Spring 2004 schedule: Tuesday and Thursday 11 -
12:30 in E51-085

Mathematical introduction to neural coding and dynamics.
Convolution, correlation, linear systems, game theory, signal
detection
theory, probability theory, information theory, and reinforcement
learning. Applications to
neural coding, focusing on the visual system. Hodgkin-Huxley and
related models of neural excitability, stochastic models of ion
channels, cable theory, and models of synaptic transmission.

Prof. Sebastian Seung,
seung@mit.edu

Office hours: TBA, E25-429

T.A.s Jennifer Wang (jenwang@mit.edu) and Justin Werfel
(jkwerfel@mit.edu)

Office hours: Tuesday, 4pm-5pm E25-425 (Jen) or
by appointment

Optional lectures will be Mondays 7-8 PM in selected weeks, held in
E25-401.

No optional lecture this week (3/8)

### Final projects

### Resources

### Philosophy

The central assumption of computational neuroscience is that the
brain computes. What does that mean? Generally speaking, a computer is
a dynamical system whose state variables encode information about the
external world. In short, computation equals coding plus dynamics. Some
neuroscientists study the way that information is encoded in neural
activity and other dynamical variables of the brain. Others try to
characterize how these dynamical variables evolve with time. The study
of neural dynamics can be further subdivided into two separate strands.
One tradition, exemplified by the work of Hodgkin and Huxley, focuses
on the biophysics of single neurons. The other focuses on the dynamics
of networks, concerning itself with phenomena that emerge from the
interactions between neurons. Therefore computational neuroscience can
be divided into three subspecialties: neural coding, biophysics of
neurons, and neural networks.

### Prerequisites

- basic biology, chemistry, and physics
- differential equations or permission of instructor. Linear
algebra is also desirable.
- knowledge of MATLAB or willingness to learn. For more information
see this MIT website

### Course requirements

- weekly problem sets
- midterm project
- final project

### Textbook

- Peter Dayan and Larry Abbott, Theoretical
Neuroscience. We will follow the first six chapters of the book
very closely, and the later chapters more sketchily.

The web page for last year's course can be found here.