CIS 6930/4930, Introduction to Computational Neuroscience, Fall 2008

Instructor:
Prof. Arunava Banerjee
Office: CSE E336.
E-mail: arunava@cise.ufl.edu.
Phone: 392-1476.
Office hours: Wednesday 2:00 p.m.-4:00 p.m. or by appointment.

Pre-requisites:

• There are no official pre-requisites for this course. However, knowledge of calculus and linear algebra is necessary since we shall be touching on areas such as measure theory, ergodic theory etc. In addition, since there will be several assignments dealing with simulations of neural systems, proficiency in some programming language is a must.

Textbook: Theoretical Neuroscience, Dayan and Abbott, MIT Press, ISBN 0-262-04199-5.
Neuroscience Reference: Fundamental Neuroscieence, Zigmond, Bloom, Landis, Roberts, and Squire, Academic Press, ISBN 0-12-780870-1.

The goal of Computational Neuroscience is to acquire a formal understanding of how the brain (or any part thereof) works. The central dogma is that there are computational principles lurking in the dynamics of systems of neurons in the brain that we can harness to create better machines for such disparate tasks as computer vision, audition, language processing etc (note that in all these cases human beings far surpass the best known solutions).

This course is aimed at giving an overview of the field. In addition to particular issues, we shall take a tour through some essential neurobiology and a couple of mathematical areas. The targeted audience is students who wish to conduct research in this field, although any body interested in acquainting themselves with the area is welcome to attend. Although there will be a text that we shall (loosely) follow (Theoretical Neuroscience by Dayan & Abbott; available as an e-book thru the UF library system), a large portion of the course will involve material from disparate sources (other books, articles etc.)

Please return to this page at least once a week to check updates in the table below

Evaluation: There will be no exams in this course. The final grade will be based on a series of written assignments, and programming projects.

Course Policies:

• Late assignments: All homework assignments are due before class.
• Plagiarism: You are expected to submit your own solutions to the assignments. While the final project and presentation will be done in groups, each member will be required to demonstrate his/her contribution to the work.
• Attendance: Their is no official attendance requirement. If you find better use of the time spent sitting thru lectures, please feel free to devote such to any occupation of your liking. However, keep in mind that it is your responsibility to stay abreast of the material presented in class.
• Cell Phones: Absolutely no phone calls during class. Please turn off the ringer on your cell phone before coming to class.

Academic Dishonesty: See http://www.dso.ufl.edu/judicial/honestybrochure.htm for Academic Honesty Guidelines. All academic dishonesty cases will be handled through the University of Florida Honor Court procedures as documented by the office of Student Services, P202 Peabody Hall. You may contact them at 392-1261 for a "Student Judicial Process: Guide for Students" pamphlet.

Students with Disabilities: Students requesting classroom accommodation must first register with the Dean of Students Office. The Dean of Students Office will provide documentation to the student who must then provide this documentation to the Instructor when requesting accommodation.

List of Topics covered

Week	Topic	Additional Reading	Assignment
Aug 24 - Aug 30	Change Blindness examples: Rensink's Website. Change Blindness examples O'Regan's Example-1. Change Blindness examples O'Regan's Example-2. Basic Neurobiology. Powerpoint Slides.
Aug 31 - Sep 06	Paper on "in vivo" recording. Paper on "slice" recording. Paper on "culture" recording. Paper on "fmri" recording. Neuro Electronics. Powerpoint slides can be found here.		Assignment 1. Due on Sep 16th. The tex file.
Sep 7 - Sep 13	Neuro Electronics continued.
Sep 14 - Sep 20	Reduced models of the neuron.	Which Model to Use for Cortical Spiking Neurons? By E. M. Izhikevich Link here. Alex found this hardware implementations of the above models. Link here Scholerpedia article on the FitzHugh-Nagumo Model: Link here.	Assignment 2. Due on Sep 30th.
Sep 21 - Sep 27	System Identification Volterra Weiner Series Stimulus Reconstruction Spike triggered averaging
Sep 28 - Oct 04	Point set topology Metric spaces	Read more about Brouwer's Fixed point theorem here
Oct 05 - Oct 11	Vector Spaces Banach and Hilbert Spaces Fourier Series
Oct 12 - Oct 18	Finished Fourier Series and Fourier Transform Started Information Theory
Oct 19 - Oct 25	Information theory continued		Assignment 3. Due on Oct 30th.
Oct 26 - Nov 01	Artificial Neural Networks perceptron (delta) learning rule Error backpropagation
Nov 02 - Nov 08	Hopfield Nets Dynamical Systems Theory		Assignment 4. Due on Nov 18th.
Nov 09 - Nov 15	Dynamical Systems Theory continued. Stability analysis
Nov 16 - Nov 22	Dynamical Systems Theory continued. Topological Conjugacy, Sensitive dependence, chaos etc.
Nov 23 - Nov 29	(Thanksgiving)
Nov 30 - Dec 06	The phase space dynamics of recurrent systems of spiking neurons Sensitivity analysis Stochastic processes.		Assignment 5. Due on Dec 11th.