Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Perspective
  • Published:

Schizophrenia and psychedelic state: Dysconnection versus hyper-connection. A perspective on two different models of psychosis stemming from dysfunctional integration processes

Abstract

Psychotic symptoms are a cross-sectional dimension affecting multiple diagnostic categories, despite schizophrenia represents the prototype of psychoses. Initially, dopamine was considered the most involved molecule in the neurobiology of schizophrenia. Over the next years, several biological factors were added to the discussion helping to constitute the concept of schizophrenia as a disease marked by a deficit of functional integration, contributing to the formulation of the Dysconnection Hypothesis in 1995. Nowadays the notion of dysconnection persists in the conceptualization of schizophrenia enriched by neuroimaging findings which corroborate the hypothesis. At the same time, in recent years, psychedelics received a lot of attention by the scientific community and astonishing findings emerged about the rearrangement of brain networks under the effect of these compounds. Specifically, a global decrease in functional connectivity was found, highlighting the disintegration of preserved and functional circuits and an increase of overall connectivity in the brain. The aim of this paper is to compare the biological bases of dysconnection in schizophrenia with the alterations of neuronal cyto-architecture induced by psychedelics and the consequent state of cerebral hyper-connection. These two models of psychosis, despite diametrically opposed, imply a substantial deficit of integration of neural signaling reached through two opposite paths.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1
Fig. 2: Altered neuronal integration processes in schizophrenia and psychedelic state.

Similar content being viewed by others

References

  1. Harrison PJ, Weinberger DR. Schizophrenia genes, gene expression, and neuropathology: On the matter of their convergence. Mol Psychiatry. 2005;10:40–68.

    CAS  Google Scholar 

  2. Guan F, Ni T, Zhu W, Williams LK, Cui LB, Li M, et al. Integrative omics of schizophrenia: From genetic determinants to clinical classification and risk prediction. Mol Psychiatry. 2022;27:113–26.

    Google Scholar 

  3. Landek-Salgado MA, Faust TE, Sawa A. Molecular substrates of schizophrenia: homeostatic signaling to connectivity. Mol Psychiatry. 2016;21:10–28.

    CAS  Google Scholar 

  4. Lv J, Di Biase M, Cash RFH, Cocchi L, Cropley VL, Klauser P, et al. Individual deviations from normative models of brain structure in a large cross-sectional schizophrenia cohort. Mol Psychiatry. 2021;26:3512–23.

    Google Scholar 

  5. Liu Z, Palaniyappan L, Wu X, Zhang K, Du J, Zhao Q, et al. Resolving heterogeneity in schizophrenia through a novel systems approach to brain structure: individualized structural covariance network analysis. Mol Psychiatry. 2021;26:7719–31.

    Google Scholar 

  6. Seitz-Holland J, Cetin-Karayumak S, Wojcik JD, Lyall A, Levitt J, Shenton ME, et al. Elucidating the relationship between white matter structure, demographic, and clinical variables in schizophrenia-a multicenter harmonized diffusion tensor imaging study. Mol Psychiatry. 2021;26:5357–70.

    Google Scholar 

  7. Barnett L, Muthukumaraswamy SD, Carhart-Harris RL, Seth AK. Decreased directed functional connectivity in the psychedelic state. Neuroimage. 2020;209:116462. https://doi.org/10.1016/j.neuroimage.2019.116462.

    Article  CAS  Google Scholar 

  8. Müller F, Dolder PC, Schmidt A, Liechti ME, Borgwardt S. Altered network hub connectivity after acute LSD administration. NeuroImage Clin. 2018;18:694–701.

    Google Scholar 

  9. Atasoy S, Roseman L, Kaelen M, Kringelbach ML, Deco G, Carhart-Harris RL. Connectome-harmonic decomposition of human brain activity reveals dynamical repertoire re-organization under LSD. Sci Rep. 2017;7:17661.

    Google Scholar 

  10. Tagliazucchi E, Carhart-Harris R, Leech R, Nutt D, Chialvo DR. Enhanced repertoire of brain dynamical states during the psychedelic experience. Hum Brain Mapp. 2014;35:5442–56.

    Google Scholar 

  11. Herzog R, Mediano PAM, Rosas FE, Carhart-Harris R, Perl YS, Tagliazucchi E, et al. A mechanistic model of the neural entropy increase elicited by psychedelic drugs. Sci Rep. 2020;10:17725. https://doi.org/10.1038/s41598-020-74060-6.

    Article  CAS  Google Scholar 

  12. de Vos CMH, Mason NL, Kuypers KPC. Psychedelics and Neuroplasticity: A Systematic Review Unraveling the Biological Underpinnings of Psychedelics. Front psychiatry. 2021;12:724606.

    Google Scholar 

  13. Ly C, Greb AC, Cameron LP, Wong JM, Barragan EV, Wilson PC, et al. Psychedelics Promote Structural and Functional Neural Plasticity. Cell Rep. 2018;23:3170–82.

    CAS  Google Scholar 

  14. Lukasiewicz K, Baker JJ, Zuo Y, Lu J. Serotonergic Psychedelics in Neural Plasticity. Front Mol Neurosci. 2021;14:748359. https://doi.org/10.3389/fnmol.2021.748359.

    Article  CAS  Google Scholar 

  15. Savalia NK, Shao LX, Kwan AC. A Dendrite-Focused Framework for Understanding the Actions of Ketamine and Psychedelics. Trends Neurosci. 2021;44:260–75.

    CAS  Google Scholar 

  16. Müller F, Lenz C, Dolder P, Lang U, Schmidt A, Liechti M, et al. Increased thalamic resting-state connectivity as a core driver of LSD-induced hallucinations. Acta Psychiatr Scand. 2017;136:648–57.

    Google Scholar 

  17. Luppi AI, Carhart-Harris RL, Roseman L, Pappas I, Menon DK, Stamatakis EA. LSD alters dynamic integration and segregation in the human brain. Neuroimage. 2021;227:117653. https://doi.org/10.1016/j.neuroimage.2020.117653.

    Article  Google Scholar 

  18. Carhart-Harris RL, Friston KJ. REBUS and the anarchic brain: Toward a unified model of the brain action of psychedelics. Pharm Rev. 2019;71:316–44.

    CAS  Google Scholar 

  19. Leptourgos P, Fortier-Davy M, Carhart-Harris R, Corlett PR, Dupuis D, Halberstadt AL, et al. Hallucinations Under Psychedelics and in the Schizophrenia Spectrum: An Interdisciplinary and Multiscale Comparison. Schizophr Bull. 2020;46:1396–408.

    Google Scholar 

  20. Ungvari GS. The Wernicke-Kleist-Leonhard school of psychiatry. Biol Psychiatry. 1993;34:749–52.

    CAS  Google Scholar 

  21. Moskowitz A, Heim G. Eugen Bleuler’s Dementia Praecox or the Group of Schizophrenias (1911): A Centenary Appreciation and Reconsideration. Schizophr Bull 2011;37:471–9.

    Google Scholar 

  22. Andreasen NC. A unitary model of schizophrenia: Bleuler’s “fragmented phrene” as schizencephaly. Arch Gen Psychiatry. 1999;56:781–7.

    CAS  Google Scholar 

  23. Friston KJ, Frith CD. Schizophrenia: A disconnection syndrome? Clin Neurosci. 1995;3:89–97.

    CAS  Google Scholar 

  24. Friston KJ. Schizophrenia and the disconnection hypothesis. Acta Psychiatr Scand Suppl. 1999;99:68–79.

    Google Scholar 

  25. Stephan KE, Baldeweg T, Friston KJ. Synaptic plasticity and dysconnection in schizophrenia. Biol Psychiatry. 2006;59:929–39.

    CAS  Google Scholar 

  26. Collin G, Turk E, Van Den Heuvel MP. Connectomics in Schizophrenia: From Early Pioneers to Recent Brain Network Findings. Biol Psychiatry Cogn Neurosci neuroimaging. 2016;1:199–208.

    Google Scholar 

  27. Friston K, Brown HR, Siemerkus J, Stephan KE. The dysconnection hypothesis (2016). Schizophr Res. 2016;176:83–94. http://linkinghub.elsevier.com/retrieve/pii/S092099641630331

    Google Scholar 

  28. Dong D, Wang Y, Chang X, Luo C, Yao D. Dysfunction of large-scale brain networks in schizophrenia: A meta-analysis of resting-state functional connectivity. Schizophr Bull. 2018;44:168–81.

    Google Scholar 

  29. Bullmore E, Sporns O. The economy of brain network organization. Nat Rev Neurosci. 2012;13:336–49.

    CAS  Google Scholar 

  30. Hilgetag CC, Goulas A. “Hierarchy” in the organization of brain networks. Philos Trans R Soc Lond B Biol Sci. 2020;375:20190319.

    Google Scholar 

  31. Tandon R, Nasrallah HA, Keshavan MS. Schizophrenia, “just the facts” 4. Clinical features and conceptualization. Schizophr Res. 2009;110:1–23.

    Google Scholar 

  32. Rosato M, Stringer S, Gebuis T, Paliukhovich I, Li KW, Posthuma D, et al. Combined cellomics and proteomics analysis reveals shared neuronal morphology and molecular pathway phenotypes for multiple schizophrenia risk genes. Mol Psychiatry. 2021;26:784–99.

    Google Scholar 

  33. Kochunov P, Thompson PM, Hong LE. Toward High Reproducibility and Accountable Heterogeneity in Schizophrenia Research. JAMA Psychiatry. 2019;76:680–1.

    Google Scholar 

  34. Chan SY, Brady RO, Lewandowski KE, Higgins A, Öngür D, Hall MH. Dynamic and progressive changes in thalamic functional connectivity over the first five years of psychosis. Mol Psychiatry. 2022;27:1177–83.

    Google Scholar 

  35. Cumming P, Abi-Dargham A, Gründer G. Molecular imaging of schizophrenia: Neurochemical findings in a heterogeneous and evolving disorder. Behav Brain Res. 2021;398:113004. https://doi.org/10.1016/j.bbr.2020.113004.

    Article  CAS  Google Scholar 

  36. Cao H, Zhou H, Cannon TD. Functional connectome-wide associations of schizophrenia polygenic risk. Mol Psychiatry. 2021;26:2553–61.

    Google Scholar 

  37. Stauffer EM, Bethlehem RAI, Warrier V, Murray GK, Romero-Garcia R, Seidlitz J, et al. Grey and white matter microstructure is associated with polygenic risk for schizophrenia. Mol Psychiatry. 2021;26:7709–18.

    CAS  Google Scholar 

  38. Druart M, Nosten-Bertrand M, Poll S, Crux S, Nebeling F, Delhaye C, et al. Elevated expression of complement C4 in the mouse prefrontal cortex causes schizophrenia-associated phenotypes. Mol Psychiatry. 2021;26:3489–501.

    CAS  Google Scholar 

  39. Cuenod M, Steullet P, Cabungcal JH, Dwir D, Khadimallah I, Klauser P, et al. Caught in vicious circles: A perspective on dynamic feed-forward loops driving oxidative stress in schizophrenia. Mol Psychiatry. 2022;27:1886–97.

    CAS  Google Scholar 

  40. Woo JJ, Pouget JG, Zai CC, Kennedy JL. The complement system in schizophrenia: Where are we now and what’s next? Mol Psychiatry. 2020;25:114–30.

    CAS  Google Scholar 

  41. Kelly S, Jahanshad N, Zalesky A, Kochunov P, Agartz I, Alloza C, et al. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: Results from the ENIGMA Schizophrenia DTI Working Group. Mol Psychiatry. 2018;23:1261–9.

    CAS  Google Scholar 

  42. Klauser P, Baker ST, Cropley VL, Bousman C, Fornito A, Cocchi L, et al. White Matter Disruptions in Schizophrenia Are Spatially Widespread and Topologically Converge on Brain Network Hubs. Schizophr Bull. 2017;43:425–35.

    Google Scholar 

  43. Sun Y, Chen Y, Lee R, Bezerianos A, Collinson SL, Sim K. Disruption of brain anatomical networks in schizophrenia: A longitudinal, diffusion tensor imaging based study. Schizophr Res. 2016;171:149–57.

    Google Scholar 

  44. Pettersson-Yeo W, Allen P, Benetti S, McGuire P, Mechelli A. Dysconnectivity in schizophrenia: Where are we now? Neurosci Biobehav Rev. 2011;35:1110–24.

    Google Scholar 

  45. Sun X, Liu J, Ma Q, Duan J, Wang X, Xu Y, et al. Disrupted Intersubject Variability Architecture in Functional Connectomes in Schizophrenia. Schizophr Bull. 2021;47:837–48.

    Google Scholar 

  46. Roalf DR, Gur RE, Verma R, Parker WA, Quarmley M, Ruparel K, et al. White matter microstructure in schizophrenia: Associations to neurocognition and clinical symptomatology. Schizophr Res. 2015;161:42–9.

    Google Scholar 

  47. Faludi G, Mirnics K. Synaptic changes in the brain of subjects with schizophrenia. Int J Dev Neurosci. 2011;29:305–9.

    Google Scholar 

  48. Feinberg I. Schizophrenia: caused by a fault in programmed synaptic elimination during adolescence? J Psychiatr Res. 1982;17:319–34.

    Google Scholar 

  49. Hoffman RE, Dobscha SK. Cortical pruning and the development of schizophrenia: A computer model. Schizophr Bull. 1989;15:477–90.

    CAS  Google Scholar 

  50. Osimo EF, Beck K, Marques TR, Howes OD. Synaptic loss in schizophrenia: A meta-analysis and systematic review of synaptic protein and mRNA measures. Mol Psychiatry. 2019;24:549–61.

    CAS  Google Scholar 

  51. Hof PR, Schmitz C. The quantitative neuropathology of schizophrenia. Acta Neuropathol. 2009;117:345–6.

    Google Scholar 

  52. Li W, Lv L, Luo XJ. In vivo study sheds new light on the dendritic spine pathology hypothesis of schizophrenia. Mol Psychiatry. 2022;27:1866–8.

    Google Scholar 

  53. Li Y, Li S, Liu J, Huo Y, Luo XJ. The schizophrenia susceptibility gene NAGA regulates dendritic spine density: Further evidence for the dendritic spine pathology of schizophrenia. Mol Psychiatry. 2021;26:7102–4.

    CAS  Google Scholar 

  54. Bellon A, Feuillet V, Cortez-Resendiz A, Mouaffak F, Kong L, Hong LE, et al. Dopamine-induced pruning in monocyte-derived-neuronal-like cells (MDNCs) from patients with schizophrenia. Mol Psychiatry. 2022;27:2787–802.

    CAS  Google Scholar 

  55. Gururajan A, Van Den Buuse M. Is the mTOR-signalling cascade disrupted in Schizophrenia? J Neurochem. 2014;129:377–87.

    CAS  Google Scholar 

  56. Chadha R, Meador-Woodruff JH. Downregulated AKT-mTOR signaling pathway proteins in dorsolateral prefrontal cortex in Schizophrenia. Neuropsychopharmacology 2020;45:1059–67.

    CAS  Google Scholar 

  57. Chadha R, Alganem K, Mccullumsmith RE, Meador-Woodruff JH. mTOR kinase activity disrupts a phosphorylation signaling network in schizophrenia brain. Mol Psychiatry. 2021;26:6868–79.

    CAS  Google Scholar 

  58. Camchong J, MacDonald AW, Bell C, Mueller BA, Lim KO. Altered functional and anatomical connectivity in schizophrenia. Schizophr Bull. 2011;37:640–50.

    Google Scholar 

  59. Skudlarski P, Jagannathan K, Anderson K, Stevens MC, Calhoun VD, Skudlarska BA, et al. Brain Connectivity Is Not Only Lower but Different in Schizophrenia: A Combined Anatomical and Functional Approach. Biol Psychiatry. 2010;68:61–9.

    Google Scholar 

  60. Hare SM, Ford JM, Mathalon DH, Damaraju E, Bustillo J, Belger A, et al. Salience-default mode functional network connectivity linked to positive and negative symptoms of schizophrenia. Schizophr Bull. 2019;45:892–901.

    Google Scholar 

  61. Lee WH, Doucet GE, Leibu E, Frangou S. Resting-state network connectivity and metastability predict clinical symptoms in schizophrenia. Schizophr Res. 2018;201:208–16.

    Google Scholar 

  62. Fan F, Tan S, Huang J, Chen S, Fan H, Wang Z, et al. Functional disconnection between subsystems of the default mode network in schizophrenia. Psychol Med. 2020:1–11. https://doi.org/10.1017/S003329172000416X. Epub ahead of print.

  63. Doucet GE, Moser DA, Luber MJ, Leibu E, Frangou S. Baseline brain structural and functional predictors of clinical outcome in the early course of schizophrenia. Mol Psychiatry. 2020;25:863–72.

    Google Scholar 

  64. Mehta UM, Ibrahim FA, Sharma MS, Venkatasubramanian G, Thirthalli J, Bharath RD, et al. Resting-state functional connectivity predictors of treatment response in schizophrenia – A systematic review and meta-analysis. Schizophr Res. 2021;237:153–65.

    Google Scholar 

  65. Salman MS, Vergara VM, Damaraju E, Calhoun VD. Decreased Cross-Domain Mutual Information in Schizophrenia From Dynamic Connectivity States. Front Neurosci. 2019;13:1–13.

    Google Scholar 

  66. Fernández A, Gómez C, Hornero R, López-Ibor JJ. Complexity and schizophrenia. Prog Neuro-Psychopharmacology. Biol Psychiatry. 2013;45:267–76.

    Google Scholar 

  67. Takahashi T, Cho RY, Mizuno T, Kikuchi M, Murata T, Takahashi K, et al. Antipsychotics reverse abnormal EEG complexity in drug-naive schizophrenia: A multiscale entropy analysis. Neuroimage 2010;51:173–82.

    CAS  Google Scholar 

  68. Carhart-Harris RL. The entropic brain - revisited. Neuropharmacology 2018;142:167–78.

    CAS  Google Scholar 

  69. Carhart-Harris RL. Serotonin, psychedelics and psychiatry. World Psychiatry. 2018;17:358–9.

    Google Scholar 

  70. Pallavicini C, Vilas MG, Villarreal M, Zamberlan F, Muthukumaraswamy S, Nutt D, et al. Spectral signatures of serotonergic psychedelics and glutamatergic dissociatives. Neuroimage 2019;200:281–91.

    CAS  Google Scholar 

  71. Olson DE. sychoplastogens: A Promising Class of Plasticity-Promoting Neurotherapeutics. J Exp Neurosci. 2018;12:1179069518800508. https://doi.org/10.1177/1179069518800508.

    Article  Google Scholar 

  72. Aleksandrova LR, Phillips AG. Neuroplasticity as a convergent mechanism of ketamine and classical psychedelics. Trends Pharm Sci. 2021;42:929–42.

    CAS  Google Scholar 

  73. Ly C, Greb AC, Vargas MV, Duim WC, Grodzki ACG, Lein PJ, et al. Transient Stimulation with Psychoplastogens Is Sufficient to Initiate Neuronal Growth. ACS Pharm Transl Sci. 2021;4:452–60.

    CAS  Google Scholar 

  74. Banks MI, Zahid Z, Jones NT, Sultan ZW, Wenthur CJ. Catalysts for change: The cellular neurobiology of psychedelics. Mol Biol Cell. 2021;32:1135–44.

    CAS  Google Scholar 

  75. Shao LX, Liao C, Gregg I, Davoudian PA, Savalia NK, Delagarza K, et al. Psilocybin induces rapid and persistent growth of dendritic spines in frontal cortex in vivo. Neuron 2021;109:2535–2544.

    CAS  Google Scholar 

  76. Smitha KA, Akhil Raja K, Arun KM, Rajesh PG, Thomas B, Kapilamoorthy TR, et al. Resting state fMRI: A review on methods in resting state connectivity analysis and resting state networks. Neuroradiol J 2017;30:305–17.

    CAS  Google Scholar 

  77. Vejmola Č, Tylš F, Piorecká V, Koudelka V, Kadeřábek L, Novák T, et al. Psilocin, LSD, mescaline, and DOB all induce broadband desynchronization of EEG and disconnection in rats with robust translational validity. Transl Psychiatry. 2021;11:506. https://doi.org/10.1038/s41398-021-01603-4.

    Article  CAS  Google Scholar 

  78. Muthukumaraswamy SD, Carhart-Harris RL, Moran RJ, Brookes MJ, Williams TM, Errtizoe D, et al. Broadband cortical desynchronization underlies the human psychedelic state. J Neurosci. 2013;33:15171–83.

    CAS  Google Scholar 

  79. Liechti ME. Modern Clinical Research on LSD. Neuropsychopharmacology 2017;42:2114–27.

    CAS  Google Scholar 

  80. Preller KH, Vollenweider FX. Phenomenology, structure, and dynamic of psychedelic states. Curr Top Behav Neurosci. 2018;36:221–56.

    CAS  Google Scholar 

  81. Schmid Y, Enzler F, Gasser P, Grouzmann E, Preller KH, Vollenweider FX, et al. Acute effects of lysergic acid diethylamide in healthy subjects. Biol Psychiatry. 2015;78:544–53.

    CAS  Google Scholar 

  82. Madsen MK, Stenbæk DS, Arvidsson A, Armand S, Marstrand-Joergensen MR, Johansen SS, et al. Psilocybin-induced changes in brain network integrity and segregation correlate with plasma psilocin level and psychedelic experience. Eur Neuropsychopharmacol. 2021;50:121–32.

    CAS  Google Scholar 

  83. Raichle ME. The brain’s default mode network. Annu Rev Neurosci. 2015;38:433–47.

    CAS  Google Scholar 

  84. Davey CG, Pujol J, Harrison BJ. Mapping the self in the brain’s default mode network. Neuroimage 2016;132:390–7.

    Google Scholar 

  85. Leech R, Scott G, Carhart-Harris R, Turkheimer F, Taylor-Robinson SD, Sharp DJ. Spatial dependencies between large-scale brain networks. PLoS One. 2014;9:e98500. https://doi.org/10.1371/journal.pone.0098500.

    Article  CAS  Google Scholar 

  86. Tagliazucchi E, Roseman L, Kaelen M, Orban C, Muthukumaraswamy SD, Murphy K, et al. Increased Global Functional Connectivity Correlates with LSD-Induced Ego Dissolution. Curr Biol. 2016;26:1043–50.

    CAS  Google Scholar 

  87. Osmond H. A review of the clinical effects of psychotomimetic agents. Ann N. Y Acad Sci. 1957;66:418–34.

    CAS  Google Scholar 

  88. Roseman L, Sereno MI, Leech R, Kaelen M, Orban C, McGonigle J, et al. LSD alters eyes-closed functional connectivity within the early visual cortex in a retinotopic fashion. Hum Brain Mapp. 2016;37:3031–40.

    Google Scholar 

  89. Klimesch W, Sauseng P, Hanslmayr S. EEG alpha oscillations: the inhibition-timing hypothesis. Brain Res Rev. 2007;53:63–88.

    Google Scholar 

  90. Nutt D, Erritzoe D, Carhart-Harris R. Psychedelic Psychiatry’s Brave New World. Cell 2020;181:24–8.

    CAS  Google Scholar 

  91. Kraehenmann R, Pokorny D, Aicher H, Preller KH, Pokorny T, Bosch OG, et al. LSD Increases Primary Process Thinking via Serotonin 2A Receptor Activation. Front Pharmacol. 2017;8:814. https://doi.org/10.3389/fphar.2017.00814.

    Article  CAS  Google Scholar 

  92. Girn M, Mills C, Roseman L, Carhart-Harris RL, Christoff K. Updating the dynamic framework of thought: Creativity and psychedelics. Neuroimage. 2020;213:116726. https://doi.org/10.1016/j.neuroimage.2020.116726.

    Article  Google Scholar 

  93. Nakahara T, Tsugawa S, Noda Y, Ueno F, Honda S, Kinjo M, et al. Glutamatergic and GABAergic metabolite levels in schizophrenia-spectrum disorders: a meta-analysis of 1 H-magnetic resonance spectroscopy studies. Mol Psychiatry. 2022;27:744–57.

    CAS  Google Scholar 

  94. Gao WJ, Yang SS, Mack NR, Chamberlin LA. Aberrant maturation and connectivity of prefrontal cortex in schizophrenia-contribution of NMDA receptor development and hypofunction. Mol Psychiatry. 2022;27:731–43.

    CAS  Google Scholar 

  95. Kath WL. Computational modeling of dendrites. J Neurobiol. 2005;64:91–9.

    Google Scholar 

  96. Chen JY. A simulation study investigating the impact of dendritic morphology and synaptic topology on neuronal firing patterns. Neural Comput. 2010;22:1086–111.

    Google Scholar 

  97. Fletcher A. Action potential: generation and propagation. Anaesth Intensive Care Med. 2019;20:243–7.

    Google Scholar 

  98. Seidl AH. Regulation of conduction time along axons. Neuroscience 2014;276:126–34.

    CAS  Google Scholar 

  99. Houben AM. Frequency Selectivity of Neural Circuits With Heterogeneous Discrete Transmission Delays. Neural Comput. 2021;33:2068–86.

    Google Scholar 

  100. Guo W, Fouda ME, Eltawil AM, Salama KN. Neural Coding in Spiking Neural Networks: A Comparative Study for Robust Neuromorphic Systems. Front Neurosci. 2021;15:638474. https://doi.org/10.3389/fnins.2021.638474.

    Article  Google Scholar 

  101. Schmidt H, Knösche TR. Action potential propagation and synchronisation in myelinated axons. PLoS Comput Biol. 2019;15:e1007004. https://doi.org/10.1371/journal.pcbi.1007004.

    Article  CAS  Google Scholar 

  102. Gulledge AT, Kampa BM, Stuart GJ. Synaptic integration in dendritic trees. J Neurobiol. 2005;64:75–90.

    CAS  Google Scholar 

  103. Magee JC. Dendritic integration of excitatory synaptic input. Nat Rev Neurosci. 2000;1:181–90.

    CAS  Google Scholar 

  104. Preller KH, Duerler P, Burt JB, Ji JL, Adkinson B, Stämpfli P, et al. Psilocybin induces time-dependent changes in global functional connectivity. Biol Psychiatry. 2020;88:197–207.

    CAS  Google Scholar 

  105. Goudar V, Buonomano DV. Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks. Elife. 2018;7:e31134. https://doi.org/10.7554/eLife.31134.

    Article  Google Scholar 

  106. Raichle ME, Snyder AZ. A default mode of brain function: A brief history of an evolving idea. Neuroimage 2007;37:1083–90.

    Google Scholar 

  107. Fazelpour S, Thompson E. The Kantian brain: Brain dynamics from a neurophenomenological perspective. Curr Opin Neurobiol. 2015;31:223–9.

    CAS  Google Scholar 

  108. Northoff G. Immanuel Kant’s mind and the brain’s resting state. Trends Cogn Sci. 2012;16:356–9.

    Google Scholar 

  109. Kercel SW. The endogenous brain. J Integr Neurosci. 2004;3:61–84.

    Google Scholar 

  110. Kercel SW. The role of volume transmission in an endogenous brain. J Integr Neurosci. 2004;3:7–18.

    Google Scholar 

  111. Canu E, Agosta F, Filippi M. A selective review of structural connectivity abnormalities of schizophrenic patients at different stages of the disease. Schizophr Res. 2015;161:19–28.

    Google Scholar 

  112. Bassett DS, Nelson BG, Mueller BA, Camchong J, Lim KO. Altered resting state complexity in schizophrenia. Neuroimage 2012;59:2196–207.

    Google Scholar 

  113. Davis AK, Barrett FS, May DG, Cosimano MP, Sepeda ND, Johnson MW, et al. Effects of psilocybin-assisted therapy on major depressive disorder: A randomized clinical trial. JAMA Psychiatry. 2021;78:481–9.

    Google Scholar 

  114. Reiff CM, Richman EE, Nemeroff CB, Carpenter LL, Widge AS, Rodriguez CI, et al. Psychedelics and psychedelic-assisted psychotherapy. Am J Psychiatry. 2020;177:391–410.

    Google Scholar 

  115. Lu J, Tjia M, Mullen B, Cao B, Lukasiewicz K, Shah-Morales S, et al. An analog of psychedelics restores functional neural circuits disrupted by unpredictable stress. Mol Psychiatry. 2021;26:6237–52.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Contributions

JS: Conceptualization and Writing-Original Draft preparation; MB, MS, FCo, RC: Writing-Reviewing and Editing, Supervision, Validation. FM, GA, FCu: Methodology, literature review. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Jacopo Sapienza.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Rights and permissions

Springer Nature or its licensor 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

Sapienza, J., Bosia, M., Spangaro, M. et al. Schizophrenia and psychedelic state: Dysconnection versus hyper-connection. A perspective on two different models of psychosis stemming from dysfunctional integration processes. Mol Psychiatry 28, 59–67 (2023). https://doi.org/10.1038/s41380-022-01721-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41380-022-01721-5

Search

Quick links