Recent Advances in Predicting and Preventing Epileptic Seizures Edited by Ronald Tetzlaff, Christian E. Elgar and Klaus Lehnertz (290 pages, Publisher: World Scientific Publishing Co Pte Ltd)

This book is an ideal way for clinicians and researchers in epileptology to update themselves about current concepts and knowledge of pathophysiological seizure generation mechanisms and ongoing developments in seizure prediction strategies. The book especially highlights the importance of multidisciplinary teamwork involving experts in the neurosciences, mathematics, physics, and engineering (especially complex signal processing), if progress toward seizure prediction and prevention is to be made. The initial chapter addresses the current concept of what an epileptic network is and explains the differences in the mechanisms underlying interictal spikes and pre-ictal spiking during critical state transition into seizures. A candid summary of the current state of knowledge about deep brain stimulation for intractable epilepsy and description of all potential stimulation sites and parameters is provided. The book goes on to produce an overview of the current principles of computer modeling of seizures and epilepsy. Both stochastic and deterministic approaches are explained. The first ever online estimation of neural mass model parameters in terms of excitatory and inhibitory synaptic strength estimation of a seizure recorded using ECoG in a patient with epilepsy is presented. The spatiotemporal modeling of microseizures from a mesoscale of cortical sheet is described, and the influence of different neuronal dynamics and network topology (lattice vs. small world vs. random type) on global synchrony is explained with great clarity. Great emphasis is given to the contributions that signal processing techniques can make toward the understanding of neural network functioning in epilepsy with particular relevance to pathophysiology and early seizure detection or prediction. Seminal works from in vitro network analyses based on animal models as well as in vivo analyses of human epileptic patients examined with intracranial EEG recordings are presented and discussed in detail. All sections highlight the findings of clinical