Harmonicity of Sound Alters Roughness Perception

Multisensory integration refers to the integration of multiple senses by the nervous system. Auditory andtactile features are closely related senses as can be understood from the fact that adjectives such as soft,rough, and warm are used commonly for auditory and tactile features. Previous studies show that auditorycues play an important role to assess the roughness of a surface. Different characteristics of auditory cuessuch as amplitude and frequency may cause perceiving surface rougher or smoother. In this study, weinvestigate the effects of harmonic and inharmonic sounds on roughness perception to examine whetherauditory roughness will affect the tactile roughness perception while they are presented simultaneously.We expected the participants to perceive surfaces rougher while they listen to inharmonic sounds due toauditory roughness. We presented simultaneous and sequential harmonic and inharmonic sounds withthree sandpapers with different roughness levels (P100, P120, P 150 grit numbers) to the participants. Wefound that participants perceive sandpaper with the P120 grit number rougher while they listen tosimultaneous inharmonic sounds than simultaneous harmonic sounds. However, any effect of harmonicityon the sandpapers with P100 and P150 grit numbers was not observed. We suggest that auditoryroughness may enhance tactile roughness perception for surfaces with particular roughness levels,possibly when the roughness estimation from the tactile sense remains ambiguous.

Investigating the Trackability of Silicon Microprobes in High-Speed Surface Measurements

High-speed tactile roughness measurements set high demand on the trackability of the stylus probe. Because of the features of low mass, low probing force, and high signal linearity, the piezoresistive silicon microprobe is a hopeful candidate for high-speed roughness measurements. This paper investigates the trackability of these microprobes through building a theoretical dynamic model, measuring their resonant response, and performing tip-flight experiments on surfaces with sharp variations. Two microprobes are investigated and compared: one with an integrated silicon tip and one with a diamond tip glued to the end of the cantilever. The result indicates that the microprobe with the silicon tip has high trackability for measurements up to traverse speeds of 10 mm/s, while the resonant response of the microprobe with diamond tip needs to be improved for the application in high-speed topography measurements.

The neural code for tactile roughness in the somatosensory nerves

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.