The present review discusses a well-established method for characterizing resting-state
activity of the human brain using multichannel electroencephalography (EEG). This method …

Electroencephalography (EEG) is one fundamental tool for functional brain imaging. EEG
signals tend to be represented by a vector or a matrix to facilitate data processing and …

Background and objectives To explore cognitive, EEG, and MRI features in COVID-19
survivors up to 10 months after hospital discharge. Methods Adult patients with a recent …

We have developed a toolbox and graphic user interface, EEGLAB, running under the
crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of …

There has been tremendous advances in our ability to produce images of human brain
function. Applications of functional brain imaging extend from improving our understanding …

This article provides a new, more comprehensive view of event-related brain dynamics
founded on an information-based approach to modeling electroencephalographic (EEG) …

This paper describes the local mean decomposition (LMD), a new iterative approach to
demodulating amplitude and frequency modulated signals. The new method decomposes …

Since its discovery in the 1960s, the P300 has been contributing both directly and indirectly
to language research. Perhaps most notably, it has been suggested that the P600, an ERP …

This review discusses the theory and practical application of independent component
analysis (ICA) to multi-channel EEG data. We use examples from an audiovisual attention …

Independent component analysis (ICA) is increasing in popularity in the field of biomedical
signal processing. It is generally used when it is required to separate measured multi …