  Bionic vision uses neuroprostheses to restore useful vision to people living
with incurable blindness. However, a major outstanding challenge is predicting
what people 'see' when they use their devices. The limited field of view of
current devices necessitates head movements to scan the scene, which is
difficult to simulate on a computer screen. In addition, many computational
models of bionic vision lack biological realism. To address these challenges,
we present VR-SPV, an open-source virtual reality toolbox for simulated
prosthetic vision that uses a psychophysically validated computational model to
allow sighted participants to 'see through the eyes' of a bionic eye user. To
demonstrate its utility, we systematically evaluated how clinically reported
visual distortions affect performance in a letter recognition and an immersive
obstacle avoidance task. Our results highlight the importance of using an
appropriate phosphene model when predicting visual outcomes for bionic vision.
