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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 contains electroencephalogram (EEG) recordings from 19 healthy participants using a brain-computer music interface designed to enable real-time control of musical tempo through motor imagery. Participants performed kinesthetic motor imagery tasks—imagining squeezing a ball to increase tempo or relaxing to decrease tempo—across nine experimental runs including a calibration phase. The data were collected at 1 kHz sampling rate with 20-second epochs synchronized to music clips, providing a resource for investigating the neural correlates of intentional tempo modulation and music-based brain-computer interface design. This dataset accompanies the publication by Daly et al. (2018). Full methodological details are available in Daly et al. (2014a, 2014b).

Participants

18

Channels

19 (10-20)

Size

2.39 GB

Version

v1.0.0

Updated

Jul 10, 2026

…The proposed language recruited bilateral superior temporal, precentral, anterior intraparietal and cerebellar…

Participants

19

Citations

5

Size

23.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset presents multimodal simultaneous fMRI/EEG data collected from participants performing an auditory category learning task, alongside resting-state fMRI scans. Each dataset includes 63-channel EEG with additional ECG, EOG, facial EMG, and skin conductance recordings, a physiological file capturing respiration and finger-pulse signals, and structural MRI (T1-weighted and PD-weighted UTE) scans for anatomical reference and electrode localization. Collected at the Combinatorial NeuroImaging core facility of the Leibniz Institute for Neurobiology, the data support research into multi-dimensional auditory category learning and its neural correlates.

Participants

34

Channels

72 (10-10)

Citations

9

Size

6.43 GB

Version

v1.0.0

Updated

Aug 19, 2026

…software filter in the opposite temporal direction. (This is the same strategy…

Participants

32

Channels

62 (10-10)

Size

136 GB

Version

v1.0.0

Updated

Aug 19, 2026

A comprehensive EEG database containing electroencephalographic signals from 87 healthy participants performing motor imagery brain-computer interface tasks. The dataset comprises over 20,800 trials (~70 hours of recording) organized into three datasets (A, B, C) using a standardized Graz protocol for right and left hand motor imagery. In addition to raw EEG signals, the database includes detailed participant demographics, personality profiles, cognitive traits, and BCI performance metrics, enabling research on user-performance relationships, cross-user machine learning algorithms, and profile-informed signal classification.

Participants

87

Channels

27 (10-10)

Citations

38

HED

v8.4.0

Size

15.8 GB

Version

v1.0.4

Updated

Aug 18, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on004276-blue…

Participants

19

Citations

1

Size

11.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

…tracking data streams, enabling precise temporal alignment across all modalities. EEG event…

Participants

23

Channels

64 (10-10)

Citations

1

Size

6.12 GB

Version

v1.0.0

Updated

Aug 18, 2026

…relationship between intrinsic brain spatio-temporal dynamics and Executive Functions. To do…

Participants

165

Channels

64 (biosemi)

Citations

16

Size

6.41 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises simultaneous EEG and fMRI recordings from 10 subjects performing motor imagery and neurofeedback tasks. Participants completed six runs including motor localization, pre- and post-neurofeedback motor imagery, and three neurofeedback conditions (bimodal EEG-fMRI, unimodal EEG, and unimodal fMRI). The dataset provides both raw and preprocessed EEG data (64 channels at 5 kHz), structural and functional MRI data (3T Siemens, 2×2×4 mm³ resolution), and computed neurofeedback scores, enabling multi-modal neuroimaging data integration studies.

Participants

10

Size

18.0 GB

Version

v1.0.0

Updated

Jul 10, 2026