Model-Based and Model-Free Control Predicts Alcohol Consumption Developmental Trajectory in Young Adults: A 3-Year Prospective Study.


Journal

Biological psychiatry
ISSN: 1873-2402
Titre abrégé: Biol Psychiatry
Pays: United States
ID NLM: 0213264

Informations de publication

Date de publication:
15 05 2021
Historique:
received: 20 07 2020
revised: 21 12 2020
accepted: 17 01 2021
pubmed: 28 3 2021
medline: 3 6 2021
entrez: 27 3 2021
Statut: ppublish

Résumé

A shift from goal-directed toward habitual control has been associated with alcohol dependence. Whether such a shift predisposes to risky drinking is not yet clear. We investigated how goal-directed and habitual control at age 18 predict alcohol use trajectories over the course of 3 years. Goal-directed and habitual control, as informed by model-based (MB) and model-free (MF) learning, were assessed with a two-step sequential decision-making task during functional magnetic resonance imaging in 146 healthy 18-year-old men. Three-year alcohol use developmental trajectories were based on either a consumption score from the self-reported Alcohol Use Disorders Identification Test (assessed every 6 months) or an interview-based binge drinking score (grams of alcohol/occasion; assessed every year). We applied a latent growth curve model to examine how MB and MF control predicted the drinking trajectory. Drinking behavior was best characterized by a linear trajectory. MB behavioral control was negatively associated with the development of the binge drinking score; MF reward prediction error blood oxygen level-dependent signals in the ventromedial prefrontal cortex and the ventral striatum predicted a higher starting point and steeper increase of the Alcohol Use Disorders Identification Test consumption score over time, respectively. We found that MB behavioral control was associated with the binge drinking trajectory, while the MF reward prediction error signal was closely linked to the consumption score development. These findings support the idea that unbalanced MB and MF control might be an important individual vulnerability in predisposing to risky drinking behavior.

Sections du résumé

BACKGROUND
A shift from goal-directed toward habitual control has been associated with alcohol dependence. Whether such a shift predisposes to risky drinking is not yet clear. We investigated how goal-directed and habitual control at age 18 predict alcohol use trajectories over the course of 3 years.
METHODS
Goal-directed and habitual control, as informed by model-based (MB) and model-free (MF) learning, were assessed with a two-step sequential decision-making task during functional magnetic resonance imaging in 146 healthy 18-year-old men. Three-year alcohol use developmental trajectories were based on either a consumption score from the self-reported Alcohol Use Disorders Identification Test (assessed every 6 months) or an interview-based binge drinking score (grams of alcohol/occasion; assessed every year). We applied a latent growth curve model to examine how MB and MF control predicted the drinking trajectory.
RESULTS
Drinking behavior was best characterized by a linear trajectory. MB behavioral control was negatively associated with the development of the binge drinking score; MF reward prediction error blood oxygen level-dependent signals in the ventromedial prefrontal cortex and the ventral striatum predicted a higher starting point and steeper increase of the Alcohol Use Disorders Identification Test consumption score over time, respectively.
CONCLUSIONS
We found that MB behavioral control was associated with the binge drinking trajectory, while the MF reward prediction error signal was closely linked to the consumption score development. These findings support the idea that unbalanced MB and MF control might be an important individual vulnerability in predisposing to risky drinking behavior.

Identifiants

pubmed: 33771349
pii: S0006-3223(21)00076-7
doi: 10.1016/j.biopsych.2021.01.009
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

980-989

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2021 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Auteurs

Hao Chen (H)

Department of Psychiatry, Technische Universität Dresden, Dresden, Germany; Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.

Negin Mojtahedzadeh (N)

Department of Psychiatry, Technische Universität Dresden, Dresden, Germany; Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.

Matthew J Belanger (MJ)

Department of Psychiatry, Technische Universität Dresden, Dresden, Germany; Neuroimaging Center, Technische Universität Dresden, Dresden, Germany.

Stephan Nebe (S)

Department of Psychiatry, Technische Universität Dresden, Dresden, Germany; Neuroimaging Center, Technische Universität Dresden, Dresden, Germany; Zurich Center for Neuroeconomics, Department of Economics, University of Zurich, Zurich, Switzerland.

Sören Kuitunen-Paul (S)

Institute of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany; Department of Child and Adolescent Psychiatry, Technische Universität Dresden, Dresden, Germany.

Miriam Sebold (M)

Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Maria Garbusow (M)

Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Quentin J M Huys (QJM)

Division of Psychiatry, University College London, London, United Kingdom; Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.

Andreas Heinz (A)

Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.

Michael A Rapp (MA)

Area of Excellence Cognitive Sciences, University of Potsdam, Potsdam, Germany.

Michael N Smolka (MN)

Department of Psychiatry, Technische Universität Dresden, Dresden, Germany; Neuroimaging Center, Technische Universität Dresden, Dresden, Germany. Electronic address: michael.smolka@tu-dresden.de.

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