Biomechanical filtering supports efficient tactile encoding in the human hand.

Touching an object elicits skin oscillations that are biomechanically transmitted throughout the hand, driving responses in thousands of tactile receptors, including numerous exquisitely sensitive Pacinian corpuscles (PCs). Accepted descriptions of PC functionality characterize their response properties as highly stereotyped, based on experimental data gathered when stimuli are applied near the receptor. However, during natural touch, spiking activity in the majority of PCs is evoked by transmitted skin oscillations that are modified by biomechanical filtering. This filtering mechanism, stemming from dispersive wave dynamics in the skin, bears some similarity to the pre-neuronal filtering of auditory signals by the basilar membrane, a mechanical process that is instrumental to perception. Thus, we sought to clarify how skin biomechanics might influence tactile information encoding in the periphery. We used vibrometry imaging and computational neural experiments to examine the influence of biomechanical filtering on neural activity in whole-hand PC populations. We observed complex, location- and frequency-dependent patterns of filtering that were shaped by tissue mechanics and hand morphology. This source of biomechanical modulation diversified PC population spiking activity and enhanced tactile information encoding efficiency. These findings indicate that biomechanics furnishes a pre-neuronal mechanism that facilitates efficient tactile encoding and processing.