119 research outputs found

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

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    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

    Inverse Modeling for MEG/EEG data

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    We provide an overview of the state-of-the-art for mathematical methods that are used to reconstruct brain activity from neurophysiological data. After a brief introduction on the mathematics of the forward problem, we discuss standard and recently proposed regularization methods, as well as Monte Carlo techniques for Bayesian inference. We classify the inverse methods based on the underlying source model, and discuss advantages and disadvantages. Finally we describe an application to the pre-surgical evaluation of epileptic patients.Comment: 15 pages, 1 figur

    Исследование параметров контроля качества дефектоскопических материалов

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    Цель данной работы - исследование параметров контроля качества дефектоскопических материалов. Изучена технология проведения контроля, параметры качества дефектоскопических материалов. В результате оценена проникающая способность наборов дефектоскопических материалов. Приведен анализ факторов, влияющих на качество дефектоскопических материалов.The purpose of this work is to study the quality control parameters of flaw detection materials. The control technology, quality parameters of flaw detection materials were studied. As a result, the penetration ability of flaw detector kits was evaluated. The analysis of factors affecting the quality of flaw detection materials is given

    Оценка токсичности бурового шлама нефтегазовых месторождений методом фитотестирования

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    Работа посвящена оценке фитотоксичности буровых шламов месторождений Томской и Иркутской областей с применением в качестве тест-объекта овса.The work is devoted to assessing phytotoxicity of drilling sludge deposits Tomsk and Irkutsk areas with application in as a test object for oats

    HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity

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    The analysis of the interdependence between time series has become an important field of research in the last years, mainly as a result of advances in the characterization of dynamical systems from the signals they produce, the introduction of concepts such as generalized and phase synchronization and the application of information theory to time series analysis. In neurophysiology, different analytical tools stemming from these concepts have added to the ‘traditional’ set of linear methods, which includes the cross-correlation and the coherency function in the time and frequency domain, respectively, or more elaborated tools such as Granger Causality. This increase in the number of approaches to tackle the existence of functional (FC) or effective connectivity (EC) between two (or among many) neural networks, along with the mathematical complexity of the corresponding time series analysis tools, makes it desirable to arrange them into a unified-easy-to-use software package. The goal is to allow neuroscientists, neurophysiologists and researchers from related fields to easily access and make use of these analysis methods from a single integrated toolbox. Here we present HERMES (http://hermes.ctb.upm.es), a toolbox for the Matlab® environment (The Mathworks, Inc), which is designed to study functional and effective brain connectivity from neurophysiological data such as multivariate EEG and/or MEG records. It includes also visualization tools and statistical methods to address the problem of multiple comparisons. We believe that this toolbox will be very helpful to all the researchers working in the emerging field of brain connectivity analysis

    Seizure prediction : ready for a new era

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    Acknowledgements: The authors acknowledge colleagues in the international seizure prediction group for valuable discussions. L.K. acknowledges funding support from the National Health and Medical Research Council (APP1130468) and the James S. McDonnell Foundation (220020419) and acknowledges the contribution of Dean R. Freestone at the University of Melbourne, Australia, to the creation of Fig. 3.Peer reviewedPostprin

    Glutamate, GABA and Acetylcholine Signaling Components in the Lamina of the Drosophila Visual System

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    Synaptic connections of neurons in the Drosophila lamina, the most peripheral synaptic region of the visual system, have been comprehensively described. Although the lamina has been used extensively as a model for the development and plasticity of synaptic connections, the neurotransmitters in these circuits are still poorly known. Thus, to unravel possible neurotransmitter circuits in the lamina of Drosophila we combined Gal4 driven green fluorescent protein in specific lamina neurons with antisera to γ-aminobutyric acid (GABA), glutamic acid decarboxylase, a GABAB type of receptor, L-glutamate, a vesicular glutamate transporter (vGluT), ionotropic and metabotropic glutamate receptors, choline acetyltransferase and a vesicular acetylcholine transporter. We suggest that acetylcholine may be used as a neurotransmitter in both L4 monopolar neurons and a previously unreported type of wide-field tangential neuron (Cha-Tan). GABA is the likely transmitter of centrifugal neurons C2 and C3 and GABAB receptor immunoreactivity is seen on these neurons as well as the Cha-Tan neurons. Based on an rdl-Gal4 line, the ionotropic GABAA receptor subunit RDL may be expressed by L4 neurons and a type of tangential neuron (rdl-Tan). Strong vGluT immunoreactivity was detected in α-processes of amacrine neurons and possibly in the large monopolar neurons L1 and L2. These neurons also express glutamate-like immunoreactivity. However, antisera to ionotropic and metabotropic glutamate receptors did not produce distinct immunosignals in the lamina. In summary, this paper describes novel features of two distinct types of tangential neurons in the Drosophila lamina and assigns putative neurotransmitters and some receptors to a few identified neuron types
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