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  • Cross subject mental work load classification from electroencephalographic signals with automatic artifact rejection and muscle pruning

    2 July 2018

    � Springer International Publishing AG 2016. Purpose of this study was to understand the effect of automatic muscle pruning of electroencephalograph on cognitive work load prediction. Pruning was achieved using an automatic Independent Component Analysis (ICA) based component classification. Initially, raw data from EEG recording was used for prediction, this result was then compared with mental work load prediction results from muscle-pruned EEG data. This study used Support Vector Machine (SVM) with Linear Kernel for cognitive work load prediction from EEG data. Initial part of the study was to learn a classification model from the whole data, whereas the second part was to learn the model from a set of subjects and predict the mental work load for an unseen subject by the model. The experimental results show that an accuracy of nearly 100% is possible with ICA and automatic pruning based pre-processing. Cross subject prediction significantly improved from a mean accuracy of 54% to 69% for an unseen subject with the pre-processing.

  • A comparative study of the detection of direct causal influence with bivariate and multivariate measures for EEG

    2 July 2018

    © 2014 IEEE. In this paper, we perform the first comparison of a large variety of connectivity measures in detecting causal effects among observed interacting systems based on their statistical significance. Well-known measures estimating direction and strength interdependence between time series are compared: information theoretic measures, model- based multivariate measures in the frequency domain, and the time domain, and phase-based measures. At the same time the phase locking index is used to consider phase relationship between signals, where the phase locking value implies that the response is delayed with respect to drive at some frequency. The performance of measures is tested on simulated data from three systems: three coupled Hénon maps; a multivariate autoregressive (MVAR) model with and without EEG as an exogenous input; and simulated EEG. No measure was consistently superior. Measures that model the data as MVAR perform well when the data are drawn from that model. Frequency domain measures perform well when the data have a clearly defined band of interest. When neither of these is true, information theoretic measures perform well.

  • EEG source analysis of data from paralysed subjects

    2 July 2018

    © 2015 SPIE. One of the limitations of Encephalography (EEG) data is its quality, as it is usually contaminated with electric signal from muscle. This research intends to study results of two EEG source analysis methods applied to scalp recordings taken in paralysis and in normal conditions during the performance of a cognitive task. The aim is to determinate which types of analysis are appropriate for dealing with EEG data containing myogenic components. The data used are the scalp recordings of six subjects in normal conditions and during paralysis while performing different cognitive tasks including the oddball task which is the object of this research. The data were pre-processed by filtering it and correcting artefact, then, epochs of one second long for targets and distractors were extracted. Distributed source analysis was performed in BESA Research 6.0, using its results and information from the literature, 9 ideal locations for source dipoles were identified. The nine dipoles were used to perform discrete source analysis, fitting them to the averaged epochs for obtaining source waveforms. The results were statistically analysed comparing the outcomes before and after the subjects were paralysed. Finally, frequency analysis was performed for better explain the results. The findings were that distributed source analysis could produce confounded results for EEG contaminated with myogenic signals, conversely, statistical analysis of the results from discrete source analysis showed that this method could help for dealing with EEG data contaminated with muscle electrical signal.

  • Detection of coupling with linear and nonlinear synchronization measures for EEG

    2 July 2018

    There has been extensive research aimed at measuring synchronization to study the relationships between complex time series, such as electroencephalography (EEG). We compare six synchronization measures: the linear measures of cross-correlation, coherence and partial coherence, and three nonlinear similarity measures, namely correntropy, phase index and mutual information. We apply these measures to simulated data (unidirectionally coupled Hénon maps) to test the detection of nonlinear and nonstationary interdependence, including in the presence of noise, and to simulated EEG. No measure fails, none is the clear winner, all measures have advantages and disadvantages. 'Best measure' depends on the research aims and data. The tests selected here for EEG research recommend correntropy as the preferred measure. © 2014 IEEE.

  • TIGIT Enhances Antigen-Specific Th2 Recall Responses and Allergic Disease.

    28 June 2018

    T cell Ig and ITIM domain receptor (TIGIT), expressed on T, NK, and regulatory T cells, is known as an inhibitory molecule that limits autoimmunity, antiviral and antitumor immunity. In this report, we demonstrate that TIGIT enhances Th2 immunity. TIGIT expression was upregulated in activated Th2 cells from mice with experimental allergic disease and in Th2 polarization cultures. In addition, its high-affinity ligand CD155 was upregulated in mediastinal lymph node dendritic cells from allergic mice. In an in vitro setting, we observed that Tigit expression in Th2 cells and its interaction with CD155 expressed in dendritic cells were important during the development of Th2 responses. In addition, blockade of TIGIT inhibited Th2, but had no effect on either Th1 or Th17 polarization. In vivo blockade of TIGIT suppressed hallmarks of allergic airway disease, such as lung eosinophilia, goblet cell hyperplasia, Ag-specific Th2 responses, and IgE production, and reduced numbers of T follicular helper and effector Th2 cells. Thus, TIGIT is critical for Th2 immunity and can be used as a therapeutic target, especially in light of recent findings showing TIGIT locus hypomethylation in T cells from pediatric patients with allergic asthma.

  • ERβ in CD4+ T Cells Is Crucial for Ligand-Mediated Suppression of Central Nervous System Autoimmunity.

    2 July 2018

    The development of therapies for multiple sclerosis targeting pathogenic T cell responses remains imperative. Previous studies have shown that estrogen receptor (ER) β ligands could inhibit experimental autoimmune encephalomyelitis. However, the effects of ERβ-specific ligands on human or murine pathogenic immune cells, such as Th17, were not investigated. In this article, we show that the synthetic ERβ-specific ligand 4-(2-phenyl-5,7-bis[trifluoromethyl]pyrazolo[1,5-a]pyrimidin-3-yl)phenol (PHTPP) reversed established paralysis and CNS inflammation, characterized by a dramatic suppression of pathogenic Th responses as well as induction of IL-10-producing regulatory CD4(+) T cell subsets in vivo. Moreover, administration of PHTPP in symptomatic mice induced regulatory CD4(+) T cells that were suppressive in vivo. PHTPP-mediated experimental autoimmune encephalomyelitis amelioration was canceled in mice with ERβ-deficient CD4(+) T cells only, indicating that expression of ERβ by these cells is crucial for the observed therapeutic effect. Importantly, synthetic ERβ-specific ligands acting directly on CD4(+) T cells suppressed human and mouse Th17 cells, downregulating Th17 cell signature gene expression and expanding IL-10-producing T cells among them. TGF-β1 and aryl hydrocarbon receptor activation enhanced the ERβ ligand-mediated expansion of IL-10-producing T cells among Th17 cells. In addition, these ERβ-specific ligands promoted the induction and maintenance of Foxp3(+) T regulatory cells, as well as their in vitro suppressive function. Thus, ERβ-specific ligands targeting pathogenic Th17 cells and inducing functional regulatory cells represent a promising subset of therapeutic agents for multiple sclerosis.

  • ERβ-Dependent Direct Suppression of Human and Murine Th17 Cells and Treatment of Established Central Nervous System Autoimmunity by a Neurosteroid.

    28 June 2018

    Multiple sclerosis (MS), an autoimmune disease of the CNS, is mediated by autoreactive Th cells. A previous study showed that the neurosteroid dehydroepiandrosterone (DHEA), when administered preclinically, could suppress progression of relapsing-remitting experimental autoimmune encephalomyelitis (EAE). However, the effects of DHEA on human or murine pathogenic immune cells, such as Th17, were unknown. In addition, effects of this neurosteroid on symptomatic disease, as well as the receptors involved, had not been investigated. In this study, we show that DHEA suppressed peripheral responses from patients with MS and reversed established paralysis and CNS inflammation in four different EAE models, including the 2D2 TCR-transgenic mouse model. DHEA directly inhibited human and murine Th17 cells, inducing IL-10-producing regulatory T cells. Administration of DHEA in symptomatic mice induced regulatory CD4(+) T cells that were suppressive in an IL-10-dependent manner. Expression of the estrogen receptor β by CD4(+) T cells was necessary for DHEA-mediated EAE amelioration, as well as for direct downregulation of Th17 responses. TGF-β1 as well as aryl hydrocarbon receptor activation was necessary for the expansion of IL-10-producing T cells by DHEA. Thus, our studies demonstrate that compounds that inhibit pathogenic Th17 responses and expand functional regulatory cells could serve as therapeutic agents for autoimmune diseases, such as MS.

  • Circulating conventional and plasmacytoid dendritic cell subsets display distinct kinetics during in vivo repeated allergen skin challenges in atopic subjects.

    28 June 2018

    Upon allergen challenge, DC subsets are recruited to target sites under the influence of chemotactic agents; however, details pertinent to their trafficking remain largely unknown. We investigated the kinetic profiles of blood and skin-infiltrating DC subsets in twelve atopic subjects receiving six weekly intradermal allergen and diluent injections. The role of activin-A, a cytokine induced in allergic and tissue repair processes, on the chemotactic profiles of DC subsets was also examined. Plasmacytoid (pDCs) and conventional DCs (cDCs) were evaluated at various time-points in the blood and skin. In situ activin-A expression was assessed in the skin and its effects on chemokine receptor expression of isolated cDCs were investigated. Blood pDCs were reduced 1 h after challenge, while cDCs decreased gradually within 24 h. Skin cDCs increased significantly 24 h after the first challenge, inversely correlating with blood cDCs. Activin-A in the skin increased 24 h after the first allergen challenge and correlated with infiltrating cDCs. Activin-A increased the CCR10/CCR4 expression ratio in cultured human cDCs. DC subsets demonstrate distinct kinetic profiles in the blood and skin especially during acute allergic inflammation, pointing to disparate roles depending on each phase of the inflammatory response. The effects of activin-A on modulating the chemotactic profile of cDCs suggest it may be a plausible therapeutic target for allergic diseases.