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Sitnikova E. Y. Thalamo-cortical dysrhythmia and its diagnostic principles. Izvestiya VUZ. Applied Nonlinear Dynamics, 2020, vol. 28, iss. 3, pp. 282-298. DOI: 10.18500/0869-6632-2020-28-3-282-298

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Thalamo-cortical dysrhythmia and its diagnostic principles

Sitnikova Evgenia Yurievna, Federal State Budgetary Institution of Science "Institute of Higher Nervous Activity and Neurophysiology RAS"

Aim. In the brain of mammals and humans, several widespread neuronal networks are capable of generating spontaneous rhythmic activity. Among them is the thalamo-cortical network, which involves neurons of the thalamus (diencephalon) and in the neocortex and characterized by hierarchical organization. The thalamo-cortical network generates alpha rhythms with a frequency of about 8...14 Hz. Various neurological and psychiatric disorders are known to associate with similar disturbances of thalamo-cortical rhythms, i.e. the thalamo-cortical dysrhythmia. In particular, absence epilepsy, a non-convulsive form of epilepsy caused by disturbances of the thalamo-cortical system. Absence seizures involve brief and sudden lapses of consciousness (i.e., the state of «absence») associated with high-amplitude spike-wave discharges in the encephalogram. The current paper describes morphology of the thalamo-cortical system and diagnostic principles of the thalamo-cortical dysrhythmia. Methods. WAG/Rij rats with genetic predisposition to absence epilepsy were used as a model of the thalamo-cortical dysrhythmia. Electrical brain activity was recorded from the surface of neocortex using implanted electrodes (electrocorticogram, ECoG). Time-frequency analysis of rhythmic activity in ECoG was performed using continuous wavelet transform and the fast Fourier transform. Results. The following hallmarks of the thalamo-cortical dysrhythmia were defined. (1) During the slow-wave sleep, the spectral power in ECoG was shifted from slow to fast frequencies. (2) Short-lasting episodes of 3...12 Hz rhythmic activity with the amplitude maximum in delta (3...4 Hz) and theta (5...9 Hz) ranges were present in the frontal ECoG. (3) The so-called «pro-epileptic» 5...9 Hz oscillations were present in the frontal ECoG. Conclusion. The most pronounced manifestation of the thalamo-cortical dysrhythmia was found in ECoG during the slow-wave sleep. The dysrhythmic mechanism mostly affected short-lasting slow-wave oscillations with a frequency of 3...4 Hz and 5...9 Hz in combination with disturbances of the time-frequency structure of ECoG.


1. Livanov M.N. Spatiotemporal Organization of Potentials and Systemic Activity of the Brain: Selected Works. Moscow: Nauka, 1989, 400 p. (in Russian).

2. Ivanitski˘ı AM, Lebedev AN. Solving the riddle of the brain rhythms. Zh. Vyssh. Nerv. Deiat. Im. I.P. Pavlova, 2007, vol. 57, no. 5, pp. 636–640 (in Russian).

3. Nekorkin V.I. Nonlinear oscillations and waves in neurodynamics. UFN, 2008, vol. 178, no. 3, pp. 313–323; Phys. Usp., 2008, vol. 51, no. 3, pp. 295–304.

4. Lopes da Silva F. Neural mechanisms underlying brain waves: From neural membranes to networks // Electroencephalogr. Clin. Neurophysiol. 1991. Vol. 79, no. 2. P. 81–93.

5. Niedermeyer E., Lopes da Silva F. Electroencephalography: Basic Principles, Clinical Applications, and Related Fields. 5th ed. Philadelphia, London: Lippincot Williams & Wilkins, 2005.

6. Zenkov L.R. Clinical Encephalography (with elements of epileptology). Guide for doctors. Moscow: MEDpress-inform, 2017, 360 p. (in Russian).

7. Le Van Quyen M., Bragin A. Analysis of dynamic brain oscillations: Methodological advances // Trends Neurosci. 2007. Vol. 30, no. 7. P. 365–373.

8. Bronzino J.D. Quantitative analysis of the EEG: General concepts and animal studies // IEEE Trans. Biomed. Eng. 1984. Vol. 31. P. 850–856.

9. Blanco S., Quiroga R.Q., Rosso O.A., Kochen S. Time-frequency analysis of electroencephalogram series // Phys. Rev. E. Stat. Phys. Plasmas Fluids Relat Interdiscip Topics. 1995. Vol. 51, no. 3. P. 2624–2631.

10. Blanco S., D’Attellis C.E., Isaacson S.I., Rosso O.A., Sirne R.O. Time-frequency analysis of electroencephalogram series. II. Gabor and wavelet transforms // Phys. Rev. E. Stat. Phys. Plasmas Fluids Relat Interdiscip Topics. 1996. Vol. 54, no. 6. P. 6661–6672.

11. Blanco S., Figliola A., Quian Quiroga R., Rosso O.A., Serrano E. Time-frequency analysis of electroencephalogram series (III): Wavelet packets and information cost function // Phys. Rev. E. 1998. Vol. 57, no. 1. P. 932–940.

12. Durka P.J. From wavelets to adaptive approximations: Time-frequency parametrization of EEG // Biomed Eng Online. 2003. Vol. 2. 1. doi:10.1186/1475-925x-2-1

13. Aldroubi A., Unser M. Wavelets in Medicine and Biology. CRC Press, Boca Raton RL, USA, 1996. 616 p.

14. Pavlov A.N., Hramov A.E., Koronovskii A.A., Sitnikova E.Yu., Makarov V.A., Ovchinnikov A.A. Wavelet analysis in neurodynamics. Phys. Usp., 2012, vol. 55, pp. 845–875.

15. Hramov A.E., Koronovskii A.A., Makarov V.A., Pavlov A.N., Sitnikova E. Wavelets in Neuroscience. London, Springer Series in Synergetics, Springer, Heidelberg, New York, 2015. 318 p.

16. 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, no. 1, pp. 86–108 (in Russian).

17. Buzsaki G. Large-scale recording of neuronal ensembles // Nature Neurosci. 2004. Vol. 7, no. 5. ´ P. 446–451.

18. Destexhe A., Sejnowski T.J. Thalamocortical assemblies. Oxford University Press, Oxford, 2001.

19. Aleksandrov M.V., Chukhlovin A.A., Pavlovskaya M.E., Kostenko I.A., Arkhipova N.B. Alphatheta continuum: Underlying neurophysiological mechanism. Medical alphabet, 2017, vol. 1, no. 14, pp. 46–50 (in Russian).

20. Bazanova O.M. Current interpretation of EEG alpha activity. Successes in physiological sciences, 2009, vol. 40, no. 3, pp. 32–53 (in Russian).

21. Sitnikova E.Yu. Disturbance of rhythmic activity in neuronal networks: Thalamocortical dysrhythmia. Proceedings of the VI All-Russian Conference «Nonlinear Dynamics in Cognitive Research – 2019», Nizhny Novgorod, IAP RAS, 2019, pp. 163–165 (in Russian). 

22. Sherman S.M., Guillery R.W. Exploring the Thalamus and its Role in Cortical Function. 2nd ed. Cambridge: MIT Press, 2006. 484 p.

23. Pyrzowski J., Siemiсski M., Sarnowska A., Jedrzejczak J., Nyka W.M. Interval analysis of interictal EEG: Pathology of the alpha rhythm in focal epilepsy // Sci. Rep. 2015. Vol. 5. 16230. doi: 10.1038/srep16230

24. Schulman J.J., Cancro R., Lowe S., Lu F., Walton K.D., Llinas R.R. ´ Imaging of thalamocortical dysrhythmia in neuropsychiatry // Front. Hum. Neurosci. 2011. Vol. 5. 69. doi: 10.3389/fnhum.2011.00069. eCollection 2011.

25. Llinas R.R., Ribary U., Jeanmonod D., Kronberg E., Mitra P.P. ´ Thalamocortical dysrhythmia: A neurological and neuropsychiatric syndrome characterized by magnetoencephalography // Proc. Natl. Acad. Sci. USA. 1999. Vol. 96, № 26. P. 15222–15227.

26. Jeanmonod D., Magnin M., Morel A., Siegemund M., Cancro A., Lanz M., Llinas R., Ribary U., ´ Kronberg E., Schulman J., Zonenshayn M. Thalamocortical dysrhythmia II. Clinical and surgical aspects // Thalamus & Related Systems. 2001. Vol. 1, № 3. P. 245–254. doi:10.1017/S1472928801000267

27. Llinas R., Ribary U., Jeanmonod D., Cancro R., Kronberg E., Schulman J., Zonenshayn M., ´ Magnin M., Morel A., Siegmund M. Thalamocortical dysrhythmia I. Functional and imaging aspects // Thal. Rel. Sys. 2001. Vol. 1. P. 237–244.

28. Llinas R., Urbano F.J., Leznik E., Ramнrez R.R., van Marle H.J. ´ Rhythmic and dysrhythmic thalamocortical dynamics: GABA systems and the edge effect // Trends Neurosci. 2005. Vol. 28, № 6. P. 325–333.

29. Lopes da Silva F.H. Electrical potentials. In: Encyclopedia of the Human Brain / Ed. V.S. Ramachandran. Elsevier Science, 2002. P. 147–167.

30. Handbook of Electroencephalography and Clinical Neurophysiology. Lopes da Silva F.H., Givens A.S., Remond A. (Eds). Amsterdam: Elsevier Science Publisher B.V., 1986.

31. Lopes da Silva F., van Rotterdam A. Biophysical aspects of EEG and MEG generation // In: Electroencephalography. Basic Principles, Clinical Applications and Related Fields. E. Niedermeyer, F. Lopes da Silva (Eds). Baltimore, Munich: Urban & Schwarzenberg, 1982. P. 5–26 (next edition 1987: 29–41). 

32. Vanneste S., Song J.J., De Ridder D. Thalamocortical dysrhythmia detected by machine learning // Nature Communications. 2018. Vol. 9. 1103. doi:10.1038/s41467-018-02820-0

33. Zobeiri M., Budde T. van Luijtelaar G. Thalamocortical dysrhythmia: Cellular and network mechanisms. Neuronus IBRO Neuroscience Forum 2018, Krakow, Poland, April 2018. https://

34. Zobeiri M., Chaudhary R., Datunashvili M., Heuermann R.J., Luttjohann A., Narayanan V., ¨ Balfanz S., Meuth P., Chetkovich D.M., Pape H.C., Baumann A., van Luijtelaar G., Budde T. Modulation of thalamocortical oscillations by TRIP8b, an auxiliary subunit for HCN channels // Brain Structure and Function. 2018. Vol. 223, no. 3. P. 1537–1564.

35. Zobeiri M., Chaudhary R., Blaich A., Rottmann M., Herrmann S., Meuth P., Bista P., Kanyshkova T., Luttjohann A., Narayanan V., Hundehege P., Meuth S.G., Romanelli M.N., Urbano F.J., ¨ Pape H.C., Budde T., Ludwig A. The Hyperpolarization-activated HCN4 channel is important for proper maintenance of oscillatory activity in the thalamocortical system // Cerebral Cortex. 2019. Vol. 29, no. 5. P. 2291–2304.

36. Luthi A., McCormick D.A. ¨ H-current: Properties of a neuronal and network pacemaker // Neuron. 1998. Vol. 21, no. 1. P. 9–12.

37. David F., ¸Car¸cak N., Furdan S., Onat F., Gould T., Mesz ´ aros ´ A., Di Giovanni G., Hern ´ andez V.M., ´ Chan C.S., Lorincz M.L., Crunelli V. ¨ Suppression of hyperpolarization-activated cyclic nucleotide-gated channel function in ihalamocortical neurons prevents genetically determined and pharmacologically induced absence seizures // J. Neurosci. 2018. Vol. 38, no. 30. P. 6615–6627.

38. Zobeiri M., van Luijtelaar G., Budde T., Sysoev I.V. The brain network in a model of thalamocortical dysrhythmia // Brain Connect. 2019. Vol. 9, no. 3. P. 273–284.

39. Coenen A.M., van Luijtelaar E.L. Genetic animal models for absence epilepsy: A review of the WAG/Rij strain of Rats // Behav. Genetics. 2003. Vol. 33. P. 635–655.

40. van Luijtelaar G., Coenen A. Genetic Models of Absence Epilepsy: New Concepts and Insights // In: Encyclopedia of Basic Epilepsy Research. Editor Philip A. Schwartzkroin. Vol. 1. Oxford: Academic Press, 2009. P. 1–8.

41. Vol’nova A.B., Lenkov D.N. Absence epilepsy: Mechanisms of hypersynchronization of neuronal ensembles. Medical Academic Journal, 2012, vol. 12, no. 1. pp. 7–19 (in Russian). 

42. Panayiotopoulos C.P. Typical absence seizures and related epileptic syndromes: Assessment of current state and directions for future research // Epilepsia. 2008. Vol. 49. P. 2131–2139.

43. van Luijtelaar G., Sitnikova E. Global and focal aspects of absence epilepsy: The contribution of genetic models // Neurosci. Biobehav. Rev. 2006. Vol. 30. P. 983–1003.

44. Luttjohann A., Pape H.C. ¨ Regional specificity of cortico-thalamic coupling strength and directionality during waxing and waning of spike and wave discharges // Sci. Rep. 2019. Vol. 9. 2100. doi:10.1038/s41598-018-37985-7

45. Luttjohann A., van Luijtelaar G. ¨ The dynamics of cortico-thalamo-cortical interactions at the transition from pre-ictal to ictal LFPs in absence epilepsy // Neurobiol. Dis. 2012. Vol. 47, no. 1. P. 49–60.

46. Luttjohann A., Schoffelen J.M., van Luijtelaar G. ¨ Peri-ictal network dynamics of spike-wave discharges: phase and spectral characteristics // Exp. Neurol. 2013. Vol. 239. P. 235–247.

47. Sysoeva M.V., Sitnikova E., Sysoev I.V., Bezruchko B.P., van Luijtelaar G. Application of adaptive nonlinear Granger causality: Disclosing network changes before and after absence seizure onset in a genetic rat model // J. Neurosci. Methods. 2014. Vol. 226. P. 33–41. doi:10.1016/j.jneumeth.2014.01.028

48. Sysoeva M.V., Sitnikova E., Sysoev I.V. Thalamo-cortical mechanisms of initiation, maintenance and termination of spike-wave discharges at WAG/Rij rats. Zh. Vyssh. Nerv. Deiat., 2016, vol. 66, no. 1, pp. 103–112.

49. Sysoeva M.V., Luttjohann A., van Luijtelaar G., Sysoev I.V. ¨ Dynamics of directional coupling underlying spike-wave discharges // Neuroscience. 2016. Vol. 314. P. 5–89.

50. Sitnikova E.Yu., Smirnov K.S., Grubov V.V., Hramov A.Е. Diagnostic principles of immature epileptic (proepileptic) EEG activity in rats with genetic predisposition to absence epilepsy. Information and Control Systems, 2019, vol. 1, pp. 89–97 (in Russian). 

51. Sitnikova E., Hramov A.E., Grubov V., Koronovsky A.A. Rhythmic activity in EEG and sleep in rats with absence epilepsy // Brain Res Bull. 2016. Vol. 120. P. 106–116.

52. van Luijtelaar G., Hramov A., Sitnikova E., Koronovskii A. Spike-wave discharges in WAG/Rij rats are preceded by delta and theta precursor activity in cortex and thalamus // Clin. Neurophysiol. 2011. Vol. 122. P. 687–695.

53. Sitnikova E.Y., Koronovskii A.A., Hramov A.E. Analysis of epileptic activity of brain in case of absence epilepsy: Applied aspects of nonlinear dynamics. Izvestiya VUZ. Applied Nonlinear Dynamics, 2011, vol. 19, no. 6, pp. 173–182 (in Russian).

54. Sitnikova E.Y., Koronovskii A.A., Hramov A.E. Analysis of rhythmic brain activity in absence epilepsy: An electroencephalographic study. Proceedings of the II All-Russian Conference «Nonlinear Dynamics in Cognitive Research – 2011». Nizhny Novgorod. IAP RAS, 2011, pp. 190–192 (in Russian).