Modeling brain electrical activity in epilepsy by reaction-diffusion cellular neural networks

Reaction-Diffusion systems can be applied to describe a broad class of nonlinear phenomena, in particular in biological systems and in the propagation of nonlinear waves in excitable media. Especially, pattern formation and chaotic behavior are observed in Reaction-Diffusion systems and can be analyzed. Due to their structure multi-layer Cellular Neural Networks (CNN) are capable of representing Reaction-Diffusion systems effectively. In this contribution Reaction-Diffusion CNN are considered for modeling dynamics of brain activity in epilepsy. Thereby the parameters of Reaction-Diffusion systems are determined in a supervised optimization process, and brain electrical activity using invasive multi-electrode EEG recordings is analyzed with the aim to detect of precursors of impending epileptic seizures. A detailed discussion of first results and potentiality of the proposed approach will be given.

[1]  Ronald Tetzlaff,et al.  Modeling nonlinear systems with cellular neural networks , 1996, 1996 IEEE International Conference on Acoustics, Speech, and Signal Processing Conference Proceedings.

[2]  C. Elger,et al.  CAN EPILEPTIC SEIZURES BE PREDICTED? EVIDENCE FROM NONLINEAR TIME SERIES ANALYSIS OF BRAIN ELECTRICAL ACTIVITY , 1998 .

[3]  R. Tetzlaff,et al.  A learning algorithm for cellular neural networks (CNN) solving nonlinear partial differential equations , 1995, Proceedings of ISSE'95 - International Symposium on Signals, Systems and Electronics.

[4]  R. Tetzla.  SCNN 2000 - Part I: Basic Structure and Features of the Simulation System for Cellular Neural Networks , 2000 .

[5]  H. Schwan,et al.  Biological Engineering , 1970 .

[6]  Leon O. Chua,et al.  Edge of Chaos and Local Activity Domain of FitzHugh-Nagumo Equation , 1998 .

[7]  Lin-Bao Yang,et al.  Cellular neural networks: theory , 1988 .

[8]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[9]  A. Loncar,et al.  SCNN 2000. I. Basic structure and features of the simulation system for cellular neural networks , 2000, Proceedings of the 2000 6th IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA 2000) (Cat. No.00TH8509).

[10]  Mika Laiho,et al.  Mixed-mode cellular array processor realization for analyzing brain electrical activity in epilepsy , 2003 .

[11]  Leon O. Chua,et al.  CNN: A Vision of Complexity , 1997 .

[12]  Ronald Tetzlaff,et al.  Prediction of brain electrical activity in epilepsy using a higher-dimensional prediction algorithm for discrete time cellular neural networks (DTCNN) , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[13]  Ronald Tetzlaff,et al.  Nonlinear prediction of brain electrical activity in epilepsy with a Volterra RLS algorithm , 2002, 2002 IEEE International Symposium on Circuits and Systems. Proceedings (Cat. No.02CH37353).

[14]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .