System psychoneurology: current understanding of the structural and functional organization of the brain
- Authors: Damulin I.V1
-
Affiliations:
- I.M.Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation
- Issue: Vol 19, No 2 (2017)
- Pages: 8-13
- Section: Articles
- URL: https://journals.rcsi.science/2075-1753/article/view/94707
- ID: 94707
Cite item
Full Text
Abstract
The article deals with modern aspects of structural and functional activity of the central nervous system. Connectome is important due to its concept, the construction of which is based on the results of functional magnetic resonance imaging and involves the separation of certain cerebral regions (oblasts), evaluating the links between these regions and the detailed analysis of these network connections. Connectome is characterized by dynamic and functional heterogeneity (exciting, inhibiting, modulating area). Operations of connectome are determined by energy metabolism in brain tissue. "Hidden" (or "internal") is not linked to external influences energy is spent on the process of evaluating and developing responses/reactions to the stimuli coming from the outside, as well as, probably, in the anticipation/prediction of events that may occur. This is important not only to the level of energy metabolism, but also fluctuations "stored energy". The brain operates with system-energy point of view in the direction of minimizing their own energy consumption. The article concludes that created in the current model (connectome) is more informative for the understanding of the processes occurring in the brain than the simple sum of the parts belonging to it. This model is the key to a new direction of development of neuroscience - system psychoneurology.
Full Text
##article.viewOnOriginalSite##About the authors
I. V Damulin
I.M.Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation
Email: damulin@mmascience.ru
д-р мед. наук, проф. каф. нервных болезней и нейрохирургии ИПО ФГАОУ ВО «Первый МГМУ им. И.М.Сеченова» 119991, Russian Federation, Moscow, ul. Trubetskaia, d. 8, str. 2
References
- Petersen S.E, Sporns O. Brain networks and cognitive architectures. Neuron 2015; 88 (1): 207-19. doi: 10.1016/j.neuron.2015.09.027
- Sporns O, Betzel R.F. Modular brain networks. Annual Review of Psychology 2016; 67 (1): 613-40. doi: 10.1146/annurev-psych-122414-033634
- Catani M, Ffytche D.H. The rises and falls of disconnection syndromes. Brain 2005; 128 (10): 2224-39. doi: 10.1093/brain/awh622
- Filley C.E, Fields R.D. White matter and cognition: making the connection. J Neurophysiology 2016; 116 (5): 2093-104. doi: 10.1152/jn.00221.2016
- Бехтерев В.М. Проводящие пути спинного и головного мозга. Руководство кь изученiю внутреннихь связей мозга. Ч. II. Волокна мозжечка, волокна мозг. полушарий и общiй обзорь провод. системь. 2-е изд. СПб.: Изданie К.Л.Риккера, 1898; с. 383.
- Geschwind N. Disconnexion syndromes in animals and man. Part I. Brain 1965; 88 (3): 237-94. doi: 10.1093/brain/88.2.237
- Geschwind N. Disconnexion syndromes in animals and man. Part II. Brain 1965; 88 (3): 585-644. doi: 10.1093/brain/88.2.237
- Mesulam M-M. Fifty years of disconnexion syndromes and the Geschwind legacy. Brain 2015; 138 (9): 2791-9. doi: 10.1093/brain/awv198
- Дамулин И.В. Корковые связи, синдром «разобщения» и высшие мозговые функции. Журн. неврологии и психиатрии им. С.С.Корсакова. 2015; 115 (11): 107-11. doi: 10.17116/jnevro2015115111107-111
- Дамулина А.И., Коновалов Р.Н., Кадыков А.С. Постинсультные когнитивные нарушения. Неврол. журн. 2015; 20 (1): 12-9.
- Catani M, Mesulam M. What is a disconnection syndrome? Cortex 2008; 44 (8): 911-3. doi: 10.1016/j.cortex.2008.05.001
- Thiebaut de Schotten M, Kinkingnehun S, Delmaire C et al. Visualization of disconnection syndromes in humans. Cortex 2008; 44 (8): 1097-103. doi: 10.1016/j.cortex.2008.02.003
- Дамулин И.В., Сиволап Ю.П. Расстройство фронтосубкортикальных связей в нейропсихиатрии. Неврол. вестн. (Журн. им. В.М.Бехтерева). 2015; 4: 78-82.
- Дамулин И.В., Сиволап Ю.П. Неврологические нарушения при шизофрении: клинические особенности и патогенетические аспекты. Рос. мед. журн. 2016; 22 (5): 267-71. doi: 10.18821/0869-2106-2016-22-5-267-271
- Filley C.M. White matter: beyond focal disconnection. Neurologic Clinics 2011; 29 (1): 81-97. doi: 10.1016/j.ncl.2010.10.003
- Bullmore E, Sporns O. The economy of brain network organization. Nature Reviews Neuroscience 2012; 13: 337-49. doi: 10.1038/nrn3214
- Nuallain S.O, Doris T. Consciousness is cheap, even if symbols are expensive; metabolism and the brain’s dark energy. Biosemiotics 2011; 5 (2): 193-210. doi: 10.1007/s12304-011-9136-y
- Van den Heuvel M.P, Bullmore E.T, Sporns O. Comparative connectomics. Trends in Cognitive Sciences 2016; 20 (5): 345-61. doi: 10.1016/j.tics.2016.03.001
- Дамулин И.В. Особенности структурной и функциональной организации головного мозга. Журн. неврологии и психиатрии им. С.С.Корсакова. 2016; 116 (11): 163-8. doi: 10.17116/jnevro2016116111163-168
- Bullmore E, Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience 2009; 10 (3): 186-98. doi: 10.1038/nrn2575
- Cao M, Wang Z, He Y. Connectomics in psychiatric research: advances and applications. Neuropsychiatric Dis Treatment 2015; 11: 2801-10. doi: 10.2147/ndt.s63470
- Lobo M.K. Lighting up the brain's reward circuitry. Ann NY Acad Sci 2012; 1260 (1): 24-33. doi: 10.1111/j.1749-6632.2011.06368.x
- Meunier D, Achard S, Morcom A, Bullmore E. Age - related changes in modular organization of human brain functional networks. NeuroImage 2009; 44 (3): 715-23. doi: 10.1016/j.neuroimage.2008.09.062
- Papo D, Buldu J.M, Boccaletti S, Bullmore E.T. Complex network theory and the brain. Philosophical Transactions of the Royal Society B: Biological Sciences 2014; 369 (1653): 20130520. doi: 10.1098/rstb.2013.0520
- Reid R.C. From functional architecture to functional connectomics. Neuron 2012; 75 (2): 209-17. doi: 10.1016/j.neuron.2012.06.031
- Veldsman M, Cumming T, Brodtmann A. Beyond BOLD: Optimizing functional imaging in stroke populations. Hum Brain Mapping 2014; 36 (4): 1620-36. doi: 10.1002/hbm.22711
- Zhang D, Raichle M.E. Disease and the brain's dark energy. Nat Rev Neurol 2010; 6 (1): 15-28. doi: 10.1038/nrneurol.2009.198
- Bandettini P.A, Bullmor E. Endogenous oscillations and networks in functional magnetic resonance imaging. Hum Brain Mapping 2008; 29 (7): 737-9. doi: 10.1002/hbm.20607
- Fornito A, Bullmore E.T. Connectomics: A new paradigm for understanding brain disease. Euro Neuropsychopharmacol 2015; 25 (5): 733-48. doi: 10.1016/j.euroneuro.2014.02.011
- Sporns O. Towards network substrates of brain disorders. Brain 2014; 137 (8): 2117-8. doi: 10.1093/brain/awu148
- Pessoa L. The Cognitive - Emotional Brain. From Interactions to Integration. Cambridge, London: The MIT Press, 2013; p. 320.
- Дамулин И.В. Поражение затылочных отделов головного мозга: некоторые клинические, патогенетические и терапевтические особенности. Мед. совет. 2016; 4: 36-41.
- De Renzi E. Disorders of visual recognition. Semin Neurol 2000; 20 (4): 479-85. doi: 10.1055/s-2000-13181
- Barton J.J.S. Disorders of color and object recognition. CONTINUUM: Lifelong Learning in Neurology 2010; 16 (4): 111-27. doi: 10.1212/01.con.0000368264.61286.9b
- Magistretti P.J, Allaman I. A cellular perspective on brain energy metabolism and functional imaging. Neuron 2015; 86 (4): 883-901. doi: 10.1016/j.neuron.2015.03.035
- Raichle M.E, Snyder A.Z. Intrinsic Brain Activity and Consciousness. In: The Neurology of Consciousness. Cognitive Neuroscience and Neuropathology. 2nd ed. Ed. by S.Laureys et al. Amsterdam etc: Elsevier Ltd, 2009; p. 81-8. doi: 10.1016/b978-0-12-374168-4.00007-1
- Robertson R.M, Money T.G.A. Temperature and neuronal circuit function: compensation, tuning and tolerance. Curr Opin Neurobiol 2012; 22 (4): 724-34. doi: 10.1016/j.conb.2012.01.008
- Gailliot M.T. Unlocking the energy dynamics of executive functioning: linking executive functioning to brain glycogen. Perspect Psychol Sci 2008; 3 (4): 245-63. doi: 10.1111/j.1745-6924.2008.00077.x
- Raichle M.E. Two views of brain function. Trends Cognitive Sci 2010; 14 (4): 180-90. doi: 10.1016/j.tics.2010.01.008
- Holcman D, Tsodyks M. The emergence of up and down states in cortical networks. PLoS Computational Biology 2006; 2 (3): e23. doi: 10.1371/journal.pcbi.0020023
- Harrington D.L, Rubinov M, Durgerian S et al. For the PREDICT-HD investigators of the Huntington Study Group and Rao S.M. Network topology and functional connectivity disturbances precede the onset of Huntington’s disease. Brain 2015; 138 (8): 2332-46. doi: 10.1093/brain/awv145
- Llinas R.R, Roy S. The ‘prediction imperative’ as the basis for self - awareness. Philosophical Transactions of the Royal Society B: Biological Sciences 2009; 364 (1521): 1301-7. doi: 10.1098/rstb.2008.0309
- Botvinick M.M. Hierarchical reinforcement learning and decision making. Curr Opin Neurobiol 2012; 22 (6): 956-62. doi: 10.1016/j.conb.2012.05.008
- Bechara A, Damasio H. Decision - making and addiction (part I): impaired activation of somatic states in substance dependent individuals when pondering decisions with negative future consequences. Neuropsychologia 2002; 40 (10): 1675-89. doi: 10.1016/s0028-3932(02)00015-5
- Clark L, Bechara A, Damasio H et al. Differential effects of insular and ventromedial prefrontal cortex lesions on risky decision - making. Brain 2007; 131 (5): 1311-22. doi: 10.1093/brain/awn066
- Sallet J, Mars R.B, Quilodran R et al. Neuroanatomical basis of motivational and cognitive control: a focus on the medial and lateral prefrontal cortex. In: Neural Basis of Motivational and Cognitive Control. Ed. by R.B.Mars et al. London, Cambridge: The MIT Press, 2011; p. 5-20.
- Yu J.Y, Frank L.M. Hippocampal - cortical interaction in decision making. Neurobiol Learn Mem 2015; 117: 34-41. doi: 10.1016/j.nlm.2014.02.002
- Llinas R.R. Inferior olive oscillation as the temporal basis for motricity and oscillatory reset as the basis for motor error correction. Neuroscience 2009; 162 (3): 797-804. doi: 10.1016/j.neuroscience.2009.04.045
- Fidelman U. Intelligence and transmission errors in the brain. Kybernetes 1996; 25 (2): 10-23. doi: 10.1108/03684929610114619
- Fidelman U. Neural transmission - errors, cerebral arousability and hemisphericity. Some relations with intelligence and personality. Kybernetes 1999; 28 (6/7): 695-725. doi: 10.1108/03684929910282962
- Fidelman U. Temporal and simultaneous processing in the brain: a possible cellular basis of cognition. Kybernetes 2002; 31 (3/4): 432-81. doi: 10.1108/03684920210422566
- Northoff G, Duncan N.W, Hayes D.J. The brain and its resting state activity - Experimental and methodological implications. Prog Neurobiol 2010; 92 (4): 593-600. doi: 10.1016/j.pneurobio.2010.09.002
- Kitzbichler M.G, Henson R.N.A, Smith M.L et al. Cognitive effort drives workspace configuration of human brain functional networks. J Neuroscience 2011; 31 (22): 8259-70. doi: 10.1523/jneurosci.0440-11.2011
- Fidelman U. Intelligence and the brain’s energy consumption: what is intelligence? Personality and Individual Differences 1993; 14 (1): 283-6. doi: 10.1016/0191-8869(93)90206-i
- Buzsaki G. Rhythms of the Brain. New York: Oxford University Press, 2006; p. 448.
- Micheloyannis S, Vourkas M, Tsirka V et al. The influence of ageing on complex brain networks: a graph theoretical analysis. Hum Brain Mapping 2009; 30: 200-8. doi: 10.1002/hbm.20492
- Fidelman U. Creativity: relation to neural transmission errors. Kybernetes 2011; 40 (5/6): 697-702. doi: 10.1108/03684921111142250
- Bendetowicz D, Urbanski M., Garcin B et al. Brain correlates of creative abilities to combine remote ideas in healthy subjects and in patients. In J Psychophysiol 2016; 108: 56. doi: 10.1016/j.ijpsycho.2016.07.187
- Labudda K, Woermann F.G, Mertens M et al. Neural correlates of decision making with explicit information about probabilities and incentives in elderly healthy subjects. Experimental Brain Res 2008; 187 (4): 641-50. doi: 10.1007/s00221-008-1332-x
- Melancon G, Joanette Y. Chaos, brain, and cognition: toward a nonlinear order? Brain Cognition 2000; 42: 33-6. doi: 10.1006/brcg.1999.1154
- Corlett P.R, Murray G.K, Honey G.D et al. Disrupted prediction - error signal in psychosis: evidence for an associative account of delusions. Brain 2007; 130 (9): 2387-400. doi: 10.1093/brain/awm173
- A critical look at connectomics (editorial). Nat Neurosci 2010; 13 (12): 1441. doi: 10.1038/nn1210-1441
- Crossley N.A, Mechelli A, Scott J et al. The hubs of the human connectome are generally implicated in the anatomy of brain disorders. Brain 2014; 137 (8): 2382-95. doi: 10.1093/brain/awu132
- Kim D-J, Skosnik P.D, Cheng H et al. Structural network topology revealed by white matter tractography in cannabis users: a graph theoretical analysis. Br Connectiv 2011; 1 (6): 473-83. doi: 10.1089/brain.2011.0053
- Dumas E.M, van den Bogaard S.J.A, Hart E.P et al. Reduced functional brain connectivity prior to and after disease onset in Huntington's disease. Neuro Image Clin 2013; 2: 377-84. doi: 10.1016/j.nicl.2013.03.001
- Leaver A.M, Turesky T.K, Seydell-Greenwald A et al. Intrinsic network activity in tinnitus investigated using functional MRI. Hum Brain Mapping 2016; 37 (8): 2717-35. doi: 10.1002/hbm.23204
- Peer M, Nitzan M, Goldberg I et al. Reversible functional connectivity disturbances during transient global amnesia. Ann Neurol 2014; 75 (5): 634-43. doi: 10.1002/ana.24137