Course information for SYDE 556/750, taught Fall 2026.
Instructor
Chris Eliasmith
Office: E7-6324
Email: celiasmith@uwaterloo.ca
Website:
http://compneuro.uwaterloo.ca
Teaching Assistant
Graeme Damberger
Office: EC4-2011
Email: graeme.damberger@uwaterloo.ca
Course times and location
Tuesday: 12:00-1:50 in E5-2004 (SYDE 556/750)
Thursday: 12:00-12:50 in E5-2004 (SYDE 556/750)
Thursday: 1:00-1:50 in E5-2004 (SYDE 750 optional 556)
Office hours
Please make an appointment by email.
The course syllabus is here.
All lecture notes and assignments are available on github. The lecture notes will be posted there before each class. While everything is available earlier on github, all material is subject to change until it is explicitly linked from the github README.
Grading will be based on writing six tests, keeping the top 5 scores. This comprises 100% of the grade for 556, and 80% for 750. For 750, the remaining 20% is determined by the final project. Late projects lose 1 mark per day and may be at most seven days late. Practice notebooks are provided on which the tests will be based. You are expected to do these notebooks individually to prepare for the tests.
The final project for the course consists of picking a neurobiological system and building a model for it. Projects are mandatory for 750. There is a list of possible projects, expectations for the project and more info at this link, but is not intended to be comprehensive, so feel free to come up with your own ideas. Please have your projects approved by Oct 29th. To do so, you will need to submit a short summary of your project earlier. Have a look at this document for more information
It is suggested that the project report is in the format discussed in chapter 1 of the book (see pp. 19-23; i.e., System Description, Design Specification, Implementation), see the project page for details.
The final document should be between, at least ten, and (at the very most) twenty content pages at 12pt, 1.25 line spacing. Have a look at the following project template for more information.
Students are expected to provide a short, 5-10 min project presentation near the end of term. Marks are not assigned for the presentation, although a skipped or very poor presentation will result in the loss of up to 4 marks on the project report. The schedule will be set later in the term. Contents can follow the recommendations in the project summary document.
Two lectures per week and practice notebooks consisting of computer exercises using Python. For SYDE 750 a larger class project is required, usually a computer simulation developed based on significant neuroscientific research and/or collaboration with a neurophysiologist. This course examines a general framework for modeling computation by neurobiological systems with an emphasis on quantitative formulations. Particular emphasis will be placed on understanding computation, representation, and dynamics in such systems. Students will learn how the fundamentals of signal processing, control theory and statistical inference, can be applied to modeling sensory, motor, and cognitive systems.
Knowing how to program with matrices using Python is highly recommended. Familiarity with Fourier Transforms and other signal processing concepts is recommended. Familiarity with calculus and linear algebra is required.
Programming
Computational Neuroscience
Neuroscience