Maladaptive Avoidance Learning in the Orbitofrontal Cortex in Adolescents With Major Depression.
David Willinger1, Iliana I Karipidis2, Selina Neuer3
1Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland.
Adolescent major depressive disorder (MDD) involves impaired processing of loss-related errors in the brain, impacting learning and potentially leading to negative bias. This finding may aid in early diagnosis and treatment selection for adolescent depression.
Area of Science:
- Neuroscience
- Psychiatry
- Computational Psychiatry
Background:
- Major depressive disorder (MDD) in adolescents affects the brain's incentive network.
- Understanding these mechanisms can inform early intervention strategies for adolescent MDD.
Purpose of the Study:
- Investigate alterations in instrumental vigor and brain responses to monetary incentives in adolescent MDD.
- Correlate these changes with symptom severity, particularly anhedonia.
Main Methods:
- Used functional magnetic resonance imaging (fMRI) and a monetary incentive delay task in adolescents with MDD and healthy controls.
- Applied computational reinforcement learning models to assess learning and response vigor.
- Analyzed brain responses and effective connectivity related to prediction errors and linked them to depression severity.
Main Results:
- Adolescents with MDD demonstrated simpler learning models and slower learning.
- Impaired processing of loss prediction errors in the orbitofrontal cortex was linked to aberrant gain control.
- Anhedonia scores correlated with loss-related error signals in the posterior insula and habenula.
Conclusions:
- Adolescent MDD shows selective impairment in processing loss-related errors, not reward errors, in the orbitofrontal cortex.
- Aberrant evaluation of losses may underlie negative bias and helplessness in adolescent depression.
- This research offers insights into MDD pathomechanisms, potentially improving early diagnosis and treatment.
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