Which Matters More in Incidental Category Learning: Edge-Based Versus Surface-Based Features

The Visual Advantage Effect in Comparing Uni-Modal and Cross-Modal Probabilistic Category Learning

People rely on multiple learning systems to complete weather prediction (WP) tasks with visual cues. However, how people perform in audio and audiovisual modalities remains elusive. The present research investigated how the cue modality influences performance in probabilistic category learning and conscious awareness about the category knowledge acquired. A modified weather prediction task was adopted, in which the cues included two dimensions from visual, auditory, or audiovisual modalities. The results of all three experiments revealed better performances in the visual modality relative to the audio and audiovisual modalities. Moreover, participants primarily acquired unconscious knowledge in the audio and audiovisual modalities, while conscious knowledge was acquired in the visual modality. Interestingly, factors such as the amount of training, the complexity of visual stimuli, and the number of objects to which the two cues belonged influenced the amount of conscious knowledge acquired but did not change the visual advantage effect. These findings suggest that individuals can learn probabilistic cues and category associations across different modalities, but a robust visual advantage persists. Specifically, visual associations can be learned more effectively, and are more likely to become conscious. The possible causes and implications of these effects are discussed.

The role of working memory and visual processing in prototype category learning

To investigate whetherworking memory and visual processing havethe same role or differentrolesin A/B and A/not A prototype category learning,the present study adoptedan A/Bor A/not A category learningtask in control and dual conditions. The results of Experiment 1 showed that an additional dual visual working memory taskrather thanadualverbal working memory task reduced accuracy of the A/B task, whereasnodual tasksinfluencedaccuracy of the A/not A task. The results of Experiment 2 revealed that an additionaldual visual processing task impairedaccuracy of the A/B task, whereas the dual visual processing task did not influence accuracy of the A/not Atask. These results indicate that visual working memory and visual processing play different roles in A/B and A/not A prototype category learning, andsupport that thesetwo types of prototype category learning are mediated by differentmemory systems.

The Role of Edge-Based and Surface-Based Information in Incidental Category Learning: Evidence From Behavior and Event-Related Potentials

Although it has been demonstrated that edge-based information is more important than surface-based information in incidental category learning, it remains unclear how the two types of information play different roles in incidental category learning. To address this issue, the present study combined behavioral and event-related potential (ERP) techniques in an incidental category learning task in which the categories were defined by either edge- or surface-based features. The results from Experiment 1 showed that participants could simultaneously learn both edge- and surface-based information in incidental category learning, and importantly, there was a larger learning effect for the edge-based category than for the surface-based category. The behavioral results from Experiment 2 replicated those from Experiment 1, and the ERP results further revealed that the stimuli from the edge-based category elicited larger anterior and posterior P2 components than those from the surface-based category, whereas the stimuli from the surface-based category elicited larger anterior N1 and P3 components than those from the edge-based category. Taken together, the results suggest that, although surface-based information might attract more attention during feature detection, edge-based information plays more important roles in evaluating the relevance of information in making a decision in categorization.