Predictive Uncertainty in State-Estimation Drives Active Sensing

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Abstract
Animals use active sensing movements to shape the spatiotemporal characteristics of sensory signals to better perceive their environment under varying conditions. However, the underlying mechanisms governing the generation of active sensing movements are not known. To address this, we investigated the role of active sensing movements in the refuge tracking behavior of Eigenmannia virescens , a species of weakly electric fish. These fish track the longitudinal movements of a refuge in which they hide by swimming back and forth in a single linear dimension. During refuge tracking, Eigenmannia exhibits stereotyped whole-body oscillations when the quality of the sensory signals degrades. We developed a feedback control model to examine the role of these ancillary movements on the task performance. Here, we show that the proposed model generates fish trajectories that are statistically indistinguishable from the actual fish, implying that active sensing movements are regulated to minimize the predictive uncertainty in state estimation.
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