Explaining Language Outcome and Recovery After Stroke (ELORAS) (360G-Wellcome-205103_Z_16_Z)

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.