Syllabus
INTRODUCTION
MATRIX CALCULUS
PROBABILITY & RANDOM VARIABLES
GENERAL LINEAR MODEL
CONTRASTS & CLASSICAL INFERENCE
THRESHOLDING
HIERARCHICAL MODELS
RESTRICTED MAXIMUM LIKELIHOOD ALGORITHM
EXPECTATION MAXIMIZATION ALGORITHM
CLASSICAL & BAYESIAN INFERENCE
PREPROCESSING & SEGMENTATION
BAYESIAN ESTIMATION OF EEG RESPONSES
