Electrical activity recorded on the scalp using electroencephalography (EEG) results from
the mixing of signals originating from different regions of the brain as well as from artifactual …

We have identified an electroencephalographic (EEG) based statistical classifier that
correctly distinguishes children with histories of Protein Energy Malnutrition (PEM) in the first …

Abstract Electrophysiological Source Imaging (ESI) is hampered by lack of “gold standards”
for model validation. Concurrent electroencephalography (EEG) and electrocorticography …

Finding the common principal component (CPC) for ultra-high dimensional data is a
multivariate technique used to discover the latent structure of covariance matrices of shared …

Brain electrical activity in different spectral bands has been associated with diverse
mechanisms underlying Brain function. Deeper reconnoitering of these mechanisms entails …

Brain activity pattern recognition from EEG or MEG signal analysis is one of the most
important method in cognitive neuroscience. The supFunSim library is a new Matlab toolbox …

Objective. We introduce Sparse exact low resolution electromagnetic tomography
(eLORETA), a novel method for estimating a nonparametric solution to the source …

摘要无创脑电磁成像技术以其高时间分辨能力, 且可通过源成像技术有效提高空间分辨力,
在推进大脑认知原理和脑疾病机制研究中起着不可或缺的重要作用. 本文从脑电/磁信号处理 …

Aim To evaluate electroencephalography (EEG) connectivity during the first year of age in
healthy full-term infants and preterm infants with prenatal and perinatal risk factors for …

Glial cells, together with their neighboring neurons, constitute an integral functional unit
within brain circuitry, rather than isolated elements. Astrocytes, for instance, are strategically …