100 results for "slow-wave sleep" · page 9 of 10 · ranked by relevance
Imported from OpenNeuro ds003380
This dataset comprises resting-state EEG recordings from 51 right-handed undergraduate participants collected at the University of Alberta, examining relationships between alpha/theta oscillatory dynamics and trait anxiety. Recordings include alternating eyes-open and eyes-closed resting blocks, accompanied by anxiety and personality questionnaire data. The dataset supports investigation into EEG correlates of trait anxiety and related psychological constructs.
…duty cycles per degree square wave) and noise patterns (spectral power distributions…
…was applied to remove possible slow drifts from the continuous MEG data…
This dataset comprises repeated-awakening EEG recordings collected during propofol sedation, designed to explore dream experiences and consciousness dynamics under anesthesia. EEG data were acquired across wakefulness (eyes open/closed) and multiple sedation and awakening conditions, including sessions with transcranial magnetic stimulation. The study aims to evaluate whether EEG complexity measures can capture subjective dream reports elicited through repeated awakenings during propofol-induced sedation.
…with a NIRx NIRScoutXP continuous wave imaging system equipped with 4 light…
This dataset comprises EEG recordings from 10 healthy subjects performing a P300-based brain-computer interface task using a 9x8 character grid with face/house visual stimuli. The study is part of the BigP3BCI project, the largest public P300 BCI dataset containing recordings across multiple paradigms and stimulus configurations. Data were acquired at 256 Hz using 32-channel EEG with a g.USBamp amplifier and include target and non-target event classifications for BCI speller applications.
…10-20 montage) using a WaveGuard EEG cap and amplifier (ANTNeuro, Hengelo…
TMNRED is an EEG dataset collected from 30 healthy, right-handed native Chinese speakers performing a natural reading task designed to investigate fuzzy semantic target identification. Participants read Chinese news headlines and short sentences containing target and non-target semantic items while EEG was recorded across 8 blocks of 400 trials each. The dataset supports research into semantic processing mechanisms during naturalistic reading in the Chinese language.
This EEG dataset comprises recordings from 18 participants engaged in auditory and visual rhythm perception tasks using an omission paradigm. The study dissociates predictive neural mechanisms from sensory-evoked activity by presenting rhythmic stimuli with occasional omissions in both auditory and visual modalities. Comprehensive preprocessing code, time-frequency analysis, frequency band extraction, and statistical procedures are provided, with cluster analysis performed using EEGLAB.