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Poster Session A: Tuesday, August 12, 1:30 – 4:30 pm, de Brug & E‑Hall

Eye-tracking based Bayesian inference for adaptive decision making and planning processes in a dynamic environment

Sanghyun Park¹, Hun S. Choi, Won Mok Shim²; ¹Sung Kyun Kwan University, ²SungKyunKwan University (SKKU)

Presenter: Sanghyun Park

In dynamically evolving environments, effective planning is crucial for guiding decisions toward optimal goals and adjusting them as conditions change. However, the underlying neurocognitive mechanisms of planning remain elusive, as these processes are not directly observable through behavior. Previous studies have largely focused on simplified decision-making tasks, often limited to static environments or single-goal scenarios. Here, we introduce a novel arithmetic paradigm that requires multi-step planning and flexible goal switching in a dynamic, multi-goal context. Using eye tracking data, we estimated the utility of each goal and modeled goal switching in real time using a Bayesian framework, capturing individual differences in how participants integrate new information into decisions. High-performing participants were more likely to adjust their choices based on updated utilities and engaged in forward planning when initial plans became infeasible. Moreover, model-derived goal switching probabilities reliably predicted activity in brain regions associated with reward processing and value-based decision-making. These findings suggest that adaptive goal switching is supported by neurocognitive processes that continuously track the evolving utility of multiple goals.

Topic Area: Reward, Value & Social Decision Making

Extended Abstract: Full Text PDF