ArticleScientific reports2023
Testing a relational account of search templates in visual foraging.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 6 citations in OpenAlex.
- FoMo: A unifying theory of visual foraging.PLoS computational biology · 2026Article
- Generative modelling of continuous feature foraging reveals probabilistic representations of target distributions.Attention, perception & psychophysics · 2026Article
- Attention directs actions in visual foraging.Scientific reports · 2025Article
- No matter what you do, travel is travel in visual foraging.Vision research · 2024Article
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3 authors at 1 institution in 1 country.
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Abstract
Search templates guide human visual attention toward relevant targets. Templates are often seen as encoding exact target features, but recent studies suggest that templates rather contain "relational properties" (e.g., they facilitate "redder" stimuli instead of specific hues of red). Such relational guidance seems helpful in naturalistic searches where illumination or perspective renders exact feature values unreliable. So far relational guidance has only been demonstrated in rather artificial single-target search tasks with briefly flashed displays. Here, we investigate whether relational guidance also occurs when humans interact with the search environment for longer durations to collect multiple target elements. In a visual foraging task, participants searched for and collected multiple targets among distractors of different relationships to the target colour. Distractors whose colour differed from the environment in the same direction as the targets reduced foraging efficiency to the same amount as distractors whose colour matched the target colour. Distractors that differed by the same colour distance but in the opposite direction of the target colour did not reduce efficiency. These findings provide evidence that search templates encode relational target features in naturalistic search tasks and suggest that attention guidance based on relational features is a common mode in dynamic, real-world search environments.
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