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NROSCI 1046 - Introduction to Computational Neuroscience

Description
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.
Recent Professors
Recent Semesters
Fall 2024, Fall 2023, Fall 2020
Former Title
Topics in Neuroscience
Class Size
22-36
Credits
3
Professor Reviews
5y
First-year
NEURO
Dr. Dong truly has a passion for teaching and wants to makes sure everyone understands the material. This is a small class and it's taught like a graduate class. Most of the information comes from reviewing journal articles, similar to a journal club. Your entire grade is based on the final exam but most do very well. Highly recommend this class.
2y
First-year
NEURO
Professor Dong is a very funny, nice, and caring person - which in my mind is highly respectable. The entire glass was graded on a midterm and a final, which were both short-responses & open book. He would give you like 4 hours to complete it, which was plenty of time to do them. All questions were straight-forward, no tricks. Highly recommended.
Read all reviews
Usually Offered
TuTh (1 hour 15 minutes)
Attributes
HIP