Language Recovery Post Stroke Is Possible By Computer Simulations

Computer simulations of the brain help predict language recovery in stroke survivors and the need for custom speech therapy treatments for those having language loss, especially Hispanic bilingual patients, as per a study at the Boston University, published in the journal Scientific Reports. The team strives to better understand how language and speech are processed in the brain, and how to best rehabilitate people who have lost their ability to communicate as a result of language loss called aphasia, due to damage to the brain responsible for language production and processing, caused by a stroke, trauma, or another type of brain injury. This long-term neurological disorder impacts over a million people in the US.

The newly developed sophisticated computer models help to predict language recovery in Hispanic patients who speak both English and Spanish fluently (aphasia patients particularly at risk of long-term language loss), even before they start therapy.

The Hispanic stroke survivors experience greater difficulties in accessing language rehabilitation as they are nearly two times less likely to be insured than all other racial or ethnic groups in the US. This breakthrough technology is anticipated to be a game-changer for the field of speech therapy and stroke survivors impacted by aphasia.

However, most of the speech therapies are only available in one language, even though patients may speak multiple languages at home (as in the case of Hispanics). This makes it difficult for clinicians to prioritize which language a patient should receive therapy in.

Computer Simulation of Brain and Language Recovery

"This work started with the question, 'If someone had a stroke in this country and [the patient] speaks two languages, which language should they receive therapy in? Are they more likely to improve if they receive therapy in English? Or in Spanish? There is more recognition with the pandemic that people from different populations--whether [those be differences of] race, ethnicity, different disability, socioeconomic status--don't receive the same level of [healthcare]. The problem we're trying to solve here is, for our patients, health disparities at their worst; they are from a population that, the data shows, does not have great access to care, and they have communication problems [due to aphasia]," says Swathi Kiran, director of BU's Aphasia Research Lab, and College of Health & Rehabilitation Sciences: Sargent College associate dean for research and James and Cecilia Tse Ying Professor in Neurorehabilitation.

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These sophisticated neural network models simulate the brain of a bilingual person that is language impaired, and their brain's response to therapy in English and Spanish. The model can then identify the optimal language to target during treatment, and predict the outcome after therapy.

It was found that the models predicted treatment effects accurately in the treated language, meaning these computational tools could guide healthcare providers to prescribe the best possible rehabilitation plan.

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"If you're bilingual you may go back and forth between languages, and what we're trying to do [in our lab] is use that as a therapy piece. We are trying to develop effective therapy programs, but we also try to deal with the patient as a whole. This is why we care deeply about these health disparities and the patient's overall well-being," says Kiran.

The study is already set in its clinical trials using this technology that will provide an even clearer picture of how the models can potentially be implemented in hospital and clinical settings.

Source-Medindia