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 used conductance-based neural mass models to infer synaptic changes in disorders like schizophrenia from M/EEG recordings.
“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]
In “From Dysconnectivity to Model-Based Diagnostics” (page unavailable), the paper describes an EEG-based dynamic causal model of synaptic plasticity and work to infer plasticity from EEG/MEG data. It does not identify that model as conductance-based or report using it to infer synaptic changes in schizophrenia patients; it presents clinical use as a future possibility. (LLM, conf=0.86)
Experimental — accuracy not yet measuredSimilar Bayesian theories have previously been stated in the context of schizophrenia.
“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]
This model and variants thereof have already found widespread application to other psychiatric disorders with perceptual aberrations, in particular schizophrenia.
“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]
Schizophrenia is a complex brain disorder marked by impaired synaptic connectivity.
“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
Impaired synaptic connectivity is a prominent and consistent pathophysiological feature of schizophrenia.
“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
Dysconnectivity in schizophrenia may rely on impaired control of synaptic plasticity, notably NMDA-dependent plasticity.
“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]
Others have linked hallucinations to a failure to attenuate the sensory consequences of inner speech, analogous to the mechanism thought to underlie delusions of control.
“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]
Cycles of demyelination and remyelination in multiple sclerosis are associated with fluctuations in conduction velocity and symptomatology, including psychotic symptomatology.
“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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“than a patient in whom the primary abnormality is a cholinergic dysregulation of NMDARs (where symptoms might be dominated by perceptual abnormalities like hallucinations and impaired attention).(24,168) In other words, from the perspective of the dysconnection hypothesis, the diversity of clinical symptoms is due to…”
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- [3]Wernicke C Grundrisse der Psychiatrie 1906 Leipzig, Germany Thieme
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Functional hierarchy underlies preferential connectivity disturbances in schizophrenia
Yang, G. J., Murray, J. D., Wang, X.-J., Glahn, D. C., Pearlson, G. D., Repovs, G., Krystal, J. H., & Anticevic, A. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1508436113 · Cited by 153 · see citing works
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On hyperpriors and hypopriors: comment on Pellicano and Burr
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Self-citationResting-state thalamic dysconnectivity in schizophrenia and relationships with symptoms
Ferri, J. M., Ford, J. M., Roach, B. J., Turner, J. A., van Erp, T. G., Voyvodic, J. T., Preda, A., Belger, A., Bustillo, J., OʼLeary, D. S., et al. (2018) · Psychological Medicine · doi:10.1017/s003329171800003x · Cited by 147 · see citing works
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van Berlekom, A. B., Muflihah, C. H., Snijders, G. J. L., MacGillavry, H. D., Middeldorp, J., Hol, E. M., Kahn, R. S., & de Witte, L. D. (2019) · Schizophrenia Bulletin · doi:10.1093/schbul/sbz060 · Cited by 149 · see citing works
- 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.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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