Spatio-temporal integration properties of the human visual system: Theoretical models and clinical applications

Visual perception has a fundamental role in supporting our interactions with the environment, yet not all visual information that reaches the eye is needed for this purpose. In order to be able to efficiently process the tremendous amount of continuously incoming visual information, our visual system needs to compress this stream both spatially and temporally. It does this in a way that is somewhat analogous to how computers compress videos in MPEG format: only the relevant information is retained, but it now requires a fraction of the memory to be stored. The quantification of this human compression process, called spatio-temporal integration, can provide useful insights into the structural and functional integrity of the central nervous system.
However, quantitative models of spatio-temporal integration are relatively rare, and existing ones are mostly confined to theoretical or experimental contexts.
In my studies, I have attempted to bridge the gap between our scientific understanding of integration and the use of this knowledge in actual clinical practice. I have used eye movements to investigate this phenomenon and I built a mathematical framework that quantifies their spatio-temporal properties. I showed how the spatio-temporal integration of visual information performed by the oculomotor system in order to track continuously moving stimuli can be used to perform neuro-ophthalmic screening assessments. Specifically, I developed time-efficient, patient-friendly techniques to measure the visual field and to detect oculomotor abnormalities associated with neurodegenerative conditions such as Parkinson’s Disease and Multiple Sclerosis.