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Stability of correlations of non-linear electrical activity of the resting brain with closed eyes

Published 2021-01-01
Articles

Abstract

Introduction: the signal of the EEG is usually interpreted from a linear perspective, however, for some decades now the electrical activity of the brain has been studied as a dynamic system, based on the theory of chaos, with non-linear mathematics. Objective: analize the stability of correlations of hurst indices over time in resting subjects with closed eyes. Methods: 13 male university students were evaluated with the brain-interface device Emotiv Epoc® with sampling frequency of 128 Hz. the frequency ranges delta (1-3 Hz), theta (3.5-7 Hz), alpha (8-12 Hz), beta (13-30 Hz) and gamma (>30 Hz) were analyzed. Results: the results show stability in the percentage of correlations in all the bands studied in most of the subjects. this situation occurs in temporary windows of 10, 30 and 60 seconds. Conclusion: this exploratory study shows the persistence intime of non-linear meta-synchronous processes that obey the dynamics of balance chaos/global order of the brain, in resting conditions, basal with closed eyes.

Categories

Authors

  • Fernando Maureira Cid

    Universidad Metropolitana de Ciencias de la Educación de Chile

  • Hernán Díaz-Muñoz

  • Marcelo Hadweh-Briceño

  • Elizabeth Flores-Ferro

  • Ángela Silva-Salse

References

Bassingthwaighte J, Raymond G. (1994). Evaluating rescaled range analysis for time series. Annals of Biomedical Engineering, 2(4): pp. 432-444.

Bear M, Connors B, Paradiso M. (2016) Neurociencia, la exploración del cerebro. 4° ed. Madrid: Wolters Kluver.

Buzsaki G. (2006). Rhythms of the brain. London: Oxford University Press.

Corless M. (2011). Introduction to dynamic systems. Indiana: Purdue University.

Díaz H, Córdova F, Cañete L, Palominos F, Cifuentes F, Sánchez C, et al. (2015). Order and chaos in the brain: fractal time series analysis of the EEG activity during a cognitive problem solving task. Procedia Computer Science, 55: pp. 1410-1419. https://doi.org/10.1016/j.procs.2015.07.135

Díaz H, Maureira F, Cohen E, Córdova F, Palominos F, Otárola J, et al. (2015). Individual differences in the order/chaos balance of the brain selforganization. Annals of Data Science, 2(3): pp. 1-18. https://doi.org/10.1016/j.procs.2017.11.378

Díaz H, Maureira F, Flores G, Fuentes I, García F, Maertens P, et al. (2018). Moving correlations and chaos in the brain during closed eyes basal conditions. Procedia Computer Science, 139: pp. 473-480. https://doi.org/10.1016/j.procs.2018.10.248

Díaz H, Maureira F, Córdova F. (2018). Times series of closed and open eyes EEG conditions reveal differential characteristics in the temporality of linear and no-linear analysis domain. Procedia Computer Science,139: pp. 570-577. https://doi.org/10.1016/j.procs.2018.10.208

Díaz H, Maureira F, Flores E, Córdova F. (2018). Intra e inter-hemispheric correlation of the order/chaos fluctuation in the brain activity during a motor imagination task. Procedia Computer Science, 139: pp. 456-463. https://doi.org/10.1016/j.procs.2018.10.250

Díaz H, Maureira F, Flores E, Cifuentes H, Córdova F. (2019). Synchronizing oscillatory chaos in the brain. Procedia Computer Science, 162: pp. 982-989. https://doi.org/10.1016/j.procs.2019.12.076

Díaz H, Maureira F, Flores E, Gárate E, Muñoz S. (2019). Intra and inter-individual variability in the chaotic component and functional connectivity of the EEG signal in basal closed eyes condition. Procedia Computer Science, 162: pp. 966-973. https://doi.org/10.1016/j.procs.2019.12.077

Díaz H, Maureira F, Otárola J, Rojas R, Alarcón O, Cañete L. (2019). EEG Beta band frequency domain evaluation for assessing stress and anxiety in resting, eyes closed, basal conditions. Procedia Computer Science, 162: pp. 974-981.

Kumar J, Bhuvaneswari P. (2012). Analysis of electroencephalography (EEG) signals and its categorization-a study. Procedia Engineering, 38: pp. 2525-2536. https://doi.org/10.1016/j.proeng.2012.06.298

Layek G. (2015). An introduction to dynamical system and chaos. New York: Springer.

Maureira F. (2017) ¿Qué es la inteligencia? 1° ed. Madrid: Bubok Publishing.

Maureira F, Flores F. (2018). Electroencefalografía (EEG) y diversas manifestaciones del movimiento: una revisión del 2000 al 2017. EmásF, Revista Digital de Educación Física, 9(51): pp. 48-63.

Michel C, Murray M. (2012) Towards the utilization of EEG as a brain imaging tool. NeuroImage, ; 61(2): pp. 371-385. https://doi.org/10.1016/j.neuroimage.2011.12.039

Montero F, Moran F. (1992). Biofísica: procesos de auto-organización en biología. Madrid: EUDEMA.

Pikovsky A, Rosenblum M, Kurths J. (2001). Synchronization: a universal concept in nonlinear sciences. 1° ed. Cambridge: Cambridge University Press.

Raimundo M, Okamoto J. (2018). Application of Hurst Exponent (H) and the R/S analysis in the classification of FOREX Securities. International Journal of Modeling and Optimization, 8(2): pp. 116-124. https://doi.org/10.7763/ijmo.2018.v8.635

World Medical Asociation. (2013). World Medical Association Declaration of Helsinki Ethical Principles for Medical Research Involving Human Subjects. JAMA, 310(20): pp. 2191-2194.

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