MDSC628

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Introduction to Computational Neuroscience

Graduate Science Educ OfficeMD - Cumming School of Medicine

Subject

MDSC - Medical Science

Description

Introduces the mathematical foundations of computational neuroscience. This includes how to model and simulate neurons (Hodgkin-Huxley or conductance-based neurons, integrate-and-fire neurons, fitting neurons to data), how to connect neurons into networks (spiking neural networks, artificial neural networks, recurrent neural networks), analytical and computational simplifications to these networks (mean-field modelling), and includes a brief introduction to techniques machine learning. This course is intended for students with a quantitative background, with a particular emphasis on dynamical systems theory, ordinary differential equations, and linear algebra.

Prerequisite(s): Mathematics 213, 313, 367 and 375 or equivalent.

Also known as (formerly Medical Science 755.10)

GFC Hours

(3-0)

Domestic Fee Rate Group

International Fee Rate Group

Signature Learning

Research & Creative Scholarship

Instructional Components

Courses may consist of a Lecture, Lab, Tutorial, and/or Seminar. Students will be required to register in each component that is required for the course as indicated in the schedule of classes. Practicums, internships or other experiential learning modalities are typically indicated as a Lab component.

Component

LEC

Units