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Predictive Computational Modeling of Neuronal Networks


Neuronal networks are capable to fuse sensory information into activity, which encodes particular behaviors. Some of these behaviors are unique and robust, e.g., locomotion or directional flight. We thereby study how neural circuits that facilitate sensory are designed by modeling their networks and investigate 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 butterfly.


Research Areas