The role of impairment of predictive coding mechanisms in the genesis of psychopathology in schizophrenia
Full Text:
Subscribers Only
|
Suggested citation:
Rabinovich EI, Telesheva KYu. [The role of impairment of predictive coding mechanisms in the genesis of psychopathology in schizophrenia]. Rossiiskii psikhiatricheskii zhurnal [Russian Journal of Psychiatry]. 2024;(1):78-86. Russian
In this scientific review, in order to systematize ideas about the relationship between impairment of the mechanisms of predictive coding and development of certain symptoms and psychopathological states in schizophrenia, we have carried out the critical analysis of existing theoretical and empirical studies. Predictive coding mechanisms underlie the functioning of almost all mental processes and explain the phenomena of anticipation, which is one of the most important regulatory mechanisms in human activity. Violation of the anticipation process can act as the main link in the development of various psychopathological processes. This makes it relevant to search for the psychophysiological foundations of predictive coding for understanding the pathogenesis of pathological conditions and creating approaches to their assessment and correction. The results of the theoretical study allow us to interpret the symptoms of schizophrenia based on the theory of predictive coding, and identify patterns in their development. In conclusion, we argue the validity of the theory of predictive coding as a theoretical and methodological basis for studying the mechanisms of the pathogenesis of mental disorders.
Keywords prediction; anticipation; schizophrenia; hallucinations; delusions; agency
1. Kahn RS, Sommer IE, Murray RM, et al. Schizophrenia. Nat Rev Dis Primers. 2015;1:15067. DOI: https://doi.org/10.1038/nrdp.2015.67 2. Sullivan PF, Kendler KS, Neale MC. Schizophrenia as a complex trait: evidence from a meta-analysis of twin studies. Arch Gen Psychiatry. 2003;60(12):1187–92. DOI: https://doi.org/10.1001/archpsyc.60.12.1187 3. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511(7510):421–7. DOI: https://doi.org/10.1038/nature13595 4. Millidge B, Seth A, Buckley CL. Predictive Coding: A Theoretical and Experimental Review. 2022. URL: https://arxiv.org/abs/2107.12979 (accessed on: 07.09.2023). 5. Samylkin DV, Tkachenko AA. [Concepts of the level violation of regulatory processes in schizophrenia: from probabilistic forecasting to predictive coding]. Rossiiskii psikhiatricheskii zhurnal [Russian Journal of Psychiatry]. 2020;(5); 34–46. (In Russ.) DOI: https://doi.org/10.24411/1560-957Х-2020-10504 6. Rao RP, Ballard DH. Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects. Nat Neurosci. 1999;2(1):79–87. DOI: https://doi.org/10.1038/4580 7. McClelland JL, Rumelhart DE. An Interactive Activation Model of Context Effects in Letter Perception: I. An Account of Basic Findings. Psychol Rev. 1981;88(5);375–407. DOI: https://doi.org/10.1037/0033-295x.88.5.375 8. Friston K. Hierarchical models in the brain. PLoS Comput Biol. 2008;4(11):e1000211. DOI: https://doi.org/10.1371/journal.pcbi.1000211 9. Falikman MA. [The principle of predictive coding in modern cognitive research]. Voprosy psikhologii. 2021;(3):3–23. (In Russ.) 10. Sterzer P, Voss M, Schlagenhauf F, Heinz A. Decision-making in schizophrenia: A predictive-coding perspective. Neuroimage. 2019;190:133–43. DOI: https://doi.org/10.1016/j.neuroimage.2018.05.074 11. Friston K, Kilner J, Harrison L. A free energy principle for the brain. J Physiol Paris. 2006;100(1–3):70–87. DOI: https://doi.org/10.1016/j.jphysparis.2006.10.001 12. Clark A. Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav Brain Sci. 2013;36(3):181–204. DOI: https://doi.org/10.1017/S0140525X12000477 13. Adams RA, Stephan KE, Brown HR, et al. The computational anatomy of psychosis. Front Psychiatry. 2013;4:47. DOI: https://doi.org/10.3389/fpsyt.2013.00047 14. Liddle PF, Liddle EB. Imprecise Predictive Coding Is at the Core of Classical Schizophrenia. Front Hum Neurosci. 2022;16:818711. DOI: https://doi.org/10.3389/fnhum.2022.818711 15. Friston K. A theory of cortical responses. Philos Trans R Soc Lond B Biol Sci. 2005;360(1456):815–36. DOI: https://doi.org/10.1098/rstb.2005.1622 16. Lavin A, Nogueira L, Lapish CC, et al. Mesocortical dopamine neurons operate in distinct temporal domains using multimodal signaling. J Neurosci. 2005;25(20):5013–23. DOI: https://doi.org/10.1523/JNEUROSCI.0557-05.2005 17. Corlett PR, Honey GD, Krystal JH, Fletcher PC. Glutamatergic model psychoses: prediction error, learning, and inference. Neuropsychopharmacology. 2011;36(1):294–315. DOI: https://doi.org/10.1038/npp.2010.163 18. Stephan KE, Baldeweg T, Friston KJ. Synaptic plasticity and dysconnection in schizophrenia. Biol Psychiatry. 2006;59(10):929–39. DOI: https://doi.org/10.1016/j.biopsych.2005.10.005 19. Harrison PJ, Lewis DA, Kleinman JE. Neuropathology of Schizophrenia. In: Schizophrenia: Third Edition. Weinberger DR, Harrison PJ, editors. Wiley-Blackwell; 2011. p. 372–92. 20. Breier A, Su TP, Saunders R, et al. Schizophrenia is associated with elevated amphetamine-induced synaptic dopamine concentrations: evidence from a novel positron emission tomography method. Proc Natl Acad Sci U S A. 1997;94(6):2569–74. DOI: https://doi.org/10.1073/pnas.94.6.2569 21. Howes OD, Kapur S. The dopamine hypothesis of schizophrenia: version III--the final common pathway. Schizophr Bull. 2009;35(3):549–62. DOI: https://doi.org/10.1093/schbul/sbp006 22. Stone JM, Erlandsson K, Arstad E, et al. Relationship between ketamine-induced psychotic symptoms and NMDA receptor occupancy: a [(123)I]CNS-1261 SPET study. Psychopharmacology (Berl). 2008;197(3):401–8. DOI: https://doi.org/10.1007/s00213-007-1047-x 23. Kessler RM, Woodward ND, Riccardi P, et al. Dopamine D2 receptor levels in striatum, thalamus, substantia nigra, limbic regions, and cortex in schizophrenic subjects. Biol Psychiatry. 2009;65(12):1024–31. DOI: https://doi.org/10.1016/j.biopsych.2008.12.029 24. Stephan KE, Friston KJ, Frith CD. Dysconnection in schizophrenia: from abnormal synaptic plasticity to failures of self-monitoring. Schizophr Bull. 2009;35(3):509–27. DOI: https://doi.org/10.1093/schbul/sbn176 25. Näätänen R, Gaillard AW, Mäntysalo S. Early selective-attention effect on evoked potential reinterpreted. Acta Psychol. 1978;42(4):313–29. DOI: https://doi.org/10.1016/0301-0511(79)90053-x 26. Martin BA, Tremblay KL, Korczak P. Speech evoked potentials: from the laboratory to the clinic. Ear Hear. 2008;29(3):285–313. DOI: https://doi.org/10.1097/AUD.0b013e3181662c0e 27. Näätänen R. The perception of speech sounds by the human brain as reflected by the mismatch negativity (MMN) and its magnetic equivalent (MMNm). Psychophysiology. 2001;38(1):1–21. DOI: https://doi.org/10.1017/s0048577201000208 28. Umbricht D, Krljes S. Mismatch negativity in schizophrenia: a meta-analysis. Schizophr Res. 2005;76(1):1–23. DOI: https://doi.org/10.1016/j.schres.2004.12.002 29. Todd J, Harms L, Schall U, Michie PT. Mismatch negativity: translating the potential. Front Psychiatry. 2013;4:171. DOI: https://doi.org/10.3389/fpsyt.2013.00171 30. Hauke DJ, Charlton CE, Schmidt A, et al. Aberrant Hierarchical Prediction Errors Are Associated With Transition to Psychosis: A Computational Single-Trial Analysis of the Mismatch Negativity. Biol Psychiatry Cogn Neurosci Neuroimaging. 2023;8(12):1176–85. DOI: https://doi.org/10.1016/j.bpsc.2023.07.011 31. Fong CY, Law WHC, Uka T, Koike S. Auditory Mismatch Negativity Under Predictive Coding Framework and Its Role in Psychotic Disorders. Front Psychiatry. 2020;11:557932. DOI: https://doi.org/10.3389/fpsyt.2020.557932 32. Sutton S, Braren M, Zubin J, John ER. Evoked-potential correlates of stimulus uncertainty. Science. 1965;150(3700):1187–8. DOI: https://doi.org/10.1126/science.150.3700.1187 33. Picton TW. The P300 wave of the human event-related potential. J Clin Neurophysiol. 1992;9(4):456–79. DOI: https://doi.org/10.1097/00004691-199210000-00002 34. Ford JM. Schizophrenia: the broken P300 and beyond. Psychophysiology. 1999;36(6):667–82. PMID: 10554581 35. Chennu S, Noreika V, Gueorguiev D, et al. Expectation and attention in hierarchical auditory prediction. J Neurosci. 2013;33(27):11194–205. DOI: https://doi.org/10.1523/JNEUROSCI.0114-13.2013 36. Walter WG, Cooper R, Aldridge VJ, et al. Contingent negative variation: an electric sign of sensorimotor association and expectancy in the human brain. Nature. 1964;203:380–4. DOI: https://doi.org/10.1038/203380a0 37. Kononowicz TW, Sander T, van Rijn H. Neuroelectromagnetic signatures of the reproduction of supra-second durations. Neuropsychologia. 2015;75:201–13. DOI: https://doi.org/10.1016/j.neuropsychologia.2015.06.001 38. Kononowicz TW, van Rijn H. Decoupling interval timing and climbing neural activity: a dissociation between CNV and N1P2 amplitudes. J Neurosci. 2014;34(8):2931–9. DOI: https://doi.org/10.1523/JNEUROSCI.2523-13.2014 39. Macar F, Vidal F, Casini L. The supplementary motor area in motor and sensory timing: evidence from slow brain potential changes. Exp Brain Res. 1999;125(3):271–80. DOI: https://doi.org/10.1007/s002210050683 40. Kononowicz TW, Penney TB. The contingent negative variation (CNV): Timing isn’t everything. Curr Opin Behav Sci. 2016;8:231–7. DOI: https://doi.org/10.1016/j.cobeha.2016.02.022 41. Birbaumer N, Elbert T, Canavan AG, Rockstroh B. Slow potentials of the cerebral cortex and behavior. Physiol Rev. 1990;70(1):1–41. DOI: https://doi.org/10.1152/physrev.1990.70.1.1 42. Brunia CH. Neural aspects of anticipatory behavior. Acta Psychol (Amst). 1999;101(2–3):213–42. DOI: https://doi.org/10.1016/s0001-6918(99)00006-2 43. Bernstein NA. Na putjah k biologii aktivnosti. Voprosy filosofii. 1965;(10):65–78. (In Russ.) 44. Bazylevich TF. Sistemnye issledovanija anticipacii v strukture individual'nosti. Voprosy psikhologii. 1988;(4):46–55. (In Russ.) 45. Bazylevich TF. Integrativnye biojelektricheskie harakteristiki mozga v sistemnoj determinacii strategii povedenija. Psikhologicheskii zhurnal. 1990;11(1):73–83. (In Russ.) 46. Kirenskaya AV, Myamlin VV, Novototsky-Vlasov VY, et al. The contingent negative variation laterality and dynamics in antisaccade task in normal and unmedicated schizophrenic subjects. Span J Psychol. 2011;14(2):869–83. DOI: https://doi.org/10.5209/rev_sjop.2011.v14.n2.34 47. Klein C, Heinks T, Andresen B, et al. Impaired modulation of the saccadic contingent negative variation preceding antisaccades in schizophrenia. Biol Psychiatry. 2000;47(11):978–90. DOI: https://doi.org/10.1016/s0006-3223(00)00234-1 48. Osborne KJ, Kraus B, Lam PH, et al. Contingent Negative Variation Blunting and Psychomotor Dysfunction in Schizophrenia: A Systematic Review. Schizophr Bull. 2020;46(5):1144–54. DOI: https://doi.org/10.1093/schbul/sbaa043 49. Liddle EB, Price D, Palaniyappan L, et al. Abnormal salience signaling in schizophrenia: The role of integrative beta oscillations. Hum Brain Mapp. 2016;37(4):1361–74. DOI: https://doi.org/10.1002/hbm.23107 50. Poliakov YuF. Patologija poznavatel'noj dejatel'nosti pri shizofrenii. Moscow: Medicina; 1974. 168 p. (In Russ.) 51. Feigenberg IM. Narushenie verojatnostnogo prognozirovanija pri shizofrenii. In: Shizofrenija i verojatnostnoe prognozirovanie. VM Morozov, IM Feigenberg, editors. Moscow: COLIUV; 1973. p. 5–19. (In Russ.) 52. Silverstein SM, Keane BP. Perceptual organization impairment in schizophrenia and associated brain mechanisms: review of research from 2005 to 2010. Schizophr Bull. 2011;37(4):690–9. DOI: https://doi.org/10.1093/schbul/sbr052 53. Samylkin DV, Tkachenko AA. [The structure of the abnormal personality as a violation of the temporal perspective]. Rossiiskii psikhiatricheskii zhurnal [Russian Journal of Psychiatry]. 2021;(3):32–44. (In Russ.) DOI: https://doi.org/10.47877/1560-957Х-2021-10304 54. Ficco L, Mancuso L, Manuello J, et al. Disentangling predictive processing in the brain: a meta-analytic study in favour of a predictive network. Sci Rep. 2021;11(1):16258. DOI: https://doi.org/10.1038/s41598-021-95603-5 55. Kapur S. Psychosis as a state of aberrant salience: a framework linking biology, phenomenology, and pharmacology in schizophrenia. Am J Psychiatry. 2003;160(1):13–23. DOI: https://doi.org/10.1176/appi.ajp.160.1.13 56. Kilteni K, Andersson BJ, Houborg C, Ehrsson HH. Motor imagery involves predicting the sensory consequences of the imagined movement. Nat Commun. 2018;9(1):1617. DOI: https://doi.org/10.1038/s41467-018-03989-0 57. Corlett PR, Frith CD, Fletcher PC. From drugs to deprivation: a Bayesian framework for understanding models of psychosis. Psychopharmacology (Berl). 2009;206(4):515–30. DOI: https://doi.org/10.1007/s00213-009-1561-0 58. Deane G. Consciousness in active inference: Deep self-models, other minds, and the challenge of psychedelic-induced ego-dissolution. Neurosci Conscious. 2021;2021(2):niab024. DOI: https://doi.org/10.1093/nc/niab024 59. Seth AK, Suzuki K, Critchley HD. An interoceptive predictive coding model of conscious presence. Front Psychol. 2012;2:395. DOI: https://doi.org/10.3389/fpsyg.2011.00395 60. Marshall AC, Gentsch A, Schütz-Bosbach S. The Interaction between Interoceptive and Action States within a Framework of Predictive Coding. Front Psychol. 2018;9:180. DOI: https://doi.org/10.3389/fpsyg.2018.00180 61. Nelson B, Lavoie S, Gawęda Ł, et al. The neurophenomenology of early psychosis: An integrative empirical study. Conscious Cogn. 2020;77:102845. DOI: https://doi.org/10.1016/j.concog.2019.102845
Article Metrics
Metrics powered by PLOS ALM