https://doi.org/10.1140/epjs/s11734-024-01371-4
Regular Article
Spiking neural network model of low-threshold mechanoreceptors system
1
Tactile communication research laboratory, The Pushkin State Russian Language Institute, Academician Volgina, 117485, Moscow, Russia
2
Department of Neurotechnology, Lobachevsky State University of Nizhny Novgorod, Gagarin Ave., 603022, Nizhny Novgorod, Russia
3
Neuromorphic computing center, ANO Neymark, st. Nartova, 603081, Nizhny Novgorod, Russia
Received:
17
September
2024
Accepted:
10
October
2024
Published online:
23
October
2024
Low-threshold mechanoreceptors (LTMRs) are specialized sensory neurons responsible for transmitting tactile information to the brain. These receptors exhibit diverse characteristics in terms of conduction velocity, myelination, and adaptation to pressure, enabling them to encode a wide range of tactile experiences. This study presents a simplified mathematical model of the LTMRs system to investigate the firing rate characteristics of different LTMRs types in response to varying brush velocities and pressing forces. The model simulates brush movement across a simplified skin surface, incorporating non-overlapping receptive fields with lanceolate endings that convert mechanical force into electrical signals. Our findings demonstrate a distinct non-linear dependence between brush velocity and firing rate for unmyelinated LTMRs, with peak firing occurring within a specific velocity range. In contrast, lightly and heavily myelinated LTMRs exhibit a directly proportional dependence. Additionally, we observe a consistent increase in firing rate with greater force applied to the skin surface across all LTMRs types. These results suggest specialized roles for different LTMRs types in encoding tactile information.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
