Mechanisms of generalization in perceptual learning

The learning of many visual perceptual tasks has been shown to be specific to practiced stimuli, while new stimuli require re-learning from scratch. Here we demonstrate generalization using a novel paradigm in motion discrimination where learning has been previously shown to be specific. We trained subjects to discriminate the directions of moving dots, and verified the previous results that learning does not transfer from the trained direction to a new one. However, by tracking the subjects' performance across time in the new direction, we found that their rate of learning doubled. Therefore, learning generalized in a task previously considered too difficult for generalization. We also replicated, in the second experiment, transfer following training with "easy" stimuli. The specificity of perceptual learning and the dichotomy between learning of "easy" vs. "difficult" tasks were hypothesized to involve different learning processes, operating at different visual cortical areas. Here we show how to interpret these results in terms of signal detection theory. With the assumption of limited computational resources, we obtain the observed phenomena - direct transfer and change of learning rate - for increasing levels of task difficulty. It appears that human generalization concurs with the expected behavior of a generic discrimination system.