Skip to main content

NEUR366

Computational Modeling of Neural Systems

Neuroscience College of Liberal Arts

Course Subject Code

NEUR

Course Number

366

Status

Active

Course Attributes

BINT: GenEd-Breadth/Interdisciplinar, EMNE: Major-Neuroscience Elective, MNEU: Major-Neuroscience, ENDA: Minor-Data Science Elective, NDAT: Minor-Data Science

Course Short Title

Comp. Modeling of Neural Sys

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. May 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. Students 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

-

Equivalent Course(s)

-