Environmental volatility is associated with adaptive caution in visual search

Nan Qiu, Fredrik Allenmark, Siyi Chen, Hermann J Müller and Zhuanghua Shi

PLOS Computational Biology, 2026, vol. 22, issue 10, 1-20

Abstract: Real-world distractors occur in environments whose states change at different rates. We asked whether such volatility alters initial overt oculomotor allocation, later target verification and response commitment, or both. Observers performed an additional-singleton search task with concurrent eye tracking while distractor presence followed high- or low-volatility sequences, with overall distractor prevalence held constant. Trial-pooled oculomotor capture was higher under high volatility, a pattern that appears to indicate altered filtering. Matching the same-location run position removed that difference, with no detectable difference in capture across volatility regimes at matched run position. The pooled capture effect was therefore consistent with a structural consequence of the volatility manipulation, which enriched high-volatility blocks with early-run positions where capture is intrinsically high. The volatility effect itself appeared on distractor-absent trials. Under high volatility, response times were longer, fixations more frequent, final-target dwell longer, and errors fewer, while target-acquisition latency itself was unchanged. Same-location repetition learning showed no detectable difference in slope across regimes. A hierarchical drift-diffusion model (DDM) and a complementary volatility Kalman-filter (VKF) comparison converged in showing that manual responses carried both boundary-related and drift-related structure. With distractor frequency held constant, the per-trial effect of volatility therefore emerged after the first saccade as an increase in response caution rather than in oculomotor capture. This pattern is consistent with precision-weighted adjustment to environmental uncertainty.Author summary: Visual environments differ not only in how often distracting objects appear but also in how frequently their presence changes. We asked whether this volatility changes what first captures the eyes or how carefully people inspect a scene before they respond. Participants searched for a tilted target while an irrelevant tilted distractor appeared in either rapidly changing or more stable sequences, with its frequency held constant. In the rapidly changing sequence, the first eye movement was directed toward the distractor more often. However, this difference followed from the sequences themselves because rapid change produced more trials on which the distractor had moved to a new location, where it was most likely to attract the first eye movement. Once we compared trials with the same repetition history, the first eye movement no longer differed between the two environments. The volatility effect appeared later, on trials without a distractor. In the rapidly changing environment, participants made more saccades, inspected the target for longer, responded more slowly, and made fewer errors. Computational models pointed the same way: people accumulated evidence more slowly and required more of it before committing. Volatility thus made observers more cautious without measurably changing what first captured their gaze.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1014310

DOI: 10.1371/journal.pcbi.1014310

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