The sense of touch provides information about the texture of an object with much better resolution than the other senses. Primates perceive texture by actively moving their fingertips over an object and encoding the resulting spatiotemporal patterns of activation of mechanoreceptors in the skin. Within the primate fingertip many types of mechanoreceptors are densely packed in the skin making it difficult to study the individual components of these complex patterns. Rats' ability to discriminate texture using the whiskers is comparable to humans using the fingertips and due to its discrete array of whiskers on the facial pad the rat whisker system offers considerable advantages for studying texture coding. However, to date, very little is known about how behaving rats actively use their whiskers to extract texture information and how this information is encoded in the nervous system. Currently there are two main hypotheses on how rats perform texture discrimination using their whiskers. In one hypothesis, whisker motion across a texture is underdamped, and texture properties drive whisker resonance as the whisker moves across a surface. In this model, the systematic variation in resonance frequency across whiskers enables texture to be encoded by the differential amplitude of vibration across whiskers. In a second, alternative hypothesis, resonance is diminished due to damping and texture information is encoded in the precise motion of each whisker across the surface. Both of these hypotheses are supported by experiments performed in anesthetized animals, however to resolve this debate it is critical to examine whisker dynamics in awake animals to determine 1) to what extent whisker resonance shapes sensory input during active whisker use and 2) how whisker dynamics reflect texture properties when the whiskers are under active muscular control. Chapter 2 of this dissertation examines whisker vibrations measured in behaving animals trained to whisk in air. We show that, in the absence of any sensory stimulus, high frequency whisker vibrations are presents and that these are filtered by whisker resonance. This suggests that, in the awake behaving animal, resonance can play a role in shaping sensory responses in the whiskers. Chapter 3 shows that active palpation onto textures can induce whisker resonance. However we argue that the degree to which resonance occurs is not dependent on the spatial properties of the texture and therefore it is unlikely to be critical for texture encoding arguing against the resonance hypothesis. We present an alternative model for texture encoding based on the magnitude of stick-slip events that were found to occur during texture palpation. We also examine the role that muscles may play in causing these stick-slip events. Chapter 4 concludes by presenting preliminary results of the neural response to stick-slip events. We show that the spiking probability of a subset of neurons is greatly increased following a texture-induced slip and that the spiking probability increases with slip acceleration, as would be required for the texture encoding hypothesis presented in chapter 3

The rodent whisker system is a major model for understanding neural mechanisms for tactile sensation of surface texture (roughness). Rats discriminate surface texture using the whiskers, and several theories exist for how texture information is physically sensed by the long, moveable macrovibrissae and encoded in spiking of neurons in somatosensory cortex. However, evaluating these theories requires a psychometric curve for texture discrimination, which is lacking. Here we trained rats to discriminate rough vs. fine sandpapers and grooved vs. smooth surfaces. Rats intermixed trials at macrovibrissa contact distance (nose >2 mm from surface) with trials at shorter distance (nose <2 mm from surface). Macrovibrissae were required for distant contact trials, while microvibrissae and non-whisker tactile cues were used for short distance trials. A psychometric curve was measured for macrovibrissa-based sandpaper texture discrimination. Rats discriminated rough P150 from smoother P180, P280, and P400 sandpaper (100, 82, 52, and 35 µm mean grit size, respectively). Use of olfactory, visual, and auditory cues was ruled out. This is the highest reported resolution for rodent texture discrimination, and constrains models of neural coding of texture information.

Rats discriminate surface textures using their whiskers (vibrissae), but how whiskers extract texture information, and how this information is encoded by the brain, are not known. In the resonance model, whisker motion across different textures excites mechanical resonance in distinct subsets of whiskers, due to variation across whiskers in resonance frequency, which varies with whisker length. Texture information is therefore encoded by the spatial pattern of activated whiskers. In the competing kinetic signature model, different textures excite resonance equally across whiskers, and instead, texture is encoded by characteristic, nonuniform temporal patterns of whisker motion. We tested these models by measuring whisker motion in awake, behaving rats whisking in air and onto sandpaper surfaces. Resonant motion was prominent during whisking in air, with fundamental frequencies ranging from approximately 35 Hz for the long Delta whisker to approximately 110 Hz for the shorter D3 whisker. Resonant vibrations also occurred while whisking against textures, but the amplitude of resonance within single whiskers was independent of texture, contradicting the resonance model. Rather, whiskers resonated transiently during discrete, high-velocity, and high-acceleration slip-stick events, which occurred prominently during whisking on surfaces. The rate and magnitude of slip-stick events varied systematically with texture. These results suggest that texture is encoded not by differential resonant motion across whiskers, but by the magnitude and temporal pattern of slip-stick motion. These findings predict a temporal code for texture in neural spike trains.