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Dynamic structure–function coupling across three major psychiatric disorders

Published online by Cambridge University Press:  12 December 2023

Zhe Zhang Open the ORCID record for Zhe Zhang [Opens in a new window] ,
Wei Wei ,
Sujie Wang ,
Mingli Li ,
Xiaojing Li ,
Xiaoyu Li ,
Qiang Wang ,
Hua Yu ,
Yamin Zhang  and
Wanjun Guo
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Zhe Zhang
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China School of Physics, Hangzhou Normal University, Hangzhou, China Institute of Brain Science, School of Basic Medical Sciences, Hangzhou Normal University, Hangzhou, China
Wei Wei
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
Sujie Wang
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
Mingli Li
Affiliation:
Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
Xiaojing Li
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
Xiaoyu Li
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China
Qiang Wang
Affiliation:
Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
Hua Yu
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
Yamin Zhang
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
Wanjun Guo
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
Xiaohong Ma
Affiliation:
Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
Liansheng Zhao
Affiliation:
Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu, China
Wei Deng
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
Pak C Sham
Affiliation:
Department of Psychiatry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China Centre for PanorOmic Sciences, The University of Hong Kong, Hong Kong SAR, China State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, China
Yu Sun*
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
Tao Li*
Affiliation:
Department of Biomedical Engineering, & Department of Neurobiology, Key Laboratory for Biomedical Engineering of Ministry of Education, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University, Hangzhou, China Translational Psychiatry Research Laboratory, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou, China Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, China
*
Corresponding author: Yu Sun; Email: yusun@zju.edu.cn; Tao Li; Email: litaozjusc@zju.edu.cn
Corresponding author: Yu Sun; Email: yusun@zju.edu.cn; Tao Li; Email: litaozjusc@zju.edu.cn
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Abstract

Background

Convergent evidence has suggested atypical relationships between brain structure and function in major psychiatric disorders, yet how the abnormal patterns coincide and/or differ across different disorders remains largely unknown. Here, we aim to investigate the common and/or unique dynamic structure–function coupling patterns across major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SZ).

Methods

We quantified the dynamic structure–function coupling in 452 patients with psychiatric disorders (MDD/BD/SZ = 166/168/118) and 205 unaffected controls at three distinct brain network levels, such as global, meso-, and local levels. We also correlated dynamic structure–function coupling with the topological features of functional networks to examine how the structure–function relationship facilitates brain information communication over time.

Results

The dynamic structure–function coupling is preserved for the three disorders at the global network level. Similar abnormalities in the rich-club organization are found in two distinct functional configuration states at the meso-level and are associated with the disease severity of MDD, BD, and SZ. At the local level, shared and unique alterations are observed in the brain regions involving the visual, cognitive control, and default mode networks. In addition, the relationships between structure–function coupling and the topological features of functional networks are altered in a manner indicative of state specificity.

Conclusions

These findings suggest both transdiagnostic and illness-specific alterations in the dynamic structure–function relationship of large-scale brain networks across MDD, BD, and SZ, providing new insights and potential biomarkers into the neurodevelopmental basis underlying the behavioral and cognitive deficits observed in these disorders.

Keywords

brain networksbipolar disordercognitive deficitsdynamic statesillness-specificmajor depressive disorderneurodevelopmentpsychiatric disordersrich-club organizationschizophreniastructure–function couplingtransdiagnostic
Type
Original Article
Information
Psychological Medicine , First View , pp. 1 - 12
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Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

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Footnotes

*

These authors contributed equally to this work.

References

Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2014). Tracking whole-brain connectivity dynamics in the resting state. Cerebral Cortex, 24(3), 663–676. https://doi.org/10.1093/cercor/bhs352.CrossRefGoogle ScholarPubMed
Baum, G. L., Ciric, R., Roalf, D. R., Betzel, R. F., Moore, T. M., Shinohara, R. T., … Satterthwaite, T. D. (2017). Modular segregation of structural brain networks supports the development of executive function in youth. Current Biology, 27(11), 1561–1572. https://doi.org/10.1016/j.cub.2017.04.051.CrossRefGoogle ScholarPubMed
Baum, G. L., Cui, Z., Roalf, D. R., Ciric, R., Betzel, R. F., Larsen, B., … Satterthwaite, T. D. (2020). Development of structure-function coupling in human brain networks during youth. Proceedings of the National Academy of Sciences, 117(1), 771–778. https://doi.org/10.1073/pnas.1912034117.CrossRefGoogle ScholarPubMed
Becker, C. O., Pequito, S., Pappas, G. J., Miller, M. B., Grafton, S. T., Bassett, D. S., & Preciado, V. M. (2018). Spectral mapping of brain functional connectivity from diffusion imaging. Scientific Reports, 8, 1411. https://doi.org/10.1038/s41598-017-18769-x.CrossRefGoogle ScholarPubMed
Berman, R. A., Gotts, S. J., McAdams, H. M., Greenstein, D., Lalonde, F., Clasen, L., … Rapoport, J. (2016). Disrupted sensorimotor and social-cognitive networks underlie symptoms in childhood-onset schizophrenia. Brain, 139, 276–291. https://doi.org/10.1093/brain/awv306.CrossRefGoogle ScholarPubMed
Buckner, R. L., Andrews-Hanna, J. R., & Schacter, D. L. (2008). The brain's default network - Anatomy, function, and relevance to disease. Annals of the New York Academy of Sciences, 1124, 1–38. https://doi.org/10.1196/annals.1440.011.CrossRefGoogle ScholarPubMed
Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186–198. https://doi.org/10.1038/nrn2575.CrossRefGoogle ScholarPubMed
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. https://doi.org/10.1002/hbm.1048.CrossRefGoogle ScholarPubMed
Calhoun, V. D., Miller, R., Pearlson, G., & Adali, T. (2014). The chronnectome: Time-varying connectivity networks as the next frontier in fMRI data discovery. Neuron, 84(2), 262–274. https://doi.org/10.1016/j.neuron.2014.10.015.CrossRefGoogle ScholarPubMed
Cavanna, A. E., & Trimble, M. R. (2006). The precuneus: A review of its functional anatomy and behavioural correlates. Brain, 129(3), 564–583. https://doi.org/10.1093/brain/awl004.CrossRefGoogle ScholarPubMed
Chana, G., Landau, S., Beasley, C., Everall, I. P., & Cotter, D. (2003). Two-dimensional assessment of cytoarchitecture in the anterior cingulate cortex in major depressive disorder, bipolar disorder, and schizophrenia: Evidence for decreased neuronal somal size and increased neuronal density. Biological Psychiatry, 53(12), 1086–1098. https://doi.org/10.1016/s0006-3223(03)00114-8.CrossRefGoogle ScholarPubMed
Chand, G. B., Dwyer, D. B., Erus, G., Sotiras, A., Varol, E., Srinivasan, D., … Davatzikos, C. (2020). Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning. Brain, 143(3), 1027–1038. https://doi.org/10.1093/brain/awaa025.CrossRefGoogle ScholarPubMed
Collin, G., Scholtens, L. H., Kahn, R. S., Hillegers, M. H. J., & van den Heuvel, M. P. (2017). Affected anatomical rich club and structural–functional coupling in young offspring of schizophrenia and bipolar disorder patients. Biological Psychiatry, 82(10), 746–755. https://doi.org/10.1016/j.biopsych.2017.06.013.CrossRefGoogle ScholarPubMed
Crofts, J. J., & Higham, D. J. (2009). A weighted communicability measure applied to complex brain networks. Journal of the Royal Society Interface, 6(33), 411–414. https://doi.org/10.1098/rsif.2008.0484.CrossRefGoogle ScholarPubMed
Cross-Disorder Group of the Psychiatric Genomics Consortium. (2013a). Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs. Nature Genetics, 45(9), 984–994. https://doi.org/10.1038/ng.2711.CrossRefGoogle Scholar
Cross-Disorder Group of the Psychiatric Genomics Consortium. (2013b). Identification of risk loci with shared effects on five major psychiatric disorders: A genome-wide analysis. The Lancet, 381(9875), 1371–1379. https://doi.org/10.1016/s0140-6736(12)62129-1.CrossRefGoogle Scholar
Cui, L. B., Wei, Y., Xi, Y. B., Griffa, A., De Lange, S. C., Kahn, R. S., … Van den Heuvel, M. P. (2019). Connectome-based patterns of first-episode medication-naive patients with schizophrenia. Schizophrenia Bulletin, 45(6), 1291–1299. https://doi.org/10.1093/schbul/sbz014.CrossRefGoogle ScholarPubMed
Delavari, F., Sandini, C., Zöller, D., Mancini, V., Bortolin, K., Schneider, M., … Eliez, S. (2021). Dysmaturation observed as altered hippocampal functional connectivity at rest is associated with the emergence of positive psychotic symptoms in patients with 22q11 deletion syndrome. Biological Psychiatry, 90(1), 58–68. https://doi.org/10.1016/j.biopsych.2020.12.033.CrossRefGoogle ScholarPubMed
Di Martino, A., Fair, D. A., Kelly, C., Satterthwaite, T. D., Castellanos, F. X., Thomason, M. E., … Milham, M. P. (2014). Unraveling the miswired connectome: A developmental perspective. Neuron, 83(6), 1335–1353. https://doi.org/10.1016/j.neuron.2014.08.050.CrossRefGoogle ScholarPubMed
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., … Liston, C. (2017). Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nature Medicine, 23(1), 28–38. https://doi.org/10.1038/nm.4246.CrossRefGoogle ScholarPubMed
Du, Y., Fryer, S. L., Fu, Z., Lin, D., Sui, J., Chen, J., … Calhoun, V. D. (2018). Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis. Neuroimage, 180, 632–645. https://doi.org/10.1016/j.neuroimage.2017.10.022.CrossRefGoogle ScholarPubMed
Elvsashagen, T., Shadrin, A., Frei, O., van der Meer, D., Bahrami, S., Kumar, V. J., … Kaufmann, T. (2021). The genetic architecture of the human thalamus and its overlap with ten common brain disorders. Nature Communications, 12(1), 2909. https://doi.org/10.1038/s41467-021-23175-z.CrossRefGoogle ScholarPubMed
Fiorenzato, E., Strafella, A. P., Kim, J., Schifano, R., Weis, L., Antonini, A., & Biundo, R. (2019). Dynamic functional connectivity changes associated with dementia in Parkinson's disease. Brain, 142(9), 2860–2872. https://doi.org/10.1093/brain/awz192.CrossRefGoogle ScholarPubMed
Fukushima, M., Betzel, R. F., He, Y., van den Heuvel, M. P., Zuo, X. N., & Sporns, O. (2018). Structure–function relationships during segregated and integrated network states of human brain functional connectivity. Brain Structure and Function, 223(3), 1091–1106. https://doi.org/10.1007/s00429-017-1539-3.CrossRefGoogle ScholarPubMed
Grayson, D. S., Ray, S., Carpenter, S., Iyer, S., Dias, T. G., Stevens, C., … Fair, D. A. (2014). Structural and functional rich club organization of the brain in children and adults. PLoS One, 9(2), e88297. https://doi.org/10.1371/journal.pone.0088297.CrossRefGoogle ScholarPubMed
Gu, Z., Jamison, K. W., Sabuncu, M. R., & Kuceyeski, A. (2021). Heritability and interindividual variability of regional structure–function coupling. Nature Communications, 12(1), 4894. https://doi.org/10.1038/s41467-021-25184-4.CrossRefGoogle ScholarPubMed
Hampson, M., Driesen, N., Roth, J. K., Gore, J. C., & Constable, R. T. (2010). Functional connectivity between task-positive and task-negative brain areas and its relation to working memory performance. Magnetic Resonance Imaging, 28(8), 1051–1057. https://doi.org/10.1016/j.mri.2010.03.021.CrossRefGoogle ScholarPubMed
Honey, C. J., Sporns, O., Cammoun, L., Gigandet, X., Thiran, J. P., Meuli, R., & Hagmann, P. (2009). Predicting human resting-state functional connectivity from structural connectivity. Proceedings of the National Academy of Sciences, 106(6), 2035–2040. https://doi.org/10.1073/pnas.0811168106.CrossRefGoogle ScholarPubMed
Huang, C. C., Luo, Q., Palaniyappan, L., Yang, A. C., Hung, C. C., Chou, K. H., … Robbins, T. W. (2020). Transdiagnostic and illness-specific functional dysconnectivity across schizophrenia, bipolar disorder, and major depressive disorder. Biological Psychiatry-Cognitive Neuroscience and Neuroimaging, 5(5), 542–553. https://doi.org/10.1016/j.bpsc.2020.01.010.CrossRefGoogle ScholarPubMed
Huang, Y., Wang, Y., Wang, H., Liu, Z., Yu, X., Yan, J., … Wu, Y. (2019). Prevalence of mental disorders in China: A cross-sectional epidemiological study. The Lancet Psychiatry, 6(3), 211–224. https://doi.org/10.1016/s2215-0366(18)30511-x.CrossRefGoogle Scholar
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., … Wang, P. (2010). Research domain criteria (RDoC): Toward a new classification framework for research on mental disorders. American Journal of psychiatry, 167(7), 748–751. https://doi.org/10.1176/appi.ajp.2010.09091379.CrossRefGoogle Scholar
Jiang, X. Y., Shen, Y. D., Yao, J. S., Zhang, L., Xu, L. Y., Feng, R., … Wang, J. H. (2019). Connectome analysis of functional and structural hemispheric brain networks in major depressive disorder. Translational Psychiatry, 9, 136. https://doi.org/10.1038/s41398-019-0467-9.CrossRefGoogle ScholarPubMed
Jones, D. K., Knösche, T. R., & Turner, R. (2013). White matter integrity, fiber count, and other fallacies: The do's and don'ts of diffusion MRI. Neuroimage, 73, 239–254. https://doi.org/10.1016/j.neuroimage.2012.06.081.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Khalsa, S., Mayhew, S. D., Chechlacz, M., Bagary, M., & Bagshaw, A. P. (2014). The structural and functional connectivity of the posterior cingulate cortex: Comparison between deterministic and probabilistic tractography for the investigation of structure–function relationships. Neuroimage, 102, 118–127. https://doi.org/10.1016/j.neuroimage.2013.12.022.CrossRefGoogle ScholarPubMed
Kim, J., Criaud, M., Cho, S. S., Díez-Cirarda, M., Mihaescu, A., Coakeley, S., … Strafella, A. P. (2017). Abnormal intrinsic brain functional network dynamics in Parkinson's disease. Brain, 140, 2955–2967. https://doi.org/10.1093/brain/awx233.CrossRefGoogle ScholarPubMed
Kim, N. Y., Hsu, J., Talmasov, D., Joutsa, J., Soussand, L., Wu, O., … Fox, M. D. (2019). Lesions causing hallucinations localize to one common brain network. Molecular Psychiatry, 26(4), 1299–1309. https://doi.org/10.1038/s41380-019-0565-3.CrossRefGoogle ScholarPubMed
Koshiyama, D., Fukunaga, M., Okada, N., Morita, K., Nemoto, K., Usui, K., … Hashimoto, R. (2019). White matter microstructural alterations across four major psychiatric disorders: Mega-analysis study in 2937 individuals. Molecular Psychiatry, 25(4), 883–895. https://doi.org/10.1038/s41380-019-0553-7.CrossRefGoogle ScholarPubMed
Kulik, S. D., Nauta, I. M., Tewarie, P., Koubiyr, I., Van Dellen, E., Ruet, A., … Schoonheim, M. M. (2022). Structure–function coupling as a correlate and potential biomarker of cognitive impairment in multiple sclerosis. Network Neuroscience, 6(2), 339–356. https://doi.org/10.1162/netn_a_00226.CrossRefGoogle ScholarPubMed
Liu, F., Wang, Y., Li, M., Wang, W., Li, R., Zhang, Z., … Chen, H. (2017). Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic–clonic seizure. Human Brain Mapping, 38(2), 957–973. https://doi.org/10.1002/hbm.23430.CrossRefGoogle ScholarPubMed
Liu, X. Y., He, C. C., Fan, D. D., Zang, F. F., Zhu, Y., Zhang, H. S., … Xie, C. M. (2021). Alterations of core structural network connectome associated with suicidal ideation in major depressive disorder patients. Translational Psychiatry, 11, 243. https://doi.org/10.1038/s41398-021-01353-3.CrossRefGoogle ScholarPubMed
Liu, Z. Q., Vázquez-Rodríguez, B., Spreng, R. N., Bernhardt, B. C., Betzel, R. F., & Misic, B. (2022). Time-resolved structure–function coupling in brain networks. Communications Biology, 5, 532. https://doi.org/10.1038/s42003-022-03466-x.CrossRefGoogle Scholar
Ma, Q., Tang, Y. Q., Wang, F., Liao, X. H., Jiang, X. W., Wei, S. N., … Xia, M. R. (2020). Transdiagnostic dysfunctions in brain modules across patients with schizophrenia, bipolar disorder, and major depressive disorder: A connectome-based study. Schizophrenia Bulletin, 46(3), 699–712. https://doi.org/10.1093/schbul/sbz111.CrossRefGoogle ScholarPubMed
Margulies, D. S., Ghosh, S. S., Goulas, A., Falkiewicz, M., Huntenburg, J. M., Langs, G., … Smallwood, J. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences, 113(44), 12574–12579. https://doi.org/10.1073/pnas.1608282113.CrossRefGoogle ScholarPubMed
Marshall, M. (2020). The hidden links between mental disorders. Nature, 581(7806), 19–22. https://link.gale.com/apps/doc/A622823168/HRCA?.CrossRefGoogle ScholarPubMed
McGuinness, A. J., Davis, J. A., Dawson, S. L., Loughman, A., Collier, F., O'Hely, M., … Jacka, F. N. (2022). A systematic review of gut microbiota composition in observational studies of major depressive disorder, bipolar disorder and schizophrenia. Molecular Psychiatry, 27(4), 1920–1935. https://doi.org/10.1038/s41380-022-01456-3.CrossRefGoogle ScholarPubMed
McNabb, C. B., Tait, R. J., McIlwain, M. E., Anderson, V. M., Suckling, J., Kydd, R. R., & Russell, B. R. (2018). Functional network dysconnectivity as a biomarker of treatment resistance in schizophrenia. Schizophrenia Research, 195, 160–167. https://doi.org/10.1016/j.schres.2017.10.015.CrossRefGoogle ScholarPubMed
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.CrossRefGoogle ScholarPubMed
Misic, B., Betzel, R. F., de Reus, M. A., van den Heuvel, M. P., Berman, M. G., McIntosh, A. R., & Sporns, O. (2016). Network-Level structure–function relationships in human neocortex. Cerebral Cortex, 26(7), 3285–3296. https://doi.org/10.1093/cercor/bhw089.CrossRefGoogle ScholarPubMed
Murray, C. J. L., Vos, T., Lozano, R., Naghavi, M., Flaxman, A. D., Michaud, C., … Lopez, A. D. (2012). Disability-adjusted life years (DALYs) for 291 diseases and injuries in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet (London, England), 380(9859), 2197–2223. https://doi.org/10.1016/S0140-6736(12)61689-4.CrossRefGoogle ScholarPubMed
Northoff, G., & Duncan, N. W. (2016). How do abnormalities in the brain's spontaneous activity translate into symptoms in schizophrenia? From an overview of resting state activity findings to a proposed spatiotemporal psychopathology. Progress in Neurobiology, 145–146, 26–45. https://doi.org/10.1016/j.pneurobio.2016.08.003.CrossRefGoogle ScholarPubMed
Northoff, G., Magioncalda, P., Martino, M., Lee, H. C., Tseng, Y. C., & Lane, T. (2018). Too fast or too slow? Time and neuronal variability in bipolar disorder—A combined theoretical and empirical investigation. Schizophrenia Bulletin, 44(1), 54–64. https://doi.org/10.1093/schbul/sbx050.CrossRefGoogle ScholarPubMed
Paus, T., Pesaresi, M., & French, L. (2014). White matter as a transport system. Neuroscience, 276, 117–125. https://doi.org/10.1016/j.neuroscience.2014.01.055.CrossRefGoogle ScholarPubMed
Rashid, B., Damaraju, E., Pearlson, G. D., & Calhoun, V. D. (2014). Dynamic connectivity states estimated from resting fMRI identify differences among Schizophrenia, bipolar disorder, and healthy control subjects. Frontiers in Human Neuroscience, 8, 897. https://doi.org/10.3389/fnhum.2014.00897.CrossRefGoogle ScholarPubMed
Reinen, J. M., Chén, O. Y., Hutchison, R. M., Yeo, B. T. T., Anderson, K. M., Sabuncu, M. R., … Holmes, A. J. (2018). The human cortex possesses a reconfigurable dynamic network architecture that is disrupted in psychosis. Nature Communications, 9, 1157. https://doi.org/10.1038/s41467-018-03462-y.CrossRefGoogle ScholarPubMed
Repple, J., Gruber, M., Mauritz, M., de Lange, S. C., Winter, N. R., Opel, N., … Dannlowski, U. (2023). Shared and specific patterns of structural brain connectivity across affective and psychotic disorders. Biological Psychiatry, 93(2), 178–186. https://doi.org/10.1016/j.biopsych.2022.05.031.CrossRefGoogle ScholarPubMed
Rizzolatti, G., & Matelli, M. (2003). Two different streams form the dorsal visual system: Anatomy and functions. Experimental Brain Research, 153(2), 146–157. https://doi.org/10.1007/s00221-003-1588-0.CrossRefGoogle ScholarPubMed
Rosenthal, G., Vasa, F., Griffa, A., Hagmann, P., Amico, E., Goni, J., … Sporns, O. (2018). Mapping higher-order relations between brain structure and function with embedded vector representations of connectomes. Nature Communications, 9(1), 2178. https://doi.org/10.1038/s41467-018-04614-w.CrossRefGoogle ScholarPubMed
Sheffield, J. M., Kandala, S., Tamminga, C. A., Pearlson, G. D., Keshavan, M. S., Sweeney, J. A., … Barch, D. M. (2017). Transdiagnostic associations between functional brain network integrity and cognition. JAMA Psychiatry, 74(6), 605–613. https://doi.org/10.1001/jamapsychiatry.2017.0669.CrossRefGoogle ScholarPubMed
Silbereis, J. C., Pochareddy, S., Zhu, Y., Li, M. F., & Sestan, N. (2016). The cellular and molecular landscapes of the developing human central nervous system. Neuron, 89(2), 248–268. https://doi.org/10.1016/j.neuron.2015.12.008.CrossRefGoogle ScholarPubMed
Stephan, K. E., Baldeweg, T., & Friston, K. J. (2006). Synaptic plasticity and dysconnection in schizophrenia. Biological Psychiatry, 59(10), 929–939. https://doi.org/10.1016/j.biopsych.2005.10.005.CrossRefGoogle ScholarPubMed
Suarez, L. E., Markello, R. D., Betzel, R. F., & Misic, B. (2020). Linking structure and function in macroscale brain networks. Trends in Cognitive Sciences, 24(4), 302–315. https://doi.org/10.1016/j.tics.2020.01.008.CrossRefGoogle ScholarPubMed
Suárez, L. E., Richards, B. A., Lajoie, G., & Misic, B. (2021). Learning function from structure in neuromorphic networks. Nature Machine Intelligence, 3(9), 771–786. https://doi.org/10.1038/s42256-021-00376-1.CrossRefGoogle Scholar
Tu, P. C., Bai, Y. M., Li, C. T., Chen, M. H., Lin, W. C., Chang, W. C., & Su, T. P. (2019a). Identification of common thalamocortical dysconnectivity in four major psychiatric disorders. Schizophrenia Bulletin, 45(5), 1143–1151. https://doi.org/10.1093/schbul/sby166.CrossRefGoogle ScholarPubMed
Tu, P. C., Chen, M. H., Chang, W. C., Kao, Z. K., Hsu, J. W., Lin, W. C., … Bai, Y. M. (2020a). Identification of common neural substrates with connectomic abnormalities in four major psychiatric disorders: A connectome-wide association study. European Psychiatry, 64(1), e8, 1–9. https://doi.org/10.1192/j.eurpsy.2020.106.Google ScholarPubMed
Tu, Y., Fu, Z., Mao, C., Falahpour, M., Gollub, R. L., Park, J., … Kong, J. (2020b). Distinct thalamocortical network dynamics are associated with the pathophysiology of chronic low back pain. Nature Communications, 11(1), 3948. https://doi.org/10.1038/s41467-020-17788-z.CrossRefGoogle ScholarPubMed
Tu, Y., Fu, Z., Zeng, F., Maleki, N., Lan, L., Li, Z., … Kong, J. (2019b). Abnormal thalamocortical network dynamics in migraine. Neurology, 92(23), e2706–e2716. https://doi.org/10.1212/WNL.0000000000007607.CrossRefGoogle ScholarPubMed
van den Heuvel, M. P., Kahn, R. S., Goni, J., & Sporns, O. (2012). High-cost, high-capacity backbone for global brain communication. Proceedings of the National Academy of Sciences, 109(28), 11372–11377. https://doi.org/10.1073/pnas.1203593109.CrossRefGoogle ScholarPubMed
van den Heuvel, M. P., Sporns, O., Collin, G., Scheewe, T., Mandl, R. C., Cahn, W., … Kahn, R. S. (2013). Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry, 70(8), 783–792. https://doi.org/10.1001/jamapsychiatry.2013.1328.CrossRefGoogle ScholarPubMed
Vazquez-Rodriguez, B., Suarez, L. E., Markello, R. D., Shafiei, G., Paquola, C., Hagmann, P., … Misic, B. (2019). Gradients of structure–function tethering across neocortex. Proceedings of the National Academy of Sciences, 116(42), 21219–21227. https://doi.org/10.1073/pnas.1903403116.CrossRefGoogle ScholarPubMed
Wang, H., Wu, H.-J., Liu, Y.-Y., & Lü, L. (2021). Higher-order interaction of brain microstructural and functional connectome. bioRxiv. https://doi.org/10.1101/2021.11.11.467196.Google Scholar
Wang, S., Gong, G., Zhong, S., Duan, J., Yin, Z., Chang, M., … Wang, F. (2020). Neurobiological commonalities and distinctions among 3 major psychiatric disorders: A graph theoretical analysis of the structural connectome. Journal of Psychiatry and Neuroscience, 45(1), 15–22. https://doi.org/10.1503/jpn.180162.CrossRefGoogle ScholarPubMed
Wei, Y. E., Chang, M., Fay, Y. W., Zhou, Q., Yin, Z. Y., Wei, S. N., … Wang, F. (2018). Local functional connectivity alterations in schizophrenia, bipolar disorder, and major depressive disorder. Journal of Affective Disorders, 236, 266–273. https://doi.org/10.1016/j.jad.2018.04.069.CrossRefGoogle ScholarPubMed
Whitfield-Gabrieli, S., & Ford, J. M. (2012). Default mode network activity and connectivity in psychopathology. Annual Review of Clinical Psychology, 8, 49–76. https://doi.org/10.1146/annurev-clinpsy-032511-143049.CrossRefGoogle ScholarPubMed
Wolfers, T., Doan, N. T., Kaufmann, T., Alnaes, D., Moberget, T., Agartz, I., … Marquand, A. F. (2018). Mapping the heterogeneous phenotype of schizophrenia and bipolar disorder using normative models. JAMA Psychiatry, 75(11), 1146–1155. https://doi.org/10.1001/jamapsychiatry.2018.2467.CrossRefGoogle ScholarPubMed
Wu, D. Y., Fan, L. Z., Song, M., Wang, H. Y., Chu, C. Y., Yu, S., & Jiang, T. Z. (2020). Hierarchy of connectivity–function relationship of the human cortex revealed through predicting activity across functional domains. Cerebral Cortex, 30(8), 4607–4616. https://doi.org/10.1093/cercor/bhaa063.CrossRefGoogle ScholarPubMed
Xie, C., Xiang, S., Shen, C., Peng, X., Kang, J., Li, Y., … Consortium, Z. I. B. (2023). A shared neural basis underlying psychiatric comorbidity. Nature Medicine, 29(5), 1232–1242. https://doi.org/10.1038/s41591-023-02317-4.CrossRefGoogle ScholarPubMed
Yang, H., Chen, X., Chen, Z. B., Li, L., Li, X. Y., Castellanos, F. X., … Yan, C. G. (2021a). Disrupted intrinsic functional brain topology in patients with major depressive disorder. Molecular Psychiatry, 26(12), 7363–7371. https://doi.org/10.1038/s41380-021-01247-2.CrossRefGoogle ScholarPubMed
Yang, H., Zhang, H., Di, X., Wang, S., Meng, C., Tian, L., & Biswal, B. (2021b). Reproducible coactivation patterns of functional brain networks reveal the aberrant dynamic state transition in schizophrenia. Neuroimage, 237, 118193. https://doi.org/10.1016/j.neuroimage.2021.118193.CrossRefGoogle ScholarPubMed
Yao, Z., Zou, Y., Zheng, W., Zhang, Z., Li, Y., Yu, Y., … Hu, B. (2019). Structural alterations of the brain preceded functional alterations in major depressive disorder patients: Evidence from multimodal connectivity. Journal of Affective Disorders, 253, 107–117. https://doi.org/10.1016/j.jad.2019.04.064.CrossRefGoogle ScholarPubMed
Yeo, B. T., Krienen, F. M., Eickhoff, S. B., Yaakub, S. N., Fox, P. T., Buckner, R. L., … Chee, M. W. (2015). Functional specialization and flexibility in human association cortex. Cerebral Cortex, 25(10), 3654–3672. https://doi.org/10.1093/cercor/bhu217.CrossRefGoogle ScholarPubMed
Zalesky, A., Fornito, A., Seal, M. L., Cocchi, L., Westin, C. F., Bullmore, E. T., … Pantelis, C. (2011). Disrupted axonal fiber connectivity in schizophrenia. Biological Psychiatry, 69(1), 80–89. https://doi.org/10.1016/j.biopsych.2010.08.022.CrossRefGoogle ScholarPubMed
Zamani Esfahlani, F., Faskowitz, J., Slack, J., Misic, B., & Betzel, R. F. (2022). Local structure–function relationships in human brain networks across the lifespan. Nature Communications, 13, 2053. https://doi.org/10.1038/s41467-022-29770-y.CrossRefGoogle ScholarPubMed
Zhang, Z., Zhuo, K., Xiang, Q., Sun, Y., Suckling, J., Wang, J., … Sun, Y. (2021). Dynamic functional connectivity and its anatomical substrate reveal treatment outcome in first-episode drug-naive schizophrenia. Translational Psychiatry, 11, 282. https://doi.org/10.1038/s41398-021-01398-4.CrossRefGoogle ScholarPubMed
Zhao, S., Wang, G., Yan, T., Xiang, J., Yu, X., Li, H., & Wang, B. (2020a). Sex differences in anatomical rich-club and structural–functional coupling in the human brain network. Cerebral Cortex, 31(4), 1987–1997. https://doi.org/10.1093/cercor/bhaa335.CrossRefGoogle Scholar
Zhao, W., Guo, S., Linli, Z., Yang, A. C., Lin, C. P., & Tsai, S. J. (2020b). Functional, anatomical, and morphological networks highlight the role of basal ganglia–thalamus–cortex circuits in schizophrenia. Schizophrenia Bulletin, 46(2), 422–431. https://doi.org/10.1093/schbul/sbz062.Google ScholarPubMed
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