A third of stroke survivors lose the ability to speak or understand language, and current therapies often fail because they focus on damaged language areas while ignoring the brain's general cognitive support systems. This research targets a fundamental gap: why some stroke patients recover language while others do not. The researcher has shown that recovery depends not just on language-specific brain regions, but on a domain-general frontoparietal network (FPN) that handles attention, working memory, and learning. Patients whose FPN functions similarly to healthy controls recover better; those with disrupted FPN activity fare worse. The project will test 50 stroke patients using real-time MRI to map FPN activity across language and non-language tasks. It will then combine this imaging with non-invasive electrical stimulation to identify personalised settings—optimal phase and frequency—that maximise FPN activation for each individual. Finally, it will test whether this personalised stimulation improves language performance. If successful, this could transform aphasia rehabilitation by shifting focus from damaged language regions to the brain's general cognitive machinery. Because the FPN supports many cognitive functions, the approach could extend beyond language to rehabilitation for other brain injuries and deficits.
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Context There are 1.2 million stroke survivors in the UK with a societal cost of £26 billion a year. Language impairment (aphasia) is a major cause of disability after stroke affecting a third of all patients. Current therapeutic strategies for treating aphasia have either had little success or demand prolonged and intensive speech and language therapy which is not feasible within the NHS. Most of these therapeutic strategies have largely focused on improving the residual language-specific processes or brain regions that support them. However, I have shown that residual language function after stroke is also dependent on support from the so-called domain-general brain regions that mediate general cognitive processes such as attention, working memory, and learning (or reacquisition) of a skill. Importantly, increased activity within the domain-general regions of a well-established bilateral frontoparietal brain network (FPN) has been shown to be associated with better recovery of language function after stroke, building a case for its potential as a prognostic biomarker and therapeutic target. The overall aim of this proposal is to investigate and to optimise the compensatory role of this domain-general brain network in recovery of language function after stroke. Objectives 1. To use a rapid real-time brain imaging protocol to measure the function of the domain-general FPN across a wide range of language and non-language tasks in patients after stroke. Based on preliminary results, it is expected that patients who have a similar FPN function compared to the controls, will have the best language outcomes following their stroke. Conversely, those patients with a dissimilar FPN functional profile to the controls will have the worse outcomes. 2. To combine real-time brain imaging and non-invasive brain stimulation to rapidly identify personalised brain stimulation settings that maximise the function of the domain-general FPN for each individual patient. 3. To investigate whether the use of personalised brain stimulation of the domain-general FPN improves behavioural performances in patients after stroke. Method I will use advanced magnetic resonance imaging (MRI) to study brain structure and function. Importantly I will use a novel technique that analyses brain function in real-time whilst participants perform tasks in the scanner. This will allow for a rapid assessment of the function of domain-general brain regions of the FPN across a wide range of experimental conditions. I have used this technique in a pilot study of patients to show that the pattern of activity of the FPN across a range of language and non-language tasks, is related to the degree of language impairment after stroke. I will use the same technique on a group of 50 patients following a stroke, and relate their imaging measures to their language function after the stroke. In a second study, I will use the same real-time brain imaging technique combined with non-invasive brain stimulation, to identify for each individual patient the optimal brain stimulation settings that maximally activate their domain-general FPN. Here, the optimal phase and frequency of the brain stimulation will be identified for each individual patient. In the third study, I will apply brain stimulation using the personalised stimulation settings for each patient, to improve behavioural performances. Potential applications and benefits Language impairment after stroke is common, and it is unclear how best to rehabilitate individuals. Identifying individuals who will benefit from rehabilitation of domain-general brain regions that support their residual language function will provide a new therapeutic avenue. Demonstration of modulation of these regions using a personalised non-invasive brain simulation will not only benefit patients with language impairment, but will have far reaching implications for rehabilitation across a wide range of brain deficits and injuries.
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