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From the April-June 2014 issue

Validating a Population Model of Tactile Mechanotransduction of Slowly Adapting Type I Afferents at Levels of Skin Mechanics, Single-Unit Response and Psychophysics

By Gregory J. Gerling, Isabelle I. Rivest, Daine R. Lesniak, Jacob R. Scanlon, and Lingtian Wan

Free Featured ArticlePrevious models of touch have linked skin mechanics to neural firing rate, neural dynamics to action potential elicitation, and mechanoreceptor populations to psychophysical discrimination. However, no one model spans all levels. The objective of work herein is to build a multi-level, computational model of tactile neurons embedded in cutaneous skin, and then validate its predictions of skin surface deflection, single-afferent firing to indenter shift, and population response for sphere discrimination. The model includes a 3D finite element representation of the distal phalange with hyper- and visco-elastic mechanics. Distributed over its surface, a population of receptor models is comprised of bi-phasic functions to represent Merkel cells' transformation of stress/strain to membrane current and a leaky integrate-and-fire neuronal models to generate the timing of action potentials. After including neuronal noise, the predictions of two population encoding strategies (gradient sum and euclidean distance) are compared to psychophysical discrimination of spheres. Results indicate that predicted skin surface deflection matches Srinivasan's observations for 50 micron and 3.17 mm diameter cylinders and single-afferent responses achieve R2 = 0.81 when compared to Johnson's recordings. Discrimination results correlate with Goodwin's experiments, whereby 287 and 365 m-1 spheres are more discriminable than 287 and 296 m-1.

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ToH is a joint publication of the IEEE Computer Society, IEEE Robotics and Automation Society and the IEEE Consumer Electronics Society.

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A word from former Editor-in-Chief J. Edward Colgate

IEEE Transactions on Haptics (ToH) is a quarterly journal that publishes archival research results related to the science, technology and applications associated with information acquisition and object manipulation through touch.
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