Parsing Heterogeneity in the Brain Connectivity of Depressed and Healthy Adults During Positive Mood
Open accessAbstract
Background There is well-known heterogeneity in affective mechanisms in depression that may extend to positive affect. We used data-driven parsing of neural connectivity to reveal subgroups present across depressed and healthy individuals during positive processing, informing targets for mechanistic intervention.Methods Ninety-two individuals (68 depressed patients, 24 never-depressed control subjects) completed a sustained positive mood induction during functional magnetic resonance imaging. Directed functional connectivity paths within a depression-relevant network were characterized using Group Iterative Multiple Model Estimation (GIMME), a method shown to accurately recover the direction and presence of connectivity paths in individual participants. During model selection, individuals were clustered using community detection on neural connectivity estimates. Subgroups were externally tested across multiple levels of analysis.Results Two connectivity-based subgroups emerged: subgroup A, characterized by weaker connectivity overall, and subgroup B, exhibiting hyperconnectivity (relative to subgroup A), particularly among ventral affective regions. Subgroup predicted diagnostic status (subgroup B contained 81% of patients; 50% of control subjects; χ 2 = 8.6, p = .003) and default mode network connectivity during a separate resting-state task. Among patients, subgroup B members had higher self-reported symptoms, lower sustained positive mood during the induction, and higher negative bias on a reaction-time task. Symptom-based depression subgroups did not predict these external variables.Conclusions Neural connectivity-based categorization travels with diagnostic category and is clinically predictive, but not clinically deterministic. Both patients and control subjects showed heterogeneous, and overlapping, profiles. The larger and more severely affected patient subgroup was characterized by ventrally driven hyperconnectivity during positive processing. Data-driven parsing suggests heterogeneous substrates of depression and possible resilience in control subjects in spite of biological overlap.
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Marked heterogeneity of depressed patients is evident at the neural network, cognitive, information processing, and clinical levels.
“Equally noteworthy, however, is the marked heterogeneity of depressed patients, which is evident at the neural network 143,144 , cognitive 145 , information processing 145,146 , and clinical 147 levels, and may help to explain the fact that no known intervention strategy is effective for all depressed patients.”
From Neuroplasticity in cognitive and psychological mechanisms of depression: an integrative model (2020) · cites this paper as [144]
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- Authors
- Price, R. B., Lane, S., Gates, K., Kraynak, T. E., Horner, M. S., Thase, M. E., & Siegle, G. J.
- Affiliations
- University of Pittsburgh (US)
- University of North Carolina at Chapel Hill (US)
- Philadelphia VA Medical Center (US)
- Corresponding author
- Price, Rebecca B.
- ORCID
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2017-02
- Volume
- 81
- Issue
- 4
- Pages
- 347-357
- ISSN
- 0006-3223 (ISSN-L)
- PMC
- PMC5215983
- OpenAlex
- W2463383187
- Cited by
- 106
- References
- 56
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 7 · 2023: 15 · 2022: 9 · 2021: 18 · 2020: 17 · 2019: 9 · 2018: 10 · 2017: 8 · 2016: 2
- FWCI
- 6.15
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (T32HL007560)
- National Institute of Mental Health (R01MH069618, K02MH082998, R01MH058397, K23MH100259, R01MH074807, R01MH058356)
- National Institute of Biomedical Imaging and Bioengineering (R21EB015573)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- depression, positive mood, neuronal heterogeneity, directed functional connectivity, GIMME, community detection, default mode network, mood induction, negative bias, resilience
- MeSH terms
- Adult, Affect, Brain, Brain Mapping, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Neural Pathways, Psychiatric Status Rating Scales, Resilience, Psychological
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