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 1101–1125 of 1655 papers

TitleStatusHype
Neural modulation enhancement using connectivity-based EEG neurofeedback with simultaneous fMRI for emotion regulation—0
Increasing the Detectability of Phase-Amplitude Coupling—0
Individual Recognition in Schizophrenia using Deep Learning Methods with Random Forest and Voting Classifiers: Insights from Resting State EEG Streams—0
Inferring Brain Dynamics via Multimodal Joint Graph Representation EEG-fMRI—0
Inferring latent neural sources via deep transcoding of simultaneously acquired EEG and fMRI—0
InfoFlowNet: A Multi-head Attention-based Self-supervised Learning Model with Surrogate Approach for Uncovering Brain Effective Connectivity—0
Information Theoretic Feature Transformation Learning for Brain Interfaces—0
Inner speech recognition through electroencephalographic signals—0
Insights into Schizophrenia: Leveraging Machine Learning for Early Identification via EEG, ERP, and Demographic Attributes—0
Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy—0
Integration of Simultaneous Resting-State Electroencephalography, Functional Magnetic Resonance Imaging, and Eye-Tracker Methods to Determine and Verify Electroencephalography Vigilance Measure—0
Intelligent analysis of EEG signals to assess consumer decisions: A Study on Neuromarketing—0
Interactive Web Application for Exploring Matrices of Neural Connectivity—0
Inter-brain substrates of role switching during mother-child interaction—0
Interoception Underlies The Therapeutic Effects of Mindfulness Meditation for Post-Traumatic Stress Disorder: A Randomized Clinical Trial—0
Interpretable and Scalable Graphical Models for Complex Spatio-temporal Processes—0
Interpretable Convolutional Neural Networks for Subject-Independent Motor Imagery Classification—0
Interpretable Deep Neural Networks for Single-Trial EEG Classification—0
Interpreting Deep Learning Models for Epileptic Seizure Detection on EEG signals—0
Interpreting Imagined Speech Waves with Machine Learning techniques—0
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding—0
Intracranial EEG structure-function coupling predicts surgical outcomes in focal epilepsy—0
Intracranial Error Detection via Deep Learning—0
Investigating critical frequency bands and channels for EEG-based emotion recognition with deep neural networks—0
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition—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