Using computer games to explore foraging-predation trade-offs and spatial learning in humans

Foraging requires organisms to balance energetic gains against multiple costs, including predation risk, while updating decisions as conditions change. Although these processes are well studied in animals, ecologically grounded paradigms for testing behavioural updating and cross-task generalization in humans remain limited. We developed two computer-game assays inspired by animal foraging research to examine how humans adjust behaviour under simulated predation risk, whether prior risk exposure affects later decisions and whether spatial performance generalizes across tasks. Participants completed a central-place open-field foraging task under safe and risky conditions and a maze-navigation task assessing spatial learning. Predation risk reduced foraging effort and increased hiding behaviour. Behavioural responses also depended on task order: individuals exposed to risk first showed attenuated shifts across contexts, indicating carryover effects and incomplete updating of environmental state. Spatial performance generalized across tasks under both safe and risky contexts. In the maze task, performance improved across trials with a negatively accelerated learning curve, consistent with spatial learning dynamics. These findings show that ecologically grounded computer games can reveal imperfect updating under changing risk while providing a controlled framework for studying human decision-making under ecological constraints.