Better understanding of how autism and ADHD arise and develop in young people

The researchers aim to gain a better understanding of how autism and ADHD symptoms emerge and develop from infancy to the age of ten.

Diagnosing neurodevelopmental conditions such as autism and ADHD in preschool-aged children is often challenging for the clinics. Many children show subtle or uncertain signs that are not yet clear enough for a diagnosis. This can result in a common, but often unhelpful, “wait-and-see” approach, which delays support for children and their families during crucial developmental years.

By following a large group of children with a family history of autism and ADHD, the project seeks to identify which early indicators truly predict a later diagnosis, and which do not.

The project will also investigate whether brain activity in infancy, measured through EEG, can help predict future outcomes. Using machine learning, the researchers will develop practical tools that clinicians can use to make earlier and more accurate assessments.

Ultimately, the results may help healthcare providers offer timely support and clearer guidance to families when concerns arise, improving long-term well-being and developmental opportunities for children at risk.