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Masayoshi Nagai, Patrick J. Bennett, Allison B. Sekuler; Spatiotemporal templates for detecting orientation-defined targets. Journal of Vision 2007;7(8):11. doi: 10.1167/7.8.11.
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© ARVO (1962-2015); The Authors (2016-present)
Using the classification image technique, the present experiments revealed several characteristics of human observers' spatiotemporal templates for the detection of orientation-defined targets. The stimulus consisted of a spatial 5 × 5 array of elements displayed in 5 ( Experiments 1 and 2) or 15 ( Experiment 3) temporal frames. A target was defined by the first- or the second-order characteristics of the textures. In Experiment 1, a target signal was presented across all five frames, and observers typically relied on the most reasonable cues in all five frames for detecting targets. In other words, they used the first-order cue for detecting the first-order target and used the second-order cue for detecting the second-order target. Moreover, the spatial profile for detecting the first-order sustained target was localized at the border of the target area, but that for the second-order sustained target showed broader spatial tuning. Presenting the target in just the third temporal frame, as was done in Experiment 2, changed the temporal profile of the observers' templates in the expected manner: Observers used the first-order cue for the first-order target detection and the second-order cue for the second-order target detection only in the third frame. However, changing the temporal characteristics also affected the kinds of spatial cues that were used to detect a target. For example, the classification images revealed that observers used second-order cues (as well as first-order cues) to detect a first-order target, and there was a trend toward increasing the extent of spatial information used when the temporal information was restricted. In Experiment 3, we found similar results for detecting the first-order flashed target with finer, 15-temporal-frame presentation. Lastly, we showed that the classification image is a useful way to reveal individual differences that are not shown with traditional psychophysical techniques.
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