Neuropsychological interpretation of disorders of consciousness using data from instrumental (neurophysiological) methods for diagnosing brain activity

Cover Page

Cite item

Full Text

Abstract

The relevance of the problem under consideration is determined by the need to develop and improve interdisciplinary approaches to the diagnosis and rehabilitation of disorders of consciousness in patients with brain pathology. The purpose of the article is an analytical review of the methods of neuropsychological and neurophysiological diagnostics and rehabilitation work with patients in reduced states of consciousness. It is noted that the neuropsychological content of the concept of "consciousness" is insufficiently developed and there is no unified point of view on the brain basis of consciousness, as well as on methodological and procedural limitations that arise when a neuropsychologist works with patients in a vegetative state of consciousness and in a state of minimal consciousness. The problem of consistency of the results of behavioral (neuropsychological) and instrumental (neurophysiological) methods for assessing the level of states of consciousness conducted by different specialists (neuropsychologists, neurologists, neurophysiologists) who are part of a multidisciplinary team is considered. The possibility of combining the procedure of neuropsychological examination and instrumental (neurophysiological) methods in the diagnosis of patients in a vegetative state of consciousness, in a state of minimal consciousness) and the prognosis of restoring the level of consciousness is analyzed. The possibility of an integrated approach to the diagnosis of a state of consciousness associated with a combination of behavioral (observation-based) and objective (instrumental) research methods is confirmed, and possible ways of its implementation are considered.

About the authors

L. I. Sedova

National Medical Research Centre "Treatment and Rehabilitation Centre"

Email: li.eseykina@gmail.com
ORCID iD: 0009-0000-6548-0402
SPIN-code: 7794-6822
Russian Federation, Moscow

E. V. Erokhina

Federal Center of Brain Research and Neurotechnologies; The Russian National Research Medical University named after N.I. Pirogov

Email: kater004@mail.ru
ORCID iD: 0009-0006-6831-6679
Russian Federation, 1/10 Ostrovityanova street, 117342 Moscow; Moscow

E. A. Baranova

Federal Center of Brain Research and Neurotechnologies; Russian Medical Academy of Continuous Professional Education

Email: ebaranova2006@mail.ru
ORCID iD: 0000-0002-9200-9234
SPIN-code: 6791-2193

MD, Cand. Sci. (Med.), Associate Professor

Russian Federation, Moscow; Moscow

V. M. Erikov

Ryazan State University S.A. Esenin

Email: v.erikov@365.rsu.edu
ORCID iD: 0009-0005-8540-6775

Associate Professor

Russian Federation, Ryazan

A. A. Nikulin

Ryazan State University S.A. Esenin

Email: a.nikulin@365.rsu.edu
ORCID iD: 0009-0000-9367-2671

Associate Professor

Russian Federation, Ryazan

G. E. Ivanova

Federal Center of Brain Research and Neurotechnologies; The Russian National Research Medical University named after N.I. Pirogov; Federal Research and Clinical Center of Intensive Care Medicine and Rehabilitology

Email: reabilivanova@mail.ru
ORCID iD: 0000-0003-3180-5525
SPIN-code: 4049-4581

MD, Dr. Sci. (Med.), Professor

Russian Federation, Moscow; Moscow; Moscow

Yu. V. Mikadze

Federal Center of Brain Research and Neurotechnologies; Lomonosov Moscow State University

Author for correspondence.
Email: ymikadze@yandex.ru
ORCID iD: 0000-0001-8137-9611
SPIN-code: 7799-8969

Dr. Sci. (Psych.), Professor

Russian Federation, Moscow; Moscow

References

  1. Belkin AA, Aleksandrova EV, Akhutina TV, et al. Chronic disorders of consciousness: Guidelines of the all-Russian public organization «Federation of Anesthesiologists and Reanimatologists». Alexander Saltanov intensive care herald. 2023;(3):7–42. EDN: SSLNAY doi: 10.21320/1818-474X-2023-3-7-42
  2. Gibson RM, Fernández-Espejo D, Gonzalez-Lara LE, et al. Multiple tasks and neuroimaging modalities increase the likelihood of detecting covert awareness in patients with disorders of consciousness. Front Hum Neurosci. 2014;8:950. doi: 10.3389/fnhum.2014.00950
  3. Boly M, Laureys S. Functional «unlocking» bedside detection of covert awareness after severe brain damage. Brain. 2018;141(5):1239–1241. doi: 10.1093/brain/awy080
  4. Belkin VA, Pozdnyakov DG, Belkin AA. Diagnosis of the phenomenon of cognitive-motor dissociation in patients with chronic consciousness disorders. Neurology, Neuropsychiatry, Psychosomatics. 2019;11(3S): 46–51. doi: 10.14412/2074-2711-2019-3S-46-51
  5. Cherkasova AN, Yatsko KA, Kovyazina MS, et al. Development of paradigms for the diagnosis of «covert cognition» and cognitive motor dissociation in patients with chronic disorders of consciousness. Physical Rehab Medicine, Medical Rehabilitation. 2021;3(3):318–321. doi: 10.36425/rehab72308
  6. Vygotsky LS. Thinking and speech. Collected Works. Vol. 2. Moscow: Pedagogika; 1982. P. 215. (In Russ).
  7. Gordeeva OV. The problem of the structure of consciousness in the works of L.S. Vygotsky. World of psychology. 1999;(1):111–118. EDN: HOVLDZ
  8. Edelman GM. Neural darwinism: The theory of neuronal group selection. New York: Basic Books; 1987. 240 p.
  9. Khomskaya ED. Neuropsychology. 4th ed. Saint Petersburg: Piter; 2005. 496 p. (In Russ).
  10. Anokhin KV. Cognitome: In search of fundamental neuroscience theory of consciousness. I.P. Pavlov J Higher Nervous Activity. 2021;71(1):39–71. EDN: TTTGKL doi: 10.31857/s0044467721010032
  11. Luria AR. Language and consciousness. Ed. by E.D. Chomskaya. Moscow: Izdatel’stvo Moskovskogo universiteta; 1979. 320 р. (In Russ).
  12. Luria AR. Higher cortical functions in man. Saint Petersburg: Piter; 2018.768 р. Series: Masters of Psychology. (In Russ).
  13. Kalmar K, Giacino JT. The JFK coma recovery scale-revised. Neuropsychol Rehabil. 2005;15(3-4):454–460. doi: 10.1080/ 09602010443000425
  14. Mochalova EG, Legostaeva LA, Zimin AA, et al. The Russian version of coma recovery scale-revised: A standardized method for assessment of patients with disorders of consciousness. S.S. Korsakov J Neurology Psychiatry. 2018;118(3-2):25–31. doi: 10.17116/jnevro20181183225-31
  15. Schnakers C, Vanhaudenhuyse A, Giacino J, et al. Diagnostic accuracy of the vegetative and minimally conscious state: Clinical consensus versus standardized neurobehavioral assessment. BMC Neurology. 2009;(9):35. EDN: ZULRYB doi: 10.1186/1471-2377-9-35
  16. Hirschberg R, Giacino JT. The vegetative and minimally conscious states: Diagnosis, prognosis and treatment. Neurol Clin. 2011;29(4):773–786. doi: 10.1016/j.ncl.2011.07.009
  17. Giacino JT, Katz DI, Schiff ND, et al. Practice guideline update recommendations summary. Disorders of consciousness: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology; the American Congress of Rehabilitation Medicin and the National Institute on Disability, Independent Living, and Rehabilitation Research. Neurology. 2018;91(10):450–460. doi: 10.1212/wnl.0000000000005926
  18. Fingelkurts AA, Fingelkurts AA, Bagnato S, et al. EEG oscillatory states as neuro-phenomenology of consciousness as revealed from patients in vegetative and minimally conscious states. Conscious Cogn. 2012;21(1):149–169. EDN: PIKPID doi: 10.1016/j.concog.2011.10.004
  19. Schnakers C, Bauer C, Formisano R, et al. What names for covert awareness? A systematic review. Front Hum Neurosci. 2022;16:971315. doi: 10.3389/fnhum.2022.971315
  20. Plaut Y, Weiss L. Electrodiagnostic evaluation of critical illness neuropathy [2022 Sep 26]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024.
  21. Bekinschtein TA, Coleman MR, Niklison J, et al. Can electromyography objectively detect voluntary movement in disorders of consciousness? J Neurol Neurosurg Psychiatry. 2008;79:826–828.
  22. Lesenfants D, Habbal D, Chatelle C, et al. Electromyographic decoding of response to command in disorders of consciousness. Neurology. 2016;87(20):2099–2107. doi: 10.1212/WNL.0000000000003333
  23. Habbal D, Gosseries O, Noirhomme Q, et al. Volitional electromyographic responses in disorders of consciousness. Brain Inj. 2014;28(9):1171–1179. doi: 10.3109/02699052.2014.920519
  24. Ballanti S, Campagnini S, Liuzzi P, et al. EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review. Clin Neurophysiol. 2022;(144):98–114. EDN: SCZPFS doi: 10.1016/j.clinph.2022.09.017
  25. Gosseries O, Schnakers C, Ledoux D, et al. Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state. Funct Neurol. 2011;26(1):25–30. EDN: YBSDZD
  26. Boly M, Garrido MI, Gosseries O, et al. Preserved feedforward but impaired top-down processes in the vegetative state. Science. 2011;332(6031):858–862. doi: 10.1126/science.1202043
  27. Scarpino M, Lolli F, Hakiki B, et al.; Intensive Rehabilitation Unit Study Group of the IRCCS Don Gnocchi Foundation, Italy. EEG and coma recovery scale-revised prediction of neurological outcome in disorder of consciousness patients. Acta Neurol Scand. 2020;142(3):221–228. doi: 10.1111/ane.13247
  28. Naro A, Bramanti P, Leo A, et al. Towards a method to differentiate chronic disorder of consciousness patients’ awareness: The low-resolution brain electromagnetic tomography analysis. J Neurol Sci. 2016;(368):178–183. doi: 10.1016/j.jns.2016.07.016
  29. Bareham CA, Allanson J, Roberts N, et al. Longitudinal bedside assessments of brain networks in disorders of consciousness: Case reports from the field. Front Neurol. 2018;(9):676. doi: 10.3389/fneur.2018.00676
  30. Cavinato M, Freo U, Ori C, et al. Post-acute P300 predicts recovery of consciousness from traumatic vegetative state. Brain Inj. 2009;23(12):973–980. doi: 10.3109/02699050903373493
  31. Bagnato S, Prestandrea C, D’Agostino T, et al. Somatosensory evoked potential amplitudes correlate with long-term consciousness recovery in patients with unresponsive wakefulness syndrome. Clin Neurophysiol. 2021;132(3):793–799. doi: 10.1016/j.clinph.2021.01.006
  32. Naro A, Russo M, Leo A, et al. Cortical responsiveness to nociceptive stimuli in patients with chronic disorders of consciousness: Do C-fiber laser evoked potentials have a role? PLoS One. 2015;10(12):e0144713. doi: 10.1371/journal.pone.0144713
  33. Spataro R, Heilinger A, Allison B, et al. Preserved somatosensory discrimination predicts consciousness recovery in unresponsive wakefulness syndrome. Clin Neurophysiol. 2018;129(6):1130–1136. doi: 10.1016/j.clinph.2018.02.131
  34. Perrin F, Schnakers C, Schabus M, et al. Brain response to one’s own name in vegetative state, minimally conscious state, and locked-in syndrome. Arch Neurol. 2006;63(4):562–569. doi: 10.1001/archneur.63.4.562
  35. Schnakers C, Giacino JT, Løvstad M, et al. Preserved covert cognition in noncommunicative patients with severe brain injury? Neurorehabil Neural Repair. 2015;29(4):308–317. doi: 10.1177/1545968314547767
  36. Annen J, Wannez S, Ortner R, et al. MindBEAGLE: An EEG-based BCI developed for patients with disorders of consciousness. In: Conference: International Brain-Computer Interface (BCI) Meeting. May, 2016.
  37. Hauger SL, Schnakers C, Andersson S, et al. Neurophysiological indicators of residual cognitive capacity in the minimally conscious state. Behav Neurol. 2015;2015:145913. doi: 10.1155/2015/145913
  38. Duszyk A, Dovgialo M, Pietrzak M, et al. Event-related potentials in the odd-ball paradigm and behavioral scales for the assessment of children and adolescents with disorders of consciousness: A proof of concept study. Clin Neuropsychologist. 2019;33(2):419–437.
  39. Annen J, Mertel I, Xu R, et al. Auditory and somatosensory p3 are complementary for the assessment of patients with disorders of consciousness. Brain Sci. 2020;10(10):748. doi: 10.3390/brainsci10100748
  40. Rosanova M, Gosseries O, Casarotto S, et al. Recovery of cortical effective connectivity and recovery of consciousness in vegetative patients. Brain. 2012;135(Pt 4):1308–1320. doi: 10.1093/brain/awr340
  41. Casali AG, Gosseries O, Rosanova M, et al. A theoretically based index of consciousness independent of sensory processing and behavior. Sci Transl Med. 2013;5(198):198ra105. doi: 10.1126/scitranslmed.3006294
  42. Casarotto S, Comanducci A, Rosanova M, et al. Stratification of unresponsive patients by an independently validated index of brain complexity. Ann Neurol. 2016;80(5):718–729. doi: 10.1002/ana.24779
  43. Sinitsyn D, Poydasheva A, Bakulin I, et al. Detecting the potential for consciousness in unresponsive patients using the perturbational complexity index. Brain Sci. 2020;10(12):917. doi: 10.917.10.3390/brainsci10120917
  44. Poydasheva AG, Bakulin IS, Legostaeva LA, et al. TMS-EEG: Current possibilities and future prospects. I.P. Pavlov J Higher Nervous Activity. 2019;69(3):267–279. doi: 10.1134/S0044467719030092
  45. Comanducci A, Boly M, Claassen J, et al. Clinical and advanced neurophysiology in the prognostic and diagnostic evaluation of disorders of consciousness: Review of an IFCN-endorsed expert group. Clin Neurophysiol. 2020;131(11):2736–2765. doi: 10.1016/j.clinph.2020.07.015
  46. Raichle ME. Behind the scenes of functional brain imaging: A historical and physiological perspective. Proc Natl Acad Sci USA. 1998;95(3):765–772. EDN: LNDFIJ doi: 10.1073/pnas.95.3.765
  47. Soddu A, Vanhaudenhuyse A, Bahri MA, et al. Identifying the default-mode component in spatial IC analyses of patients with disorders of consciousness. Hum Brain Mapp. 2012;33(4):778–796. doi: 10.1002/hbm.21249
  48. Vanhaudenhuyse A, Noirhomme Q, Tshibanda L, et al. Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. Brain. 2010;13(Pt 1): 161–171. doi: 10.1093/brain/awp313
  49. Demertzi A, Antonopoulos G, Heine L, et al. Intrinsic functional connectivity differentiates minimally conscious from unresponsive patients. Brain. 2015;138(Pt 9):2619–2631. doi: 10.1093/brain/awv169
  50. Legostaeva LA, Kremneva EI, Sinitsyn DO, et al. Features of residual cerebral brain activity in patients with chronic disorders of consciousness on resting-state functional MRI. Ann Clin Exp Neurol. 2022;16(2):15–24. doi: 10.54101/ACEN.2022.2.2
  51. Rodriguez MD, Schiff ND, Giacino J, et al. A network approach to assessing cognition in disorders of consciousness. Neurology. 2010;75(21):1871–1878. doi: 10.1212/WNL.0b013e3181feb259
  52. Bardin JC, Fins JJ, Katz DI, et al. Dissociations between behavioural and functional magnetic resonance imaging-based evaluations of cognitive function after brain injury. Brain. 2011;134(Pt 3):769–782. doi: 10.1093/brain/awr005
  53. Owen AM, Coleman MR, Boly M, et al. Detecting awareness in the vegetative state. Science. 2006;313(5792):1402. doi: 10.1126/science.1130197
  54. Monti MM, Vanhaudenhuyse A, Coleman MR, et al. Willful modulation of brain activity in disorders of consciousness. N Engl J Med. 2010;362(7):579–589. doi: 10.1056/NEJMoa0905370
  55. Owen AM, Coleman MR. Functional neuroimaging of the vegetative state. Nat Rev Neurosci. 2008;9(3):235–243. doi: 10.1038/nrn2330
  56. Laureys S, Owen AM, Schiff ND. Brain function in coma, vegetative state, and related disorders. Lancet Neurol. 2004;3(9):537–546. doi: 10.1016/S1474-4422(04)00852-X
  57. Stender J, Gosseries O, Bruno MA, et al. Diagnostic precision of PET imaging and functional MRI in disorders of consciousness: A clinical validation study. Lancet. 2014;384(9942):514–522. doi: 10.1016/S0140-6736(14)60042-8
  58. Stender J, Kupers R, Rodell A, et al. Quantitative rates of brain glucose metabolism distinguish minimally conscious from vegetative state patients. J Cereb Blood Flow Metab. 2014b;35(1):58–65. doi: 10.1038/jcbfm.2014.169
  59. Laureys S, Goldman S, Phillips C, et al. Impaired effective cortical connectivity in vegetative state: Preliminary investigation using PET. Neuroimage. 1999;9(4):377–382. doi: 10.1006/nimg.1998.0414
  60. Baars BJ, Ramsøy TZ, Laureys S. Brain, conscious experience and the observing self. Trends Neurosci. 2003;26(12):671–675. EDN: ETBMQP doi: 10.1016/j.tins.2003.09.015
  61. Laureys S, Lemaire C, Maquet P, et al. Cerebral metabolism during vegetative state and after recovery to consciousness. J Neurol Neurosurg Psychiatry. 1999;67(1):121. doi: 10.1136/jnnp.67.1.121
  62. Laureys S, Faymonville ME, Luxen A, et al. Restoration of thalamocortical connectivity after recovery from persistent vegetative state. Lancet. 2000;355(9217):1790–1791. EDN: DHJJCT doi: 10.1016/s0140-6736(00)02271-6
  63. Sharon H, Pasternak Y, Ben Simon E, et al. Emotional processing of personally familiar faces in the vegetative state. PLoS ONE. 2013;8(9):e74711. doi: 10.1371/journal.pone.0074711
  64. Laureys S, Faymonville ME, Peigneux P, et al. Cortical processing of noxious somatosensory stimuli in the persistent vegetative state. Neuroimage. 2002;17(2):732–741.
  65. Boly M, Faymonville ME, Peigneux P, et al. Auditory processing in severely brain injured patients: Differences between the minimally conscious state and the persistent vegetative state. Arch Neurol. 2004;61(2):233–238. doi: 10.1001/archneur.61.2.233
  66. Laureys S, Faymonville ME, Degueldre C, et al. Auditory processing in the vegetative state. Brain. 2000;123(Pt 8): 1589–1601. EDN: ILZVNV doi: 10.1093/brain/123.8.1589

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2024 Eco-Vector

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
 


Согласие на обработку персональных данных с помощью сервиса «Яндекс.Метрика»

1. Я (далее – «Пользователь» или «Субъект персональных данных»), осуществляя использование сайта https://journals.rcsi.science/ (далее – «Сайт»), подтверждая свою полную дееспособность даю согласие на обработку персональных данных с использованием средств автоматизации Оператору - федеральному государственному бюджетному учреждению «Российский центр научной информации» (РЦНИ), далее – «Оператор», расположенному по адресу: 119991, г. Москва, Ленинский просп., д.32А, со следующими условиями.

2. Категории обрабатываемых данных: файлы «cookies» (куки-файлы). Файлы «cookie» – это небольшой текстовый файл, который веб-сервер может хранить в браузере Пользователя. Данные файлы веб-сервер загружает на устройство Пользователя при посещении им Сайта. При каждом следующем посещении Пользователем Сайта «cookie» файлы отправляются на Сайт Оператора. Данные файлы позволяют Сайту распознавать устройство Пользователя. Содержимое такого файла может как относиться, так и не относиться к персональным данным, в зависимости от того, содержит ли такой файл персональные данные или содержит обезличенные технические данные.

3. Цель обработки персональных данных: анализ пользовательской активности с помощью сервиса «Яндекс.Метрика».

4. Категории субъектов персональных данных: все Пользователи Сайта, которые дали согласие на обработку файлов «cookie».

5. Способы обработки: сбор, запись, систематизация, накопление, хранение, уточнение (обновление, изменение), извлечение, использование, передача (доступ, предоставление), блокирование, удаление, уничтожение персональных данных.

6. Срок обработки и хранения: до получения от Субъекта персональных данных требования о прекращении обработки/отзыва согласия.

7. Способ отзыва: заявление об отзыве в письменном виде путём его направления на адрес электронной почты Оператора: info@rcsi.science или путем письменного обращения по юридическому адресу: 119991, г. Москва, Ленинский просп., д.32А

8. Субъект персональных данных вправе запретить своему оборудованию прием этих данных или ограничить прием этих данных. При отказе от получения таких данных или при ограничении приема данных некоторые функции Сайта могут работать некорректно. Субъект персональных данных обязуется сам настроить свое оборудование таким способом, чтобы оно обеспечивало адекватный его желаниям режим работы и уровень защиты данных файлов «cookie», Оператор не предоставляет технологических и правовых консультаций на темы подобного характера.

9. Порядок уничтожения персональных данных при достижении цели их обработки или при наступлении иных законных оснований определяется Оператором в соответствии с законодательством Российской Федерации.

10. Я согласен/согласна квалифицировать в качестве своей простой электронной подписи под настоящим Согласием и под Политикой обработки персональных данных выполнение мною следующего действия на сайте: https://journals.rcsi.science/ нажатие мною на интерфейсе с текстом: «Сайт использует сервис «Яндекс.Метрика» (который использует файлы «cookie») на элемент с текстом «Принять и продолжить».