Literature DB >> 11562082

The frequency selectivity of information-processing channels in the tactile sensory system.

G A Gescheider1, S J Bolanowski, K R Hardick.   

Abstract

The frequency selectivity of the P, NP I, and NP II channels of the four-channel model of mechanoreception for glabrous skin was measured psychophysically by an adaptation tuning curve procedure. The results substantially extend the frequency range over which the frequency selectivity of these channels is known and further confirm the hypothesis that the input stage of each of these channels consists of specific sensory nerve fibers and associated receptors. Specifically, the frequency characteristics of Pacinian nerve fibers, rapidly adapting (RA) nerve fibers, and slowly adapting Type II (SA II) nerve fibers were found to be the peripheral neurophysiological correlates of the P, NP I, and NP II channels, respectively. The finding that the tuning characteristic for a test stimulus of 250 Hz delivered through a small (0.008 cm2) contactor depended dramatically on the duration of the test stimulus whereas the detection threshold did not, provides new evidence in support of the hypothesis that separate NP II and P channels exist.

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Mesh:

Year:  2001        PMID: 11562082     DOI: 10.1080/01421590120072187

Source DB:  PubMed          Journal:  Somatosens Mot Res        ISSN: 0899-0220            Impact factor:   1.111


  8 in total

1.  Integration of auditory and vibrotactile stimuli: effects of frequency.

Authors:  E Courtenay Wilson; Charlotte M Reed; Louis D Braida
Journal:  J Acoust Soc Am       Date:  2010-05       Impact factor: 1.840

2.  Noninformative vision causes adaptive changes in tactile sensitivity.

Authors:  Justin A Harris; Ehsan Arabzadeh; Clinton A Moore; Colin W G Clifford
Journal:  J Neurosci       Date:  2007-07-04       Impact factor: 6.167

3.  Effect of skin-transmitted vibration enhancement on vibrotactile perception.

Authors:  Yoshihiro Tanaka; Yuichiro Ueda; Akihito Sano
Journal:  Exp Brain Res       Date:  2015-03-19       Impact factor: 1.972

4.  Tactile Evaluation Feedback System for Multi-Layered Structure Inspired by Human Tactile Perception Mechanism.

Authors:  Iza Husna Mohamad Hashim; Shogo Kumamoto; Kenjiro Takemura; Takashi Maeno; Shin Okuda; Yukio Mori
Journal:  Sensors (Basel)       Date:  2017-11-11       Impact factor: 3.576

5.  A Model for Estimating Tactile Sensation by Machine Learning Based on Vibration Information Obtained while Touching an Object.

Authors:  Fumiya Ito; Kenjiro Takemura
Journal:  Sensors (Basel)       Date:  2021-11-23       Impact factor: 3.576

6.  Embodiment of supernumerary robotic limbs in virtual reality.

Authors:  Ken Arai; Hiroto Saito; Masaaki Fukuoka; Sachiyo Ueda; Maki Sugimoto; Michiteru Kitazaki; Masahiko Inami
Journal:  Sci Rep       Date:  2022-06-27       Impact factor: 4.996

7.  Nonlinear Tactile Estimation Model Based on Perceptibility of Mechanoreceptors Improves Quantitative Tactile Sensing.

Authors:  Momoko Sagara; Lisako Nobuyama; Kenjiro Takemura
Journal:  Sensors (Basel)       Date:  2022-09-04       Impact factor: 3.847

8.  Tactile Estimation of Molded Plastic Plates Based on the Estimated Impulse Responses of Mechanoreceptive Units.

Authors:  Lisako Nobuyama; Yuta Kurashina; Kei Kawauchi; Koji Matsui; Kenjiro Takemura
Journal:  Sensors (Basel)       Date:  2018-05-16       Impact factor: 3.576

  8 in total

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