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: 159)
Language: 
Russian
Article type: 
Review
UDC: 
537.86; 612.825.3+612.08+612.82

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

Autors: 
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, Immanuel Kant Baltic Federal University
Abstract: 

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.

Reference: 
  1. Abarbanel HD, Rabinovich MI, Selverston A, Bazhenov MV, Huerta R, Sushchik MM, Rubchinskii LL. Synchronisation in neural networks. Phys. Usp. 1996;39(4):337–362. DOI: 10.1070/PU1996v039n04ABEH000141.
  2. Mosekilde E, Maistrenko Y, Postnov DE. Chaotic Synchronization, Applications to Living Systems. Singapore: World Scientific; 2002. 440 p. DOI: 10.1142/4845.
  3. Bezruchko BP, Ponomarenko VI, Prokhorov MD, Smirnov DA, Tass PA. Modeling nonlinear oscillatory systems and diagnostics of coupling between them using chaotic time series analysis: applications in neurophysiology. Phys. Usp. 2008;51(3):304–310. DOI: 10.1070/PU2008v051n03ABEH006494.
  4. Nekorkin VI. Nonlinear oscillations and waves in neurodynamics. Phys. Usp. 2008;51(3):295–304. DOI: 10.1070/PU2008v051n03ABEH006493.
  5. Tass PA et al. Detection of n:m phase locking from noisy data: Application to magnetoencephalography. Phys. Rev. Lett. 1998;81(15):3291–3294. DOI: 10.1103/PhysRevLett.81.3291.
  6. Tass PA, 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;90(8):088101. DOI: 10.1103/physrevlett.90.088101.
  7. Anishchenko VS, Balanov AG, Janson NB et al. Entrainment between heart rate and weak nonlinear forcing. Int. J. Bifurcation Chaos. 2000;10(10):2339–2348. DOI: 10.1142/S0218127400001468.
  8. Prokhorov MD, Ponomarenko VI, Gridnev VI et al. Synchronization between main rhythmic processes in the human cardiovascular system. Phys. Rev. E. 2003;68(4):041913. DOI: 10.1103/physreve.68.041913.
  9. Hramov AE, Koronovskii AA, Ponomarenko VI, Prokhorov MD. Detecting synchronization of self-sustained oscillators by external driving with varying frequency. Phys. Rev. E. 2006;73(2):026208. 10.1103/PhysRevE.73.026208.
  10. Koronovskii AA, Ponomarenko VI, Prokhorov MD, Hramov AE. Method of studying the synchronization of self-sustained oscillations using continuous wavelet analysis of univariant data. Tech. Phys. 2007;52(7):1106–1116. DOI: 10.1134/S1063784207090022.
  11. Meinecke FC, Ziehe A, Kurths J, Muller KR. Measuring phase synchronization of superimposed signals. Phys. Rev. Lett. 2005;94(8):084102. DOI: 10.1103/physrevlett.94.084102.
  12. Chavez M, Adam C, Navarro V et al. On the intrinsic time scales involved in synchronization: A data-driven approach. Chaos. 2005;15(2):023904. DOI: 10.1063/1.1938467.
  13. Tass PA, Fieseler T, Dammers J, Dolan KT, Morosan P, Majtanik M, Boers F, Muren A, Zilles K, Fink GR. Synchronization tomography: A method for three-dimensional localization of phase synchronized neuronal populations in the human brain using magnetoencephalography. Phys. Rev. Lett. 2003;90(8):088101. DOI: 10.1103/physrevlett.90.088101.
  14. Perez Velazquez JL, Khosravani H, Lozano A et al. Type III intermittency in human partial epilepsy. European Journal of Neuroscience. 1999;11(7):2571–2576. DOI: 10.1046/j.1460-9568.1999.00688.x.
  15. Koronovskii AA, Kuznetsova GD, Midzyanovskaya IS, Sitnikova EY, Trubetskov DI, Khramov AE. Regularities of alternate behavior in spontaneous nonconvulsive seizure activity in rats. Doklady Biological Sciences. 2006;409(1):275–277. DOI: 10.1134/S0012496606040016.
  16. Hramov AE, Koronovskii AA, Midzyanovskaya IS et al. On-off intermittency in time series of spontaneous paroxysmal activity in rats with genetic absence epilepsy. Chaos. 2006;16(4):043111. DOI: 10.1063/1.2360505.
  17. Koronovskii AA, Khramov AE. Continuous Wavelet Analysis and Its Applications. Moscow: Fizmatlit; 2003. 176 p. (in Russian).
  18. Torrence C, Compo GP. A practical guide to wavelet analysis. Bulletin of the American Meteorological Society. 1998;79(1):61–78. DOI: 10.1175/1520-0477(1998)079<0061:APGTWA>2.0.CO;2.
  19. Van den Berg JC Wavelets in Physics. Cambridge: Cambridge University Press; 2004. 453 p. DOI: 10.1017/CBO9780511613265.
  20. Aldroubi A, Unser M. Wavelets in Medicine and Biology. CRC-Press; 1996. 632 p.
  21. Anfinogentov VG, Koronovskii AA, Khramov AE. Wavelet analysis and its use to analyze the dynamics of nonlinear dynamic systems of various nature. Bulletin of the Russian Academy of Sciences: Physics. 2000;64(12):2383 (in Russian).
  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;9(3):218–224. DOI: 10.1016/0920-1211(91)90055-k.
  23. Durka PJ. From wavelets to adaptive approximations: Time-frequency parametrization of EEG. Biomed. Eng. Online. 2003;2:1. DOI: https://dx.doi.org/10.1186/1475-925X-2-1.
  24. Quiroga RQ, Kraskov A, Kreuz T, Grassberger P. Performance of different synchronization measures in real data: A case study on electroencephalographic signals. Phys. Rev. E. 2002;65(4):041903. DOI: 10.1103/PhysRevE.65.041903.
  25. Aldroubi A, Unser M. Wavelets in Medicine and Biology. CRC-Press; 1996. 632 p.
  26. Doron I, Hulata E, Baruchi I, Towle VL, Ben-Jacob E. Time-invariant person-specific frequency templates in human brain activity. Phys. Rev. Lett. 2006;96(25):258101. DOI: 10.1103/PhysRevLett.96.258101.
  27. Gong P, Nikolaev AR, van Leeuwen S. Intermittent dynamics underlying the intrinsic fluctuations of the collective synchronization patterns in electrocortical activity. Phys. Rev. E. 2007;76(1):011904. DOI: 10.1103/PhysRevE.76.011904.
  28. Makarov VA, Pavlov AN, Tupitsyn AN, Panetsos F, Moreno A. Stability of neural firing in the trigeminal nuclei under mechanical whisker stimulation. Computational Intelligence and Neuroscience. 2010;2010:340541. DOI: 10.1155/2010/340541.
  29. Pavlov AN. Wavelet-­analysis and examples of it's applications. Izvestiya VUZ. Applied Nonlinear Dynamics. 2009;17(5):99–111 (in Russian). DOI: 10.18500/0869-6632-2009-17-5-99-111.
  30. Steriade M. Neuronal Substrates of Sleep an Epilepsy. Cambridge (UK): Cambridge University Press; 2003. 522 p. DOI: 10.1017/CBO9780511541711.
  31. Steriade M. Thalamocortical oscillations in the sleeping and aroused brain. Science. 1993;262(5134):679–685. DOI: 10.1126/science.8235588.
  32. Sitnikova E, van Luijtelaar G. Cortical and thalamic coherence during spike-wave seizures in WAG/Rij rats. Epilepsy Res. 2006;71:159.
  33. Strogatz SH. Exploring complex networks. Nature. 2001;410(6825):268–276. DOI: 10.1038/35065725.
  34. Boccaletti S, Latora V, Moreno V et al. Complex networks: Structure and dynamics. Physics Reports. 2006;424(4–5):175–308. DOI: 10.1016/j.physrep.2005.10.009.
  35. Kryukov AK, Osipov GV, Polovinkin AV, Kurths J. Synchronous regimes in ensembles of coupled Bonhoeffer–van der Pol oscillators. Phys. Rev. E. 2009;79(4):046209. DOI: 10.1103/PhysRevE.79.046209.
  36. Zenett DM and Mikhailov AS. Mutual synchronization in ensembles of globally coupled neural networks. Phys. Rev. E. 1998;58(1):872–875. DOI: 10.1103/PhysRevE.58.872.
  37. Ito H, Nikolaev AR, Leeuwen C. Dynamics of spontaneous transitions between global brain states. Human Brain Mapping. 2007;28(9):904–913. DOI: 10.1002/hbm.20316.
  38. Nikolaev AR, Pulin G, Leeuwen C. Evoked phase synchronization between adjacent high-density electrodes in human scalp EEG: Duration and time course related to behavior. Clin. Neurophysiol. 2005;116(10):2403–2419. DOI: 10.1016/j.clinph.2005.07.003.
  39. Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clin. Neurophysiol. 2002;113(6):767–791. DOI: 10.1016/S1388-2457(02)00057-3.
  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. Rehabil. Eng. 2000;8(4):447–456. DOI: 10.1109/86.895947.
  41. Astaf’eva NM. Wavelet analysis: basic theory and some applications. Phys. Usp. 1996;39(11):1085–1108. DOI: 10.1070/PU1996v039n11ABEH000177.
  42. Astafieva N.M. Wavelet analysis: spectral analysis of local disturbances (basic theory and application examples). Izvestiya VUZ. Applied Nonlinear Dynamics. 1996;4(2):3 (in Russian).
  43. Dremin IM, Ivanov OV, Nechitailo VA. Wavelets and their uses. Phys. Usp. 2001;44(5):447–478. DOI: 10.1070/PU2001v044n05ABEH000918.
  44. Sitnikova EY, Hramov AE, Koronovskii AA, 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;180(2):304–316. DOI: 10.1016/j.jneumeth.2009.04.006.
  45. Hramov AE, Koronovskii AA, Ponomarenko VI, Prokhorov MD. Detection of synchronization from univariate data using wavelet transform. Phys. Rev. E. 2007;75(5):056207. DOI: 10.1103/physreve.75.056207.
  46. Freeman WJ. Mass Action in the Nervous System. N.Y.: Academic Press; 1975. 489 p. DOI: 10.1016/C2009-0-03145-6.
  47. Steriade M, Deschenes M. The thalamus as a neuronal oscillator. Brain Res. Rev. 1984;8(1):1–63. DOI: 10.1016/0165-0173(84)90017-1.
  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;194(1):172–178. DOI: 10.1016/j.jneumeth.2010.09.017.
  49. Destexhe A, Sejnowski TJ. Thalamocortical Assemblies. Oxford: Oxford University Press; 2001. 472 p.
  50. Kostopoulos GK. Spike-and-wave discharges of absence seizures as a transformation of sleep spindles: the continuing development of a hypothesis. Clin. Neurophysiol. 2000;111(Suppl. 2):S27–S38. DOI: 10.1016/s1388-2457(00)00399-0.
  51. Brunelli R. Template Matching Techniques in Computer Vision: Theory and Practice. Wiley; 2009. 352 p.
  52. van Luijtelaar G, Hramov AE, Sitnikova EY, Koronovskii AA. Spike-wave discharges in WAG/Rij rats are preceded by delta and theta precursor activity in cortex and thalamus. Clin. Neurophysiology. 2011;122(4):687–695. DOI: 10.1016/j.clinph.2010.10.038.
  53. Drinkenburg WH et al. Spike-wave discharges and sleep-wake states in rats with absence epilepsy. Epilepsy Res. 1991;9(3):218–224 (in Russian).
  54. Ovchinnikov AA, Hramov AE, Luttjehann A et al. Method for diagnostics of characteristic patterns of observable time series and its real-time experimental implementation for neurophysiological signals. Tech. Phys.2011;56(1):1–7. DOI: 10.1134/S1063784211010191.
  55. Wolpaw JR, Birbaumer N, McFarland DJ, Pfurtscheller G, Vaughan TM. Brain-computer interfaces for communication and control. Clin. Neurophysiol. 2002;113(6):767–791. DOI: 10.1016/S1388-2457(02)00057-3.
  56. Ivanitsky GA, Naumov RA, Roik AO, Ivanitsky AM. How to determine what the brain is doing by its electrical potentials? Stable EEG patterns when performing cognitive tasks. Questions of Artificial Intelligence. 2008;1(1):93–102 (in Russian).
  57. Kaplan AY, Lim JJ, Jin KS, Park BW, Byeon JG, Tarasova SU. Unconscious operant conditioning in the paradigm of brain-computer interface based on color perception. Int. J. Neurosci. 2005;115(6):781–802. DOI: 10.1080/00207450590881975.
  58. Dataq Instruments [Electronic resource]. Available from: http://www.dataq.com.  
Received: 
16.10.2010
Accepted: 
16.10.2010
Published: 
29.04.2011
Short text (in English):
(downloads: 80)