Email this article Study of the influence of synaptic plasticity on the formation of a feature space by a spiking neural network
- Authors: Lebedev A.A.1, Kazantsev V.B.2, Stasenko S.V.1
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Affiliations:
- Lobachevsky State University of Nizhny Novgorod
- Institute of Applied Physics of the Russian Academy of Sciences
- Issue: Vol 32, No 2 (2024)
- Pages: 253-267
- Section: Articles
- URL: https://ogarev-online.ru/0869-6632/article/view/254258
- DOI: https://doi.org/10.18500/0869-6632-003092
- EDN: https://elibrary.ru/STLCRP
- ID: 254258
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Abstract
The purpose of this study is to study the influence of synaptic plasticity on excitatory and inhibitory synapses on the formation of the feature space of the input image on the excitatory and inhibitory layers of neurons in a spiking neural network. Methods. To simulate the dynamics of the neuron, the computationally efficient model “Leaky integrate-and-fire” was used. The conductance-based synapse model was used as a synaptic contact model. Synaptic plasticity in excitatory and inhibitory synapses was modeled by the classical model of time dependent synaptic plasticity. A neural network composed of them generates a feature space, which is divided into classes by a machine learning algorithm. Results. A model of a spiking neural network was built with excitatory and inhibitory layers of neurons with adaptation of synaptic contacts due to synaptic plasticity. Various configurations of the model with synaptic plasticity were considered for the problem of forming the feature space of the input image on the excitatory and inhibitory layers of neurons, and their comparison was also carried out. Conclusion. It has been shown that synaptic plasticity in inhibitory synapses impairs the formation of an image feature space for a classification task. The model constraints are also obtained and the best model configuration is selected.
About the authors
Andrey Aleksandrovich Lebedev
Lobachevsky State University of Nizhny Novgorod603950 Nizhny Novgorod, Gagarin Avenue, 23
Viktor Borisovich Kazantsev
Institute of Applied Physics of the Russian Academy of Sciences
ORCID iD: 0000-0002-2881-6648
ResearcherId: L-1424-2013
ul. Ul'yanova, 46, Nizhny Novgorod , 603950, Russia
Sergey Victorovich Stasenko
Lobachevsky State University of Nizhny Novgorod
ORCID iD: 0000-0002-3032-5469
Scopus Author ID: 55327776400
ResearcherId: J-4825-2013
603950 Nizhny Novgorod, Gagarin Avenue, 23
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