VS298: Neural Computation

People

Email: baolshausen AT berkeley DOT edu
Office: 570 Evans
Office hours: TBD

GSI: Amir Khosrowshahi

Email: amirk AT berkeley DOT edu
Office: 567 Evans
Office hours: TBD

Course description

This is a 3-unit course that provides an introduction to the theory of neural computation. The goal is to familiarize students with the major theoretical frameworks and models used in neuroscience and psychology, and to provide hands-on experience in using these models.

This course differs from MCB 262, Advanced Topics in Systems Neuroscience, in that it emphasizes the theoretical underpinnings of models - i.e., their mathematical and computational properties - rather than their application to the analysis of neuroscientific data. It will be offered in alternate years, interleaving with MCB 262. Students interested in computational neuroscience are encouraged to take both of these courses as they complement each other.

Lectures

Location: Evans 508-20
Times: TBD
Telebears: {CCN, Section, Units, Grade Option} == {TBD, 02 LEC, 3, Letter Grade}

Email list and forum

Please subscribe to the class email list here. The list name is vs298-students.
A bulletin board is provided here for discussion regarding lecture material, readings, and problem sets. Signup required for posting.

Grading

Based on weekly homework assignments (60%) and a final project (40%).

Required background

Prerequisites are calculus, ordinary differential equations, basic probability and statistics, and linear algebra. Familiarity with programming in a high level language, ideally Matlab, is also required.

Textbooks

[HKP] Hertz, J. and Krogh, A. and Palmer, R.G. Introduction to the theory of neural computation. Amazon
[DJCM] MacKay, D.J.C. Information Theory, Inference and Learning Algorithms. Available online or Amazon
[DA] Dayan, P. and Abbott, L.F. Theoretical neuroscience: computational and mathematical modeling of neural systems. Amazon

HKP and DA are available as paperback. Some copies of HKP and DJCM are available at the Berkeley bookstore. Additional reading, such as primary source material, will be suggested on a lecture by lecture basis.

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