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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



ID: 312113.0, MPI für biologische Kybernetik / Biologische Kybernetik
Texture signals in whisker vibrations
Authors:Hipp, J.; Arabzadeh, E.; Conradt, J.; Zorzin, E.; Kayser, C.; Diamond, M.; König, P.
Date of Publication (YYYY-MM-DD):2006-02
Title of Journal:Journal of Neurophysiology
Volume:95
Issue / Number:3
Start Page:1792
End Page:1799
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:Rodents excel in making texture judgments by sweeping their whiskers across a
surface. Here, we aimed to identify the signals present in whisker vibrations that give
rise to such fine sensory discriminations. First, we used sensors to capture vibration
signals in metal whiskers during active whisking of an artificial system and in natural
whiskers during whisking of rats in vivo. Then, we developed a classification
algorithm that successfully matched the vibration frequency spectra of single trials to
the texture which induced it. For artificial whiskers, the algorithm correctly identified
1 texture out of 8 alternatives on 40% of trials; for in vivo natural whiskers, the
algorithm correctly identified 1 texture out of 5 alternatives on 80% of trials. Finally,
we asked which were the key discriminative features of the vibration spectra. Under
both artificial and natural conditions, the combination of two features accounted for
most of the information: The modulation power – the power of the part of the whisker
movement representing the modulation due to the texture surface – increased with the
coarseness of the texture; the modulation centroid – a measure related to the center of
gravity within the power spectrum – decreased with the coarseness of the texture.
Indeed, restricting the signal to these two parameters led to performance three-fourths
as high as the full spectra. Because earlier work showed that modulation power and
centroid are directly related to neuronal responses in the whisker pathway, we
conclude that the biological system optimally extracts vibration features to permit
texture classification.
External Publication Status:published
Document Type:Article
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Neurophysiology (Dept. Logothetis)
Identifiers:LOCALID:3720
URL:http://jn.physiology.org/cgi/reprint/95/3/1792
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