RT Journal Article SR Electronic T1 I like coffee with cream and dog? Change in an implicit probabilistic representation captures meaning processing in the brain JF bioRxiv FD Cold Spring Harbor Laboratory SP 138149 DO 10.1101/138149 A1 Milena Rabovsky A1 Steven S. Hansen A1 James L. McClelland YR 2017 UL http://biorxiv.org/content/early/2017/05/16/138149.abstract AB The N400 component of the event-related brain potential has aroused much interest because it is thought to provide an online measure of meaning processing in the brain. This component, however, has been hard to capture within traditional approaches to language processing. Here, we show that a neural network that eschews these traditions can capture a wide range of findings on the factors that affect the amplitude of the N400. The model simulates the N400 as the change induced by an incoming word in an initial, implicit probabilistic representation of the situation or event described by the linguistic input, captured by the hidden unit activation pattern in a neural network. We further propose a new learning rule in which the process underlying the N400 drives implicit learning in the network. The model provides a unified account of a large body of findings and connects human language processing with successful deep learning approaches to language processing.