Abstract
Major depressive disorder (MDD) is associated with aberrant function and interaction encompassing large parts of cortical, subcortical and limbic regions that always organized into integrative networks implicated in specific tasks. And cumulative evidence suggests that MDD can be understood as a disorder of dysregulated network. Our study used resting-state fMRI and independent component analysis (ICA) to investigate intrinsic functional connectivity (FC) within and between resting-state networks (RSNs) in 27 drug-free MDD patients and 54 healthy control subjects (HCs). Granger causality analysis (GCA) was further used to identify the direct functional interaction between RSNs. We identified sixteen independent components (ICs) as meaningful RSNs. Compared with HCs, the MDD had significantly decreased intra-FC within lateral visual network (VN), parietal network (PN) and posterior default mode network (pDMN), decreased inter-FC between fronto-parietal network (FPN) and subcortical network, between pDMN and anterior DMN, and increased inter-FC between salience network and FPN, and enhanced effective connectivity from VN to PN and to cerebellum network. The functional synchronization of pDMN was negatively correlated with Hamilton Depression Rating Scores. The relatively small number of MDD, the use of medication and the application challenges of GCA on fMRI data may limit the interpretability. These findings indicated that MDD is indeed a disorder of dysregulated network, especially in the functional networks implicated in self-referential activities and emotional visual processing.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W., Segall, J. M., Silva, R. F., Havlicek, M., Rachakonda, S., Fries, J., Kalyanam, R., Michael, A. M., Caprihan, A., Turner, J. A., Eichele, T., Adelsheim, S., Bryan, A. D., Bustillo, J., Clark, V. P., Feldstein Ewing, S. W., Filbey, F., Ford, C. C., Hutchison, K., Jung, R. E., Kiehl, K. A., Kodituwakku, P., Komesu, Y. M., Mayer, A. R., Pearlson, G. D., Phillips, J. P., Sadek, J. R., Stevens, M., Teuscher, U., Thoma, R. J., & Calhoun, V. D. (2011). A baseline for the multivariate comparison of resting-state networks. Frontiers in Systems Neuroscience, 5, 2. https://doi.org/10.3389/fnsys.2011.00002.
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(4), 550–562. https://doi.org/10.1016/j.neuron.2010.02.005.
Arbabshirani, M. R., Havlicek, M., Kiehl, K. A., Pearlson, G. D., & Calhoun, V. D. (2013). Functional network connectivity during rest and task conditions: a comparative study. Human Brain Mapping, 34(11), 2959–2971. https://doi.org/10.1002/hbm.22118.
Barch, D. M., & Sheffield, J. M. (2014). Cognitive impairments in psychotic disorders: common mechanisms and measurement. World Psychiatry, 13(3), 224–232. https://doi.org/10.1002/wps.20145.
Beauchamp, M. S., Petit, L., Ellmore, T. M., Ingeholm, J., & Haxby, J. V. (2001). A parametric fMRI study of overt and covert shifts of visuospatial attention. Neuroimage, 14(2), 310–321. https://doi.org/10.1006/nimg.2001.0788.
Bell, A. J., & Sejnowski, T. J. (1995). An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7(6), 1129–1159.
Belzung, C., Willner, P., & Philippot, P. (2015). Depression: from psychopathology to pathophysiology. Current Opinion in Neurobiology, 30, 24–30. https://doi.org/10.1016/j.conb.2014.08.013.
Bermpohl, F., Pascual-Leone, A., Amedi, A., Merabet, L. B., Fregni, F., Gaab, N., Alsop, D., Schlaug, G., & Northoff, G. (2006). Dissociable networks for the expectancy and perception of emotional stimuli in the human brain. Neuroimage, 30(2), 588–600. https://doi.org/10.1016/j.neuroimage.2005.09.040.
Brakowski, J., Spinelli, S., Dorig, N., Bosch, O. G., Manoliu, A., Holtforth, M. G., et al. (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.
Brown, E. C., Clark, D. L., Hassel, S., MacQueen, G., & Ramasubbu, R. (2017). Thalamocortical connectivity in major depressive disorder. Journal of Affective Disorders, 217, 125–131. https://doi.org/10.1016/j.jad.2017.04.004.
Calhoun, V. D., & Adali, T. (2012). Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery. IEEE Reviews in Biomedical Engineering, 5, 60–73. https://doi.org/10.1109/RBME.2012.2211076.
Calhoun, V. D., Adali, T., Pearlson, G. D., & Pekar, J. J. (2001). A method for making group inferences from functional MRI data using independent component analysis. Human Brain Mapping, 14(3), 140–151.
Calhoun, V. D., Liu, J., & Adali, T. (2009). A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. Neuroimage, 45(1 Suppl), S163–S172. https://doi.org/10.1016/j.neuroimage.2008.10.057.
Cavanna, A. E., & Trimble, M. R. (2006). The precuneus: a review of its functional anatomy and behavioural correlates. Brain, 129(Pt 3), 564–583. https://doi.org/10.1093/brain/awl004.
Coutinho, J. F., Fernandesl, S. V., Soares, J. M., Maia, L., Goncalves, O. F., & Sampaio, A. (2016). Default mode network dissociation in depressive and anxiety states. Brain Imaging and Behavior, 10(1), 147–157. https://doi.org/10.1007/s11682-015-9375-7.
Damoiseaux, J. S., Rombouts, S. A., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006). Consistent resting-state networks across healthy subjects. Proceedings of the National Academy of Sciences of the United States of America, 103(37), 13848–13853. https://doi.org/10.1073/pnas.0601417103.
Desseilles, M., Balteau, E., Sterpenich, V., Dang-Vu, T. T., Darsaud, A., Vandewalle, G., Albouy, G., Salmon, E., Peters, F., Schmidt, C., Schabus, M., Gais, S., Degueldre, C., Phillips, C., Luxen, A., Ansseau, M., Maquet, P., & Schwartz, S. (2009). Abnormal neural filtering of irrelevant visual information in depression. The Journal of Neuroscience, 29(5), 1395–1403. https://doi.org/10.1523/JNEUROSCI.3341-08.2009.
Desseilles, M., Schwartz, S., Dang-Vu, T. T., Sterpenich, V., Ansseau, M., Maquet, P., & Phillips, C. (2011). Depression alters “top-down” visual attention: a dynamic causal modeling comparison between depressed and healthy subjects. Neuroimage, 54(2), 1662–1668. https://doi.org/10.1016/j.neuroimage.2010.08.061.
Diener, C., Kuehner, C., Brusniak, W., Ubl, B., Wessa, M., & Flor, H. (2012). A meta-analysis of neurofunctional imaging studies of emotion and cognition in major depression. Neuroimage, 61(3), 677–685. https://doi.org/10.1016/j.neuroimage.2012.04.005.
Erhardt, E. B., Rachakonda, S., Bedrick, E. J., Allen, E. A., Adali, T., & Calhoun, V. D. (2011). Comparison of multi-subject ICA methods for analysis of fMRI data. Human Brain Mapping, 32(12), 2075–2095. https://doi.org/10.1002/hbm.21170.
Friston, K., Moran, R., & Seth, A. K. (2013). Analysing connectivity with granger causality and dynamic causal modelling. Current Opinion in Neurobiology, 23(2), 172–178. https://doi.org/10.1016/j.conb.2012.11.010.
Goulden, N., McKie, S., Thomas, E. J., Downey, D., Juhasz, G., Williams, S. R., Rowe, J. B., Deakin, J. F., Anderson, I. M., & Elliott, R. (2012). Reversed frontotemporal connectivity during emotional face processing in remitted depression. Biological Psychiatry, 72(7), 604–611.
Greicius, M. D., Flores, B. H., Menon, V., Glover, G. H., Solvason, H. B., Kenna, H., et al. (2007). Resting-state functional connectivity in major depression: Abnormally increased contributions from subgenual cingulate cortex and thalamus. Biological Psychiatry, 62(5), 429–437. https://doi.org/10.1016/j.biopsych.2006.09.020.
Haber, S. N., & Calzavara, R. (2009). The cortico-basal ganglia integrative network: the role of the thalamus. Brain Research Bulletin, 78(2–3), 69–74. https://doi.org/10.1016/j.brainresbull.2008.09.013.
Hahn, T., Marquand, A. F., Ehlis, A. C., Dresler, T., Kittel-Schneider, S., Jarczok, T. A., et al. (2011). Integrating neurobiological markers of depression. Archives of General Psychiatry, 68(4), 361–368. https://doi.org/10.1001/archgenpsychiatry.2010.178.
Henje Blom, E., Connolly, C. G., Ho, T. C., LeWinn, K. Z., Mobayed, N., Han, L., et al. (2015). Altered insular activation and increased insular functional connectivity during sad and happy face processing in adolescent major depressive disorder. Journal of Affective Disorders, 178, 215–223. https://doi.org/10.1016/j.jad.2015.03.012.
Ho, T. C., Zhang, S., Sacchet, M. D., Weng, H., Connolly, C. G., Henje Blom, E., Han, L. K., Mobayed, N. O., & Yang, T. T. (2016). Fusiform Gyrus dysfunction is associated with perceptual processing efficiency to emotional faces in adolescent depression: a model-based approach. Frontiers in Psychology, 7, 40. https://doi.org/10.3389/fpsyg.2016.00040.
Ikemoto, S., Yang, C., & Tan, A. (2015). Basal ganglia circuit loops, dopamine and motivation: a review and enquiry. Behavioural Brain Research, 290, 17–31. https://doi.org/10.1016/j.bbr.2015.04.018.
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.
Jafri, M. J., Pearlson, G. D., Stevens, M., & Calhoun, V. D. (2008). A method for functional network connectivity among spatially independent resting-state components in schizophrenia. Neuroimage, 39(4), 1666–1681. https://doi.org/10.1016/j.neuroimage.2007.11.001.
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(6), 603–611. https://doi.org/10.1001/jamapsychiatry.2015.0071.
Kober, H., Barrett, L. F., Joseph, J., Bliss-Moreau, E., Lindquist, K., & Wager, T. D. (2008). Functional grouping and cortical-subcortical interactions in emotion: a meta-analysis of neuroimaging studies. Neuroimage, 42(2), 998–1031. https://doi.org/10.1016/j.neuroimage.2008.03.059.
Korgaonkar, M. S., Fornito, A., Williams, L. M., & Grieve, S. M. (2014). Abnormal structural networks characterize major depressive disorder: a connectome analysis. Biological Psychiatry, 76(7), 567–574. https://doi.org/10.1016/j.biopsych.2014.02.018.
Kuniecki, M., Woloszyn, K., Domagalik, A., & Pilarczyk, J. (2018). Disentangling brain activity related to the processing of emotional visual information and emotional arousal. Brain Structure & Function, 223(4), 1589–1597. https://doi.org/10.1007/s00429-017-1576-y.
Laird, A. R., Fox, P. M., Eickhoff, S. B., Turner, J. A., Ray, K. L., McKay, D. R., et al. (2011). Behavioral interpretations of intrinsic connectivity networks. Journal of Cognitive Neuroscience, 23(12), 4022–4037. https://doi.org/10.1162/jocn_a_00077.
Leung, K. K., Lee, T. M., Wong, M. M., Li, L. S., Yip, P. S., & Khong, P. L. (2009). Neural correlates of attention biases of people with major depressive disorder: a voxel-based morphometric study. Psychological Medicine, 39(7), 1097–1106. https://doi.org/10.1017/S0033291708004546.
Liu, Y., Wu, X., Zhang, J., Guo, X., Long, Z., & Yao, L. (2015). Altered effective connectivity model in the default mode network between bipolar and unipolar depression based on resting-state fMRI. Journal of Affective Disorders, 182, 8–17. https://doi.org/10.1016/j.jad.2015.04.009.
Liu, C. H., Ma, X., Yuan, Z., Song, L. P., Jing, B., Lu, H. Y., Tang, L. R., Fan, J., Walter, M., Liu, C. Z., Wang, L., & Wang, C. Y. (2017). Decreased resting-state activity in the Precuneus is associated with depressive episodes in recurrent depression. The Journal of Clinical Psychiatry, 78(4), e372–e382. https://doi.org/10.4088/JCP.15m10022.
Liu, J., Xu, P., Zhang, J., Jiang, N., Li, X., & Luo, Y. (2019). Ventral attention-network effective connectivity predicts individual differences in adolescent depression. Journal of Affective Disorders, 252, 55–59.
Menon, V. (2011). Large-scale brain networks and psychopathology: a unifying triple network model. Trends in Cognitive Sciences, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003.
Mueller, S., Costa, A., Keeser, D., Pogarell, O., Berman, A., Coates, U., Reiser, M. F., Riedel, M., Möller, H. J., Ettinger, U., & Meindl, T. (2014). The effects of methylphenidate on whole brain intrinsic functional connectivity. Human Brain Mapping, 35(11), 5379–5388. https://doi.org/10.1002/hbm.22557.
Mulders, P. C., van Eijndhoven, P. F., Schene, A. H., Beckmann, C. F., & Tendolkar, I. (2015). Resting-state functional connectivity in major depressive disorder: a review. Neuroscience and Biobehavioral Reviews, 56, 330–344. https://doi.org/10.1016/j.neubiorev.2015.07.014.
Passarotti, A. M., Sweeney, J. A., & Pavuluri, M. N. (2009). Neural correlates of incidental and directed facial emotion processing in adolescents and adults. Social Cognitive and Affective Neuroscience, 4(4), 387–398. https://doi.org/10.1093/scan/nsp029.
Peng, D., Liddle, E. B., Iwabuchi, S. J., Zhang, C., Wu, Z., Liu, J., Jiang, K., Xu, L., Liddle, P. F., Palaniyappan, L., & Fang, Y. (2015). Dissociated large-scale functional connectivity networks of the precuneus in medication-naive first-episode depression. Psychiatry Research, 232(3), 250–256. https://doi.org/10.1016/j.pscychresns.2015.03.003.
Rolls, E. T., Cheng, W., Gilson, M., Qiu, J., Hu, Z., Ruan, H., Li, Y., Huang, C. C., Yang, A. C., Tsai, S. J., Zhang, X., Zhuang, K., Lin, C. P., Deco, G., Xie, P., & Feng, J. (2018). Effective connectivity in depression. Biological Psychiatry Cognitive Neuroscience and Neuroimaging, 3(2), 187–197. https://doi.org/10.1016/j.bpsc.2017.10.004.
Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007). Dissociable intrinsic connectivity networks for salience processing and executive control. The Journal of Neuroscience, 27(9), 2349–2356. https://doi.org/10.1523/JNEUROSCI.5587-06.2007.
Selemon, L. D., & Goldman-Rakic, P. S. (1988). Common cortical and subcortical targets of the dorsolateral prefrontal and posterior parietal cortices in the rhesus monkey: evidence for a distributed neural network subserving spatially guided behavior. The Journal of Neuroscience, 8(11), 4049–4068.
Seth, A. K. (2010). A MATLAB toolbox for granger causal connectivity analysis. Journal of Neuroscience Methods, 186(2), 262–273. https://doi.org/10.1016/j.jneumeth.2009.11.020.
Seth, A. K., Barrett, A. B., & Barnett, L. (2015). Granger causality analysis in neuroscience and neuroimaging. The Journal of Neuroscience, 35(8), 3293–3297. https://doi.org/10.1523/JNEUROSCI.4399-14.2015.
Sun, H., Luo, L., Yuan, X., Zhang, L., He, Y., Yao, S., Wang, J., & Xiao, J. (2018). Regional homogeneity and functional connectivity patterns in major depressive disorder, cognitive vulnerability to depression and healthy subjects. Journal of Affective Disorders, 235, 229–235. https://doi.org/10.1016/j.jad.2018.04.061.
Valdes-Sosa, P. A., Roebroeck, A., Daunizeau, J., & Friston, K. (2011). Effective connectivity: influence, causality and biophysical modeling. Neuroimage, 58(2), 339–361. https://doi.org/10.1016/j.neuroimage.2011.03.058.
van den Heuvel, M. P., & Hulshoff Pol, H. E. (2010). Exploring the brain network: a review on resting-state fMRI functional connectivity. European Neuropsychopharmacology, 20(8), 519–534. https://doi.org/10.1016/j.euroneuro.2010.03.008.
Wager, T. D., Davidson, M. L., Hughes, B. L., Lindquist, M. A., & Ochsner, K. N. (2008). Prefrontal-subcortical pathways mediating successful emotion regulation. Neuron, 59(6), 1037–1050. https://doi.org/10.1016/j.neuron.2008.09.006.
Wang, L., Hermens, D. F., Hickie, I. B., & Lagopoulos, J. (2012). A systematic review of resting-state functional-MRI studies in major depression. Journal of Affective Disorders, 142(1–3), 6–12. https://doi.org/10.1016/j.jad.2012.04.013.
Wang, C., Liu, B., Long, H., Fan, L., Li, J., Zhang, X., Qiu, C., Yu, C., & Jiang, T. (2015). Epistatic interaction of BDNF and COMT on the frontostriatal system. Neuroscience, 298, 380–388. https://doi.org/10.1016/j.neuroscience.2015.04.014.
Wang, J., Wei, Q., Bai, T., Zhou, X., Sun, H., Becker, B., Tian, Y., Wang, K., & Kendrick, K. (2017a). Electroconvulsive therapy selectively enhanced feedforward connectivity from fusiform face area to amygdala in major depressive disorder. Social Cognitive and Affective Neuroscience, 12(12), 1983–1992. https://doi.org/10.1093/scan/nsx100.
Wang, J., Wei, Q., Yuan, X., Jiang, X., Xu, J., Zhou, X., et al. (2017b). Local functional connectivity density is closely associated with the response of electroconvulsive therapy in major depressive disorder. Journal of Affective Disorders, 225, 658–664. https://doi.org/10.1016/j.jad.2017.09.001.
Wang, J., Xie, S., Guo, X., Becker, B., Fox, P. T., Eickhoff, S. B., & Jiang, T. (2017c). Correspondent functional topography of the human left inferior parietal lobule at rest and under task revealed using resting-state fMRI and coactivation based parcellation. Human Brain Mapping, 38(3), 1659–1675. https://doi.org/10.1002/hbm.23488.
Wang, C., Wu, H., Chen, F., Xu, J., Li, H., Li, H., & Wang, J. (2018a). Disrupted functional connectivity patterns of the insula subregions in drug-free major depressive disorder. Journal of Affective Disorders, 234, 297–304. https://doi.org/10.1016/j.jad.2017.12.033.
Wang, J., Wei, Q., Wang, L., Zhang, H., Bai, T., Cheng, L., Tian, Y., & Wang, K. (2018b). Functional reorganization of intra- and internetwork connectivity in major depressive disorder after electroconvulsive therapy. Human Brain Mapping, 39(3), 1403–1411. https://doi.org/10.1002/hbm.23928.
Wang, J., Becker, B., Wang, L., Li, H., Zhao, X., & Jiang, T. (2019a). Corresponding anatomical and coactivation architecture of the human precuneus showing similar connectivity patterns with macaques. Neuroimage, 200, 562–574. https://doi.org/10.1016/j.neuroimage.2019.07.001.
Wang, L., Wei, Q., Wang, C., Xu, J., Wang, K., Tian, Y., & Wang, J. (2019b). Altered functional connectivity patterns of insular subregions in major depressive disorder after electroconvulsive therapy. Brain Imaging and Behavior, 1–9. https://doi.org/10.1007/s11682-018-0013-z.
Wu, H., Sun, H., Xu, J., Wu, Y., Wang, C., Xiao, J., She, S., Huang, J., Zou, W., Peng, H., Lu, X., Huang, G., Jiang, T., Ning, Y., & Wang, J. (2016). Changed hub and corresponding functional connectivity of subgenual anterior cingulate cortex in major depressive disorder. Frontiers in Neuroanatomy, 10, 120. https://doi.org/10.3389/fnana.2016.00120.
Yuksel, D., Dietsche, B., Forstner, A. J., Witt, S. H., Maier, R., Rietschel, M., et al. (2017). Polygenic risk for depression and the neural correlates of working memory in healthy subjects. Progress in Neuropsychopharmacology and Biological Psychiatry, 79(Pt B), 67–76. https://doi.org/10.1016/j.pnpbp.2017.06.010.
Zeng, L. L., Shen, H., Liu, L., Wang, L., Li, B., Fang, P., Zhou, Z., Li, Y., & Hu, D. (2012). Identifying major depression using whole-brain functional connectivity: a multivariate pattern analysis. Brain, 135(Pt 5), 1498–1507. https://doi.org/10.1093/brain/aws059.
Zhang, L., Wu, H., Xu, J., & Shang, J. (2018). Abnormal global functional connectivity patterns in medication-free major depressive disorder. Frontiers in Neuroscience, 12, 692. https://doi.org/10.3389/fnins.2018.00692.
Zhi, D., Calhoun, V. D., Lv, L., Ma, X., Ke, Q., Fu, Z., du, Y., Yang, Y., Yang, X., Pan, M., Qi, S., Jiang, R., Yu, Q., & Sui, J. (2018). Aberrant dynamic functional network connectivity and graph properties in major depressive disorder. Frontiers in Psychiatry, 9, 339. https://doi.org/10.3389/fpsyt.2018.00339.
Zhong, X., Shi, H., Ming, Q., Dong, D., Zhang, X., Zeng, L. L., & Yao, S. (2017). Whole-brain resting-state functional connectivity identified major depressive disorder: a multivariate pattern analysis in two independent samples. Journal of Affective Disorders, 218, 346–352. https://doi.org/10.1016/j.jad.2017.04.040.
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(7), 611–617. https://doi.org/10.1016/j.biopsych.2011.10.035.
Acknowledgements
This work was financially supported in part by grants from the National Natural Science Foundation of China (Grants 31600920 and 31500867), the Shenzhen Basic Research Project (JCYJ2017081802123707), the Natural Science Foundation of Guangdong (2017A03031037), the Science and Technology Program of Guangzhou (201807010064), the Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions (2019SHIBS0003) and the National Natural Science Foundation of China (Grant no. 31771223) awarded to Prof. Jing Xiao.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest and disclosure
The authors declare that they have no competing financial interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
ESM 1
(DOCX 158 kb)
Rights and permissions
About this article
Cite this article
Luo, L., Wu, H., Xu, J. et al. Abnormal large-scale resting-state functional networks in drug-free major depressive disorder. Brain Imaging and Behavior 15, 96–106 (2021). https://doi.org/10.1007/s11682-019-00236-y
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11682-019-00236-y