the activity of large networks of neurons. It is particularly interesting because, even in its relatively simple form, it can produce a surprising variety of behaviours, from steady rhythms to complex oscillations. A key factor influencing these dynamics is the presence of time delays, reflecting the time it takes for signals to travel between neurons. This article offers an accessible introduction to the Wilson-Cowan model, focusing on how these time delays affect its behaviour. We explore the core concepts behind the model, survey the existing literature, and introduce some numerical techniques specifically designed for analysing such delay differential equations. We also provide a practical, hands-on tutorial on using the DDE-BIFTOOL software package, demonstrating its application to the Wilson-Cowan model. Downloadable code allows the reader to reproduce our results and to explore the model's dynamics further, including MATLAB code for all computations, using DDE-BIFTOOL for the continuation, and Python versions of simulation codes.

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来源:arXiv q-bio.NC 预印本 · arxiv.org

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