Abstract
There is a growing literature investigating how rewards influence the planning of saccadic eye movements and the activity of underlying neural mechanisms (for a review see, Trommershauser et al., 2009). Most of these studies reward correct eye movements towards a target at a given location (e.g., Liston and Stone, 2008). Yet, in every day life, rewards are not directly linked to eye movements but rather to a correct perceptual decision and follow-up action. The role of eye movements is to explore the visual scene and maximize the gathering of information for a subsequent perceptual decision. In this context, we investigate how varying the rewards across locations assigned to correct perceptual decisions in a search task influences the planning of human eye movements. We extend the ideal Bayesian searcher (Najemnik & Geisler, 2005) by explicitly including reward structure to: 1) determine the (optimal) fixation sequences that maximize total reward gains; 2) predict the theoretical increase in gains from taking into account reward structure in planning eye movements during search. We show that humans strategize their eye movements to collect more reward. The pattern of human fixations shares many of the properties with the fixations of the ideal reward searcher. Human increases in total gains from using information about the reward structure are also comparable to the benefits in gains of the ideal searcher. Finally, we use theoretical simulations to show that the observed discrepancies between the fixations of humans and the ideal reward searcher do not have major impact in the total collected rewards. Together, the results increase our understanding of how rewards influence optimal and human saccade planning in ecologically valid tasks such as visual search.