Bursting Dynamics of Spiking Neural Network Induced by Active Extracellular Medium

Sergey V. Stasenko and Victor B. Kazantsev ()
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Sergey V. Stasenko: Moscow Institute of Physics and Technology, 117303 Moscow, Russia
Victor B. Kazantsev: Moscow Institute of Physics and Technology, 117303 Moscow, Russia

Mathematics, 2023, vol. 11, issue 9, 1-17

Abstract: We propose a mathematical model of a spiking neural network (SNN) that interacts with an active extracellular field formed by the brain extracellular matrix (ECM). The SNN exhibits irregular spiking dynamics induced by a constant noise drive. Following neurobiological facts, neuronal firing leads to the production of the ECM that occupies the extracellular space. In turn, active components of the ECM can modulate neuronal signaling and synaptic transmission, for example, through the effect of so-called synaptic scaling. By simulating the model, we discovered that the ECM-mediated regulation of neuronal activity promotes spike grouping into quasi-synchronous population discharges called population bursts. We investigated how model parameters, particularly the strengths of ECM influence on synaptic transmission, may facilitate SNN bursting and increase the degree of neuronal population synchrony.

Keywords: spiking neural network; tetrapartite synapse; neuron; ECM (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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