A constructivist neural network model of German verb inflection in agrammatic aphasia

We present a constructivist neural network that closely models the performance of agrammatic aphasics on German participle inflection. The network constructs a modular architecture leading to a double dissociation between regular and irregular verbs, and lesioning the trained network accounts for data obtained from aphasic subjects. We analyze the internal structure of the network with respect to the representation of regular and irregular verbs and argue that the constructivist neural network presents a more plausible account of verb inflection than a recently proposed dual-mechanism theory.