Memristive circuit-based model of central pattern generator to reproduce spinal neuronal activity in walking pattern.

Autor:	Masaev DN; ITIS, IFMB, Kazan Federal University, Kazan, Russia.; B-Rain Labs LLC, Kazan, Russia., Suleimanova AA; B-Rain Labs LLC, Kazan, Russia., Prudnikov NV; National Research Centre Kurchatov Institute, Moscow, Russia.; Moscow Institute of Physics and Technology, National Research University, Moscow, Russia., Serenko MV; National Research Centre Kurchatov Institute, Moscow, Russia.; Moscow Institute of Physics and Technology, National Research University, Moscow, Russia., Emelyanov AV; National Research Centre Kurchatov Institute, Moscow, Russia.; Moscow Institute of Physics and Technology, National Research University, Moscow, Russia., Demin VA; National Research Centre Kurchatov Institute, Moscow, Russia., Lavrov IA; ITIS, IFMB, Kazan Federal University, Kazan, Russia.; Department of Neurology, Mayo Clinic, Rochester, MN, United States.; Skolkovo Institute of Science and Technology, Moscow, Russia., Talanov MO; ITIS, IFMB, Kazan Federal University, Kazan, Russia.; Institute for Artificial Intelligence R&D, Novi Sad, Serbia., Erokhin VV; Consiglio Nazionale delle Ricerche at Istituto dei Materiali per l'Elettronica ed il Magnetismo, Rome, Italy.
Jazyk:	angličtina
Zdroj:	Frontiers in neuroscience [Front Neurosci] 2023 Feb 28; Vol. 17, pp. 1124950. Date of Electronic Publication: 2023 Feb 28 (Print Publication: 2023).
DOI:	10.3389/fnins.2023.1124950
Abstrakt:	Existing methods of neurorehabilitation include invasive or non-invasive stimulators that are usually simple digital generators with manually set parameters like pulse width, period, burst duration, and frequency of stimulation series. An obvious lack of adaptation capability of stimulators, as well as poor biocompatibility and high power consumption of prosthetic devices, highlights the need for medical usage of neuromorphic systems including memristive devices. The latter are electrical devices providing a wide range of complex synaptic functionality within a single element. In this study, we propose the memristive schematic capable of self-learning according to bio-plausible spike-timing-dependant plasticity to organize the electrical activity of the walking pattern generated by the central pattern generator. Competing Interests: AS and DM were employed by the company B-Rain LLC. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2023 Masaev, Suleimanova, Prudnikov, Serenko, Emelyanov, Demin, Lavrov, Talanov and Erokhin.)
Databáze:	MEDLINE
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