This article is cited in 3 scientific papers (total in 3 papers)
Scientific articles
On connection between continuous and discontinuous neural field models with microstructure: II. Radially symmetric stationary solutions in 2D (“bumps”)
Abstract:
We suggest a method allowing to investigate existence and the measure of proximity between the stationary solutions to continuous and discontinuous neural fields with microstructure. The present part involves results on proximity of the stationary solutions to specific homogenized neural field equations with continuous and discontinuous activation functions. The results of numerical investigation of radially symmetric stationary solutions (bumps) to the neural field with a discontinuous activation function and a given microstructure are presented.
Keywords:
mathematical neuroscience, neural field models with microstructure, solvability, continuous dependence on parameters.
The work is partially supported by the Russian Fund for Basic Research (project no. 20-511-23001 РЯИК_а).
Received: 14.01.2020
Document Type:
Article
UDC:
51-76, 517.988
Language: Russian
Citation:
E. O. Burlakov, I. N. Malkov, “On connection between continuous and discontinuous neural field models with microstructure: II. Radially symmetric stationary solutions in 2D (“bumps”)”, Russian Universities Reports. Mathematics, 25:129 (2020), 6–17
This publication is cited in the following 3 articles:
A. S. Lanina, E. A. Pluzhnikova, “O svoistvakh reshenii differentsialnykh sistem, modeliruyuschikh elektricheskuyu aktivnost golovnogo mozga”, Vestnik rossiiskikh universitetov. Matematika, 27:139 (2022), 270–283
R. Atmaniya, E. O. Burlakov, I. N. Malkov, “O suschestvovanii i ustoichivosti reshenii tipa «koltso» uravnenii neironnogo polya Amari s periodicheskoi mikrostrukturoi i funktsiei aktivatsii Khevisaida”, Vestnik rossiiskikh universitetov. Matematika, 27:140 (2022), 318–327
R. Atmaniya, E. O. Burlakov, I. N. Malkov, “O resheniyakh tipa «koltso» uravnenii neironnogo polya”, Vestnik rossiiskikh universitetov. Matematika, 26:136 (2021), 363–371