RT Journal Article
SR Electronic
T1 Human Visual Search Follows Suboptimal Bayesian Strategy Revealed by a Spatiotemporal Computational Model
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 779652
DO 10.1101/779652
A1 Yunhui Zhou
A1 Yuguo Yu
YR 2020
UL http://biorxiv.org/content/early/2020/02/11/779652.abstract
AB Humans perform sequences of eye movements to search for a target in complex environment, but the efficiency of human search strategy is still controversial. Previous studies showed that humans can optimally integrate information across fixations and determine the next fixation location. However, their models ignored the temporal control of eye movement, ignored the limited human memory capacity, and the model prediction did not agree with details of human eye movement metrics well. Here, we measured the temporal course of human visibility map and recorded the eye movements of human subjects performing a visual search task. We further built a continuous-time eye movement model which considered saccadic inaccuracy, saccadic bias, and memory constraints in the visual system. This model agreed with many spatial and temporal properties of human eye movements, and showed several similar statistical dependencies between successive eye movements. In addition, our model also predicted that the human saccade decision is shaped by a memory capacity of around 8 recent fixations. These results suggest that human visual search strategy is not strictly optimal in the sense of fully utilizing the visibility map, but instead tries to balance between search performance and the costs to perform the task.Author Summary During visual search, how do humans determine when and where to make eye movement is an important unsolved issue. Previous studies suggested that human can optimally use the visibility map to determine fixation locations, but we found that such model didn’t agree with details of human eye movement metrics because it ignored several realistic biological limitations of human brain functions, and couldn’t explain the temporal control of eye movements. Instead, we showed that considering the temporal course of visual processing and several constrains of the visual system could greatly improve the prediction on the spatiotemporal properties of human eye movement while only slightly affected the search performance in terms of median fixation numbers. Therefore, humans may not use the visibility map in a strictly optimal sense, but tried to balance between search performance and the costs to perform the task.