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Symbolic analysis of bursting dynamical regimes of Rulkov neural networks
- Publication Year :
- 2020
- Publisher :
- arXiv, 2020.
-
Abstract
- 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.
- Subjects :
- 0209 industrial biotechnology
Artificial neural network
Quantitative Biology::Neurons and Cognition
Computer science
Cognitive Neuroscience
FOS: Physical sciences
Rulkov map
02 engineering and technology
Network topology
Symbolic data analysis
Nonlinear Sciences - Adaptation and Self-Organizing Systems
Computer Science Applications
Nonlinear system
Bursting
020901 industrial engineering & automation
Artificial Intelligence
Quantitative Biology - Neurons and Cognition
FOS: Biological sciences
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Neurons and Cognition (q-bio.NC)
Biological system
Adaptation and Self-Organizing Systems (nlin.AO)
Topology (chemistry)
Subjects
Details
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....a255604270dd60b1d968703b415310c4
- Full Text :
- https://doi.org/10.48550/arxiv.2005.03430