Epilepsy and Nonlinear Dynamics

Abstract

This overview summarizes findings obtained from analyzing electroencephalographic (EEG) recordings from epilepsy patients with methods from the theory of nonlinear dynamical systems. The last two decades have shown that nonlinear time series analysis techniques allow an improved characterization of epileptic brain states and help to gain deeper insights into the spatial and temporal dynamics of the epileptic process. Nonlinear EEG analyses can help to improve the evaluation of patients prior to neurosurgery, and with an unequivocal identification of precursors of seizures, they can be of great value in the development of seizure warning and prevention techniques.

Detection and Prediction of Absence Seizures Based on Nonlinear Analysis of the EEG in Wag/Rij Animal Model

“…Proposed geometric properties can be calculated in accordance with equation (1) to the trajectory x (t) in dimension d. In practice, all d states are not accessible in the phase space, and only the vector of observations x (t) is available. 30 seizures with dynamic EEG changes in people with absence epilepsy is still open problem 16,17 . Additionally, understanding the transition of brain activity to epileptic seizures and the identification of some pioneering tasks is challenging 8,9 .…”

“…A variety of new concepts and time series analysis techniques have been developed to allow the description of the behavioral dynamics of the system for an indefinite system. Proposed geometric properties can be calculated in accordance with equation (1) to the trajectory x (t) in dimension d. In practice, all d states are not accessible in the phase space, and only the vector of observations x (t) is available 30 .…”

Effects of Speech Phonological Features during Passive Perception on Cortical Auditory Evoked Potential in Sensorineural Hearing Loss

“…Several non-linear methods presented by previous researchers including sample entropy (SampEnt), higher order spectra (HOS), fractal dimension (FD) and recurrent quantification analysis (RQA) provide a better and valuable mechanism for result interpretation (Acharya et al 2015(Acharya et al , 2011Chua et al 2011Chua et al , 2009. For the last two decades, more exploration was conducted using nonlinear dynamic method in giving potential understanding as this technique extracts hidden complexity in the time series brain signal (Lehnertz 2008;Mormann et al 2005Mormann et al , 2003. According to Acharya et al (2013), higher order spectra (HOS) method is considered as one of powerful mechanisms to justify the presence of abnormalities, besides usefulness in the event of signal distortion due to Gaussian noise.…”

Permutation Entropy Applied to the Characterization of the Clinical Evolution of Epileptic Patients under PharmacologicalTreatment

“…Several works have been devoted to quantifying the therapeutic effects of drugs from the analysis of EEG records by means of quantities arising in the theory of nonlinear systems [10]. One of these quantities is permutation entropy (PE).…”