BMES 5733 Computational Neuroscience and Neuroengineering 3.0 Credits
This course introduces computational neuroscience and neuroengineering foundations. Students study neural dynamics and information processing, linking electrophysiology to how neurons encode, transform, and transmit signals. Students build models of neurons and circuits, from rate-based descriptions to spiking neuron models, and scale up to recurrent neural networks for perception, decision-making, and control. Students will explore numerical simulation of neurons and neural networks, parameter fitting, and interpreting model behavior. The course then connects models to neurotechnology: recording and stimulation methods, signal processing, and closed-loop systems that can monitor and alter brain activity. Applications and limitations in research and translation are discussed.
Repeat Status: Not repeatable for credit