Results 291 to 300 of about 141,761 (332)

Tracking causal pathways in TMS-evoked brain responses. [PDF]

PLoS Comput Biol
Xiao J, Yin Q, Li L, Meng Y, Liu X, Hu W, Huang X, Feng Y, Shan X, Zhao W, Wang P, Wang X, Li Y, Chen H, Duan X.   +14 more
europepmc   +1 more source

A single-center retrospective analysis of autoimmune glial fibrillary acidic protein astrocytopathy with seizures in children. [PDF]

Front Neurol
Fang H, Hu W, Jiang Z.
europepmc   +1 more source

Changes in postural sway and cortical activities after napping. [PDF]

PLoS One
Chen HY, Chen LY, Lou SZ, Lin CL.
europepmc   +1 more source

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Self-Supervised Learning for Electroencephalography

IEEE Transactions on Neural Networks and Learning Systems, 2022
Decades of research have shown machine learning superiority in discovering highly nonlinear patterns embedded in electroencephalography (EEG) records compared with conventional statistical techniques.
M. Rafiei, Lynne V. Gauthier, H. Adeli, Daniel Takabi   +3 more
semanticscholar   +1 more source

Attention-Inception and Long- Short-Term Memory-Based Electroencephalography Classification for Motor Imagery Tasks in Rehabilitation

IEEE Transactions on Industrial Informatics, 2022
In recent years, the contributions of deep learning have had a phenomenal impact on electroencephalography-based brain-computer interfaces. While the decoding accuracy of electroencephalography signals has continued to increase, the process has caused ...
S. Amin, Hamdi Altaheri, G. Muhammad, Mansour Alsulaiman, A. Wadood   +4 more
semanticscholar   +1 more source

Materials for Dry Electrodes for the Electroencephalography: Advances, Challenges, Perspectives

Advanced Materials & Technologies, 2021
Electroencephalography (EEG) is extensively applied in brain cognition, clinical diagnosis, and artificial intelligence through detecting and analyzing the human brain biopotential.
Liangtao Yang, Qing Liu, Zhilin Zhang, Lu Gan, Yi Zhang, Jinglong Wu   +5 more
semanticscholar   +1 more source

Electroencephalography and video-electroencephalography

2012
Abstract Electroencephalography (EEG) is a specific investigation to support the diagnosis of epilepsy, demonstrating interictal epileptiform activity in the majority of individuals with epilepsy. The EEG can also help classify the epilepsy as focal or generalized, and can suggest certain epileptic syndromes.
Antonio Gil-Nagel, Bassel Abou-Khalil
openaire   +3 more sources

Machine learning for decoding listeners’ attention from electroencephalography evoked by continuous speech

European Journal of Neuroscience, 2020
Previous research has shown that it is possible to predict which speaker is attended in a multispeaker scene by analyzing a listener's electroencephalography (EEG) activity.
Tobias de Taillez, B. Kollmeier, B. Meyer   +2 more
semanticscholar   +1 more source

Fatigue Detection With Covariance Manifolds of Electroencephalography in Transportation Industry

IEEE Transactions on Industrial Informatics, 2021
Driver fatigue has become a leading cause of accidents and death in the transportation industry. Electroencephalography (EEG)-based fatigue detection can be a good way to reduce accidents and improve safety and efficiencies throughout the transportation ...
Xiaowei Zhang, Dawei Lu, Jing Pan, Jian Shen, Manxi Wu, Xiping Hu, Bin Hu   +6 more
semanticscholar   +1 more source

Dormison in electroencephalography

Electroencephalography and Clinical Neurophysiology, 1952
Abstract 1. 1. Dormison is a satisfactory hypnotic. The sleep induced is always of a restful type. 2. 2. The drug has a mild sedative effect in uncooperative and restless children. Sleep, at times, follows a period of quietness. 3. 3. Dormison does not interfere with cerebral electrical activity before sleep is induced.
Maide Tükel, Maide Tükel, Kenan Tükel
openaire   +3 more sources