ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)

For citation:

Koronovskii A. A., van Luijtelaar G. ., Ovchinnikov A. A., Sitnikova E. Y., Hramov A. E. Diagnostics and analysis of oscillatory neuronal network activity of brain with continuous wavelet analysis. Izvestiya VUZ. Applied Nonlinear Dynamics, 2011, vol. 19, iss. 1, pp. 86-108. DOI: 10.18500/0869-6632-2011-19-1-86-108

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Full text:
(downloads: 123)
Article type: 
537.86; 612.825.3+612.08+612.82

Diagnostics and analysis of oscillatory neuronal network activity of brain with continuous wavelet analysis

Koronovskii Aleksei Aleksandrovich, Saratov State University
van Luijtelaar Gilles , University Nijmegen
Ovchinnikov Aleksej Aleksandrovich, Saratov State University
Sitnikova Evgenia Yurievna, Federal State Budgetary Institution of Science "Institute of Higher Nervous Activity and Neurophysiology RAS"
Hramov Aleksandr Evgenevich, Innopolis University

In the article we present an overview of a number of continuous wavelet transformbased techniques for analysis and diagnostic of oscillatory neuronal network activity of brain in experimentally obtained electroencephalographic data. We describe a technique for automatic detection of characteristic patterns for paroxysmal activity (spike-wave discharges) in epileptic electroencephalogram (EEG) based on wavelet spectrum power analysis, obtained with continuous wavelet transform with complex mother wavelet (Morlet) in specific frequency ranges. An effective approach to sleep spindles detection and classification based on special adaptive wavelet-basis construction (spindle-wavelets) is proposed. Proposed techniques are shaped for real time EEG signals study and can be used for building systems for monitoring activity of a brain challenged with epilepsy. A study of spectral and temporal structure of EEG before spike-wave discharges is carried out and characteristic predecessors of paroxysmal activity are found, which can be used for detecting brain transition state. Such diagnostics can be used to predict epileptic seizures in clinical practice.

  1. Абарбанель Г.Д.И., Рабинович М.И., Селверстон А. и др. Синхронизация в нейронных ансамблях // Успехи физических наук. 1996. Т. 166. С. 363.
  2. Mosekilde E., Maistrenko Yu., Postnov D.E. Chaotic synchronization, applications to living systems. Singapore: World Scientific, 2002.
  3. Безручко, Б.П., Пономаренко, В.И., Прохоров М.Д. и др. Моделирование и диагностика взаимодействия нелинейных колебательных систем по хаотическим временным рядам (приложения в нейрофизиологии) // Успехи физических на- ук. 2008. Т. 178. С. 323.
  4. Некоркин В.И. Нелинейные колебания и волны в нейродинамике // Успехи физических наук. 2008. Т. 178. С. 313.
  5. Tass P.A. et al. Detection of n:m phase locking from noisy data: Application to magnetoencephalography // Phys. Rev. Lett. 1998. Vol. 81. P. 3291.
  6. Tass P.A., Fieseler T., Dammers J. et al. Synchronization tomography: A method for three-dimensional localization of phase synchronized neuronal populations in the human brain using magnetoencephalography // Phys. Rev. Lett. 2003. Vol. 90. P. 088101.
  7. Anishchenko V.S., Balanov A.G., Janson N.B. et al. Entrainment between heart rate and weak nonlinear forcing // Int. J. Bifurcation and Chaos. 2000. Vol. 10. P. 2339.
  8. Prokhorov M.D., Ponomarenko V.I., Gridnev V.I. et al. Synchronization between main rhythmic processes in the human cardiovascular system // Phys. Rev. E. 2003. Vol. 68. P. 041913.
  9. Hramov A.E., Koronovskii A.A., Ponomarenko V.I., Prokhorov M.D. Detecting synch-ronization of self-sustained oscillators by external driving with varying frequency // Phys. Rev. E. 2006. Vol. 73. P. 026208.
  10. Короновский А.А., Пономаренко В.И., Прохоров М.Д., Храмов А.Е. Метод исследования синхронизации автоколебаний по унивариантным данным с использованием непрерывного вейвлетного анализа // ЖТФ. 2007. T. 77, No 9. С. 6.
  11. Meinecke F.C., Ziehe A., Kurths J., Muller K.-R. Measuring phase synchronization of superimposed signals // Phys. Rev. Lett. 2005. Vol. 94. P. 084102.
  12. Chavez M., Adam C., Navarro V. et al. On the intrinsic time scales involved in synchronization: A data-driven approach // Chaos. 2005. Vol. 15. P. 023904.
  13. Tass P. A., Fieseler T., Dammers J., Dolan K.T., Morosan P., Majtanik M., Boers F., Muren A., Zilles K., Fink G.R. Synchronization tomography: A method for threedimensional localization of phase synchronized neuronal populations in the human brain using magnetoencephalography // Phys. Rev. Lett. 2003. Vol. 90, No 8. 088101.
  14. Perez Velazquez J.L., Khosravani H., Lozano A. et al. Type III inermittency in human partial epilepcy // European Journal of Neuroscience. 1999. Vol. 11. P. 2571.
  15. Короновский А.А., Кузнецова Г.Д., Мидзяновcкая И.С., Ситникова Е.Ю., Трубецков Д.И., Храмов А.Е. Закономерности перемежающегося поведения в спонтанной неконвульсивной судорожной активности у крыс // ДАН. 2006. T. 409. C. 274.
  16. Hramov A.E., Koronovskii A.A., Midzyanovskaya I.S. et al. On-off intermittency in time series of spontaneous paroxysmal activity in rats with genetic absence epilepsy // Chaos. 2006. Vol. 16. P. 043111.
  17. Короновский А.А., Храмов А.Е. Непрерывный вейвлетный анализ и его приложения. М.: Физматлит, 2003.
  18. Torrence C., Compo G.P. A practical guide to wavelet analysis // Bulletin of the American Meteorological Society. 1998. Vol. 79. P. 61.
  19. Wavelets in Physics / Van den Berg, J.C. Eds. Cambridge: Cambridge University Press, 2004.
  20. Aldroubi A., Unser M. Wavelets in Medicine and Biology. CRC-Press, 1996.
  21. Анфиногентов В.Г., Короновский А.А., Храмов А.Е. Вейвлетный анализ и его использование для анализа динамики нелинейных динамических систем различной природы // Изв. РАН, cер. физич. 2000. Vol. 64, No 12. P. 2383.
  22. Drinkenburg WHIM, Coenen AML, Vossen JMH, van Luijtelaar ELJM. Spike-wave discharges and sleep-wake states in rats with absence epilepsy // Epilepsy Res. 1991. Vol. 9. P. 218.
  23. Durka P.J. From wavelets to adaptive approximations: Time-frequency parametrization of EEG // Biomed. Eng. Online. 2003; 2:1.
  24. Quiroga R.Q., Kraskov A., Kreuz T., Grassberger P. Perfomance of different synchronization measures in real data: A case study on electroencephalographic signals // Phys. Rev. E. 2002. Vol. 65. P. 041903.
  25. Aldroubi A., Unser M. Wavelets in Medicine and Biology. CRC-Press, 1996.
  26. Doron I., Hulata E., Baruchi I., Towle V.L., Ben-Jacob E. Time-invariant personspecific frequency templates in human brain activity // Physical Review Letters. 2006. Vol. 96. P. 258101.
  27. Gong Pulin, Nikolaev A.R., L. van Cees. Intermittent dynamics underlying the intrinsic fluctuations of the collective synchronization patterns in electrocortical activity // Phys. Rev. E. 2007. Vol. 76. P. 011904.
  28. Makarov V.A., Pavlov A.N., Tupitsyn A.N., Panetsos F., Moreno A. Stability of neural firing in the trigeminal nuclei under mechanical whisker stimulation // Computational Intelligence and Neuroscience. 2010. Vol. 2010.
  29. Павлов А.Н. Вейвлет-анализ и примеры его применения // Известия вузов. Прикладная нелинейная динамика. 2009. Т. 17, No 5. С. 99.
  30. Steriade M. Neuronal substrates of sleep an epilepsy. Cambridge (UK): Cambridge University Press, 2003.
  31. Steriade M. Thalamocortical oscillations in the sleeping and aroused brain // Science. 1993. Vol. 262. P. 679.
  32. Sitnikova E., van Luijtelaar G. Cortical and thalamic coherence during spike-wave seizures in WAG/Rij rats // Epilepsy Res. 2006. Vol. 71. P. 159.
  33. Strogatz S.H. Exploring complex networks // Nature. 2001. Vol. 410. P. 268.
  34. Boccaletti S., Latora V., Moreno V. et al. Complex networks: Structure and dynamics // Physics Reports. 2006. Vol. 424. P. 175.
  35. Kryukov A.K., Osipov G.V., Polovinkin A.V., Kurth J. Synchronous regimes in ensembles of coupled Bonhoeffer–van der Pol oscillators // Physical Review E. 2009. Vol. 79. P. 046209.
  36. Zenett D.M. and Mikhailov A.S. Mutual synchronization in ensembles of globally coupled neural networks // Phys. Rev. E. 1998. Vol. 58. P. 872.
  37. Ito H., Nikolaev A.R., Leeuwen C. Dynamics of spontaneous transitions between global brain states // Human Brain Mapping. 2007. Vol. 28. P. 904.
  38. Nikolaev A.R., Pulin G., Leeuwen C. Evoked phase synchronization between adjacent high-density electrodes in human scalp EEG: Duration and time course related to behavior // Clinical Neurophysiology. 2005. Vol. 116. P. 2403.
  39. Wolpaw J.R., Birbaumer N., McFarland D.J., Pfurtscheller G., Vaughan T.M. Brain-computer interfaces for communication and control // Clin Neurophysiol. 2002. Vol. 113. P. 767.
  40. Guger C., Ramoser H., and Pfurtscheller G. Real-time EEG analysis for a brain-computer interface (BCI) with subject-specific spatial patterns // IEEE Trans. Rehab. Eng. 2000. Vol. 8. P. 562.
  41. Астафьева Н.М. Вейвлет–анализ: Основы теории и примеры применения // УФН. 1996. Vol. 166, No 11. P. 1145.
  42. Астафьева Н.М. Вейвлет-анализ: Спектральный анализ локальных возмущений (основы теории и примеры применения) // Известия вузов. Прикладная нелинейная динамика. 1996. Т. 4, No 2. С. 3.
  43. Дремин И.М., Иванов О.В., Нечитайло В.А. Вейвлеты и их применение // УФН. 2001. Т. 171, No 5. С. 465.
  44. Sitnikova E.Yu., Hramov A.E., Koronovskii A.A., van Luijtelaar G. Sleep spindles and spike-wave discharges in EEG: Their generic features, similarities and distinctions disclosed with Fourier transform and continuous wavelet analysis // Journal of Neuroscience Methods. 2009. Vol. 180. P. 304.
  45. Hramov A.E., Koronovskii A.A., Ponomarenko V.I., Prokhorov M.D. Detection of synchronization from univariate data using wavelet transform // Phys. Rev. E. 2007. Vol. 75, No 5. 056207.
  46. Freeman W.J. Mass Action in the Nervous System. N.Y.: Academic Press, 1975.
  47. Steriade M., Deschenes M. The thalamus as a neuronal oscillator // Brain Res. Rev. 1984. Vol. 8. P. 1.
  48. Ovchinnikov A., Luttjohann A., Hramov A., van Luijtelaar G. An algorithm for real-time detection of spike-wave discharges in rodents // Journal of Neuroscience Methods. 2010.
  49. Destexhe A., Sejnowski T.J. Thalamocortical assemblies. Oxford: Oxford University Press, 2001.
  50. Kostopoulos G.K. Spike-and-wave discharges of absence seizures as a transformation of sleep spindles: the continuing development of a hypothesis // Clin Neurophysiol. 2000; Suppl. 2: S27-38.
  51. Brunelli R. Template Matching Techniques in Computer Vision: Theory and Practice. Wiley, 2009.
  52. van Luijtelaar G., Hramov A.E., Sitnikova E.Yu., Koronovskii A.A. Spike-wave discharges in WAG/Rij rats are preceded by delta and theta precursor activity in cortex and thalamus // Clinical Neurophysiology. 2010.
  53. Drinkenburg W.H. et al. Spike-wave discharges and sleep-wake states in rats with absence epilepsy // Epilepsy Res. 1991. Vol. 9, No 3. P. 218.
  54. Овчинников А.А., Храмов А.Е., Люттьеханн А., Короновский А.А., ван Луйтелаар Ж. Метод диагностики характерных паттернов на наблюдаемых временных рядах и его экспериментальная реализация в режиме реального времени применительно к нейрофизиологическим сигналам // ЖТФ. 2011. Т. 81, No 1. С. 3.
  55. Wolpaw J.R., Birbaumer N., McFarland D.J., Pfurtscheller G., Vaughan T.M. Brain-computer interfaces for communication and control // Clin Neurophysiol. 2002. Vol. 113, No 6. P. 767.
  56. Иваницкий Г.А., Наумов Р.А., Роик А.О., Иваницкий А.М. Как определить, чем занят мозг, по его электрическим потенциалам? Устойчивые паттерны ЭЭГ при выполнении когнитивных заданий // Вопросы искусственного интеллекта. 2008. Т. 1, No 1. С. 93.
  57. Kaplan A.Ya., Lim J.J., Jin K.S., Park B.W., Byeon J.G., Tarasova S.U. Unconscious operant conditioning in the paradigm of brain-computer interface based on color perception // Intern. J. Neurosci. 2005. Vol. 115. Т. 781.
Short text (in English):
(downloads: 41)