Synaptic plasticity and dysconnection in schizophrenia
Open accessAbstract
Current pathophysiological theories of schizophrenia highlight the role of altered brain connectivity. This dysconnectivity could manifest 1) anatomically, through structural changes of association fibers at the cellular level, and/or 2) functionally, through aberrant control of synaptic plasticity at the synaptic level. In this article, we review the evidence for these theories, focusing on the modulation of synaptic plasticity. In particular, we discuss how dysconnectivity, observed between brain regions in schizophrenic patients, could result from abnormal modulation of N-methyl-D-aspartate (NMDA)-dependent plasticity by other neurotransmitter systems. We focus on the implication of the dysconnection hypothesis for functional imaging at the systems level. In particular, we review recent advances in measuring plasticity in the human brain using functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) that can be used to address dysconnectivity in schizophrenia. Promising experimental paradigms include perceptual and reinforcement learning. We describe how theoretical and causal models of brain responses might contribute to a mechanistic understanding of synaptic plasticity in schizophrenia.
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The findings support the proposed role of abnormal modulation of synaptic efficacy in the pathophysiology of schizophrenia.
“These findings support the proposed role of abnormal modulation of synaptic efficacy in the pathophysiology of schizophrenia (Friston and Frith, 1995, Friston, 1998, Stephan et al., 2006).”
From The functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding (2014) · cites this paper as Stephan et al., 2006
In the context of psychiatric disorders, the availability of behavioral or brain activity measurements suggests that validated generative models could be developed into clinically applicable 'computational assays,' in analogy to biochemical assays in internal medicine.
“In the context of psychiatric disorders, the relatively straightforward availability of behavioral or brain activity measurements suggests that validated generative models could be developed into clinically applicable “computational assays,” in analogy to biochemical assays in internal medicine (63).”
From Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice? (2016) · cites this paper as [63]
Similar 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 [63]
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 [63]
Numerous neurophysiological studies have provided evidence for signaling of prediction errors along forward connections and predictions along backward connections.
“Numerous neurophysiological studies have provided evidence for signaling of prediction errors along forward connections and predictions along backward connections [(63, 72) for reviews see (126, 127)].”
From Can Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice? (2016) · cites this paper as [63]
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 [41]
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Book Review: Neural Network Models of Schizophrenia
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A disturbance of nonlinear interdependence in scalp EEG of subjects with first episode schizophrenia
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Self-citationDeterminants of the auditory mismatch response
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Brain interactions in chronic schizophrenics under resting and activation conditions
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Implicit learning of visuospatial sequences in schizophenia.
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Stepping out of the spotlight: MMN attenuation as a function of distance from the attended location
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Contribution of AMPA and NMDA receptors to excitatory responses in the inferior colliculus
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Bayesian model selection for group studies
Stephan, K. E., Penny, W. D., Daunizeau, J., Moran, R. J., & Friston, K. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.03.025 · Cited by 1,423 · see citing works
Self-citationThe mismatch negativity: a review of underlying mechanisms
Garrido, M. I., Kilner, J. M., Stephan, K. E., & Friston, K. J. (2009) · Clinical Neurophysiology · doi:10.1016/j.clinph.2008.11.029 · Cited by 1,441 · see citing works
“Two features make the MMN a particularly interesting paradigm for schizophrenia research (see Stephan et al., 2006, for a review).”
BackgroundSelf-citationPrenatal Infection and Schizophrenia: A Review of Epidemiologic and Translational Studies
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Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring
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Self-citationThe Computational Anatomy of Psychosis
Adams, R. A., Stephan, K. E., Brown, H. R., Frith, C. D., & Friston, K. J. (2013) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2013.00047 · Cited by 850 · see citing works
“NMDA-Rs play a central role in theories of schizophrenia (Olney and Farber, 1995; Abi-Saab et al., 1998; Goff and Coyle, 2001; Stephan et al., 2006; Corlett et al., 2011).”
BackgroundSelf-citationSchizophrenia, neuroimaging and connectomics
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Development of structure–function coupling in human brain networks during youth
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Disrupted axonal fiber connectivity in schizophrenia
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An anatomical substrate for integration among functional networks in human cortex
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Toward a neurobiology of delusions
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Neural Mechanisms of a Genome-Wide Supported Psychosis Variant
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Hierarchical Prediction Errors in Midbrain and Basal Forebrain during Sensory Learning
Iglesias, S., Mathys, C., Brodersen, K. H., Kasper, L., Piccirelli, M., den Ouden, H. E. M., & Stephan, K. E. (2013) · Neuron · doi:10.1016/j.neuron.2013.09.009 · Cited by 342 · see citing works
Self-citationA Bayesian perspective on magnitude estimation
Petzschner, F. H., Glasauer, S., & Stephan, K. E. (2015) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2015.03.002 · Cited by 327 · see citing works
Self-citationSynapse Pathology in Psychiatric and Neurologic Disease
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Linking oligodendrocyte and myelin dysfunction to neurocircuitry abnormalities in schizophrenia
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Striatal Prediction Error Modulates Cortical Coupling
den Ouden, H. E. M., Daunizeau, J., Roiser, J., Friston, K. J., & Stephan, K. E. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.4458-09.2010 · Cited by 304 · see citing works
Self-citationAn integrative perspective on the role of dopamine in schizophrenia
Maia, T. V., & Frank, M. J. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.05.021 · Cited by 293 · see citing works
Computational psychiatry: towards a mathematically informed understanding of mental illness
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Small worlds inside big brains
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Computational approaches to psychiatry
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Glutamatergic model psychoses: prediction error, learning, and inference
Corlett, P. R., Honey, G. D., Krystal, J. H., & Fletcher, P. C. (2011) · Neuropsychopharmacology · doi:10.1038/npp.2010.163 · Cited by 229 · see citing works
From prediction error to psychosis: Ketamine as a pharmacological model of delusions
Corlett, P. R., Honey, G. D., & Fletcher, P. C. (2007) · Journal of Psychopharmacology · doi:10.1177/0269881107077716 · Cited by 227 · see citing works
Reduced prefrontal-parietal effective connectivity and working memory deficits in schizophrenia
Deserno, L., Sterzer, P., Wüstenberg, T., Heinz, A., & Schlagenhauf, F. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.3405-11.2012 · Cited by 214 · see citing works
Analyzing effective connectivity with functional magnetic resonance imaging
Stephan, K. E., & Friston, K. J. (2010) · WIREs Cognitive Science · doi:10.1002/wcs.58 · Cited by 202 · see citing works
Self-citationActivity-dependent neural plasticity from bench to bedside
Ganguly, K., & Poo, M.-M. (2013) · Neuron · doi:10.1016/j.neuron.2013.10.028 · Cited by 202 · see citing works
Petzschner, F. H., Weber, L. A. E., Gard, T., & Stephan, K. E. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.05.012 · Cited by 181 · see citing works
Self-citationReward feedback alterations in unmedicated schizophrenia patients: Relevance for delusions
Schlagenhauf, F., Sterzer, P., Schmack, K., Ballmaier, M., Rapp, M., Wrase, J., Juckel, G., Gallinat, J., & Heinz, A. (2009) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.12.016 · Cited by 195 · see citing works
Dynamic causal models of steady-state responses
Moran, R. J., Stephan, K. E., Seidenbecher, T., Pape, H.-C., Dolan, R. J., & Friston, K. J. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.09.048 · Cited by 195 · see citing works
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Translational perspectives for computational neuroimaging
Stephan, K. E., Iglesias, S., Heinzle, J., & Diaconescu, A. O. (2015) · Neuron · doi:10.1016/j.neuron.2015.07.008 · Cited by 169 · see citing works
Self-citationMisattribution of speech and impaired connectivity in patients with auditory verbal hallucinations
Mechelli, A., Allen, P., Amaro, E., Fu, C. H. Y., Williams, S. C. R., Brammer, M. J., Johns, L. C., & McGuire, P. K. (2007) · Human Brain Mapping · doi:10.1002/hbm.20341 · Cited by 175 · see citing works
Takao, K., Kobayashi, K., Hagihara, H., Ohira, K., Shoji, H., Hattori, S., Koshimizu, H., Umemori, J., Toyama, K., Nakamura, H. K., et al. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2013.38 · Cited by 173 · see citing works
Modelling trial-by-trial changes in the mismatch negativity
Lieder, F., Daunizeau, J., Garrido, M. I., Friston, K. J., & Stephan, K. E. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002911 · Cited by 168 · see citing works
A Dynamical Systems Hypothesis of Schizophrenia
Loh, M., Rolls, E. T., & Deco, G. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030228 · Cited by 164 · see citing works
TAPAS: An Open-Source Software Package for Translational Neuromodeling and Computational Psychiatry
Frässle, S., Aponte, E. A., Bollmann, S., Brodersen, K. H., Do, C. T., Harrison, O. K., Harrison, S. J., Heinzle, J., Iglesias, S., Kasper, L., et al. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.680811 · Cited by 169 · see citing works
Self-citationAre hallucinations due to an imbalance between excitatory and inhibitory influences on the brain?
Jardri, R., Hugdahl, K., Hughes, M., Brunelin, J., Waters, F., Alderson-Day, B., Smailes, D., Sterzer, P., Corlett, P. R., Leptourgos, P., et al. (2016) · Schizophrenia Bulletin · doi:10.1093/schbul/sbw075 · Cited by 157 · see citing works
A hemodynamic model for layered BOLD signals
Heinzle, J., Koopmans, P. J., den Ouden, H. E. M., Raman, S., & Stephan, K. E. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.10.025 · Cited by 144 · see citing works
Self-citationCan Bayesian Theories of Autism Spectrum Disorder Help Improve Clinical Practice?
Haker, H., Schneebeli, M., & Stephan, K. E. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00107 · Cited by 130 · see citing works
Self-citationRETRACTED: Impaired Visual Cortical Plasticity in Schizophrenia
Çavuş, I., Reinhart, R. M. G., Roach, B. J., Gueorguieva, R., Teyler, T. J., Clapp, W. C., Ford, J. M., Krystal, J. H., & Mathalon, D. H. (2012) · Biological Psychiatry · doi:10.1016/j.biopsych.2012.01.013 · Cited by 130 · see citing works
RetractedBrain Neuroplasticity in Healthy, Hyperactive and Psychotic Children: Insights from Neuroimaging
Rapoport, J. L., & Gogtay, N. (2008) · Neuropsychopharmacology · doi:10.1038/sj.npp.1301553 · Cited by 132 · see citing works
Dysfunctional neural plasticity in patients with schizophrenia
Daskalakis, Z. J., Christensen, B. K., Fitzgerald, P. B., & Chen, R. (2008) · Archives of General Psychiatry · doi:10.1001/archpsyc.65.4.378 · Cited by 130 · see citing works
Bayesian estimation of synaptic physiology from the spectral responses of neural masses
Moran, R. J., Stephan, K. E., Kiebel, S. J., Rombach, N., O'Connor, W. T., Murphy, K. J., Reilly, R. B., & Friston, K. J. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.01.025 · Cited by 126 · see citing works
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Impaired top-down processes in schizophrenia: a DCM study of ERPs
Dima, D., Dietrich, D. E., Dillo, W., & Emrich, H. M. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.086 · Cited by 122 · see citing works
Mismatch negativity encoding of prediction errors predicts S-ketamine-induced cognitive impairments
Schmidt, A., Bachmann, R., Kometer, M., Csomor, P. A., Stephan, K. E., Seifritz, E., & Vollenweider, F. X. (2012) · Neuropsychopharmacology · doi:10.1038/npp.2011.261 · Cited by 121 · see citing works
Menzies, L., Ooi, C., Kamath, S., Suckling, J., McKenna, P., Fletcher, P., Bullmore, E., & Stephenson, C. (2007) · Archives of General Psychiatry · doi:10.1001/archpsyc.64.2.156 · Cited by 120 · see citing works
Midbrain activation during pavlovian conditioning and delusional symptoms in schizophrenia
Romaniuk, L., Honey, G. D., King, J. R. L., Whalley, H. C., McIntosh, A. M., Levita, L., Hughes, M., Johnstone, E. C., Day, M., Lawrie, S. M., et al. (2010) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2010.169 · Cited by 113 · see citing works
de Bartolomeis, A., Barone, A., Vellucci, L., Mazza, B., Austin, M. C., Iasevoli, F., & Ciccarelli, M. (2022) · Molecular Neurobiology · doi:10.1007/s12035-022-02976-3 · Cited by 113 · see citing works
Modeling ketamine effects on synaptic plasticity during the mismatch negativity
Schmidt, A., Diaconescu, A. O., Kometer, M., Friston, K. J., Stephan, K. E., & Vollenweider, F. X. (2013) · Cerebral Cortex · doi:10.1093/cercor/bhs238 · Cited by 109 · see citing works
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Self-citationSmooth pursuit and visual occlusion: active inference and oculomotor control in schizophrenia
Adams, R. A., Perrinet, L. U., & Friston, K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0047502 · Cited by 91 · see citing works
Self-citationThe functional anatomy of schizophrenia: A dynamic causal modeling study of predictive coding
Fogelson, N., Litvak, V., Peled, A., Fernandez-del-Olmo, M., & Friston, K. (2014) · Schizophrenia Research · doi:10.1016/j.schres.2014.06.011 · Cited by 85 · see citing works
“…are expressed most densely in superficial layers (for example, dopamine— D1-R and NMDA-R) and are involved in the modulation of postsynaptic excitability or gain (Cohen and Servan-Schreiber, 1992; Friston and Frith, 1995; Friston, 1998; Wang, 2002; Coyle and Tsai, 2004; Stephan et al., 2006).”
Self-citationRanlund, S., Adams, R. A., Díez, Á., Constante, M., Dutt, A., Hall, M., Maestro Carbayo, A., McDonald, C., Petrella, S., Schulze, K., et al. (2016) · Human Brain Mapping · doi:10.1002/hbm.23035 · Cited by 77 · see citing works
Self-citationStructural organization of long-range GABAergic projection system of the hippocampus
Jinno, S. (2009) · Frontiers in Neuroanatomy · doi:10.3389/neuro.05.013.2009 · Cited by 75 · see citing works
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Multi-subject analyses with dynamic causal modeling
Kasess, C. H., Stephan, K. E., Weissenbacher, A., Pezawas, L., Moser, E., & Windischberger, C. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.037 · Cited by 70 · see citing works
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Striatal dopamine, reward, and decision making in schizophrenia
Deserno, L., Schlagenhauf, F., & Heinz, A. (2016) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2016.18.1/ldeserno · Cited by 58 · see citing works
Green tea extract enhances parieto-frontal connectivity during working memory processing
Schmidt, A., Hammann, F., Wölnerhanssen, B., Meyer-Gerspach, A. C., Drewe, J., Beglinger, C., & Borgwardt, S. (2014) · Psychopharmacology · doi:10.1007/s00213-014-3526-1 · Cited by 57 · see citing works
Cognitive Remediation in Schizophrenia
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Role of N-Methyl D-aspartate receptors in action-based predictive coding deficits in schizophrenia
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Model-based dynamical analysis of functional disconnection in schizophrenia
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Neuroimaging and plasticity in schizophrenia
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Neural and neuronal discoordination in schizophrenia: from ensembles through networks to symptoms
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Model-based prediction of muscarinic receptor function from auditory mismatch negativity responses
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Self-citationA predictive coding account of psychotic symptoms in autism spectrum disorder
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Apparent motion perception in patients with paranoid schizophrenia
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Computational Models of Hallucinations
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Schizophrenia patients show augmented spatial frame illusion for visual and visuomotor tasks
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Delayed early proprioceptive information processing in schizophrenia
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The generalized Hierarchical Gaussian Filter
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Self-citation
- Authors
- Stephan, K. E., Baldeweg, T., & Friston, K. J.
- Affiliations
- UCL Queen Square Institute of Neurology (GB)
- Great Ormond Street Hospital (GB)
- Corresponding author
- Stephan, Klaas E.
- Venue
- Biological Psychiatry
- Publisher
- Elsevier BV
- Published
- 2006-05
- Volume
- 59
- Issue
- 10
- Pages
- 929-939
- ISSN
- 0006-3223 (ISSN-L)
- OpenAlex
- W1998679999
- Cited by
- 841
- References
- 127
- Citations by year
- 2026: 20 · 2025: 21 · 2024: 27 · 2023: 18 · 2022: 30 · 2021: 40 · 2020: 41 · 2019: 47 · 2018: 29 · 2017: 55 · 2016: 45 · 2015: 64 · 2014: 55 · 2013: 69 · 2012: 51
- FWCI
- 5.96
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Locations
- Biological Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Wellcome Trust (056750)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- schizophrenia, synaptic plasticity, brain dysconnectivity, neurotransmitter systems, perceptual learning, reinforcement learning, association fibers
- MeSH terms
- Acetylcholine, Brain, Brain Mapping, Contingent Negative Variation, Dopamine, Electroencephalography, Humans, Models, Neurological, Nerve Fibers, Nerve Net, Neuronal Plasticity, Schizophrenia, Synapses, N-Methylaspartate, Glutamic Acid
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