nm000232
THINGS-EEG2: A large and rich EEG dataset for modeling human visual object recognition
BEH EEG
- Size
- 159 GB
- Updated
- May 16, 2026
Discover datasets
78 results for "stereoelectroencephalography" · page 5 of 8 · ranked by relevance
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- nm000153
Langer et al. 2017 — Multimodal Resource for Studying Information Processing in the Developing Brain (MIPDB)
EEGMIPDB is a multimodal neuroimaging resource comprising high-density EEG and eye-tracking data collected from 111 participants spanning childhood to adulthood. Participants completed a standardized battery of six cognitive and perceptual paradigms (resting state, surround suppression, naturalistic viewing, contrast-change detection, sequence learning, and symbol search) designed to probe information processing maturation across development. This dataset enables investigation of neurodevelopmental trajectories in sensory and cognitive processing.
- Size
- 110 GB
- Updated
- Jun 17, 2026
- ds006547
Visual EEG Study (BrainVision → BIDS)
EEG- Participants
- 31
- nm000134
Alljoined-1.6M
EEG- Citations
- 1
- Size
- 7.75 GB
- Updated
- May 18, 2026
- ds005810
NOD-MEG
MEG MRI- Participants
- 31
- nm000263
Visual object ERP EEG dataset (Kaneshiro et al. 2015)
EEGA high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 trials of photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects) with 72 unique images per category, each presented for 500 ms. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.
- Size
- 469 MB
- Updated
- Jun 23, 2026
- ds005087
rapid-hemifield-object-eeg
EEG- Participants
- 20
- nm000146
Motor Imagery dataset from Weibo et al 2014
EEG- Size
- 1.60 GB
- Updated
- May 25, 2026
- nm000338
Lee et al. 2019 (Motor Imagery) — EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy
EEGA comprehensive EEG dataset comprising 54 healthy subjects performing three major brain-computer interface (BCI) paradigms—motor imagery, event-related potentials, and steady-state visually evoked potentials—across two sessions. The dataset investigates BCI illiteracy rates and performance variations, revealing that motor imagery exhibits the highest illiteracy rate (53.7%) compared to other paradigms, while all participants demonstrated proficiency with at least one BCI system.
- Citations
- 98
- Size
- 60.8 GB
- Updated
- Jun 3, 2026
- ds005586
EEG responses to the number of objects in partially occluded and uncovered scenes
EEG- Participants
- 23