Abstract
Disrupted whole-brain resting-state functional connectivity (RSFC) of the posterior cingulate (PCC) has been highlighted to associate with cognitive and affective dysfunction in major depressive disorder (MDD). However, prior findings showed certain inconsistency about the RSFC of the PCC in MDD. This study aims to investigate the aberrant RSFC of the PCC in MDD using anisotropic effect-size version of seed-based d mapping (AES-SDM). Web of Science and PubMed were searched for studies investigating PCC-based RSFC in MDD. A total of 17 studies, involving 804 patients and 724 healthy controls (HCs), fit our selection criteria. Additionally, to seek for the link between functional and structural differences, we did a meta-analysis on the studies in conjunction with voxel-based morphology (VBM) analysis. The PCC showed higher RSFC with the left middle temporal gyrus (MTG) and the right middle frontal gyrus (MFG), and lower RSFC with the left superior frontal gyrus (SFG) and the left precuneus in patients with MDD than HCs. Moreover, the meta-regression analysis revealed a negative correlation between the FC alteration of the right MFG with the PCC and depression severity. Notably, the left MTG and the left MFG demonstrated gray matter deviations in conjunction analysis. Our results indicated that the aberrant RSFC between the PCC and brain regions sub-serving cognitive control and emotional regulation in patients with MDD. And such functional alterations may have structural basis. These findings may underlie the mechanisms of deficits in cognitive control and emotional regulation of MDD.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
Data and code will be made available on request.
References
Alexopoulos, G. S., Hoptman, M. J., Kanellopoulos, D., Murphy, C. F., Lim, K. O., & Gunning, F. M. (2012). Functional connectivity in the cognitive control network and the default mode network in late-life depression. Journal of Affective Disorders, 139, 56–65. https://doi.org/10.1016/j.jad.2011.12.002
Andreescu, C., Tudorascu, D. L., Butters, M. A., Tamburo, E., Patel, M., Price, J., Karp, J. F., Reynolds, C. F., 3rd., & Aizenstein, H. (2013). Resting state functional connectivity and treatment response in late-life depression. Psychiatry Research, 214, 313–321. https://doi.org/10.1016/j.pscychresns.2013.08.007
Andrews-Hanna, J. R., Reidler, J. S., Sepulcre, J., Poulin, R., & Buckner, R. L. (2010). Functional-anatomic fractionation of the brain’s default network. Neuron, 65, 550–562. https://doi.org/10.1016/j.neuron.2010.02.005
Andrews, P. W., & Thomson, J. A., Jr. (2009). The bright side of being blue: Depression as an adaptation for analyzing complex problems. Psychological Review, 116, 620–654. https://doi.org/10.1037/a0016242
Arnone, D., Job, D., Selvaraj, S., Abe, O., Amico, F., Cheng, Y., Colloby, S. J., O’Brien, J. T., Frodl, T., Gotlib, I. H., Ham, B. J., Kim, M. J., Koolschijn, P. C., Périco, C. A., Salvadore, G., Thomas, A. J., Van Tol, M. J., van der Wee, N. J., Veltman, D. J., … McIntosh, A. M. (2016). Computational meta-analysis of statistical parametric maps in major depression. Human Brain Mapping, 37, 1393–1404. https://doi.org/10.1002/hbm.23108
Beckmann, M., Johansen-Berg, H., & Rushworth, M. F. S. (2009) Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization. Journal of Neuroscience, 29(4), 1175-1190. https://doi.org/10.1523/JNEUROSCI.3328-08.2009
Berman, M. G., Misic, B., Buschkuehl, M., Kross, E., Deldin, P. J., Peltier, S., Churchill, N. W., Jaeggi, S. M., Vakorin, V., McIntosh, A. R., & Jonides, J. (2014). Does resting-state connectivity reflect depressive rumination? A tale of two analyses. NeuroImage, 103, 267–279. https://doi.org/10.1016/j.neuroimage.2014.09.027
Berman, M. G., Peltier, S., Nee, D. E., Kross, E., Deldin, P. J., & Jonides, J. (2011). Depression, rumination and the default network. Soc Cogn Affect Neurosci., 6, 548–555. https://doi.org/10.1093/scan/nsq080
Bessette, K. L., Jenkins, L. M., Skerrett, K. A., Gowins, J. R., DelDonno, S. R., Zubieta, J. K., McInnis, M. G., Jacobs, R. H., Ajilore, O., & Langenecker, S. A. (2018). Reliability, Convergent Validity and Time Invariance of Default Mode Network Deviations in Early Adult Major Depressive Disorder. Front Psychiatry., 9, 244. https://doi.org/10.3389/fpsyt.2018.00244
Bluhm, R., Williamson, P., Lanius, R., Théberge, J., Densmore, M., Bartha, R., Neufeld, R., & Osuch, E. (2009). Resting state default-mode network connectivity in early depression using a seed region-of-interest analysis: Decreased connectivity with caudate nucleus. Psychiatry and Clinical Neurosciences, 63, 754–761. https://doi.org/10.1111/j.1440-1819.2009.02030.x
Brakowski, J., Spinelli, S., Dörig, N., Bosch, O. G., Manoliu, A., Holtforth, M. G., & Seifritz, E. (2017). Resting state brain network function in major depression - Depression symptomatology, antidepressant treatment effects, future research. Journal of Psychiatric Research, 92, 147–159. https://doi.org/10.1016/j.jpsychires.2017.04.007
Castellanos, F. X., Di Martino, A., Craddock, R. C., Mehta, A. D., & Milham, M. P. (2013). Clinical applications of the functional connectome. NeuroImage, 80, 527–540. https://doi.org/10.1016/j.neuroimage.2013.04.083
Chase, H. W., Moses-Kolko, E. L., Zevallos, C., Wisner, K. L., & Phillips, M. L. (2014). Disrupted posterior cingulate-amygdala connectivity in postpartum depressed women as measured with resting BOLD fMRI. Social Cognitive and Affective Neuroscience., 9, 1069–1075. https://doi.org/10.1093/scan/nst083
Cheng, W., Rolls, E. T., Qiu, J., Xie, X., Wei, D., Huang, C. C., Yang, A. C., Tsai, S. J., Li, Q., Meng, J., Lin, C. P., Xie, P., & Feng, J. (2018). Increased functional connectivity of the posterior cingulate cortex with the lateral orbitofrontal cortex in depression. Translational Psychiatry, 8, 90. https://doi.org/10.1038/s41398-018-0139-1
Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews Neuroscience, 3, 201–215. https://doi.org/10.1038/nrn755
Cunnington, R., Windischberger, C., Deecke, L., & Moser, E. (2002). The preparation and execution of self-initiated and externally-triggered movement: A study of event-related fMRI. NeuroImage, 15, 373–385. https://doi.org/10.1006/nimg.2001.0976
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., Schatzberg, A. F., Sudheimer, K., Keller, J., Mayberg, H. S., Gunning, F. M., Alexopoulos, G. S., Fox, M. D., Pascual-Leone, A., Voss, H. U., … Liston, C. (2017). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine, 23, 28–38. https://doi.org/10.1038/nm.4246
du Boisgueheneuc, F., Levy, R., Volle, E., Seassau, M., Duffau, H., Kinkingnehun, S., Samson, Y., Zhang, S., & Dubois, B. (2006). Functions of the left superior frontal gyrus in humans: A lesion study. Brain, 129, 3315–3328. https://doi.org/10.1093/brain/awl244
Duko, B., Ayano, G., Pereira, G., Betts, K., & Alati, R. (2020). Prenatal tobacco use and the risk of mood disorders in offspring: A systematic review and meta-analysis. Social Psychiatry and Psychiatric Epidemiology, 55, 1549–1562. https://doi.org/10.1007/s00127-020-01949-y
Eickhoff, S. B., Nichols, T. E., Laird, A. R., Hoffstaedter, F., Amunts, K., Fox, P. T., Bzdok, D., & Eickhoff, C. R. (2016). Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation. NeuroImage, 137, 70–85. https://doi.org/10.1016/j.neuroimage.2016.04.072
Emch, M., von Bastian, C. C., & Koch, K. (2019). Neural Correlates of Verbal Working Memory: An fMRI Meta-Analysis. Frontiers in Human Neuroscience, 13, 180. https://doi.org/10.3389/fnhum.2019.00180
Ferrari, A. J., Charlson, F. J., Norman, R. E., Patten, S. B., Freedman, G., Murray, C. J., Vos, T., & Whiteford, H. A. (2013). Burden of depressive disorders by country, sex, age, and year: Findings from the global burden of disease study 2010. PLoS Medicine, 10, e1001547. https://doi.org/10.1371/journal.pmed.1001547
Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2006). Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proceedings of National Academy of Science of the U S A, 103, 10046–10051. https://doi.org/10.1073/pnas.0604187103
Fox, M. D., & Raichle, M. E. (2007). Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nature Reviews Neuroscience, 8, 700–711. https://doi.org/10.1038/nrn2201
Fransson, P., & Marrelec, G. (2008). The precuneus/posterior cingulate cortex plays a pivotal role in the default mode network: Evidence from a partial correlation network analysis. NeuroImage, 42, 1178–1184. https://doi.org/10.1016/j.neuroimage.2008.05.059
Fresco, D. M., Roy, A. K., Adelsberg, S., Seeley, S., García-Lesy, E., Liston, C., & Mennin, D. S. (2017). Distinct Functional Connectivities Predict Clinical Response with Emotion Regulation Therapy. Frontiers in Human Neuroscience, 11, 86. https://doi.org/10.3389/fnhum.2017.00086
Frith, U., & Frith, C. D. (2003). Development and neurophysiology of mentalizing. Philosophical Transactions of the Royal Society of London. Series b, Biological Sciences, 358, 459–473. https://doi.org/10.1098/rstb.2002.1218
Gaffrey, M. S., Luby, J. L., Botteron, K., Repovš, G., & Barch, D. M. (2012). Default mode network connectivity in children with a history of preschool onset depression. Journal of Child Psychology and Psychiatry, 53, 964–972. https://doi.org/10.1111/j.1469-7610.2012.02552.x
Greicius, M. D., Srivastava, G., Reiss, A. L., & Menon, V. (2004). Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proceeding of the National Academy of Science of the U S A., 101, 4637–4642. https://doi.org/10.1073/pnas.0308627101
Guo, W., Liu, F., Dai, Y., Jiang, M., Zhang, J., Yu, L., Long, L., Chen, H., Gao, Q., & Xiao, C. (2013). Decreased interhemispheric resting-state functional connectivity in first-episode, drug-naive major depressive disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 41, 24–29. https://doi.org/10.1016/j.pnpbp.2012.11.003
Guo, W., Liu, F., Yu, M., Zhang, J., Zhang, Z., Liu, J., Xiao, C., & Zhao, J. (2014). Functional and anatomical brain deficits in drug-naive major depressive disorder. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 54, 1–6. https://doi.org/10.1016/j.pnpbp.2014.05.008
Habas, C., Kamdar, N., Nguyen, D., Prater, K., Beckmann, C. F., Menon, V., & Greicius, M. D. (2009). Distinct cerebellar contributions to intrinsic connectivity networks. Journal of Neuroscience, 29, 8586–8594. https://doi.org/10.1523/jneurosci.1868-09.2009
Hearne, L., Cocchi, L., Zalesky, A., & Mattingley, J. B. (2015). Interactions between default mode and control networks as a function of increasing cognitive reasoning complexity. Human Brain Mapping, 36, 2719–2731. https://doi.org/10.1002/hbm.22802
Iwabuchi, S. J., Krishnadas, R., Li, C., Auer, D. P., Radua, J., & Palaniyappan, L. (2015). Localized connectivity in depression: A meta-analysis of resting state functional imaging studies. Neuroscience and Biobehavioral Reviews, 51, 77–86. https://doi.org/10.1016/j.neubiorev.2015.01.006
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. (2016). Decoupling of the amygdala to other salience network regions in adolescent-onset recurrent major depressive disorder. Psychological Medicine, 46, 1055–1067. https://doi.org/10.1017/s0033291715002615
Jacobs, R. H., Jenkins, L. M., Gabriel, L. B., Barba, A., Ryan, K. A., Weisenbach, S. L., Verges, A., Baker, A. M., Peters, A. T., Crane, N. A., Gotlib, I. H., Zubieta, J. K., Phan, K. L., Langenecker, S. A., & Welsh, R. C. (2014). Increased coupling of intrinsic networks in remitted depressed youth predicts rumination and cognitive control. PLoS ONE, 9, e104366. https://doi.org/10.1371/journal.pone.0104366
Janca, A., & Hiller, W. (1996). ICD-10 checklists–a tool for clinicians’ use of the ICD-10 classification of mental and behavioral disorders. Comprehensive Psychiatry, 37, 180–187. https://doi.org/10.1016/s0010-440x(96)90034-6
Johnson, M. K., Raye, C. L., Mitchell, K. J., Touryan, S. R., Greene, E. J., & Nolen-Hoeksema, S. (2006). Dissociating medial frontal and posterior cingulate activity during self-reflection. Soc Cogn Affect Neurosci., 1, 56–64. https://doi.org/10.1093/scan/nsl004
Jones, R., & Bhattacharya, J. (2014). A role for the precuneus in thought-action fusion: Evidence from participants with significant obsessive-compulsive symptoms. Neuroimage Clinical., 4, 112–121. https://doi.org/10.1016/j.nicl.2013.11.008
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015). Large-Scale Network Dysfunction in Major Depressive Disorder: A Meta-analysis of Resting-State Functional Connectivity. JAMA Psychiatry., 72, 603–611. https://doi.org/10.1001/jamapsychiatry.2015.0071
Kandilarova, S., Stoyanov, D., Sirakov, N., Maes, M., & Specht, K. (2019). Reduced grey matter volume in frontal and temporal areas in depression: Contributions from voxel-based morphometry study. Acta Neuropsychiatrica., 31, 252–257. https://doi.org/10.1017/neu.2019.20
Kaufman, J., Birmaher, B., Brent, D., Rao, U., Flynn, C., Moreci, P., Williamson, D., & Ryan, N. (1997). Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime Version (K-SADS-PL): Initial reliability and validity data. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 980–988. https://doi.org/10.1097/00004583-199707000-00021
Kim, S. M., Park, S. Y., Kim, Y. I., Son, Y. D., Chung, U. S., Min, K. J., & Han, D. H. (2016). Affective network and default mode network in depressive adolescents with disruptive behaviors. Neuropsychiatric Disease and Treatment, 12, 49–56. https://doi.org/10.2147/ndt.S95541
Köhler-Forsberg, K., Jorgensen, A., Dam, V. H., Stenbæk, D. S., Fisher, P. M., Ip, C. T., Ganz, M., Poulsen, H. E., Giraldi, A., Ozenne, B., Jørgensen, M. B., Knudsen, G. M., & Frokjaer, V. G. (2020). Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol. Front Psychiatry., 11, 641. https://doi.org/10.3389/fpsyt.2020.00641
Kohn, N., Eickhoff, S. B., Scheller, M., Laird, A. R., Fox, P. T., & Habel, U. (2014). Neural network of cognitive emotion regulation–an ALE meta-analysis and MACM analysis. NeuroImage, 87, 345–355. https://doi.org/10.1016/j.neuroimage.2013.11.001
Kucyi, A., Moayedi, M., Weissman-Fogel, I., Hodaie, M., & Davis, K. D. (2012). Hemispheric asymmetry in white matter connectivity of the temporoparietal junction with the insula and prefrontal cortex. PLoS ONE, 7, e35589. https://doi.org/10.1371/journal.pone.0035589
Lai, C. H. (2018). The regional homogeneity of cingulate-precuneus regions: The putative biomarker for depression and anxiety. Journal of Affective Disorders, 229, 171–176. https://doi.org/10.1016/j.jad.2017.12.086
Lai, C. H., & Wu, Y. T. (2014). Frontal-insula gray matter deficits in first-episode medication-naïve patients with major depressive disorder. Journal of Affective Disorders, 160, 74–79. https://doi.org/10.1016/j.jad.2013.12.036
Levy, R., & Goldman-Rakic, P. S. (2000). Segregation of working memory functions within the dorsolateral prefrontal cortex. Experimental Brain Research, 133, 23–32. https://doi.org/10.1007/s002210000397
Li, G., Liu, Y., Zheng, Y., Li, D., Liang, X., Chen, Y., Cui, Y., Yap, P. T., Qiu, S., Zhang, H., & Shen, D. (2020a). Large-scale dynamic causal modeling of major depressive disorder based on resting-state functional magnetic resonance imaging. Human Brain Mapping, 41, 865–881. https://doi.org/10.1002/hbm.24845
Li, Q., Zhao, Y., Chen, Z., Long, J., Dai, J., Huang, X., Lui, S., Radua, J., Vieta, E., Kemp, G. J., Sweeney, J. A., Li, F., & Gong, Q. (2020b). Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder. Neuropsychopharmacology, 45, 703–712. https://doi.org/10.1038/s41386-019-0563-9
Liu, Q., He, H., Yang, J., Feng, X., Zhao, F., & Lyu, J. (2020). Changes in the global burden of depression from 1990 to 2017: Findings from the Global Burden of Disease study. Journal of Psychiatric Research, 126, 134–140. https://doi.org/10.1016/j.jpsychires.2019.08.002
Liu, R., Yue, Y., Hou, Z., Yuan, Y., & Wang, Q. (2018). Risk factors associated with cognitions for late-onset depression based on anterior and posterior default mode sub-networks. Journal of Affective Disorders, 235, 544–550. https://doi.org/10.1016/j.jad.2018.04.065
Ma, C., Ding, J., Li, J., Guo, W., Long, Z., Liu, F., Gao, Q., Zeng, L., Zhao, J., & Chen, H. (2012). Resting-state functional connectivity bias of middle temporal gyrus and caudate with altered gray matter volume in major depression. PLoS ONE, 7, e45263. https://doi.org/10.1371/journal.pone.0045263
Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends in Cognitive Sciences, 15, 483–506. https://doi.org/10.1016/j.tics.2011.08.003
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6, e1000097. https://doi.org/10.1371/journal.pmed.1000097
Morrow, J., & Nolen-Hoeksema, S. (1990). Effects of responses to depression on the remediation of depressive affect. Journal of Personality and Social Psychology, 58, 519–527. https://doi.org/10.1037//0022-3514.58.3.519
Oudega, M. L., van der Werf, Y. D., Dols, A., Wattjes, M. P., Barkhof, F., Bouckaert, F., Vandenbulcke, M., De Winter, F. L., Sienaert, P., Eikelenboom, P., Stek, M. L., van den Heuvel, O. A., Emsell, L., Rhebergen, D., & van Exel, E. (2019). Exploring resting state connectivity in patients with psychotic depression. PLoS ONE, 14, e0209908. https://doi.org/10.1371/journal.pone.0209908
Peng, H., Wu, K., Li, J., Qi, H., Guo, S., Chi, M., Wu, X., Guo, Y., Yang, Y., & Ning, Y. (2014). Increased suicide attempts in young depressed patients with abnormal temporal-parietal-limbic gray matter volume. Journal of Affective Disorders, 165, 69–73. https://doi.org/10.1016/j.jad.2014.04.046
Peters, A. T., Burkhouse, K., Feldhaus, C. C., Langenecker, S. A., & Jacobs, R. H. (2016). Aberrant resting-state functional connectivity in limbic and cognitive control networks relates to depressive rumination and mindfulness: A pilot study among adolescents with a history of depression. Journal of Affective Disorders, 200, 178–181. https://doi.org/10.1016/j.jad.2016.03.059
Petrides, M. (2000). The role of the mid-dorsolateral prefrontal cortex in working memory. Experimental Brain Research, 133, 44–54. https://doi.org/10.1007/s002210000399
Radua, J., & Mataix-Cols, D. (2009). Voxel-wise meta-analysis of grey matter changes in obsessive-compulsive disorder. British Journal of Psychiatry, 195, 393–402. https://doi.org/10.1192/bjp.bp.108.055046
Radua, J., & Mataix-Cols, D. (2012). Meta-analytic methods for neuroimaging data explained. Biology of Mood & Anxiety Disorder., 2, 6. https://doi.org/10.1186/2045-5380-2-6
Radua, J., Rubia, K., Canales-Rodríguez, E. J., Pomarol-Clotet, E., Fusar-Poli, P., & Mataix-Cols, D. (2014). Anisotropic kernels for coordinate-based meta-analyses of neuroimaging studies. Front Psychiatry., 5, 13. https://doi.org/10.3389/fpsyt.2014.00013
Renner, F., Siep, N., Arntz, A., van de Ven, V., Peeters, F., Quaedflieg, C., & Huibers, M. J. H. (2017). Negative mood-induction modulates default mode network resting-state functional connectivity in chronic depression. Journal of Affective Disorders, 208, 590–596. https://doi.org/10.1016/j.jad.2016.10.022
Ren, W., Lui, S., Deng, W., Li, F., Li, M., Huang, X., Wang, Y., Li, T., Sweeney, J. A., & Gong, Q. (2013). Anatomical and functional brain abnormalities in drug-naive first-episode schizophrenia. American Journal of Psychiatry, 170, 1308–1316. https://doi.org/10.1176/appi.ajp.2013.12091148
Rogers, M. A., Kasai, K., Koji, M., Fukuda, R., Iwanami, A., Nakagome, K., Fukuda, M., & Kato, N. (2004). Executive and prefrontal dysfunction in unipolar depression: A review of neuropsychological and imaging evidence. Neuroscience Research, 50, 1–11. https://doi.org/10.1016/j.neures.2004.05.003
Sarkheil, P., Odysseos, P., Bee, I., Zvyagintsev, M., Neuner, I., & Mathiak, K. (2020). Functional connectivity of supplementary motor area during finger-tapping in major depression. Comprehensive Psychiatry, 99, 152166. https://doi.org/10.1016/j.comppsych.2020.152166
Satyshur, M. D., Layden, E. A., Gowins, J. R., Buchanan, A., & Gollan, J. K. (2018). Functional connectivity of reflective and brooding rumination in depressed and healthy women. Cognitive, Affective, & Behavioral Neuroscience, 18, 884–901. https://doi.org/10.3758/s13415-018-0611-7
Sheline, Y. I., Barch, D. M., Price, J. L., Rundle, M. M., Vaishnavi, S. N., Snyder, A. Z., Mintun, M. A., Wang, S., Coalson, R. S., & Raichle, M. E. (2009). The default mode network and self-referential processes in depression. Proceeding of the National Academy of Science of the U S A., 106, 1942–1947. https://doi.org/10.1073/pnas.0812686106
Sheline, Y. I., Price, J. L., Yan, Z., & Mintun, M. A. (2010). Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proceeding of the National Academy of Science of the U S A., 107, 11020–11025. https://doi.org/10.1073/pnas.1000446107
Spalding, K. N., Schlichting, M. L., Zeithamova, D., Preston, A. R., Tranel, D., Duff, M. C., & Warren, D. E. (2018). Ventromedial Prefrontal Cortex Is Necessary for Normal Associative Inference and Memory Integration. Journal of Neuroscience, 38, 3767–3775. https://doi.org/10.1523/jneurosci.2501-17.2018
Wang, S., Zhao, Y., Zhang, L., Wang, X., Wang, X., Cheng, B., Luo, K., & Gong, Q. (2019). Stress and the brain: Perceived stress mediates the impact of the superior frontal gyrus spontaneous activity on depressive symptoms in late adolescence. Human Brain Mapping, 40, 4982–4993. https://doi.org/10.1002/hbm.24752
Wang, Z., Yuan, Y., Bai, F., You, J., Li, L., & Zhang, Z. (2012). Abnormal default-mode network in angiotensin converting enzyme D allele carriers with remitted geriatric depression. Behavioural Brain Research, 230, 325–332. https://doi.org/10.1016/j.bbr.2012.02.011
Yang, R., Gao, C., Wu, X., Yang, J., Li, S., & Cheng, H. (2016). Decreased functional connectivity to posterior cingulate cortex in major depressive disorder. Psychiatry Res Neuroimaging, 255, 15–23. https://doi.org/10.1016/j.pscychresns.2016.07.010
Zhang, R., Geng, X., & Lee, T. M. C. (2017). Large-scale functional neural network correlates of response inhibition: An fMRI meta-analysis. Brain Structure & Function, 222, 3973–3990. https://doi.org/10.1007/s00429-017-1443-x
Zhang, R., Kranz, G. S., Zou, W., Deng, Y., Huang, X., Lin, K., & Lee, T. M. C. (2020). Rumination network dysfunction in major depression: A brain connectome study. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 98, 109819. https://doi.org/10.1016/j.pnpbp.2019.109819
Zhang, Y. F., Han, Y., Wang, Y. Z., Zhang, Y. F., Jia, H. X., Jin, E. H., Deng, L. G., & Li, L. (2015). Characterization of resting-state fMRI-derived functional connectivity in patients with deficiency versus excess patterns of major depression. Complementary Therapies in Medicine, 23, 7–13. https://doi.org/10.1016/j.ctim.2014.12.010
Zhou, H. X., Chen, X., Shen, Y. Q., Li, L., Chen, N. X., Zhu, Z. C., Castellanos, F. X., & Yan, C. G. (2020). Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. NeuroImage, 206, 116287. https://doi.org/10.1016/j.neuroimage.2019.116287
Zhu, X., Wang, X., Xiao, J., Liao, J., Zhong, M., Wang, W., & Yao, S. (2012). Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients. Biological Psychiatry, 71, 611–617. https://doi.org/10.1016/j.biopsych.2011.10.035
Acknowledgements
This study was supported by Nature Science Foundation of China (ref: 31900806). The funding organizations played no further role in study design, data collection, analysis and interpretation, and paper writing.
Funding
This study was funded by Nature Science Foundation of China (ref: 31900806).
Author information
Authors and Affiliations
Contributions
The study concepts, study design and integrity of the entire study are guaranteed by ZZ, RZ; RZ designed the study, ZZ researched the literature, extracted and analyzed the data. WL, ML, and RZ wrote the manuscript. YW, XW, YL and RH edited and revised the manuscript.
Corresponding author
Ethics declarations
Ethical approval
The article does not contain any studies with human participants or animals perform by any of the authors.
Consent to Participate
Not applicable.
Consent to Publish
Agree.
Conflict of interest
The authors declare that they have no competing interests.
Additional information
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Zhu, Z., Wang, Y., Lau, W.K.W. et al. Hyperconnectivity between the posterior cingulate and middle frontal and temporal gyrus in depression: Based on functional connectivity meta-analyses. Brain Imaging and Behavior 16, 1538–1551 (2022). https://doi.org/10.1007/s11682-022-00628-7
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11682-022-00628-7