Abstract
In this work MagnetoEncephaloGram (MEG) recordings of epileptic patients are modeled using a genetic programming approach. This is the first time that genetic programming is used to model MEG signal. Numerous experiments were conducted giving highly successful results. It is demonstrated that genetic programming can produce very simple nonlinear models that fit with great accuracy the observed data of MEG.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Arbib M. (2003), The Handbook of Brain Theory and Neural Networks, MIT Press, Cambridge, MA.
Niedermeyer E., and Lopes da Silva F. (2004), Electroencephalography: Basic Principles, Clinical Applications, and Related Fields, Lippincott Williams & Wilkins, Philadelphia, PA.
Stam C.J. (2005), Nonlinear dynamical analysis of EEG and MEG: Review of an emerging field, Clinical Neurophysiology, 116(10): 2266–2301.
Dassios G., Fokas A.S., and Hadjiloizi D. (2007), On the complementarity of EEG and MEG, Inverse Problems, 23(6): 2541–2549.
Anninos P.A., Tsagas N., and Adamopoulos A. (1989), A brain model theory for epilepsy and its treatment: experimental verification using SQUID measurements. In Cotterill, R.M.J. (ed.) Models of Brain Function, Cambridge University Press, Cambridge, pp. 405–422.
Jouny C.C., Frabaszczuk P.L., and Bergey G.K., Complexity-based analysis of the dynamic of propagation of epileptic seizures, 2nd International IEEE EMBS Conference on Neural Engineering Proceedings, pp. 155–157.
Tsoutsouras V.G., Iliopoulos A.C., and Pavlos G.P. (2006), Non-linear analysis and modelling of EEG in patients with epilepsy, 19th Panhellenic Conference on Nonlinear Science and Complexity, July 10–22, Thessaloniki, Greece.
Adamopoulos A., Pavlos G., Anninos P., Tsitsis D., and Rigas A. (1991), Chaotic analysis of biomagnetic measurements of human brain, NATO ASI on Chaotic Synamics – Theory and Practice, July, 11–20, Patras, Greece, 1991.
Adamopoulos A.V. (2006), Intelligent adaptive modelling and identification of MEG of epileptic patients, WSEAS Transactions on Biology and Biomedicine, 3(2): 69–76.
Koza J.R. (1990), A genetic approach to econometric modeling, Sixth World Congress of the Econometric Society, Barcelona, Spain, August 27.
Koza J.R. (1992),Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, Cambridge, MA.
Koza J.R. (1998), Genetic programming. In: Williams, J. G. and Kent, A. (eds.) Encyclopedia of Computer Science and Technology, New York, NY: Marcel-Dekker, 39(24): 29–43.
Banzhaf W.P., Nordin P., Keller R.E., and Francone F.D. (1998). Genetic Programming: An Introduction, Kaufmann, San Mateo, CA.
Adamopoulos A., Anninos P., Likothanassis S., and Georgopoulos E. (1998), On the predictability of MΕG of epileptic patients using RBF networks evolved with genetic algorithms, BIOSIGNAL’98, Brno, Czech Republic, June 23–25.
Adamopoulos A., Georgopoulos G., Likothanassis S., and Anninos P. (1999), Forecasting the Magnetoengaphalogram (MEG) of epileptic patient using genetically optimized neural networks, Genetic and Evolutionary Computation Conference (GECCO’99), Orlando, Florida, USA, July 14–17.
Adamopoulos A., Georgopoulos E., and Likothanassis S. (2004), Evolutionary neural networks for timeseries prediction, WSEAS Transactions on Biology and Biomedicine, 1(1): 137–147.
Likothanassis S., Georgopoulos E., and Adamopoulos A. (2000), Structure determination and training of neural networks using evolution programs, Neural, Parallel and Scientific Computations Journal, 8(1): 29–48
Adamopoulos A., and Anninos P. (1993), Application of chaotic dynamics data analysis methods on the MEG of epileptic and parkinsonian patients, in order to evaluate their improvement using external magnetic fields, Biophysical Journal 64(2), Part 2. Abstracts of 37th Annual Meeting of the Biophysical Society.
Anninos P., Kotini A., Adamopoulos A., and Tsagas N. (2003), Magnetic stimulation can modulate seizures in epileptic patients, Brain Topography, 16(1): 57–64.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Georgopoulos, E.F., Adamopoulos, A.V., Likothanassis, S.D. (2009). Genetic Programming Modeling and Complexity Analysis of the Magnetoencephalogram of Epileptic Patients. In: Papadopoulos, G., Wojtkowski, W., Wojtkowski, G., Wrycza, S., Zupancic, J. (eds) Information Systems Development. Springer, Boston, MA. https://doi.org/10.1007/b137171_40
Download citation
DOI: https://doi.org/10.1007/b137171_40
Published:
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-84809-9
Online ISBN: 978-0-387-84810-5
eBook Packages: Computer ScienceComputer Science (R0)