Cited by 289Decision-Making and Behavioral EconomicsNeural and Behavioral Psychology StudiesGaze Tracking and Assistive Technology

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Eye tracking and pupillometry are indicators of dissociable latent decision processes.

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Cavanagh, James F., Wiecki, Thomas V., Kochar, Angad, Frank, Michael J.·2014·Journal of Experimental Psychology: General

DOI 10.1037/a0035813PMC PMC4114997

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Abstract

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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Authors: Cavanagh, J. F., Wiecki, T. V., Kochar, A., & Frank, M. J.
Affiliations: Brown University (US)
ORCID: Cavanagh, James F.
Wiecki, Thomas V.
Kochar, Angad
Frank, Michael J.
Venue: Journal of Experimental Psychology: General
Publisher: American Psychological Association (APA)
Published: 2014
Volume: 143
Issue: 4
Pages: 1476-1488
ISSN: 0096-3445 (ISSN-L)
1939-2222
DOI: 10.1037/a0035813
PMC: PMC4114997
OpenAlex: W2132578666
Cited by: 289
References: 58
Citations by year: 2026: 23 · 2025: 24 · 2024: 22 · 2023: 22 · 2022: 27 · 2021: 36 · 2020: 31 · 2019: 29 · 2018: 21 · 2017: 23 · 2016: 20 · 2015: 7 · 2014: 4
FWCI: 16.42
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Locations: Journal of Experimental Psychology General (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health (5T32MH019118-21 and RO1 MH080066-01)
National Science Foundation (1125788)
Topics: Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
Keywords: eye tracking, pupillometry, decision-making, drift-diffusion model, drift rate, decision threshold, response caution, evidence accumulation, pupil dilation, hierarchical Bayesian estimation
MeSH terms: Attention, Computer Simulation, Conflict, Psychological, Decision Making, Eye Movements, Female, Humans, Male, Models, Psychological, Pupil, Eye Movement Measurements, Young Adult

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Eye tracking and pupillometry are indicators of dissociable latent decision processes.

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