Rehabilitation in bilingual aphasia

In this project, Risto Miikkulainen uses artificial neural networks to model individual bilingual patients whose lexical performance is impaired following an ischemic stroke. The model consists of a self-organizing map for the semantics of words, and a self-organizing map for their phonological forms, connected with associated connections. The model is trained to match the patient’s language history, damaged to match their post-stroke impairment, and then used to search for the most effective rehabilitation recipe. This model is currently tested in an NIH-funded clinical trial—to our knowledge, the first artificial neural network model to be tested in this role.