SOTAVerified

Electroencephalogram (EEG)

Electroencephalogram (EEG) is a method of recording brain activity using electrophysiological indexes. When the brain is active, a large number of postsynaptic potentials generated synchronously by neurons are formed after summation. It records the changes of electric waves during brain activity and is the overall reflection of the electrophysiological activities of brain nerve cells on the surface of cerebral cortex or scalp. Brain waves originate from the postsynaptic potential of the apical dendrites of pyramidal cells. The formation of synchronous rhythm of EEG is also related to the activity of nonspecific projection system of cortex and thalamus. EEG is the basic theoretical research of brain science. EEG monitoring is widely used in its clinical application.

Papers

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Showing 1451–1500 of 1655 papers

TitleStatusHype
Hierarchical internal representation of spectral features in deep convolutional networks trained for EEG decoding—0
Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security—0
Real-time fMRI neurofeedback of the mediodorsal and anterior thalamus enhances correlation between thalamic BOLD activity and alpha EEG rhythm—0
The signature of robot action success in EEG signals of a human observer: Decoding and visualization using deep convolutional neural networks—0
Neurology-as-a-Service for the Developing World—0
An EEG-based Image Annotation System—0
Occipital and left temporal EEG correlates of phenomenal consciousness—0
Deep Transfer Learning for Error Decoding from Non-Invasive EEG—0
Effects of Images with Different Levels of Familiarity on EEG—0
Deep Convolutional Neural Networks for Interpretable Analysis of EEG Sleep Stage Scoring—0
Unidirectional brain to muscle connectivity reveals motor cortex control of leg muscles during stereotyped walking—0
Generative Adversarial Networks Conditioned by Brain Signals—0
Accounting for the Complex Hierarchical Topology of EEG Phase-Based Functional Connectivity in Network Binarisation—0
Converting Your Thoughts to Texts: Enabling Brain Typing via Deep Feature Learning of EEG SignalsCode0
Multi-Person Brain Activity Recognition via Comprehensive EEG Signal Analysis—0
Ensemble Classifier for Eye State Classification using EEG Signals—0
Neonatal Seizure Detection using Convolutional Neural Networks—0
Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection—0
Deep learning with convolutional neural networks for decoding and visualization of EEG pathologyCode0
Multichannel sleep spindle detection using sparse low-rank optimizationCode0
Brain Responses During Robot-Error Observation—0
Applying advanced machine learning models to classify electro-physiological activity of human brain for use in biometric identificationCode0
SPLICE: Fully Tractable Hierarchical Extension of ICA with Pooling—0
SLEEPNET: Automated Sleep Staging System via Deep Learning—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
A comparison of single-trial EEG classification and EEG-informed fMRI across three MR compatible EEG recording systems—0
Stance leg and surface stability modulate cortical activity during human single leg stance—0
Multiscale Granger causality analysis by à trous wavelet transformCode0
A Generalised Seizure Prediction with Convolutional Neural Networks for Intracranial and Scalp Electroencephalogram Data Analysis—0
A deep learning architecture for temporal sleep stage classification using multivariate and multimodal time seriesCode1
Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network—0
Sparsity Enables Estimation of both Subcortical and Cortical Activity from MEG and EEG—0
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data—0
Individual Recognition in Schizophrenia using Deep Learning Methods with Random Forest and Voting Classifiers: Insights from Resting State EEG Streams—0
Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings—0
Decline of long-range temporal correlations in the human brain during sustained wakefulness—0
The interplay between long- and short-range temporal correlations shapes cortex dynamics across vigilance states—0
Deep Recurrent Neural Networks for seizure detection and early seizure detection systems—0
DeepKey: An EEG and Gait Based Dual-Authentication System—0
Generalized Concomitant Multi-Task Lasso for sparse multimodal regressionCode0
Bayesian Belief Updating of Spatiotemporal Seizure Dynamics—0
Improving classification accuracy of feedforward neural networks for spiking neuromorphic chips—0
Deep neural networks on graph signals for brain imaging analysis—0
Spatial-Temporal Recurrent Neural Network for Emotion Recognition—0
Emotion Specification from Musical Stimuli: An EEG Study with AFA and DFA—0
Can Musical Emotion Be Quantified With Neural Jitter Or Shimmer? A Novel EEG Based Study With Hindustani Classical Music—0
EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features—0
AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups—0
Automated Diagnosis of Epilepsy Employing Multifractal Detrended Fluctuation Analysis Based Features—0
Multimodal deep learning approach for joint EEG-EMG data compression and classification—0
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All datasetsSEED-IVHS-SSVEPSEED

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1BiHDMAccuracy74.35—Unverified
2DGCNNAccuracy69.88—Unverified
3DBNAccuracy66.77—Unverified
#ModelMetricClaimedVerifiedStatus
1MultitaskSSVEPAccuracy (5-fold)92.2—Unverified
#ModelMetricClaimedVerifiedStatus
1DBNAccuracy86.08—Unverified