Hartmann, M. J. Z. | bioRxiv Science

bioRxiv2020

Three-dimensional contact point determination and contour reconstruction during active whisking behavior of the awake rat

The rodent vibrissal (whisker) system has been studied for decades as a model of active touch sensing. There are no sensors along the length of a whisker; all sensing occurs at the whisker base. Therefore, a large open question in many neuroscience studies is how an animal could estimate the three-dimensional location at which a whisker makes contact with an object. In the present work we simulated the exact shape of a real rat whisker to demonstrate the existence of a unique mapping from triplets of mechanical signals at the whisker base to the three-dimensional whisker-object contact point. We then used high speed video to record whisker deflections as an awake rat whisked against a peg and used the mechanics resulting from those deflections to extract the contact points along the peg surface. A video shows the contour of the peg gradually emerging during active whisking behavior.

neuroscience↗

bioRxiv2019

Continuous, multidimensional coding of 3D complex tactile stimuli by primary sensory neurons of the vibrissal system

To reveal the full representational capabilities of sensory neurons, it is essential to observe their responses to complex stimuli. In the rodent vibrissal system, mechanical information at the whisker base drives responses of primary sensory neurons in the trigeminal ganglion (Vg). Studies of how Vg neurons encode stimulus properties are typically limited to 2D analyses and restricted stimulus sets. Here we record from Vg neurons during 3D stimulation while quantifying the complete 3D whisker shape and mechanics. Results show that individual Vg neurons simultaneously represent multiple mechanical features of the stimulus, do not preferentially encode principal components of the stimuli, and represent continuous and tiled variations of all available mechanical information. As a population, the neurons span a continuum of rapid and slow adaptation properties; a binary distinction between these adaptation classes is oversimplified. These results contrast with proposed codes in which Vg neurons segregate into functional classes.

neuroscience↗