Vision recognition

Four

research institutions have each received a $500,000 (£286,000) grant from the US

to develop new computational models of how the brain’s visual system learns to recognise objects.

The project’s researchers - at New York University’s Courant Institute of Mathematical Sciences, Stanford University, MIT, and the University of California, Berkeley - hope to uncover new mechanisms that could explain the learning process in the brain’s neural circuits.

Results from psychophysics, neuroscience and computational modelling show that the rapid recognition of everyday objects can be explained by viewing the brain’s visual cortex as a multi-layer, feed-forward system in which the neural activity propagates from the eye to the higher brain areas, with little feedback from the higher layers to the lower layers.

Yet, there are as many feedback connections as feed-forward connections in the visual cortex, and the researchers will seek to understand their role.