Effort-based decision-making in major depressive disorder: A translational model of motivational anhedonia.
2012/07/09 by Michael T. Treadway, Nicholas A. Bossaller, Richard C. Shelton +1 · 742 citations
Neuroscience · Psychology · #Anhedonia #Anticipation (artificial intelligence) #Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes #Clinical psychology #Cognitive psychology #Developmental psychology #Functional Brain Connectivity Studies #Major depressive disorder #Mental Health Research Topics #Mood #Pleasure #Psychology #Psychotherapist #Task (project management)
paper · open access · doi:10.1037/a0028813
published in Journal of Abnormal Psychology 121(3), 553-558 (American Psychological Association)
openalex publication_date 2012/07/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
Abstract
Anhedonia is a core feature of major depressive disorder (MDD), but the precise nature of anhedonic symptoms is unknown. Whereas anhedonia has traditionally been viewed as a deficit in the experience of pleasure, more recent evidence suggests that reduced anticipation and motivation may also be a core feature of this symptom. Here, we provide data from a study in MDD patients and healthy controls using a translational measure of reward motivation, the Effort Expenditure for Rewards Task (EEfRT or "effort"). This task offers subjects a series of trials where they may choose to expend more or less effort for the opportunity to win varying amounts of monetary rewards. We found that MDD patients were less willing to expend effort for rewards than controls. Additionally, we observed that patients were less able to effectively use information about magnitude and probability of rewards to guide their choice behavior. Finally, within the MDD patient group, duration of the current episode was a significant negative predictor of EEfRT task performance. These findings offer novel support for theoretical models proposing that anhedonia in MDD may reflect specific impairments in motivation and reward-based decision-making.
Citations
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