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Chimera states in uncoupled neurons induced by a multilayer structure
Soumen Majhi1, Matjaž Perc2,3, Dibakar Ghosh1
1Physics and Applied Mathematics Unit, Indian Statistical Institute, Kolkata-700108, India.
Scientific Reports
|December 14, 2016
Summary
Chimera states emerge in uncoupled neurons within a multilayer network. Competing electrical and chemical synapses in the lower layer drive this complex neural dynamics, revealing a density-dependent threshold.
Area of Science:
- Neuroscience
- Complex Systems
- Computational Biology
Background:
- Chimera states represent a unique phenomenon where spatially separated parts of a network exhibit coexisting coherent and incoherent dynamics.
- Understanding chimera states is crucial for deciphering complex behaviors in biological and artificial networks.
Purpose of the Study:
- To investigate the emergence of chimera states in a multilayer neural network where the upper layer neurons are uncoupled.
- To explore the role of inter-layer coupling and heterogeneity in the formation of these states.
Main Methods:
- Utilized a multilayer network model with Hindmarsh-Rose neurons exhibiting square wave bursting dynamics.
- Implemented global electrical synapses in the lower layer and chemical synapses between layers.
- Analyzed chimera state formation under varying neuron densities, inter-layer heterogeneity, and transmission delays.
Main Results:
- Demonstrated the occurrence of chimera states in the upper layer of uncoupled neurons.
- Identified a density-dependent threshold for chimera state emergence, analogous to quorum sensing.
- Showcased the influence of inter-layer synaptic competition and transmission delays on chimera dynamics.
Conclusions:
- Multilayer network architecture with specific synaptic configurations can induce complex dynamics like chimera states in previously uncoupled neuronal populations.
- The findings highlight a novel mechanism for generating chimera states and offer insights into neural information processing.
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