Huanying Yeh

Abstract To execute sensory-guided behavior, the nervous system must manage uncertainty within multiple streams of information. There are two highly nonlinear mechanisms for achieving this: 1) sensory reweighting, an internal neural computation which places more emphasis on sensory information that exhibits the least uncertainty, e.g. in a Bayesian framework, and 2) active sensing, an overt behavior that seeks to improve the quality of sensory information before it enters the nervous system.

Abstract Animals integrate multiple sensory inputs to explore environments and execute locomotor behaviors. To carry out these behaviors, the nervous system internally reweights controller gains, putting more emphasis on those with the least uncertainty, e.g. in a Bayesian framework. Meanwhile, as sensory uncertainty increases, animals produce more vigorous active sensing movements.