Mechanisms of information transmission using tactile sense are one of major concerns in producing simulated experience in virtual or augmented reality as well as in compensating elderly or impaired people with diminished tactile sensory function. However, important mechanism of the difference of peak latency in the primary somatosensory cortex (SI) between electrical and mechanical stimulations of finger skin is not fully understood. We propose a computational approach to fuse a computational model to simulate temporal and spatial transmission processes from mechanical stimuli to the SI and experimental method using a magnetoencephalograph (MEG). In our model, a tactile model that combined a three-dimensional mechanical model of fingertip skin and a neurophysiological model of a slowly adapting type 1 (SA1) mechanoreceptor was integrated with a somatosensory evoked field (SEF) response model. Electrical and mechanical stimulations were applied to the same locations of the right or left index fingertips of three subjects using a MEG. By identifying parameters of the SEF response model using the electrical stimulation test data, predicted first peak latency due to a mechanical stimulus was identical to its average value obtained from the mechanical stimulation test data, while the spatial map predicted at the multiple SA1 receptors qualitatively corresponded to the MEG image map in the timings of peak latency. This suggests that mechanical change in the skin and neurophysiological responses generate the difference of peak latency in SI between electrical and mechanical stimulations. The computational approach has the potential for detailed investigation of mechanisms of tactile information transmission.
Computational approach to understand temporal and spatial tactile transmission processes from mechanical stimuli of the index fingertip to the primary somatosensory cortex.
M. Iwamoto,Toru Hamasaki,Y. Asano,J. Shinoda
Published 2021 in Journal of Neuroscience Methods
ABSTRACT
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- Publication year
2021
- Venue
Journal of Neuroscience Methods
- Publication date
2021-05-03
- Fields of study
Medicine, Engineering
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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