Advances in ocular motor and pupil biomarkers for neurological disorders

Neurological disorders are often difficult to diagnose and monitor, particularly in the early stages when symptoms may be subtle or nonspecific. Because the visual system engages a large portion of the cerebral cortex and relies on well-defined neural pathways, it offers a unique and accessible window into brain function. In this context, the concepts of oculomics and oculometrics have gained increasing attention. Oculomics refers to the study of systemic and neurological diseases through ocular biomarkers, while oculometrics involves the computational quantification of eye and pupil parameters. Together, these approaches provide noninvasive, objective, and reproducible methods to assess neurological function, with strong potential to improve diagnostic precision, monitor disease progression, and guide individualized care. This review synthesizes recent advances in ocular motor and pupillary biomarkers in three major neurological conditions: multiple sclerosis, Parkinson's disease, and Alzheimer's disease. In multiple sclerosis, early ocular motor disturbances such as internuclear ophthalmoplegia, saccadic dysmetria, and impaired smooth pursuit are frequently observed and may reflect brainstem and cerebellar involvement. Relative afferent pupillary defect, objectively measured with pupillometry, is a strong indicator of optic neuritis. In Parkinson's disease, impaired saccadic initiation, hypometric saccades, and convergence abnormalities reflect basal ganglia dysfunction, while pupil irregularities suggest underlying autonomic imbalance. In Alzheimer's disease, impairments in saccades, smooth pursuit, fixation instability, and the pupillary light reflex have been associated with early cortical and brainstem pathology, reflecting deficits in attention, executive control, and cholinergic function. We also discuss the integration of eye-tracking data with neuroimaging and electrophysiology biomarkers to support multimodal diagnostic frameworks with the potential to improve diagnostic accuracy and disease monitoring. In addition, we highlight how recent technological developments in virtual reality-based eye-tracking could offer immersive, standardized testing conditions to enable scalable implementation of oculometric assessments in clinical practice. As the fields of oculomics and oculometrics continue to evolve, these approaches hold promise to bridge the gap between research and clinical application. However, large-scale validation studies, standardized protocols, and normative datasets are essential for broader clinical adoption. By embedding ocular motor and pupillary biomarkers into routine neurological assessments, clinicians may be able to detect disease earlier, differentiate between overlapping syndromes, and monitor therapeutic outcomes more effectively.