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A Model for Evolutionary Structural Plasticity and Synchronization of a Network of Neurons
Author(s) -
Gualberto SolísPerales,
Jairo Sánchez-Estrada
Publication year - 2021
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2021/9956319
Subject(s) - synchronization (alternating current) , coupling (piping) , computer science , plasticity , node (physics) , network model , function (biology) , neuron , biological system , structural plasticity , topology (electrical circuits) , physics , control theory (sociology) , neuroscience , mathematics , artificial intelligence , biology , materials science , evolutionary biology , metallurgy , thermodynamics , computer network , channel (broadcasting) , control (management) , quantum mechanics , combinatorics
A model of time-dependent structural plasticity for the synchronization of neuron networks is presented. It is known that synchronized oscillations reproduce structured communities, and this synchronization is transient since it can be enhanced or suppressed, and the proposed model reproduces this characteristic. The evolutionary behavior of the couplings is comparable to those of a network of biological neurons. In the structural network, the physical connections of axons and dendrites between neurons are modeled, and the evolution in the connections depends on the neurons' potential. Moreover, it is shown that the coupling force's function behaves as an adaptive controller that leads the neurons in the network to synchronization. The change in the node's degree shows that the network exhibits time-dependent structural plasticity, achieved through the evolutionary or adaptive change of the coupling force between the nodes. The coupling force function is based on the computed magnitude of the membrane potential deviations with its neighbors and a threshold that determines the neuron's connections. These rule the functional network structure along the time.

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