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Cary Feria; Attentional prioritizations based on spatial probabilities can be maintained on multiple simultaneously moving objects. Journal of Vision 2009;9(8):251. doi: https://doi.org/10.1167/9.8.251.
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© ARVO (1962-2015); The Authors (2016-present)
Previous research has shown that the visual system prioritizes attention to locations based on the probabilities of a target appearing at those locations. Feria (Perception & Psychophysics, 2008) found that when tracking several moving objects, attention can be prioritized to high-probability locations on the objects, if the observer is informed of the location probabilities. The present study investigates whether prioritizations within moving objects can be learned and maintained over time, if the observer is not given information about the location probabilities. On each trial, observers viewed two long white moving lines. Small gray circular probes appeared briefly on the lines, and observers' performance at detecting the probes was used to measure the distribution of attention. In one block of trials, the probes appeared with probability .9 on the center of each line, and with probability .05 near either of the ends of each line. In another block of trials, probes appeared with probability .9 near one end of each line, with probability .05 on the center of each line, and with probability .05 near the other end of each line. When probes appeared with high probability on the centers of lines, probe detection was much more accurate at centers than near the ends of lines. However, when probes appeared with high probability near one of the ends of each line, accuracy was more similar for centers and ends. These results indicate that the distribution of attention within the objects was biased toward the centers of the objects, but was also affected by spatial probabilities. These findings suggest that observers are capable of learning spatial probability distributions, and prioritizing attention based on these distributions, in multiple independently moving reference frames.
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