Project title: AI-enabled understanding of oculomotor control through high-resolution imaging of the living human retina
PI: Martin Booth
The human retina is a directly observable part of the central nervous system (CNS). Cutting-edge cellular-resolution retinal imaging technology is the key to understanding covert mechanisms in visual neuroscience but suffers from artefacts arising from constant involuntary eye movements that in itself reflect CNS control. This project aims to develop a fully AI-enabled framework to analyse and understand oculomotor control with unprecedented efficiency, precision, and reliability.
