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First impressions: Computer model behaves like humans on visual categorization task

keleton of a theory of vision. The huge task in front of us is to incorporate into the model the effects of attention and top-down beliefs." The team is now exploring what happens after the first feed-forward sweep, during the next 200-300 milliseconds of object recognition.

The Poggio lab plans to include feedback loops in the model by modeling the widespread anatomical backprojections in cortex, while Oliva is designing behavioral studies that can test if the enhanced model matches the performance of humans who have more time to examine a scene.

For cognitive neuroscientists, these results add to the convergence of evidence about the feed-forward hypothesis for rapid categorization. "There could be other mechanisms involved, but this a big step forward in understanding how humans see," said Oliva. "For me, it's putting light in the black box and gives direction to design new experiments, for instance to explore perception in clutter."


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Contact: Laurie Ledeen
ledeen@mit.edu
617-324-0134
McGovern Institute for Brain Research
2-Apr-2007


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