Discover datasets

This dataset examines the effects of theta transcranial alternating current stimulation (tACS) on working memory performance and associated EEG activity. Participants received either verum or sham 20-minute tACS at 1 mA and 6 Hz over Fpz-CPz, followed by working memory tasks requiring mental manipulation or retention of memory items, while EEG was recorded. Resting-state EEG (eyes closed and eyes open) was also collected prior to the working memory task.

Participants

25

Channels

129 (egi-geodesic)

Citations

3

Size

61.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This open-access EEG dataset comprises multi-session, multi-task recordings from 15 healthy participants performing resting state and graded difficulty levels of the MATB-II task. Acquired at 500 Hz using 62 active electrodes, the dataset includes 90 trials per participant across two sessions and is designed to support passive brain-computer interface research and mental workload estimation in neuroergonomic applications.

Participants

15

Channels

61 (10-10)

Citations

64

HED

v8.4.0

Size

4.04 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset comprises EEG recordings from 15 healthy subjects performing six different upper limb movements (elbow flexion/extension, forearm supination/pronation, hand open/close) and rest conditions in both movement execution and motor imagery modalities. The study investigates neural encoding of individual upper limb movements using low-frequency EEG signals (0.3-3 Hz) and achieves classification accuracies of 55-87% for executed movements and 27-73% for imagined movements. Source localization analysis identifies discriminative movement information in premotor areas, primary motor cortex, somatosensory cortex, and posterior parietal cortex, with applications toward non-invasive control of motor neuroprostheses and robotic arms.

Participants

15

Channels

61 (10-05)

Citations

94

HED

v8.4.0

Size

34.0 GB

Version

v1.0.3

Updated

Aug 18, 2026

Imported from OpenNeuro ds003380

Participants

12

Size

1.43 GB

Version

v1.0.0

Updated

Jul 10, 2026

BCIComp2020UpperLimb is a preprocessed EEG dataset from BCI Competition 2020 Track 4 containing motor imagery recordings of three grasping tasks (cylindrical, spherical, lumbrical) from 15 healthy subjects across three sessions. The dataset comprises 60-channel EEG data sampled at 250 Hz with 450 trials per subject (150 trials per session across 3 sessions), designed to evaluate session-to-session transfer learning in brain-computer interface applications. Data were preprocessed with 60 Hz notch filtering and cue-aligned epoching, with the 4-second motor imagery window extracted for analysis.

Participants

14

Channels

60 (10-10)

Citations

73

HED

v8.4.0

Size

2.76 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset contains EEG recordings from 16 participants viewing object images presented in eight different 2-D rotations, using rapid visual streams at two presentation rates (5 Hz and 20 Hz). The data support investigation of rotation-tolerant object representations and the time course of high-level visual object processing. EEG data are formatted according to the BIDS standard.

Participants

16

Size

18.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

Imported from OpenNeuro ds004745

Participants

6

Channels

8 (other)

Citations

27

Size

242 MB

Version

v1.0.0

Updated

Jul 10, 2026

This high-density functional near-infrared spectroscopy (fNIRS) dataset comprises neuroimaging recordings from the motor cortex during three experimental paradigms: resting state, ball-squeezing motor tasks (both hands performed sequentially), and purposeful motion artifact creation. The dataset includes concurrent accelerometer measurements and is designed to support the development and validation of motion artifact correction algorithms in fNIRS neuroimaging.

Participants

12

Size

572 MB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains electroencephalogram (EEG), galvanic skin response (GSR), and electrocardiogram (ECG) recordings from 19 healthy adult participants during a calibration session of an affective brain-computer music interface system. Participants listened to 40-second synthetic music clips designed to induce specific affective states defined by valence and arousal dimensions across 5 runs of 18 trials each. The synthetic music was generated in real-time based on target emotional states and could be modified online to induce target emotional states. The dataset includes self-reported affective state ratings and auxiliary variables, serving as calibration data for the brain-computer music interface system. This dataset is part of a three-dataset collection that includes offline training and online real-time control sessions.

Participants

19

Channels

32 (10-10)

Size

6.10 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains cue-locked EEG recordings and behavioral event annotations from 43 healthy adults performing a random-dot kinematogram (RDK) task designed to dissociate low-level and high-level hierarchical priors during perceptual decision-making. The study examines how such priors bias behavior via signal detection theory and generalized drift-diffusion modeling, and how they modulate occipital oscillatory and aperiodic EEG activity. Participants also completed questionnaires assessing psychosis proneness and psychological flexibility traits.

Participants

43

Channels

31 (10-10)

Size

8.76 GB

Version

v1.0.0

Updated

Aug 18, 2026