The roles of lower- and higher-order surface statistics in tactile texture perception

Crossmodal associations between naturally occurring tactile and sound textures

This study investigates the crossmodal associations between naturally occurring sound textures and tactile textures. Previous research has demonstrated the association between low-level sensory features of sound and touch, as well as higher-level, cognitively mediated associations involving language, emotions, and metaphors. However, stimuli like textures, which are found in both modalities have received less attention. In this study, we conducted two experiments: a free association task and a two alternate forced choice task using everyday tactile textures and sound textures selected from natural sound categories. The results revealed consistent crossmodal associations reported by participants between the textures of the two modalities. They tended to associate more sound textures (e.g., wood shavings and sandpaper) with tactile surfaces that were rated as harder, rougher, and intermediate on the sticky-slippery scale. While some participants based the auditory-tactile association on sensory features, others made the associations based on semantic relationships, co-occurrence in nature, and emotional mediation. Interestingly, the statistical features of the sound textures (mean, variance, kurtosis, power, autocorrelation, and correlation) did not show significant correlations with the crossmodal associations, indicating a higher-level association. This study provides insights into auditory-tactile associations by highlighting the role of sensory and emotional (or cognitive) factors in prompting these associations.

Tactile perception of randomness: Effect of varying stimulus size and participants age

We investigated participants' ability to differentiate between random and organized two-dimensional tactile tiles with embossed dots and examined how this ability varies with size and participant age. Four experiments were conducted to evaluate the effect of these variations on participants' capacity to utilize touch in identifying which of two stimuli exhibited greater randomness. Participants were instructed to explore embossed tiles using both hands. The tiles had varying levels of randomness from organized to random sets. In Experiments 1, 2, and 4, the sets were of equal size, while in Experiment 3, they differed in size. Results revealed a significant difference between the random and organized sets, with random stimuli being more easily discernible. These findings suggest that touch can be utilized to discern random patterns on tactile maps or displays. However, older participants encountered difficulties making this distinction, indicating similarities between vision and touch in perceiving randomness.

Roughness perception: A multisensory/crossmodal perspective

Roughness is a perceptual attribute typically associated with certain stimuli that are presented in one of the spatial senses. In auditory research, the term is typically used to describe the harsh effects that are induced by particular sound qualities (i.e., dissonance) and human/animal vocalizations (e.g., screams, distress cries). In the tactile domain, roughness is a crucial factor determining the perceptual features of a surface. The same feature can also be ascertained visually, by means of the extraction of pattern features that determine the haptic quality of surfaces, such as grain size and density. By contrast, the term roughness has rarely been applied to the description of those stimuli perceived via the chemical senses. In this review, we take a critical look at the putative meaning(s) of the term roughness, when used in both unisensory and multisensory contexts, in an attempt to answer two key questions: (1) Is the use of the term 'roughness' the same in each modality when considered individually? and (2) Do crossmodal correspondences involving roughness match distinct perceptual features or (at least on certain occasions) do they merely pick-up on an amodal property? We start by examining the use of the term in the auditory domain. Next, we summarize the ways in which the term roughness has been used in the literature on tactile and visual perception, and in the domain of olfaction and gustation. Then, we move on to the crossmodal context, reviewing the literature on the perception of roughness in the audiovisual, audiotactile, and auditory-gustatory/olfactory domains. Finally, we highlight some limitations of the reviewed literature and we outline a number of key directions for future empirical research in roughness perception.

The neural basis of tactile texture perception

Running our fingers across a textured surface gives rise to two types of skin deformations, each transduced by different tactile nerve fibers. Coarse features produce large-scale skin deformations whose spatial configuration is reflected in the spatial pattern of activation of some tactile fibers. Scanning a finely textured surface elicits vibrations in the skin, which in turn evoked temporally patterned responses in other fibers. These two neural codes-spatial and temporal-drive a spectrum of neural response properties in somatosensory cortex: At one extreme, neurons are sensitive to spatial patterns and encode coarse features; at the other extreme, neurons are sensitive to vibrations and encode fine features. While the texture responses of nerve fibers are dependent on scanning speed, those of cortical neurons are less so, giving rise to a speed invariant texture percept. Neurons in high-level somatosensory cortices combine information about texture with information about task variables.

Multiple Spatial Spectral Components of Static Skin Deformation for Predicting Macroscopic Roughness Perception

A previous study suggested a relationship between the spatial spectrum of finger pad skin deformation and perception of macroscopic roughness features. This study tested a new hypothesis that macroscopic roughness perception is the result of a weighted linear combination of multiple spatial spectral components of skin deformation. Experiments were conducted by capturing close-up images of finger pad deformation while the pads were pushed onto specimens with macroscopic features. Additionally, the roughness perceptions of these specimens were collected using a magnitude estimation method. The combination of spectral components predicted the roughness perception more accurately than any single spectral component. This suggests that roughness perception is mediated by multiple Gabor filter-like neural systems with different spatial periods, such as visual perception.