NROSCI 1046 - INTRODUCTION TO COMPUTATIONAL NEUROSCIENCE

Minimum Credits: 3
Maximum Credits: 3
Computational neuroscience applies theoretical and numerical techniques to understand brain functions and neural coding. In this course, students will learn how to simulate and analyze model neurons and networks of neurons, and how simple neuronal networks perform computations. Students will also learn how to analyze spike train data and decode information from neural responses. We will have hands-on MATLAB practice sessions throughout the course. By the end of the course, students will be familiar with the mathematical formulations to study neural coding and network dynamics, and acquire programming skills in MATLAB. Knowledge of linear algebra, probability and differential equations is recommended, but not required.
Academic Career: Undergraduate
Course Component: Lecture
Grade Component: Letter Grade
Course Requirements: PREQ: NROSCI 1000 (MIN GRADE: 'B-') or 1003 (MIN GRADE: 'B-'); PLAN: Neuroscience (BS or MN)
Course Attributes: Capstone Course

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