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Preeti Verghese; Active search for multiple targets is inefficient. Journal of Vision 2010;10(7):1296. doi: https://doi.org/10.1167/10.7.1296.
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© ARVO (1962-2015); The Authors (2016-present)
Rationale: When the task is to find multiple targets in noise in a limited time, saccades need to be efficient to maximize the information gained (Verghese, VSS, 2008). The strategy that is most informative depends on the prior probability of the target at a location: when the target prior is low and multiple-target trials are rare, making a saccade to the most likely target location is informative, but when the target prior is high and multiple-target trials are frequent, selecting uncertain locations is more informative. Do observers adjust their saccade strategy depending on the prior to maximize the information gained?
Methods. Observers actively searched a noisy display with 6 potential target locations equally spaced on a 3° eccentric circle. Each location had an independent probability of a target, so the number of targets in a trial ranged from 0 to 6. The target was a vertical string of 5 dots among noise dots positioned randomly. Observers searched the display for 350, 700 or 1150ms and subsequently selected all potential target locations with a cursor. We varied the prior probability of the target from 0.17 to 0.67 to determine whether observers adjusted their saccades strategies to maximize information. We performed a trial-by-trial analysis of observers' saccades to determine saccade strategy.
Results & Conclusion: Observers (n=5, 3 naïve) made saccades to the most likely target location more often than the most uncertain location, for all target priors ranging from low to high. Fixating likely locations is efficient only when multiple targets are rare, as in the case of a low target prior, or in the case of more standard single-target search task. Yet it is the preferred saccade strategy in all our conditions, even when multiple targets are frequent. These findings indicate that humans are far from ideal searchers in multiple-target search.
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