The visual ecology of colour and light

The human visual system has been moulded by the spatial and spectral properties of its environment. This session illustrates four examples of this interaction - showing how human visual processing is affected by changes in mean illumination and colour across the day, statistical regularities in spatiochromatic signals and our own activity within those environments.

Visual prosthetics

Amid challenges in commercializing retinal implant technology, scientific efforts are underway to learn from previous obstacles and spearhead the next wave of prosthetic vision innovations. This session will cover the current state and future directions in visual prosthetics, focusing on the creation of implants with large counts of flexible electrodes, and how their design and functionality may be informed by advancements in our understanding of device-neural tissue interactions and artificial intelligence. Insights from current clinical trials will provide a well-rounded view of the progress toward more effective visual prosthetic solutions.

Focusing on the human fovea

The machinery of human vision is spatially inhomogeneous, with a neuronal sampling gradient that peaks near the line of sight and declines sharply with eccentricity. Despite the foveated nature of the visual system, our field of vision appears comparatively uniform in quality. This session will feature recent work that characterizes the structure of foveal pathways using high-resolution ophthalmoscopy and neuroimaging, and will highlight complementary behavioral studies that show how oculomotor control, attentional processing, and the integration of information across the central retina influence our subjective experience.

Machine learning and AI approaches to retinal diagnostics

The human retina is a vascularized neural structure that is uniquely accessible to optical imaging. This means that large amounts of imaging data are available from clinical retinal scans and it is possible to use these data to teach machine learning models to diagnose disease. Our speakers will present the current state-of-the-art analysis of retinal imagining using AI/machine learning and discuss the broader ethical ramifications of this technology and potential future applications.

Stay tuned for the full schedule of events. Call for abstract submissions will be out soon!