Epileptic activity or eeg similar to epileptic activity. How to recognize? Review

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Abstract

The review examines the recently accumulated clinical and experimental data on the mechanisms of epileptogenesis, and the most appropriate methods for recording an electroencephalogram to detect epileptiform activity. A description of epi-patterns is provided, as well as artifacts – graph elements similar to epi-patterns. All descriptions are supported by appropriate illustrations. In order to identify possible epi-activity, the need for preliminary registration of electroencephalogram with functional tests in the form of rhythmic photostimulation and hyperventilation for a person participating as a subject in studies related to physical and postural loads is emphasized.

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About the authors

Nadezhda L. Guseva

Institute of Experimental Medicine

Email: guseva_nad@mail.ru
ORCID iD: 0000-0002-4660-3873
SPIN-code: 3322-0668
Scopus Author ID: 56711691000

Cand. Sci. (Biol.), Leading Research associate of the Department of Ecological Physiology 

 

Russian Federation, 12 Academician Pavlov St., Saint Petersburg, 197022

Nikolay B. Suvorov

Institute of Experimental Medicine

Email: nbsuvorov@yandex.ru
ORCID iD: 0000-0003-2363-6012
SPIN-code: 6164-5994
Scopus Author ID: 16521673300

Professor, Dr. Sci. (Biol.), Leading Research associate of the Department of Ecological Physiology 

Russian Federation, 12 Academician Pavlov St., Saint Petersburg, 197022

Elizaveta A. Agapova

Institute of Experimental Medicine

Author for correspondence.
Email: agapova.ea@iemspb.ru
ORCID iD: 0000-0002-0767-2120
SPIN-code: 3383-9600
Scopus Author ID: 57215663447

Researcher Associate of the Department of Ecological Physiology

Russian Federation, 12 Academician Pavlov St., Saint Petersburg, 197022

Timofey V. Sergeev

Institute of Experimental Medicine, Saint Petersburg, Russia

Email: stim9@yandex.ru
ORCID iD: 0000-0001-9088-0619
SPIN-code: 4952-5143
Scopus Author ID: 57201501819

Cand. Sei. (Biol.), Head of the Biofeetback Physiology Laboratory of the Department of Ecological Physiology

Russian Federation, St.-Peterburg, Akademika Pavlova st., 12

Anton Yu. Filatov

Saint Petersburg Electrotechnical University “LETI”

Email: aifilatov@etu.ru
ORCID iD: 0000-0003-4298-8523
SPIN-code: 5926-7391
Scopus Author ID: 57194078312

Cand. Sci. (Engr.), Assistant Professor of Department of Software Engineering and Computer Applications

Russian Federation, 5, Professora Popova str. 197022 Saint Petersburg

Yulia A. Shichkina

Saint Petersburg Electrotechnical University “LETI”

Email: shichkina@co-evolution.ai
ORCID iD: 0000-0001-7140-1686
SPIN-code: 5634-7858
Scopus Author ID: 57144627300
ResearcherId: K-6530-2017

Dr. Sci. (Engr.), Professor, Head Of Department “Technologies of Artificial Intelligence in Physiology and Medicine”

Russian Federation, 5, Professora Popova str. 197022 Saint Petersburg

Mikhail S. Kupriyanov

Saint Petersburg Electrotechnical University “LETI”

Email: mskupriyanov@mail.ru
ORCID iD: 0000-0003-4695-4507
SPIN-code: 3937-5770
Scopus Author ID: 56785609900

Dr. Sci. (Engr.), Professor; Head of Department of Computer Science and Engineering

Russian Federation, 5, Professora Popova str. 197022 Saint Petersburg

References

  1. Shmidt RF, Lang F, Khekmann M, editors. Human physiology with the basics of pathophysiology. In 2 vol. Vol. 1. Transl. from German. Moscow: Laboratoriya znanii; 2019. 537 p. (In Russ.)
  2. Zenkov LR. Clinical electroencephalography (with elements of epileptology). Guide for doctors. 9th ed. Moscow: MEDpress-inform; 2018. 360 p. (In Russ.)
  3. Nerobkova LN, Tkachenko SB. Clinical electroencephalography: textbook. Moscow: RMAPO; 2016. 213 p. (In Russ.)
  4. Daly DD, Pedley A. Current Practice of Clinical Electroencephalography. 2nd ed. Lippincott Williams and Wilkins; 1990. 848 p.
  5. Jadhav C, Kamble P, Mundewadi S, et al. Clinical applications of EEG as an excellent tool for event related potentials in psychiatric and neurotic disorders. Int J Physiol Pathophysiol Pharmacol. 2022;14(2):73–83.
  6. Guseva NL, Svyatogor IA, Sofronov GA, Sirbiladze KT. Dynamics of background and jet EEG patterns of children with minimum brain dysfunctions before and after sessions of transcranial direct current stimulation. Medical Academic Journal. 2015;15(1):47–53. EDN: TOPRIV
  7. Hashemi A, Pino LJ, Moffat G, et al. Characterizing population EEG dynamics throughout adulthood. eNeuro. 2016;3(6):ENEURO.0275- 16.2016. doi: 10.1523/ENEURO.0275-16.2016
  8. Tatum WO, Rubboli G, Kaplan PW, et al. Clinical utility of EEG in diagnosing and monitoring epilepsy in adults. Clin Neurophysiol. 2018;129(5):1056–1082. doi: 10.1016/j.clinph.2018.01.019
  9. Jasper HH. The ten twenty electrode system of the international federation. Electroencephalogr Clin Neurophysiol. 1957;28:173–179.
  10. Mukhin KYu, Petrukhin AS, Glukhova LYu. Epilepsy: atlas of electro-clinical diagnostics. Moscow: Alvarez Publishing; 2004. 439 p. (In Russ.)
  11. Luder H, Noachtar S. Atlas and Classification of Electroencephalography. Philadelphia: WB Saunders; 2000. 203 р.
  12. Svyatogor IA, Dick OE, Nozdrachev AD, Guseva NL. Analysis of changes in EEG patterns in response to rhythmic photic stimulation under various disruptions of the functional state of the central nervous system. Fiziologiya cheloveka. 2015;41(3):261–268. EDN: TQQVYX doi: 10.7868/S0131164615030170
  13. Britton JW, Frey LC, Hopp JL, et al. Electroencephalography (EEG): An introductory text and atlas of normal and abnormal findings in adults, children, and infants [Internet]. Chicago: American Epilepsy Society; 2016 [cited 08.11.2023]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK390354/
  14. Kolyagin VV. Epilepsy. Irkutsk: IGMAPO; 2013. 232 p. (In Russ.) EDN: TUCJCR
  15. Svyatogor IA, Dick OE, Guseva NL, Mokhovikova IA. Neurophysiological correlates of maladaptive disorders. Saint Petersburg: Politekh-Press; 2022. 199 p. (In Russ.)
  16. Goldberg EM, Coulter DA. Mechanisms of epileptogenesis: a convergence on neural circuit dysfunction. Nat Rev Neurosci. 2013;14(5):337–349. doi: 10.1038/nrn3482
  17. Sinkin MV, Kvaskova NE, Brutyan AG, et al. Russian glossary of terms used in clinical electroencephalography. Nervnye bolezni. 2021;(1):83–88. EDN: UBAMSW doi: 10.24412/2226-0757-2021-12312
  18. Emmady PD, Anilkumar AC. EEG Abnormal Waveforms. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 [cited 08.11.2023]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK557655/
  19. Kasteleijn-Nolst Trenité D, Rubboli G, Hirsch E, et al. Methodology of photic stimulation revisited: updated European algorithm for visual stimulation in the EEG laboratory. Epilepsia. 2012;53(1):16–24. doi: 10.1111/j.1528-1167.2011.03319.x
  20. Puglia JF, Brenner RP, Soso MJ. Relationship between prolonged and self-limited photoparoxysmal responses and seizure incidence: study and review. J Clin Neurophysiol. 1992;9(1):137–144. doi: 10.1097/00004691-199201000-00015
  21. Waltz S, Christen HJ, Doose H. The different patterns of the photoparoxysmal response – a genetic study. Electroencephalogr Clin Neurophysiol. 1992;83(2):138–145. doi: 10.1016/0013-4694(92)90027-f
  22. Kasteleijn-Nolst Trenite DG, Guerrini R, Binnie CD, Genton P. Visual sensitivity and epilepsy: a proposed terminology and classification for clinical and EEG phenomenology. Epilepsia. 2001;42(5):692–701. doi: 10.1046/j.1528-1157.2001.30600.x
  23. Gulyaev SA, Arkhipenko IV. Artifacts of electroencephalographic research: their identification and differential diagnosis RMJ. 2013;21(10):486–491. (In Russ.) EDN: QZYXPV
  24. Grubov VV, Runnova AE, Hramov AE. Adaptive filtration of physiological artifacts in EEG signals in humans using empirical mode decomposition. Technical Physics. 2018;63(5):759–767. EDN: YUUYNM doi: 10.21883/JTF.2018.05.45908.2304
  25. Mari-Acevedo J, Yelvington K, Tatum WO. Normal EEG variants. Handb Clin Neurol. 2019;160:143–160. doi: 10.1016/B978-0-444-64032-1.00009-6
  26. Peltola J, Surges R, Voges B, von Oertzen TJ. Expert opinion on diagnosis and management of epilepsy-associated comorbidities. Epilepsia Open. 2024;9(1):15–32. doi: 10.1002/epi4.12851
  27. Lucke-Wold BP, Nguyen L, Turner RC, et al. Traumatic brain injury and epilepsy: underlying mechanisms leading to seizure. 2015. Seizure. 2015;33:13–23. doi: 10.1016/j.seizure.2015.10.002
  28. Christian CA, Reddy DS, Maguire J, Forcelli PA. Sex differences in the epilepsies and associated comorbidities: implications for use and development of pharmacotherapies. Pharmacol Rev. 2020;72(4):767–800. doi: 10.1124/pr.119.017392
  29. McHugh JC, Delanty N. Epidemiology and classification of epilepsy: gender comparisons. Int Rev Neurobiol. 2008;83:11–26. doi: 10.1016/S0074-7742(08)00002-0
  30. Ramantani G, Holthausen H. Epilepsy after cerebral infection: review of the literature and the potential for surgery. Epileptic Disord. 2017;19(2):117–136. doi: 10.1684/epd.2017.0916
  31. Fisher RS, Acevedo C, Arzimanoglou A, et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia. 2014;55:475–482. doi: 10.1111/epi.12550
  32. Fiest KM, Sauro KM, Wiebe S, et al. Prevalence and incidence of epilepsy. A systematic review and meta-analysis of international studies. Neurology. 2017;88:296–303. doi: 10.1212/WNL.0000000000003509
  33. Beghi E, Giussani G, Sander JW. The natural history and prognosis of epilepsy. Epileptic Disord. 2015;17:243–253. doi: 10.1684/epd.2015.0751
  34. Beghi E. The epidemiology of epilepsy. Neuroepidemiology. 2020;54(2):185–191. doi: 10.1159/000503831
  35. Åndell E, Tomson T, Åmark P, et al. Childhood-onset seizures: A long-term cohort study of use of antiepileptic drugs, and drugs for neuropsychiatric conditions. Epilepsy Res. 2020;168:106489. doi: 10.1016/j.eplepsyres.2020.106489
  36. Reddy DS. Brain structural and neuroendocrine basis of sex differences in epilepsy. Handb Clin Neurol. 2020;175:223–233. doi: 10.1016/B978-0-444-64123-6.00016-3
  37. Zöllner JP, Schmitt FC, Rosenow F, et al. Seizures and epilepsy in patients with ischaemic stroke. Neurol Res Pract. 2021;3(1):63. doi: 10.1186/s42466-021-00161-w
  38. Gregory RP, Oates T, Merry R.T. Electroencephalogram epileptiform abnormalities in candidates for aircrew training. Electroencephalogr Clin Neurophysiol. 1993;86:75–77. doi: 10.1016/0013-4694(93)90069-8
  39. Boutros N, Mirolo HA, Struve F. Normative data for the unquantified EEG: examination of adequacy for neuropsychiatric research. J Neuropsychiatry Clin Neurosci. 2005;17(1):84–90. doi: 10.1176/jnp.17.1.84
  40. Shelley BP, Trimble MR, Boutros NN. Electroencephalographic cerebral dysrhythmic abnormalities in the trinity of nonepileptic general population, neuropsychiatric, and neurobehavioral disorders. J Neuropsychiatry Clin Neurosci. 2008;20:7–22. doi: 10.1176/jnp.2008.20.1.7
  41. Verrotti A, Matricardi S, Rinaldi VE, et al. Neuropsychological impairment in childhood absence epilepsy: review of the literature. J Neurol Sci. 2015;359(1–2):59–66. doi: 10.1016/j.jns.2015.10.035
  42. Gil-Nagel A, Abou-Khalil B. Physiological monitoring during V-EEG. Handb Clin Neurol. 2012;107:343–345. doi: 10.1016/B978-0-444-52898-8.00020-3
  43. Mukherjee S, Arisi GM, Mims K, et al. Neuroinflammatory mechanisms of posttraumatic epilepsy. J Neuroinflammation. 2020;17:193. doi: 10.1186/s12974-020-01854-w
  44. Salazar AM, Grafman J. Post-traumatic epilepsy: clinical clues to pathogenesis and paths to prevention. Handb Clin Neurol. 2015;128:525–538. doi: 10.1016/B978-0-444-63521-1.00033-9
  45. Strauss KI, Elisevich KV. Brain region and epilepsy-associated differences in inflammatory mediator levels in medically refractory mesial temporal lobe epilepsy. J Neuroinflammation. 2016;13(1):270. doi: 10.1186/s12974-016-0727-z
  46. Coulthard LG, Hawksworth OA, Woodruff TM. Complement: The emerging architect of the developing brain. Trends Neurosci. 2018;41(6):373–384. doi: 10.1016/j.tins.2018.03.009
  47. Webster KM, Sun M, Crack P, et al. Inflammation in epileptogenesis after traumatic brain injury. J Neuroinflammation. 2017;14(1):10. doi: 10.1186/s12974-016-0786-1
  48. Dadas A, Janigro D. Breakdown of blood brain barrier as a mechanism of post-traumatic epilepsy. Neurobiol Dis. 2019;123:20–26. doi: 10.1016/j.nbd.2018.06.022
  49. van Vliet EA, Aronica E, Gorter JA. Blood-brain barrier dysfunction, seizures and epilepsy. Semin Cell Dev Biol. 2015;38:26–34. doi: 10.1016/j.semcdb.2014.10.003
  50. Bazhanova ED, Kozlov AA, Litovchenko AV. Mechanisms of drug resistance in the pathogenesis of epilepsy: role of neuroinflammation. A literature review. Brain Sci. 2021;11:663. doi: 10.3390/brainsci11050663
  51. Lipatova LV, Serebryanaya NB, Sivakova NA. The role of neuroinflammation in the pathogenesis of epilepsy. Neurology, neuropsychiatry, psychosomatics. 2018;10(S1):38–45. EDN: VBGRZG doi: 10.14412/2074-2711-2018-1S-38-45
  52. Sharma R, Leung WL, Zamani AJ, et al. Neuroinflammation in post-traumatic epilepsy: Pathophysiology and tractable therapeutic targets. Brain Sci. 2019;9(11):318. doi: 10.3390/brainsci9110318
  53. Uludag IF, Bilgin S, Zorlu Y, et al. Interleukin-6, interleukin-1 beta and interleukin-1 receptor antagonist levels in epileptic seizures. Seizure. 2013;22(6):457–461. doi: 10.1016/j.seizure.2013.03.004
  54. Barker-Haliski ML, Löscher W, White HS, Galanopoulou AS. Neuroinflammation in epileptogenesis: Insights and translational perspectives from new models of epilepsy. Epilepsia. 2017;58 Suppl 3(Suppl 3):39–47. doi: 10.1111/epi.13785
  55. Rana A, Musto AE. The role of inflammation in the development of epilepsy. J Neuroinflammation. 2018;15(1):144. doi: 10.1186/s12974-018-1192-7
  56. Wofford KL, Harris JP, Browne KD, et al. Rapid neuroinflammatory response localized to injured neurons after diffuse traumatic brain injury in swine. Exp Neurol. 2017;290:85–94. doi: 10.1016/j.expneurol.2017.01.004
  57. Yong HYF, Rawji KS, Ghorbani S, et al. The benefits of neuroinflammation for the repair of the injured central nervous system. Cell Mol Immunol. 2019;16(6):540–546. doi: 10.1038/s41423-019-0223-3
  58. Scheffer IE, French J, Hirsch E, et al. Classification of the epilepsies: New concepts for discussion and debate – special report of the ILAE Classification Task Force of the Commission for Classification and Terminology. Epilepsia Open. 2016;1(1–2):37–44. doi: 10.1002/epi4.5
  59. Feyissa AM, Tatum WO. Adult EEG. Handb Clin Neurol. 2019;160:103–124. doi: 10.1016/B978-0-444-64032-1.00007-2
  60. Seneviratne U, D’Souza WJ. Ambulatory EEG. Handb Clin Neurol. 2019;160:161–170. doi: 10.1016/B978-0-444-64032-1.00010-2
  61. Kotov AS. Epilepsy and sleep. S.S. Korsakov Journal of Neurology and Psychiatry. 2013;113(7):4–10. EDN: QZUPLH
  62. Delil S, Senel GB, Demiray DY, Yeni N. The role of sleep electroencephalography in patient with new onset epilepsy. Seizure. 2015;31:80–83. doi: 10.1016/j.seizure.2015.07.011
  63. Shnayder NA. Video monitoring of electroencephalography at epilepsy. Siberian medical review. 2016;(2(98)):93–106. EDN: WEFKKN
  64. Aivazyan SO. Non epileptic paroxysmal events imitating epilepsy in children. Epilepsy and Paroxysmal Conditions. 2016;8(4):23. EDN: YJCHEX doi: 10.17749/2077-8333.2016.8.4.023-033
  65. Kozhokaru АB, Karlov VА, Vlasov PN, Orlova АS. Video-EEG monitoring in diagnostics and treatment efficacy evaluation in newly-diagnosed generalized epilepsy in adults. Epilepsy and Paroxysmal Conditions. 2021;13(1):21–32. EDN: ZNCUWF doi: 17749/2077-8333/epi.par.con.2021.046
  66. Jain SV, Dye T, Kedia P. Value of combined video EEG and polysomnography in clinical management of children with epilepsy and daytime or nocturnal spells. Seizure. 2019;65:1–5. doi: 10.1016/j.seizure.2018.12.009
  67. Bergmann M, Brandauer E, Stefani A, et al. The additional diagnostic benefits of performing both video-polysomnography and prolonged video-EEG-monitoring: When and why. Clin Neurophysiol Pract. 2022;7:98–102. doi: 10.1016/j.cnp.2022.02.002
  68. Pensel MC, Nass RD, Tauboll E, et al. Prevention of sudden unexpected death in epilepsy: current status and future perspectives. Expert Rev Neurother. 2020;20(5):497–508. doi: 10.1080/14737175.2020.1754195
  69. Moore JL, Carvalho DZ, St Louis EK, Bazil C. Sleep and epilepsy: a focused review of pathophysiology, clinical syndromes, co-morbidities, and therapy. Neurotherapeutics. 2021;18(1):170–180. doi: 10.1007/s13311-021-01021-w
  70. Fountain NB, Kim JS, Lee SI. Sleep deprivation activates epileptiform discharges independent of the activating effects of sleep. J Clin Neurophysiol. 1998;15(1):69–75. doi: 10.1097/00004691-199801000-00009
  71. Guerrero-Aranda A, Enríquez-Zaragoza A, López-Jiménez K, González-Garrido AA. Yield of sleep deprivation EEG in suspected epilepsy. A retrospective study. Clin EEG Neurosci. 2024;55(2):235–240. doi: 10.1177/15500594221142397
  72. Dell’Aquila JT, Soti V. Sleep deprivation: a risk for epileptic seizures. Sleep Sci. 2022;15(2):245–249. doi: 10.5935/1984-0063.20220046
  73. Liu X, Fu Z. A novel recognition strategy for epilepsy EEG signals based on conditional entropy of ordinal patterns. Entropy (Basel). 2020;22(10):1092. doi: 10.3390/e22101092
  74. Supriya S, Siuly S, Wang H, Zhang Y. Automated epilepsy detection techniques from electroencephalogram signals: a review study. Health Inf Sci Syst. 2020;8(1):33. doi: 10.1007/s13755-020-00129-1
  75. Kim T, Nguyen P, Pham N, et al. Epileptic seizure detection and experimental treatment: a review. Front Neurol. 2020;11:701. doi: 10.3389/fneur.2020.00701
  76. Baldini S, Pittau F, Birot G, et al. Detection of epileptic activity in presumably normal EEG. Brain Commun. 2020;2(2):fcaa104. doi: 10.1093/braincomms/fcaa104
  77. Zhou1 D, Li X. Epilepsy EEG signal classification algorithm based on improved RBF. Front Neurosci. 2020;14:606. doi: 10.3389/fnins.2020.00606
  78. Ma M, Cheng Y, Wei X, et al. Research on epileptic EEG recognition based on improved residual networks of 1-D CNN and indRNN. BMC Med Inform Decis Mak. 2021;21(Suppl 2):100. doi: 10.1186/s12911-021-01438-5
  79. Najafi T, Jaafar R, Remli R, et al. A classification model of EEG signals based on RNN-LSTM for diagnosing focal and generalized epilepsy. Sensors (Basel). 2022;22(19):7269. doi: 10.3390/s22197269
  80. Parveen S, Siva Kumar SA, Jabakumar K, et al. Design of a dense layered network model for epileptic seizures prediction with feature representation. IJACSA. 2022;13(10):218–223. doi: 10.14569/IJACSA.2022.0131027
  81. Al-Salman W, Li Y, Wen P, et al. Extracting epileptic features in EEGs using a dual-tree complex wavelet transform coupled with a classification algorithm. Brain Res. 2022;1779:147777. doi: 10.1016/j.brainres.2022.147777
  82. Wang Z, Mengoni P. Seizure classification with selected frequency bands and EEG montages: a natural language processing approach. Brain Inform. 2022;9(1):11. doi: 10.1186/s40708-022-00159-3
  83. Lee K, Jeong H, Kim S, et al. Real-time seizure detection using EEG: a comprehensive comparison of recent approaches under a realistic setting. Proceedings of Machine Learning Research LEAVE UNSET:1-20, 2022. P. 1–26.

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2. Fig. 1. Patient, 12 years old, diagnosis: Rolandic epilepsy. Electroencephalogram (bipolar montage), wakefulness. Grouped sharp–slow wave complexes in the left frontotemporal leads. In leads T5–F7 the electric dipole is directed positively (down), and in leads F7–F3 it is directed negatively (up). Thus, a negative phase reversal is determined at electrode F7 [10]

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3. Fig. 2. Patient, 9 years old, diagnosis: Cryptogenic occipital epilepsy. Electroencephalogram (unipolar montage), wakefulness [10]

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4. Fig. 3. Electroencephalogram, characteristic of the norm, with dominance of the alpha rhythm with a frequency of 11 cps and maximum amplitude in the occipital leads [12]

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5. Fig. 4. An electroencephalogram fragment demonstrating depression of the alpha rhythm when the eyes are open (ОГ mark) and its recovery when the eyes are closed (ЗГ mark) [archival data from N.L. Guseva, I.A. Svyatogor]

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6. Fig. 5. The main types of epileptiform activity: 1 — spikes; 2 — sharp waves; 3 — sharp waves in the β band (14–20 Hz); 4 — spike-wave; 5 — multiple spikes-wave; 6 — sharp wave–slow wave. (The calibration signal value for spike-wave 4 is 100 µV, for other records — 50 µV.) [2]

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7. Fig. 6. Peak–slow wave [10, 11]

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8. Fig. 7. Increasing peak–slow wave complexes [10, 11]

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9. Fig. 8. Polyspikes [10, 11]

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10. Fig. 9. Three-phase waves [18]

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11. Fig. 10. Spike-wave generalized [18]

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12. Fig. 11. Electroencephalogram pattern of seizure [10, 11]

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13. Fig. 12. Electroencephalogram status pattern [10, 11]

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14. Fig. 13. Outbreak of epileptiform activity during RFS at a frequency of 16 Hz in a patient with post-traumatic encephalopathy with convulsive syndrome [archival data from N.L. Guseva and I.A. Svyatogor]

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15. Fig. 14. Artifacts in electroencephalogram during eye movements [10, 11]

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16. Fig. 15. An example of an electrocardiogram artifact [10, 11]

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17. Fig. 16. Electroencephalogram with a rheographic artifact recorded on channel F3 [archival data from N.L. Guseva and I.A. Svyatogor]

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18. Fig. 17. Electroencephalogram with galvanic skin responsein artifacts [archival data from N.L. Guseva and I.A. Svyatogor]

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