PHY 461 - Computational Neuroscience (3)

This course provides an introduction to computational methods for understanding what nervous systems do and for determining how they function. Students explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory. Specific topics that will be covered include representation of information by spiking neurons, processing of information in neural networks, and algorithms for adaptation and learning. Students make use of Python demonstrations and exercises to gain a deeper understanding of concepts and methods introduced in the course. The course is primarily aimed at third- or fourth-year undergraduates interested in learning how the brain processes information.

Prerequisite(s): MAT 252, MAT 271, PHY 211, and PHY 212, or permission from department.
Grading Method: Letter Grade
Term Typically Offered: Spring