Showing 10 of 581 datasets · page 20 of 59
This dataset contains EEG recordings collected as part of the UV_EEG study by Yukako Ito, mirrored on NEMAR from the original OpenNeuro repository. It provides electrophysiological data intended for reuse in EEG research, following BIDS standards for data organization.
This dataset investigates the neural representation of consciously seen and unseen information, likely using EEG recordings to examine visual consciousness and perception. It is designed to support research into the neural correlates of conscious versus unconscious processing of visual stimuli.
NeuroMorph is a high-temporal resolution MEG dataset designed for morpheme-based linguistic analysis, comprising recordings from 24 subjects totaling over 17 hours of data. Data were collected using a KIT/Yokogawa MEG system to investigate visual language and cognitive processing, with a focus on morphological structure in written language comprehension.
This dataset comprises overnight sleep EEG recordings from 20 healthy participants, collected in spring 2017 as part of a wearable sleep monitoring study at the Surrey Clinical Research Centre. Recordings include full polysomnography (PSG) and around-the-ear cEEGrid measurements, with most subjects having both modalities recorded on the same night. The dataset supports comparison between conventional PSG and wearable cEEGrid sleep staging approaches.
This dataset contains EEG and eye-tracking recordings from 30 participants who searched for objects in naturalistic scenes and intentionally memorized others, followed by a surprise recognition memory test. The study examines the 'search superiority effect,' testing whether incidentally encoded memories differ qualitatively from intentional ones through recollection and familiarity processes indexed by FN400 and late parietal ERP components. Behavioral remember-know judgments and ROC analyses were used alongside EEG measures to disentangle these memory processes.
This dataset comprises multi-night ear-EEG and polysomnography (PSG) recordings collected between 2018 and 2020 to develop and validate ear-EEG as a home-based sleep monitoring platform. Twenty subjects were recorded across four nights with partial PSG, ear-EEG, and actigraphy, while ten of these subjects continued for an additional twelve nights using only ear-EEG, actigraphy, and a single EOG electrode. Supplementary behavioral data include nightly comfort questionnaires, sleep diaries, and actigraphy recordings, providing a rich resource for studying sleep physiology and wearable EEG signal quality.
This dataset comprises overnight ear-EEG recordings from 10 healthy participants, collected between 2020 and 2022 as part of a study on ear-EEG based sleep monitoring. The first two recordings include simultaneous polysomnography (PSG) and ear-EEG measurements, while subsequent nights consist solely of ear-EEG recordings performed at the subjects' homes. The dataset is intended to support development and validation of ear-EEG as a wearable alternative to traditional PSG for sleep staging and monitoring.
Chisco is a Chinese imagined speech EEG dataset collected from five participants, each recorded over 5-6 sessions. The dataset includes raw EEG recordings and preprocessed data (in fif and pkl formats), along with accompanying text stimuli used to elicit imagined speech. It is intended to support research on imagined speech decoding and brain-computer interface applications using EEG signals.
This dataset comprises intracranial EEG (iEEG) recordings from 22 patients undergoing stereo-EEG presurgical evaluation for drug-resistant epilepsy, capturing responses to 115 high-frequency cortical stimulations that evoked visual hallucinations. Each recording includes 21 seconds of iEEG data surrounding each stimulation event, with detailed annotations of stimulation parameters and 14 categories of evoked clinical visual phenomena. The dataset supports investigation of brain networks underlying stimulation-evoked visual symptoms and enables construction of symptom-related activation and connectivity maps.
This dataset comprises EEG recordings from two experiments investigating evoked responses to sounds presented at varying elevations from loudspeakers in a hemi-anechoic chamber. In Experiment I, a deviant detection paradigm was used to examine responses to changes in sound source elevation between an adapter and probe stimulus. In Experiment II, a one-back task assessed elevation discrimination via white noise adaptation and localization judgments, including a subset of subjects tested with sound localization disrupted by ear molds. The dataset also includes behavioral localization test data for most subjects.