Literature DB >> 16920074

Alterations in reward-related decision making in boys with recent and future depression.

Erika E Forbes1, Daniel S Shaw, Ronald E Dahl.   

Abstract

BACKGROUND: Altered reward processing is postulated to be a feature of depression. Reward processing may be valuable to understanding early-onset depressive disorders, which tend to be chronic and recurrent.
METHODS: Reward-related decision making was examined within a longitudinal study of 221 11-year-old boys, 25 of whom had a depressive disorder at age 10 or 11. Participants completed a behavioral decision-making task involving varying probability and magnitude of obtaining reward.
RESULTS: Under conditions involving a high probability of winning, boys with depression failed to distinguish between options involving small or large possible reward. Boys with anxiety or externalizing disorders at age 10 or 11 did not differ from others in their reward-related decisions. Low frequency of choosing the high-probability, large reward option at age 11 predicted depressive disorders, anxiety disorders, and depressive symptoms 1 year later. Furthermore, reward-related decisions predicted later depressive or anxiety disorders even when adjusting for the continuity of such disorders and the presence of concurrent externalizing disorders.
CONCLUSIONS: Findings are consistent with affective neuroscience models of altered reward processing and diminished positive affect in depression. This study represents a step toward elucidating the motivational and emotional aspects of early-onset depression.

Entities:  

Mesh:

Year:  2006        PMID: 16920074     DOI: 10.1016/j.biopsych.2006.05.026

Source DB:  PubMed          Journal:  Biol Psychiatry        ISSN: 0006-3223            Impact factor:   13.382


  80 in total

1.  Neural reactivity to monetary rewards and losses differentiates social from generalized anxiety in children.

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2.  Positive Affect Stimulation and Sustainment (PASS) Module for Depressed Mood: A preliminary investigation of treatment-related effects.

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3.  Effort-based decision-making in major depressive disorder: a translational model of motivational anhedonia.

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4.  Neuroeconomics for the study of social cognition in adolescent depression.

Authors:  William Mellick; Carla Sharp; Monique Ernst
Journal:  Clin Psychol (New York)       Date:  2015-09-25

5.  Developmental trajectories of positive and negative affect in children at high and low familial risk for depressive disorder.

Authors:  Thomas M Olino; Nestor L Lopez-Duran; Maria Kovacs; Charles J George; Amy L Gentzler; Daniel S Shaw
Journal:  J Child Psychol Psychiatry       Date:  2010-10-06       Impact factor: 8.982

6.  The role of HIV infection, cognition, and depression in risky decision-making.

Authors:  April D Thames; Vanessa Streiff; Sapna M Patel; Stella E Panos; Steven A Castellon; Charles H Hinkin
Journal:  J Neuropsychiatry Clin Neurosci       Date:  2012       Impact factor: 2.198

Review 7.  A systems neuroscience approach to the pathophysiology of pediatric mood and anxiety disorders.

Authors:  Wan-Ling Tseng; Ellen Leibenluft; Melissa A Brotman
Journal:  Curr Top Behav Neurosci       Date:  2014

8.  Reward-related decision-making in pediatric major depressive disorder: an fMRI study.

Authors:  Erika E Forbes; J Christopher May; Greg J Siegle; Cecile D Ladouceur; Neal D Ryan; Cameron S Carter; Boris Birmaher; David A Axelson; Ronald E Dahl
Journal:  J Child Psychol Psychiatry       Date:  2006-10       Impact factor: 8.982

9.  Reduced reward learning predicts outcome in major depressive disorder.

Authors:  Elske Vrieze; Diego A Pizzagalli; Koen Demyttenaere; Titia Hompes; Pascal Sienaert; Peter de Boer; Mark Schmidt; Stephan Claes
Journal:  Biol Psychiatry       Date:  2012-12-08       Impact factor: 13.382

10.  Perturbed reward processing in pediatric bipolar disorder: an antisaccade study.

Authors:  Sven C Mueller; Pamela Ng; Veronica Temple; Michael G Hardin; Daniel S Pine; Ellen Leibenluft; Monique Ernst
Journal:  J Psychopharmacol       Date:  2010-01-15       Impact factor: 4.153

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