Discover datasets

This dataset comprises EEG recordings from two patients with chronic post-stroke anomia who underwent an 8-week individualized transcranial alternating current stimulation (tACS) intervention. Using a single-case experimental design with alternating stimulation and non-stimulation phases, the study investigated whether personalized tACS guided by individual EEG profiles could enhance naming abilities through cortical entrainment. EEG data were collected during picture naming tasks at weekly intervals, with behavioral and electrophysiological measures assessed across 24 naming sessions and 6 EEG recording sessions per participant.

Participants

2

Channels

32 (10-10)

Size

1.09 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises high-density EEG recordings from 15 healthy young adults during treadmill walking at multiple speeds (0.0–1.6 m/s) with intermittent visual occlusions induced by liquid crystal lens goggles. The study investigates neurophysiological responses to visual processing disruptions during gait by measuring electrocortical alpha synchronization. Concurrent recordings include EMG, ground reaction forces, and inertial measurement unit data to characterize the sensorimotor context of visual processing during locomotion. NOTE: This dataset represents a subset of a larger protocol containing 13 additional conditions. Some participants have incomplete or missing Loadsol insole sensor data (sub-05, sub-06, sub-07) and IMU data (sub-02, sub-04, sub-06, sub-12). One participant (sub-01) is missing part of the noise sensor array.

Participants

15

Channels

120 (other)

Size

3.31 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 84 healthy participants performing motor imagery tasks across multiple controlled environments (laboratory and simulated hospital), with a supplementary cohort of 3 participants recorded in microgravity conditions in a space station environment. The dataset includes multiple motor imagery paradigms (Graz, SSMVEP-MI, and hybrid variants) with 64-channel EEG recordings at 1000 Hz sampling rate (69 channels acquired, 60 channels used in analysis), designed to investigate environmental effects on brain-computer interface performance and enable cross-environment robustness evaluation. This dataset is a republication of OpenNeuro ds007221 on the NEMAR platform to enhance accessibility and discoverability within the neuroimaging research community.

Participants

84

Channels

69 (10-10)

Size

143 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This multi-session dataset comprises simultaneous EEG-fMRI recordings from 24 healthy adults (ages 18-35) performing a sustained attention task (GradCPT) and resting state with online experience sampling. The dataset includes 31-channel cortical EEG (plus 4 carbon wire loop sensors and 1 ECG channel for a total of 36 recorded channels) with carbon wire loop sensors for artifact removal, concurrent fMRI, ECG, behavioral responses, and multi-dimensional experience sampling ratings assessing thought contents and processes. Approximately 1 hour 20 minutes of data were collected per participant per session across two sessions, enabling investigation of neural correlates of spontaneous cognitive processes including mind-wandering and attentional fluctuations. All structural MRI images were defaced for privacy. Note: One session (sub-003_ses-001) contains incomplete data collection with 3 runs instead of the standard 4 runs due to time constraints.

Participants

24

Channels

31 (10-10)

Size

115 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises resting-state and task-based EEG recordings from 100 participants designed to investigate hemispheric asymmetries in electroencephalographic activity. The study examines the association between N1 lateralization and alpha asymmetry across multiple cognitive domains including word recognition, face processing, emotion perception, and visual object categorization. Participants completed approximately 8 minutes of resting-state EEG with alternating eyes-open and eyes-closed periods, followed by four randomized tasks involving stimulus-response paradigms with counterbalanced hand responses.

Participants

100

Channels

32 (10-10)

Size

11.0 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This multimodal dataset comprises synchronized EEG, ECG, and pupillometry recordings from 18 participants performing an n-back working memory task with four difficulty levels (1-back through 4-back). The study employed a combined mobile EEG+ECG system and Pupil Labs eye tracker synchronized via Lab Streaming Layer, capturing cognitive workload modulation across task difficulty. Raw XDF recordings were converted to BIDS format with EEG in BrainVision format, pupil data exported as TSV files, and task events aligned to EEG start time. The dataset includes 19-channel EEG at 250 Hz, 3-lead ECG, and asynchronous pupil tracking, with detailed task event annotations and participant exclusion metadata.

Participants

18

Channels

19 (10-20)

Size

2.13 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This EEG dataset contains neural recordings from 34 participants performing a visual object recognition task using a curated stimulus set of 242 images (121 challenge and 121 control images). Participants viewed sequences of 14 images presented for 200 ms each with 100 ms interstimulus intervals and performed a detection task. The dataset includes time-resolved decoding analyses examining adaptive recruitment of cortical recurrence mechanisms during visual object recognition.

Participants

34

Channels

63 (10-10)

Size

59.6 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings acquired during non-REM sleep from patients undergoing clinical monitoring. The data were collected to investigate high-frequency activity patterns and develop comprehensive models of neural oscillations during sleep, contributing to understanding of intracranial electrophysiology and sleep neuroscience.

Participants

65

Size

33.0 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings acquired during non-REM sleep from patients undergoing clinical monitoring. The data were collected to investigate high-frequency activity patterns and develop comprehensive models of neural oscillations during sleep, as described in Hatano et al. (in press). This represents part 3 of a multi-part iEEG high-frequency activity modeling study.

Participants

103

Size

32.6 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings acquired during non-REM sleep from multiple subjects. The data were collected to develop and validate a comprehensive model of high-frequency activity (HFA) in epilepsy research. This represents part 1 of a multi-part dataset designed to characterize neural oscillations and their clinical significance during sleep states.

Participants

65

Size

33.8 GB

Version

vv1.0.0

Updated

Jul 10, 2026