Literature DB >> 26520256

Chronic motivational state interacts with task reward structure in dynamic decision-making.

Jessica A Cooper1, Darrell A Worthy2, W Todd Maddox3.   

Abstract

Research distinguishes between a habitual, model-free system motivated toward immediately rewarding actions, and a goal-directed, model-based system motivated toward actions that improve future state. We examined the balance of processing in these two systems during state-based decision-making. We tested a regulatory fit hypothesis (Maddox & Markman, 2010) that predicts that global trait motivation affects the balance of habitual- vs. goal-directed processing but only through its interaction with the task framing as gain-maximization or loss-minimization. We found support for the hypothesis that a match between an individual's chronic motivational state and the task framing enhances goal-directed processing, and thus state-based decision-making. Specifically, chronic promotion-focused individuals under gain-maximization and chronic prevention-focused individuals under loss-minimization both showed enhanced state-based decision-making. Computational modeling indicates that individuals in a match between global chronic motivational state and local task reward structure engaged more goal-directed processing, whereas those in a mismatch engaged more habitual processing.
Copyright © 2015 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Decision-making; Motivation; Regulatory fit; Regulatory focus; Reward

Mesh:

Year:  2015        PMID: 26520256      PMCID: PMC4648662          DOI: 10.1016/j.cogpsych.2015.09.001

Source DB:  PubMed          Journal:  Cogn Psychol        ISSN: 0010-0285            Impact factor:   3.468


  35 in total

1.  Multiple model-based reinforcement learning.

Authors:  Kenji Doya; Kazuyuki Samejima; Ken-ichi Katagiri; Mitsuo Kawato
Journal:  Neural Comput       Date:  2002-06       Impact factor: 2.026

2.  Regulatory fit and persuasion: transfer from "Feeling Right.".

Authors:  Joseph Cesario; Heidi Grant; E Tory Higgins
Journal:  J Pers Soc Psychol       Date:  2004-03

3.  A computational role for dopamine delivery in human decision-making.

Authors:  D M Egelman; C Person; P R Montague
Journal:  J Cogn Neurosci       Date:  1998-09       Impact factor: 3.225

4.  The Psychophysics Toolbox.

Authors:  D H Brainard
Journal:  Spat Vis       Date:  1997

Review 5.  Mechanisms of motivation-cognition interaction: challenges and opportunities.

Authors:  Todd S Braver; Marie K Krug; Kimberly S Chiew; Wouter Kool; J Andrew Westbrook; Nathan J Clement; R Alison Adcock; Deanna M Barch; Matthew M Botvinick; Charles S Carver; Roshan Cools; Ruud Custers; Anthony Dickinson; Carol S Dweck; Ayelet Fishbach; Peter M Gollwitzer; Thomas M Hess; Derek M Isaacowitz; Mara Mather; Kou Murayama; Luiz Pessoa; Gregory R Samanez-Larkin; Leah H Somerville
Journal:  Cogn Affect Behav Neurosci       Date:  2014-06       Impact factor: 3.282

6.  Disinhibitory psychopathology and delay discounting in alcohol dependence: personality and cognitive correlates.

Authors:  Lyuba Bobova; Peter R Finn; Martin E Rickert; Jesolyn Lucas
Journal:  Exp Clin Psychopharmacol       Date:  2009-02       Impact factor: 3.157

7.  The emotion probe. Studies of motivation and attention.

Authors:  P J Lang
Journal:  Am Psychol       Date:  1995-05

8.  Differential Effects of Regulatory Fit on Category Learning.

Authors:  Lisa R Grimm; Arthur B Markman; W Todd Maddox; Grant C Baldwin
Journal:  J Exp Soc Psychol       Date:  2008-05

9.  Learning in Noise: Dynamic Decision-Making in a Variable Environment.

Authors:  Todd M Gureckis; Bradley C Love
Journal:  J Math Psychol       Date:  2009-06       Impact factor: 2.223

10.  Of goals and habits: age-related and individual differences in goal-directed decision-making.

Authors:  Ben Eppinger; Maik Walter; Hauke R Heekeren; Shu-Chen Li
Journal:  Front Neurosci       Date:  2013-12-24       Impact factor: 4.677

View more
  3 in total

1.  Using Bayesian regression to test hypotheses about relationships between parameters and covariates in cognitive models.

Authors:  Udo Boehm; Helen Steingroever; Eric-Jan Wagenmakers
Journal:  Behav Res Methods       Date:  2018-06

2.  On the importance of avoiding shortcuts in applying cognitive models to hierarchical data.

Authors:  Udo Boehm; Maarten Marsman; Dora Matzke; Eric-Jan Wagenmakers
Journal:  Behav Res Methods       Date:  2018-08

3.  Correct response negativity may reflect subjective value of reaction time under regulatory fit in a speed-rewarded task.

Authors:  Benjamin T Files; Kimberly A Pollard; Ashley H Oiknine; Peter Khooshabeh; Antony D Passaro
Journal:  Psychophysiology       Date:  2021-06-06       Impact factor: 4.016

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.