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Title
Gaze bias differences capture individual choice behaviour
Authors
Keywords
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Journal
Nature Human Behaviour
Volume 3, Issue 6, Pages 625-635
Publisher
Springer Science and Business Media LLC
Online
2019-04-16
DOI
10.1038/s41562-019-0584-8
References
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Related references
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- Finding the right fit: A comparison of process assumptions underlying popular drift-diffusion models.
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- Gaze data reveal distinct choice processes underlying model-based and model-free reinforcement learning
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- Biasing moral decisions by exploiting the dynamics of eye gaze
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- Testing necessary regional frontal contributions to value assessment and fixation-based updating
- (2015) Avinash R. Vaidya et al. Nature Communications
- Simultaneous modeling of visual saliency and value computation improves predictions of economic choice
- (2013) R. B. Towal et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- HDDM: Hierarchical Bayesian estimation of the Drift-Diffusion Model in Python
- (2013) Thomas V. Wiecki et al. Frontiers in Neuroinformatics
- Salience driven value integration explains decision biases and preference reversal
- (2012) K. Tsetsos et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions
- (2011) I. Krajbich et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Visual fixations and the computation and comparison of value in simple choice
- (2010) Ian Krajbich et al. NATURE NEUROSCIENCE
- Individual differences, aging, and IQ in two-choice tasks
- (2009) Roger Ratcliff et al. COGNITIVE PSYCHOLOGY
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