Discover datasets

The RECAP-EEG dataset provides resting-state electroencephalography recordings from 21 neurotypical undergraduate students collected before and after different study interventions (active retrieval practice, passive review, and control conditions) at the Federal University of Paraíba, Brazil. The dataset aims to support research into the neural correlates of learning, retrieval practice, and educational neuroscience. Recordings include pre- and post-intervention resting-state EEG with eyes-open and eyes-closed blocks.

Participants

21

Channels

31

Citations

1

Size

1.32 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings from 30 participants who performed a Multiple Object Monitoring (MOM) task, designed to investigate attentional tracking of multiple moving objects. The data were collected to examine the neural correlates underlying dynamic attention allocation and object monitoring processes. The dataset is intended for use in cognitive neuroscience research on visual attention and working memory.

Participants

30

Size

11.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

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 27 healthy adult subjects investigating the interaction of pitch and time in music encoding using 'chimeric music' stimuli that recombine pitch contours and note onset-times from two distinct melodies. Data were collected between September and November 2023 at the University of Rochester, with participants exposed to original and chimeric monophonic music clips alongside click trains during a two-phase experiment. The dataset is formatted according to the EEG-BIDS standard and includes raw BrainVision format EEG data.

Participants

27

Channels

34 (10-10)

Size

193 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings collected from a three-electrode forehead patch device (CGX) designed to validate automated spectral sleep staging against manual polysomnography-based scoring. Each recording includes both a visual hypnogram (manual sleep stage scoring in 30-second epochs) and spectral staging derived from the forehead patch channels. The dataset supports research into simplified, wearable EEG-based sleep monitoring as an alternative to standard multi-channel polysomnography.

Participants

19

Channels

3 (other)

Citations

6

Size

9.36 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises 64-channel EEG recordings and behavioural ratings from 47 participants who read and evaluated 210 short English-language texts, including Haiku, Senryu, and non-poetic Control texts. Each text was rated on five subjective dimensions: Aesthetic Appeal, Vivid Imagery, Being Moved, Originality, and Creativity. The dataset supports research into the neural and cognitive processes underlying aesthetic and creative engagement with poetic language, and includes resting-state EEG segments recorded before and after the experimental session.

Participants

47

Channels

64 (10-10)

Size

45.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains 64-channel EEG recordings and behavioural ratings from 4 participants who read and evaluated English-language poetic and non-poetic texts (Haiku, Senryu, and Control). It is a supplementary companion to Poetry Assessment EEG Dataset 1, including participants whose EEG data were acquired in segmented sessions and later concatenated, excluded from primary PSD analyses but retained for completeness. The study investigates neural and psychological correlates of aesthetic appreciation, emotional response, and creativity judgments in response to poetic language.

Participants

4

Channels

64 (10-10)

Size

4.29 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises simultaneous EEG and eye-tracking recordings from 21 participants performing a matrix-based brain-computer interface (BCI) typing task using a single-character-presentation paradigm. Data were collected at Northeastern University in 2023 using the BciPy software platform, including calibration and copy-spelling sessions with event markers for target and non-target stimuli. The dataset supports research on multimodal sensor fusion for EEG-based BCI typing systems.

Participants

21

Channels

19 (10-20)

Size

616 MB

Version

v1.0.0

Updated

Aug 19, 2026

This multimodal dataset contains fMRI and EEG data from 69 participants examining the role of REM sleep in the neural differentiation of hippocampal memory representations. Each participant completed three fMRI scan sessions and one EEG session, during which either nap-based sleep or quiet wakefulness data were recorded depending on experimental condition. The dataset supports investigation of how sleep-related neural processes contribute to memory consolidation and differentiation in the hippocampus.

Participants

69

Channels

64 (other)

Citations

2

Size

650 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains continuous 64-channel scalp EEG recordings from 12 right-handed subjects performing a visual attention task designed to examine dimension-based attentional modulation of early visual processing. The data include independent component analysis (ICA) decompositions with expert-annotated component labels, originally collected for a study on visual attention and later reused for research on automatic classification of independent components. The dataset was converted to BIDS format from the original recordings with permission from the original authors.

Participants

12

Channels

64 (10-10)

Citations

35

Size

5.63 GB

Version

v1.0.0

Updated

Aug 19, 2026