General Information

  • Course title
    Simulating Neurobiological Systems (SYDE 556/750)

  • Course website
    Links to all course material, including lecture notes and slides can be found at the following URLs:

    Note: Any material on GitHub should be considered “preliminary” until officially linked at from the github README. Until then, the material is still subject to change.

  • Instructor
    Chris Eliasmith
    Office: E7-6324
    Email: celiasmith@uwaterloo.ca
    Website: http://compneuro.uwaterloo.ca

  • Course times and location

    • Wednesday: 11:00-11:50 in E5-6008 (SYDE 750, optional for 556)

    • Thursday: 4:00-5:20 in E5-6008 (SYDE 556/750)

    • Friday: 3:30-4:50 in E5-6008 (SYDE 556/750)

  • Office hours

    • By appointment
  • Readings

    • Main resource: “Neural Engineering: Representation, Computation and Dynamics in Neurobiological Systems”, Chris Eliasmith and Charles Anderson, 2003. MIT Press.

    • Optional: “How to Build a Brain”, Chris Eliasmith, 2012

  • Course Description
    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.

  • Prerequisites:
    Knowing how to program using numpy in Python is highly recommended. Familiarity with calculus and linear algebra is required.

Schedule

Date Reading Topic Assignments
WEEK 1
Sept 8 Chapter 1 Introduction
Sept 9 Chapter 2 Neurons
WEEK 2
Sept 15 Chapter 2 Population Representation (I) #1 posted
Sept 16 Chapter 2 Population Representation (II)
WEEK 3
Sept 22 Chapter 4 Temporal Representation (I)
Sept 23 Chapter 4 Temporal Representation (II)
WEEK 4
Sept 29 Chapters 5, 6 Feedforward Transformations (I) #2 posted
Sept 30 Chapters 5, 6 Feedforward Transformations (II) #1 due*
WEEK 5
Oct 6 Chapter 8 Nengo Tutorial
Oct 7 Chapter 8 Dynamics (I)
WEEK 6
― Reading week, no lectures ―
WEEK 7
Oct 20 Chapter 8 Dynamics (II) #3 posted
Oct 21 see notes Temporal Basis Functions #2 due*
Oct 21 Project proposal due
WEEK 8
Oct 27 Chapter 9 Learning (I)
Oct 28 Chapter 9 Learning (II)
WEEK 9
Nov 3 Chapter 9 Learning (III) #4 posted
Nov 4 Chapter 7 Analysing Representations #3 due*
WEEK 10
Nov 10 provided Symbols (I)
Nov 11 provided Symbols (II)
WEEK 11
Nov 17 provided SPA (I, Working Memory) #5 posted
Nov 18 provided SPA (II, Action Selection) #4 due*
WEEK 12
Nov 24 provided Biological Details
Nov 25 Conclusion
WEEK 13
Dec 1 Project Presentations
Dec 2 Project Presentations #5 due*
WEEK 15
Dec 18 Projects due*

* The project and all assignments are due at midnight (≈ 11:59p EST) of that day.

Grading

The course requires five assignments from all students (100% for 556, 80% for 750) and a final project (20%) from students taking 750. Assignments are due electronically by Midnight of the due date. Late assignments lose 1 mark per day and may be at most seven days late. Assignments are to be done individually (everyone writes their own code and answers questions themselves).

Learning Objectives

By the end of the course students should be able to:

  1. Demonstrate a basic understanding of neural processes, neural mechanisms, theories of neural communication and computation, and theories of neural dynamics. (KB: 1b, 1c, 1d)
  2. Converse at a fundamental level with neuroscientists, psychologists, and neural and cogitive modelers. (KB: 1b, I: 3b)
  3. Design and Analyze simple and complex neural circuits for performing small- and large-scale neural computations. (I: 3b, 3c)
  4. Apply engineering methods in signal processing, optimization, and control theory, among others, to characterizing and building neural circuits. (Kb: 1d, UET: 5c)
  5. Identify problems and solutions that may exploit the advantages of neural computation in an engineering context. (UET: 5a, 5c)

Abbreviations

KB - Knowledge base - 1b: Demonstrate understanding of concepts in natural science - 1c: Demonstrate understanding of engineering fundamentals - 1d: Demonstrate understanding of specialized engineering knowledge

I - Investigation - 3b: Gather information from relevant sources2 to address complex engineering problems - 3c: Synthesize information from multiple sources,such as modeling, simulation or experiments, to reach valid conclusions

UET - Use of Engineering Tools - 5a Select appropriate engineering tools, considering their limitations - 5c Use engineering tools appropriately

Policies

Academic Integrity

In order to maintain a culture of academic integrity, members of the University of Waterloo are expected to promote honesty, trust, fairness, respect and responsibility.

Discipline

A student is expected to know what constitutes academic integrity, to avoid committing academic offences, and to take responsibility for his/her actions. A student who is unsure whether an action constitutes an offence, or who needs help in learning how to avoid offences (e.g., plagiarism, cheating) or about "rules" for group work/collaboration should seek guidance from the course professor, academic advisor, or the Undergraduate Associate Dean. When misconduct has been found to have occurred, disciplinary penalties will be imposed under Policy 71 - Student Discipline. For information on categories of offenses and types of penalties, students should refer to Policy 71 - Student Discipline

Grievance

A student who believes that a decision affecting some aspect of his/her university life has been unfair or unreasonable may have grounds for initiating a grievance. Read Policy 70 - Student Petitions and Grievances, Section 4

Appeals

A student may appeal the finding and/or penalty in a decision made under Policy 70 - Student Petitions and Grievances (other than regarding a petition) or Policy 71 - Student Discipline if a ground for an appeal can be established. Read Policy 72 - Student Appeals

Academic Integrity Office (UW)

See http://uwaterloo.ca/academicintegrity/

Accommodation for Students with Disabilities

The Office for Persons with disabilities (OPD), located in Needles Hall, Room 1132, collaborates with all academic departments to arrange appropriate accommodations for students with disabilities without compromising the academic integrity of the curriculum. If you require academic accommodations to lessen the impact of your disability, please register with the OPD at the beginning of each academic term.

Intellectual Property

Students should be aware that this course contains the intellectual property of their instructor, TA, and/or the University of Waterloo. Intellectual property includes items such as:

  • Lecture content, spoken and written (and any audio/video recording thereof);
  • Lecture handouts, presentations, and other materials prepared for the course (e.g., PowerPoint slides);
  • Questions or solution sets from various types of assessments (e.g., assignments, quizzes, tests, final exams); and
  • Work protected by copyright (e.g., any work authored by the instructor or TA or used by the instructor or TA with permission of the copyright owner).

Course materials and the intellectual property contained therein, are used to enhance a student's educational experience. However, sharing this intellectual property without the intellectual property owner's permission is a violation of intellectual property rights. For this reason, it is necessary to ask the instructor, TA and/or the University of Waterloo for permission before uploading and sharing the intellectual property of others online (e.g., to an online repository).

Permission from an instructor, TA or the University is also necessary before sharing the intellectual property of others from completed courses with students taking the same/similar courses in subsequent terms/years. In many cases, instructors might be happy to allow distribution of certain materials. However, doing so without expressed permission is considered a violation of intellectual property rights.

Please alert the instructor if you become aware of intellectual property belonging to others (past or present) circulating, either through the student body or online. The intellectual property rights owner deserves to know (and may have already given their consent).