Euclidian model, INDSCAL, measurement, similarities, data analysis, similarities data, quantification, successive block algorithm,

The purpose of this study was to examine the subjective dimensionality of tactile surface texture perception. Seventeen tactile stimuli, such as wood, sandpaper, and velvet, were moved across the index finger of the subject, who sorted them into categories on the basis of perceived similarity. Multidimensional scaling (MDS) techniques were then used to position the stimuli in a perceptual space on the basis of combined data of 20 subjects. A three-dimensional space was judged to give a satisfactory representation of the data. Subjects' ratings of each stimulus on five scales representing putative dimensions of perceived surface texture were then fitted by regression analysis into the MDS space. Roughness-smoothness and hardness-softness were found to be robust and orthogonal dimensions; the third dimension did not correspond closely with any of the rating scales used, but post hoc inspection of the data suggested that it may reflect the compressional elasticity ("springiness") of the surface.A complex sensory experience occurs when a person draws a finger across the surface of an object. In addition to whatever information may be gained about the shape and other geometrical properties of the object, the observer also receives impressions related to the nature of the surface. These experiences of surface texture are the subject of this report. Although some aspects of surface texture have been extensively studied, an overall understanding of texture perception remains elusive. In the words of Connor, Hsiao, Phillips, and Johnson (1990), "Tactile texture perception is poorly understood; with few exceptions, little is known about its dimensionality, its physical determinants, or its neural mechanisms."Modem study of texture perception dates from the work of David Katz, whose monograph The World of Touch (1925/l989) set the agenda for much of the later work on the subject. Katz asked subjects to discriminate, and to describe, a wide variety of tactile surfaces under various conditions of touching. One of Katz's central concepts was a distinction between two types of surface properties, which he called Modifikationen (qualities) and Spezifikationen (identifying characteristics). By "qualities," he meant properties on which any tactile surface could be rated; he mentioned roughness and hardness as two such dimensional qualities, but left open the possibility that there were others, as yet unidentified. By "identifying characteristics," Katz meant the characteristic overall feel of a surface-the "Ieatheriness" of leather, the "rubberiness" of rubber, and so on. It is unclear in Katz's writings, probably because he had no settled opinion on the subject, exactly what the relationship is between these two types of properties. Are identifying characteristics simply certain combinations of values of the qualities? That is, will all surfaces with a particular roughness, combined with a particular hardness and particular values on other qualitative dimensions that may exist, feel like the same material? Or, alternatively, doe...

multiple correspondence analysis, optimal scaling, dual scaling, homogeneity analysis, categorical multivariate data,

Ratio scaling was used to obtain from 5 subjects estimates of the subjective dissimilarity between the members of all possible pairs of 17 tactile surfaces. The stimuli were a diverse array of everyday surfaces, such as corduroy, sandpaper, and synthetic fur. The results were analyzed using the multidimensional scaling (MDS) program ALSCAL. There was substantial, but not complete, agreement across subjects in the spatial arrangement of perceived textures. Scree plots and multivariate analysis suggested that, for some subjects, a two-dimensional space was the optimal MDS solution, whereas for other subjects, a three-dimensional space was indicated. Subsequent to their dissimilarity scaling, subjects rated each stimulus on each of five adjective scales. Consistent with earlier research, two of these (rough/smooth and soft/hard) were robustly related to the space for all subjects. A third scale, sticky/slippery, was more variably related to the dissimilarity data: regressed into three-dimensional MDS space, it was angled steeply into the third dimension only for subjects whose scree plots favored a nonplanar solution. We conclude that the sticky/slippery dimension is perceptually weighted less than the rough/smooth and soft/hard dimensions, materially contributing to the structure of perceptual space only in some individuals.In touch, as in other sensory modalities, stimuli can differ in a large number of physical properties. For example, the surfaces ofobjects presented to the sense of touch can differ from one another in their frictional resistance to lateral movement of a finger across them, in their compressibility in response to radial force, their thermal conductivity, and in the presence, density, size, composition, and arrangement of structural elements that disturb the flatness of the surface. Considerable research documents the close relationship between these properties and subjective qualities such as roughness, softness, and slipperiness (Connor, Hsiao, Phillips, & Johnson, 1990;Connor & Johnson, 1992;Katz, 1925Katz, /1989Lederman & Taylor, 1972;Srinivasan & LaMotte, 1996;Srinivasan, Whitehouse, & LaMotte, 1990;S. S. Stevens & Harris, 1962;Taylor & Lederman, 1975). When an overall impression of such a stimulus is obtained in a relatively brief exposure, it is reasonable to ask (I) which and how many of its properties enter into this impression, and how fully they are combined, and (2) how the stimuli seem to the subject to be related to one another-for example, whether they are arranged in an orderly dimensional structure (analogous, e.g., to color space) defined by the subjective dimensions corresponding to their component properties.

exploratory data analysis, descriptive data analysis, multivariate data analysis, nonmetric data analysis, alternating least squares, scaling, data theory,