Extra eye movements could improve self-driving cars

The study, recently published in PLOS Computational Biology, focuses on the unnoticed eye movements humans make, showing that they serve a vital purpose in allowing people to stably recognise objects. 

Through this work, Andrea Benucci and colleagues at the RIKEN CBS in Japan have developed a way to create artificial neural networks that can reportedly learn to recognise objects faster and more accurately.

Despite making constant head and eye movements throughout the day, objects in the world do not blur or become unrecognisable, even though the physical information hitting human retinas changes constantly. 

What likely makes this perceptual stability possible are neural copies of the movement commands. These copies are sent throughout the brain each time humans move, and are thought to allow the brain to account for people’s own movements and keep perception stable.

In addition to stable perception, evidence suggests that eye movements, and their motor copies, might also help people to stably recognise objects in the world, but how this happens remains a mystery.