PHYS366

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Computational Modeling of Neural Systems

Physics College of Liberal Arts

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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