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Found 11 papers, 0 papers with code
Neurophysiological Response Based on Auditory Sense for Brain Modulation Using Monaural Beat
For analysis, we calculated the power spectral density (PSD) of EEG for each session and compared them in frequency, time, and five brain regions.
Impact of Nap on Performance in Different Working Memory Tasks Using EEG
Electroencephalography (EEG) has been widely used to study the relationship between naps and working memory, yet the effects of naps on distinct working memory tasks remain unclear.
Multi-Signal Reconstruction Using Masked Autoencoder From EEG During Polysomnography
Polysomnography (PSG) is an indispensable diagnostic tool in sleep medicine, essential for identifying various sleep disorders.
Relationship Between Mood, Sleepiness, and EEG Functional Connectivity by 40 Hz Monaural Beats
The monaural beat is known that it can modulate brain and personal states.
Changes in Power and Information Flow in Resting-state EEG by Working Memory Process
Here, we identified frequency-specific power and information flow patterns among three RS EEG before and after WM encoding and WM retrieval.
Development of Personalized Sleep Induction System based on Mental States
We aim to develop a personalized sleep induction system based on mental states using electroencephalogram and auditory stimulation.
Siamese Sleep Transformer For Robust Sleep Stage Scoring With Self-knowledge Distillation and Selective Batch Sampling
These results could show that SST extracted effective learning features against the bias of labels in datasets, and the selective batch sampling strategy worked for the model robustness in training.
Differential EEG Characteristics during Working Memory Encoding and Re-encoding
Also, there was a statistically significant difference in PAC.
Automatic Micro-sleep Detection under Car-driving Simulation Environment using Night-sleep EEG
We pre-trained the U-Net to classify the 5-class sleep stages using night-sleep EEG and used the sleep stages estimated by the U-Net to detect micro-sleep during driving.
Predicting the Transition from Short-term to Long-term Memory based on Deep Neural Network
So far, many studies have analyzed electroencephalogram (EEG) signals at encoding to predict later remembered items, but few studies have predicted long-term memory only with EEG signals of successful short-term memory.
Assessment of Unconsciousness for Memory Consolidation Using EEG Signals
Seven participants performed two memory tasks (word-pairs and visuo-spatial) before and after the nap to assess the memory consolidation during unconsciousness.
