Participants performed an additional-singleton visual-search task while their eye movements were recorded. Distractor presence followed either high- or low-volatility sequences, and the overall prevalence of distractors remained constant across the two regimes. That difference disappeared when comparisons were matched by position in the run.

The pooled effect was therefore consistent with a structural consequence of the manipulation: high-volatility blocks contained more early-run positions, where capture is intrinsically more frequent. On distractor-absent trials, which isolated the effect of volatility without a competing item, capture showed no detectable difference between regimes. Behavioral differences emerged later in the decision process.

Under high volatility, participants produced longer response times, made more fixations, spent more time dwelling on the final target and committed fewer errors. Target-acquisition latency—the time needed to reach the target—remained unchanged. Together, these observations locate the volatility effect after the first saccade, when observers were deciding whether the available visual evidence justified a response.

The authors evaluated the data with a hierarchical drift-diffusion model and a complementary volatility Kalman-filter model. Both analyses indicated that manual responses contained boundary-related and drift-related structure, linking environmental volatility to the accumulation of evidence and the thresholds used for decision-making. With distractor frequency held constant, the findings support increased response caution rather than a direct change in early oculomotor capture.

The authors describe this pattern as consistent with precision-weighted adjustment to environmental uncertainty. Because the evidence comes from a controlled laboratory task with eye tracking, the study establishes an association within that search paradigm rather than demonstrating how volatility influences decisions in everyday settings.

Subject of Research: How environmental volatility affects oculomotor capture and cautious decisions in visual search

Article Title: Environmental volatility is associated with adaptive caution in visual search

Article References: Qiu, N., Allenmark, F., Chen, S., Müller, H. J., & Shi, Z. (2026). Environmental volatility is associated with adaptive caution in visual search. PLOS Computational Biology, 22(10), e1014310. https://doi.org/10.1371/journal.pcbi.1014310

Image Credits: AI Generated

DOI: 10.1371/journal.pcbi.1014310

Keywords: visual search, environmental volatility, eye tracking, response caution, decision-making, drift-diffusion model, Kalman filtering, oculomotor capture, visual uncertainty, Environmental, volatility, associated