The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample
Open accessAbstract
OBJECTIVE: Previous studies have implicated aberrant reward processing in the pathogenesis of adolescent depression. However, no study has used functional connectivity within a distributed reward network, assessed using resting-state functional MRI (fMRI), to predict the onset of depression in adolescents. This study used reward network-based functional connectivity at baseline to predict depressive disorder at follow-up in a community sample of adolescents. METHOD: A total of 637 children 6-12 years old underwent resting-state fMRI. Discovery and replication analyses tested intrinsic functional connectivity (iFC) among nodes of a putative reward network. Logistic regression tested whether striatal node strength, a measure of reward-related iFC, predicted onset of a depressive disorder at 3-year follow-up. Further analyses investigated the specificity of this prediction. RESULTS: Increased left ventral striatum node strength predicted increased risk for future depressive disorder (odds ratio=1.54, 95% CI=1.09-2.18), even after excluding participants who had depressive disorders at baseline (odds ratio=1.52, 95% CI=1.05-2.20). Among 11 reward-network nodes, only the left ventral striatum significantly predicted depression. Striatal node strength did not predict other common adolescent psychopathology, such as anxiety, attention deficit hyperactivity disorder, and substance use. CONCLUSIONS: Aberrant ventral striatum functional connectivity specifically predicts future risk for depressive disorder. This finding further emphasizes the need to understand how brain reward networks contribute to youth depression.
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“Across studies, over-recruitment of PFC regions (mPFC, dlPFC) during reward processing has been interpreted as suggesting over-compensation for reduced striatal responses to rewards [104, 111, 112].”
From Prefrontal cortex and depression (2022) · cites this paper as [112]
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“Highlighting specificity, this metric did not predict the emergence of ADHD, anxiety or substance abuse over the same time period.”
From Prefrontal cortex and depression (2022) · cites this paper as [112]
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“Critically, in a community-based sample of 6-12 years children (N = 637), rsFC strength between the ventral striatum and other reward-related regions (vmPFC, dACC, VTA) predicted the new onset of depressive disorder 3 years later [112].”
From Prefrontal cortex and depression (2022) · cites this paper as [112]
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Cites
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522 · cited 3×
“Such work quantifies the degree to which brain “nodes” (9) facilitate signal integration among network components.”
InfluentialPower, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429 · cited 2×
“Finally, iFC data are sensitive to head motion (22, 23).”
Methods to detect, characterize, and remove motion artifact in resting state fMRI
Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748 · cited 2×
“Finally, iFC data are sensitive to head motion (22, 23).”
The reward circuit: linking primate anatomy and human imaging
Haber, S. N., & Knutson, B. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.129 · Cited by 3,718 · cited 1×
“Our first step was to show resting-state coupling between brain regions typically activated during rewardrelatedbehaviors (3,26,37).”
Ferrari, A. J., Charlson, F. J., Norman, R. E., Patten, S. B., Freedman, G., Murray, C. J. L., Vos, T., & Whiteford, H. A. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001547 · Cited by 3,115
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.0071 · Cited by 2,281
Resting-state connectivity biomarkers define neurophysiological subtypes of depression
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017) · Nature Medicine · doi:10.1038/nm.4246 · Cited by 2,170
Bartra, O., McGuire, J. T., & Kable, J. W. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.063 · Cited by 1,927 · cited 2×
“Our first step was to show resting-state coupling between brain regions typically activated during rewardrelatedbehaviors (3,26,37).”
Goodman, R., Ford, T., Richards, H., Gatward, R., & Meltzer, H. (2000) · Journal of Child Psychology and Psychiatry · doi:10.1111/j.1469-7610.2000.tb02345.x · Cited by 1,755
Dimidjian, S., Hollon, S. D., Dobson, K. S., Schmaling, K. B., Kohlenberg, R. J., Addis, M. E., Gallop, R., McGlinchey, J. B., Markley, D. K., Gollan, J. K., et al. (2006) · Journal of Consulting and Clinical Psychology · doi:10.1037/0022-006x.74.4.658 · Cited by 1,607
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Prefrontal cortex and depression
Pizzagalli, D. A., & Roberts, A. C. (2022) · Neuropsychopharmacology · doi:10.1038/s41386-021-01101-7 · Cited by 667
“An important exception is the recent study by Pan and colleagues [112], who found that resting state functional connectivity within the brain reward pathway predicted the new onset of depressive disorder – but not ADHD, anxiety or substance abuse – 3 years later.”
BackgroundReward Processing in Depression: A Conceptual and Meta-Analytic Review Across fMRI and EEG Studies
Keren, H., O’Callaghan, G., Vidal-Ribas, P., Buzzell, G. A., Brotman, M. A., Leibenluft, E., Pan, P. M., Meffert, L., Kaiser, A., Wolke, S., et al. (2018) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2018.17101124 · Cited by 521
“Interestingly, a recent connectivity study (89) demonstrated that increased connectivity of the ventral striatum predicts depression, in keeping with striatal aberrations in this disorder.”
BackgroundSelf-citationPizzagalli, D. A. (2022) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20220423 · Cited by 214
“In a notable study involving a large community-based sample of 9-year-old children (N5637), rsFC between the ventral striatum and other key reward hubs (vmPFC, dACC, VTA) predicted new onset of depressive disorders 3 years later, but not attention deficit hyperactivity disorder, anxiety disorders, or substance use dis…”
BackgroundEditorial: What is depression?
Stringaris, A. K. (2017) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12844 · Cited by 155
Self-citationKetamine modulates fronto-striatal circuitry in depressed and healthy individuals
Mkrtchian, A., Evans, J. W., Kraus, C., Yuan, P., Kadriu, B., Nugent, A. C., Roiser, J. P., & Zarate, C. A. (2021) · Molecular Psychiatry · doi:10.1038/s41380-020-00878-1 · Cited by 110
Metadata
- Authors
- Pan, P. M., Sato, J. R., Salum, G. A., Rohde, L. A., Gadelha, A., Zugman, A., Mari, J., Jackowski, A., Picon, F., Miguel, E. C., Pine, D. S., Leibenluft, E., Bressan, R. A., & Stringaris, A.
- Affiliations
- From the Department of Psychiatry, Laboratório Interdisciplinar de Neurociências Clínicas, Universidade Federal de São Paulo, São Paulo, Brazil; the Mood, Brain, and Development Unit, Emotion and Development Branch, NIMH, Bethesda, Md.; Center for Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil; the Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; the Department and Institute of...
- Universidade Federal do Rio Grande do Sul (BR)
- ORCID
- Venue
- American Journal of Psychiatry
- Published
- 2017-11-01
- Volume
- 174
- Issue
- 11
- Pages
- 1112-1119
- ISSN
- 0002-953X (ISSN-L)
- 1535-7228
- PMC
- PMC10752293
- OpenAlex
- W2758286034
- Cited by
- 156
- References
- 40
- Citations by year
- 2026: 1 · 2025: 13 · 2024: 14 · 2023: 14 · 2022: 21 · 2021: 38 · 2020: 23 · 2019: 19 · 2018: 11 · 2017: 2
- FWCI
- 8.63
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Funders
- Eli Lilly and Company
- Wellcome Trust
- University of Cambridge
- University College London
- University of Oxford
- Fundação de Amparo à Pesquisa do Estado de São Paulo (2014/, 14/50917-0, 13/08531-5)
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (2014‐2, 2013/08531-5, 465550/2014-2, CNPq 465550/2014-2)
- H. Lundbeck A/S
- National Institutes of Health
- National Institute of Mental Health (Z01MH002781, Z01MH002782)
- Daiichi Sankyo Europe
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- ventral striatum, functional connectivity, adolescent depression, reward processing, reward network, intrinsic functional connectivity, risk prediction, children and adolescents, longitudinal prediction
- MeSH terms
- Adolescent, Brain, Brazil, Child, Major Depressive Disorder, Depressive Disorder, Female, Follow-Up Studies, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Reward, Cohort Studies, Odds Ratio, Risk Assessment, Functional Neuroimaging, Ventral Striatum
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