In all sensory modalities, the data acquired by the nervous system is shaped by the biomechanics, material properties, and the morphology of the peripheral sensory organs. The rat vibrissal (whisker) system is one of the premier models in neuroscience to study the relationship between physical embodiment of the sensor array and the neural circuits underlying perception. To date, however, the three-dimensional morphology of the vibrissal array has not been characterized. Quantifying array morphology is important because it directly constrains the mechanosensory inputs that will be generated during behavior. These inputs in turn shape all subsequent neural processing in the vibrissal-trigeminal system, from the trigeminal ganglion to primary somatosensory (“barrel”) cortex. Here we develop a set of equations for the morphology of the vibrissal array that accurately describes the location of every point on every whisker to within ±5% of the whisker length. Given only a whisker's identity (row and column location within the array), the equations establish the whisker's two-dimensional (2D) shape as well as three-dimensional (3D) position and orientation. The equations were developed via parameterization of 2D and 3D scans of six rat vibrissal arrays, and the parameters were specifically chosen to be consistent with those commonly measured in behavioral studies. The final morphological model was used to simulate the contact patterns that would be generated as a rat uses its whiskers to tactually explore objects with varying curvatures. The simulations demonstrate that altering the morphology of the array changes the relationship between the sensory signals acquired and the curvature of the object. The morphology of the vibrissal array thus directly constrains the nature of the neural computations that can be associated with extraction of a particular object feature. These results illustrate the key role that the physical embodiment of the sensor array plays in the sensing process.

Rats actively tap and sweep their large mystacial vibrissae (whiskers) against objects to tactually explore their surroundings. When a vibrissa makes contact with an object, it bends, and this bending generates forces and bending moments at the vibrissa base. Researchers have only recently begun to quantify these mechanical variables. The present study quantifies the forces and bending moments at the vibrissa base with a quasi-static model of vibrissa deflection. The model was validated with experiments on real vibrissae. Initial simulations demonstrated that almost all vibrissa-object collisions during natural behavior will occur with the concave side of the vibrissa facing the object, and we therefore paid particular attention to the role of the vibrissa's intrinsic curvature in shaping the forces at the base. Both simulations and experiments showed that vibrissae with larger intrinsic curvatures will generate larger axial forces. Simulations also demonstrated that the range of forces and moments at the vibrissal base vary over approximately three orders of magnitude, depending on the location along the vibrissa at which object contact is made. Both simulations and experiments demonstrated that collisions in which the concave side of the vibrissa faces the object generate longer-duration contacts and larger net forces than collisions with the convex side. These results suggest that the orientation of the vibrissa's intrinsic curvature on the mystacial pad may increase forces during object contact and provide increased sensitivity to detailed surface features.

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During exploratory behavior, rats brush and tap their whiskers against objects, and the mechanical signals so generated constitute the primary sensory variables upon which these animals base their vibrissotactile perception of the world. To date, however, we lack a general dynamic model of the vibrissa that includes the effects of inertia, damping, and collisions. We simulated vibrissal dynamics to compute the time-varying forces and bending moment at the vibrissa base during both noncontact (free-air) whisking and whisking against an object (collision). Results show the following: (1) during noncontact whisking, mechanical signals contain components at both the whisking frequency and also twice the whisking frequency (the latter could code whisking speed); (2) when rats whisk rhythmically against an object, the intrinsic dynamics of the vibrissa can be as large as many of the mechanical effects of the collision, however, the axial force could still generate responses that reliably indicate collision based on thresholding; and (3) whisking velocity will have only a small effect on the transient response generated during a whisker-object collision. Instead, the transient response will depend in large part on how the rat chooses to decelerate its vibrissae after the collision. The model allows experimentalists to estimate error bounds on quasi-static descriptions of vibrissal shape, and its predictions can be used to bound realistic expectations from neurons that code vibrissal sensing. We discuss the implications of these results under the assumption that primary sensory neurons of the trigeminal ganglion are sensitive to various combinations of mechanical signals.

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