Discover datasets

This dataset contains 64-channel EEG recordings from 62 participants (31 pairs) who played a competitive, computerised version of the Rock-Paper-Scissors game across 480 games. The study investigates the neural correlates of competitive decision-making during real-time social interaction. This dataset supports research on neural decoding of strategic choices in a dyadic competitive context.

Participants

31

Channels

64

Citations

6

Size

78.0 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings from 25 college-age participants performing a reinforcement learning task with affective feedback. Collected in 2019 at the University of New Mexico's Clinical Research Center Lab, the data were acquired to investigate the sensitivity of the reward positivity (RewP) component to affective liking during probabilistic learning. This represents Experiment #2 of a study examining neural correlates of reward processing and emotional valuation in decision-making. This is a re-hosted version of OpenNeuro dataset ds003753.

Participants

25

Channels

66 (10-10)

Citations

1

Size

4.62 GB

Version

v1.0.0

Updated

Jul 22, 2026

A large-scale longitudinal dataset of sensorimotor rhythm-based brain-computer interface (BCI) training in 62 healthy adults. The dataset comprises over 600 hours of EEG recordings across 598 sessions with more than 250,000 trials of motor imagery tasks (left hand, right hand, both hands, and rest). This resource enables investigation of BCI learning dynamics and algorithm development for non-invasive neural control applications.

Participants

62

Channels

60 (10-10)

Citations

59

HED

v8.4.0

Size

722 GB

Version

v1.0.4

Updated

Aug 18, 2026

This dataset contains invasive electrophysiological recordings from the human cervical spinal cord in patients with neuropathic pain who had epidural electrodes implanted for pain management. The study investigates whether temporal expectation, manipulated via variable versus fixed cue-to-stimulus intervals, influences initial sensory processing of median nerve stimulation at the level of the spinal cord. Eight patients performed a counting task while receiving auditory cues followed by single or double electric median nerve stimuli.

Participants

8

Size

722 MB

Updated

Aug 19, 2026

This dataset contains electroencephalography (EEG) recordings from a study investigating how expectation modulates repetition suppression of neural responses to nociceptive (pain-related) stimuli. It provides raw EEG data organized in BIDS format, intended to support analyses of expectation effects on cortical processing of repeated nociceptive stimulation.

Participants

36

Channels

32 (10-10)

Size

42.7 GB

Version

v1.0.0

Updated

Aug 19, 2026

An EEG study investigating the effects of episodic future thinking on temporal discounting behavior. Participants generated descriptions of future events and subsequently used mental imagery of these events as cues during intertemporal choice tasks, with concurrent measurement of imagery vividness. This dataset provides neurophysiological recordings during decision-making processes influenced by prospective cognition.

Participants

29

Channels

64 (10-10)

Size

16.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

Imported from OpenNeuro ds004745

Participants

6

Channels

8 (other)

Citations

27

Size

242 MB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises raw magnetoencephalography (MEG) recordings, T1-weighted anatomical MRI scans, and behavioural logfiles collected during an audiovisual speech memory paradigm. Participants performed encoding, distractor, and retrieval tasks designed to probe theta oscillatory dynamics underlying audiovisual integration and memory replay of speech content. The data support analyses of neocortical and hippocampal theta oscillations reported in an associated Journal of Neuroscience publication.

Participants

30

Citations

7

Size

172 GB

Version

v1.0.0

Updated

Aug 19, 2026

A longitudinal EEG dataset from 13 infants recorded at 4, 8, and 12 months of age, comprising 48 recording sessions. The dataset includes test-retest reliability assessments at 4 months (11 infants with complete longitudinal data, 2 infants with reliability data only) and was used to develop and validate APPLESEED, an automated preprocessing pipeline for estimating scale-wise entropy from pediatric EEG data. This example dataset accompanies the 2022 APPLESEED pipeline publication in Developmental Cognitive Neuroscience and demonstrates the application of entropy-based EEG analysis methods in early human development. The dataset is part of a larger longitudinal study initially described in Puglia et al. (2020).

Participants

13

Channels

32 (10-10)

Citations

14

Size

10.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

Imported from OpenNeuro ds003801

Participants

20

Channels

24 (10-10)

Size

1.15 GB

Version

v1.0.0

Updated

Jul 10, 2026