Supervision, Category Structure, and Selective Attention in Category Learning: A Comparative Approach

We investigated the interactions between supervision, category structure, and selective attention in category learning. We compared human adults and pigeons in a category learning task, where we manipulated the category structure (dense vs. sparse) and the level of supervision by corrective feedback (low vs. high). Results showed a benefit of supervision across species, which was particularly strong in learning the sparse categories. Moreover, both species benefitted from category structures that had multiple category-relevant dimensions (i.e., dense categories). In addition, human adults, who have a more advanced ability to attend selectively, showed faster learning and better generalization overall. Finally, attention was optimized to the category-relevant dimension in the sparse category only in human adults. Subsequent computational simulation of the data indicated that these patterns were well explained by a parameter that controls the ability to flexibly switch attention to category-relevant dimensions.