Computational phenotyping of brain-behavior dynamics underlying approach-avoidance conflict in major depressive disorder
Name
journal.pcbi.1008955.pdf
Description
Published version
Size
1.85 MB
Format
Adobe PDF
Checksum (MD5)
bba12445651efb85850b11219907a6d9
Author(s)
Pedersen, Mads L
Ironside, Maria
Amemori, Ken-ichi
McGrath, Callie L
Kang, Min S
Graybiel, Ann M
Pizzagalli, Diego A
Frank, Michael J
Date Issued
2021
Journal
PLoS Computational Biology
Publisher
Public Library of Science (PLoS)
Citation
Pedersen, Mads L, Ironside, Maria, Amemori, Ken-ichi, McGrath, Callie L, Kang, Min S et al. 2021. "Computational phenotyping of brain-behavior dynamics underlying approach-avoidance conflict in major depressive disorder." PLoS Computational Biology, 17 (5).
Version
Final published version
Abstract
Adaptive behavior requires balancing approach and avoidance based on the rewarding and aversive consequences of actions. Imbalances in this evaluation are thought to characterize mood disorders such as major depressive disorder (MDD). We present a novel application of the drift diffusion model (DDM) suited to quantify how offers of reward and aversiveness, and neural correlates thereof, are dynamically integrated to form decisions, and how such processes are altered in MDD. Hierarchical parameter estimation from the DDM demonstrated that the MDD group differed in three distinct reward-related parameters driving approach-based decision making. First, MDD was associated with reduced reward sensitivity, measured as the impact of offered reward on evidence accumulation. Notably, this effect was replicated in a follow-up study. Second, the MDD group showed lower starting point bias towards approaching offers. Third, this starting point was influenced in opposite directions by Pavlovian effects and by nucleus accumbens activity across the groups: greater accumbens activity was related to approach bias in controls but avoid bias in MDD. Cross-validation revealed that the combination of these computational biomarkers were diagnostic of patient status, with accumbens influences being particularly diagnostic. Finally, within the MDD group, reward sensitivity and nucleus accumbens parameters were differentially related to symptoms of perceived stress and depression. Collectively, these findings establish the promise of computational psychiatry approaches to dissecting approach-avoidance decision dynamics relevant for affective disorders.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1371/JOURNAL.PCBI.1008955
