Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions

By Ian Krajbich, Antonio Rangel. Proceedings of the National Academy of Sciences of the United States of America, 2011

681 citations recorded by the source corpus.

Subfields: Applied Psychology, Cognitive Neuroscience, General Decision Sciences

View Paper: https://www.semanticscholar.org/paper/8e128e7d8463a654512234906e66c7901289c5bd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Applied Psychology

1. John A. Clithero
2. Antonio Rangel
3. Colin F. Camerer
4. Roger Ratcliff
5. Gail McKoon
6. Dingchao Lu
7. Philip L. Smith
8. Scott D. Brown

In Cognitive Neuroscience

1. Antonio Rangel
2. John A. Clithero
3. Scott D. Brown
4. Jacob L. Orquin
5. Ian Krajbich
6. Roger Ratcliff
7. Gail McKoon
8. Simone Mueller Loose

In General Decision Sciences

1. Antonio Rangel
2. John A. Clithero
3. Roger Ratcliff
4. Colin F. Camerer
5. Scott D. Brown
6. Philip L. Smith
7. Gail McKoon
8. Milica D. Milosavljević

Citations in the corpus

• Relative visual saliency differences induce sizable bias in consumer choice (2012, background): “…and decision neuroscience suggests that the way in which the brain processes low-level visual and value information might also lead to decision making biases (Krajbich & Rangel, 2011; Krajbich, Armel, & Rangel, 2010; Rangel, Camerer, & Montague, 2008; Shimojo, Simion, Shimojo, & Scheier, 2003).”
• The Computation of Stimulus Values in Simple Choice (2014, methodology): “…choice, that the SV signals use an attention-modulated relative subjective value code, and that these values are integrated using a comparator processes with computational properties that are well-described by the attentional drift-diffusion model (Krajbich and Rangel, 2011; Krajbich et al., 2010).”
• Attention and choice: a review on eye movements in decision making. (2013, background): “Other studies have also found that the first and last fixations are typically shorter than the middle fixations (Krajbich & Rangel, 2011; Krajbich et al., 2010, 2012).”
• Eye Tracking Reveals Processes that Enable Conjoint Choices to Become Increasingly Efficient with Practice (2016, background): “Threshold models arise naturally from decision field theory (Busemeyer and Townsend 1993) and have been applied in marketing (Krajbich and Rangel 2011).”
• The Attentional Drift-Diffusion Model Extends to Simple Purchasing Decisions (2012, methodology): “This mismatch has been consistently observed with the aDDM (Krajbich et al., 2010; Krajbich and Rangel, 2011), is an unavoidable consequence of the procedures used to carry out the simulations, and does not reflect an inherent limitation of the model.”
• Benefits of neuroeconomic modeling: New policy interventions and predictors of preference (2014, background): “Neuroeconomics aims at providing a detailed computational and neurobiological account of the decision-making process that will serve as a foundation for a better understanding of human behavior and well-being (Fehr and Rangel 2011).”
• Diffusion Decision Model: Current Issues and History (2016, positive): “Recent research on value-based decision making has used the attention drift diffusion model [205,206].”
• Using eye-tracking to trace a cognitive process: Gaze behavior during decision making in a natural environment (2013, neutral): “…decision-making literature has incorporated eye movement recordings previously (e.g. Glaholt & Reingold, 2009, 2011; Glaholt, Wu, & Reingold, 2010; Krajbich, Armel and Rangel, 2010; Krajbich & Rangel, 2011; Schotter, Berry, McKenzie & Rayner, 2010; Simion & Shimojo, 2006; Wedell & Senter, 1997).”