Literature DB >> 23658007

Constraints on decision making: implications from genetics, personality, and addiction.

Travis E Baker1, Tim Stockwell, Clay B Holroyd.   

Abstract

An influential neurocomputational theory of the biological mechanisms of decision making, the "basal ganglia go/no-go model," holds that individual variability in decision making is determined by differences in the makeup of a striatal system for approach and avoidance learning. The model has been tested empirically with the probabilistic selection task (PST), which determines whether individuals learn better from positive or negative feedback. In accordance with the model, in the present study we examined whether an individual's ability to learn from positive and negative reinforcement can be predicted by genetic factors related to the midbrain dopamine system. We also asked whether psychiatric and personality factors related to substance dependence and dopamine affect PST performance. Although we found characteristics that predicted individual differences in approach versus avoidance learning, these observations were qualified by additional findings that appear inconsistent with the predictions of the go/no-go model. These results highlight a need for future research to validate the PST as a measure of basal ganglia reward learning.

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Year:  2013        PMID: 23658007     DOI: 10.3758/s13415-013-0164-8

Source DB:  PubMed          Journal:  Cogn Affect Behav Neurosci        ISSN: 1530-7026            Impact factor:   3.526


  93 in total

Review 1.  Anatomy of a decision: striato-orbitofrontal interactions in reinforcement learning, decision making, and reversal.

Authors:  Michael J Frank; Eric D Claus
Journal:  Psychol Rev       Date:  2006-04       Impact factor: 8.934

2.  MENDELIAN PROPORTIONS IN A MIXED POPULATION.

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Journal:  Science       Date:  1908-07-10       Impact factor: 47.728

3.  Personality traits are differentially associated with patterns of reward and novelty processing in the human substantia nigra/ventral tegmental area.

Authors:  Ruth M Krebs; Björn H Schott; Emrah Düzel
Journal:  Biol Psychiatry       Date:  2008-10-02       Impact factor: 13.382

4.  All Negative Moods Are Not Equal: Motivational Influences of Anxiety and Sadness on Decision Making.

Authors: 
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5.  Orbitofrontal correlates of aggression and impulsivity in psychiatric patients.

Authors:  Ami Sheth Antonucci; David A Gansler; Simon Tan; Rafeeque Bhadelia; Sam Patz; Carl Fulwiler
Journal:  Psychiatry Res       Date:  2006-09-06       Impact factor: 3.222

6.  Evaluation of genetic variability in the dopamine receptor D2 in relation to behavioral inhibition and impulsivity/sensation seeking: an exploratory study with d-amphetamine in healthy participants.

Authors:  Ajna Hamidovic; Andrea Dlugos; Andrew Skol; Abraham A Palmer; Harriet de Wit
Journal:  Exp Clin Psychopharmacol       Date:  2009-12       Impact factor: 3.157

7.  Synonymous mutations in the human dopamine receptor D2 (DRD2) affect mRNA stability and synthesis of the receptor.

Authors:  Jubao Duan; Mark S Wainwright; Josep M Comeron; Naruya Saitou; Alan R Sanders; Joel Gelernter; Pablo V Gejman
Journal:  Hum Mol Genet       Date:  2003-02-01       Impact factor: 6.150

8.  COMT genetic variation affects fear processing: psychophysiological evidence.

Authors:  Christian Montag; Joshua W Buckholtz; Peter Hartmann; Michael Merz; Christian Burk; Juergen Hennig; Martin Reuter
Journal:  Behav Neurosci       Date:  2008-08       Impact factor: 1.912

9.  Understanding decision-making deficits in neurological conditions: insights from models of natural action selection.

Authors:  Michael J Frank; Anouk Scheres; Scott J Sherman
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2007-09-29       Impact factor: 6.237

10.  Assessing the molecular genetics of attention networks.

Authors:  John Fossella; Tobias Sommer; Jin Fan; Yanhong Wu; James M Swanson; Donald W Pfaff; Michael I Posner
Journal:  BMC Neurosci       Date:  2002-10-04       Impact factor: 3.288

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  6 in total

1.  Predicting Attention-Shaping Response in People With Schizophrenia.

Authors:  Danielle M Beaudette; James M Gold; James Waltz; Judy L Thompson; Lindsay Cherneski; Victoria Martin; Brian Monteiro; Lisa N Cruz; Steven M Silverstein
Journal:  J Nerv Ment Dis       Date:  2021-03-01       Impact factor: 2.254

2.  Linking Individual Learning Styles to Approach-Avoidance Motivational Traits and Computational Aspects of Reinforcement Learning.

Authors:  Kristoffer Carl Aberg; Kimberly C Doell; Sophie Schwartz
Journal:  PLoS One       Date:  2016-11-16       Impact factor: 3.240

3.  Effects of dopamine on reinforcement learning and consolidation in Parkinson's disease.

Authors:  John P Grogan; Demitra Tsivos; Laura Smith; Brogan E Knight; Rafal Bogacz; Alan Whone; Elizabeth J Coulthard
Journal:  Elife       Date:  2017-07-10       Impact factor: 8.140

4.  Meditation experience predicts negative reinforcement learning and is associated with attenuated FRN amplitude.

Authors:  Paul Knytl; Bertram Opitz
Journal:  Cogn Affect Behav Neurosci       Date:  2019-04       Impact factor: 3.282

Review 5.  Transition to substance use disorders: impulsivity for reward and learning from reward.

Authors:  Antoinette Poulton; Robert Hester
Journal:  Soc Cogn Affect Neurosci       Date:  2020-11-10       Impact factor: 3.436

6.  Recovering Reliable Idiographic Biological Parameters from Noisy Behavioral Data: the Case of Basal Ganglia Indices in the Probabilistic Selection Task.

Authors:  Yinan Xu; Andrea Stocco
Journal:  Comput Brain Behav       Date:  2021-03-24
  6 in total

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