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Decoupling of the amygdala to other salience network regions in adolescent-onset recurrent major depressive disorder
Open accessAbstract
Background: Recent meta-analyses of resting-state networks in major depressive disorder (MDD) implicate network disruptions underlying cognitive and affective features of illness. Heterogeneity of findings to date may stem from the relative lack of data parsing clinical features of MDD such as phase of illness and the burden of multiple episodes. Method: Resting-state functional magnetic resonance imaging data were collected from 17 active MDD and 34 remitted MDD patients, and 26 healthy controls (HCs) across two sites. Participants were medication-free and further subdivided into those with single v.multiple episodes to examine disease burden. Seed-based connectivity using the posterior cingulate cortex (PCC) seed to probe the default mode network as well as the amygdala and subgenual anterior cingulate cortex (sgACC) seeds to probe the salience network (SN) were conducted. Results: Young adults with remitted MDD demonstrated hyperconnectivity of the left PCC to the left inferior frontal gyrus and of the left sgACC to the right ventromedial prefrontal cortex (PFC) and left hippocampus compared with HCs. Episode-independent effects were observed between the left PCC and the right dorsolateral PFC, as well as between the left amygdala and right insula and caudate, whereas the burden of multiple episodes was associated with hypoconnectivity of the left PCC to multiple cognitive control regions as well as hypoconnectivity of the amygdala to large portions of the SN. Conclusions: This is the first study of a homogeneous sample of unmedicated young adults with a history of adolescent-onset MDD illustrating brain-based episodic features of illness.
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“Second, the evidence in favour of abnormal RSFC of the sgACC, on which we based our hypotheses and analyses, is admittedly heterogeneous and also does rely on partially overlapping samples15,19–21.”
From The relationship between resting-state functional connectivity, antidepressant discontinuation and depression relapse (2020) · cites this paper as [20]
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Cites
Hamilton, M. (1960) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.23.1.56 · Cited by 32,817
The human brain is intrinsically organized into dynamic, anticorrelated functional networks
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553
Dissociable intrinsic connectivity networks for salience processing and executive control
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.5587-06.2007 · Cited by 7,426
Saliency, switching, attention and control: a network model of insula function
Menon, V., & Uddin, L. Q. (2010) · Brain Structure and Function · doi:10.1007/s00429-010-0262-0 · Cited by 5,592
A component based noise correction method (CompCor) for BOLD and perfusion based fMRI
Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.042 · Cited by 4,502
Large-scale brain networks and psychopathology: a unifying triple network model
Menon, V. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2011.08.003 · Cited by 4,168
Mayberg, H. S., Liotti, M., Brannan, S. K., McGinnis, S., Mahurin, R. K., Jerabek, P. A., Silva, J. A., Tekell, J. L., Martin, C. C., Lancaster, J. L., et al. (1999) · American Journal of Psychiatry · doi:10.1176/ajp.156.5.675 · Cited by 2,416
Large-scale brain networks in cognition: emerging methods and principles
Bressler, S. L., & Menon, V. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.04.004 · Cited by 2,348
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
Drevets, W. C., Price, J. L., & Furey, M. L. (2008) · Brain Structure and Function · doi:10.1007/s00429-008-0189-x · Cited by 2,241 · cited 1×
“Dysfunction in the SN contributes to biases in emotion processing and autonomic regulation (Drevets et al. 2008; Briceño et al. 2013; for a review, see Price & Drevets, 2010).”
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Tang, S., Lu, L., Zhang, L., Hu, X., Bu, X., Li, H., Hu, X., Gao, Y., Zeng, Z., Gong, Q., et al. (2018) · EBioMedicine · doi:10.1016/j.ebiom.2018.09.010 · Cited by 187
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Jacobs, R. H., Watkins, E. R., Peters, A. T., Feldhaus, C. G., Barba, A., Carbray, J. A., & Langenecker, S. A. (2016) · PLoS ONE · doi:10.1371/journal.pone.0163952 · Cited by 116
Self-citationEllard, K. K., Zimmerman, J. P., Kaur, N., Dijk, K. R. A. V., Roffman, J. L., Nierenberg, A. A., Dougherty, D. D., Deckersbach, T., & Camprodon, J. A. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.01.013 · Cited by 114
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Self-citationGong, J., Chen, G., Jia, Y., Zhong, S., Zhao, L., Luo, X., Qiu, S., Lai, S., Qi, Z., Huang, L., et al. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2018.06.012 · Cited by 110
Clark, U. S., Miller, E. R., & Hegde, R. R. (2017) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2017.11.011 · Cited by 106
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Zhu, Z., Wang, Y., Lau, W. K., Wei, X., Liu, Y., Huang, R., & Zhang, R. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00628-7 · Cited by 62
Peters, A. T., Burkhouse, K. L., Feldhaus, C. G., Langenecker, S. A., & Jacobs, R. H. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.03.059 · Cited by 64
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Liu, D., Ju, X., Gao, Y., Han, J., Li, Z., Hu, X., Tan, Z., Northoff, G., & Song, X. M. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab343 · Cited by 59
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Liu, J., Fan, Y., Zeng, L., Liu, B., Ju, Y., Wang, M., Dong, Q., Lu, X., Sun, J., Zhang, L., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01227-8 · Cited by 55
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Self-citationSingh, A., Erwin-Grabner, T., Sutcliffe, G., Antal, A., Paulus, W., & Goya‐Maldonado, R. (2019) · Scientific Reports · doi:10.1038/s41598-019-42067-3 · Cited by 47
Tse, N. Y., Ratheesh, A., Ganesan, S., Zalesky, A., & Cash, R. F. H. (2023) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105394 · Cited by 47
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Dong, D., Ming, Q., Zhong, X. B., Pu, W., Zhang, X., Jiang, Y., Gao, Y., Sun, X., Wang, X., & Yao, S. (2018) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2018.08.031 · Cited by 42
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Self-citationRakesh, D., Allen, N. B., & Whittle, S. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100775 · Cited by 44
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Olson, E. A., Kaiser, R. H., Pizzagalli, D. A., Rauch, S. L., & Rosso, I. M. (2018) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.09.012 · Cited by 39
Fu, Y., Long, Z., Luo, Q., Xu, Z., Xiang, Y., Du, W., Cao, Y., Cheng, X., & Du, L. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.645936 · Cited by 38
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Self-citationDepping, M. S., Schmitgen, M. M., Bach, C., Listunova, L., Kienzle, J., Kubera, K. M., Roesch-Ely, D., & Wolf, R. C. (2020) · The Cerebellum · doi:10.1007/s12311-020-01157-z · Cited by 31
Willinger, D., Häberling, I. S., Ilioska, I., Berger, G. E., Walitza, S., & Brem, S. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1386984 · Cited by 32
Berwian, I. M., Wenzel, J. G., Kuehn, L., Schnuerer, I., Kasper, L., Veer, I. M., Seifritz, E., Stephan, K. E., Walter, H., & Huys, Q. J. M. (2020) · Scientific Reports · doi:10.1038/s41598-020-79170-9 · Cited by 29
Jenkins, L. M., Stange, J. P., Barba, A., DelDonno, S. R., Kling, L. R., Briceño, E. M., Weisenbach, S. L., Phan, K. L., Shankman, S. A., Welsh, R. C., et al. (2017) · Cognitive, Affective, & Behavioral Neuroscience · doi:10.3758/s13415-017-0547-3 · Cited by 28
Self-citationDong, D., Li, C., Ming, Q., Zhong, X., Zhang, X., Sun, X., Jiang, Y., Gao, Y., Wang, X., & Yao, S. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.03.030 · Cited by 26
Ouden, L. D., Suo, C., Albertella, L., Greenwood, L., Lee, R. S. C., Fontenelle, L. F., Parkes, L., Tiego, J., Chamberlain, S. R., Richardson, K. E., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-021-01773-1 · Cited by 28
Liu, C., Belleau, E. L., Dong, D., Sun, X., Xiong, G., Pizzagalli, D. A., Auerbach, R. P., Wang, X., & Yao, S. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.05.074 · Cited by 22
Hou, Z., Gong, L., Zhi, M., Yin, Y., Zhang, Y., Xie, C., & Yuan, Y. (2017) · Brain Imaging and Behavior · doi:10.1007/s11682-017-9773-0 · Cited by 22
Ju, Y., Wang, M., Liu, J., Liu, B., Yan, D., Lu, X., Sun, J., Dong, Q., Zhang, L., Guo, H., et al. (2022) · Psychological Medicine · doi:10.1017/s0033291722002628 · Cited by 22
Guo, Z., Chen, L., Tang, L., Gao, Y., Chand, T., Şen, Z. D., Li, M., Walter, M., Wang, L., & Liu, C. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.02.083 · Cited by 21
Sun, J., Du, Z., Ma, Y., Chen, L., Wang, Z., Guo, C., Luo, Y., Gao, D., Yang, H., Zhang, L., et al. (2022) · Frontiers in Neurology · doi:10.3389/fneur.2022.922207 · Cited by 20
Bessette, K. L., Jacobs, R. H., Heleniak, C. M., Peters, A. T., Welsh, R. C., Watkins, E. R., & Langenecker, S. A. (2020) · PLoS ONE · doi:10.1371/journal.pone.0233539 · Cited by 22
Self-citationBanihashemi, L., Peng, C. W., Rangarajan, A., Karim, H. T., Wallace, M. L., Sibbach, B. M., Singh, J., Stinley, M. M., Germain, A., & Aizenstein, H. J. (2022) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.805049 · Cited by 19
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Liu, J., Liu, B., Wang, M., Ju, Y., Dong, Q., Lu, X., Sun, J., Zhang, L., Guo, H., Zhao, F., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.627695 · Cited by 13
Wesarg, C., Veer, I. M., Oei, N. Y. L., Daedelow, L. S., Lett, T. A. P., Banaschewski, T., Barker, G. J., Bokde, A. L. W., Quinlan, E. B., Desrivières, S., et al. (2021) · Human Brain Mapping · doi:10.1002/hbm.25433 · Cited by 17
Langenecker, S. A., Klumpp, H., Peters, A. T., Crane, N. A., DelDonno, S. R., Bessette, K. L., Ajilore, O., Leow, A., Shankman, S. A., Walker, S. J., et al. (2019) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2018.07.001 · Cited by 11
Self-citationSchreiner, M. W., Roberts, H., Dillahunt, A. K., Farstead, B. W., Feldman, D. A., Thomas, L. R., Jacobs, R. H., Bessette, K. L., Welsh, R. C., Watkins, E. R., et al. (2023) · Suicide and Life-Threatening Behavior · doi:10.1111/sltb.12960 · Cited by 11
Self-citationLuo, L., Dimitrovski, M., Wise, T., & Iniesta, R. (2025) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2025.106309 · Cited by 10
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Chen, X.-L., Yang, H., Cui, L., & Li, X. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1170625 · Cited by 9
Stange, J. P., Jenkins, L. M., Bessette, K. L., Kling, L. R., Bark, J. S., Shepard, R., Hamlat, E. J., DelDonno, S. R., Phan, K. L., Passarotti, A. M., et al. (2018) · Brain Connectivity · doi:10.1089/brain.2018.0619 · Cited by 9
Self-citationHuang, S., Hao, S., Si, Y., Shen, D., Cui, L., Zhang, Y., Lin, H., Wang, S., Gao, Y., & Guo, X. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.03.166 · Cited by 8
Winters, D. E., Pruitt, P. J., Gambin, M., Fukui, S., Cyders, M. A., Pierce, B. J., Lay, K., & Damoiseaux, J. S. (2021) · Child Psychiatry & Human Development · doi:10.1007/s10578-021-01242-2 · Cited by 8
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Kalhan, S., McFadyen, J., Tsuchiya, N., & Garrido, M. I. (2022) · Human Brain Mapping · doi:10.1002/hbm.25889 · Cited by 8
Sun, J., Du, Z., Ma, Y., Guo, C., Gao, S., Luo, Y., Chen, Q., Yang, H., Xiao, X., Yu, X., et al. (2022) · Brain Sciences · doi:10.3390/brainsci12121603 · Cited by 8
Treatment-Resistant Depression and Ketamine Response in a Patient With Bilateral Amygdala Damage
Scheele, D., Zimbal, S., Feinstein, J. S., Delis, A., Neumann, C., Mielacher, C., Philipsen, A., & Hurlemann, R. (2019) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2019.18101219 · Cited by 7
Sun, F., Kong, Z., Tang, Y., Yang, J., Huang, G.-D., Liu, Y., Jiang, W., Yang, M., & Jia, X. (2024) · Academic Radiology · doi:10.1016/j.acra.2024.04.043 · Cited by 6
Langenecker, S. A., Schreiner, M. W., Thomas, L. R., Bessette, K. L., DelDonno, S. R., Jenkins, L. M., Easter, R. E., Stange, J. P., Pocius, S. L., Dillahunt, A. K., et al. (2021) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2021.06.014 · Cited by 8
Self-citationXiao, X., Bentzley, B. S., Cole, E. J., Tischler, C., Stimpson, K. H., Duvio, D., Bishop, J. H., DeSouza, D. D., Schatzberg, A. F., Keller, C. J., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/672154 · Cited by 7
Marečková, K., Hawco, C. S., Santos, F. C. D., Bakht, A., Calarco, N., Miles, A. E., Voineskos, A. N., Sibille, E. L., Hariri, A. R., & Nikolova, Y. S. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01277-y · Cited by 6
Mo, L., Liao, D., She, J., Yan, B., & Chen, M. (2025) · Complementary Therapies in Medicine · doi:10.1016/j.ctim.2025.103253 · Cited by 5
Jacobson, M. M., Jenkins, L. M., Feldman, D. A., Crane, N. A., & Langenecker, S. A. (2023) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2023.111642 · Cited by 5
Self-citationPeterman, J. S., Marshall, D., Lamping, E., Easter, R. E., Babu, P., Langenecker, S. A., McInnis, M. G., & Ryan, K. A. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.01.073 · Cited by 5
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Caceres, G. A., Scambray, K. A., Malee, K., Smith, R. A., Williams, P. L., Wang, L., & Jenkins, L. M. (2023) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.11.026 · Cited by 4
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Metadata
- Authors
- Jacobs, R. H., Barba, A., Gowins, J. R., Klumpp, H., Jenkins, L. M., Mickey, B. J., Ajilore, O., Peciña, M., Sikora, M., Ryan, K. A., Hsu, D. T., Welsh, R. C., Zubieta, J.-K., Phan, K. L., & Langenecker, S. A.
- Affiliations
- University of Illinois Chicago (US)
- University of Michigan (US)
- Corresponding author
- Langenecker, S. A.
- ORCID
- Venue
- Psychological Medicine
- Publisher
- Cambridge University Press (CUP)
- Published
- 2016-01-20
- Volume
- 46
- Issue
- 5
- Pages
- 1055-1067
- ISSN
- 0033-2917 (ISSN-L)
- 1469-8978
- PMC
- PMC4810773
- OpenAlex
- W2262083186
- Cited by
- 108
- References
- 44
- Citations by year
- 2026: 5 · 2025: 9 · 2024: 5 · 2023: 7 · 2022: 8 · 2021: 35 · 2020: 9 · 2019: 8 · 2018: 11 · 2017: 6 · 2016: 5
- FWCI
- 6.36
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Psychological Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (UL1TR000050, 5r01ns052514-04, KL2TR000434)
- National Institute of Mental Health (R01MH091811, K01MH085035, R01MH101497, K23MH092648, R01MH086858, K23MH093679, R01MH101487)
- National Institute of Neurological Disorders and Stroke (1R01NS052514, R01-NS052514)
- National Center for Advancing Translational Sciences (UL1TR00050)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- recurrent major depressive disorder, adolescent-onset depression, salience network, amygdala, default mode network, posterior cingulate cortex, subgenual anterior cingulate cortex, resting-state functional connectivity, remitted depression, cognitive control, young adults
- MeSH terms
- Adolescent, Adult, Amygdala, Brain Mapping, Depressive Disorder, Major, Major Depressive Disorder, Female, Frontal Lobe, Gyrus Cinguli, Humans, Magnetic Resonance Imaging, Male, Neural Pathways, Recurrence, Case-Control Studies, Young Adult, Executive Function
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