Volume 1, Issue 2
Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops

Jianfu Ma & Jianhong Wu

J. Nonl. Mod. Anal., 1 (2019), pp. 129-150.

Published online: 2021-04

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  • 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.

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@Article{JNMA-1-129, author = {Ma , Jianfu and Wu , Jianhong}, title = {Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops}, journal = {Journal of Nonlinear Modeling and Analysis}, year = {2021}, volume = {1}, number = {2}, pages = {129--150}, 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.

}, issn = {2562-2862}, doi = {https://doi.org/10.12150/jnma.2019.129}, url = {http://global-sci.org/intro/article_detail/jnma/18853.html} }
TY - JOUR T1 - Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops AU - Ma , Jianfu AU - Wu , Jianhong JO - Journal of Nonlinear Modeling and Analysis VL - 2 SP - 129 EP - 150 PY - 2021 DA - 2021/04 SN - 1 DO - http://doi.org/10.12150/jnma.2019.129 UR - https://global-sci.org/intro/article_detail/jnma/18853.html KW - Multistability, periodic pattern, neural network, time delay, pattern formation, recurrent inhibitory loops. AB -

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.

Ma , Jianfu and Wu , Jianhong. (2021). Trajectory Segmentation and Symbolic Representation of Dynamics of Delayed Recurrent Inhibitory Neural Loops. Journal of Nonlinear Modeling and Analysis. 1 (2). 129-150. doi:10.12150/jnma.2019.129
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