Publicación:
Estabilidad de correlaciones de la actividad eléctrica no-lineal del cerebro en reposo con ojos cerrados

Vista sencilla de ítem
dc.contributor.authorMaureira Cid, Fernandospa
dc.contributor.authorDíaz-Muñoz , Hernánspa
dc.contributor.authorHadweh-Briceño, Marcelospa
dc.contributor.authorFlores-Ferro, Elizabethspa
dc.contributor.authorSilva-Salse , Ángelaspa
dc.date.accessioned2020-12-31 14:30:36
dc.date.accessioned2022-06-17T20:21:01Z
dc.date.available2020-12-31 14:30:36
dc.date.available2022-06-17T20:21:01Z
dc.date.issued2020-12-31
dc.description.abstractIntroducción: la señal del EEG suele interpretarse desde una mirada lineal, sin embargo, desde hace algunas décadas se estudia la actividad eléctrica cerebral como un sistema dinámico, basado en la teoría del caos, con matemáticas no lineales. Objetivo: analizar la estabilidad de las correlaciones de los índices de Hurst a través del tiempo en sujetos en reposo con los ojos cerrados. Métodos: se evaluaron 13 varones universitarios con el dispositivo cerebro-interfaz Emotiv Epoc® con frecuencia de muestreo de 128 Hz. Se analizaron los rangos de frecuencia delta (1-3 Hz), theta (3,5-7 Hz), alfa (8-12 Hz), beta (13-30 Hz) y gamma (>30 Hz). Resultados: los resultados muestran estabilidad en el porcentaje de correlaciones en todas las bandas estudiadas en la mayoría de los sujetos. esta situación ocurre en ventanas temporales de 10, 30 y 60 segundos. Conclusiones: este estudio exploratorio muestra la persistencia en el tiempo de procesos meta-sincrónicos no-lineales que obedecen a la dinámica del balance caos/orden global del cerebro, en condiciones de reposo, basal con ojos cerrados.spa
dc.description.abstractIntroduction: 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.eng
dc.format.mimetypeapplication/pdfspa
dc.identifier.doi10.24050/reia.v18i35.1463
dc.identifier.eissn2463-0950
dc.identifier.issn1794-1237
dc.identifier.urihttps://repository.eia.edu.co/handle/11190/5133
dc.identifier.urlhttps://doi.org/10.24050/reia.v18i35.1463
dc.language.isospaspa
dc.publisherFondo Editorial EIA - Universidad EIAspa
dc.relation.bitstreamhttps://revistas.eia.edu.co/index.php/reveia/article/download/1463/1382
dc.relation.citationeditionNúm. 35 , Año 2021spa
dc.relation.citationendpage13
dc.relation.citationissue35spa
dc.relation.citationstartpage35006 pp. 1
dc.relation.citationvolume18spa
dc.relation.ispartofjournalRevista EIAspa
dc.relation.referencesBassingthwaighte J, Raymond G. (1994). Evaluating rescaled range analysis for time series. Annals of Biomedical Engineering, 2(4): pp. 432-444.spa
dc.relation.referencesBear M, Connors B, Paradiso M. (2016) Neurociencia, la exploración del cerebro. 4° ed. Madrid: Wolters Kluver.spa
dc.relation.referencesBuzsaki G. (2006). Rhythms of the brain. London: Oxford University Press.spa
dc.relation.referencesCorless M. (2011). Introduction to dynamic systems. Indiana: Purdue University.spa
dc.relation.referencesDíaz 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.2015.07.135spa
dc.relation.referencesDíaz 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.2017.11.378spa
dc.relation.referencesDíaz 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.2018.10.248spa
dc.relation.referencesDíaz 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.2018.10.208spa
dc.relation.referencesDíaz 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.2018.10.250spa
dc.relation.referencesDíaz 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.2019.12.076spa
dc.relation.referencesDíaz 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.2019.12.077spa
dc.relation.referencesDíaz 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.spa
dc.relation.referencesKumar 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.2012.06.298spa
dc.relation.referencesLayek G. (2015). An introduction to dynamical system and chaos. New York: Springer.spa
dc.relation.referencesMaureira F. (2017) ¿Qué es la inteligencia? 1° ed. Madrid: Bubok Publishing.spa
dc.relation.referencesMaureira 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.spa
dc.relation.referencesMichel 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.2011.12.039spa
dc.relation.referencesMontero F, Moran F. (1992). Biofísica: procesos de auto-organización en biología. Madrid: EUDEMA.spa
dc.relation.referencesPikovsky A, Rosenblum M, Kurths J. (2001). Synchronization: a universal concept in nonlinear sciences. 1° ed. Cambridge: Cambridge University Press.spa
dc.relation.referencesRaimundo 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.v8.635spa
dc.relation.referencesWorld Medical Asociation. (2013). World Medical Association Declaration of Helsinki Ethical Principles for Medical Research Involving Human Subjects. JAMA, 310(20): pp. 2191-2194.spa
dc.rightsRevista EIA - 2020spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
dc.rights.creativecommonsEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.spa
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0spa
dc.sourcehttps://revistas.eia.edu.co/index.php/reveia/article/view/1463spa
dc.subjectelectroencefalografíaspa
dc.subjectexponente de Hurstspa
dc.subjectcorrelacionesspa
dc.subjectestado basalspa
dc.subjectelecroencephalohraphyeng
dc.subjecthurst indexeng
dc.subjectcorrelationseng
dc.subjectbaseline statuseng
dc.titleEstabilidad de correlaciones de la actividad eléctrica no-lineal del cerebro en reposo con ojos cerradosspa
dc.title.translatedStability of correlations of non-linear electrical activity of the resting brain with closed eyeseng
dc.typeArtículo de revistaspa
dc.typeJournal articleeng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTREFspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
dspace.entity.typePublication
Archivos
Colecciones
Revista EIA (Portal de Revistas)