News/Notices

Feb. 17, 11:45, Wei Ji Ma. Optimality and Probabilistic Computation in Visual Categorization

Paradoxical effects of attention on visuomotor learning

Joo-Hyun Song

Department of Cognitive, Linguistic & Psychological Sciences

Brown University 

Searching for a visual target interferes with detecting background changes and performing an auditory detection task interferes with a sequential response task. These well-known findings show that divided attention within or across tasks can be very costly, confirming the common sense idea of capacity limits of attention. However, paradoxically, we demonstrated that for visual motor learning tasks, divided attention can have major benefits. In a series of behavioral studies in which we combined the visuomotor adaptation task with attention-demanding visual detection tasks, we showed that attention can be allocated to both visual and motor goals. Furthermore, our results are the first to show that having reduced attentional resources available at recall resulted in better retrieval of a recently acquired visuomotor memory. We revealed that this pattern depends on the consistency of attentional states between learning and recall phases, such that recall is better under conditions of divided attention if learning also occurred in a divided attentional state. Furthermore, these attentional states can be maintained across different tasks and sensory modalities. Finally, we showed that attentional-state dependent modulation on visuomotor memory lasts over a day. Thus, we demonstrate a novel attentional state-dependent mechanism mediating visuomotor memory formation and recall.