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University of Washington

Predictive Computational Modeling of Neuronal Networks

Neuronal networks are capable of fusing sensory information into activity, which encodes particular behaviors. Some of these behaviors are unique and robust, e.g., locomotion or directional flight. We are studying the design of neural circuits that facilitate sensory responses by modeling their networks and investigating the building blocks, robustness, optimality and controllability of these systems. Example project: We have developed a neuronal model that integrates solar azimuthal position and signals that encode time of day and facilitates directional flight in migrating monarch butterflies.

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