on003194
Neuroepo multisession
EEG
Imported from OpenNeuro ds003194
- Participants
- 15
- Channels
- 19 (10-20)
- Size
- 189 MB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
Discover datasets
70 results for "affective computing" · page 7 of 7 · ranked by relevance
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- nm000255
The Brain, Body, and Behaviour Dataset (1.0.0) - Experiment 2
BEH EEGThe Brain, Body, and Behaviour Dataset (Experiment 2) is a multimodal neurophysiological dataset comprising 31 subjects across 2 sessions designed to investigate incidental learning and attentional modulation. Participants watched five educational videos under attentive and distracted conditions while simultaneous recordings of EEG, ECG, EOG, eye-tracking, and pupil dynamics were acquired. This derivative dataset includes preprocessed physiological signals and behavioral responses to memory questionnaires, providing a comprehensive resource for studying the neural and physiological correlates of attention, learning, and cognitive load.
- Participants
- 31
- Channels
- 64 (10-10)
- Size
- 5.23 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- nm000132
ERP CORE
EEG Zarr verified- Participants
- 40
- Channels
- 30 (10-10)
- Citations
- 92
- HED
- v8.4.0
- Size
- 17.5 GB
- Version
- v1.1.1
- Updated
- Jul 10, 2026
- on004067
Moral conviction and metacognitive ability shape multiple stages of information processing
EEGThis dataset comprises human electroencephalography (EEG) recordings from 80 participants engaged in a moral decision-making task. Participants evaluated their attitudes toward sociopolitical issues, then viewed protest photographs with varying levels of indicated social support, followed by judgments of support for the protesters. The study investigates how moral conviction and metacognitive ability influence information processing across multiple cognitive stages.
- Participants
- 80
- Citations
- 1
- Size
- 101 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026
- on007322
Personalized smartphone notifications bias auditory salience across processing stages
EEGThis dataset contains EEG recordings from an auditory oddball paradigm designed to investigate how personalized smartphone notification sounds bias auditory salience processing at different neural processing stages. The study examines attentional and perceptual effects of self-relevant notification stimuli compared to standard oddball tones. This resource enables analysis of event-related potentials associated with salience detection and personalized auditory cues.
- Participants
- 57
- Channels
- 64 (10-10)
- Size
- 42.5 GB
- Version
- v1.0.0
- Updated
- Aug 18, 2026
- nm000343
Hinss et al. 2021 — Open multi-session and multi-task EEG cognitive Dataset for passive brain-computer Interface Applications
EEGThis open-access EEG dataset comprises multi-session, multi-task recordings from 15 healthy participants performing resting state and graded difficulty levels of the MATB-II task. Acquired at 500 Hz using 62 active electrodes, the dataset includes 90 trials per participant across two sessions and is designed to support passive brain-computer interface research and mental workload estimation in neuroergonomic applications.
- Participants
- 15
- Channels
- 61 (10-10)
- Citations
- 64
- HED
- v8.4.0
- Size
- 4.04 GB
- Version
- v1.0.3
- Updated
- Aug 18, 2026
- on004194
Visual ECoG dataset
ANAT iEEGThis dataset comprises intracranial EEG (ECoG) recordings from 14 epilepsy patients implanted with subdural grid and depth electrodes, collected while they viewed grayscale and color visual stimuli varying in spatial and temporal properties. The recordings were designed to characterize temporal and spatial dynamics of neural responses in human visual cortex, including population receptive field mapping and category-selective responses. Pre-implantation T1-weighted MRI scans are also included for electrode localization. The dataset supports multiple published studies on visual cortical dynamics and adaptation.
- Participants
- 14
- Citations
- 61
- Size
- 57.9 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on005383
TMNRED, A Chinese Language EEG Dataset for Fuzzy Semantic Target Identification in Natural Reading Environments
EEGTMNRED 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.
- Participants
- 30
- Channels
- 30 (10-10)
- Citations
- 1
- Size
- 17.4 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004196
Bimodal dataset on Inner speech
ANAT EEG FMAP FUNCThis dataset provides bimodal EEG and fMRI recordings acquired non-simultaneously during an inner-speech production task. Four healthy, right-handed participants silently produced eight words drawn from two semantic categories (social and numerical) across multiple trials. The dataset aims to support the development of speech prostheses and brain-computer interfaces by enabling multimodal fusion of high temporal (EEG) and high spatial (fMRI) resolution neuroimaging data.
- Participants
- 4
- Channels
- 64 (10-10)
- Citations
- 27
- Size
- 9.33 GB
- Version
- v1.0.0
- Updated
- Aug 19, 2026
- on004107
MIND DATA
ANAT MEGThis magnetoencephalography (MEG) dataset comprises neuroimaging data collected to establish standardized protocols for cross-site pooling of MEG data. The dataset demonstrates the application of BIDS formatting to MEG neuroimaging, facilitating data harmonization and reproducible analysis across multiple research institutions.
- Participants
- 9
- Citations
- 17
- Size
- 77.2 GB
- Version
- v1.0.0
- Updated
- Jul 10, 2026