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Dynamic Translation of Surface Coarseness Into Whisker Vibrations

Department of Physiology, Zlotowski Center for Neuroscience, Ben-Gurion University, Israel

Submitted 25 February 2008; accepted in final form 14 September 2008

Rodents in their natural environment use their whiskers to distinguish between surfaces having subtly different textures and shapes. They do so by actively sweeping their whiskers across surfaces in a rhythmic motion. To determine how textures are transformed into vibration signals in whiskers and how these vibrations are expressed in neuronal discharges, we induced active whisking in anesthetized rats, monitored the movement of whiskers across surfaces, and concurrently recorded from trigeminal ganglion (TG) neurons. We show that tactile information is transmitted through high-frequency micromotions superimposed on whisking macro motions. Consistent with this, we find that in most TG neurons, spike activity, and high-frequency micromotions are closely correlated. To determine whether these vibration signals can support texture discrimination, we examined their dependence on surface roughness and found that both vibration signals carry information about surface coarseness. Despite a large variability in this translation process, different textures are translated into distinct vibrations profiles. These profiles depend on whiskers properties, on radial distance to the surface, and on whisking frequency. Using the characteristics of these signals, we employ linear discriminant analysis and found that all whiskers were able to discriminate between different textures. While deteriorating with radial distance, this classification did not depend on whisking frequency. Finally, increasing the number of whisks and integrating tactile information from multiple whiskers improved texture discrimination. These results indicate that surface roughness is translated into distinct whisker vibration signals that result in neuronal discharges. However, due to the dynamic nature of this translation process, we propose that texture discrimination may require the integration of signals from multiple spatial and temporal sensory channels to disambiguate surface roughness.