Как мы можем связать мозг и симптомы? Пространственно-временная психопатология

Полный текст:
Читать

Рекомендуемое оформление библиографической ссылки:

Нортхофф Г. Как мы можем связать мозг и симптомы? Пространственно-временная психопатология // Российский психиатрический журнал. 2022. №4. С. 44-56.

Аннотация

В настоящее время понимание психопатологических симптомов фокусируется на самих по себе симптомах или преимущественно на активности мозга. Это оставляет нерешённым вопрос об их близкой связи. Новый подход, пространственно-временная психопатология, предполагает, что внутренняя пространственно-временная организация нейронной активности мозга обеспечивает пространственно-временную организацию психопатологических симптомов. Точнее говоря, нейрональная топография и динамика мозга проявляются в более или менее схожей пространственно-временной организации психического уровня, т.е. в психической топографии и динамике. Это убедительно подтверждается различными примерами, включая большое депрессивное расстройство, биполярное расстройство, шизофрению и аутизм. В результате мы делаем вывод, что пространственно-временная психопатология представляет собой многообещающий подход, способный раскрыть тесную связь между мозговой активностью и симптомами психических расстройств.

 

Ключевые слова мозг; психопатологические симптомы; пространственно-временная психопатология; шизофрения; депрессия

Литература

1. Stanghellini G. The meanings of psychopathology. Curr Opin Psychiatry. 2009;22(6):559–64. DOI: https://doi.org/10.1097/YCO.0b013e3283318e36 2. Stanghellini G, Broome MR. Psychopathology as the basic science of psychiatry. Br J Psychiatry. 2014;205(3):169–70. DOI: https://doi.org/10.1192/bjp.bp.113.138974 3. Fuchs T. Temporality and psychopathology. Phenomenol Cogn Sci. 2013;12(1):75–104. DOI: https://doi.org/10.1007/S11097-010-9189-4 4. Stanghellini G, Broome MR, Fernandez AV, et al. Phenomenological Psychopathology. Oxford Handbook. Oxford, New York: Oxford University Press; 2018. 1216 p. 5. Halligan PW, David AS. Cognitive neuropsychiatry: towards a scientific psychopathology. Nat Rev Neurosci. 2001;2(3):209–15. DOI: https://doi.org/10.1038/35058586 6. Panksepp J. Textbook of biological psychiatry. Hoboken, New Jersey: Wiley-Liss; 2004. 736 p. 7. Sheppes G, Suri G, Gross JJ. Emotion regulation and psychopathology. Annu Rev Clin Psychol. 2015;11:379–405. DOI: https://doi.org/10.1146/annurev-clinpsy-032814-112739 8. Northoff G, Wainio-Theberge S, Evers K. Spatiotemporal neuroscience – what is it and why we need it. Phys Life Rev. 2020;33:78–87. DOI: https://doi.org/10.1016/j.plrev.2020.06.005 9. Northoff G, Wainio-Theberge S, Evers K. Is temporo-spatial dynamics the “common currency” of brain and mind? In Quest of “Spatiotemporal Neuroscience”. Phys Life Rev. 2020;33:34–54. DOI: https://doi.org/10.1016/j.plrev.2019.05.002 10. Kant I. Critique of Pure reason. Cambridge: Cambridge University Press; 1998. 785 p. 11. Northoff G. Immanuel Kant’s mind and the brain’s resting state. Trends Cogn Sci. 2012;16(7):356–9. DOI: https://doi.org/10.1016/j.tics.2012.06.001 12. Northoff G, Magioncalda P, Martino M, et al. Too fast or too slow? Time and neuronal variability in bipolar disorder – a combined theoretical and empirical investigation. Schizophr Bull. 2018;44(1):54–64. DOI: https://doi.org/10.1093/schbul/sbx050 13. Northoff G, Wiebking C, Feinberg T, Panksepp J. The “resting-state hypothesis” of major depressive disorder-A translational subcortical-cortical framework for a system disorder. Neurosci Biobehav Rev. 2011;35(9):1929–45. DOI: https://doi.org/10.1016/j.neubiorev.2010.12.007 14. Northoff G. Spatiotemporal Psychopathology I: No rest for the brain’s resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms. J Affect Disord. 2016;190:854–66. DOI: https://doi.org/10.1016/j.jad.2015.05.007 15. Northoff G. Spatiotemporal Psychopathology II: How does a psychopathology of the brain’s resting state look like? Spatiotemporal approach and the history of psychopathology. J Affect Disord. 2016;190:867–79. DOI: https://doi.org/10.1016/j.jad.2015.05.008 16. Northoff G. The brain’s spontaneous activity and its psychopathological symptoms – “Spatiotemporal binding and integration”. Prog Neuropsychopharmacol Biol Psychiatry. 2018;80(Pt. B):81–90. DOI: https://doi.org/10.1016/j.pnpbp.2017.03.019 17. Northoff G. Anxiety Disorders and the Brain’s Resting State Networks: From Altered Spatiotemporal Synchronization to Psychopathological Symptoms. Adv Exp Med Biol. 2020;1191:71–90. DOI: https://doi.org/10.1007/978-981-32-9705-0_5 18. Fingelkurts AA, Fingelkurts AA. Brain space and time in mental disorders: Paradigm shift in biological psychiatry. Int J Psychiatry Med. 2019;54(1):53–63. DOI: https://doi.org/10.1177/0091217418791438 19. Northoff G, Scalabrini A. “Project for a Spatiotemporal Neuroscience” – Brain and Psyche Share Their Topography and Dynamic. Front Psychol. 2021;12:717402. DOI: https://doi.org/10.3389/fpsyg.2021.717402 20. Buzsáki G, Llinás R. Space and time in the brain. Science. 2017;358(6362):482–5. DOI: https://doi.org/10.1126/science.aan8869 21. Drayton L, Furman M. Thy Mind, Thy Brain and Time. Trends Cogn Sci. 2018;22(10):841–3. DOI: https://doi.org/10.1016/j.tics.2018.08.007 22. Fingelkurts AA, Fingelkurts AA, Neves CFH. Natural world physical, brain operational, and mind phenomenal space-time. Phys Life Rev. 2010;7(2):195–249. DOI: https://doi.org/10.1016/j.plrev.2010.04.001 23. Liu TT, Nalci A, Falahpour M. The global signal in fMRI: Nuisance or Information? Neuroimage. 2017;150:213–29. DOI: https://doi.org/10.1016/j.neuroimage.2017.02.036 24. Liu X, Zhang N, Chang C, Duyn JH. Co-activation patterns in resting-state fMRI signals. Neuroimage. 2018;180:485–94. DOI: https://doi.org/10.1016/j.neuroimage.2018.01.041 25. Power JD, Plitt M, Laumann TO, Martin A. Sources and implications of whole-brain fMRI signals in humans. Neuroimage. 2017;146:609–25. DOI: https://doi.org/10.1016/j.neuroimage.2016.09.038 26. Zhang J, Huang Z, Tumati S, Northoff G. Rest-task modulation of fMRI-derived global signal topography is mediated by transient coactivation patterns. PLoS Biol. 2020;18(7):e3000733. DOI: https://doi.org/10.1371/journal.pbio.3000733 27. Murphy K, Fox MD. Towards a consensus regarding global signal regression for resting state functional connectivity MRI. Neuroimage. 2017;154:169–73. DOI: https://doi.org/10.1016/j.neuroimage.2016.11.052 28. Chai XJ, Castañón AN, Öngür D, Whitfield-Gabrieli S. Anticorrelations in resting state networks without global signal regression. Neuroimage. 2012;59(2):1420–8. DOI: https://doi.org/10.1016/j.neuroimage.2011.08.048 29. Nalci A, Rao BD, Liu TT. Global signal regression acts as a temporal downweighting process in resting-state fMRI. Neuroimage. 2017;152:602–18. DOI: https://doi.org/10.1016/j.neuroimage.2017.01.015 30. Wong CW, Olafsson V, Tal O, Liu TT. Anti-correlated networks, global signal regression, and the effects of caffeine in resting-state functional MRI. Neuroimage. 2012;63(1):356–64. DOI: https://doi.org/10.1016/j.neuroimage.2012.06.035 31. Birn RM, Smith MA, Jones TB, Bandettini PA. The Respiration Response Function: The temporal dynamics of fMRI signal fluctuations related to changes in respiration. Neuroimage. 2008;40(2):644–54. DOI: https://doi.org/10.1016/j.neuroimage.2007.11.059 32. Birn RM, Diamond JB, Smith MA, Bandettini PA. Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. Neuroimage. 2006;31(4):1536–48. DOI: https://doi.org/10.1016/j.neuroimage.2006.02.048 33. Orban C, Kong R, Li J, et al. Time of day is associated with paradoxical reductions in global signal fluctuation and functional connectivity. PLoS Biol. 2020;18(2):e3000602. DOI: https://doi.org/10.1371/journal.pbio.3000602 34. Uddin LQ. Bring the Noise: Reconceptualizing Spontaneous Neural Activity. Trends Cogn Sci. 2020;24(9):734–46. DOI: https://doi.org/10.1016/j.tics.2020.06.003 35. Uddin LQ. Mixed Signals: On Separating Brain Signal from Noise. Trends Cogn Sci. 2017;21(6):405–6. DOI: https://doi.org/10.1016/j.tics.2017.04.002 36. Yang GJ, Murray JD, Glasser M, et al. Altered Global Signal Topography in Schizophrenia. Cereb Cortex. 2017;27(11):5156–69. DOI: https://doi.org/10.1093/cercor/bhw297 37. Yang GJ, Murray JD, Repovs G, et al. Altered global brain signal in schizophrenia. Proc Natl Acad Sci U S A. 2014;111(20):7438–43. DOI: https://doi.org/10.1073/pnas.1405289111 38. Wang X, Liao W, Han S, et al. Altered dynamic global signal topography in antipsychotic-naive adolescents with early-onset schizophrenia. Schizophr Res. 2019;208:308–16. DOI: https://doi.org/10.1016/j.schres.2019.01.035 39. Argyelan M, Ikuta T, DeRosse P, et al. Resting-state fMRI connectivity impairment in schizophrenia and bipolar disorder. Schizophr Bull. 2014;40(1):100–10. DOI: https://doi.org/10.1093/schbul/sbt092 40. Argyelan M, Gallego JA, Robinson DG, et al. Abnormal resting state FMRI activity predicts processing speed deficits in first-episode psychosis. Neuropsychopharmacology. 2015;40(7):1631–9. DOI: https://doi.org/10.1038/npp.2015.7 41. Hahamy A, Calhoun V, Pearlson G, et al. Save the global: global signal connectivity as a tool for studying clinical populations with functional magnetic resonance imaging. Brain Connect. 2014;4(6):395–403. DOI: https://doi.org/10.1089/brain.2014.0244 42. Northoff G, Duncan NW. How do abnormalities in the brain’s spontaneous activity translate into symptoms in schizophrenia? From an overview of resting state activity findings to a proposed spatiotemporal psychopathology. Prog Neurobiol. 2016;145–146:26–45. DOI: https://doi.org/10.1016/j.pneurobio.2016.08.003 43. Parnas J. The core Gestalt of schizophrenia. World Psychiatry. 2012;11(2):67–9. DOI: https://doi.org/10.1016/j.wpsyc.2012.05.002 44. Northoff G, Sandsten KE, Nordgaard J, et al. The Self and Its Prolonged Intrinsic Neural Timescale in Schizophrenia. Schizophr Bull. 2021;47(1):170–9. DOI: https://doi.org/10.1093/schbul/sbaa083 45. Zhang J, Magioncalda P, Huang Z, et al. Altered Global Signal Topography and Its Different Regional Localization in Motor Cortex and Hippocampus in Mania and Depression. Schizophr Bull. 2019;45(4):902–10. DOI: https://doi.org/10.1093/schbul/sby138 46. Gotts SJ, Simmons WK, Milbury LA, et al. Fractionation of social brain circuits in autism spectrum disorders. Brain. 2012;135(Pt 9):2711–25. DOI: https://doi.org/10.1093/brain/aws160 47. Abbas A, Bassil Y, Keilholz S. Quasi-periodic patterns of brain activity in individuals with attention-deficit/hyperactivity disorder. Neuroimage Clin. 2019;21:101653. DOI: https://doi.org/10.1016/j.nicl.2019.101653 48. Murrough JW, Abdallah CG, Anticevic A, et al. Reduced global functional connectivity of the medial prefrontal cortex in major depressive disorder. Hum Brain Mapp. 2016;37(9):3214–23. DOI: https://doi.org/10.1002/hbm.23235 49. Scalabrini A, Vai B, Poletti S, et al. All roads lead to the default-mode network-global source of DMN abnormalities in major depressive disorder. Neuropsychopharmacology. 2020;45(12):2058–69. DOI: https://doi.org/10.1038/s41386-020-0785-x 50. Abdallah CG, Averill CL, Salas R, et al. Prefrontal Connectivity and Glutamate Transmission: Relevance to Depression Pathophysiology and Ketamine Treatment. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017;2(7):566–74. DOI: https://doi.org/10.1016/j.bpsc.2017.04.006 51. Scheinost D, Holmes SE, DellaGioia N, et al. Multimodal Investigation of Network Level Effects Using Intrinsic Functional Connectivity, Anatomical Covariance, and Structure-to-Function Correlations in Unmedicated Major Depressive Disorder. Neuropsychopharmacology. 2018;43(5):1119–27. DOI: https://doi.org/10.1038/npp.2017.229 52. Northoff G. Psychopathology and pathophysiology of the self in depression – Neuropsychiatric hypothesis. J Affect Disord. 2007;104(1–3):1–14. DOI: https://doi.org/10.1016/j.jad.2007.02.012 53. Buzsáki G. Rhythms of the Brain. Oxford, New York: Oxford University Press; 2006. 465 p. 54. He BJ, Zempel JM, Snyder AZ, Raichle ME. The temporal structures and functional significance of scale-free brain activity. Neuron. 2010;66(3):353–69. DOI: https://doi.org/10.1016/j.neuron.2010.04.020 55. Huang Z, Obara N, Davis HH, et al. The temporal structure of resting-state brain activity in the medial prefrontal cortex predicts self-consciousness. Neuropsychologia. 2016;82:161–70. DOI: https://doi.org/10.1016/j.neuropsychologia.2016.01.025 56. Linkenkaer-Hansen K, Nikouline VV, Palva JM, Ilmoniemi RJ. Long-Range Temporal Correlations and Scaling Behavior in Human Brain Oscillations. J Neuroscience. 2001;21(4):1370–7. DOI: https://doi.org/10.1523/jneurosci.21-04-01370.2001 57. Northoff G. Personal Identity and Cortical Midline Structure (CMS): Do Temporal Features of CMS Neural Activity Transform Into “Self-Continuity”? Psychol Inquiry. 2017l;28(2–3):122–31. DOI: https://doi.org/10.1080/1047840x.2017.1337396 58. Hasson U, Chen J, Honey CJ. Hierarchical process memory: memory as an integral component of information processing. Trends Cogn Sci. 2015;19(6):304–13. DOI: https://doi.org/10.1016/j.tics.2015.04.006 59. Golesorkhi M, Gomez-Pilar J, Zilio F, et al. The brain and its time: intrinsic neural timescales are key for input processing. Commun Biol. 2021;4(1):970. DOI: https://doi.org/10.1038/s42003-021-02483-6 60. Golesorkhi M, Gomez-Pilar J, Tumati S, et al. Temporal hierarchy of intrinsic neural timescales converges with spatial core-periphery organization. Commun Biol. 2021;4(1):277. DOI: https://doi.org/10.1038/s42003-021-01785-z 61. Wolff A, Berberian N, Golesorkhi M, et al. Intrinsic neural timescales: temporal integration and segregation. Trends Cogn Sci. 2022;26(2):159–73. DOI: https://doi.org/10.1016/j.tics.2021.11.007 62. Raut RV, Mitra A, Marek S, et al. Organization of Propagated Intrinsic Brain Activity in Individual Humans. Cereb Cortex. 2020;30(3):1716–34. DOI: https://doi.org/10.1093/cercor/bhz198 63. Ito T, Hearne LJ, Cole MW. A cortical hierarchy of localized and distributed processes revealed via dissociation of task activations, connectivity changes, and intrinsic timescales. Neuroimage. 2020;221:117141. DOI: https://doi.org/10.1016/j.neuroimage.2020.117141 64. Tagliazucchi E, von Wegner F, Morzelewski A, et al. Breakdown of long-range temporal dependence in default mode and attention networks during deep sleep. Proc Natl Acad Sci U S A. 2013;110(38):15419–24. DOI: https://doi.org/10.1073/pnas.1312848110 65. Tagliazucchi E, Roseman L, Kaelen M, et al. Increased Global Functional Connectivity Correlates with LSD-Induced Ego Dissolution. Curr Biol. 2016;26(8):1043–50. DOI: https://doi.org/10.1016/j.cub.2016.02.010 66. Zhang L, Wu H, Xu J, Shang J. Abnormal Global Functional Connectivity Patterns in Medication-Free Major Depressive Disorder. Front Neurosci. 2018;12:692. DOI: https://doi.org/10.3389/fnins.2018.00692 67. Zilio F, Gomez-Pilar J, Cao S, et al. Are intrinsic neural timescales related to sensory processing? Evidence from abnormal behavioral states. Neuroimage. 2021;226:117579. DOI: https://doi.org/10.1016/j.neuroimage.2020.117579 68. Huang Z, Zhang J, Wu J, et al. Disrupted neural variability during propofol-induced sedation and unconsciousness. Hum Brain Mapp. 2018;39(11):4533–44. DOI: https://doi.org/10.1002/hbm.24304 69. Watanabe T, Rees G, Masuda N. Atypical intrinsic neural timescale in autism. Elife. 2019;8:e42256. DOI: https://doi.org/10.7554/elife.42256 70. Damiani S, Scalabrini A, Gomez-Pilar J, et al. Increased scale-free dynamics in salience network in adult high-functioning autism. Neuroimage Clin. 2019;21:101634. DOI: https://doi.org/10.1016/j.nicl.2018.101634 71. Wengler K, Goldberg AT, Chahine G, Horga G. Distinct hierarchical alterations of intrinsic neural timescales account for different manifestations of psychosis. Elife. 2020;9:e56151. DOI: https://doi.org/10.7554/elife.56151 72. Uscătescu LC, Said-Yürekli S, Kronbichler L, et al. Reduced intrinsic neural timescales in schizophrenia along posterior parietal and occipital areas. NPJ Schizophrenia. 2021;7(1):55. DOI: https://doi.org/10.1038/s41537-021-00184-x 73. Gupta A, Wolff A, Northoff G. Extending the “resting state hypothesis of depression” – dynamics and topography of abnormal rest-task modulation. Psychiatry Res Neuroimaging. 2021;317:111367. DOI: https://doi.org/10.1016/j.pscychresns.2021.111367



DOI: http://dx.doi.org/10.47877/1560-957Х-2022-10406

Метрики статей

Загрузка метрик ...

Metrics powered by PLOS ALM