The Drift Diffusion Model can account for the accuracy and reaction time of value-based choices under high and low time pressure

By Milica D. Milosavljević, Jonathan Malmaud, Alexander G. Huth, Christof Koch, Antonio Rangel. Judgment and Decision Making, 2010

344 citations recorded by the source corpus.

An important open problem is how values are compared to make simple choices. A natural hypothesis is that the brain carries out the computations associated with the value comparisons in a manner consistent with the Drift Diffusion Model (DDM), since this model has been able to account for a large amount of data in other domains. We investigated the ability of four different versions of the DDM to explain the data in a real binary food choice task under conditions of high and low time pressure. We found that a seven-parameter version of the DDM can account for the choice and reaction time data with high-accuracy, in both the high and low time pressure conditions. The changes associated with the introduction of time pressure could be traced to changes in two key model parameters: the barrier height and the noise in the slope of the drift process.

Subfields: Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/48b22d9c7e9c538e56dd413e1c78c4b1e010af18

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In Cognitive Neuroscience

Citations in the corpus

An Introduction to Model-Based Cognitive Neuroscience (2015, methodology): “Here are four course books on cognitive modeling, take your pick: Lewandowsky and Farrell [66], Busemeyer and Diederich [67], Hunt [68], and Polk and Seifert [69].”
Rethinking fast and slow based on a critique of reaction time reverse inference (2015, unknown): “In the realm of value-based choice, decision problems involving similar options tend to take a large amount of time, while choices between dissimilar options generally take less time 26,29,30,33,35 .”
The Attentional Drift-Diffusion Model Extends to Simple Purchasing Decisions (2012, methodology): “Keywords: drift-diffusion, decision-making, neuroeonomics, decision neuroscience, eye-tracking, valuation, choice, purchasing”
The Computation of Stimulus Values in Simple Choice (2014, methodology): “…description of the choice and reaction time curves generated by simple choice Common psychometric choice curveCommon choice environment(A) (B) NEUROECONOMICS tasks (Basten et al., 2010; Gluth et al., 2012; Krajbich and Rangel, 2011; Krajbich et al., 2010, 2012; Milosavljevic et al., 2010).”
Multialternative drift-diffusion model predicts the relationship between visual fixations and choice in value-based decisions (2011, methodology): “Even in the binary choice case, there are many variations to the DDM that have been proposed in the literature (9, 17, 27, 42).”
Diffusion Decision Model: Current Issues and History (2016, background): “Note that there are other ways of producing fast or slow errors (relative to correct responses) such as collapsing bounds (discussed later), but few of these have received extensive testing [41].”