ECE 598TC - Spring 2007

Inference, Estimation and Neuroscience

Instructor: Prof. Todd Coleman

Time and Place: MW 10-11:20am, 141 Coordinated Science Laboratory

Handouts:

• Course Information

Lecture Notes:

• Introduction
• Probability Theory
• Multiple Random Variables
• Point Processes for Modeling Neural Spiking
• Nonrandom Parameter Estimation I (Method of Moments, Confidence Intervals)
• Nonrandom Parameter Estimation II (Likelihood Methods)
• Bayesian Estimation
• Monte-Carlo Methods
• The EM Algorithm
• Linear Regression
• Information Theoretic Model Selection
• Exponential Families and the Generalized Linear Model (GLM)
• Hidden Markov Models and Recursive Estimation

Problem Sets:

• Problem Set 1 due 2/19/07
• Problem Set 2 due 3/12/07
• Problem Set 3 due 4/11/07
• Problem Set 4 due 5/2/07

See here for Matlab files for Problem Sets