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This dataset comprises intraoperative intracranial EEG recordings from 10 patients undergoing brain tumor resection in the perirolandic region. Median nerve somatosensory evoked potentials (SEP) were recorded simultaneously using two 4-contact ECoG electrode strips with different impedance characteristics (low impedance: 3.4 kΩ and high impedance: 6.9 kΩ) to investigate the efficacy of low-impedance electrodes for detecting high-frequency oscillations in clinical neurophysiology.

Participants

10

Citations

9

Size

1.20 GB

Version

v1.0.0

Updated

Jul 10, 2026

NEMAR Dataset nm000105: discrete_gestures - Discrete hand gesture detection from EMG

Participants

100

Size

20.6 GB

Version

v2.0.0

Updated

Jul 10, 2026

VEPCON is a multimodal neuroimaging dataset comprising high-density EEG, structural MRI, and diffusion-weighted imaging from 20 participants performing visual discrimination tasks (face vs. scrambled faces, coherent vs. incoherent motion). The dataset includes preprocessed EEG single trials, individual brain parcellations at five spatial resolutions, structural connectomes derived from diffusion data, and EEG source imaging solutions based on individual anatomy. This resource supports multimodal methods development, structure-function relationship studies, and optimization of source imaging and graph analysis techniques.

Participants

20

Channels

128 (biosemi)

Citations

24

Size

58.2 GB

Version

v1.0.0

Updated

Jul 22, 2026

Imported from OpenNeuro ds004852

Participants

1

Channels

64 (10-10)

HED

v8.1.0

Size

78.9 MB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises multimodal physiological recordings from 23 healthy adult participants collected during naturalistic smartphone interaction and standardized video viewing conditions. Simultaneous EEG (64-channel), eye-tracking, photoplethysmography (PPG), and galvanic skin response (GSR) data were acquired, synchronized via hardware TTL pulses. The dataset supports research into physiological and neural correlates of smartphone use and passive video viewing.

Participants

23

Channels

64 (10-10)

Citations

1

Size

6.12 GB

Version

v1.0.0

Updated

Aug 18, 2026

A high-density 124-channel EEG dataset comprising event-related potentials (ERPs) from 10 healthy participants during a visual object recognition task. Participants viewed 5,184 photographs from six object categories (human body, human face, animal body, animal face, fruit/vegetable, and inanimate objects), with 72 photographs per category, presented for 500 ms each. The dataset is suitable for investigating neural representations of object categories through single-trial EEG classification and representational similarity analysis.

Participants

10

Channels

124 (egi-geodesic)

Citations

93

HED

v8.4.0

Size

3.40 GB

Version

v1.0.3

Updated

Aug 18, 2026

2417 clinical EEG recordings, 19-ch 10-20 montage, normal/abnormal labels. EDF format. Zenodo DOI:10.5281/zenodo.10909103

Participants

2417

Channels

21 (10-20)

Size

13.8 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings from participants performing a novel instruction-following task and an accompanying 1-back localizer task, designed to investigate how complex task instructions are represented and implemented in the brain. Each participant completed a single session including 16 blocks of the main instruction-following task, requiring integration or selection of visual features across sequential instruction screens, and 8 blocks of a localizer task. The dataset is intended to support research on instruction-based cognitive control and rule representation.

Participants

41

Channels

63 (10-10)

Citations

5

Size

57.7 GB

Version

v1.0.0

Updated

Aug 19, 2026

THINGS-EEG2 is a large-scale EEG dataset comprising recordings from 10 subjects viewing 16,540 distinct training images and 200 test images presented via rapid serial visual presentation at 5 Hz. The dataset includes 63-channel EEG data sampled at 1000 Hz across 4 sessions per subject, with approximately 32,540 training trials and 16,000 test trials, designed to support computational modeling of human visual object recognition. Stimuli are drawn from the THINGS database, and the dataset includes resting-state recordings and behavioral annotations for each trial.

Participants

10

Channels

63 (10-10)

Citations

82

Size

198 GB

Version

v1.1.0

Updated

Jul 10, 2026

This multimodal dataset comprises EEG, ECG, and pupillometry recordings from participants performing an n-back working memory task at four difficulty levels (1-back through 4-back). Data were collected using a combined mobile EEG+ECG system synchronized with a Pupil Labs eye tracker via Lab Streaming Layer, and converted from raw XDF recordings into BIDS format. The dataset is intended to support research on cognitive workload assessment across multiple physiological modalities.

Participants

18

Channels

19 (10-20)

Size

2.13 GB

Version

v1.0.0

Updated

Aug 19, 2026