title: Value-based decision-making battery: A Bayesian adaptive approach to assess impulsive and risky behavior.
abstract: Using simple mathematical models of choice behavior, we present a Bayesian adaptive algorithm to assess measures of impulsive and risky decision making. Practically, these measures are characterized by discounting rates and are used to classify individuals or population groups, to distinguish unhealthy behavior, and to predict developmental courses. However, a constant demand for improved tools to assess these constructs remains unanswered. The algorithm is based on trial-by-trial observations. At each step, a choice is made between immediate (certain) and delayed (risky) options. Then the current parameter estimates are updated by the likelihood of observing the choice, and the next offers are provided from the indifference point, so that they will acquire the most informative data based on the current parameter estimates. The procedure continues for a certain number of trials in order to reach a stable estimation. The algorithm is discussed in detail for the delay discounting case, and results from decision making under risk for gains, losses, and mixed prospects are also provided. Simulated experiments using prescribed parameter values were performed to justify the algorithm in terms of the reproducibility of its parameters for individual assessments, and to test the reliability of the estimation procedure in a group-level analysis. The algorithm was implemented as an experimental battery to measure temporal and probability discounting rates together with loss aversion, and was tested on a healthy participant sample.
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
authors.forename: Shakoor
authors.initials: S
authors.lastname: Pooseh
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
authors.forename: Nadine
authors.initials: N
authors.lastname: Bernhardt
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany.|Escuela de Matemática, Universidad de Costa Rica, Ciudad universitaria Rodrigo Facio Brenes, Costa Rica.
authors.forename: Alvaro
authors.initials: A
authors.lastname: Guevara
authors.affiliation: Translational Neuromodeling Unit, Hospital of Psychiatry, University of Zürich and Swiss Federal Institute of Technology, Zurich, Switzerland.|Psychiatry, Psychosomatics, and Psychotherapy, University of Zürich, Zurich, Switzerland.
authors.forename: Quentin J M
authors.initials: QJM
authors.lastname: Huys
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany. michael.smolka@tu-dresden.de.
authors.forename: Michael N
authors.initials: MN
authors.lastname: Smolka
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D000067289:Behavior Observation Techniques / Q000379:methods*; D002755:Choice Behavior; D003657:Decision Making; D065786:Delay Discounting; D006801:Humans; D007175:Impulsive Behavior; D008297:Male; D015203:Reproducibility of Results
keywords: Bayesian estimation; Delay discounting; Intertemporal choice; Loss aversion; Risk seeking