Dr. Mitra Hartmann received a Bachelor of Science in Applied and Engineering Physics from Cornell University, and a PhD in Integrative Neuroscience from the California Institute of Technology. She was a postdoctoral scholar at the Jet Propulsion Laboratory in Pasadena, California in the Bio-Inspired Technology and Systems group, and joined the faculty at Northwestern University in 2003. Dr. Hartmann is the recipient of the NSF CAREER award, a fellow of the AIMBE, an alumna of the Defense Science Study Group, and has received numerous teaching awards. She is presently a Professor at Northwestern with a 50-50 joint appointment between the departments of Biomedical Engineering and Mechanical Engineering.
Rats are expert at navigating the world in the dark using their sense of touch. They rhythmically brush and tap about 60 large vibrissae (whiskers) against objects to determine size, shape, orientation, and texture. At the same time, whiskers also help the animal sense the direction of airflow, likely helping to localize odor sources. A whisker has no sensors along its length; instead, all mechanosensory information is transmitted to sensors located within a follicle at its base. Now imagine that we could quantify the head movements of the rat, as well as the mechanical signals at the base of every whisker as the rat explores its world through touch and airflow. We would then have access to all of the primary mechanical information that the nervous system requires in order for the animal to perceive its environment through vibrissal-touch. In this talk, I will describe how our lab combines mechanical simulations and experiments, hardware models, behavioral studies, and neurophysiology to study the sense of touch in the rat vibrissal system. We aim to integrate realistic simulations of vibrissal dynamics with behaviorally-measured head and vibrissal kinematics to model the rat's tactile sampling strategies for different objects and airflow. Our goal is to quantify the mechanics at each vibrissa base for a given exploratory sequence and the associated responses of primary sensory neurons in the brain. Ultimately, these data can then be used to constrain computations at more central levels of the nervous system.