(Duke University)
This sort of analysis, made by measuring a large set of geometrical images with a device called a laser range scanner, showed that the brain is not a calculating engine, cranking out stimulus features, but a “statistical engine” wired by evolution and a person’s experience to make the best statistical guess about objects in a visual scene, based on how successful those guesses have been in the past.
“So, vision is not about extracting features from a scene; it’s about extracting statistics in the sense of relating the image on your retina to the visually guided behavior that’s worked in the past,” said Purves. “This framework for thinking about vision explains quantitatively—sometimes in amazing detail—what we end up seeing.”
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