Comparative study of nonlinear properties of EEG signals of a normal person and an epileptic patient

Background: Investigation of the functioning of the brain in living systems has been a major effort amongst scientists and medical practitioners. Amongst the various disorder of the brain, epilepsy has drawn the most attention because this disorder can affect the quality of life of a person. In this paper we have reinvestigated the EEGs for normal and epileptic patients using surrogate analysis, probability distribution function and Hurst exponent. Results: Using random shuffled surrogate analysis, we have obtained some of the nonlinear features that was obtained by Andrzejak \textit{et al.} [Phys Rev E 2001, 64:061907], for the epileptic patients during seizure. Probability distribution function shows that the activity of an epileptic brain is nongaussian in nature. Hurst exponent has been shown to be useful to characterize a normal and an epileptic brain and it shows that the epileptic brain is long term anticorrelated whereas, the normal brain is more or less stochastic. Among all the techniques, used here, Hurst exponent is found very useful for characterization different cases. Conclusions: In this article, differences in characteristics for normal subjects with eyes open and closed, epileptic subjects during seizure and seizure free intervals have been shown mainly using Hurst exponent. The H shows that the brain activity of a normal man is uncorrelated in nature whereas, epileptic brain activity shows long range anticorrelation.Comment: Keywords:EEG, epilepsy, Correlation dimension, Surrogate analysis, Hurst exponent. 9 page

Nonlinear analysis of EEG signals at different mental states

BACKGROUND: The EEG (Electroencephalogram) is a representative signal containing information about the condition of the brain. The shape of the wave may contain useful information about the state of the brain. However, the human observer can not directly monitor these subtle details. Besides, since bio-signals are highly subjective, the symptoms may appear at random in the time scale. Therefore, the EEG signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. This work discusses the effect on the EEG signal due to music and reflexological stimulation. METHODS: In this work, nonlinear parameters like Correlation Dimension (CD), Largest Lyapunov Exponent (LLE), Hurst Exponent (H) and Approximate Entropy (ApEn) are evaluated from the EEG signals under different mental states. RESULTS: The results obtained show that EEG to become less complex relative to the normal state with a confidence level of more than 85% due to stimulation. CONCLUSIONS: It is found that the measures are significantly lower when the subjects are under sound or reflexologic stimulation as compared to the normal state. The dimension increases with the degree of the cognitive activity. This suggests that when the subjects are under sound or reflexologic stimuli, the number of parallel functional processes active in the brain is less and the brain goes to a more relaxed stat

An investigation of the phase locking index for measuring of interdependency of cortical source signals recorded in the EEG

The phase locking index (PLI) was introduced to quantify in a statistical sense the phase synchronization of two signals. It has been commonly used to process biosignals. In this article, we investigate the PLI for measuring the interdependency of cortical source signals (CSSs) recorded in the Electroencephalogram (EEG). To this end, we consider simple analytical models for the mapping of simulated CSSs into the EEG. For these models, the PLI is investigated analytically and through numerical simulations. An evaluation is made of the sensitivity of the PLI to the amount of crosstalk between the sources through biological tissues of the head. It is found that the PLI is a useful interdependency measure for CSSs, especially when the amount of crosstalk is small. Another common interdependency measure is the coherence. A direct comparison of both measures has not been made in the literature so far. We assess the performance of the PLI and coherence for estimation and detection purposes based on, respectively, a normalized variance and a novel statistical measure termed contrast. Based on these performance measures, it is found that the PLI is similar or better than the CM in most cases. This result is also confirmed through analysis of EEGs recorded from epileptic patients

Average multipolarity of continuum transitions in nuclei at high angular momentum

The multipolarity of continuum transitions deexciting high-spin states has been deduced from measured conversion coefficients. The investigated 146Nd(20Ne, 4n or 5n) 162,161Yb reactions were selected by gating on discrete lines. The average multipolarity gradually changes from E2 at 0.5 MeV to E1 above 1.5 MeV

EEG-based emotion recognition via fast and robust feature smoothing

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On the origin and suddenness of absences in genetic absence models

Item does not contain fulltextThe origin of spike-wave discharges (SWDs), typical for absences, has been debated for at least half a century. While most classical views adhere to a thalamic oscillatory machinery and an active role of the cortex in modifying normal oscillations into pathological SWDs, recent studies in genetic models such as WAG/Rij and GAERS rats have challenged this proposal. It seems now well established that SWDs originate from the deep layers of the somatosensory cortex, that the activity quickly spreads over the cortex and invades the thalamus. The reticular thalamic nucleus and other thalamic nuclei provide a resonance circuitry for the amplification, spreading and entrainment of the SWDs. Conclusive evidence has been found that the changed functionality of HCN1 channels is a causative factor for the changes in local excitability and age-dependent increase in SWD. Furthermore, upregulation of two subtypes of Na+ channels, reduction of GABA(B) and mGlu 2/3 receptors might also play a role in the local increased excitability in WAG/Rij rats. Signal analytical studies have also challenged the view that SWDs occur suddenly from a normal background EEG. SWDs are recruited cortical responses and they develop from increasing associations within and between cortical layers and subsequently subcortical regions, triggered by the simultaneous occurrence of theta and delta precursor activity in the cortex and thalamus in case both structures are in a favorable condition, and increased directional coupling between cortex and thalamus. It is hypothesized that the cortex is the driving force throughout the whole SWD and is also responsible for its end15 p