Texture from touch

From Scholarpedia
Sliman Bensmaia (2009), Scholarpedia, 4(8):7956. doi:10.4249/scholarpedia.7956 revision #149771 [link to/cite this article]
Jump to: navigation, search

Texture from touch refers to the processing of information about surface material and microgeometry obtained from tactile exploration. Though textural information can be obtained both visually (Heller, 1989) and auditorily (Lederman, 1979), touch yields much finer and more complex textural information than do the other sensory modalities. Humans can distinguish textures whose elements differ in size by tens of nanometers or whose spatial periods differ by hundreds of nanometers (Skedung et al., 2014). When we run our fingers across a surface, we may perceive the surface as being rough, like sandpaper, or smooth, like glass; the surface may also vary along other sensory continua, such as hardness (e.g., stone) vs. softness (e.g. moist sponge), stickiness (e.g., tape) vs. slipperiness (e.g., soap). Also, whether a texture is thermally isolating (e.g., leather) or thermally conductive (like metal) contributes to the textural percept (Hollins et al., 1993; Hollins et al., 2000; Bensmaia and Hollins, 2005). Tactile texture perception plays a role in the tactile recognition of objects (Klatzky et al., 1987) as most natural objects differ not only in shape but in texture as well. Furthermore, certain types of texture information are essential in order to properly manipulate objects (Johansson and Flanagan, 2009). Texture is represented at the somatosensory periphery in the spatiotemporal pattern of activity in populations of receptors embedded in the skin and in cortex by different populations of neurons with different response properties.


Neural basis of texture perception in the nerve

Three types of mechanoreceptive afferents contribute to the tactile perception of texture, namely slowly adapting type 1 (SA1), rapidly adapting (RA), and Pacinian (PC) afferents, which innervate Merkel cells, Meissner corpuscles, and Pacinian corpuscles, respectively. Coarse textural features, with element sizes on the order of millimeters, are encoded in the responses of SA1 afferents. Specifically, the spatial configuration of coarse surface elements is reflected in the spatial pattern of SA1 activation. However, this encoding mechanism is limited by the innervation density of these receptors (which are spaced about 1 mm apart; cf. Vallbo and Johansson, 1979). To perceive fine textural features, motion between skin and surface is required: When the exploring finger scans a fine texture, small vibrations are produced in the skin, which reflect both the microgeometry of the surface and that of the fingerprint (Hollins et al., 1998; Hollins et al., 2001; Hollins et al., 2002; Bensmaia and Hollins, 2003; Bensmaia and Hollins, 2005; Manfredi et al., 2014). These texture-elicited vibrations are transduced and processed by two other populations of vibration-sensitive fibers, namely RA and PC afferents (Weber et al., 2013). These fibers respond to textures by producing highly repeatable temporal spiking patterns, which are sufficiently informative about texture identify to mediate our ability to identify and discriminate tactile textures (Weber et al., 2013). This vibrotactile coding scheme is analogous to that is observed in the vibrissal system of rodents (see http://www.scholarpedia.org/article/Vibrissal_texture_decoding).

Neural basis of texture perception in cortex

As discussed above, tactile texture perception relies on two distinct mechanism: a spatial mechanism mediated by SA1 fibers, and a temporal mechanism mediated by RA and PC fibers. In cortex, a subpopulation of neurons exhibit receptive field properties that are well suited to analyze the spatial image of a texture conveyed by SA1 afferents. To investigate the receptive field properties of these neurons, random dot patterns (DiCarlo et al., 1998; DiCarlo and Johnson, 1999; DiCarlo and Johnson, 2000) or spatiotemporal white noise stimuli (Sripati et al., 2005) were presented to the glabrous skin of the distal finger pads while neuronal responses in primary somatosensory cortex (SI) were recorded. The spatial and spatiotemporal receptive fields (SRFs and STRFs) of SI neurons were computed from these measurements using reverse correlation (DiCarlo et al., 1998; DiCarlo and Johnson, 1999; DiCarlo and Johnson, 2000; Sripati et al., 2005). A subpopulation of neurons, whose SRFs or STRFs comprise excitatory and inhibitory sub-regions and are thus highly analogous to neurons in primary visual cortex, are ideally suited to analyze the spatial image conveyed by SA1 neurons. The texture signal carried in the responses of RA and PC afferents likely drives the responses of another population of SI neurons that exhibits highly patterned responses to skin vibrations (Harvey et al., 2013). Indeed, these neurons receive input from both RA and PC afferents (Saal et al., 2014) and produce entrained responses to simple and complex (texture-like) vibrations across the range of frequencies that are experienced during tactile texture exploration. How texture information from these two streams – spatial and temporal – is combined to culminate in a holistic percept of texture remains to be elucidated.

The dimensions of texture

The tactile exploration of a surface has been shown to yield a multidimensional textural percept that includes sensations of roughness/smoothness, hardness/softness, stickiness/slipperiness, warmth/coolness (Hollins et al., 1993; Hollins et al., 2000; Bensmaia and Hollins, 2005). The overall textural percept of a surface is strongly determined by three of these texture properties, namely roughness, hardness and stickiness. Of all textural continua, the study of roughness has been the most extensive and has yielded important insights into neural coding in the somatosensory system.


The subjective sense of roughness seems to vary along a single dimension and has been shown to vary predictably with surface properties. In psychophysical studies, the perceived roughness of sandpapers increases as a power function of particle size (exponent ≈ 1.5), the roughness of gratings increases linearly with spatial period (Lederman and Taylor, 1972; Chapman et al., 2002), and that of embossed dots increases monotonically with inter-element spacing up to a spatial period of about 2 mm, then decreases with further increases in spatial period (Morley et al., 1983; Connor et al., 1990). For gratings, however, the spatial period does not seem to be the relevant stimulus property. For instance, changing the groove width and ridge width of gratings has opposite effects on perceived roughness (Lederman and Taylor, 1972; Sathian et al., 1989). The main determinant of perceived roughness seems to be the spatial pattern of deformation of the skin (Taylor and Lederman, 1975) although temporal cues (Cascio and Sathian, 2001; Gamzu and Ahissar, 2001) and tangential forces (Smith et al., 2002) also play a role. In a series of studies pairing human psychophysics with macaque neurophysiology, Johnson and colleagues set out to establish the peripheral neural code underlying roughness perception (Connor et al., 1990; Connor and Johnson, 1992; Blake et al., 1997; Yoshioka et al., 2001). Their approach consisted of devising and testing a set of hypotheses linking the activity evoked by textured surfaces in populations of mechanoreceptive afferents, measured in macaque monkeys, to estimates of their perceived roughness, measured in human observers. The stimuli consisted of embossed dot patterns, varying in their spatial properties, presented passively to the skin using a rotating drum stimulator (Johnson and Phillips, 1988). The roughness estimates, obtained for a variety of dot patterns, were plotted against predictions derived from each putative neural code. A hypothesis was eliminated if it failed to account for roughness estimates under any single experimental condition. The putative neural codes for roughness included (1) the mean firing rate elicited in a given population of mechanoreceptive afferents fibers; (2) the temporal variability in the firing of a given population of mechanoreceptive afferent fibers; (3) the spatial variability in the firing of a given population of mechanoreceptive afferent fibers. The spatial variability in the responses of slowly adapting type 1 afferents was found to account for perceived roughness of all the textures tested.

In the aforementioned studies, however, textured surfaces tended to be relatively coarse, ranging in inter-element spacing from 0.5 mm to 5 mm (with the exception one or two stimuli in Yoshioka et al., 2001). A first hint that SA1 afferents were not solely responsible for roughness coding was provided in a study that showed that low-frequency vibratory adaptation (at 10 Hz), which would primarily desensitize RA and SA1 fibers (Bensmaia et al., 2005), had no effect on fine texture discrimination (with elements sized in the tens of microns), whereas high-frequency adaptation, targeting PC fibers, abolished subjects ability to discriminate fine textures (Hollins et al., 2001). When roughness coding was investigated with a wide range of textures, it was found that the spatial code mediated by SA1 fibers could not account for the perceived roughness over the range of tangible textures. Rather, roughness judgments could be accounted for based on a combination of spatial variation in SA1 (following Johnson and colleagues) and temporal variation in RA and PC fibers (Weber et al., 2013). That is, a texture is rough to the extent that the response it evokes in SA1 afferents is spatially inhomogeneous and the response it evokes in RA and PC afferents is temporally inhomogeneous.

Information about roughness is encoded in SI as evidenced by the fact that the responses of neurons in this brain area are sensitive to changes in surface properties that determine perceived roughness, namely the spatial period of embossed dot patterns and the groove width of tactile gratings (Darian-Smith et al., 1982; Darian-Smith et al., 1984; Sinclair and Burton, 1991; Tremblay et al., 1996; Sinclair et al., 1996; Chapman et al., 2002). Lesions in SI, particularly in areas 3b and 1, lead to severe impairments in roughness discrimination (Randolph and Semmes, 1974). The second somatosensory cortex (SII) has also been implicated in the processing of surface roughness as it contains neurons that are sensitive to the relevant surface properties (Jiang et al., 1997; Pruett, Jr. et al., 2000) and lesions in SII cause impairments in roughness discrimination (Murray and Mishkin, 1984). Finally, the lateral parietal opercular cortex (Roland et al., 1998; Stilla and Sathian, 2008) is selectively activated when human subjects perform a roughness discrimination task, as are the posterior insula and the medial occipital cortex (Stilla and Sathian, 2008), indicating that they too are involved in the cortical processing of roughness information. Spatial variability in the peripheral response – which drives the perception of roughness for coarse textures – is likely computed by the subpopulation of neurons, described above, whose receptive fields comprise excitatory and inhibitory sub-regions. In fact, a subset of these neurons exhibit responses to embossed dot patterns that match their perceived roughness: Their response increases for inter-element spacings up to about 2mm, then decreases (Arun Sripati, personal communication); this population of neurons is thus ideally suited to extract roughness information from spatial patterns of SA1 activation. The roughness signal carried in the responses of RA and PC afferents likely drives responses in another population of SI neurons, also described above, that are highly sensitive to skin vibrations over a wide range of frequencies (Harvey et al., 2013) and receive input from both RA and PC fibers (Saal et al., 2014).


Hardness/softness is the subjective continuum associated with the compliance of an object: Hardness ratings have been shown to be inversely proportional to softness ratings; these ratings are, in turn, related to surface compliance following Stevens’s power law (Harper and Stevens, 1964). Softness perception has been shown to rely primarily on cutaneous cues: eliminating kinesthetic information has no effect on subjects’ ability to discriminate softness (Srinivasan and LaMotte, 1995). As the hand is pressed up against a compliant object, it conforms to the contour of the hand in proportion to the contact force. The compliance (and the softness) of the object may be signaled by the growth of the area over which the skin contacts the object as the contact force increases, as well as the increase in the force exerted by the object on the skin across the contact area. Softness perception likely relies on signals from SA1 fibers (Srinivasan and LaMotte, 1996): First, PC fibers are too sparse and their RFs too large to play a significant role in softness perception. Second, the response of RA fibers to a surface indented into the skin is not modulated by the compliance of the surface whereas the response of SA1 fibers is (Srinivasan and LaMotte, 1996). Although the evidence suggests that SA1 fibers are implicated in softness perception, the neural code for softness is unclear: the rate of indentation (in addition to surface compliance) modulates the discharge rate in individual SA1 afferents whereas softness perception is independent of the rate with which a surface is (passively) indented into the skin. Thus, the firing rate in a single SA1 fiber does not unambiguously encode the compliance of an object. One possibility is that the average pressure exerted across the contact area is predictive of compliance and invariant with respect to indentation velocity; it may then be this quantity – average pressure – that is encoded in the population response of SA1 fibers.


Stickiness/slipperiness is the sensory continuum associated with the friction between skin and surface. Indeed, magnitude estimates of stickiness have been shown to closely match the measured kinetic friction between skin and surface, i.e. the ratio between the force exerted normal to the surface to that exerted parallel to the plane of the surface (Smith and Scott, 1996). Furthermore, when judging stickiness, subjects do not substantially vary the normal forces they apply on the surface, but the applied tangential forces tend to vary across surfaces, suggesting that tangential forces are critical in the perception of stickiness. As slowly adapting type 2 fibers are sensitive to skin stretch (Witt and Hensel, 1959; Iggo, 1966; Knibestöl, 1975), this population of mechanoreceptive afferent fibers may provide the peripheral signals underlying stickiness perception, although recent evidence suggests that other mechanoreceptive afferents also convey information about tangential forces exerted on the skin (Birznieks et al., 2001).

Thermal conductivity

Because ambient temperatures are generally cooler than the temperature of the skin, objects in the environment tend to conduct heat out of the skin when contacted. The perceived warmth or coolness of a surface is determined by how slowly or rapidly heat is conducted out of the skin (Ho and Jones, 2006; Ho and Jones, 2008). The perception of the thermal quality of a surface is likely mediated by thermoreceptors in the skin (Darian-Smith et al., 1973; Johnson et al., 1973; Darian-Smith et al., 1979; Johnson et al., 1979).


Bensmaia SJ, Hollins M (2003) The vibrations of texture. Somatosens Mot Res 20:33-43.

Bensmaia SJ, Hollins M (2005) Pacinian representations of fine surface texture. Percept Psychophys 67:842-854.

Bensmaia SJ, Leung YY, Hsiao SS, Johnson KO (2005) Vibratory adaptation of cutaneous mechanoreceptive afferents. J Neurophysiol 94:3023-3036.

Birznieks I, Jenmalm P, Goodwin AW, Johansson RS (2001) Encoding of direction of fingertip forces by human tactile afferents. J Neurosci 21:8222-8237.

Blake DT, Hsiao SS, Johnson KO (1997) Neural coding mechanisms in tactile pattern recognition: the relative contributions of slowly and rapidly adapting mechanoreceptors to perceived roughness. J Neurosci 17:7480-7489.

Cascio CJ, Sathian K (2001) Temporal cues contribute to tactile perception of roughness. J Neurosci 21:5289-5296.

Chapman CE, Tremblay F, Jiang W, Belingard L, Meftah EM (2002) Central neural mechanisms contributing to the perception of tactile roughness. Behav Brain Res 135:225-233.

Connor CE, Hsiao SS, Phillips JR, Johnson KO (1990) Tactile roughness: neural codes that account for psychophysical magnitude estimates. J Neurosci 10:3823-3836.

Connor CE, Johnson KO (1992) Neural coding of tactile texture: comparisons of spatial and temporal mechanisms for roughness perception. J Neurosci 12:3414-3426.

Darian-Smith I, Goodwin AW, Sugitani M, Heywood J (1984) The tangible features of textured surfaces: their representation in the monkey's somatosensory cortex. In: Dynamic Aspects of Neocortical Function (Edelman GM, Gall WE, Cowan WM, eds), pp 475-500. New York: Wiley. Darian-Smith I, Johnson KO, Dykes RW (1973) The 'cold' fiber population innervating palmar and digital skin of the monkey: responses to cooling pulses. J Neurophysiol 36:325-346.

Darian-Smith I, Johnson KO, LaMotte CC, Shigenaga Y, Kenins P, Champness P (1979) Warm fibers innervating palmar and digital skin of the monkey: responses to thermal stimuli. J Neurophysiol 42:1297-1315.

Darian-Smith I, Sugitani M, Heywood J, Karita K, Goodwin AW (1982) Touching textured surfaces: Cells in somatosensory cortex respond both to finger movements and to surface features. Science 218:906-909.

DiCarlo JJ, Johnson KO (1999) Velocity invariance of receptive field structure in somatosensory cortical area 3b of the alert monkey. J Neurosci 19:401-419.

DiCarlo JJ, Johnson KO (2000) Spatial and temporal structure of receptive fields in primate somatosensory area 3b: effects of stimulus scanning direction and orientation. J Neurosci 20:495-510.

DiCarlo JJ, Johnson KO, Hsiao SS (1998) Structure of receptive fields in area 3b of primary somatosensory cortex in the alert monkey. J Neurosci 18:2626-2645.

Gamzu E, Ahissar E (2001) Importance of temporal cues for tactile spatial-frequency discrimination. J Neurosci 21:7416-7427.

Harper R, Stevens SS (1964) Subjective hardness of compliant materials. Q J Exp Psychol 16:204-215.

Harvey M, Saal, HP, Dammann, JF, Bensmaia SJ (2013) Multiplexing stimulus information through rate and temporal codes in primate somatosensory cortex. PLoS Biol 11:e1001558.

Heller MA (1989) Texture perception in sighted and blind observers. Percept Psychophys 45:49-54.

Ho HN, Jones LA (2006) Contribution of thermal cues to material discrimination and localization. Percept Psychophys 68:118-128.

Ho HN, Jones LA (2008) Modeling the thermal responses of the skin surface during hand-object interactions. J Biomech Eng 130:021005.

Hollins M, Bensmaïa SJ, Karlof K, Young F (2000) Individual differences in perceptual space for tactile textures: Evidence from multidimensional scaling. Percept Psychophys 62:1534-1544.

Hollins M, Bensmaïa SJ, Risner R (1998) The duplex theory of tactile texture perception. In: Fechner Day 98: Proceedings of the Fourteenth Annual Meeting of the International Society for Psychophysics (Grondin S, Lacouture Y, eds), pp 115-120. Quebec, Canada: The International Society for Psychophysics.

Hollins M, Bensmaia SJ, Roy EA (2002) Vibrotaction and texture perception. Behav Brain Res 135:51-56.

Hollins M, Bensmaia SJ, Washburn S (2001) Vibrotactile adaptation impairs discrimination of fine, but not coarse, textures. Somatosens Mot Res 18:253-262.

Hollins M, Faldowski R, Rao S, Young F (1993) Perceptual dimensions of tactile surface texture: A multidimensional-scaling analysis. Percept Psychophys 54:697-705.

Iggo A (1966) Cutaneous receptors with a high sensitivity to mechanical displacement. In: Touch, Heat and Pain (de Reuck AV, Knight J, eds), pp 237-260. Boston: Little, Brown and Company.

Jiang W, Tremblay F, Chapman CE (1997) Neuronal encoding of texture changes in the primary and the secondary somatosensory cortical areas of monkeys during passive texture discrimination. J Neurophysiol 77:1656-1662.

Johansson RS, Flanagan JR (2009) Coding and use of tactile signals from the fingertips in object manipulation tasks. Nat Rev Neurosci 10:345-359.

Johnson KO, Darian-Smith I, LaMotte CC (1973) Peripheral neural determinants of temperature discrimination in man: a correlative study of responses to cooling skin. J Neurophysiol 36:347-370.

Johnson KO, Darian-Smith I, LaMotte CC, Johnson B, Oldfield SR (1979) Coding of incremental changes in skin temperature by a population of warm fibers in the monkey: Correlation with intensity discrimination in man. J Neurophysiol 42:1332-1353.

Johnson KO, Phillips JR (1988) A rotating drum stimulator for scanning embossed patterns and textures across the skin. J Neurosci Methods 22:221-231.

Klatzky RL, Lederman SJ, Reed CL (1987) There's more to touch than meets the eye: The salience of object attributes for haptics with and without vision. J Exp Psychol Gen 116:356-369.

Knibestöl M (1975) Stimulus-response functions of slowly adapting mechanoreceptors in the human glabrous skin area. J Physiol 245:63-80. Lederman SJ (1979) Auditory texture perception. Perception 8:93-103.

Lederman SJ, Taylor MM (1972) Fingertip force, surface geometry, and the perception of roughness by active touch. Percept Psychophys 12:401-408.

Manfredi LR, Saal HP, Brown KJ, Zielinski MC, Dammann JF, Polashock VS, Bensmaia SJ (2013) Natural scenes in tactile texture 111:1792:1802.

Morley JW, Goodwin AW, Darian-Smith I (1983) Tactile discrimination of gratings. Exp Brain Res 49:291-299.

Murray EA, Mishkin M (1984) Relative contributions of SII and area 5 to tactile discrimination in monkeys. Behav Brain Res 11:67-85. Pruett JR, Jr., Sinclair RJ, Burton H (2000) Response patterns in second somatosensory cortex (SII) of awake monkeys to passively applied tactile gratings. J Neurophysiol 84:780-797.

Randolph M, Semmes J (1974) Behavioral consequences of selective ablations in the postcentral gyrus of Macaca mulatta. Brain Res 70:55-70. Roland PE, O'Sullivan B, Kawashima R (1998) Shape and roughness activate different somatosensory areas in the human brain. Proc Natl Acad Sci U S A 95:3295-3300.

Saal HP, Harvey MA, Bensmaia SJ (2014) Integration of cutaneous submodalities in primate somatosensory cortex. SfN abstracts 44: 339.07.

Sathian K, Goodwin AW, John KT, Darian-Smith I (1989) Perceived roughness of a grating: correlation with responses of mechanoreceptive afferents innervating the monkey's fingerpad. J Neurosci 9:1273-1279.

Sinclair RJ, Burton H (1991) Neuronal activity in the primary somatosensory cortex in monkeys (Macaca mulatta) during active touch of textured surface gratings: Responses to groove width, applied force, and velocity of motion. J Neurophysiol 66:153-169.

Sinclair RJ, Pruett JR, Burton H (1996) Responses in primary somatosensory cortex of rhesus monkey to controlled application of embossed grating and bar patterns. Somatosens Mot Res 13:287-306.

Skedung L, Arvidsson M, Chung JY, Stafford CM, Berglund B, Rutland MW (2013). Feeling small: exploring the tactile perception limits. Sci Rep 3:2617.

Smith AM, Chapman CE, Deslandes M, Langlais JS, Thibodeau MP (2002) Role of friction and tangential force variation in the subjective scaling of tactile roughness. Exp Brain Res 144:211-223.

Smith AM, Scott SH (1996) Subjective scaling of smooth surface friction. J Neurophysiol 75:1957-1962.

Srinivasan MA, LaMotte RH (1995) Tactual discrimination of softness. J Neurophysiol 73:88-101.

Srinivasan MA, LaMotte RH (1996) Tactual discrimination of softness: Abilities and mechanisms. In: Somesthesis and the Neurobiology of the Somatosensory Cortex (Franzén O, Johansson RS, Terenius L, eds), pp 123-135. Basel: Birkhäuser.

Sripati AP, Yoshioka T, Denchev P, Hsiao SS, Johnson KO (2006) Spatiotemporal receptive fields of peripheral afferents and cortical area 3b and 1 neurons in the primate somatosensory system. J Neurosci 26:2101-2114.

Stilla R, Sathian K (2008) Selective visuo-haptic processing of shape and texture. Hum Brain Mapp 29:1123-1193.

Taylor MM, Lederman SJ (1975) Tactile roughness of grooved surfaces: A model and the effect of friction. Percept Psychophys 17:23-36.

Tremblay F, Ageranioti-Bélanger SA, Chapman CE (1996) Cortical mechanisms underlying tactile discrimination in the monkey. I. role of primary somatosensory cortex in passive texture discrimination. J Neurophysiol 79:3382-3403.

Vallbo, AB, Johansson, RS (1979) Tactile sensibility in the human hand: relative and absolute densities of four types of mechanoreceptive units in glabrous skin. J Physiol 286:283-300.

Weber AI, Saal HP, Lieber JD, Cheng JW, Manfredi LR, Dammann JF, Bensmaia SJ (2013) Spatial and temporal codes mediate the tactile perception of textures. Proc Natl Acad Sci 110:18279-18284.

Witt I, Hensel H (1959) Afferente Impulse aus der Extremitätenhaut der Katze bei thermischer und mechanischer Reizung. Pflugers Arch ges Phsyiol 268:582-596.

Yoshioka T, Gibb B, Dorsch AK, Hsiao SS, Johnson KO (2001) Neural coding mechanisms underlying perceived roughness of finely textured surfaces. J Neurosci 21:6905-6916.

See also

Personal tools

Focal areas