Symbolic analysis of bursting dynamical regimes of Rulkov neural networks

Neurons modeled by the Rulkov map display a variety of dynamic regimes that include tonic spikes and chaotic bursting. Here we study an ensemble of bursting neurons coupled with the Watts-Strogatz small world topology. We characterize the sequences of bursts using the symbolic method of time-series analysis known as ordinal analysis, which detects nonlinear temporal correlations. We show that the probabilities of the different symbols distinguish different dynamical regimes, which depend on the coupling strength and the network topology. These regimes have different spatio-temporal properties that can be visualized with raster plots.& nbsp; (C)& nbsp;2021 Elsevier B.V. All rights reserved.

Automated summary

The study investigates bursting neurons coupled with a small world topology, using ordinal analysis to characterize burst sequences and distinguish different dynamical regimes based on symbol probabilities, which are influenced by coupling strength and network topology. Different spatio-temporal properties of these regimes can be visualized with raster plots.