scholarly journals Reward and punishment reversal-learning in major depressive disorder.

2020 ◽  
Vol 129 (8) ◽  
pp. 810-823
Author(s):  
Dahlia Mukherjee ◽  
Alexandre L. S. Filipowicz ◽  
Khoi Vo ◽  
Theodore D. Satterthwaite ◽  
Joseph W. Kable
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Reversal Learning ◽  
Major Depressive ◽  
Reward And Punishment

scholarly journals Ventral Striatum Response During Reward and Punishment Reversal Learning in Unmedicated Major Depressive Disorder

2012 ◽  
Vol 169 (2) ◽  
pp. 152-159 ◽  
Author(s):  
Oliver J. Robinson ◽  
Roshan Cools ◽  
Christina O. Carlisi ◽  
Barbara J. Sahakian ◽  
Wayne C. Drevets
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Reversal Learning ◽  
Ventral Striatum ◽  
Major Depressive ◽  
Reward And Punishment

scholarly journals Reward and punishment reversal learning in major depressive disorder

2020 ◽  
Author(s):  
Dahlia Mukherjee ◽  
Alexandre Leo Stephen Filipowicz ◽  
Khoi D. Vo ◽  
Theodore Sattherwaite ◽  
Joe Kable
Keyword(s):  
Major Depressive Disorder ◽  
Reinforcement Learning ◽  
Depressive Disorder ◽  
Computational Modeling ◽  
Reversal Learning ◽  
Performance Metrics ◽  
Learning Task ◽  
Major Depressive ◽  
Learning Rates ◽  
Reward And Punishment

Depression has been associated with impaired reward and punishment processing, but the specific nature of these deficits is less understood and still widely debated. We analyzed reinforcement-based decision-making in individuals diagnosed with major depressive disorder (MDD) to identify the specific decision mechanisms contributing to poorer performance. Individuals with MDD (n = 64) and matched healthy controls (n = 64) performed a probabilistic reversal learning task in which they used feedback to identify which of two stimuli had the highest probability of reward (reward condition) or lowest probability of punishment (punishment condition). Learning differences were characterized using a hierarchical Bayesian reinforcement learning model. While both groups showed reinforcement learning-like behavior, depressed individuals made fewer optimal choices and adjusted more slowly to reversals in both the reward and punishment conditions. Our computational modeling analysis found that depressed individuals showed lower learning rates and, to a lesser extent, lower value sensitivity in both the reward and punishment conditions. Learning rates also predicted depression more accurately than simple performance metrics. These results demonstrate that depression is characterized by a hyposensitivity to positive outcomes, which influences the rate at which depressed individuals learn from feedback, but not a hypersensitivity to negative outcomes as has previously been suggested. Additionally, we demonstrate that computational modeling provides a more precise characterization of the dynamics contributing to these learning deficits, and offers stronger insights into the mechanistic processes affected by depression.

scholarly journals Differential frontal–striatal and paralimbic activity during reversal learning in major depressive disorder and obsessive–compulsive disorder

2009 ◽  
Vol 39 (9) ◽  
pp. 1503-1518 ◽  
Author(s):  
P. L. Remijnse ◽  
M. M. A. Nielen ◽  
A. J. L. M. van Balkom ◽  
G.-J. Hendriks ◽  
W. J. Hoogendijk ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Obsessive Compulsive Disorder ◽  
Reversal Learning ◽  
Anterior Insula ◽  
Healthy Controls ◽  
Obsessive Compulsive ◽  
Major Depressive ◽  
Compulsive Disorder ◽  
Imaging Results

BackgroundSeveral lines of research suggest a disturbance of reversal learning (reward and punishment processing, and affective switching) in patients with major depressive disorder (MDD). Obsessive–compulsive disorder (OCD) is also characterized by abnormal reversal learning, and is often co-morbid with MDD. However, neurobiological distinctions between the disorders are unclear. Functional neuroimaging (activation) studies comparing MDD and OCD directly are lacking.MethodTwenty non-medicated OCD-free patients with MDD, 20 non-medicated MDD-free patients with OCD, and 27 healthy controls performed a self-paced reversal learning task in an event-related design during functional magnetic resonance imaging (fMRI).ResultsCompared with healthy controls, both MDD and OCD patients displayed prolonged mean reaction times (RTs) but normal accuracy. In MDD subjects, mean RTs were correlated with disease severity. Imaging results showed MDD-specific hyperactivity in the anterior insula during punishment processing and in the putamen during reward processing. Moreover, blood oxygen level-dependent (BOLD) responses in the dorsolateral prefrontal cortex (DLPFC) and the anterior PFC during affective switching showed a linear decrease across controls, MDD and OCD. Finally, the OCD group showed blunted responsiveness of the orbitofrontal (OFC)–striatal loop during reward, and in the OFC and anterior insula during affective switching.ConclusionsThis study shows frontal–striatal and (para)limbic functional abnormalities during reversal learning in MDD, in the context of generic psychomotor slowing. These data converge with currently influential models on the neuropathophysiology of MDD. Moreover, this study reports differential neural patterns in frontal–striatal and paralimbic structures on this task between MDD and OCD, confirming previous findings regarding the neural correlates of deficient reversal learning in OCD.

Early change in reward and punishment sensitivity as a predictor of response to antidepressant treatment for major depressive disorder: a CAN-BIND-1 report

2018 ◽  
Vol 49 (10) ◽  
pp. 1629-1638 ◽  
Author(s):  
Timothy A. Allen ◽  
Raymond W. Lam ◽  
Roumen Milev ◽  
Sakina J. Rizvi ◽  
Benicio N. Frey ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Antidepressant Treatment ◽  
Reward Processing ◽  
Reward Sensitivity ◽  
Major Depressive ◽  
Early Change ◽  
Symptoms Of Depression ◽  
Punishment Sensitivity ◽  
Reward And Punishment

AbstractBackgroundIn an effort to optimize patient outcomes, considerable attention is being devoted to identifying patient characteristics associated with major depressive disorder (MDD) and its responsiveness to treatment. In the current study, we extend this work by evaluating whether early change in these sensitivities is associated with response to antidepressant treatment for MDD.MethodsParticipants included 210 patients with MDD who were treated with 8 weeks of escitalopram and 112 healthy comparison participants. Of the original 210 patients, 90 non-responders received adjunctive aripiprazole for an additional 8 weeks. Symptoms of depression and anhedonia were assessed at the beginning of treatment and 8 weeks later in both samples. Reward and punishment sensitivity were assessed using the BIS/BAS scales measured at the initiation of treatment and 2 weeks later.ResultsIndividuals with MDD exhibited higher punishment sensitivity and lower reward sensitivity compared with healthy comparison participants. Change in reward sensitivity during the first 2 weeks of treatment was associated with improved depressive symptoms and anhedonia following 8 weeks of treatment with escitalopram. Similarly, improvement in reward responsiveness during the first 2 weeks of adjunctive therapy with aripiprazole was associated with fewer symptoms of depression at post-treatment.ConclusionsFindings highlight the predictive utility of early change in reward sensitivity during antidepressant treatment for major depression. In a clinical setting, a lack of change in early reward processing may signal a need to modify a patient's treatment plan with alternative or augmented treatment approaches.

Altered neural processing of reward and punishment in adolescents with Major Depressive Disorder

2018 ◽  
Vol 232 ◽  
pp. 23-33 ◽  
Author(s):  
I. Landes ◽  
S. Bakos ◽  
G. Kohls ◽  
J. Bartling ◽  
G. Schulte-Körne ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Neural Processing ◽  
Major Depressive ◽  
Reward And Punishment
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