When confronted with many visual items, people can compute their variability accurately and rapidly, which facilitates efficient information processing and optimal decision making. However, how the visual system computes variability is still unclear. To investigate this, we implemented situations whereby estimates of variability based on several possible variability measures (e.g., range, standard deviation, and weighted standard deviation) could be differentiated, and then examined which best accounted for human variability perception. In three psychophysical experiments, participants watched two arrays of items with various orientations and judged which had more variable orientations. Results showed that perceived variability was most consistent with the weighted standard deviation based on the reliability of individual items. Specifically, participants gave less consideration to deviant orientations that were likely to be outliers, and greater consideration to salient orientations that were likely to be encoded precisely. This reliability-based weighted standard deviation suggests an efficient and flexible way of representing visual variability.
Bibliographical noteFunding Information:
This research was supported by the Brain Research Program of National Research Foundation (NRF) funded by the Korean government (MSIT) (NRF-2017M3C7A1029658). All of the data were presented at the 2020 Virtual Vision Sciences Society, and the 2020 Korean Society for Cognitive and Biological Psychology. All data were included in Jinhyeok Jeong’s master’s thesis. The raw data for all the experiments are available on the Open Science Framework (https://osf.io/a7q3d/).
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All Science Journal Classification (ASJC) codes
- Sensory Systems