Embodied Information Processing: Vibrissa Mechanics and Texture Features Shape Micro-Motions in Actively Sensing Rats
Identifieur interne : 004B66 ( Main/Exploration ); précédent : 004B65; suivant : 004B67Embodied Information Processing: Vibrissa Mechanics and Texture Features Shape Micro-Motions in Actively Sensing Rats
Auteurs : Jason T. Ritt ; Mark L. Andermann ; Christopher I. MooreSource :
- Neuron [ 0896-6273 ] ; 2008.
Abstract
Peripheral sensory organs provide the first transformation of sensory information, and understanding how their physical embodiment shapes transduction is central to understanding perception. We report the first characterization of surface transduction during active sensing in the rodent vibrissa sensory system, a widely used model. Employing high-speed videography, we tracked vibrissae while rats sampled rough and smooth textures. Variation in vibrissa length predicted motion mean frequencies, including for the highest velocity events, indicating that biomechanics, such as vibrissa resonance, shape signals most likely to drive neural activity. Rough surface contact generated large amplitude, high velocity “stick-slip-ring” events, while smooth surfaces generated smaller and more regular stick-slip oscillations. Both surfaces produced velocities exceeding those applied in reduced preparations, indicating active sensation of surfaces generates more robust drive than previously predicted. These findings demonstrate a key role for embodiment in vibrissal sensing, and the importance of input transformations in sensory representation.
Url:
DOI: 10.1016/j.neuron.2007.12.024
PubMed: 18304488
PubMed Central: 4391974
Affiliations:
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<front><div type="abstract" xml:lang="en"><p id="P2">Peripheral sensory organs provide the first transformation of sensory information, and understanding how their physical embodiment shapes transduction is central to understanding perception. We report the first characterization of surface transduction during active sensing in the rodent vibrissa sensory system, a widely used model. Employing high-speed videography, we tracked vibrissae while rats sampled rough and smooth textures. Variation in vibrissa length predicted motion mean frequencies, including for the highest velocity events, indicating that biomechanics, such as vibrissa resonance, shape signals most likely to drive neural activity. Rough surface contact generated large amplitude, high velocity “stick-slip-ring” events, while smooth surfaces generated smaller and more regular stick-slip oscillations. Both surfaces produced velocities exceeding those applied in reduced preparations, indicating active sensation of surfaces generates more robust drive than previously predicted. These findings demonstrate a key role for embodiment in vibrissal sensing, and the importance of input transformations in sensory representation.</p>
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