Quantitative Assessment of Autistic Spectrum Disorder

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition, characterised by persistent deficits in verbal and nonverbal communication as well as restricted and repetitive behaviour, interests and activities. Symptoms most commonly appear in children around the age of 3 or sometimes as early as 1--2 years old. The condition is relatively common, with a reported prevalence of around 1.5%. Current methods of diagnosing ASD rely purely on behavioural observations, and no physiological diagnostic test exists. Hence diagnosis often comes very late, even in adulthood, affecting the individual's life chances. There is widespread interest in devising training or other remedial action to alleviate the symptoms and (hopefully) normalise the ASD child's developmental pathway. But for this approach to be effective, there needs to a quantitative physiological method of identifying ASD and monitoring its development. We now propose to develop such a method.

The work will be carried out in collaboration with MyMind (https://mymind.life/), a life science company based in Vienna, with a vision "to help people with neurological impairments live towards their full brain potential with affordable and easy to use technology". The company has a specific interest in developing therapies for children with ASD. To realise its aims MyMind needs a quantitative way of assessing the condition, and the aim of Sam Barnes's project is therefore to
develop algorithms and software for this assessment, using electroencephalograph (EEG) measurements of the kind that can be carried out routinely. The algorithms will be based on the results of our recent Lancaster/Blackpool project on ASD children, supported by Action Medical Research. Sam will make use of the toolbox MODA developed by members of the Nonlinear and Biomedical Physics research group. MODA is available both in MatLab and in Python. EEG data being recorded from children in Switzerland, Portugal and Austria will be made available by the company. The PhD research will therefore involve theory, data analysis and computation. Most of the work will be done in Lancaster, but in very close collaboration with MyMind. Contact will be partly by Teams and partly be e-mail, probably twice per week, or daily when needed. There will be at least one placement in Vienna for Sam to acquire experience of the industrial perspective and understand the processes and criteria to be met in bringing a new instrument to market.