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ItemHuman ability to scale and discriminate forces typical of those occurring during grasp and manipulationWheat, HE ; Salo, LM ; Goodwin, AW (SOC NEUROSCIENCE, 2004-03-31)When humans manipulate objects, the sensorimotor system coordinates three-dimensional forces to optimize and maintain grasp stability. To do this, the CNS requires precise information about the magnitude and direction of load force (tangential to skin surface) plus feedback about grip force (normal to skin). Previous studies have shown that there is rapid, precise coordination between grip and load forces that deteriorates with digital nerve block. Obviously, mechanoreceptive afferents innervating fingerpad skin contribute essential information. We quantify human capacity to scale tangential and normal forces using only cutaneous information. Our paradigm simulated natural manipulations (a force tangential to the skin superimposed on an indenting force normal to the skin). Precisely controlled forces were applied by a custom-built stimulator to an immobilized fingerpad. Using magnitude estimation, subjects (n = 8) scaled the magnitude of tangential force (0.25-2.8 N) in two experiments (normal force, 2.5 and 4 N, respectively). Performance was unaffected by normal force magnitude and tangential force direction. Moreover, when both normal (2-4 N) and tangential forces were varied in a randomized-block factorial design, the relationship between applied and perceived tangential force remained near linear, with a minor but statistically significant nonlinearity. Our subjects could also discriminate small differences in tangential force, and this was the case for two different reference stimuli. In both cases, the Weber fraction was 0.16. Finally, scaling functions for magnitude estimates of normal force (1-5 N) were also approximately linear. These data show that the cutaneous afferents provide a wealth of precise information about both normal and tangential force.
ItemHow is tactile information affected by parameters of the population such as non-uniform fiber sensitivity, innervation geometry and response variability?Goodwin, AW ; Wheat, HE (ELSEVIER SCIENCE BV, 2002-09-20)Analysis of population responses in the tactile system requires a step beyond the isomorphic representations that are commonly presented. Using a simple model based on our data for spheres contacting the fingerpad, we illustrate how the parameters of the population itself have a profound effect on the fidelity of neural representations or codes. The effects of these parameters, such as innervation density, variability of sensitivity, type and covariance of noise are not apparent from single unit responses and, at least at present, require a theoretical or modeling approach of some sort.
ItemTactile discrimination of edge shape: Limits on spatial resolution imposed by parameters of the peripheral neural populationWheat, HE ; Goodwin, AW (SOC NEUROSCIENCE, 2001-10-01)When the flat faces of a coin are grasped between thumb and index finger, a "curved edge" is felt. Analogous curved edges were generated by our stimuli, which comprised the flat face of segments of annuli applied passively to immobilized fingers. Humans could scale the curvature of the annulus and could discriminate changes in curvature of approximately 20 m(-1). The responses of single slowly adapting type I afferents (SAIs) recorded in anesthetized monkeys could be quantified by the product of two factors: their sensitivity and a spatial profile dependent only on the radius of the annulus. This allowed us to reconstruct realistic SAI population responses that included noise, variation in fiber sensitivity, and varying innervation patterns. The critical question was how relatively small populations ( approximately 70 active fibers) can encode edge curvature with such precision. A template-matching approach was used to establish the accuracy of edge representation in the population. The known large interfiber variability in sensitivity had no effect on curvature resolution. Neural resolution was superior to human performance until large levels of central noise were present showing that, unlike simple detection, spatial processing is limited centrally. In contrast to the behavior of mean response codes, neural resolution improved with increasing covariance in noise. Surprisingly, resolution for any single population varied considerably with small changes in the position of the stimulus relative to the SAI matrix. Overall innervation density was not as critical as the spacing of receptive fields at right angles to the edge.