N 400 amplitudes as change in a probabilistic representation of meaning : A neural network model

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. Yet, the underlying process of meaning construction remains incompletely understood. Here, we present a computationally explicit account of this process and the emerging representation of sentence meaning. We simulate N400 amplitudes as the change induced by an incoming stimulus in an implicit and probabilistic representation of meaning captured by the hidden unit activation pattern in a neural network model of sentence comprehension, and propose that the process underlying the N400 also drives implicit learning in the network. We account for a broad range of empirically observed N400 effects which have previously been difficult to capture within a single integrated framework.