Abstract
A hallmark of visual intelligence is the ability to extract relationships among objects. One form of extraction produces stimulus-specific knowledge (statistical learning). Another form produces stimulus-general principles (inductive learning). These two learning processes seem incompatible on the surface, but may be related on a deeper level. Here we examine how statistical learning and inductive learning interact. In Experiment 1, observers were randomly assigned to one of three conditions where they viewed a sequence of circles of varying sizes. In the rule+regularities condition, the sequence contained repeated triplets (regularities) that followed a rule: the three circles increased in size in each triplet. In the rule-only condition, the sequence contained sets of three circles that followed the same rule, but all sets were unique (no regularities). In the regularities-only condition, the sequence contained repeated triplets that did not follow the rule. We found that learning of the rule and learning of the regularities were both stronger in the rule+regularities condition than in the rule-only, or the regularities-only condition. This suggests that statistical learning and inductive learning are mutually beneficial. To tease apart whether one learning process is necessary for the other, we increased the complexity of the rule in Experiment 2. Everything was identical to Experiment 1, except now the rule was that within each triplet or set, the first circle was smaller than the second circle, and the second was larger than the third. Learning of the rule was only successful in the rule+regularities condition, but not in the rule-only condition. Moreover, there was no learning of regularities. This suggests that the presence of regularities facilitated rule learning, but the presence of the rule did not help the learning of regularities. These findings demonstrate that statistical learning and inductive learning are related, and that stimulus-specific regularities are necessary for inductive learning.
Meeting abstract presented at VSS 2015