Skip to main content
SpringerLink
Log in

Abnormal synchronization of functional and structural networks in schizophrenia

  • Original Research
  • Published:
Brain Imaging and Behavior Aims and scope Submit manuscript

Abstract

Synchronization is believed to play an important role in information processing of the brain. Mounting evidence supports the hypothesis that schizophrenia is related to impaired neural synchrony. However, most previous studies characterize brain synchronization from the perspective of temporal coordination of distributed neural activity, rather than network properties. Our aim was to investigate the network synchronization alterations in schizophrenia using publically available data. Resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) were performed in 96 schizophrenia patients and 120 healthy controls. The whole-brain functional and structural networks were constructed and analyzed using graph theoretical approaches. Inter-group differences in network synchronization were investigated. Both the binary and weighted functional networks of schizophrenia patients exhibited decreased synchronizability (increased eigenratio) than those of healthy controls. With respect to the structural binary networks, schizophrenia patients showed a trend towards excessive synchronizability (decreased eigenratio). In addition, the excessive synchronizability of the structural binary networks was associated with more severe negative symptoms in schizophrenia patients. Our findings provide novel biological evidence that schizophrenia involves a disruption of neural synchrony from the perspective of network properties.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Achard, S., & Bullmore, E. (2007). Efficiency and cost of economical brain functional networks. PLoS Computational Biology, 3, e17.

    PubMed  PubMed Central  Google Scholar 

  • Andreasen, N. C. (1984). Scale for the assessment of positive symptoms (SAPS). Iowa City: University of Iowa.

    Google Scholar 

  • Andreasen, N. C. (1989). The scale for the assessment of negative symptoms (SANS): conceptual and theoretical foundations. The British Journal of Psychiatry Supplement, 49–58.

  • Arenas, A., Diaz-Guilera, A., & Perez-Vicente, C. J. (2006). Synchronization reveals topological scales in complex networks. Physical Review Letters, 96, 114102.

    PubMed  Google Scholar 

  • Ashburner, J. (2007). A fast diffeomorphic image registration algorithm. Neuroimage, 38, 95–113.

    PubMed  Google Scholar 

  • Atay, F. M., Jost, J., & Wende, A. (2004). Delays, connection topology, and synchronization of coupled chaotic maps. Physical Review Letters, 92, 144101.

    PubMed  Google Scholar 

  • Baggio, H. C., Segura, B., Junque, C., de Reus, M. A., Sala-Llonch, R., & Van den Heuvel, M. P. (2015). Rich Club organization and cognitive performance in healthy older participants. Journal of Cognitive Neuroscience, 27, 1801–1810.

    PubMed  Google Scholar 

  • Bai, F., Shu, N., Yuan, Y., Shi, Y., Yu, H., Wu, D., Wang, J., Xia, M., He, Y., & Zhang, Z. (2012). Topologically convergent and divergent structural connectivity patterns between patients with remitted geriatric depression and amnestic mild cognitive impairment. The Journal of Neuroscience, 32, 4307–4318.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Barahona, M., & Pecora, L. M. (2002). Synchronization in small-world systems. Physical Review Letters, 89, 054101.

    PubMed  Google Scholar 

  • Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., & Hwang, D. (2006). Complex networks: Structure and dynamics. Physics Reports, 424, 175–308.

    Google Scholar 

  • Bullmore, E. T., & Bassett, D. S. (2011). Brain graphs: graphical models of the human brain connectome. Annual Review of Clinical Psychology, 7, 113–140.

    PubMed  Google Scholar 

  • Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10, 186–198.

    CAS  PubMed  Google Scholar 

  • Buzsaki, G. (2006). Rhythms of the brain (1st ed.). New York: Oxford University Press.

    Google Scholar 

  • Cammoun, L., Gigandet, X., Meskaldji, D., Thiran, J. P., Sporns, O., Do, K. Q., Maeder, P., Meuli, R., & Hagmann, P. (2012). Mapping the human connectome at multiple scales with diffusion spectrum MRI. Journal of Neuroscience Methods, 203, 386–397.

    PubMed  Google Scholar 

  • Cetin, M. S., Christensen, F., Abbott, C. C., Stephen, J. M., Mayer, A. R., Canive, J. M., Bustillo, J. R., Pearlson, G. D., & Calhoun, V. D. (2014). Thalamus and posterior temporal lobe show greater inter-network connectivity at rest and across sensory paradigms in schizophrenia. Neuroimage, 97, 117–126.

    PubMed  Google Scholar 

  • Chao-Gan, Y., & Yu-Feng, Z. (2010). DPARSF: A MATLAB toolbox for "pipeline" data analysis of resting-state fMRI. Frontiers in Systems Neuroscience, 4, 13.

    PubMed  PubMed Central  Google Scholar 

  • Chavez, M., Hwang, D. U., Amann, A., & Boccaletti, S. (2006). Synchronizing weighted complex networks. Chaos, 16, 015106.

    CAS  PubMed  Google Scholar 

  • Cui, Z., Zhong, S., Xu, P., He, Y., & Gong, G. (2013). PANDA: A pipeline toolbox for analyzing brain diffusion images. Frontiers in Human Neuroscience, 7, 42.

    PubMed  PubMed Central  Google Scholar 

  • Fitzsimmons, J., Kubicki, M., & Shenton, M. E. (2013). Review of functional and anatomical brain connectivity findings in schizophrenia. Current Opinion in Psychiatry, 26, 172–187.

    PubMed  Google Scholar 

  • Ford, J. M., & Mathalon, D. H. (2008). Neural synchrony in schizophrenia. Schizophrenia Bulletin, 34, 904–906.

    PubMed  PubMed Central  Google Scholar 

  • Ford, J. M., Krystal, J. H., & Mathalon, D. H. (2007). Neural synchrony in schizophrenia: From networks to new treatments. Schizophrenia Bulletin, 33, 848–852.

    PubMed  PubMed Central  Google Scholar 

  • Fornito, A., Zalesky, A., & Bullmore, E. T. (2010). Network scaling effects in graph analytic studies of human resting-state FMRI data. Frontiers in Systems Neuroscience, 4, 22.

    PubMed  PubMed Central  Google Scholar 

  • Fornito, A., Zalesky, A., Pantelis, C., & Bullmore, E. T. (2012). Schizophrenia, neuroimaging and connectomics. Neuroimage, 62, 2296–2314.

    PubMed  Google Scholar 

  • Fornito, A., Zalesky, A., & Breakspear, M. (2013). Graph analysis of the human connectome: Promise, progress, and pitfalls. Neuroimage, 80, 426–444.

    PubMed  Google Scholar 

  • Fries, P. (2009). Neuronal gamma-band synchronization as a fundamental process in cortical computation. Annual Review of Neuroscience, 32, 209–224.

    CAS  PubMed  Google Scholar 

  • Gong, G., He, Y., Concha, L., Lebel, C., Gross, D. W., Evans, A. C., & Beaulieu, C. (2009). Mapping anatomical connectivity patterns of human cerebral cortex using in vivo diffusion tensor imaging tractography. Cerebral Cortex, 19, 524–536.

    PubMed  Google Scholar 

  • Hayasaka, S., & Laurienti, P. J. (2010). Comparison of characteristics between region-and voxel-based network analyses in resting-state fMRI data. Neuroimage, 50, 499–508.

    PubMed  Google Scholar 

  • He, Y., & Evans, A. (2010). Graph theoretical modeling of brain connectivity. Current Opinion in Neurology, 23, 341–350.

    PubMed  Google Scholar 

  • He, Y., Dagher, A., Chen, Z., Charil, A., Zijdenbos, A., Worsley, K., & Evans, A. (2009). Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. Brain, 132, 3366–3379.

    PubMed  PubMed Central  Google Scholar 

  • Hong, H., Choi, M. Y., & Kim, B. J. (2002). Synchronization on small-world networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 65, 026139.

    CAS  PubMed  Google Scholar 

  • Jalili, M., & Knyazeva, M. G. (2011). EEG-based functional networks in schizophrenia. Computers in Biology and Medicine, 41, 1178–1186.

    PubMed  Google Scholar 

  • Karbasforoushan, H., & Woodward, N. D. (2012). Resting-state networks in schizophrenia. Current Topics in Medicinal Chemistry, 12, 2404–2414.

    CAS  PubMed  Google Scholar 

  • Kay, S. R., Fiszbein, A., & Opler, L. A. (1987). The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophrenia Bulletin, 13, 261–276.

    CAS  PubMed  Google Scholar 

  • Lee, D. S. (2005). Synchronization transition in scale-free networks: Clusters of synchrony. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 72, 026208.

    PubMed  Google Scholar 

  • Lei, D., Li, K., Li, L., Chen, F., Huang, X., Lui, S., Li, J., Bi, F., & Gong, Q. (2015). Disrupted functional brain connectome in patients with posttraumatic stress disorder. Radiology, 276, 818–827.

  • Leucht, S., Samara, M., Heres, S., Patel, M. X., Woods, S. W., & Davis, J. M. (2014). Dose equivalents for second-generation antipsychotics: The minimum effective dose method. Schizophrenia Bulletin, 40, 314–326.

    PubMed  PubMed Central  Google Scholar 

  • Li, Y., Liu, Y., Li, J., Qin, W., Li, K., Yu, C., & Jiang, T. (2009). Brain anatomical network and intelligence. PLoS Computational Biology, 5, e1000395.

    PubMed  PubMed Central  Google Scholar 

  • Liao, W., Zhang, Z., Pan, Z., Mantini, D., Ding, J., Duan, X., Luo, C., Wang, Z., Tan, Q., Lu, G., et al. (2011). Default mode network abnormalities in mesial temporal lobe epilepsy: A study combining fMRI and DTI. Human Brain Mapping, 32, 883–895.

    PubMed  Google Scholar 

  • Liao, X., Vasilakos, A. V., & He, Y. (2017). Small-world human brain networks: Perspectives and challenges. Neuroscience and Biobehavioral Reviews, 77, 286–300.

    PubMed  Google Scholar 

  • Micheloyannis, S. (2012). Graph-based network analysis in schizophrenia. World Journal of Psychiatry, 2, 1–12.

    PubMed  PubMed Central  Google Scholar 

  • Mori, S., Crain, B. J., Chacko, V. P., & van Zijl, P. C. (1999). Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging. Annals of Neurology, 45, 265–269.

    CAS  PubMed  Google Scholar 

  • Motter, A. E., Zhou, C., & Kurths, J. (2005a). Network synchronization, diffusion, and the paradox of heterogeneity. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 71, 016116.

    PubMed  Google Scholar 

  • Motter, A. E., Zhou, C. S., & Kurths, J. (2005b). Enhancing complex-network synchronization. Europhysics Letters (EPL), 69, 334–340.

    CAS  Google Scholar 

  • Motter, A. E., Matías, M. A., Kurths, J., & Ott, E. (2006). Dynamics on complex networks and applications. Physica D: Nonlinear Phenomena, 224, vii–viii.

    Google Scholar 

  • Narr, K. L., & Leaver, A. M. (2015). Connectome and schizophrenia. Current Opinion in Psychiatry, 28, 229–235.

    PubMed  Google Scholar 

  • Nishikawa, T., Motter, A. E., Lai, Y. C., & Hoppensteadt, F. C. (2003). Heterogeneity in oscillator networks: Are smaller worlds easier to synchronize? Physical Review Letters, 91, 014101.

    PubMed  Google Scholar 

  • Pecora, L. M., & Carroll, T. L. (1998). Master stability functions for synchronized coupled systems. Physical Review Letters, 80, 2109–2112.

    CAS  Google Scholar 

  • Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage, 59, 2142–2154.

    PubMed  Google Scholar 

  • Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. Neuroimage, 52, 1059–1069.

    PubMed  Google Scholar 

  • Rubinov, M., & Sporns, O. (2011). Weight-conserving characterization of complex functional brain networks. Neuroimage, 56, 2068–2079.

    PubMed  Google Scholar 

  • Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage, 23(Suppl 1), S208–S219.

    PubMed  Google Scholar 

  • Spellman, T. J., & Gordon, J. A. (2015). Synchrony in schizophrenia: A window into circuit-level pathophysiology. Current Opinion in Neurobiology, 30, 17–23.

    CAS  PubMed  Google Scholar 

  • Stam, C. J., & Reijneveld, J. C. (2007). Graph theoretical analysis of complex networks in the brain. Nonlinear Biomedical Physics, 1, 3.

    PubMed  PubMed Central  Google Scholar 

  • Suo, X., Lei, D., Li, K., Chen, F., Li, F., Li, L., Huang, X., Lui, S., Kemp, G. J., & Gong, Q. (2015). Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting-state fMRI study. Human Brain Mapping, 36, 3677–3686.

    PubMed  PubMed Central  Google Scholar 

  • Tzourio-Mazoyer, N., Landeau, B., Papathanassiou, D., Crivello, F., Etard, O., Delcroix, N., Mazoyer, B., & Joliot, M. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage, 15, 273–289.

    CAS  PubMed  Google Scholar 

  • Uhlhaas, P. J. (2013). Dysconnectivity, large-scale networks and neuronal dynamics in schizophrenia. Current Opinion in Neurobiology, 23, 283–290.

    CAS  PubMed  Google Scholar 

  • Uhlhaas, P. J., & Singer, W. (2010). Abnormal neural oscillations and synchrony in schizophrenia. Nature Reviews Neuroscience, 11, 100–113.

    CAS  PubMed  Google Scholar 

  • Uhlhaas, P. J., Haenschel, C., Nikolic, D., & Singer, W. (2008). The role of oscillations and synchrony in cortical networks and their putative relevance for the pathophysiology of schizophrenia. Schizophrenia Bulletin, 34, 927–943.

    PubMed  PubMed Central  Google Scholar 

  • van den Heuvel, M. P., & Fornito, A. (2014). Brain networks in schizophrenia. Neuropsychology Review, 24, 32–48.

    PubMed  Google Scholar 

  • Wang, J., Wang, L., Zang, Y., Yang, H., Tang, H., Gong, Q., Chen, Z., Zhu, C., & He, Y. (2009). Parcellation-dependent small-world brain functional networks: A resting-state fMRI study. Human Brain Mapping, 30, 1511–1523.

    PubMed  Google Scholar 

  • Wang, Q., Su, T. P., Zhou, Y., Chou, K. H., Chen, I. Y., Jiang, T., & Lin, C. P. (2012). Anatomical insights into disrupted small-world networks in schizophrenia. Neuroimage, 59, 1085–1093.

    PubMed  Google Scholar 

  • Wang, J., Wang, X., Xia, M., Liao, X., Evans, A., & He, Y. (2015). GRETNA: A graph theoretical network analysis toolbox for imaging connectomics. Frontiers in Human Neuroscience, 9, 386.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Woods, S. W. (2003). Chlorpromazine equivalent doses for the newer atypical antipsychotics. The Journal of Clinical Psychiatry, 64, 663–667.

    CAS  PubMed  Google Scholar 

  • Yu, Q., Allen, E. A., Sui, J., Arbabshirani, M. R., Pearlson, G., & Calhoun, V. D. (2012). Brain connectivity networks in schizophrenia underlying resting state functional magnetic resonance imaging. Current Topics in Medicinal Chemistry, 12, 2415–2425.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Zalesky, A., Fornito, A., Harding, I. H., Cocchi, L., Yucel, M., Pantelis, C., & Bullmore, E. T. (2010). Whole-brain anatomical networks: Does the choice of nodes matter? Neuroimage, 50, 970–983.

    PubMed  Google Scholar 

  • Zhang, J., Wang, J., Wu, Q., Kuang, W., Huang, X., He, Y., & Gong, Q. (2011). Disrupted brain connectivity networks in drug-naive, first-episode major depressive disorder. Biological Psychiatry, 70, 334–342.

    PubMed  Google Scholar 

  • Zhang, R., Wei, Q., Kang, Z., Zalesky, A., Li, M., Xu, Y., Li, L., Wang, J., Zheng, L., Wang, B., et al. (2015). Disrupted brain anatomical connectivity in medication-naive patients with first-episode schizophrenia. Brain Structure & Function, 220, 1145–1159.

    CAS  Google Scholar 

  • Zhao, T., Cao, M., Niu, H., Zuo, X. N., Evans, A., He, Y., Dong, Q., & Shu, N. (2015). Age-related changes in the topological organization of the white matter structural connectome across the human lifespan. Human Brain Mapping, 36, 3777–3792.

    PubMed  PubMed Central  Google Scholar 

  • Zhong, S., He, Y., & Gong, G. (2015). Convergence and divergence across construction methods for human brain white matter networks: An assessment based on individual differences. Human Brain Mapping, 36, 1995–2013.

    PubMed  PubMed Central  Google Scholar 

  • Zhou, C., Motter, A. E., & Kurths, J. (2006). Universality in the synchronization of weighted random networks. Physical Review Letters, 96, 034101.

    PubMed  Google Scholar 

  • Zhu, J., Zhuo, C., Liu, F., Qin, W., Xu, L., & Yu, C. (2016). Distinct disruptions of resting-state functional brain networks in familial and sporadic schizophrenia. Scientific Reports, 6, 23577.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

The work was supported by the National Natural Science Foundation of China (grant numbers: 81801679, 81571308 and 81771817). Data used in preparation of this article were obtained from the SchizConnect database (http://schizconnect.org). As such, the investigators within SchizConnect contributed to the design and implementation of SchizConnect and/or provided data but did not participate in analysis or writing of this report. Data collection and sharing for this project was funded by NIMH cooperative agreement 1 U01 MH097435. Parts of these data were downloaded from the COllaborative Informatics and Neuroimaging Suite Data Exchange tool (COINS; http://coins.mrn.org/dx) and data collection was performed at the Mind Research Network, and funded by a Center of Biomedical Research Excellence (COBRE) grant 5P20RR021938/P20GM103472 from the NIH to Dr. Vince Calhoun. The other parts of these data were obtained from the Neuromorphometry by Computer Algorithm Chicago (NMorphCH) dataset (http://nunda.northwestern.edu/nunda/data/projects/NMorphCH). As such, the investigators within NMorphCH contributed to the design and implementation of NMorphCH and/or provided data but did not participate in analysis or writing of this report. Data collection and sharing for this project was funded by NIMH grant R01 MH056584.

Author information

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital of Anhui Medical University, No. 218, Jixi Road, Shushan District, Hefei, 230022, China

    Jiajia Zhu, Yinfeng Qian, Biao Zhang, Xiaohu Li, Ya Bai, Xiaoshu Li & Yongqiang Yu

Authors
  1. Jiajia Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yinfeng Qian
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Biao Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaohu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ya Bai
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiaoshu Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Yongqiang Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

JZ and YY designed the current study and wrote the paper. All of the authors performed the experiments and analyzed the data. All of the authors read and approved the final manuscript.

Corresponding author

Correspondence to Yongqiang Yu.

Ethics declarations

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, J., Qian, Y., Zhang, B. et al. Abnormal synchronization of functional and structural networks in schizophrenia. Brain Imaging and Behavior 14, 2232–2241 (2020). https://doi.org/10.1007/s11682-019-00175-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11682-019-00175-8

Keywords

Search

Navigation