Abstract Links between the eye and the central nervous system (CNS) have been recognized since the origins of the ophthalmoscope. Owing to the elegant topography of the afferent visual pathway and its close embryonic, anatomical, and physiological connections to the brain, it is possible to capture structural effects of CNS injury in the retina. The availability of large-scale, high-quality retinal imaging datasets and ongoing advances in artificial intelligence (AI) have paved the way for Oculomics, a field in which ocular measures act as biomarkers for systemic diseases. Similarly, ocular images have been used in AI models to provide critical insights about neurologic disorders in the fledgling discipline of what might be considered Neuro-Oculomics. In this review, we will describe key ocular imaging techniques and highlight emerging roles for AI in the diagnosis and management of important neurological conditions.
Costello et al. (Mon,) studied this question.