16:30 - 18:00
Parallel sessions 6
16:30 - 18:00
Room: C-Building - N14
Chair/s:
Jan Tünnermann, Iris Wiegand
In visual foraging, people search continuously for multiple targets across space and time. Perceptual, attentional, and decision-making processes act together to efficiently collect visual targets from dynamic environments. This symposium addresses how flexibly humans adapt their behaviour in these complex search tasks akin to many real-world search scenarios. Thornton and Kristjánsson will discuss the impact of grouping on “foraging for change” when searching in time-varying environments. Kristjánsson et al. investigate whether cross-modal synchrony cues influence foraging. Sauter and Tünnermann demonstrate how statistical learning guides the discovery of spatiotemporal hotspots in dynamic foraging tasks, highlighting sensitivity to environmental regularities. Hughes and Clarke present advances in modelling foraging behaviour to capture the dynamics of target selection. Finally, Wiegand shows that a foraging task with memory load can uncover both cognitive impairments, as well as compensatory strategies, in patients with Korsakoff syndrome and alcohol use disorder. Together, these contributions demonstrate how adaptive foraging behaviour emerges in response to the complex demands of dynamic, interactive environments.
Submission 376
Catching Regularities: Statistical Learning of Spatiotemporal Hotspots in Dynamic Foraging Marian Sauter & Jan Tünnermann
SymposiumTalk-03
Presented by: Marian Sauter
Marian Sauter 1, Jan Tünnermann 2
1 Ulm University, Experimental Psychology, Germany
2 Charlotte Fresenius Hochschule, Germany
Adaptive behavior depends on the ability to detect and exploit regularities in the environment. Statistical learning has been shown to shape attentional priority maps in static tasks, but its contribution to active exploration of dynamic environments remains understudied. This study examines how humans learn and adapt to probabilistic structure in a dynamic foraging task. In interactive displays with moving targets and distractors, participants collected conjunction-defined targets that followed biased trajectories. Experiment 1 revealed emergent spatial biases toward high-probability target regions; Experiment 2 demonstrated flexible reweighting after contingency shifts; Experiment 3 (ongoing) tests continuous adaptation to a moving hotspot. The findings advance theories of selection history and predictive control, with statistical learning as a mechanism for adaptive exploration in dynamic environments.