COGST 3300

Introduction to Computational Neuroscience

Course Description

Course information provided by the 2026-2027 Catalog.

Covers the basic ideas and techniques involved in computational neuroscience. Surveys diverse topics, including neural dynamics of small networks of cells, neural coding, learning in neural networks and in brain structures, memory models of the hippocampus, sensory coding, and others.

Prerequisites BIONB 2220 or permission of instructor.

Distribution Requirements (OPHLS-AG), (BIO-AS, SDS-AS)

Last 4 Terms Offered 2024FA, 2022FA, 2018FA, 2016FA

Learning Outcomes

• Upon completion of this course you will be able to create models of neural circuits to complete simple tasks such as learning to be fearful of an object.
• Upon completion of this course you be able to synthesize information from complex computational neuroscience publications.
• Upon completion of this course you will be able to use linear algebra and differential equations to describe neural brain function.
• Upon completion of this course you will be able to create links between neural computation and human brain function.

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