DE Seminar: Kathleen Hoffman (UMBC)

knifefish Eigenmannia virescens incorporates an electric field as one of its active sensing mechanisms. The motion of the knifefish in a stationary refuge is captured using high-resolution motion tracking. We observe small amplitude axial movements inside the refuge interspersed with fewer high amplitude ``jumps''.

We show that the probability distribution of the fish velocities is far from normal. The velocity distributions are fit much better by Gaussian mixture models whose tails reflect the frequency of high amplitude jumps. Time series position measurements taken in the dark showing more frequent bursts of high amplitude movement than those in the light, presumably because the fish must rely only on their electric sensor for sensory input. Computational models of active state and parameter estimation with noise injected into the system based on threshold triggers exhibit velocity distributions that resemble those of the experimental data, more so than with pure noise or zero  noise inputs. Our analysis of time series from several other motor control systems in different species and different sensory systems finds that non-normal velocity distributions are ubiquitous.