Changes of brain electric activity nonlinear dynamics brain electric activity in girls with visual dysfunction

I. V. Redka, O. Yu. Mayorov

Abstract


An assessment of neural systems of the brain of girls with visual dysfunctions (congenital and acquired) and sighted girls has been examined by methods of nonlinear analysis in resting state with eyes closed. We studied embedding dimension, correlation dimension, the maximum Lyapunov exponent and Kolmogorov-Sinai entropy. It has been found that the visual dysfunction lead to brain functionality reorganization in girls at 8 to 12 age during resting-state with eyes closed. This changes has been dependent in acquisition time of visual dysfunctions and visual acuity.  The changes in neurodynamics of ventrolateral prefrontal cortex are characteristic features in congenital visual dysfunctions compared with control and acquired visual dysfunctions. Generalized increase in the level of chaos in the brain electrical activity is a characteristic feature of neurodynamics in acquired visual dysfunctions. The changes in neurodynamics of temporal areas in visual dysfunctions may reflect changes in the activity of auditory perceptual system. Nonlinear analysis techniques  provide additional information  of  brain neurodynamics systems during normal and pathological conditions.

Keywords


EEG; nonlinear dynamics; visual dysfunction girls

References


Майоров О.Ю. Реализация метода смещения с помощью оценки размеров осей аттрактора динамической системы мозга / Майоров О.Ю., Глухов А.Б., Фенченко В.Н. // Кибернетика и вычислительная техника. – 2007. – Вып. 153. – С. 3 – 11.

Майоров О.Ю. Исследование биоэлектрической активности мозга с позиций многоразмерного линейного и нелинейного анализа ЭЭГ / О.Ю. Майоров, В.Н. Фенченко // Ж. Клиническая информатика и телемедицина. – 2008. – Т. 4, Вып. 5. – С. 12 – 20.

Burton H. Resting state functional connectivity in early blind humans / H. Burton, A. Z. Snyder, M. E. Raichle // Frontiers in Systems Neuroscience. – 2014. – Vol. 8, Article 51. – 13 p.

Beauchamp M.S. Touch, sound and vision in human superior temporal sulcus / Beauchamp M.S., Yasar N.E., Frye R.E., Ro T. // Neuroimage. – 2008. – Vol. 41 (3). – P. 1011–1020.

Calvert G.A. Evidence from functional magnetic resonance imaging of crossmodal binding in the human heteromodal cortex / Calvert G.A., Campbell R., Brammer M.J. // Curr Biol. – 2000. – Vol. 10 (11). – P. 649–657.

Corbetta M. Control of goal-directed and stimulus-driven attention in the brain / Corbetta M., Shulman G.L. // Nature Reviews Neuroscience. – 2002. – Vol. 3 (3). – P. 201–215.

Goldberger A.L. What is physiologic complexity and how does it change with aging and disease? / Goldberger A.L., Peng C., Lipsitz L.A. // Neurobiol.Aging. – 2002. – Vol. 23 (1). – P. 23–26.

Hosseinifard B. Classifying depression patients and normal subjects using machine learning techniques and nonlinear features from EEG signal / Hosseinifard B., Moradi M.H., Rostami R. // Comput. Methods Programs Biomed. – 2013. – Vol. 109 (3). – P. 339 – 345.

Lainscsek C. Non-Linear Dynamical Analysis of EEG Time Series Distinguishes Patients with Parkinson’s Disease from Healthy Individuals/ Claudia Lainscsek, Manuel E. Hernandez, Jonathan Weyhenmeyer, Terrence J. Sejnowski, Howard Poizner // Front Neurol. – 2013. – Vol. 4, article 200. – 8 p.

Leporé N. Brain Structure Changes Visualized in Early- and Late-Onset Blind Subjects / N. Leporé, P. Voss, F. Lepore et al. // Neuroimage. – 2010. – Vol. 49 (1). – P. 134–140.

Mayorov O. Yu. New neurodiagnostics technology for brain research on the basis of multivariate and nonlinear (deterministic chaos) analysis of an EEG / Mayorov O. Yu., Fritzsche M., Glukhov A.B. et al. // Achievements in space medicine into health care practice and industry: Proceedings of 2nd European Congress. – Berlin: Pabst Science Publ., 2003. – P. 157 – 166.

McDonough I.M. Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project / I.M. McDonough, K. Nashiro // Front Hum Neurosci. – 2014. – Vol. 8, Article 409. – 15 p.

Noppeney U. Early visual deprivation induces structural plasticity in gray and white matter / Noppeney U., Friston K.J., Ashburner J., Frackowiak R., Price C.J // Curr. Biol. – 2005. – Vol. 15 (13). – P. 488–490.

Pool R. Is it healthy to be chaotic? / Pool R. // Science. – 1989. – Vol. 243 (4891). – P. 604–607.

Sokunbi M.O. Inter-individual differences in fMRI entropy measurements in old age / Sokunbi M.O., Staff R.T., Waiter G.D. et al. // IEEE Trans.Biomed.Eng. – 2011. – Vol. 58 (1), 3206–3214.

Sokunbi M.O. Resting state fMRI entropy probes complexity of brain activity in adults with ADHD / Sokunbi M.O., Fung W., Sawlani V. et al. // Psychiatry Res. – 2013. – Vol. 214 (3). – P. 341–348.

Vossel S. Dorsal and Ventral Attention Systems: Distinct Neural Circuits but Collaborative Roles / Simone Vossel, Joy J. Geng and Gereon R. Fink // Neuroscientist. – 2014. – Vol. 20 (2). – P. 150–159.

Wang D. Altered resting-state network connectivity in congenital blind / D. Wang, W. Qin, Y. Liu et al. // Human Brain Mapping. – 2014. – Vol. 35 (6). – P. 2573–2581.


Full Text: PDF (Українська)

Refbacks

  • There are currently no refbacks.
Archive
2014 2 36
2015 2 19
2016 1 2
2017 1 2
2018 1 2
2019 1 2

Requirements for registration of articles

User

Information

Journal Content

Browse

Language