English

Pairing cellular and synaptic dynamics into building blocks of rhythmic neural circuits

Neurons and Cognition 2022-11-02 v1 Dynamical Systems Adaptation and Self-Organizing Systems Chaotic Dynamics

Abstract

The purpose of this paper is trifold -- to serve as an instructive resource and a reference catalog for biologically plausible modeling with i) conductance-based models, coupled with ii) strength-varying slow synapse models, culminating in iii) two canonical pair-wise rhythm-generating networks. We document the properties of basic network components: cell models and synaptic models, which are prerequisites for proper network assembly. Using the slow-fast decomposition we present a detailed analysis of the cellular dynamics including a discussion of the most relevant bifurcations. Several approaches to model synaptic coupling are also discussed, and a new logistic model of slow synapses is introduced. Finally, we describe and examine two types of bicellular rhythm-generating networks: i) half-center oscillators ii) excitatory-inhibitory pairs and elucidate a key principle -- the network hysteresis underlying the stable onset of emergent slow bursting in these neural building blocks. These two cell networks are a basis for more complicated neural circuits of rhythmogensis and feature in our models of swim central pattern generators.

Keywords

Cite

@article{arxiv.2211.00245,
  title  = {Pairing cellular and synaptic dynamics into building blocks of rhythmic neural circuits},
  author = {James Scully and Jassem Bourahmah and David Bloom and Andrey L Shilnikov},
  journal= {arXiv preprint arXiv:2211.00245},
  year   = {2022}
}
R2 v1 2026-06-28T04:54:15.613Z