People with focal upper limb dystonia lose control of their hand during specific tasks like writing or playing an instrument, and this project will use ultra-powerful brain scanners to trace the microscopic changes driving that loss of control. The problem is that while doctors know dystonia involves faulty brain signals, they do not understand exactly what goes wrong at the level of individual nerve fibres and synapses in the motor network. Most previous studies have used relatively coarse imaging techniques that cannot distinguish between different types of tissue damage. This project will combine a specialised MRI scanner with magnetoencephalography to measure both the structural integrity of white matter pathways and the electrical activity of neurons in the same patients, then use computational models to work out which changes cause the others. If the research succeeds, it will reveal whether the primary defect lies in localised microstructural damage or in how different brain regions communicate. That distinction matters because it points toward different treatment strategies—for example, whether to target the affected hand area directly or to rebalance wider network activity. This is fundamental science: understanding the biological mechanism of a poorly understood neurological condition. Similar work on other movement disorders has eventually guided the development of focused ultrasound and deep brain stimulation therapies.
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Background Dystonia is a heterogenous group of disorders involving abnormal postures. Focal forms, such as adult-onset idiopathic upper limb dystonia (AOIFULD), provide opportunity to study motor-phenotype specific changes in this poorly understood disorder. Previous studies indicate disruption to inhibitory activity in motor brain networks, with microstructural white matter pathway changes identified in cervical dystonia using modelling approaches. To date, studies of AOIFULD have implicated microstructural changes using non-specific volumetric and diffusion tensor-based approaches. AOIFULD represents a dystonia form that is therapeutically challenging to manage, and differs from cervical dystonia in its task-based and lateralized nature. Work assessing the microstructural underpinnings of this distinct phenotype and bridging to biologically relevant network level changes is vital in extending our wider comprehension of dystonia pathophysiology. Aims and Objectives 1) Recruitment of a highly phenotyped cohort of individuals diagnosed with AOIFULD (n=19). All participants will undergo in depth structural (diffusion MRI) and functional (functional MRI- fMRI, MEG) brain imaging utilising the ultra-strong diffusion gradient Connectom MRI scanner and Magnetoencephalography (MEG) facilities available at the Cardiff University Brain Research Imaging Centre (CUBRIC). 2) Determination of dystonia specific localised motor network differences in microstructure (diffusion MRI- SANDI and Standard Model) and synaptic activity (MEG- beta band activity; fMRI- BOLD signal responses), and to explore how these translate to network level motor differences in structural (diffusion MRI) and functional (fMRI, MEG) connectivity 3) Using this to infer biological mechanisms of focal idiopathic dystonias using effective connectivity models (dynamic causal modelling, inferring directionality) of underlying cortical circuitry abnormalities.
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