Neural Computation

The neural computation research realm highlights the fundamental questions of the origins and optimization of emergent behavior in the neural system. Specifically, neural computation researchers address how the brain computes and learns, how to modulate and reverse engineer brain computation and brain function, and how to computationally model and measure physical and physiological phenomena.

Research examples:

• Modeling the neural basis and development of circuits that produce songbird song (Dezhe Jin)
• Network models for seizure and spreading depolarization propagation (Bruce Gluckman)
• Algebraic, topological, and geometric approaches to understanding neural coding and networks (Carina Curto and Vladimir Itskov)
• Continuum fluid-structure mechanics modeling underlying fluid flow in the extracellular space (Francesco Costanzo)
• Fluid, ion, and/or solid modeling to understand the hydrocephalous (Corina Drapaca)
• Model-predictions of concussion-related brain damage in sports from mouth-worn accelerometers (Reuban Kraft)
• Reverse engineering vision coordination with flight motor control in flies (Jean-Michel Mongeau)