Self-Motion and the Shaping of Sensory Signals
Identifieur interne : 001450 ( Ncbi/Checkpoint ); précédent : 001449; suivant : 001451Self-Motion and the Shaping of Sensory Signals
Auteurs : Robert A. Jenks ; Ashkan Vaziri [États-Unis] ; Ali-Reza Boloori [États-Unis] ; Garrett B. Stanley [Géorgie (pays)]Source :
- Journal of Neurophysiology [ 0022-3077 ] ; 2010.
Abstract
Sensory systems must form stable representations of the external environment in the presence of self-induced variations in sensory signals. It is also possible that the variations themselves may provide useful information about self-motion relative to the external environment. Rats have been shown to be capable of fine texture discrimination and object localization based on palpation by facial vibrissae, or whiskers, alone. During behavior, the facial vibrissae brush against objects and undergo deflection patterns that are influenced both by the surface features of the objects and by the animal's own motion. The extent to which behavioral variability shapes the sensory inputs to this pathway is unknown. Using high-resolution, high-speed videography of unconstrained rats running on a linear track, we measured several behavioral variables including running speed, distance to the track wall, and head angle, as well as the proximal vibrissa deflections while the distal portions of the vibrissae were in contact with periodic gratings. The measured deflections, which serve as the sensory input to this pathway, were strongly modulated both by the properties of the gratings and the trial-to-trial variations in head-motion and locomotion. Using presumed internal knowledge of locomotion and head-rotation, gratings were classified using short-duration trials (<150 ms) from high-frequency vibrissa motion, and the continuous trajectory of the animal's own motion through the track was decoded from the low frequency content. Together, these results suggest that rats have simultaneous access to low- and high-frequency information about their environment, which has been shown to be parsed into different processing streams that are likely important for accurate object localization and texture coding.
Url:
DOI: 10.1152/jn.00106.2009
PubMed: 20164407
PubMed Central: 2853282
Affiliations:
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PMC:2853282Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>Sensory systems must form stable representations of the external environment in the presence of self-induced variations in sensory signals. It is also possible that the variations themselves may provide useful information about self-motion relative to the external environment. Rats have been shown to be capable of fine texture discrimination and object localization based on palpation by facial vibrissae, or whiskers, alone. During behavior, the facial vibrissae brush against objects and undergo deflection patterns that are influenced both by the surface features of the objects and by the animal's own motion. The extent to which behavioral variability shapes the sensory inputs to this pathway is unknown. Using high-resolution, high-speed videography of unconstrained rats running on a linear track, we measured several behavioral variables including running speed, distance to the track wall, and head angle, as well as the proximal vibrissa deflections while the distal portions of the vibrissae were in contact with periodic gratings. The measured deflections, which serve as the sensory input to this pathway, were strongly modulated both by the properties of the gratings and the trial-to-trial variations in head-motion and locomotion. Using presumed internal knowledge of locomotion and head-rotation, gratings were classified using short-duration trials (<150 ms) from high-frequency vibrissa motion, and the continuous trajectory of the animal's own motion through the track was decoded from the low frequency content. Together, these results suggest that rats have simultaneous access to low- and high-frequency information about their environment, which has been shown to be parsed into different processing streams that are likely important for accurate object localization and texture coding.</p>
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