Analysis of Residue Probability Density Function and Comparator Offset Error in Pipelined ADCs

This paper presents a new approach to analyze the convergence of residue probability density function (pdf) in pipelined ADCs. Compared to the previous approaches, in the proposed approach, in addition to the analysis of residue pdfs for different input densities, the analysis of the sub-ADC comparator offsets impact on output pdf is possible. Using Fourier analysis, it will be shown that the residue density converges to uniformity. In the half-bit redundant structure, residue pdf concentrates in the center half of the stage full-scale range and 6 dB of extra resolution can be gained. Also, the share of each stage in this resolution improvement is investigated. Examining the sub-ADC threshold offsets impact on residue pdfs, it is observed that with respect to the impact on converter additional resolution, the final stages offset errors are more significant than the first stages offsets

Suivi de relation en temps et en fréquence dans les signaux SEEG épileptiques. Evaluation de deux estimateurs linéaires

Dans cet article, on s'intéresse au suivi de l'évolution en temps et en fréquence de la relation linéaire entre deux signaux non stationnaires (signaux EEG intracérébraux enregistrés chez des patients épileptiques). Un estimateur est proposé, basé sur la mesure du coefficient de corrélation linéaire entre les signaux de sous-bandes, optimisé pour le retard, et comparé à un estimateur de la fonction de cohérence (classiquement utilisé dans l'analyse du signal EEG). Les résultats obtenus sur signaux simulés montrent que l'estimateur proposé permet de réduire le biais, et la variance d'estimation. Sur signaux réels, ils permettent de mettre en évidence une différence, importante sur le plan de la physiopathologie, sur la corrélation des signaux durant l'activité intercritique (en dehors des crises) et durant l'activité critique (pendant les crises)

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

Glutamate Induces Mitochondrial Dynamic Imbalance and Autophagy Activation: Preventive Effects of Selenium

Glutamate-induced cytotoxicity is partially mediated by enhanced oxidative stress. The objectives of the present study are to determine the effects of glutamate on mitochondrial membrane potential, oxygen consumption, mitochondrial dynamics and autophagy regulating factors and to explore the protective effects of selenium against glutamate cytotoxicity in murine neuronal HT22 cells. Our results demonstrated that glutamate resulted in cell death in a dose-dependent manner and supplementation of 100 nM sodium selenite prevented the detrimental effects of glutamate on cell survival. The glutamate induced cytotoxicity was associated with mitochondrial hyperpolarization, increased ROS production and enhanced oxygen consumption. Selenium reversed these alterations. Furthermore, glutamate increased the levels of mitochondrial fission protein markers pDrp1 and Fis1 and caused increase in mitochondrial fragmentation. Selenium corrected the glutamate-caused mitochondrial dynamic imbalance and reduced the number of cells with fragmented mitochondria. Finally, glutamate activated autophagy markers Beclin 1 and LC3-II, while selenium prevented the activation. These results suggest that glutamate targets the mitochondria and selenium supplementation within physiological concentration is capable of preventing the detrimental effects of glutamate on the mitochondria. Therefore, adequate selenium supplementation may be an efficient strategy to prevent the detrimental glutamate toxicity and further studies are warranted to define the therapeutic potentials of selenium in animal disease models and in human

Entropy and Complexity Analyses in Alzheimer’s Disease: An MEG Study

Alzheimer’s disease (AD) is one of the most frequent disorders among elderly population and it is considered the main cause of dementia in western countries. This irreversible brain disorder is characterized by neural loss and the appearance of neurofibrillary tangles and senile plaques. The aim of the present study was the analysis of the magnetoencephalogram (MEG) background activity from AD patients and elderly control subjects. MEG recordings from 36 AD patients and 26 controls were analyzed by means of six entropy and complexity measures: Shannon spectral entropy (SSE), approximate entropy (ApEn), sample entropy (SampEn), Higuchi’s fractal dimension (HFD), Maragos and Sun’s fractal dimension (MSFD), and Lempel-Ziv complexity (LZC). SSE is an irregularity estimator in terms of the flatness of the spectrum, whereas ApEn and SampEn are embbeding entropies that quantify the signal regularity. The complexity measures HFD and MSFD were applied to MEG signals to estimate their fractal dimension. Finally, LZC measures the number of different substrings and the rate of their recurrence along the original time series. Our results show that MEG recordings are less complex and more regular in AD patients than in control subjects. Significant differences between both groups were found in several brain regions using all these methods, with the exception of MSFD (p-value < 0.05, Welch’s t-test with Bonferroni’s correction). Using receiver operating characteristic curves with a leave-one-out cross-validation procedure, the highest accuracy was achieved with SSE: 77.42%. We conclude that entropy and complexity analyses from MEG background activity could be useful to help in AD diagnosis