SPATIO-TEMPORAL DYNAMICS OF BRAIN ELECTRICAL ACTIVITY IN EPILEPSY: ANALYSIS WITH CELLULAR NEURAL NETWORKS (CNNs)

摘要

In this contribution a new procedure is proposed for the analysis of the spatio-temporal dynamics of brain electrical activity in epilepsy. Recent investigations have clarified that changes of estimates of the effective correlation dimension D_2 (k, m) from successive data segments allow a characterization of the epileptogenic process. These results provide important information for diagnostical purposes and enable a prediction of seizures in many cases. It will be shown that an accurate approximation of D_2~*(k, m) can be obtained by Cellular Neural Networks (CNNs), which form a unified paradigm. Moreover, the type of CNN presented here is optimized with respect to future implementations as VLSI realizations.