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Nature 431, 775-781 (14 October 2004) | doi:10.1038/nature03013; Published online 13 October 2004
review article Neural networks and perceptual learning
Misha Tsodyks1 & Charles Gilbert2
Abstract
Sensory perception is a learned trait. The brain strategies we use to perceive the world are constantly modified by experience. With practice, we subconsciously become better at identifying familiar objects or distinguishing fine details in our environment. Current theoretical models simulate some properties of perceptual learning, but neglect the underlying cortical circuits. Future neural network models must incorporate the top-down alteration of cortical function by expectation or perceptual tasks. These newly found dynamic processes are challenging earlier views of static and feedforward processing of sensory information.
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