Tactile detection of slip: surface microgeometry and peripheral neural codes

Abstract

1. The role of the microgeometry of planar surfaces in the detection of sliding of the surfaces on human and monkey fingerpads was investigated. By the use of a servo-controlled tactile stimulator to press and stroke glass plates on passive fingerpads of human subjects, the ability of humans to discriminate the direction of skin stretch caused by friction and to detect the sliding motion (slip) of the plates with or without micrometer-sized surface features was determined. To identify the associated peripheral neural codes, evoked responses to the same stimuli were recorded from single, low-threshold mechanoreceptive afferent fibers innervating the fingerpads of anesthetized macaque monkeys. 2. Humans could not detect the slip of a smooth glass plate on the fingerpad. However, the direction of skin stretch was perceived based on the information conveyed by the slowly adapting afferents that respond differentially to the stretch directions. Whereas the direction of skin stretch signaled the direction of impending slip, the perception of relative motion between the plate and the finger required the existence of detectable surface features. 3. Barely detectable micrometer-sized protrusions on smooth surfaces led to the detection of slip of these surfaces, because of the exclusive activation of rapidly adapting fibers of either the Meissner (RA) or the Pacinian (PC) type to specific geometries of the microfeatures. The motion of a smooth plate with a very small single raised dot (4 microns high, 550 microns diam) caused the sequential activation of neighboring RAs along the dot path, thus providing a reliable spatiotemporal code. The stroking of the plate with a fine homogeneous texture composed of a matrix of dots (1 microns high, 50 microns diam, and spaced at 100 microns center-to-center) induced vibrations in the fingerpad that activated only the PCs and resulted in an intensive code. 4. The results show that surprisingly small features on smooth surfaces are detected by humans and lead to the detection of slip of these surfaces, with the geometry of the microfeatures governing the associated neural codes. When the surface features are of sizes greater than the response thresholds of all the receptors, redundant spatiotemporal and intensive information is available for the detection of slip.