A growing body of clinical and cognitive neuroscience studies have adapted a broadband
EEG microstate approach to evaluate the electrical activity of large-scale cortical networks …

Over the past decade, many researchers have come up with different implementations of
systems for decoding covert or imagined speech from EEG (electroencephalogram). They …

Alzheimer's disease (AD) is a neurodegenerative disease causing progressive cognitive
decline until eventual death. AD affects millions of individuals worldwide in the absence of …

EEG microstates represent functional brain networks observable in resting EEG recordings
that remain stable for 40–120ms before rapidly switching into another network. It is assumed …

Parkinson's disease (PD) exhibits significant clinical heterogeneity, presenting challenges in
the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning …

Mental disorders are among the leading causes of disability worldwide. The first step in
treating these conditions is to obtain an accurate diagnosis. Machine learning algorithms …

Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders in the
world. Although there is no known cure for it at the present, preventive drug trials and …

Functional connectivity of the human brain, representing statistical dependence of
information flow between cortical regions, significantly contributes to the study of the intrinsic …

Background Resting-state EEG microstates are thought to reflect brief activations of several
interacting components of resting-state brain networks. Surprisingly, we still know little about …

The development of the next generation therapy for Alzheimer's disease (AD) presents a
huge challenge given the number of promising treatment candidates that failed in trials …