Electrocorticography (ECoG) recordings from 20 C57BL/6 mice in three cohorts: blinking light only, transcranial diagnostic ultrasound (tDUS) only, and combined tDUS with light. The dataset was collected to test how tDUS modulates the visual cortex's response to external visual stimulation. It includes raw, event-triggered, and processed ECoG data.
EEG dataset from the PROTEUS brain-computer interface (BCI) project in Bordeaux, released for the EEG/EMG Foundation Challenge 2026 (Track 02). It contains recordings from 10 participants across 14 sessions (112 runs) performing three cued mental tasks: kinesthetic motor imagery, mental subtraction and word generation. Runs include resting baselines, calibration runs with sham feedback and online runs with real feedback, using Graz and BrainHero interfaces.
An EEG dataset from the NeuroTechs group, collected in the context of STEM (science, technology, engineering and mathematics) skills. Recordings were acquired with a Unicorn wearable EEG system through its Python API, and values are provided in microvolts. The dataset is organized according to BIDS with HED annotations.
EEG dataset investigating proactive selective attention across different competition contexts. The dataset is mirrored on NEMAR from OpenNeuro (ds005089) and organized in BIDS format.
MEG dataset from 22 participants performing a visual working memory task in which two Gabor stimuli were presented and a retro-cue indicated which stimulus and attribute to maintain for comparison with a probe. Each participant was recorded in two MEG sessions, with a one-back control task and anatomical T1 MRI. The data support investigation of the distinct brain mechanisms of selecting and maintaining information in working memory.
EEG recordings from a Probabilistic Selection Task (PST) collected in two studies: 80 healthy participants plus 5 pilot placebo sessions, and a double-blind cabergoline (1.25 mg) challenge study with 27 completers. Data were collected circa 2012-2013 at Brown University and share a sample with a previously published study on conflict as an implicit cost in reinforcement learning. The dataset supports research on reinforcement learning, dopamine, and feedback processing.
This fNIRS dataset captures brain oxygenation changes during exercise-induced hypoalgesia in 22 endurance athletes and 20 non-athletes. Participants completed high-intensity interval training (HIIT) and pressure pain tests while oxyhemoglobin was recorded over the prefrontal, sensorimotor and posterior parietal cortices. The data support comparisons of athlete and non-athlete neural responses to exercise and pain, and how these relate to pain perception.
This dataset contains EEG recordings from 19 healthy participants from Study B of the bigP3BCI collection. Participants used a P300-based speller with a 6x6 checkerboard character grid over 8 sessions each. Data were recorded from 16 EEG channels at 256 Hz with a g.USBamp and annotated with HED tags for target and non-target events. The dataset is a MOABB-derived version of the bigP3BCI resource hosted on PhysioNet.
Stereo-EEG recordings from six patients with medically refractory epilepsy performing a scene recognition memory task with concurrent EyeLink eye tracking. The dataset accompanies a study of how the human hippocampus rapidly coordinates effective learning, and is a lossless iEEG-BIDS re-packaging of the authors' public Zenodo release. It includes electrode MNI coordinates, behavioural arrays, eye-tracking files and the authors' analysis code in sourcedata.
Simultaneous EEG-fMRI dataset from 18 participants who played two games (a face game and a maze game) during wakefulness in a 3T MRI scanner. One game was randomly assigned to be won (reward) and the other lost (no reward). Participants then slept in the scanner with 64-channel EEG for 1-2 hours. A classifier trained on game-session data was applied to sleep-session fMRI to examine reward-biased spontaneous neural reactivation, and memory for both tasks was tested the next day.