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Hee Yeon Im, Sang Chul Chong; How many mean sizes can we represent?. Journal of Vision 2008;8(6):873. doi: https://doi.org/10.1167/8.6.873.
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© ARVO (1962-2015); The Authors (2016-present)
The current study investigated how many mean sizes one could extract in multiple sets. We presented two to five sets of five different sizes in a display. Each set was defined by different colors. In Experiment 1, the display presented for 250 ms and was immediately followed by the probe display in which two randomly chosen colors from the previous display were presented. The participants had to compare which probed set had larger mean size. Participants' performance decreased as the number of sets increased. However, their performance remained above chance even when the number of sets was five. Furthermore, when we separately analyzed the largest mean-size pairs, the effect of set size disappeared. In Experiment 2, we increased the ISI to 1 second and found that this delay did not affect participants' performance. In Experiment 3, we added a pre-cue condition to investigate why the performance dropped as the set size increased. Participants' accuracy was higher in the pre-cue condition than in the post-cue condition. Their accuracy decreased as the set size increased in the post-cue condition, whereas it remained the same in the pre-cue condition. However, when we selected only the largest mean-size pairs, there was no difference between the pre-cue and the post-cue condition. These results suggest that the effect of set size observed in all three experiments may be due to the difficulty of selection, rather than the capacity of visual system. In other words, when the selection was easy as in the largest mean-size pairs, participants' performance did not decrease as the set size increased. Our results suggest that one could simultaneously extract 5 mean sizes accurately and maintain them for 1 second, which is more than the capacity of visual working memory.
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