Assessing Brain Pathophysiology through Non-Linear Analysis of MEG in Ιdiopathic Generalized Epilepsy Cases


Background: Non-linear signal analysis has proven to be a technique that is capable of revealing qualitative and quan- titative differentiations between different dynamical systems (biological or otherwise). In the present work it has been demonstrated that this capability reveals quantitative differences in the Magnetoencephalograms (MEG) received from patients with Idiopathic Generalized Epilepsy (IGE) and from healthy volunteers. Method: We present MEG record- ings of 10 epileptic patients with IGE and the corresponding ones from 10 healthy volunteers. A 122-channel SQUID biomagnetometer in an electromagnetically shielded room was used to record the MEG signals and the Grassber- ger-Procaccia method for the estimation of the correlation dimension was applied in the phase space reconstruction of the recorded signal from each patient. Results: The aforementioned analysis demonstrates the existence of spatially diffused low dimensionality in the MEG signals of patients with IGE. Conclusion: The obtained results provide support for the hypothesis that low dimensionality in MEG signals is linked to functional brain pathogeny.

Share and Cite:

P. Antoniou, A. Adamopoulos, P. Anninos, H. Piperidou and A. Kotini, "Assessing Brain Pathophysiology through Non-Linear Analysis of MEG in Ιdiopathic Generalized Epilepsy Cases," Journal of Behavioral and Brain Science, Vol. 2 No. 4, 2012, pp. 445-453. doi: 10.4236/jbbs.2012.24052.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] A. Kotini and P. Anninos, “Detection of Non-Linearity in Schizophrenic Patients Using Magnetoencephalography,” Brain Topography, Vol. 15, No. 2, 2002, pp. 107-113. Hdoi:10.1023/A:1021420507901
[2] P. A. Anninos, A. V. Adamopoulos, A. Kotini and N. Tsagas, “Nonlinear Analysis of Brain Activity in Magnetically Influenced Parkinson’s Patients,” Brain Topography, Vol. 13, No. 2, 2000, pp. 135-144. Hdoi:10.1023/A:1026611219551
[3] P. Antoniou, P. A. Anninos, H. Piperidou, A. Adamopoulos, A. Kotini, M. Koukourakis and E. Sivridis, “Non-Linear Analysis of Magnetoencephalographic Signals as a Tool for Assessing Malignant Lesions of the Brain: First Results,” Brain Topography, Vol. 17, No. 2, 2004, pp. 117- 123. Hdoi:10.1007/s10548-004-1009-0H
[4] D. F. Rose, P. D. Smith and S. Sato, “Magnetoencephalography and Epilepsy Research,” Science, Vol. 238, No. 4825, 1987, pp. 329-335. Hdoi:10.1126/science.3310234H
[5] P. Anastasiadis, Ph. Anninos and E. Sivridis, “Biomagnetic Activity in Breast Lesions,” The Breast, Vol. 3, No. 3, 1994, pp. 177-180. Hdoi:10.1016/0960-9776(94)90072-8H
[6] P. A. Anninos, G. Anogianakis, G. Lehnertz, C. H. Pantev and M. Hoke, “Biomagnetic Measurements Using Squids,” International Journal of Neuroscience, Vol. 37, No. 3-4, 1987, pp. 149-168. Hdoi:10.3109/00207458708987144H
[7] J. P. Eckmann and D. Ruelle, “Ergodic Theory of Chaos and Strange Attractors,” Reviews of Modern Physics, Vol. 57, No. 3, 1985, pp. 617-656. Hdoi:10.1103/RevModPhys.57.617
[8] P. E. Rapp, “Is There Evidence for Chaos in the Human Central Nervous System,” In: R. Robertson and A. Combs, Eds., Chaos Theory in Psychology and the Life Sciences, Lawrence Erlbaum Associates, Mahwah, 1995, pp. 89-102.
[9] R. A. Hrachovy and J. D. Frost Jr., “The EEG in Selected Generalized Seizures,” Journal of Clinical Neurophysiology, Vol. 23, No. 4, 2006, pp. 312-332. Hdoi:10.1097/01.wnp.0000228496.66246.e0
[10] P. Grassberger and I. Procaccia, “Characterization of Strange Attractors,” Physical Review Letters, Vol. 50, No. 5, 1983, pp. 346-349. Hdoi:10.1103/PhysRevLett.50.346
[11] P. Grassberger and I. Procaccia, “Measuring the Strangeness of Strange Attractors,” Physica D: Nonlinear Phenomena, Vol. 9, No. 1-2, 1983, pp. 189-208. Hdoi:10.1016/0167-2789(83)90298-1
[12] P. A. Anninos, N. Tsagas, R. Sandyk and K. Derpapas, “Magnetic Stimulation in the Treatment of Partial Seizures,” International Journal of Neuroscience, Vol. 60, No. 3-4, 1991, pp. 141-171. Hdoi:10.3109/00207459109167029
[13] C. H. Elger, M. Hoke, K. Lehnertz, C. Pantev, B. Lutkenhoner, P. A. Anninos, et al., “Mapping of MEG Amplitude Spectra, Its Significance for the Diagnosis of Focal Epilepsy,” In: K. Maurer, Ed., Topographic Brain Mapping of EEG and Evoked Potentials, Spinger Verlag, Berlin, 1989, pp. 565-570. Hdoi:10.1007/978-3-642-72658-3_59
[14] B. D. Josephson, “Possible Effects in Superconducting Tunneling,” Physics Letters, Vol. 1, No. 7, 1962, pp. 252- 256. Hdoi:10.1016/0031-9163(62)91369-0H
[15] F. Takens, “Detecting Strange Attractors in the Turbulence,” In: D. A. Rand and L. S. Young, Eds., Lecture Notes in Mathematics, Springer, Berlin, 1981, pp. 366-381.
[16] C. J. Stam, B. Jelles, H. A. Achtereekte, S. A. Rombouts, J. P. Slaets and R. W. Keunen, “Investigation of EEG Non- Linearity in Dementia and Parkinson’s Disease,” Electroencephalography and Clinical Neurophysiology, Vol. 95, No. 5, 1995, pp. 309-317. Hdoi:10.1016/0013-4694(95)00147-Q
[17] Y. J. Lee, Y. S. Zhu, Y. H. Xu, M. F. Shen, H. X. Zhang and N. V. Thakor, “Detection of Non-Linearity in the EEG of Schizophrenic Patients,” Clinical Neurophysiology, Vol. 112, No. 7, 2001, pp. 1288-1294. Hdoi:10.1016/S1388-2457(01)00544-2H
[18] C. Gómez, R. Hornero, D. Abásolo, A. Fernández and M. López, “Complexity Analysis of the Magnetoencephalogram Background Activity in Alzheimer’s Disease Patients,” Medical Engineering & Physics, Vol. 28, No. 9, 2006, pp. 851-859. Hdoi:10.1016/j.medengphy.2006.01.003
[19] C. Gómez, A. Mediavilla, R. Hornero, D. Abásolo and A. Fernández, “Use of the Higuchi’s Fractal Dimension for The Analysis of MEG Recordings from Alzheimer’s Disease Patients,” Medical Engineering & Physics, Vol. 31, No. 3, 2009, pp. 306-313. Hdoi:10.1016/j.medengphy.2008.06.010
[20] P. Bob, J. Chladek, M. Susta, K. Glaslova, F. Jagla and M. Kukleta, “Neural Chaos and Schizophrenia,” General Physiology and Biophysics, Vol. 26, No. 2007, pp. 298-305.
[21] P. Bob, M. Susta, J. Chladek, K. Glaslova and M. Palus “Chaos in Schizophrenia Associations, Reality or Metaphor?” International Journal of Psychophysiology, Vol. 73, No. 3, 2009, pp. 179-185. Hdoi:10.1016/j.ijpsycho.2008.12.013
[22] D. Kernick, “Migraine—New Perspectives from Chaos Theory,” Cephalalgia, Vol. 25, No. 8, 2005, pp. 561-566. Hdoi:10.1111/j.1468-2982.2005.00934.xH
[23] N. C. Bentzen, A. M. Zhabotinsky and J. L. Laugesen, “Modeling of Glutamate-Induced Dynamical Patterns,” International Journal of Neural Systems, Vol. 19, No. 6, 2009, pp. 395-407. Hdoi:10.1142/S0129065709002105
[24] M. Hutchinson and P. D. Swanson, “Chaos Theory and the Treatment of Refractory Status Epilepticus: Who Benefits from Prolonged Anesthesia, and Is There a Better Way?” Medical Hypotheses, Vol. 68, No. 2, 2007, pp. 439- 441. Hdoi:10.1016/j.mehy.2006.07.025H
[25] W. S. Pritchard, K. K. Krieble and D. W. Duke, “On the Validity of Estimating EEG Correlation Dimension from a Spatial Embedding,” Psychophysiology, Vol. 33, No. 4, 1996, pp. 362-368. Hdoi:10.1111/j.1469-8986.1996.tb01060.x
[26] H. Stefan, A. Paulini-Ruf, R. Hopfeng?rtner and S. Rampp, “Network Characteristics of Idiopathic Generalized Epilepsies in Combined MEG/EEG,” Epilepsy Research, Vol. 85, No. 2, 2009, pp. 187-198. Hdoi:10.1016/j.eplepsyres.2009.03.015
[27] A. Kotini, N. Koutlaki, P. Anninos, A. Adamopoulos, V. Liberis and P. Anastasiadis,” Biology of the Neonate, Vol. 84, No. 2003, pp. 214-221. Hdoi:10.1159/000072305
[28] J. Theilert, S. Eubank, A. Longtin, B. Galdrikian and J. D. Farmer, “Testing for Non-Linearity in Time Series: The Method of Surrogate Data,” Physica D: Nonlinear Phenomena, Vol. 58, No. 1-4, 1992, pp. 77-94. Hdoi:10.1016/0167-2789(92)90102-SH.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.