Perceptual learning is defined as the ability to improve one’s performance in basic discrimination tasks via extended practice. Is this process influenced by statistical regularities in the scene that have no relation to the discrimination task at hand? Using a 5-day standard perceptual training protocol, we trained two groups of observers to perform an orientation discrimination task with Gabor patches. For one group, the background color of the scene changed across trials according to a fixed sequence, while for the other group, the background color changed randomly throughout the training. Baseline and post training discrimination thresholds were assessed in three conditions: (1) with randomly changing background colors, (2) with backgrounds following the fixed color sequence, and (3) with gray background. Overall, the group trained with fixed color sequence learnt more (had a larger reduction in orientation threshold by the end of the fifth day) than the group trained with randomly changing colors. Furthermore, while there was no difference across the baseline thresholds in the three conditions before training, after training, observers in the fixed sequence group showed the lowest threshold with fixed color sequence of the background, while their thresholds with random, and gray backgrounds were equally worse (higher). In contrast, observers in the random sequence group showed the lowest threshold during post test with the randomly changing background, intermediate thresholds with gray background, and the worst thresholds with fixed color sequence. Our results suggest that task irrelevant statistical structure in perceptual tasks is automatically and implicitly built in the developing internal representation during learning, and it can differentially affect the learning process. Moreover, altering such irrelevant context after learning has a highly specific effect on performance arguing for the emergence of a complex internal representation even in the simplest perceptual learning tasks.

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