Coding properties of Vibrissal-Responsive Trigeminal Ganglion Neurons

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 DESCRIPTION (provided by applicant): We see because retinal ganglion cells respond to light. We hear because spiral ganglion cells respond to sound. We feel because primary somatosensory neurons respond to "touch." But what is "touch?" Whereas light and sound can be characterized by physical parameters (amplitude, frequency, phase, and polarization), the mechanics of touch, and the manner in which primary sensory neurons encode the parameters of touch, are largely unquantified. This is a glaring gap within the entire field of somatosensation, and it occurs because mechanics are difficult to quantify. To close this gap we will use the rat vibrissal (whisker) system as a model to directly relate the responses of primary sensory neurons to the quantified mechanics of touch. Paralleling the increased use of rodents in genetic and optogenetic research, the rodent vibrissal array has become an increasingly important model for the study of touch and sensorimotor integration. In the past few years, our laboratory has made rapid progress in characterizing vibrissal mechanics, and we are now uniquely positioned to determine how 3D whisker deflections and vibrations are represented in the firing patterns of primary sensory neurons of the trigeminal ganglion (Vg) during natural whisking behavior. The central goal of our investigation is to predict the responses of Vg neurons during both contact and non-contact whisking by appropriately combining 3D dynamic and quasistatic models of mechanical signals. Our three aims move from the outside of the rat inwards, from whisker, to follicle, to Vg neurons. In Aim 1, we will develop models of mechanical coding by the whisker, quantifying the 3D mechanical signals at the vibrissal base during both contact and non-contact whisking. In Aim 2, these models will be used to predict responses of mechanoreceptors within the follicle and thus to identify classes of Vg neurons based on the mechanical transformation they perform. Finally, in Aim 3 we will quantify the responses of Vg neurons during natural whisking behavior in awake animals. Exploiting the cell classes identified in Aim 2, and consistent with the modeling of Aim1, we will test the hypothesis that Vg responses are more linearly correlated with mechanical signals during whisking than they are with the geometry and kinematics of whisking behavior. The proposed work will be the first to record from Vg neurons in awake behaving animals while fully characterizing the mechanical input during both contact and non-contact whisking. We aim to solve a large portion of the "coding problem" for the vibrissal-trigeminal system. Solving this problem will provide a better understanding of what a Vg spike "means" for more central stages of the trigeminal system, including sensory thalamus and barrel cortex.