Journal
JOURNAL OF EXPERIMENTAL PSYCHOLOGY-GENERAL
Volume 143, Issue 4, Pages 1476-1488Publisher
AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/a0035813
Keywords
decision making; drift rate; decision threshold; pupil; eye tracking
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Funding
- NIH HHS [S10 OD016366] Funding Source: Medline
- NIMH NIH HHS [5T32MH019118-21, T32 MH019118, R01 MH080066, R01 MH080066-01] Funding Source: Medline
- Division Of Behavioral and Cognitive Sci
- Direct For Social, Behav & Economic Scie [1125788] Funding Source: National Science Foundation
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Can you predict what people are going to do just by watching them? This is certainly difficult: it would require a clear mapping between observable indicators and unobservable cognitive states. In this report, we demonstrate how this is possible by monitoring eye gaze and pupil dilation, which predict dissociable biases during decision making. We quantified decision making using the drift diffusion model (DDM), which provides an algorithmic account of how evidence accumulation and response caution contribute to decisions through separate latent parameters of drift rate and decision threshold, respectively. We used a hierarchical Bayesian estimation approach to assess the single trial influence of observable physiological signals on these latent DDM parameters. Increased eye gaze dwell time specifically predicted an increased drift rate toward the fixated option, irrespective of the value of the option. In contrast, greater pupil dilation specifically predicted an increase in decision threshold during difficult decisions. These findings suggest that eye tracking and pupillometry reflect the operations of dissociated latent decision processes.
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