Completed Brain & Nervous System Psychology & Behaviour

Explaining Language Outcome and Recovery After Stroke (ELORAS)

In plain English

AI plain-English summary

Two people who have the same stroke can end up with very different language abilities—and this project aims to find out why. Currently, doctors cannot reliably predict which stroke patients with aphasia will recover their speech, or how quickly. The standard assumption has been that the same language task, such as describing a picture, relies on the same brain regions in everyone. This project challenges that assumption. The researcher hypothesises that different people can use different sets of brain pathways to perform the same language task, and that this variation depends on an individual’s prior experience and inherent brain structure. To test this, the team will use functional neuroimaging to map the brain pathways healthy volunteers and stroke patients use during a range of language tasks. They will then cluster participants into groups based on which neural systems they recruit, and compare those groups on demographic, behavioural, and structural brain measures. If successful, the work will produce a new patient stratification system that could make prognoses for aphasia recovery far more accurate. That would allow clinicians to design individualised therapies tailored to the specific neural pathways a patient has available—rather than applying a one-size-fits-all approach. The research is fundamental science: it seeks a deeper theoretical understanding of how the brain sustains language, which could ultimately reshape how post-stroke rehabilitation is designed and evaluated.

View original technical description
My aim is to develop a theoretical model of language processing that explains inter-patient variability in outcome after stroke. My hypotheses are that the same language task (e.g. describing a picture) can be sustained by different sets of brain regions (and neuronal pathways) and that inter-subject variability in neuronal pathways for the same language task reflect an individual’s inherent potential and prior experience. My investigations will (1) use functional neuroimaging to characterize inter-subject variability in neuronal pathways in a range of language tasks; (2) cluster healthy individuals and stroke patients into different groups according to the neural systems used for the same task; and (3) compare the identified groups on a multitude of demographic, behavioural and structural imaging measures. The results will identify the factors that distinguish which neuronal pathways a subject typically uses and which neural pathways are available to support recovery. The work will provide: (i) greater understanding of the neuronal pathways sustaining recovery; (ii) improved accuracy and precision in our prognoses for whether and when patients with aphasia will recover after stroke, and (iii) a new patient stratification system that can be used to design effective, individualised therapeutic interventions.

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Researchers

Catherine Price (EPMC Awardee)

Related Research

Grants with similar aims, by meaning.

Predicting language outcome and recovery after stroke.
Towards a new neurological model of language that explains outcome after stroke.
Predicting Language Outcome and Recovery After Stroke
Developing a neuroscience-led basis for diagnosis, prognosis, management and therapy for aphasia post-stroke.
How the human brain supports language in different ways

Original classification

Principal Research Fellowship Renewal

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