Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies
Substantial progress has been made over the past two decades in detecting, predicting and
promoting recovery of consciousness in patients with disorders of consciousness (DoC) …
promoting recovery of consciousness in patients with disorders of consciousness (DoC) …
[HTML][HTML] TMS combined with EEG: Recommendations and open issues for data collection and analysis
Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and
connected brain regions. The evoked brain response can be measured with …
connected brain regions. The evoked brain response can be measured with …
Deep learning-based electroencephalography analysis: a systematic review
Context. Electroencephalography (EEG) is a complex signal and can require several years
of training, as well as advanced signal processing and feature extraction methodologies to …
of training, as well as advanced signal processing and feature extraction methodologies to …
Concurrent fNIRS and EEG for brain function investigation: a systematic, methodology-focused review
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis …
Sparse Bayesian learning for end-to-end EEG decoding
Decoding brain activity from non-invasive electroencephalography (EEG) is crucial for brain-
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …
computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG …
The clinical promise of biomarkers of synapse damage or loss in Alzheimer's disease
Background Synapse damage and loss are fundamental to the pathophysiology of
Alzheimer's disease (AD) and lead to reduced cognitive function. The goal of this review is to …
Alzheimer's disease (AD) and lead to reduced cognitive function. The goal of this review is to …
Riemannian geometry for EEG-based brain-computer interfaces; a primer and a review
Despite its short history, the use of Riemannian geometry in brain-computer interface (BCI)
decoding is currently attracting increasing attention, due to accumulating documentation of …
decoding is currently attracting increasing attention, due to accumulating documentation of …
[图书][B] Fundamentals of brain network analysis
Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to
methods for unraveling the extraordinary complexity of neuronal connectivity. From the …
methods for unraveling the extraordinary complexity of neuronal connectivity. From the …
A deep learning approach for automatic seizure detection in children with epilepsy
A Abdelhameed, M Bayoumi - Frontiers in Computational …, 2021 - frontiersin.org
Over the last few decades, electroencephalogram (EEG) has become one of the most vital
tools used by physicians to diagnose several neurological disorders of the human brain and …
tools used by physicians to diagnose several neurological disorders of the human brain and …
[HTML][HTML] International Federation of Clinical Neurophysiology (IFCN)–EEG research workgroup: Recommendations on frequency and topographic analysis of resting …
Abstract In 1999, the International Federation of Clinical Neurophysiology (IFCN) published
“IFCN Guidelines for topographic and frequency analysis of EEGs and EPs”(Nuwer et al …
“IFCN Guidelines for topographic and frequency analysis of EEGs and EPs”(Nuwer et al …