Active search for multiple targets is inefficient

This study examines saccade strategy in a novel task where observers actively search a display to find multiple targets in a limited time. Theory predicts that the relative merit of different saccade strategies 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 close to the optimal strategy, but when the target prior is high and multiple-target trials are frequent, selecting uncertain locations is more informative. The prior probability of the target was varied from 0.17 to 0.67 to determine whether observers adjusted their saccades strategies to maximize information. Observers actively searched a noisy display with six potential target locations. Each location had an independent probability of a target, so the number of targets in a trial ranged from 0 to 6. For all target priors ranging from low to high, a trial-by-trial analysis of saccade strategy indicated that observers made saccades to the most likely target location more often than the most uncertain location. 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 the 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.

► We measured eye movements in a search task with an unknown number of targets in noise. ► Fixations were compared to models that selected the most likely or the most uncertain locations. ► The strategy of selecting uncertain locations was more informative for the multi-target search task. ► A trial-by-trial analysis indicated that observers chose likely locations over uncertain locations. ► Training with informative precues and full feedback did not change saccade strategy.