Skip to main content
SpringerLink
Log in

Revisiting Functional Dysconnectivity: a Review of Three Model Frameworks in Schizophrenia

  • Review
  • Published:
Current Neurology and Neuroscience Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Over the last decade, evidence suggests that a combination of behavioral and neuroimaging findings can help illuminate changes in functional dysconnectivity in schizophrenia. We review the recent connectivity literature considering several vital models, considering connectivity findings, and relationships with clinical symptoms. We reviewed resting state fMRI studies from 2017 to 2023. We summarized the role of two sets of brain networks (cerebello-thalamo-cortical (CTCC) and the triple network set) across three hypothesized models of schizophrenia etiology (neurodevelopmental, vulnerability-stress, and neurotransmitter hypotheses).

Recent Findings

The neurotransmitter and neurodevelopmental models best explained CTCC-subcortical dysfunction, which was consistently connected to symptom severity and motor symptoms. Triple network dysconnectivity was linked to deficits in executive functioning, and the salience network (SN)–default mode network dysconnectivity was tied to disordered thought and attentional deficits.

Summary

This paper links behavioral symptoms of schizophrenia (symptom severity, motor, executive functioning, and attentional deficits) to various hypothesized mechanisms.

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

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

  1. Stephan KE, Friston KJ, Frith CD. Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring. Schizophr Bull. 2009;35:509–27.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Friston KJ. The disconnection hypothesis. Schizophr Res. 1998;30:115–25.

    Article  CAS  PubMed  Google Scholar 

  3. Friston K, Brown HR, Siemerkus J, Stephan KE. The dysconnection hypothesis (2016). Schizophr Res. 2016;176:83–94.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Limongi R, Jeon P, Mackinley M, Das T, Dempster K, Théberge J, Bartha R, Wong D, Palaniyappan L. Glutamate and dysconnection in the salience network: neurochemical, effective connectivity, and computational evidence in schizophrenia. Biol Psychiatry. 2020;88:273–81.

    Article  CAS  PubMed  Google Scholar 

  5. Giraldo-Chica M, Woodward ND. Review of thalamocortical resting-state fMRI studies in schizophrenia. Schizophr Res. 2017;180:58–63.

    Article  PubMed  Google Scholar 

  6. Kraguljac NV, Frölich MA, Tran S, White DM, Nichols N, Barton-McArdle A, Reid MA, Bolding MS, Lahti AC. Ketamine modulates hippocampal neurochemistry and functional connectivity: a combined magnetic resonance spectroscopy and resting-state fMRI study in healthy volunteers. Mol Psychiatry. 2017;22:562–9.

    Article  CAS  PubMed  Google Scholar 

  7. Birnbaum R, Weinberger DR. Genetic insights into the neurodevelopmental origins of schizophrenia. Nat Rev Neurosci. 2017;18:727–40.

    Article  CAS  PubMed  Google Scholar 

  8. Correll CU, Schooler NR. Negative symptoms in schizophrenia: a review and clinical guide for recognition, assessment, and treatment. Neuropsychiatr Dis Treat. 2020;16:519–34.

    Article  PubMed  PubMed Central  Google Scholar 

  9. McCutcheon RA, Reis Marques T, Howes OD. Schizophrenia—an overview. JAMA Psychiatry. 2020;77:201.

    Article  PubMed  Google Scholar 

  10. Andreasen NC. The lifetime trajectory of schizophrenia and the concept of neurodevelopment. Dialogues Clin Neurosci. 2010;12:409–15.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Satterthwaite TD, Baker JT. How can studies of resting-state functional connectivity help us understand psychosis as a disorder of brain development? Curr Opin Neurobiol. 2015;30:85–91.

    Article  CAS  PubMed  Google Scholar 

  12. Fournier M, Ferrari C, Baumann PS, et al. Impaired metabolic reactivity to oxidative stress in early psychosis patients. Schizophr Bull. 2014;40:973–83.

    Article  PubMed  PubMed Central  Google Scholar 

  13. •• Ľupták M, Michaličková D, Fišar Z, Kitzlerová E, Hroudová J. Novel approaches in schizophrenia-from risk factors and hypotheses to novel drug targets. World J Psychiatry. 2021;11:277–96. This is a seminal paper from which our review adopted the models. Various models including biomarkers of schizophrenia are discussed here.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Biswal B, Yetkin FZ, Haughton VM, Hyde JS. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn Reson Med Off J Soc Magn Reson Med Soc Magn Reson Med. 1995;34:537–41.

    Article  CAS  Google Scholar 

  15. Keshavan MS, Collin G, Guimond S, Kelly S, Prasad KM, Lizano P. Neuroimaging in schizophrenia. Neuroimaging Clin N Am. 2020;30:73–83.

    Article  PubMed  Google Scholar 

  16. Salman MS, Du Y, Lin D, et al. Group ICA for identifying biomarkers in schizophrenia: ‘adaptive’ networks via spatially constrained ICA show more sensitivity to group differences than spatio-temporal regression. NeuroImage Clin. 2019;22:101747.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Calhoun VD, Liu J, Adalı T. A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. NeuroImage. 2009;45:S163–72.

    Article  PubMed  Google Scholar 

  18. Iraji A, Faghiri A, Fu Z, et al. Multi-spatial-scale dynamic interactions between functional sources reveal sex-specific changes in schizophrenia. Netw Neurosci. 2022;6:357–81.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Meng X, Iraji A, Fu Z, et al. Multi-model order spatially constrained ICA reveals highly replicable group differences and consistent predictive results from fMRI data. A large N fMRI schizophrenia study. NeuroImage: Clinical. 2022;38:103434. https://doi.org/10.1101/2022.11.02.514809.

    Article  Google Scholar 

  20. Hassanzadeh R, Abrol A, Calhoun V. Classification of schizophrenia and Alzheimer’s disease using resting-state functional network connectivity. In: 2022 IEEE-EMBS Int. Conf. Biomed. Health Inform. BHI. Ioannina, Greece: IEEE; 2022. p. 01–4.

    Google Scholar 

  21. Du Y, Pearlson GD, Liu J, Sui J, Yu Q, He H, Castro E, Calhoun VD. A group ICA based framework for evaluating resting fMRI markers when disease categories are unclear: application to schizophrenia, bipolar, and schizoaffective disorders. NeuroImage. 2015;122:272–80.

    Article  PubMed  Google Scholar 

  22. Shahhosseini Y, Miranda MF. Functional connectivity methods and their applications in fMRI data. Entropy. 2022;24:390.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Yu Q, Allen EA, Sui J, Arbabshirani MR, Calhoun VD. Brain connectivity networks in schizophrenia underlying resting state functional magnetic resonance imaging. Curr Top Med Chem. 2015;12(21):2415–25.

    Google Scholar 

  24. Walther S, Stegmayer K, Federspiel A, Bohlhalter S, Wiest R, Viher PV. Aberrant hyperconnectivity in the motor system at rest is linked to motor abnormalities in schizophrenia spectrum disorders. Schizophr Bull. 2017;43:982–92.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Calhoun VD. Functional brain networks in schizophrenia: a review. Front Hum Neurosci. 2009; https://doi.org/10.3389/neuro.09.017.2009.

  26. • Clark SV, Tannahill A, Calhoun VD, Bernard JA, Bustillo J, Turner JA. Weaker cerebellocortical connectivity within sensorimotor and executive networks in schizophrenia compared to healthy controls: relationships with processing speed. Brain Connect. 2020;10:490–503. This paper discusses the link between reduced processing speed and cerebello-cortical connectivity in schizophrenia. We deemed it important given that it is a timely paper with salient findings tying together cognitive deficits and cerebello-cortical connectivity.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Anticevic A, Cole MW, Repovs G, Murray JD, Brumbaugh MS, Winkler AM, Savic A, Krystal JH, Pearlson GD, Glahn DC. Characterizing thalamo-cortical disturbances in schizophrenia and bipolar illness. Cereb Cortex. 2014;24:3116–30.

    Article  PubMed  Google Scholar 

  28. Ramsay IS. An Activation Likelihood Estimate meta-analysis of thalamocortical dysconnectivity in psychosis. Biol Psychiatry Cogn Neurosci Neuroimaging. 2019;4:859–69.

    PubMed  Google Scholar 

  29. Ferri J, Ford JM, Roach BJ, et al. Resting-state thalamic dysconnectivity in schizophrenia and relationships with symptoms. Psychol Med. 2018;48:2492–9.

    Article  CAS  PubMed  Google Scholar 

  30. • Benoit LJ, Canetta S, Kellendonk C. Thalamocortical development: a neurodevelopmental framework for schizophrenia. Biol Psychiatry. 2022;92:491–500. This is an important and timely paper that discusses in great detail how the neurodevelopmental framework/model best explains thalamocortical development. We found this to be a crucial paper in explaining the neurodevelopmental deficits in frontal and thalamic dysfunction.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Bernard JA, Orr JM, Mittal VA. Cerebello-thalamo-cortical networks predict positive symptom progression in individuals at ultra-high risk for psychosis. NeuroImage Clin. 2017;14:622–8.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Bernard JA, Goen JRM, Maldonado T. A case for motor network contributions to schizophrenia symptoms: evidence from resting-state connectivity: Motor Networks and Schizophrenia. Hum Brain Mapp. 2017;38:4535–45.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Menon B. Towards a new model of understanding – The triple network, psychopathology and the structure of the mind. Med Hypotheses. 2019;133:109385.

    Article  PubMed  Google Scholar 

  34. Menon V. Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci. 2011;15:483–506.

    Article  PubMed  Google Scholar 

  35. Tu P-C, Lee Y-C, Chen Y-S, Li C-T, Su T-P. Schizophrenia and the brain’s control network: aberrant within- and between-network connectivity of the frontoparietal network in schizophrenia. Schizophr Res. 2013;147:339–47.

    Article  PubMed  Google Scholar 

  36. Hu M-L, Zong X-F, Mann JJ, Zheng J-J, Liao Y-H, Li Z-C, He Y, Chen X-G, Tang J-S. A review of the functional and anatomical default mode network in schizophrenia. Neurosci Bull. 2017;33:73–84.

    Article  CAS  PubMed  Google Scholar 

  37. Sridharan D, Levitin DJ, Menon V. A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci. 2008;105:12569–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. O’Neill A, Mechelli A, Bhattacharyya S. Dysconnectivity of large-scale functional networks in early psychosis: a meta-analysis. Schizophr Bull. 2019;45:579–90.

    Article  PubMed  Google Scholar 

  39. Jiang Y, Duan M, Chen X, Chang X, He H, Li Y, Luo C, Yao D. Common and distinct dysfunctional patterns contribute to triple network model in schizophrenia and depression: a preliminary study. Prog Neuropsychopharmacol Biol Psychiatry. 2017;79:302–10.

    Article  PubMed  Google Scholar 

  40. Ma X, Yang WFZ, Zheng W, et al. Neuronal dysfunction in individuals at early stage of schizophrenia, a resting-state fMRI study. Psychiatry Res. 2023;322:115123.

    Article  PubMed  Google Scholar 

  41. Huang H, Botao Z, Jiang Y, et al. Aberrant resting-state functional connectivity of salience network in first-episode schizophrenia. Brain Imaging Behav. 2020;14:1350–60.

    Article  PubMed  Google Scholar 

  42. Huang H, Chen C, Rong B, Wan Q, Chen J, Liu Z, Zhou Y, Wang G, Wang H. Resting-state functional connectivity of salience network in schizophrenia and depression. Sci Rep. 2022;12:11204.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. van Ommen M, Invernizzi A, Renken RJ, Bruggeman R, Cornelissen FW, van Laar T. Impaired functional connectivity in patients with psychosis and visual hallucinations. 2022; https://doi.org/10.1101/2022.05.06.22274666.

  44. Xiang Q, Xu J, Wang Y, et al. Modular functional-metabolic coupling alterations of frontoparietal network in schizophrenia patients. Front Neurosci. 2019;13:40.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Kandilarova S, Stoyanov D, Paunova R, Todeva-Radneva A, Aryutova K, Maes M. Effective connectivity between major nodes of the limbic system, salience and frontoparietal networks differentiates schizophrenia and mood disorders from healthy controls. J Pers Med. 2021;11:1110.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Hummer TA, Yung MG, Goñi J, Conroy SK, Francis MM, Mehdiyoun NF, Breier A. Functional network connectivity in early-stage schizophrenia. Schizophr Res. 2020;218:107–15.

    Article  PubMed  Google Scholar 

  47. Sarpal DK, Tarcijonas G, Calabro FJ, Foran W, Haas GL, Luna B, Murty VP. Context-specific abnormalities of the central executive network in first-episode psychosis: relationship with cognition. Psychol Med. 2022;52:2299–308.

    Article  PubMed  Google Scholar 

  48. Friston KJ, Harrison L, Penny W. Dynamic causal modelling. NeuroImage. 2003;19:1273–302.

    Article  CAS  PubMed  Google Scholar 

  49. Xi Y-B, Guo F, Liu W-M, et al. Triple network hypothesis-related disrupted connections in schizophrenia: a spectral dynamic causal modeling analysis with functional magnetic resonance imaging. Schizophr Res. 2021;233:89–96.

    Article  PubMed  Google Scholar 

  50. Rodriguez M, Zaytseva Y, Cvrčková A, et al. Cognitive profiles and functional connectivity in first-episode schizophrenia spectrum disorders – linking behavioral and neuronal data. Front Psychol. 2019;10:689.

    Article  PubMed  PubMed Central  Google Scholar 

  51. Xu P, Klaasen NG, Opmeer EM, Pijnenborg GHM, van Tol M-J, Liemburg EJ, Aleman A. Intrinsic mesocorticolimbic connectivity is negatively associated with social amotivation in people with schizophrenia. Schizophr Res. 2019;208:353–9.

    Article  PubMed  Google Scholar 

  52. Wylie KP, Harris JG, Ghosh D, Olincy A, Tregellas JR. Association of working memory with distributed executive control networks in schizophrenia. J Neuropsychiatry Clin Neurosci. 2019;31:368–77.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Hare SM. Hallucinations: a functional network model of how sensory representations become selected for conscious awareness in schizophrenia. Front Neurosci. 2021;15:733038.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Hare SM, Ford JM, Mathalon DH, et al. Salience–default mode functional network connectivity linked to positive and negative symptoms of schizophrenia. Schizophr Bull. 2019;45:892–901.

    Article  PubMed  Google Scholar 

  55. Conio B, Martino M, Magioncalda P, Escelsior A, Inglese M, Amore M, Northoff G. Opposite effects of dopamine and serotonin on resting-state networks: review and implications for psychiatric disorders. Mol Psychiatry. 2020;25:82–93.

    Article  PubMed  Google Scholar 

  56. Han S, Cui Q, Guo X, Fan Y-S, Guo J, Zong X, Hu M, Lu F, Chen X, Chen H. Disconnectivity between the raphe nucleus and subcortical dopamine-related regions contributes altered salience network in schizophrenia. Schizophr Res. 2020;216:382–8.

    Article  PubMed  Google Scholar 

  57. Fan Y, Li L, Peng Y, et al. Individual-specific functional connectome biomarkers predict schizophrenia positive symptoms during adolescent brain maturation. Hum Brain Mapp. 2021;42:1475–84.

    Article  Google Scholar 

  58. • Maximo JO, Briend F, Armstrong WP, Kraguljac NV, Lahti AC. Salience network glutamate and brain connectivity in medication-naïve first episode patients – A multimodal magnetic resonance spectroscopy and resting state functional connectivity MRI study. NeuroImage Clin. 2021;32:102845. This was an interesting study that linked neurotransmitter functioning to functional connectivity; we found this study to be particularly interesting given that dysconnectivity was noted in medication-naive patients, and few studies examined neurotrasmitter links + functional connectivity.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Shukla DK, Wijtenburg SA, Chen H, Chiappelli JJ, Kochunov P, Hong LE, Rowland LM. Anterior cingulate glutamate and gaba associations on functional connectivity in schizophrenia. Schizophr Bull. 2019;45:647–58.

    Article  PubMed  Google Scholar 

  60. Romme IAC, De Reus MA, Ophoff RA, Kahn RS, Van Den Heuvel MP. Connectome disconnectivity and cortical gene expression in patients with schizophrenia. Biol Psychiatry. 2017;81:495–502.

    Article  CAS  PubMed  Google Scholar 

  61. Vass E, Fekete Z, Simon V, Simon L. Interventions for the treatment of theory of mind deficits in schizophrenia: systematic literature review. Psychiatry Res. 2018;267:37–47.

    Article  PubMed  Google Scholar 

  62. Doody GA, Götz M, Johnstone EC, Frith CD, Cunningham Owens DG. Theory of mind and psychoses. Psychol Med. 1998;28:397–405.

    Article  CAS  PubMed  Google Scholar 

  63. Shin S, Jung WH, McCutcheon R, Veronese M, Beck K, Lee JS, Lee Y-S, Howes OD, Kim E, Kwon JS. The relationship between frontostriatal connectivity and striatal dopamine function in schizophrenia: an 18F-DOPA PET and diffusion tensor imaging study in treatment responsive and resistant patients. Psychiatry Investig. 2022;19:570–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Funding

This work was supported by the National Institute of Health (NIH) grants R01MH129047 and partly by NSF 2112455 and NIH 2R01EB006841. Amritha Harikumar is currently supported by the Georgia State University Brains and Behavior Fellowship.

Author information

Author notes

  1. Jessica A. Turner and Vince D. Calhoun are co-senior authors.

Authors and Affiliations

  1. The Georgia State University/Georgia Institute of Technology/Emory University Center for Translational Research in Neuroimaging and Data Science (TReNDS Center), 55 Park Pl NE, Atlanta, GA, 30303, USA

    Amritha Harikumar, Kseniya P. Solovyeva, Maria Misiura, Armin Iraji, Sergey M. Plis & Vince D. Calhoun

  2. Departments of Psychiatry and Neuroscience, Yale School of Medicine, New Haven, CT, USA

    Godfrey D. Pearlson

  3. The Ohio State University Wexner Medical Center, Columbus, OH, USA

    Jessica A. Turner

Authors
  1. Amritha Harikumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kseniya P. Solovyeva
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Maria Misiura
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Armin Iraji
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sergey M. Plis
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Godfrey D. Pearlson
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jessica A. Turner
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Vince D. Calhoun
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vince D. Calhoun.

Ethics declarations

Conflict of Interest

The authors do not have competing disclosures or conflicts of interest to report.

Human/Animal Rights and Informed Consent

This paper is a review paper and reviews studies that obtained informed consent.

Additional information

Publisher’s Note

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

Amritha Harikumar and Kseniya P. Solovyeva are co-first authors.

Supplementary Information

ESM 1

(XLSX 90 kb)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Harikumar, A., Solovyeva, K.P., Misiura, M. et al. Revisiting Functional Dysconnectivity: a Review of Three Model Frameworks in Schizophrenia. Curr Neurol Neurosci Rep 23, 937–946 (2023). https://doi.org/10.1007/s11910-023-01325-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11910-023-01325-8

Keywords

Search

Navigation