on007119
iEEG_comprehensive_HFA_model_part3
iEEG Zarr
…nemar.on007119) This dataset contains intracranial EEG data recorded during non-REM…
- Participants
- 103
- Size
- 32.6 GB
- Version
- v1.0.0
- Updated
- Jun 30, 2026
Discover datasets
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- on007118
iEEG_comprehensive_HFA_model_part1
iEEG Zarr…nemar.on007118) This dataset contains intracranial EEG data recorded during non-REM…
- Participants
- 65
- Size
- 33.8 GB
- Version
- v1.0.0
- Updated
- Jun 30, 2026
- nm000345
Castillos et al. 2023, Burst c-VEP, 40% amplitude depth: Burst c-VEP Based BCI: Optimizing stimulus design for enhanced classification with minimal calibration data and improved user experience
EEG ZarrEEG recordings from 12 healthy participants performing an offline 4-class reactive BCI task based on code-modulated visual evoked potentials (c-VEP). The dataset covers the 'Burst c-VEP' condition at 40% amplitude depth, in which short bursts of aperiodic flashes are presented at 2-4 flashes per second. It supports work on stimulus design, visual comfort, and CNN-based bitwise decoding with minimal calibration data.
- Participants
- 12
- Channels
- 32 (10-10)
- Citations
- 18
- HED
- v8.4.0
- Size
- 337 MB
- Version
- v1.0.3
- Updated
- Oct 8, 2026
- on006394
Electrophysiological markers of surprise-induced failures of visual and auditory awareness
BEH EEG ZarrEEG recordings from 33 participants who each completed both a visual and an auditory surprise task, with task order counterbalanced. The dataset supports investigation of electrophysiological markers of surprise-induced failures of visual and auditory awareness. Data from participants excluded at various analysis stages are included up to the stage of processing they reached.
- Participants
- 33
- Channels
- 16 (10-20)
- Size
- 535 MB
- Version
- v1.0.0
- Updated
- Jun 28, 2026
- nm000362
MNI Open iEEG Atlas: normal intracranial EEG in wakefulness and sleep (processed 200 Hz atlas clips)
iEEG…normal intracranial EEG in wakefulness and sleep (processed 200 Hz clips) ## Overview…
- Participants
- 106
- Size
- 3.19 GB
- Version
- v1.0.0
- Updated
- Oct 8, 2026
- on006317
Chisco-2.0
EEG ZarrChisco-2.0 is an EEG dataset of imagined speech recorded from two participants (sub-01 and sub-02). The raw recordings are provided in EDF format and organized according to the BIDS standard. The dataset is intended to support research on decoding imagined speech from brain activity.
- Participants
- 2
- Channels
- 124 (10-05)
- Size
- 52.9 GB
- Version
- v1.0.0
- Updated
- Jun 28, 2026
- nm000432
Human subthalamic nucleus LFP and prefrontal subdural recordings during a working-memory encoding decision task (Zavala, Jang & Zaghloul, 2018) - derivative
iEEGIntraoperative recordings from 18 patients with Parkinson's disease undergoing subthalamic nucleus (STN) deep brain stimulation surgery, combining macroelectrode LFP from STN trajectories with subdural strip recordings over anterior and lateral prefrontal cortex. Participants performed a working-memory encoding task, viewing eight sequential digits and remembering only those inside a target shape. This derivative release contains band-passed, notch-filtered, downsampled and re-referenced iEEG data in BIDS format with trial-level events.
- Participants
- 18
- Size
- 8.09 GB
- Version
- v1.0.0
- Updated
- Oct 13, 2026
- nm000472
Zenodo-22150094: example stereo-EEG (sEEG) recording with one clinically confirmed seizure
iEEG…of one patient during clinical intracranial monitoring, released on Zenodo by "AI…
- Participants
- 1
- Size
- 709 MB
- Version
- v1.0.0
- Updated
- Oct 13, 2026
- nm000342
Castillos et al. 2023, m-sequence c-VEP, 40% amplitude depth: Burst c-VEP Based BCI: Optimizing stimulus design for enhanced classification with minimal calibration data and improved user experience
EEG ZarrEEG recordings from 12 healthy participants performing an offline 4-class code-modulated visual evoked potential (c-VEP) reactive BCI task. This subset contains the m-sequence condition at 40% amplitude depth, from a factorial study that compared burst and m-sequence codes at 100% and 40% modulation depth. The dataset supports evaluation of CNN-based decoding with minimal calibration data and of the visual comfort of reduced-intensity stimuli.
- Participants
- 12
- Channels
- 32 (10-10)
- Citations
- 19
- HED
- v8.4.0
- Size
- 340 MB
- Version
- v1.0.3
- Updated
- Oct 8, 2026
- on004789
Delayed Free Recall of Word Lists
BEH iEEG Zarr…dataset contains behavioral events and intracranial electrophysiological recordings from a delayed free…
- Participants
- 280
- Size
- 576 GB
- Version
- v1.0.0
- Updated
- Jun 25, 2026