Dynamics and bifurcations in multistable 3-cell neural networks
Adaptation and Self-Organizing Systems
2020-08-26 v3
Abstract
We disclose the generality of the intrinsic mechanisms underlying multistability in reciprocally inhibitory 3-cell circuits composed of simplified, low-dimensional models of oscillatory neurons, as opposed to those of a detailed Hodgkin- Huxley type . The computational reduction to return maps for the phase-lags between neurons reveals a rich multiplicity of rhythmic patterns in such circuits. We perform a detailed bifurcation analysis to show how such rhythms can emerge, disappear, and gain or lose stability, as the parameters of the individual cells and the synapses are varied.
Cite
@article{arxiv.2005.04278,
title = {Dynamics and bifurcations in multistable 3-cell neural networks},
author = {J. Collens and K. Pusuluri and A. Kelly and D. Knapper and T. Xing and S. Basodi and D. Alacam and A. L. Shilnikov},
journal= {arXiv preprint arXiv:2005.04278},
year = {2020}
}