PI: Noah J. Cowan, Dept. of Mechanical Engineering, Johns Hopkins University Co-PI: Eric S. Fortune, Dept. of Psychological and Brain Sciences, Johns Hopkins University Intellectual Merit- A tightly integrated and multidisciplinary approach using a uniquely suited model system will help answer a fundamental question in sensorimotor integration: how is information processed by the nervous system to control locomotion? In the model system, weakly electric fish robustly and naturally swim back and forth to stabilize visual and/or electrosensory images, just as humans smoothly track moving objects with their eyes to stabilize visual images. This collaborative work builds on the strengths of the PI, a modeler of sensorimotor locomotion systems and the Co-PI, an organismal sensory neurobiologist. The approach incorporates mathematical modeling, behavioral experiments, and neurophysiological analyses. A mathematical model of the tracking behavior makes specific, testable predictions of both behavior and neural processing. The model's predictions of behavior will be tested by systematically varying visual and electrosensory information available to the fish for tracking a moving sensory image. The model's predictions will also be tested using central nervous system recordings in awake, behaving animals. The stimuli will include signals identical to those used for behavioral experiments, whose input-output relations are predictable from the model. Broader Impacts Undergraduate and graduate trainees will receive multidisciplinary training in neuroscience, experimental design, data collection and analysis, and computational modeling. Further, we will co-teach a new undergraduate course in sensor-based animal locomotion, and a companion graduate seminar. Finally, the study of sensorimotor animal behaviors has great potential to inspire novel strategies for autonomous control in artificial systems.
