Jan 15, 2025  
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PHYS 366 - Computational Modeling of Neural Systems

4 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. Same as NEUR 366 . Prerequisite or corequisite: PHYS 160 , MATH 151 . CLA-Breadth/Interdisciplinary


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