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Dysconnection in Schizophrenia: From Abnormal Synaptic Plasticity to Failures of Self-monitoring
Open accessAbstract
Over the last 2 decades, a large number of neurophysiological and neuroimaging studies of patients with schizophrenia have furnished in vivo evidence for dysconnectivity, ie, abnormal functional integration of brain processes. While the evidence for dysconnectivity in schizophrenia is strong, its etiology, pathophysiological mechanisms, and significance for clinical symptoms are unclear. First, dysconnectivity could result from aberrant wiring of connections during development, from aberrant synaptic plasticity, or from both. Second, it is not clear how schizophrenic symptoms can be understood mechanistically as a consequence of dysconnectivity. Third, if dysconnectivity is the primary pathophysiology, and not just an epiphenomenon, then it should provide a mechanistic explanation for known empirical facts about schizophrenia. This article addresses these 3 issues in the framework of the dysconnection hypothesis. This theory postulates that the core pathology in schizophrenia resides in aberrant N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic plasticity due to abnormal regulation of NMDARs by neuromodulatory transmitters like dopamine, serotonin, or acetylcholine. We argue that this neurobiological mechanism can explain failures of self-monitoring, leading to a mechanistic explanation for first-rank symptoms as pathognomonic features of schizophrenia, and may provide a basis for future diagnostic classifications with physiologically defined patient subgroups. Finally, we test the explanatory power of our theory against a list of empirical facts about schizophrenia.
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“Computational psychiatry studies have done exactly this – for instance, using conductance-based neural mass models to infer synaptic changes in disorders like schizophrenia from M/EEG recordings (25, 26).”
From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [25]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“A prominent and consistent pathophysiological characteristic that has emerged in schizophrenia involves impaired synaptic connectivity (Stephan et al., 2009)”
From Perineuronal nets and schizophrenia: The importance of neuronal coatings (2014) · cites this paper as Stephan et al., 2009
In the citing paper
“It is of interest to note that similar Bayesian theories have previously been stated in the context of schizophrenia (63, 68, 89–92).”
From Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice? (2016) · cites this paper as [89]
In the citing paper
“This model, and variants thereof, has already found widespread application to other psychiatric disorders with perceptual aberrations, in particular schizophrenia (63, 89, 90, 92, 107).”
From Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice? (2016) · cites this paper as [89]
In the citing paper
“A prominent and consistent pathophysiological characteristic that has emerged in schizophrenia involves impaired synaptic connectivity (Stephan et al., 2009)”
From Perineuronal nets and schizophrenia: The importance of neuronal coatings (2014) · cites this paper as Stephan et al., 2009
In the citing paper
“Overall, studies conducted in SCZ suggest that this dysconnectivity may rely at the microscale on impaired control of synaptic plasticity, 40 notably of NMDAdependent plasticity.41,42”
From Are hallucinations due to an imbalance between excitatory and inhibitory influences on the brain? (2016) · cites this paper as [42]
In the citing paper
“Others have linked hallucinations to a failure to attenuate the sensory consequences of inner speech, in analogy to the mechanism that is thought to underlie delusions of control.42,124,135”
From Are hallucinations due to an imbalance between excitatory and inhibitory influences on the brain? (2016) · cites this paper as [42]
In the citing paper
“Such a possibility would be akin to the cycles of demyelination and remyelination often experienced by patients with multiple sclerosis 72 : cycles that have been shown to be associated with fluctuations in conduction velocity 46 and symptomatology, including psychotic symptomatology.[73][74][75]”
From Schizophrenia, myelination, and delayed corollary discharges: a hypothesis (2012) · cites this paper as [73]
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Markoš, I. Š., Blažeković, I., Orlović, I., Peitl, V., Fröbe, A., & Karlović, D. (2024) · Research Square · doi:10.21203/rs.3.rs-5287898/v1 · Cited by 1
Dynamic Causal Models for fMRI
Stephan, K. E. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-397025-1.00339-0
Self-citationUnderstanding the Mental Disease of Schizophrenia
Taylor, J. G. (2013) · Springer eBooks · doi:10.1007/978-94-007-7645-6_10
Díez, Á. (2013) · Gredos (University of Salamanca) · doi:10.14201/gredos.122923
The Utility of Electromagnetic Activity Measures in Obsessive Compulsive Disorder and Schizophrenia
Harris, E., & Korostenskaj, M. (2014) · InTech eBooks · doi:10.5772/57247 · Cited by 1
Niarchou, M. (2013) · ORCA Online Research @Cardiff (Cardiff University)
System Models for Inference on Mechanisms of Neuronal Dynamics
Stephan, K. E., & Friston, K. J. (2012) · Wiley-VCH eBooks · doi:10.1002/3527600906.mcb.201100042
Self-citationPrinz, S. (2011) · Universitätsbibliothek der FU Berlin Hochschulschriftenstelle u. Dokumentenserver · doi:10.17169/refubium-10537
9 – Hypothèses neurodéveloppementales et plasticité cérébrale
Amad, A., & Thomas, P. (2015) · doi:10.1016/b978-2-294-73908-8.00009-4
The function of TCF4 in Pitt-Hopkins syndrome and schizophrenia
Forrest, M. P. (2013) · ORCA Online Research @Cardiff (Cardiff University)
Kaneko, Y. A. (2010) · Europe PMC (PubMed Central)
Vinckier, F. (2013) · L information psychiatrique · doi:10.1684/ipe.2013.1130
Functional Neuroradiology of Psychiatric Diseases
Nucifora, P. G. P. (2011) · Springer eBooks · doi:10.1007/978-1-4419-0345-7_14
Liu, M., Wang, L., Shen, H., Liu, Z., & Hu, D. (2011) · Procedia Environmental Sciences · doi:10.1016/j.proenv.2011.10.109
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Metadata
- Authors
- Stephan, K. E., Friston, K. J., & Frith, C. D.
- Affiliations
- Wellcome Centre for Human Neuroimaging (GB)
- Corresponding author
- Stephan, K. E.
- Venue
- Schizophrenia Bulletin
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-03-30
- Volume
- 35
- Issue
- 3
- Pages
- 509-527
- ISSN
- 0586-7614 (ISSN-L)
- 1745-1701
- PMC
- PMC2669579
- OpenAlex
- W2095651675
- Semantic Scholar
- 8cfeb68228d86d29ef7a86331cbc4aefac1a2e9b
- Cited by
- 1,134
- References
- 233
- Citations by year
- 2026: 45 · 2025: 41 · 2024: 43 · 2023: 49 · 2022: 54 · 2021: 81 · 2020: 79 · 2019: 59 · 2018: 80 · 2017: 91 · 2016: 87 · 2015: 79 · 2014: 63 · 2013: 101 · 2012: 67
- FWCI
- 7.65
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Schizophrenia Bulletin (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion, cc-by-nc-sa)
- UCL Discovery (University College London) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion, cc-by-nc-sa)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Wellcome Trust (056750, 088130)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- schizophrenia, dysconnectivity
- MeSH terms
- Acetylcholine, Awareness, Brain, Delusions, Dopamine, Electroencephalography, Hallucinations, Humans, Magnetic Resonance Imaging, Nerve Net, Neuronal Plasticity, Reality Testing, Schizophrenia, Schizophrenic Psychology, Serotonin, Synapses, Magnetoencephalography, Receptors, N-Methyl-D-Aspartate
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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