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Vibrotactile Sensitivity Threshold: Nonlinear Stochastic Mechanotransduction Model of the Pacinian Corpuscle

Authors: Biswas, Abhijit; Manivannan, M.; Srinivasan, Mandayam A.;

Vibrotactile Sensitivity Threshold: Nonlinear Stochastic Mechanotransduction Model of the Pacinian Corpuscle

Abstract

Based on recent discoveries of stretch and voltage activated ion channels in the receptive area of the Pacinian Corpuscle (PC), this paper describes a two-stage mechanotransduction model of its near threshold Vibrotactile (VT) sensitivity valid over 10 Hz to a few kHz. The model is based on the nonlinear and stochastic behavior of the ion channels represented as dependent charge sources loaded with membrane impedance. It simulates the neural response of the PC considering the morphological and statistical properties of the receptor potential and action potential with the help of an adaptive relaxation pulse frequency modulator. This model also simulates the plateaus and nonmonotonic saturation of spike rate characteristics. The stochastic simulation based on the addition of mechanical and neural noise describes that the VT Sensitivity Threshold (VTST) at higher frequencies is more noise dependent. Above 800 Hz even a SNR = 150 improves the neurophysiological VTST more than 3 dBμ. In that frequency range, an absence of the entrainment threshold and a lower sensitivity index near the absolute threshold make the upper bound of the psychophysical VTST more dependent on the experimental protocol and physical set-up. This model can be extended to simulate the neural response of a group of PCs.

Keywords

Models, Neurological, Action Potentials, Neurophysiology, Mechanotransduction, Cellular, Models, Biological, Vibration, Electric Stimulation, Ion Channels, Biomechanical Phenomena, Nonlinear Dynamics, Touch, Humans, Pacinian Corpuscles, Skin

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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