233 research outputs found

    On the methodological unification in electroencephalography

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    BACKGROUND: This paper presents results of a pursuit of a repeatable and objective methodology of analysis of the electroencephalographic (EEG) time series. METHODS: Adaptive time-frequency approximations of EEG are discussed in the light of the available experimental and theoretical evidence, and applicability in various experimental and clinical setups. RESULTS: Four lemmas and three conjectures support the following conclusion. CONCLUSION: Adaptive time-frequency approximations of signals unify most of the univariate computational approaches to EEG analysis, and offer compatibility with its traditional (visual) analysis, used in clinical applications

    From wavelets to adaptive approximations: time-frequency parametrization of EEG

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    This paper presents a summary of time-frequency analysis of the electrical activity of the brain (EEG). It covers in details two major steps: introduction of wavelets and adaptive approximations. Presented studies include time-frequency solutions to several standard research and clinical problems, encountered in analysis of evoked potentials, sleep EEG, epileptic activities, ERD/ERS and pharmaco-EEG. Based upon these results we conclude that the matching pursuit algorithm provides a unified parametrization of EEG, applicable in a variety of experimental and clinical setups. This conclusion is followed by a brief discussion of the current state of the mathematical and algorithmical aspects of adaptive time-frequency approximations of signals

    Increased Coprophagic Activity of the Beetle, Tenebrio molitor, on Feces Containing Eggs of the Tapeworm, Hymenolepis diminuta

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    When provided with fecal pellets from uninfected (control) rats and rats infected with the tapeworm Hymenolepis diminuta, more fed and starved (72 h) female and starved male Tenebrio molitor fed on fecal pellets from infected- than from control rats; compared to fecal pellets from controls rats, fed males avoided the infective fecal pellets. Uninfective and infective fecal pellets had similar moisture contents, so increased coprophagic activity was not due to differences in moisture content. Fed and starved males and females were fed on fecal pellets containing tapeworm eggs and examined for cysticercoids. Significantly greater numbers of starved beetles than fed beetles were infected with cysticercoids, but the numbers of infected males and females within each treatment were not significantly different. On the other hand, males contained significantly greater numbers of cysticercoids than did females, and there was no significant difference between the numbers of cysticercoids recovered from fed and starved beetles. The data support the hypothesis that the feeding behavior of T. molitor on rat feces is altered by the presence of tapeworm eggs. The data demonstrated further that transmission dynamics are affected by a complex interaction of the beetle's sex and nutritional status

    Hamiltonian analysis of SO(4,1) constrained BF theory

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    In this paper we discuss canonical analysis of SO(4,1) constrained BF theory. The action of this theory contains topological terms appended by a term that breaks the gauge symmetry down to the Lorentz subgroup SO(3,1). The equations of motion of this theory turn out to be the vacuum Einstein equations. By solving the B field equations one finds that the action of this theory contains not only the standard Einstein-Cartan term, but also the Holst term proportional to the inverse of the Immirzi parameter, as well as a combination of topological invariants. We show that the structure of the constraints of a SO(4,1) constrained BF theory is exactly that of gravity in Holst formulation. We also briefly discuss quantization of the theory.Comment: 9 page

    Lorentz-covariant Hamiltonian analysis of BF gravity with the Immirzi parameter

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    We perform the Lorentz-covariant Hamiltonian analysis of two Lagrangian action principles that describe general relativity as a constrained BF theory and that include the Immirzi parameter. The relation between these two Lagrangian actions has been already studied through a map among the fields involved. The main difference between these is the way the Immirzi parameter is included, since in one of them the Immirzi parameter is included explicitly in the BF terms, whereas in the other (the CMPR action) it is in the constraint on the B fields. In this work we continue the analysis of their relationship but at the Hamiltonian level. Particularly, we are interested in seeing how the above difference appears in the constraint structure of both action principles. We find that they both possess the same number of first-class and second-class constraints and satisfy a very similar (off-shell) Poisson-bracket algebra on account of the type of canonical variables employed. The two algebras can be transformed into each other by making a suitable change of variablesComment: LaTeX file, no figure

    Open Database of Epileptic EEG with MRI and Postoperational Assessment of Foci—a Real World Verification for the EEG Inverse Solutions

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    This paper introduces a freely accessible database http://eeg.pl/epi, containing 23 datasets from patients diagnosed with and operated on for drug-resistant epilepsy. This was collected as part of the clinical routine at the Warsaw Memorial Child Hospital. Each record contains (1) pre-surgical electroencephalography (EEG) recording (10–20 system) with inter-ictal discharges marked separately by an expert, (2) a full set of magnetic resonance imaging (MRI) scans for calculations of the realistic forward models, (3) structural placement of the epileptogenic zone, recognized by electrocorticography (ECoG) and post-surgical results, plotted on pre-surgical MRI scans in transverse, sagittal and coronal projections, (4) brief clinical description of each case. The main goal of this project is evaluation of possible improvements of localization of epileptic foci from the surface EEG recordings. These datasets offer a unique possibility for evaluating different EEG inverse solutions. We present preliminary results from a subset of these cases, including comparison of different schemes for the EEG inverse solution and preprocessing. We report also a finding which relates to the selective parametrization of single waveforms by multivariate matching pursuit, which is used in the preprocessing for the inverse solutions. It seems to offer a possibility of tracing the spatial evolution of seizures in time

    Time-Frequency based Feature Selection for Discrimination of non stationary Biosignals.

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    This research proposes a generic methodology for dimensionality reduction upon time-frequency representations applied to the classification of different types of biosignals. The methodology directly deals with the highly redundant and irrelevant data contained in these representations, combining a first stage of irrelevant data removal by variable selection, with a second stage of redundancy reduction using methods based on linear transformations. The study addresses two techniques that provided a similar performance: the first one is based on the selection of a set of the most relevant time?frequency points, whereas the second one selects the most relevant frequency bands. The first methodology needs a lower quantity of components, leading to a lower feature space; but the second improves the capture of the time-varying dynamics of the signal, and therefore provides a more stable performance. In order to evaluate the generalization capabilities of the methodology proposed it has been applied to two types of biosignals with different kinds of non-stationary behaviors: electroencephalographic and phonocardiographic biosignals. Even when these two databases contain samples with different degrees of complexity and a wide variety of characterizing patterns, the results demonstrate a good accuracy for the detection of pathologies, over 98%.The results open the possibility to extrapolate the methodology to the study of other biosignals

    EEG windowed statistical wavelet scoring for evaluation and discrimination of muscular artifacts

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    EEG recordings are usually corrupted by spurious extra-cerebral artifacts, which should be rejected or cleaned up by the practitioner. Since manual screening of human EEGs is inherently error prone and might induce experimental bias, automatic artifact detection is an issue of importance. Automatic artifact detection is the best guarantee for objective and clean results. We present a new approach, based on the time–frequency shape of muscular artifacts, to achieve reliable and automatic scoring. The impact of muscular activity on the signal can be evaluated using this methodology by placing emphasis on the analysis of EEG activity. The method is used to discriminate evoked potentials from several types of recorded muscular artifacts—with a sensitivity of 98.8% and a specificity of 92.2%. Automatic cleaning ofEEGdata are then successfully realized using this method, combined with independent component analysis. The outcome of the automatic cleaning is then compared with the Slepian multitaper spectrum based technique introduced by Delorme et al (2007 Neuroimage 34 1443–9)

    TRY plant trait database - enhanced coverage and open access

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    Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    High dispersal ability is related to fast life-history strategies

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    1. Seed dispersal is an essential, yet often overlooked process in plant ecology and evolution, affecting adaptation capacity, population persistence and invasiveness. A species’ ability to disperse is expected to covary with other life‐history traits to form dispersal syndromes. Dispersal might be linked to the rate of life history, fecundity or generation time, depending on the relative selection pressures of bet‐hedging, kin competition or maintaining gene flow. However, the linkage between dispersal and plant life‐history strategies remains unknown because it is difficult to observe, quantify and manipulate the influence of dispersal over large spatiotemporal scales. 2. We integrate datasets describing plant vital rates, dispersal and functional traits to incorporate dispersal explicitly into the rich spectra of plant life‐history strategies. For 141 plant species, we estimated dispersal ability by predicting maximum dispersal distances using allometric relationships based on growth form, dispersal mode, terminal velocity and seed mass. We derived life‐history traits from matrix population models parameterized with field data from the COMPADRE Plant Matrix Database. We analysed the covariation in dispersal ability and life‐history traits using multivariate techniques. 3. We found that three main axes of variation described plant dispersal syndromes: the fast‐slow life‐history continuum, the dispersal strategy axis and the reproductive strategy axis. On the dispersal strategy axis, species’ dispersal abilities were positively correlated with aspects of fast life histories. Species with a high net reproductive rate, a long window of reproduction, low likelihood of escaping senescence and low shrinkage tendencies disperse their seeds further. The overall phylogenetic signal in our multidimensional analyses was low (Pagel's λ < 0.24), implying a high degree of taxonomic generality in our findings. 4. Synthesis. Dispersal has been largely neglected in comparative demographic studies, despite its pivotal importance for populations. Our explicit incorporation of dispersal in a comparative life‐history framework provides key insights to bridge the gap between dispersal ecology and life‐history traits. Species with fast life‐history strategies disperse their seeds further than slow‐living plants, suggesting that longer dispersal distances may allow these species to take advantage of habitats varying unpredictably in space and time as a bet‐hedging strategy
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