Estimating Generalized Synchronization in Brain Electrical Activity from Epilepsy Patients with Cellular Nonlinear Networks

We present a method for estimating the degree of generalized synchronization between long-lasting multichannel recordings of brain electrical activity from epilepsy patients. Using the nonlinear interdependency measure N as an estimator for generalized synchronization and the parallel computing power of a cellular nonlinear network (CNN) with polynomial-type template functions we show that an accurate approximation of N, detecting changes over several days, is possible

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