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Poster B in Poster Session B: Tuesday, August 4, 2:00 – 3:45 pm, Kimmel Center, Shorin & Rosenthal Rooms

Serial Dependence in Value-based Decisions Is Gated by Uncertainty

Ling Huang¹, Hui-Kuan Chung², Hsin-Hung Li¹; ¹Ohio State University, Columbus, ²University of Zurich

Presenter: Ling Huang

Human decisions are systematically influenced by recent history, a phenomenon known as serial dependence. Theories from the perceptual domain suggest that serial dependence reflects Bayesian integration of past experience and current input by their respective uncertainty. Here, we test the hypothesis that serial dependence in subjective preference-based valuation is governed by a similar computational process. Participants performed a value estimation task with trial-wise uncertainty reports. We observed an attractive bias, with current valuations drawn toward those of the previous trial. Critically, this serial dependence was modulated by the relative uncertainty between trials, consistent with the predictions of a Bayesian integration model. Neural uncertainty decoded from fMRI activity in the prefrontal cortex predicted this modulation. These results provide behavioral and neural evidence for Bayesian integration over time in preference-based valuation.

Topic Area: Decision-Making, Cognitive Control & Event Cognition