Introduction to Computational Neuroscience (MECH 550)

This 3-credit course provides an introduction to selected topics in Computational Neuroscience, a discipline in which the tools of mathematics and computing are applied to understanding the mechanisms of perception, memory, behaviour and consciousness. Topics that may be covered include:

  1. What is computation and is the brain a computer?
  2. Biophysics of individual nerve cell function
  3. Overview of the brain and cerebral cortex anatomy
  4. Models of learning and modifiable synapses
  5. Modelling simple networks of biologically realistic neurons
  6. Review of different classes of artificial neural network, including Hopfield nets, back-propagation nets, Willshaw associative nets, Kohonen self-organising nets, and their application to neurobiological problems
  7. Models of information processing in the visual system
  8. Neurobiologically inspired theories of consciousness

The class is structured in a student-presentation based seminar format. It's recommended that students have a background in at least one, and preferably more, of the following areas: computer science, mathematics, physics, engineering, psychology and neuroscience.

Grading is based on:

  1. Presentations during the course
  2. Presentation of a project at the end of the term
  3. A written examination


For further information, contact:


Nicholas Swindale, Professor

Dept. of Ophthalmology and Visual Sciences

E-mail: (@mail.ubc.ca) swindale

Tel: 604-875-5379

SwindaleLab: MECH550 (last edited 2013-12-20 16:34:08 by MartinSpacek)