Related press release:

In the mind’s eye: How the brain makes a whole out of parts

When a human looks at a number, letter or other shape, neurones in various areas of the brain’s visual center respond to different components of that shape, almost instantaneously fitting them together like a puzzle to create an image that the individual then “sees” and understands. All of this seems immediate and effortless, but shape perception is computationally very difficult – machine vision systems have not come anywhere near human performance. How the brain sees, recognizes and understands objects is one of the most intriguing questions in neuroscience.

What makes shape perception so difficult? First, any given object can present an infinity of different images to the retina, and your visual system has to somehow map all those images to one category.

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Somehow, your visual system correctly maps all these very different images to the category “dolphins.”

Second, there is a virtual infinity of objects in the world, and you have to be able to perceive each one, store it in memory, and recognize it when you see it again.

All of this is accomplished by a large but finite number of neurones. There aren’t enough neurones in the brain to have one for each object, much less one for each retinal image of each object. The visual system must have a neural representation scheme with the capacity to encode an infinity of shapes and the flexibility to handle different retinal images of the same shape.

This is just an introduction to the fascinating field of shape perception
– read more by following the links above.