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Regulating synchronous patterns in neurons and networks via field coupling.

Authors :
Yao, Zhao
Wang, Chunni
Zhou, Ping
Ma, Jun
Source :
Communications in Nonlinear Science & Numerical Simulation. Apr2021, Vol. 95, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

Both electrical and chemical synapses play important role in receiving and propagating signals between biological neurons. The activation of electrical synapse coupling is generated via gap junction connection while chemical synapse coupling depends on the release of neurotransmitter for triggering stable propagation of ions. In a practical way, voltage coupling via resistor connection between artificial neural circuits is often used to describe the gap junction coupling via electrical synapse between neurons. Magnetic field coupling via induction coil between neural circuits can be effective to estimate the chemical synapse coupling when ions are propagated and released in the cell. In this paper, the physical properties of magnetic field coupling between neural circuits are discussed. For simplicity, two Hindmarsh–Rose neurons are connected to trigger magnetic field coupling and the coupling channel is tamed to detect possible occurrence of synchronization. Two neurons are stimulated with different stimuli, and it is confirmed that the synchronous firing mode is decided by the neuron with higher forcing amplitude. Furthermore, the collective behaviors of HR neuron in the small-world network and scale free network are investigated by changing the coupling intensity and diversity in external stimulus, respectively. Statistical synchronization factor is calculated to estimate the dependence of synchronization on coupling gain and the number of bursting neurons in the network. In case of small-world connection, synchronization approach becomes difficult. However, complete synchronization can be stabilized on the scale free network under magnetic field coupling. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10075704
Volume :
95
Database :
Academic Search Index
Journal :
Communications in Nonlinear Science & Numerical Simulation
Publication Type :
Periodical
Accession number :
148125581
Full Text :
https://doi.org/10.1016/j.cnsns.2020.105583