Bilingual people with language loss due to stroke can pose a treatment challenge – computational modeling may help clinicians treat them – The Conversation

Researchers can program neural networks composed of artificial neurons to simulate language processing. Andriy Onufriyenko/Getty Images


The big idea

New research shows that computational modeling can predict how bilingual stroke patients will respond to language treatment – and that could help clinicians identify which language to focus treatment on and increase chances for improvement in both.

Aphasia is a speech and language disorder often caused by stroke. Bilingual people with aphasia typically experience difficulty retrieving words in both of their languages. While language therapy can help them improve their ability to communicate, it’s not often clear to clinicians which language to target in treatment.

I’m a cognitive neuroscientist, and my current work focuses on language treatment outcomes in bilinguals with aphasia. As part of the Aphasia Research Laboratory at Boston University, my colleagues and I worked with computer scientists at the University of Texas at Austin to develop BiLex – a computational model that simulates the ability to retrieve words from memory in bilinguals.

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