Author:
Wagner Ilja,Henare Dion,Tünnermann Jan,Schubö Anna,Schütz Alexander C.
Abstract
AbstractTo interact with one’s environment, relevant objects have to be selected as targets for saccadic eye movements. Previous studies have demonstrated that factors such as visual saliency and reward influence saccade target selection, and that humans can dynamically trade off these factors to maximize expected value during visual search. However, expected value in everyday situations not only depends on saliency and reward, but also on the required time to find objects, and the likelihood of a successful object-interaction after search. Here we studied whether search costs and the accuracy to discriminate an object feature can be traded off to maximize expected value. We designed a combined visual search and perceptual discrimination task, where participants chose whether to search for an easy- or difficult-to-discriminate target in search displays populated by distractors that shared features with either the easy or the difficult target. Participants received a monetary reward for correct discriminations and were given limited time to complete as many trials as they could. We found that participants considered their discrimination performance and the search costs when choosing targets and, by this, maximized expected value. However, the accumulated reward was constrained by noise in both the choice of which target to search for, and which elements to fixate during search. We conclude that humans take into account the prospective search time and the likelihood of successful a object-interaction, when deciding what to search for. However, search performance is constrained by noise in decisions about what to search for and how to search for it.
Funder
H2020 European Research Council
Deutsche Forschungsgemeinschaft
Publisher
Springer Science and Business Media LLC
Subject
Linguistics and Language,Sensory Systems,Language and Linguistics,Experimental and Cognitive Psychology
Cited by
1 articles.
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1. Good-enough attentional guidance;Trends in Cognitive Sciences;2023-04