Modeling the regular/irregular dissociation in non-fluent aphasia in a recurrent neural network

In the debate between single-route and dual-route models of verb inflection, the dissociation between regular and irregular verbs in the non-fluent variety of aphasia has been a key sticking point for the proponents of the single-route model. This paper adopts a state-of-the-art neural model which has previously been used to learn inflectional morphology, and shows that it can also be used to model data from non-fluent aphasia. This challenges the assumption that a dual-route model is necessary to capture apparent dissociations in aphasia data and encourages a reanalysis of the deficits involved in non-fluent aphasia