Abstract
Forming summary representations is important to process complex information. Indeed, numerous studies have shown evidence for efficient computations of statistical summaries such as mean size. Yet few studies have examined how the individual size contributes to the mean size computation. Here, we investigated how attended individual size influenced mean size estimation process. Specifically, we tested if varying individual size attended by either a pre- or post-cue could modulate mean size computation. In each trial, the test set comprising 8 gratings with different sizes and orientations was presented. Participants were asked to report both an individual orientation designated by a cue as well as the mean size of the gratings. One of the gratings with four size levels (size condition) were cued by an arrow either before (pre-cue condition) or after (post-cue condition) the test set. The orientation task performance was statistically above chance with no significant difference between size conditions. This result indicates that attention was successfully allocated to the cued grating. To test how the attended size contributed to the mean size computation, we analyzed the mean size bias by calculating the percentage difference between the reported and actual mean sizes. We found that the estimated mean size got larger as the size of the cued grating increased. However, the systematic trend was different between the cueing conditions. In the pre-cue condition, there was a significant linear trend depending on the attended size whereas the post-cue condition showed a significantly large estimation solely in the largest size condition. The overall results showed that mean size estimation changes systematically as a function of the attended individual size in summary representation. These post- and pre- attentional effects in the present study suggest that mean size is computed based on the representation of individual sizes themselves.
Acknowledgement: This research was supported by the Brain Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (NRF-2017M3C7A1029658).