Imaging genetics

Genetic diagnoses for epilepsy and other neurodevelopmental disorders are becoming increasingly prevalent, but symptoms, prognoses and optimal treatment strategies vary even among those with the same genetic mutation.

This project aims to develop machine learning methods to link genetic diagnosis, brain development, and neurodevelopmental profiles in rare genetic cohorts, hoping to contribute to our understanding of genetic disorders and potential clinical translation.

The current aims of the project are:

• Create a large MRI dataset of typically developing controls
• Collect MRI data from multi-centre clinical cohorts of subjects with genetic neurodevelopmental disorders
• Develop tools for:
  • processing infant scans
  • charting paediatric normative brain development across the lifespan, particularly in younger children and infants, and centile scoring the development of neurodevelopmental disorder cohorts

Genetic cohorts in progress include:

• SCN1A
• SCN2A
• DHDDS
• ATP1A3
• TSC

Other neurodevelopmental cohorts:

• Rasmussen’s

If you are interested in getting involved, please contact us at: MELD.study@gmail.com