SWEC iEEG Dataset
…at source) - Intracranial strip, grid, and depth electrodes (mixed). - 16-bit analog…
- Participants
- 50
- Citations
- 6
- Size
- 3.85 TB
- Version
- v1.1.0
- Updated
- Oct 7, 2026
…at source) - Intracranial strip, grid, and depth electrodes (mixed). - 16-bit analog…
Intracranial EEG (stereo-EEG) recordings from 22 patients with drug-resistant epilepsy undergoing presurgical evaluation, capturing responses to 115 high-frequency intracranial electrical stimulations that evoked visual hallucinations. Each recording spans 21 seconds around the stimulation, with events annotated by stimulated contact pair, current intensity, and evoked effect, classified into 14 clinical categories. The data support identification of brain networks underlying visual symptoms and creation of symptom-related activation and connectivity maps.
…Electrocorticography (ECoG; grids, strips and in some participants depth electrodes) recorded opportunistically…
…electrodes or 1 week after placement of subdural grids or strips [...] and…
…resistant epilepsy (subdural grids, strips and depth electrodes; Yale New Haven Hospital…
…grids or strips of platinum-iridium electrodes (Ad-Tech Medical, Oak Creek…
ltpDelayRepFRReadOnly is an EEG dataset from Michael Kahana's laboratory, collected with a delayed, repeated-item free recall paradigm. The dataset is organized in BIDS format and distributed as a read-only release. It supports research on human episodic memory and the neural correlates of free recall.
…of 'grid' (4x8 8x8) and strip arrays, numbering between 32 and 81…
TX17 is an EEG dataset formatted according to BIDS with HED annotations, contributed by Johnson, Gordon, Touryan, and King. The README describes it only as a placeholder, so no further details on the experimental paradigm or participants are provided. It is a NEMAR-hosted copy of an OpenNeuro deposit.
EEG recordings from 30 knee pain patients performing a two-class lower-limb motor imagery task (left vs. right leg flexion/extension). Each participant completed 5 sessions of 100 cue-based trials, recorded with a 30-channel system at 500 Hz. The dataset supports brain-computer interface research for rehabilitation and benchmarking of classifiers such as CSP+LDA, FBCSP+SVM and EEGNet.