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Tactual discrimination of softness: abilities and mechanisms

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Part of the Advances in Life Sciences book series (ALS)

Summary

The ability of human subjects to discriminate softness was investigated. In addition, the associated mechanistic cues and the peripheral neural codes on which the discrimination may be based were investigated using monkeys. Two sets of compliant objects were constructed: (1) those with a deformable surface, composed of transparent silicone rubber of variable softness; (2) rigid plates supported by springs of variable compliance in cylindrical sleeves. To assess the relative contributions of tactile and kinesthetic information, psychophysical experiments were performed on human subjects under both active and passive touch, with or without local anesthesia that blocked the tactile information from the fingerpads. The results for objects with deformable surfaces show that whereas the subjects are quite good at discriminating subtle differences in softness under both active and passive touch without anesthesia, they are unable to discriminate even large differences under active touch with anesthesia. Therefore, we conclude that the discrimination is based entirely on tactile information. The mechanistic data for rubber specimens indicates that the basis for the perception of softness of rubber-like objects is likely to be the spatio-temporal variation of pressure on the skin (or, equivalently, the skin displacement and its derivatives). Neurophysiological data shows that the resulting responses from slowly adapting type I afferent population within the skin might encode the compliance of the objects. For compliant objects with rigid surfaces best discrimination was achieved only with active touch, due to the availability of both tactile and kinesthetic information; under passive conditions, the absence of kinesthetic information resulted in considerable deterioration of discriminability

Keywords

Rigid Surface Just Noticeable Difference Tactile Information Deformable Surface Active Touch 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Birkhäuser Verlag Basel/Switzerland 1996

Authors and Affiliations

  1. 1.Department of Mechanical Engineering and Research Laboratory of ElectronicsMassachusetts Institute of TechnologyCambridgeUSA
  2. 2.Department of AnesthesiologyYale University School of MedicineNew HavenUSA

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