Pairing cellular and synaptic dynamics into building blocks of rhythmic neural circuits
James ScullyiD, Jassem Bourahmah, David Bloom, ANDREY L. SHILNIKOViD
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 rhythmogenesis and feature in our models of swim central pattern generators.
02 /Specification & Classification
Click any tag to browse matching papersReproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- Effect of time delay on the synchronization of excitatory-inhibitory neural networks
Hwayeon Ryu, Sue Ann Campbell·bioRxiv·Aug 30, 2020
- Bursting emerges from the complementary roles of neurons in a four-cell network
Akira Sakurai, Paul S. Katz·Journal of NeurophysiologyPeer-reviewed·Mar 23, 2022
- Simplified model of intrinsically bursting neurons
Nikhil Xie Bhattasali, Lerrel Pinto, Grace W. Lindsay·bioRxiv·Mar 5, 2026
- Connectivity for Rapid Synchronization in a Neural Pacemaker Network
Ezekiel Williams, Aaron R. Shifman, John E. Lewis·bioRxiv·Oct 5, 2020
- Bidirectional Cycling Dynamics of Living Neuronal Networks in Vitro
Arseniy Gladkov, Oleg Grinchuk, … Alexey S. Pimashkin·PLoS ONEPeer-reviewed·Feb 7, 2018
- Dynamically rich states in balanced networks induced by single-neuron dynamics
Moritz Drangmeister, Rainer Engelken, … Susanne Schreiber·bioRxiv·Feb 28, 2025