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This dataset comprises EEG recordings from 39 Italian-speaking participants performing a picture-matching task under four cue conditions (Physical, Imagery, Literal, and Metaphorical), designed to investigate how mental representations generated by verbal and non-verbal cues influence the processing of subsequent target pictures. The study, part of the ERC-funded PROMENADE project, focuses on the neurocognitive processing of metaphorical versus literal language and mental imagery. EEG data were collected in long epochs around target picture onset, alongside behavioral accuracy and questionnaire-based measures of vocabulary and imagery ability.

Participants

39

Channels

58 (10-10)

Size

14.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Donders Institute for Brain, Cognition and Behaviour - **Country**: NL - **Repository**: Radboud - **Data…

Participants

30

Channels

8 (10-10)

Citations

66

HED

v8.4.0

Size

3.16 GB

Version

v1.0.4

Updated

Aug 18, 2026

This dataset contains magnetoencephalography (MEG) recordings from 20 adult participants examining the neural mechanisms underlying perception of regular geometric shapes such as hexagons, triangles, and quadrilaterals. The study investigates how geometric regularity modulates brain activity in ventral visual, intraparietal, and inferior temporal regions, and compares neural responses to predictions from convolutional neural networks and transformer vision models. A companion fMRI dataset examining the same phenomenon is shared separately.

Participants

21

Citations

13

Size

71.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

…Donders Center for Cognition - **Country**: NL - **Repository**: GitHub - **Data URL**: https://public…

Participants

12

Channels

64 (10-10)

Citations

72

HED

v8.4.0

Size

11.0 GB

Version

v1.0.3

Updated

Aug 18, 2026

This dataset comprises 64-channel EEG recordings from 7 participants performing an auditory imagery task, in which they imagined sounds associated with animals and tools following visual stimulus cues. The dataset is intended to support research on semantic decoding of imagined auditory content and brain-computer interface applications.

Participants

7

Channels

64 (10-10)

Size

12.7 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

This dataset comprises electroencephalography (EEG) recordings from 13 participants performing semantic imagination and perception tasks across visual and auditory modalities. Participants were presented with stimuli from three semantically dissimilar categories (guitar, flower, penguin) in pictorial, orthographic, and auditory formats. The dataset includes raw, preprocessed, and epoched EEG data acquired using a 124-channel ANT-Neuro system, providing a resource for investigating neural correlates of semantic processing and cross-modal perception.

Participants

12

Channels

124 (10-05)

Citations

1

Size

79.1 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings collected using the CorTec BrainInterchange implantable device and the BCI2000 software platform, developed as part of an ecosystem of technology and protocols for adaptive neuromodulation research in humans. The data support research into closed-loop neuromodulation approaches and adaptive brain-computer interface systems. Recordings were obtained under IACUC-approved protocols in collaboration with Mayo Clinic and academic partners.

Participants

3

Size

19.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

Imported from OpenNeuro ds005028

Participants

11

Citations

2

Size

1.46 GB

Version

v1.0.0

Updated

Jul 10, 2026

TMNRED is an EEG dataset collected from 30 healthy, right-handed native Chinese speakers performing a natural reading task designed to investigate fuzzy semantic target identification. Participants read Chinese news headlines and short sentences containing target and non-target semantic items while EEG was recorded across 8 blocks of 400 trials each. The dataset supports research into semantic processing mechanisms during naturalistic reading in the Chinese language.

Participants

30

Channels

30 (10-10)

Citations

1

Size

17.4 GB

Version

v1.0.0

Updated

Aug 19, 2026