553 research outputs found

    Inward continuation of the scalp potential distribution by means of the (vector) BEM

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    The vector Boundary Element Method (vBEM) is used for the calculation of a matrix that links the tangential components of the current density on the cortical and scalp surface. This so-called transfer matrix is compared to the transfer matrix that links the potential distribution on both surfaces. Forward and inverse calculations are performed to evaluate both types of transfer matrice

    Post-movement Beta synchronization studied with linear estimation

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    Event-related desynchronization (ERS) describes a short-lasting and localized amplitude enhancement of specific frequency components. The spatial distribution of a post-movement beta ERS can be visualized by computing the local average reference (LAR). The Linear estimation (LE) method can also be applied to study the spatiotemporal ERS patterns. As source space an hemisphere was used with equally distributed radially oriented current dipoles. The lead field matrix is normalized to make sure that all dipoles have the same average impact on the sensors. A distributed source solution is found for each timestep and for each trial. Event-related Desynchronization calculations are carried out for every dipole (squaring of amplitude, averaging over all trials and time averaging over 16 time points). Both methods were conducted for the study of voluntary hand movement. The results are similar but in contrast to the LAR maps, the LE maps show a better spatial resolution. This is not surprising since the LAR method is limited to the electrode sites whereas with LE the EEG activity is projected onto the source space. Furthermore, the LE method counteracts the deblurring caused by the poorly conducting skull. Linear Estimation depends on several assumptions about the source space, volume conductor and the regularization parameter. Further investigation is needed to evaluate the application of LE for the study of Event-Related EEG phenomena

    Cortical Imaging Based on an Analytic High Resolution EEG

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    It is well known that the EEG is a blurred and spatially low-pass filtered representation of the cortical activity. Since additional recording electrodes will not necessarily lead to an improved spatial resolution, further steps have to be taken. We derived the analytic downward continuation of the scalp potential field to an arbitrary inner surface for a spherical volume conductor model with piecewise constant conductivities. The basic idea of the Analytic High Resolution BEG (AHREEG) is the fact that a function defined on a sphere can be expressed as a weighted sum of spherical harmonics. Considering the spatial transfer function between the cortex and the scalp surface, the potential distribution on the cortex is theoretically computed by the application of the inverse transfer function to the scalp potential field. Compared to source localization procedures, the AHREEG is not based on any source distribution or on the nature of the sources. Furthermore the proposed method is unique, though ill-posed. Due to this fact and the fact that real world data are always contaminated by noise, a regularization based on general cross validation is performed to stabilize the inverse solution. Simulation results as well as the application of the AHREEG to EEG recorded during median nerve stimulation will be presented and critically discussed

    Time/space regularization of the inward continuation problem in EEG using the Boundary Element Method

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    The inward continuation problem in EEG consists in the computation of the cortical potential distribution from the measured potential distribution on the scalp. Although unique this inverse problem is ill-posed. That is, low-level noise in the scalp potential data or a small error in the geometrical data can lead to unbounded errors in the solution. Regularization techniques have to be used to minimize these effects. The inverse problem is solved in two steps. First Tikhonov regularization is applied yielding a solution of the potential on the inside of the skull surface for every timestep. Than the solution of the first step is used for Twomey regularization. At each moment in time a new solution is found by using as a priori estimate the average of the first solution one timestep prior and one timestep after. This combination of spatial (Tikhonov) and temporal (Twomey) regularization improves the solution and smoothes the solution in space and time. Both simulations and the application to EEG data of a Median Nerve stimulation experiment yield encouraging results. Further comparative studies have to be carried out to evaluate the application of time/space regularization of the inward continuation problem in EEG

    A novel metabolomic approach used for the comparison of Staphylococcus aureus planktonic cells and biofilm samples

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    Introduction: Bacterial cell characteristics change significantly during differentiation between planktonic and biofilm states. While established methods exist to detect and identify transcriptional and proteomic changes, metabolic fluctuations that distinguish these developmental stages have been less amenable to investigation. Objectives: The objectives of the study were to develop a robust reproducible sample preparation methodology for high throughput biofilm analysis and to determine differences between Staphylococcus aureus in planktonic and biofilm states. Methods: The method uses bead beating in a chloroform/methanol/water extraction solvent to both disrupt cells and quench metabolism. Verification of the method was performed using liquid-chromatography-mass spectrometry. Raw mass-spectrometry data was analysed using an in-house bioinformatics pipe-line incorporating XCMS, MzMatch and in-house R-scripts, with identifications matched to internal standards and metabolite data-base entries. Results: We have demonstrated a novel mechanical bead beating method that has been optimised for the extraction of the metabolome from cells of a clinical Staphylococcus aureus strain existing in a planktonic or biofilm state. This high-throughput method is fast and reproducible, allowing for direct comparison between different bacterial growth states. Significant changes in arginine biosynthesis were identified between the two cell populations. Conclusions: The method described herein represents a valuable tool in studying microbial biochemistry at a molecular level. While the methodology is generally applicable to the lysis and extraction of metabolites from Gram positive bacteria, it is particularly applicable to biofilms. Bacteria that exist as a biofilm are shown to be highly distinct metabolically from their ‘free living’ counterparts, thus highlighting the need to study microbes in different growth states. Metabolomics can successfully distinguish between a planktonic and biofilm growth state. Importantly, this study design, incorporating metabolomics, could be optimised for studying the effects of antimicrobials and drug modes of action, potentially providing explanations and mechanisms of antibiotic resistance and to help devise new antimicrobials
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