Neural coding mechanisms underlying perceived roughness of finely texturedsurfaces

Combined psychophysical and neurophysiological studies have shown that the perceived roughness of surfaces with element spacings of >1 mm is based on spatial variation in the firing rates of slowly adapting type 1 (SA1) affer ents (mean absolute difference in firing rates between SA1 afferents with r eceptive fields separated by similar to2 mm). The question addressed here i s whether this mechanism accounts for the perceived roughness of surfaces w ith element spacings of <1 mm. Twenty triangular and trapezoidal gratings p lus a smooth surface were used as stimulus patterns [spatial periods, 0.1-2 .0 mm; groove widths (GWs), 0.1-2.0 mm; and ridge widths (RWs), 0-1.0 mm]. In the human psychophysical studies, we found that the following equation d escribed the mean roughness magnitude estimates of the subjects accurately (0.99 correlation): 0.2 + 1.6GW - 0.5RW - 0.25GW(2). In the neurophysiologi cal studies, these surfaces were scanned across the receptive fields of SA1 , rapidly adapting, and Pacinian (PC) afferents, innervating the glabrous s kin of anesthetized macaque monkeys. SA1 spatial variation was highly corre lated (0.97) with human roughness judgments. There was no consistent relati onship between PC responses and roughness judgments; PC afferents responded strongly and almost equally to all of the patterns. Spatial variation in S A1 firing rates is the only neural code that accounts for the perceived rou ghness of surfaces with finely and coarsely spaced elements. When surface e lements are widely spaced, the spatial variation in firing rates is determi ned primarily by the surface pattern; when the elements are finely spaced, the variation in firing rates between SA1 afferents is determined by stocha stic variation in spike rates.