CSCI 6508 Neurocomputing

Fundamentals in Computational Neuroscience

News: Nov. 18: SOM code

Nov. 12: Assignment 3

Oct 23: Follow the AI'2004 paper format for your project paper.

Oct 9 Assignment 2 (Also, I try to update the schedule a bit. However, we are quite flexible with this schedule. We will concentrate on some concrete network architectures and algorithms in the next little while.)

Oct 7 Project topics

Sep 16 Assignment1

Sep 11 Here is a test pattern. What is this letter?

Sep.9 Tutorial1: MATLAB and simple pattern recognition (Teaching lab 2 in CS building, 2:30pm)


Human cognitive abilities have long guided the development of computer systems. This course introduces the principles of information-processing in the brain, including the functionality of single neurons, networks of neurons, and large-scale neural architectures for specific cognitive functions. We discuss the information representation in the brain (distributed versus localist), information theoretical studies of spiking neurons, synaptic plasticity and adaptive architectures, and various forms of memory. We will also study some specific mental abilities and some research topics (time permitted) such as vision, motor control, navigation, sleep, and consciousness. These issues will be contrasted with approaches that are discussed in the machine learning literature. The course includes a MATLAB tutorial, and the students are encouraged to explore some of the functionalities of basic neural networks.

Instructor: Dr. Thomas Trappenberg  
Office Hours: Tuesdays/Thursdays 1-2pm  

Thomas P. Trappenberg

Fundamental of Computational Neuroscience

Oxford University Press, ISBN 0-19-851583-9

Programs of the book

Grading Scheme:

Assignments 20%

Tests 20%

Project 60%

Schedule: Rough schedule (can change)  

It is important for students to be aware of the Intellectual Honesty regulations at Dalhousie University. Please see for more information. Any suspected cases of plagiarism will be forwarded to the Senate Discipline Committee.