Synchronous Propagation of Periodic Signals in Feedforward Networks of Standard Model Neurons

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Main Authors: Stewart, Ian, Wood, David
Format: Preprint
Published: 2025
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_version_ 1866913892155785216
author Stewart, Ian
Wood, David
author_facet Stewart, Ian
Wood, David
contents Periodic signals propagating along chains are common in biology, for example in locomotion and peristalsis, and are also of interest for continuum robots. In previous work we constructed such networks as 'feedforward lifts' of a central pattern generator (CPG). When the CPG undergoes periodic oscillations, created by Hopf bifurcation or other mechanisms, it can then transmit periodic signals along one or more feedforward chains in a synchronous or phase-synchronous manner. We proved necessary and sufficient conditions for the stability of these lifted periodic orbits, in several senses. Here we examine the implications of the resulting theory for chains of neurons, using several standard neuron models: FitzHugh-Nagumo, Morris-Lecar, Hindmarsh-Rose, and Hodgkin-Huxley. We compare different notions of transverse stability, and summarize some numerical simulations showing that for all these neuron models the propagating signal can be transversely Floquet stable. Finally we discuss implications for less idealized models.
format Preprint
id arxiv_https___arxiv_org_abs_2506_11776
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Synchronous Propagation of Periodic Signals in Feedforward Networks of Standard Model Neurons
Stewart, Ian
Wood, David
Chaotic Dynamics
Dynamical Systems
Neurons and Cognition
37C10, 37C55, 37N25
Periodic signals propagating along chains are common in biology, for example in locomotion and peristalsis, and are also of interest for continuum robots. In previous work we constructed such networks as 'feedforward lifts' of a central pattern generator (CPG). When the CPG undergoes periodic oscillations, created by Hopf bifurcation or other mechanisms, it can then transmit periodic signals along one or more feedforward chains in a synchronous or phase-synchronous manner. We proved necessary and sufficient conditions for the stability of these lifted periodic orbits, in several senses. Here we examine the implications of the resulting theory for chains of neurons, using several standard neuron models: FitzHugh-Nagumo, Morris-Lecar, Hindmarsh-Rose, and Hodgkin-Huxley. We compare different notions of transverse stability, and summarize some numerical simulations showing that for all these neuron models the propagating signal can be transversely Floquet stable. Finally we discuss implications for less idealized models.
title Synchronous Propagation of Periodic Signals in Feedforward Networks of Standard Model Neurons
topic Chaotic Dynamics
Dynamical Systems
Neurons and Cognition
37C10, 37C55, 37N25
url https://arxiv.org/abs/2506.11776