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High regularities in eye-movement patterns reveal the dynamics of the visual working memory allocation mechanism
Authors:Kong Xiaohui  Schunn Christian D  Wallstrom Garrick L
Affiliation:Intelligent Systems Program, University of Pittsburgh Department of Psychology, University of Pittsburgh Department of Biomedical Informatics, University of Pittsburgh.
Abstract:With only two to five slots of visual working memory (VWM), humans are able to quickly solve complex visual problems to near optimal solutions. To explain the paradox between tightly constrained VWM and impressively complex human visual problem-solving ability, we propose several principles for dynamic VWM allocation. In particular, we propose that complex visual information is represented in a temporal manner using only a few slots of VWM that include global and local visual chunks. We built a model of human traveling salesman problem solving based on these principles of VWM allocation and tested the model with eye-movement data. Exactly as the model predicted, human eye movements during traveling salesman problem solving have precise quantitative regularities with regard to both the general statistical pattern of attentional fixations and how they vary across individuals with different VWM capacities. Even though VWM capacity is very limited, eye movements dynamically allocate VWM resources to both local and global information, enabling attention to fine details without loss of the big picture.
Keywords:Visual working memory  Complex problem solving  Computational cognitive model  Global visual information processing
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