Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops

Authors

  • Jianfu Ma Laboratory for Industrial and Applied Mathematics, Department of Mathe-matics and Statistics, Fields-CQUM Laboratory of Mathematics for PublicHealth, York University, Toronto, Ontario, M3J 1P3, Canada 
  • Jianhong Wu

DOI:

https://doi.org/10.12150/jnma.2019.129

Keywords:

Multistability, periodic pattern, neural network, time delay, pattern formation, recurrent inhibitory loops.

Abstract

We develop a general symbolic dynamics framework to examine the dynamics of an analogue of the integrate-and-fire neuron model of recurrent inhibitory loops with delayed feedback, which incorporates the firing procedure and absolute refractoriness. We first show that the interaction of the delay, the inhibitory feedback and the absolute refractoriness can generate three basic types of oscillations, and these oscillations can be pinned together to form interesting coexisting periodic patterns in the case of short feedback duration. We then develop a natural symbolic dynamics formulation for the segmentation of a typical trajectory in terms of the basic oscillatory patterns, and use this to derive general principles that determine whether a periodic pattern can and should occur.

Published

2024-04-10

Abstract View

  • 22296

Pdf View

  • 2379

Issue

Section

Articles

How to Cite

Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops. (2024). Journal of Nonlinear Modeling and Analysis, 1(2), 129-150. https://doi.org/10.12150/jnma.2019.129