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MDSC628

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Introduction to Computational Neuroscience

Graduate Science Education (O) MD - 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.

Also known as (formerly Medical Science 755.10)

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

Course Attributes

Fee Rate Group(Domestic) - A, Fee Rate Group(International) -B, GFC Hours (3-0)

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

3

Repeat for Credit

No

Subject code

MDSC

Understanding Course Information

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