PHYS366
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Computational Modeling of Neural Systems
Course Subject Code
PHYS
Course Number
366
Status
Active
Course Short Title
Computational Mod of Neu Syst
Course Long Title
Computational Modeling of Neural Systems
Course Description
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.
Min
4
Repeatable
-
Course Attributes
BINT: GenEd-Breadth/Interdisciplinar, CEA: ProgCLA-CEA and Au Pair, EMMT: Major-Mathematics Elective, EMPY: Major-Physics BA Elective, MMAT: Major-Mathematics, MPHY: Major-Physics BA, ENDA: Minor-Data Science Elective, ENMH: Minor-Mathematics Elective, NDAT: Minor-Data Science, NMAT: Minor-Mathematics
Equivalent Course(s)
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