The neural code for tactile roughness in the somatosensory nerves

Abstract

Roughness is the most salient perceptual dimension of surface texture but has no well-defined physical basis. We seek to determine the neural determinants of tactile roughness in the somatosensory nerves. Specifically, we record the patterns of activation evoked in tactile nerve fibers of anesthetized Rhesus macaques to a large and diverse set of natural textures and assess what aspect of these patterns of activation can account for psychophysical judgments of roughness, obtained from human observers. We show that perceived roughness is determined by the variation in the population response, weighted by fiber type. That is, a surface will feel rough to the extent that the activity varies across nerve fibers and varies across time within nerve fibers. We show that this variation-based neural code can account not only for magnitude estimates of roughness but also for roughness discrimination performance. NEW & NOTEWORTHY Our sense of touch endows us with an exquisite sensitivity to the microstructure of surfaces, the most salient aspect of which is roughness. We analyze the responses evoked in tactile fibers of monkeys by natural textures and compare them to judgments of roughness obtained for the same textures from human observers. We then describe how texture signals from three populations of nerve fibers are integrated to culminate in a percept of roughness.