Associative symmetry vs. independent associations

Abstract We develop a neural network model of paired-associate learning based upon an auto-associative learning mechanism. We show that this relatively simple neural network can replicate complex human behavioral data, but only when the correlation between forward and backward learning is highly correlated. This network-based analysis is used to constrain psychological theories of association in humans.