Volume Conduction Effects on Wavelet Cross-Bicoherence Analysis

Cross-bicoherence analysis is one of the important nonlinear signal processing tools which is used to measure quadratic phase coupling between frequencies of two different time series. It is frequently used in the diagnosis of various cognitive and neurological disorders in EEG (Electroencephalography) analysis. Volume conduction effects of various uncorrelated sources present in the brain can produce biased estimates into the estimated values of cross-bicoherence function. Previous studies have discussed volume conduction effects on coherence function which is used to measure linear relationship between EEG signals in terms of their phase and amplitude. However, volume conduction effect on crossbicoherence analysis which is quite a different technique has not been investigated up to now to the best of our knowledge. This study is divided into two major parts, the first part deals with the investigation of VCUS (Volume Conduction effects due to Uncorrelated Sources) characteristics on EEG-cross-bicoherence analysis. The simulated EEG data due to uncorrelated sources present in the brain was used in this part of study. The next part of study is based upon investigating the effects of VCUS on the statistical analysis of results of EEG-based cross-bicoherence analysis. The study provides an important clinical application because most of studies based on EEG cross-bicoherence analysis have avoided the issue of VCUS. The cross-bicoherence analysis was performed by detecting the change in MSCB (Magnitude Square CrossBicoherence Function) between EEG activities of change detection and no-change detection trials. The real EEG signals were use

Wavelet Coherence Analysis of Change Blindness

Change blindness is the incapability of the brain to detect substantial visual changes in the presence of other visual interruption. The objectives of this study are to examine the EEG (Electroencephalographic) based changes in functional connectivity of the brain due to the change blindness. The functional connectivity was estimated using the wavelet-based MSC (Magnitude Square Coherence) function of ERPs (Event Related Potentials). The ERPs of 30 subjects were used and were recorded using the visual attention experiment in which subjects were instructed to detect changes in visual stimulus presented before them through the computer monitor. The two-way ANOVA statistical test revealed significant increase in both gamma and theta band MSCs, and significant decrease in beta band MSC for change detection trials. These findings imply that change blindness might be associated to the lack of functional connectivity in gamma and theta bands and increase of functional connectivity in beta band. Since gamma, theta, and beta frequency bands reflect different functions of cognitive process such as maintenance, encoding, retrieval, and matching and work load of VSTM (Visual Short Term Memory), the change in functional connectivity might be correlated to these cognitive processes during change blindness

Highly Sensitive Voltammetric Determination of Acrylamide Based on Ibuprofen Capped Mercury Nanoparticles

Highly stable, small-sized and evenly distributed solid mercury nanoparticles capped with ibuprofen (Ibu-HgNPs) were prepared via reduction with hydrazine and capped with ibuprofen as a stabilizing agent. Characterization of Ibu-HgNPs was carried out by UV-Vis spectrophotometry and transmission electron microscopy (TEM). The prepared Ibu-HgNPs were immobilized onto a glassy carbon electrode (GCE) and used for the first time as the sensing element for voltammetric determination of low concentrations of acrylamide (AA) in aqueous solutions. Various parameters such as the type of supporting electrolyte, voltammetric mode, frequency, deposition time, stirring rate and initial potential were optimized to obtain the highest peak current of AA. The sensor delivered the best results in combination with the square wave voltammetry (SWV) mode, with good repeatability (relative standard deviation (RSD) of 25 repetitions was 1.4% for 1000 ppb AA). The study further revealed that Ibu-HgNPs are strongly adhered to GCE and hence do not contaminate the environment even after several runs. The newly developed AA sensor provides linear calibration dependence in the range of 100–1300 ppb with an R2 value of 0.996 and limit of detection (LOD) of 8.5 ppb. Negligible interference was confirmed from several organic compounds, cations and anions. The developed sensor was successfully applied for AA determination in various types of environmental real water samples to prove its practical usefulness and applicability