title: Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions.
abstract: Sequential sampling models assume that people make speeded decisions by gradually accumulating noisy information until a threshold of evidence is reached. In cognitive science, one such model--the diffusion decision model--is now regularly used to decompose task performance into underlying processes such as the quality of information processing, response caution, and a priori bias. In the cognitive neurosciences, the diffusion decision model has recently been adopted as a quantitative tool to study the neural basis of decision making under time pressure. We present a selective overview of several recent applications and extensions of the diffusion decision model in the cognitive neurosciences.
authors.affiliation: Amsterdam Brain and Cognition Center, University of Amsterdam, 1018 WS Amsterdam, The Netherlands; email: buforstmann@gmail.com.
authors.forename: B U
authors.initials: BU
authors.lastname: Forstmann
authors.affiliation: Department of Psychology, Ohio State University, Columbus, Ohio 43210.
authors.forename: R
authors.initials: R
authors.lastname: Ratcliff
authors.affiliation: Department of Methodology, University of Amsterdam, 1018 WV Amsterdam, The Netherlands.
authors.forename: E-J
authors.initials: EJ
authors.lastname: Wagenmakers
mesh_terms: D000066494:Cognitive Neuroscience; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D008960:Models, Psychological; D011930:Reaction Time / Q000502:physiology; D013647:Task Performance and Analysis
keywords: decision making; diffusion decision model; drift rate; information accumulation; response time; speed-accuracy trade-off