Rule based and information integration category learning

The following dataset includes sessions from rats and humans learning and generalizing to Rule-based and Information Integration categories. Here, category exemplars are Gabor patches, which are circular stimuli that contain black and white gratings. Across exemplars, these gratings can change in their spatial frequency and orientation. For Rule-based tasks, only one stimulus dimension (i.e., spatial frequency or orientation) is category-relevant, and the other dimension varies randomly. For Information Integration tasks, both stimulus dimensions (i.e., spatial frequency and orientation) are category-relevant. On each learning trial, participants are presented with a category exemplar and must decide its category membership. Feedback guides learning. Rats are trained using a touchscreen apparatus, whereas humans are trained using a desktop computer.Â