EEG-based source localization with enhanced virtual aperture using second order statistics

For the past few decades source localization, based on EEG modality, has been a very active area of research. EEG signal provides temporal resolution in millisecond range that can capture rapidly changing patterns of brain activity but it has a low spatial resolution as compared to techniques like fMRI, PET, CT scan, etc. So, one of the motives of this research is to improve the spatial resolution of the EEG signal. Many successful attempts have been made to localise the active neural sources using EEG signals with the introduction of techniques like MNE, LORETA, sLORETA, FOCUSS, etc. But these techniques require a large number of electrodes for correct localization of a few sources. This paper aims at providing a new method for the localization of EEG sources with a fewer electrode. This is achieved by exploiting the second-order statistics to enhance the aperture and solve the EEG localization problem. The comparison of the proposed method with the state-of-the-art methods is done by observing the localization error with variation in SNR, number of snapshots (time samples), number of active sources, and number of electrodes. The results show that the proposed method can detect a greater number of sources with fewer electrodes and with higher accuracy as compared to methods available in the literature. Real -time EEG signal during an arithmetic task is considered and the proposed algorithm clearly shows a sparse activity in the frontal region.

Analysis of chemical deposits on tooth enamel exposed to total particulate matter from cigarette smoke and tobacco heating system 2.2 aerosol by novel GC-MS deconvolution procedures

Tobacco smoking contributes to tooth discoloration. Pigmented compounds in the smoke generated by combustion of tobacco can cause discoloration of dental hard tissues. However, aerosols from heated tobacco products cause less discoloration than cigarette smoke (CS) in vitro. The objective of the present study was to optimize a method for extracting the colored chemical compounds deposited on tooth enamel following exposure to total particulate matter (TPM) from CS or a heated tobacco product (Tobacco Heating System [THS] 2.2), analyze the extracts by gas chromatography coupled to time-of-flight mass spectrometry, and identify the key chemicals associated with tooth discoloration. Sixty bovine enamel blocks were exposed for 2 weeks to TPM from CS or THS 2.2 aerosol or to artificial saliva as a control. Brushing without toothpaste and color measurements were performed each week. Noticeable discoloration of enamel was observed following exposure to CS TPM. The discoloration following exposure to THS 2.2 aerosol TPM or artificial saliva was not distinguishable to the eye (ΔE < 3.3). Carbon disulfide was used to extract surface-deposited chemicals. Untargeted analyses were followed by partial least squares correlation against discoloration scores (R2 = 0.96). Eleven compounds had variable importance in projection scores greater than 2. Discriminant autocorrelation matrix calculation of their mass spectral information identified eight of the eleven compounds as terpenoids. None of the compounds were related to nicotine. Several of these compounds were also detected in THS 2.2 aerosol TPM-exposed enamel, but at lower levels, in line with our findings showing less discoloration. Compared with CS TPM exposure, THS 2.2 aerosol TPM exposure resulted in lower deposition of color-related compounds on enamel surface, consistent with minimal discoloration of dental enamel.