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| 02/03 - 05/22 | ||||||
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1:40 pm |
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Subject: Neuroscience (NSCI)
CRN: 22743
Lab
St Paul: O'Shaughnessy Science Hall 333
The brain is a complex, dynamical system consisting of billions of neurons. Computational models are essential for understanding how brain functions arise through neuronal interactions. This course covers current computational approaches of studying neural codes, network dynamics, and learning. In the process, we will learn how to characterize the coding and decoding in nervous systems, how the visual and auditory systems work, how to model individual neurons and network of dynamics, how neural integrators function, and how learning occurs through synaptic plasticity, self-organization, and reinforcement learning. The goal is to understand how cognitive growth and human-level cognition emerge from interactions of neuronal networks. Prerequisite: C- or better in NSCI 301 or permission of the instructor.
0 Credits