Introduction to Computational Neuroscience Winter 2007
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Instructor: William L. Kath

Contact Information:, x1-8784, Tech M460

Class times: Tuesday, 9:30-10:50 Tech LR4; Thursday, 9:30-10:50 Tech M152

Textbook: There is no actual required textbook, but for some of the material we will be following
Theoretical Neuroscience by Peter Dayan and Larry Abbott. Members of the Northwestern community
can access the book on-line at no cost through the MIT Cognet Library. Note this version of the book
consists of pdf files that can be viewed on-screen, but which cannot be printed or searched.  We will
be starting with material of Chapter 5, somewhat out of order with respect to the book.

Lecture Materials (only accessible from inside the Northwestern network)

Information about course projects (only accessible from inside the Northwestern network)

Course Description: The course will cover the basic computational models of neurons - their passive properties, models of ionic conductances, and the effect of a cell's morphology. Next, models of synapses (excitatory and inhibitory) will be considered, and we will discuss simplified models of neurons, e.g., integrate-and-fire models. We will then consider the behavior of networks of neurons, and how these can be approximated with firing rate models. As time permits, we will discuss spike train statistics and information theory. We will conclude with the topic of computational models of plasticity and learning.

Throughout the course, computer demonstrations will be used to explore each concept. These demonstrations will be done using the NEURON simulation package (, or with Matlab; participants will have the opportunity to learn to use these packages. Grades will be based upon completion of a project during the quarter; topics for the projects will be made available in the first few weeks of the course.