Perceptual constancy of texture roughness in the tactile system

Takashi Yoshioka, James C. Craig, Graham C. Beck, Steven S. Hsiao

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

Abstract

Our tactual perception of roughness is independent of the manner in which we touch the surface. A brick surface feels rough no matter how slowly or how rapidly we move our fingers, despite the fluctuating sensory inputs that are transmitted to the finger. Current theories of roughness perception rely solely on inputs from the cutaneous afferents, which are highly affected by scan velocity and force. The question then is: how is roughness constancy achieved? To this end, we characterized the subject's perceived roughness in six scanning conditions. These included two modes of touch: direct touch, where the finger is in contact with the surface, and indirect touch, where the surface is scanned with a hand-held probe; and three scanning modes: active (moving the hand across a stationary surface), passive (moving the surface across a stationary hand), and pseudo-passive (subject's hand is moved by the experimenter across a stationary surface). Here,weshow that roughness constancy is preserved during active but not passive scanning, indicating that the hand movement is necessary for roughness constancy in both direct and indirect touch. Roughness constancy is also preserved during pseudo-passive scanning, which stresses the importance of proprioceptive input. The results show that cutaneous input provides the signals necessary for roughness perception and that proprioceptive input resulting from hand movement-rather than a motor efference copy-is necessary to achieve roughness constancy. These findings have important implications in providing realistic sensory feedback for prosthetic-hand users.

Original languageEnglish (US)
Pages (from-to)17603-17611
Number of pages9
JournalJournal of Neuroscience
Volume31
Issue number48
DOIs
StatePublished - Nov 30 2011
Externally publishedYes

ASJC Scopus subject areas

  • General Neuroscience

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