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Nihong Chen, Taiyong Bi, Zili Liu, Fang Fang; Neural mechanisms of motion perceptual learning. Journal of Vision 2012;12(9):1126. doi: 10.1167/12.9.1126.
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© ARVO (1962-2015); The Authors (2016-present)
Practice substantially improves motion direction discrimination. However, the neural mechanism of this perceptual learning is little understood. We studied this mechanism with functional magnetic resonance imaging before and after training. During training, nine subjects practiced eight daily sessions (9,600 trials total) to discriminate motion directions of two successive random-dot kinematograms at 100% coherence, with the method of constant accuracy at 75% correct. Each of the subjects was trained along one of the following eight directions that started from 22.5° and with an increment of 45°. Before and after training, the subjects’ motion direction discrimination thresholds were measured along the directions that were 0°, 30°, 60°, and 90° away from the trained direction. Blood-oxygenation-level-dependent (BOLD) signals were also measured in a 3T Siemens magnet while subjects performed the same motion discrimination task along these motion directions at 75% correct. Behaviorally, training gave rise to 44% improvement along the trained direction, which transferred little to the untrained directions. BOLD signals were analyzed in V1, V2, V3, V5/MT+, posterior as well as anterior intra-parietal sulci (pIPS and aIPS), all of which were sensitive to visual motion. We found that, as a result of training, the BOLD responses in V3 and V5/MT+ to stimuli along the trained direction were reduced as compared to stimuli along the untrained directions. Multi-voxel pattern analysis further showed that the decoding accuracy in aIPS was selectively improved for the trained direction after training. Our analysis at the population level suggests that perceptual learning results in a more efficient representation in the visual cortex and a more accurate read-out in the higher-level cortex for the trained stimuli.
Meeting abstract presented at VSS 2012
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