Behavioral and Neural Circuit Algorithms for Rapid Learning in Spatial Navigation

Department of Computational Biology

Featuring Dr. Ann Hermundstad, Group Leader, Janelia Research Campus
 

Animals can learn to modify their behavior from limited experience in a new setting. This rapid flexibility is enabled in part by neural circuit architectures that capture existing knowledge about predictable structure in an animal’s surroundings, and in its relationship to those surroundings. Using navigational learning tasks for mice and flies, I will show how we can use behavioral data to constrain compact generative models of action selection and rapid learning. In flies, we can map this model onto genetically-specified circuit architectures that combine multiple evolving internal representations to guide behavior. Finally, I will highlight how behavioral and circuit level constraints can shed light on rapid learning and behavioral flexibility in biological and artificial agents more broadly.

Seminar Host: Dr. Andrew Hein