Electroencephalograms of 220 patients with post-coma disorders of consciousness after severe traumatic brain injury were analyzed using nonlinear multidimensional analysis, and the results were compared with those of standard linear time-amplitude analysis. Quantitative multichannel EEGs were recorded in the course of one-year-long clinical restorative treatment and rehabilitation. We tried to identify informative indices obtained using nonlinear analysis, which most closely correlated with the dynamics of the syndromes of altered consciousness (classification according to Dobrokhotova [34]). The diagnostic informational value of the results of nonlinear analysis of quantitative EEGs and sensitivity of this methodical approach in predicting positive/negative dynamics of consciousness recovery were estimated. Results of mapping of the values of entropy, dimension of the brain dynamic systems (complexity), parameters of the attractors, and multifractal properties of EEGs in different patient groups are described. It is concluded that the obtained results of nonlinear analysis demonstrate sertain advantages in prediction of the clinical course of post-coma disturbances of consciousness after brain trauma.
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S. Boccaletti, C. Grebogi, Y.-C. Lai, et al., “The control of chaos: Theory and applications,” Phys. Rep., 329, 108–109 (2000).
O. Yu. Mayorov, A. D. Glukhov, V. N. Fenchenko, and A. B. Prognimak, “Implementation of the method of displacement using estimation of the size of the attractor axes in the dynamic system of the brain,” Kibernet. Vychisl. Tekhn., 153, 3–9 (2017).
O. Yu. Mayorov and V. N. Fenchenko, “Study of brain bioelectrical activity from the standpoint of multidimensional linear and nonlinear EEG analyses,” Klin. Inform. Telemed., 4, No. 5, 12–20 (2008).
O. Yu. Mayorov and V. N. Fenchenko, “Method of channels and jokers in the study of brain bioelectrical activity,” Klinich. Informat. Telemed., 8, No .9, 17–23 (2012).
I. B. Starchenko, A. A. Reznichenko, and R. Yu. Budko, “Modeling of electrical processes in the human brain using non-linear dynamics methods,” Prikasp. Zh. Upravl. Vys. Tekhnol., 2, No. 22, 80–88 (2013).
A. C. Soong and C. I. Stuart, “Evidence of chaotic dynamics underlying the human alpha-rhythm electroencephalogram,” Biol. Cybern., 62, No. 1, 55–62 (1989).
M. V. Aleksandrov, “Possibilities of quantitative EEG in assessing the level of depressed consciousness: ways to overcome the methodological crisis,” Proc. II Vseros. Sci. Pract. Conf. “Quantitative EEG and neurotherapy”, St. Petersburg, April 27-29, P. 5 (2009).
Yu. V. Andreyev, A. S. Dmitriyev, and D. A. Kuminov, “Chaotic processors,” Usp. Sovrem. Radioelektron., No. 10, 50-77 (1997).
A. S. Dmitriyev, “Chaos and information processing in nonlinear dynamic systems,” Radiotekh. Elektron., 38, No. 1, 1–24 (1993).
A. Rényi, “On measures of information and entropy,” in Proc. 4th Berkeley Symp. Math. Stat. Probab., Vol. 1, University of California Press, Berkeley, 547–561 (1960).
C. J. Stam, “Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field,” Clin. Neurophysiol., 116, No. 10, 2266–2301 (2005).
P. E. Rapp, T. R. Bashore, J. M. Martinerie, et al., “Dynamics of brain electrical activity,” Brain Topogr., 2, Nos. 1–2, 99–118 (1989).
J. J. Dunkin, A. F. Leuchter, T. F. Newton, and I. A. Cook, “Reduced EEG coherence in dementia: state or trait marker?” Biol. Psychiatry, 35, No. 11, 870–879 (1994).
O. Gosseries, C. Schnakers, D. Ledoux, et al., “Automated EEG entropy measurements in coma, vegetative state/unresponsive wakefulness syndrome and minimally conscious state,” Funct. Neurol., 26, No. 1, 25–30 (2011).
A. Babloyantz, “Chaotic dynamics in brain activity,” Behav. Brain Sci., 10, No. 2, 173–174 (1987).
R. G. Michel, L. Glass, M. C. Mackey,and A Shrier, “Chaos in neurobiology,” IEEE Trans. Syst. Man Cybern., 13, No. 5, 790–798 (1983).
G. Mayer-Kress and S. P. Layne, “Dimensionality of the human encephalogram,” Ann. N.Y. Acad. Sci., 504, 62–87 (1987).
M. Lin, H. Chan, and S. Fang, “Linear and nonlinear EEG indexes in relation to the severity of coma,” Conf. Proc. IEEE Eng. Med. Biol. Soc., 5, 4580–4583 (2005).
B. Vivien, O. Langeron, and B. Riou, “Entropy and bispectral index in brain-dead organ donors,” Intens. Care Med., 33, No. 5, 919–920 (2007).
J. Wennervirta, T. Salmi, M. Hynynen, et al., “Entropy is more resistant to artifacts than bispectral index in braindead organ donors,” Intens. Care Med., 33, No. 1, 133–136 (2007).
D. Y. Wu, G. Cai, Y. Yuan, et al., “Application of nonlinear dynamics analysis in assessing unconsciousness: A preliminary study,” Clin. Neurophysiol., 122, No. 3, 490-498 (2011).
O. Yu. Mayorov and V. N. Fenchenko, “On calculation of the parameters of deterministic chaos in studies of bioelectrical activity (EEG),” Klin. Inform. Telemed., 3, No. 4, 37–46 (2006).
J. Röschke, J. Fell, and P. Beckmann, “Nonlinear analysis of sleep EEG data in schizophrenia: calculation of the principal Lyapunov exponent,” Psychiatry Res.” 56, No. 3, 257–269 (1995).
A. Babloyantz and A. Destexhe, “Low-dimensional chaos in an instance of epilepsy,” Proc. Natl. Acad. Sci. U.S.A., 83, No. 10, 3515–3517 (1986).
A. Babloyantz and A. Destexhe, “The Creutzfeldt–Jacob disease in the hierarchy of chaotic attractors,” In From Chemical to Biological Organization (M. Markus, S. Muller, and G. Nicolis, eds.), Springer, Berlin, 307–316 (1987).
R. Hornero, A. Alonso, N. Jimero, et al., “Nonlinear analysis of time series generated by schizophrenic patients,” IEEE Eng. Med. Biol., 18, No. 3, 84–90 (1999).
J. Jeong, J. H. Chae, S. Y. Kim, and S. H. Han, “Nonlinear dynamic analysis of the EEG in patients with Alzheimer’s disease and vascular dementia,” J. Clin. Neurophysiol., 18, No. 1, 58–67 (2001).
F. Wendling., J. J. Bellanger, F. Bartolomei, and P. Chauvel,“ Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals,” Biol. Cybernet., 83, No. 4, 367–378 (2000).
N. V. Thakor and S. Tong., “Advances in quantitative electroencephalogram analysis methods,” Annu. Rev. Biomed. Eng., 6, 453–495 (2004).
Ye. V. Sharova, O. S. Zaytsev, G. A. Shchekut’yeva, et al., “EEG and EPs in predicting the development of unconscious states after a severe trauma,” Proc. Don. Natl. Med. Univ., 4, 82–84 (2008).
S. Slobounov, W. Sebastianelli, and M. Hallett, “Residual brain dysfunction observed one year post-mild traumatic brain injury: combined EEG and balance study,” Clin. Neurophysiol., 123, No. 9, 1755–1761 (2012).
S. Spasic, M. Culic, G. Grbic, et al., “Spectral and fractal analysis of cerebellar activity after single and repeated brain injury,” Bull. Math. Biol., 70, No. 4, 1235–1249 (2008).
R. W. Thatcher, C. Biver, R. McAlaster, and A. Salazar, “Biophysical linkage between MRI and EEG coherence in closed head injury,” NeuroImage, 8, No. 4, 307–326 (1998).
O. S Zaitsev and S. V Tsarenko, Neuroreanimatology in Coming out of the Coma (Therapy of Postcomatous States), Litass, Moscow (2012).
D. Y. Wu, G. Cai, R. D. Zorowitz, et al., “Measuring interconnection of the residual cortical functional islands in persistent vegetative state and minimal conscious state with EEG nonlinear analysis,” Clin. Neurophysiol., 122, No. 10, 1956–1966 (2011).
A. Destexhe, J.A. Sepulchre, and A. Babloyantz., “A comparative study of the experimental quantification of deterministic chaos,” Phys. Lett. A, 132, No. 2, 101–106 (1988).
W. J. Freeman, “Simulation of chaotic EEG pattern with a dynamic model of the olfactory system,” Biol. Cybern., 56, No. 2–3, 139–150 (1987).
W. J. Freeman, Y. Yao, and B. Burke, “Central pattern generating and recognition in olfactory bulb: a correlation learning rule,” Neural Networks, 1, No. 4, 277–288 (1988)
C. A. Skarda and W. J. Freeman, “How brains make chaos in order to make sense of the world,” Behav. Brain Sci., 10, 161–195 (1987).
C. K. Peng, S. Havlin, H. E. Stanley, and A. L. Goldberger, “Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series,” Chaos, 5, No. 1, 82–87 (1995).
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Kulyk, O.V. Nonlinear Analysis of Quantitative EEGs in Patients with Syndromes of Post-Coma Disorders of Consciousness after Severe Traumatic Brain Injury. Neurophysiology 50, 456–465 (2018). https://doi.org/10.1007/s11062-019-09778-9
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DOI: https://doi.org/10.1007/s11062-019-09778-9