Fig. 1: Degenerative retinal diseases cause irreversible vision loss in more than 10 million people worldwide. Analogous to cochlear implants, retinal prostheses electrically stimulate surviving retinal cells in order to evoke neuronal responses that are inter-preted by the brain as visual percepts (‘phosphenes’).
The 'bionic eye'—so long a dream of the future—is finally becoming a reality with retinal prostheses available in the US and Europe (Fig. 1; over 300 patients implanted). With cortical implants, optogenetic approaches, and stem cell therapy in development, a wide range of sight recovery (SR) options will be available to patients suffering from severe blindness.
Despite the increasing clinical and commercial use of these devices, the perceptual experience of SR patients is surprisingly poorly understood. A common misconception in the field is that each electrode in an array 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. However, almost all SR technologies are likely to suffer from perceptual distortions and subsequent loss of information due to interactions between the technology and the underlying neurophysiology.
The goal of my research is therefore:
  1. to understand how interactions between SR technologies and neurophysiological mechanisms shape the visual perception of SR patients, and
  2. to use this knowledge to develop advanced stimulation strategies for different SR devices, with the ultimate goal of restoring useful vision to people suffering from severe blindness.

Selected Publications

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Current retinal implant users report seeing distorted and often elongated shapes rather than small focal spots of light that match the shape of the implant electrodes. Here we show that the perceptual experience of retinal implant users can be accurately predicted using a computational model that simulates each individual patient’s retinal ganglion axon pathways. This opens up the possibility for future devices that incorporate stimulation strategies tailored to each individual patient’s retina.
bioRxiv 453035, 2018

The goal of this review is to summarize the vast basic science literature on developmental and adult cortical plasticity with an emphasis on how this literature might relate to the field of prosthetic vision.
J Neural Eng 14(5), 2017

We developed pulse2percept, an open-source Python implementation of a computational model that predicts the perceptual experience of retinal prosthesis patients across a wide range of implant configurations. A modular and extensible user interface exposes the different building blocks of the software, making it easy for users to simulate novel implants, stimuli, and retinal models.
SciPy: 81-88, 2017