Biologically Inspired Algorithms for Restoring Vision to the Blind
Degenerative retinal diseases such as retinitis pigmentosa and macular degeneration cause irreversible vision loss in more than 10 million people worldwide. Analogous to cochlear implants, retinal prostheses use a grid of electrodes to stimulate surviving retinal cells in order to evoke visual percepts. However, a major outstanding challenge in the use of these devices is translating electrode stimulation into a code that the visual system can interpret. A common misconception is that each electrode in the grid can be thought of as a ‘pixel’ in an image; to generate a complex visual experience, one then simply needs to turn on the right combination of pixels.
Contrary to this belief, I will present recent evidence showing that the generated visual experience includes nontrivial perceptual distortions caused by interactions between the implant electronics and the retinal neurophysiology. In particular, I will present a computational model based on clinical and psychophysical data that accurately predicts these distortions across a wide range of subjects and implant configurations. I will then discuss how detailed knowledge of the visual system can be combined with data-driven techniques to develop novel encoding algorithms aimed at minimizing distortions and improving patient outcomes. I will close by outlining future strategies for leveraging virtual/augmented reality to quickly and efficiently test novel stimulation strategies in real-world tasks using visually typical individuals as ‘virtual patients’.
Overall this work has the potential to 1) further our understanding of how sight recovery technologies such as retinal implants interact with the human visual system, 2) drastically improve the perceptual experience of current retinal prosthesis patients, and 3) accelerate the prototyping of new devices.
Michael Beyeler is a Postdoctoral Fellow in Neuroengineering and Data Science at the University of Washington (UW) in Seattle. He has a PhD in Computer Science from UC Irvine as well as a BS in Electrical Engineering and a MS in Biomedical Engineering from ETH Zurich, Switzerland. His research focuses on the development of novel methods and algorithms to interface sight recovery technologies with the human visual system, with the ultimate goal of restoring useful vision to people suffering from severe blindness. Most recently, he was awarded the prestigious Washington Research Foundation Innovation Fellowship, which enabled his early postdoctoral work at UW and led to an NIH K99 Pathway to Independence Award.