ОРИГИНАЛЬНОЕ ИССЛЕДОВАНИЕ

Особенности биоэлектрической активности ретросплениальной коры головного мозга

Информация об авторах

1 Инженерно-физический институт биомедицины Национального исследовательского ядерного университета «МИФИ», Москва, Россия

2 Клиника Ла Салюте, Москва, Россия

Для корреспонденции: Сергей Александрович Гуляев
Раменки, д. 31, к. 136, г. Москва, 119607, Россия; moc.liamg@37veaylug.s

Информация о статье

Вклад авторов: С. А. Гуляев — идея проекта, реализация клинико-нейрофизиологического исследования, статистический анализ результатов; Л. М. Ханухова — организация исследования; А. А. Гармаш — общее руководство исследованием.

Соблюдение этических стандартов: исследование одобрено этическим комитетом НИЯУ МИФИ (протокол № 05/23 от 25 мая 2023 г.), проведено в соответствии с принципами биомедицинской этики, сформулированными в Хельсинкской декларации 1964 г. и ее последующими обновлениями.

Статья получена: 27.06.2023 Статья принята к печати: 04.09.2023 Опубликовано online: 25.09.2023
|
  1. Delorme A, Makeig S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004; 134 (1): 9–21. Available from: https://doi.org/10.1016/j.jneumeth.2003.10.009. PMID: 15102499.
  2. Martínez-Cancino R, Delorme A, Truong D, Artoni F, KreutzDelgado K, Sivagnanam S, et al. The open EEGLAB portal Interface: High-Performance computing with EEGLAB. Neuroimage. 2021; 224: 116778. Available from: https://doi.org/10.1016/j.neuroimage.2020.116778. Epub 2020 Apr 11. PMID: 32289453; PMCID: PMC8341158.
  3. Tadel F, Bock E, Niso G, Mosher JC, Cousineau M, Pantazis D, et al. MEG/EEG Group Analysis With Brainstorm. Front Neurosci. 2019; 13: 76. Available from: https://doi.org/10.3389/fnins.2019.00076. PMID: 30804744; PMCID: PMC6378958.
  4. Jasper H, Penfield W. Electrocorticograms in man: effect of voluntary movement upon the electrical activity of the precentral gyrus. Archiv für Psychiatrie und Nervenkrankheiten. 1949; 183: 163–74.
  5. Lopes Da Silva FH, Storm Van Leeuwen W. The cortical source of the alpha rhythm. Neurosci Lett. 1977; 6 (2-3): 237–41. Available from: https://www.doi.org/10.1016/0304-3940(77)90024-6.
  6. Klimesch W. α-Band oscillations, attention, and controlled access to stored information. Trends Cogn Sci. 2012; 16 (12): 606–17. Available from: https://www.doi.org/10.1016/j.tics.2012.10.007.
  7. Klimesch W. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Res Brain Res Rev. 1999; 29 (2-3): 169–95. Available from: https://www.doi.org/10.1016/s0165-0173(98)00056-3.
  8. Klimesch W, Sauseng P, Hanslmayr S. EEG alpha oscillations: the inhibition-timing hypothesis. Brain Res Rev. 2007; 53 (1): 63–88. Available from: https://www.doi.org/10.1016/j.brainresrev.2006.06.003.
  9. Klimesch W, Doppelmayr M, Hanslmayr S. Upper alpha ERD and absolute power: their meaning for memory performance. Prog Brain Res. 2006; 159: 151–65. Available from: https://www.doi.org/10.1016/S0079-6123(06)59010-7.
  10. Иванов Л. Б. Спектр мощности электроэнцефалограммы: ошибки и практика применения (лекция первая). Медицинский алфавит. 2021; (39): 45–52. Доступно по ссылке: https://doi.org/10.33667/2078-5631-2021-39-45-52.
  11. Lydon EA, Nguyen LT, Shende SA, Chiang HS, Spence JS, Mudar RA. EEG theta and alpha oscillations in early versus late mild cognitive impairment during a semantic Go/NoGo task. Behav Brain Res. 2022; 416: 113539. DOI: 10.1016/j.bbr.2021.113539. Epub 2021 Aug 17. PMID: 34416304.
  12. Rusiniak M, Lewandowska M, Wolak T, Pluta A, Milner R, Skarźyński H. Mozliwości i problemy jednoczesnych rejestracji EEG-fMRI--badanie rytmu alfa [The possibilities and limitations of simultaneous EEG-fMRI registration--the alpha rhythm study]. Przegl Lek. 2015; 72 (11): 616–9. PMID: 27012118. Polish.
  13. Alexander AS, Place R, Starrett MJ, Chrastil ER, Nitz DA. Rethinking retrosplenial cortex: Perspectives and predictions. Neuron. 2023; 111 (2): 150–75. Available from: https://doi.org/10.1016/j.neuron.2022.11.006. Epub 2022 Dec 1. PMID: 36460006.
  14. Todd TP, Fournier DI, Bucci DJ. Retrosplenial cortex and its role in cue-specific learning and memory. Neurosci Biobehav Rev. 2019; 107: 713–28. Available from: https://doi.org/10.1016/j.neubiorev.2019.04.016. Epub 2019 May 2. PMID: 31055014; PMCID: PMC6906080.
  15. Trask S, Fournier DI. Examining a role for the retrosplenial cortex in age-related memory impairment. Neurobiol Learn Mem. 2022; 189: 107601. DOI: 10.1016/j.nlm.2022.107601. Epub 2022 Feb 22. PMID: 35202816.
  16. Olsen GM, Ohara S, Iijima T, Witter MP. Parahippocampal and retrosplenial connections of rat posterior parietal cortex. Hippocampus. 2017; 27 (4): 335–58. Available from: https://doi.org/10.1002/hipo.22701. Epub 2017 Jan 16. PMID: 28032674.
  17. Sugar J, Witter MP, van Strien NM, Cappaert NL. The retrosplenial cortex: intrinsic connectivity and connections with the (para) hippocampal region in the rat. An interactive connectome. Front Neuroinform. 2011; 5: 7. Available from: https://doi.org/10.3389/fninf.2011.00007. PMID: 21847380; PMCID: PMC3147162.
  18. Dillen KNH, Jacobs HIL, Kukolja J, von Reutern B, Richter N, Onur ÖA, Dronse J, Langen KJ, Fink GR. Aberrant functional connectivity differentiates retrosplenial cortex from posterior cingulate cortex in prodromal Alzheimer's disease. Neurobiol Aging. 2016; 44: 114–26. Available from: https://doi.org/10.1016/j.neurobiolaging.2016.04.010. Epub 2016 Apr 22. PMID: 27318139.
  19. Squire LR, Genzel L, Wixted JT, Morris RG. Memory consolidation. Cold Spring Harb Perspect Biol. 2015; 7 (8): a021766. Available from: https://doi.org/10.1101/cshperspect.a021766. PMID: 26238360; PMCID: PMC4526749.
  20. de Sousa AF, Cowansage KK, Zutshi I, Cardozo LM, Yoo EJ, Leutgeb S, Mayford M. Optogenetic reactivation of memory ensembles in the retrosplenial cortex induces systems consolidation. Proc Natl Acad Sci U S A. 2019; 116 (17): 8576– 81. Available from: https://doi.org/10.1073/pnas.1818432116. Epub 2019 Mar 15. PMID: 30877252; PMCID: PMC6486739
  21. Auger SD, Maguire EA. Retrosplenial Cortex Indexes Stability beyond the Spatial Domain. J Neurosci. 2018; 38 (6): 1472–81. Available from: https://doi.org/10.1523/JNEUROSCI.2602-17.2017. Epub 2018 Jan 8. PMID: 29311139; PMCID: PMC5815348.
  22. Mitchell AS, Czajkowski R, Zhang N, Jeffery K, Nelson AJD. Retrosplenial cortex and its role in spatial cognition. Brain Neurosci Adv. 2018; 2: 2398212818757098. Available from: https://doi.org/10.1177/2398212818757098. PMID: 30221204; PMCID: PMC6095108.
  23. Corcoran KA, Yamawaki N, Leaderbrand K, Radulovic J. Role of retrosplenial cortex in processing stress-related context memories. Behav Neurosci. 2018; 132 (5): 388–95. Available from: https://doi.org/10.1037/bne0000223. Epub 2018 Jun. 7. PMID: 29878804; PMCID: PMC6188831.
  24. Milczarek MM, Vann SD. The retrosplenial cortex and long-term spatial memory: from the cell to the network. Curr Opin Behav Sci. 2020; 32: 50–56. Available from: https://doi.org/10.1016/j.cobeha.2020.01.014. PMID: 32715030; PMCID: PMC7374566.
  25. Mitchell AS, Czajkowski R, Zhang N, Jeffery K, Nelson AJD. Retrosplenial cortex and its role in spatial cognition. Brain Neurosci Adv. 2018; 2: 2398212818757098. Available from: https://doi.org/10.1177/2398212818757098. PMID: 30221204; PMCID: PMC6095108.
  26. Powell A, Connelly WM, Vasalauskaite A, Nelson AJD, Vann SD, Aggleton JP, et al. Stable Encoding of Visual Cues in the Mouse Retrosplenial Cortex. Cereb Cortex. 2020; 30 (8): 4424–37. Available from: https://doi.org/10.1093/cercor/bhaa030. PMID: 32147692; PMCID: PMC7438634.
  27. Fischer LF, Mojica Soto-Albors R, Buck F, Harnett MT. Representation of visual landmarks in retrosplenial cortex. Elife. 2020; 9: e51458. Available from: https://doi.org/10.7554/eLife.51458. PMID: 32154781; PMCID: PMC7064342.
  28. Fournier DI, Monasch RR, Bucci DJ, Todd TP. Retrosplenial cortex damage impairs unimodal sensory preconditioning. Behav Neurosci. 2020; 134 (3): 198–207. DOI: 10.1037/bne0000365. Epub 2020 Mar 9. PMID: 32150422; PMCID: PMC7244381.
  29. Mao D, Molina LA, Bonin V, McNaughton BL. Vision and Locomotion Combine to Drive Path Integration Sequences in Mouse Retrosplenial Cortex. Curr Biol. 2020; 30 (9): 1680–8.e4. Available from: https://doi.org/10.1016/j.cub.2020.02.070. Epub 2020 Mar 19. PMID: 32197086.
  30. Morris R, Pandya DN, Petrides M. Fiber system linking the middorsolateral frontal cortex with the retrosplenial/presubicular region in the rhesus monkey. J Comp Neurol. 1999; 407 (2): 183–92. Available from: https://doi.org/10.1002/(sici)1096-9861(19990503)407:2<183::aid-cne3>3.0.co;2-n. PMID: 10213090.
  31. Clark BJ, Simmons CM, Berkowitz LE, Wilber AA. The retrosplenial-parietal network and reference frame coordination for spatial navigation. Behav Neurosci. 2018; 132 (5): 416–29. Available from: https://doi.org/10.1037/bne0000260. Epub 2018 Aug 9. PMID: 30091619; PMCID: PMC6188841.
  32. Aggleton JP, Yanakieva S, Sengpiel F, Nelson AJ. The separate and combined properties of the granular (area 29) and dysgranular (area 30) retrosplenial cortex. Neurobiol Learn Mem. 2021; 185: 107516. DOI: 10.1016/j.nlm.2021.107516. Epub 2021 Sep 3. PMID: 34481970.
  33. Epstein RA, Parker WE, Feiler AM. Where am I now? Distinct roles for parahippocampal and retrosplenial cortices in place recognition. J Neurosci. 2007; 27 (23): 6141–9. Available from: https://doi.org/10.1523/JNEUROSCI.0799-07.2007. PMID: 17553986; PMCID: PMC6672165.
  34. Spiers HJ, Maguire EA. Thoughts, behavior, and brain dynamics during navigation in the real world. Neuroimage. 2006; 31 (4): 1826–40. Available from: https://doi.org/10.1016/j.neuroimage.2006.01.037. Epub 2006 Apr 11. PMID: 16584892.
  35. Tamburro G, Fiedler P, Stone D, Haueisen J, Comani S. A new ICAbased fingerprint method for the automatic removal of physiological artifacts from EEG recordings. PeerJ. 2018; 6: e4380. DOI: 10.7717/peerj.4380. PMID: 29492336; PMCID: PMC5826009.
  36. Lehmann D, Strik WK, Henggeler B, Koenig T, Koukkou M Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. Int J Psychophysiol. 1998; 29 (1): 1–11. Available from: https://doi.org/10.1016/s0167-8760(97)00098-6.
  37. Schacter DL, Crovitz HF. "Falling" while falling asleep: sex differences. Percept Mot Skills. 1977; 44 (2): 656. DOI: 10.2466/ pms.1977.44.2.656. PMID: 866074.
  38. Sarter M Fritschy JM Reporting statistical methods and statistical results in EJN. Eur J Neurosci. 2008; 28 (12): 2363–4. Available from: https://doi.org/10.1111/j.1460-9568.2008.06581.x.
  39. Иванов Л. Б. Спектр мощности по электроэнцефалограмме: ошибки и практика применения (лекция вторая). Дисперсионный анализ электроэнцефалограммы по Росману. Медицинский алфавит. 2022; (9): 38–43. Available from: https://doi.org/10.33667/2078-5631-2022-9-38-43.
  40. Croce P, Quercia A, Costa S, Zappasodi F. EEG microstates associated with intra- and inter-subject alpha variability. Sci Rep. 2020; 10 (1): 2469. Available from: https://doi.org/ 10.1038/ s41598-020-58787-w.
  41. Poskanzer C, Denis D, Herrick A, Stickgold R. Using EEG microstates to examine post-encoding quiet rest and subsequent word-pair memory. Neurobiol Learn Mem. 2021; 181: 107424. Available from: https://doi.org/ 10.1016/j.nlm.2021.107424.
  42. Pascual-Marqui RD, Michel CM, Lehmann D. Segmentation of brain electrical activity into microstates: model estimation and validation. IEEE Trans Biomed Eng. 1995; 42 (7): 658–65. Available from: https://doi.org/10.1109/10.391164.
  43. Milz P, Pascual-Marqui RD, Lehmann D, Faber PL. Modalities of Thinking: State and Trait Effects on Cross-Frequency Functional Independent Brain Networks. Brain Topogr. 2016; 29 (3): 477–90. Available from: https://doi.org/10.1007/s10548-016-0469-3.
  44. Seitzman BA, Abell M, Bartley SC, Erickson MA, Bolbecker AR, Hetrick WP. Cognitive manipulation of brain electric microstates. Neuroimage. 2017; 146: 533–43. Available from: https://doi.org/10.1016/j.neuroimage.2016.10.002.
  45. Mishra A, Englitz B, Cohen MX. EEG microstates as a continuous phenomenon. Neuroimage. 2020; 208: 116454. Available from: https://doi.org/10.1016/j.neuroimage.2019.116454. Epub 2019 Dec 10.
  46. Milz P, Faber PL, Lehmann D, Koenig T, Kochi K, PascualMarqui RD. The functional significance of EEG microstates-Associations with modalities of thinking. Neuroimage. 2016; 125: 643–56. Available from: https://doi.org/10.1016/j. neuroimage.2015.08.023.
  47. Pascual-Marqui RD, Esslen M, Kochi K, Lehmann D. Functional imaging with low-resolution brain electromagnetic tomography (LORETA): a review. Methods Find Exp Clin Pharmacol. 2002; 24 Suppl C: 91–5. PMID: 12575492.
  48. Grech R, Cassar T, Muscat J, Camilleri KP, Fabri SG, Zervakis M, et al. Review on solving the inverse problem in EEG source analysis. J Neuroeng Rehabil. 2008; 5: 25. Available from: https:// doi.org/10.1186/1743-0003-5-25.
  49. Neuner I, Arrubla J, Werner CJ, Hitz K, Boers F, Kawohl W, et al. The default mode network and EEG regional spectral power: a simultaneous fMRI-EEG study. PLoS One. 2014; 9 (2): e88214. Available from: https://doi.org/10.1371/journal.pone.0088214
  50. Vukovic N, Hansen B, Lund TE, Jespersen S, Shtyrov Y. Rapid microstructural plasticity in the cortical semantic network following a short language learning session. PLoS Biol. 2021; 19 (6): e3001290. Available from: https://doi.org/10.1371/journal.pbio.3001290. PMID: 34125828; PMCID: PMC8202930.
  51. Hubert V, Beaunieux H, Chételat G, Platel H, Landeau B, Viader F, Desgranges B, Eustache F. Age-related changes in the cerebral substrates of cognitive procedural learning. Hum Brain Mapp. 2009; 30 (4): 1374–86. Available from: https://doi.org/10.1002/hbm.20605. PMID: 18537110; PMCID: PMC2935916.
  52. Just MA, Keller TA. Converging measures of neural change at the microstructural, informational, and cortical network levels in the hippocampus during the learning of the structure of organic compounds. Brain Struct Funct. 2019; 224 (3): 1345–57. Available from: https://doi.org/10.1007/s00429-019-01838-4. Epub 2019 Feb 6. PMID: 30725233.
  53. Nunez PL, Wingeier BM, Silberstein RB. Spatial-temporal structures of human alpha rhythms: theory, microcurrent sources, multiscale measurements, and global binding of local networks. Hum Brain Mapp. 2001; 13 (3): 125–64. Available from: https://doi.org/10.1002/hbm.1030. PMID: 11376500; PMCID: PMC6872048.
  54. Rodriguez-Larios J, ElShafei A, Wiehe M, Haegens S. Visual working memory recruits two functionally distinct alpha rhythms in posterior cortex. eNeuro. 2022; 9 (5): ENEURO.0159-22.2022. DOI: 10.1523/ENEURO.0159-22.2022. Epub ahead of print. PMID: 36171059; PMCID: PMC9536853.