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Apr 16, 2024
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NEUR 366 - Computational Modeling of Neural Systems4 credits
Computational neuroscience is the study of the brain as a computational and information-processing organ. It is a highly interdisciplinary field that employs various ideas and techniques from physics, biology, chemistry, mathematics, computer science, psychology, and (of course) neuroscience. In this course, we cover the following topics: biophysics of a single neuron; dynamics of neural networks; models of associative memory and object recognition; and numerical methods and tools for analyzing and simulating a dynamical system. We study the fundamental biophysical properties and processes of the neurons and their networks, while also learning to use several analytical and numerical methods for studying a complex dynamical system. The goal of the course is to develop an interdisciplinary approach for analyzing a biological system. Prerequisite: PHYS 150 , MATH 150 . Corequisite: PHYS 160 , MATH 151 . Same as: PHYS 366. CLA-Breadth/Interdisciplinary
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