Computing phenotype in the hyperkinetic movement disorders

The work in my proposal aims to transform our understanding of hyperkinetic movement disorders (chorea, dystonia, myoclonus, tics and tremor). I will apply an innovative combination of computational methods to leverage meaning from current clinical classification of phenotype. I will then flip the perspective to analytically challenge traditional approaches and probe existing assumptions for novel insight. Key goals are: 1) Define the feature space and boundaries of each phenotype 2) Model the behavioural signatures for each phenotype 3) Evaluate which behavioural tasks have the most 'signal' for each phenotype 4) Reveal how a data-led clustering of hyperkinetic movement compares to current clinical classification. An early-career award would be based at the Gatsby Computational Neuroscience Centre, an opportunity to acquire an exceptional training in state-of-the art pattern recognition and machine learning and apply computational methods to ambitious and carefully curated behavioural datasets. All datasets and analysis will be published online as resources for the international movement disorders community.