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Seonggyu Choe, Jongmin Moon, Oh-sang Kwon; Temporal Dynamics of Visual Attention Allocation. Journal of Vision 2018;18(10):1025. doi: 10.1167/18.10.1025.
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© ARVO (1962-2015); The Authors (2016-present)
Visual attention to a specific space and time improves performance on the focused point (Carrasco, et al., 2004; Correa et al., 2005). It is expected that benefits of the focused attention partially spread out to adjacent area in space and time. The performances for spatially adjacent objects indeed improve depending on the distance from the focused location (Downing, 1988). However, the influence of attention on temporally adjacent objects is not known. METHODS: In Experiment 1, we presented a visual countdown from 5 to 1 with one-second interval to focus attention at one second after the countdown. A Gabor-patch appeared after the countdown with inter-stimulus-interval (ISI) randomly selected from nine ISIs between 0.7 and 1.3 sec. Subjects reported the orientation of the Gabor-patch. Contrast threshold was measured for each ISI. In Experiment 2, we repeated the procedure of Experiment 1 with an additional task to report the perceived duration of ISI relative to the countdown interval (one sec) after the orientation judgment task. The bias in time perception was measured to examine the effect of perceived time on visual performance. RESULTS: Contrast thresholds were significantly different across ISI (F(6,84)=9.121,p< 0.001) manifesting the effect of temporal attention. Interestingly, the contrast thresholds for ISIs between 0.7 and 1 sec were virtually constant (slope=-0.0031), whereas the contrast thresholds for ISIs after 1 sec gradually increase (slope=0.0279) showing asymmetric decay of temporal attention and significant difference in the bootstrap test (t(14)=-23.7643,p< 0.001). Results of Experiment 2 show that subjects perceived 1.2 sec as 1 sec implying that the improved performances on shorter ISIs are not due to the biased time perception. CONCLUSIONS: Results show that temporal attention decays faster after the focused point than before unlike spatial attention. A model controls temporal attention based on the conditional probability of future events can explain the results.
Meeting abstract presented at VSS 2018
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