The diminishing returns of distance: Computational analysis of approach-avoidance behavior under threat of predation

Abstract

Foraging under threat of predation is a paradigmatic scenario involving the interplay between approach and avoidance motivation across species. Previous foraging paradigms in humans have revealed aspects of approach-avoidance behavior and its neural underpinnings, but have generally involved simple choices such as a binary decision to stay or flee. Here, we present results from 40 adult participants who completed the Weighing Opportunity and Loss in Foraging (WOLF) task, a novel two-dimensional foraging context with threat of predation in which participants choose from five possible actions at each turn. We fit computational models in which choices depend on the subjective utility of each option, which itself depends on approach motivation (resource richness) and avoidance motivation (predator distance). Model comparison revealed that an inverse power law model, in which the marginal subjective utility of additional distance from the wolf diminished with wolf distance, outperformed a linear model. Model parameters explained more than 75% of the variance in task performance, mediated by the average resource richness of choices (for the approach-related parameter) and the number of deaths on the task (for the avoidance-related parameters). An exploratory analysis found that self-reported anxious arousal was associated with a more linear relationship between wolf distance and avoidance motivation. The results demonstrate that a behaviorally rich foraging paradigm in which participants select from multiple options at each turn can enable explicit modeling of subjective utilities in the interplay between approach and avoidance motivation. Future work can examine neural underpinnings of complex approach-avoidance behavior and their alteration in mental health disorders.

The authors' abstract, as published at the source. PLoS ONE, 2026 · DOI ↗