Discover datasets

THINGS-MEG is a large-scale magnetoencephalographic dataset comprising neural recordings from participants viewing thousands of photographic images representing 1,854 object concepts from the THINGS database. This dataset is part of the multimodal THINGS-data collection, which integrates MEG recordings with behavioral judgments and complementary neuroimaging modalities to enable comprehensive investigation of visual and semantic object processing. The dataset includes structural MRI for source localization and eye-tracking data, providing rich temporal and spatial dynamics of object representations across the brain.

Participants

5

Size

1.05 TB

Version

vv1.0.0

Updated

Jul 22, 2026

This dataset comprises behavioral and neuroimaging data from twenty participants who learned to produce and perceive three distinct temporal intervals through interleaved production and perception tasks. Participants either produced temporal intervals or judged computer-generated intervals as correct or incorrect, receiving visual feedback. The study investigates temporal cognition and interval learning mechanisms.

Participants

20

Channels

37 (10-10)

Size

7.21 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This bimodal neuroimaging dataset combines electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data acquired during inner-speech production tasks. The dataset includes recordings from four healthy participants performing inner-speech tasks with eight words from social and numerical categories, with 40 trials per word per modality. This multimodal approach leverages the complementary temporal resolution of EEG and spatial resolution of fMRI to advance brain-computer interface research for speech prostheses applications.

Participants

4

Channels

64 (10-10)

Size

9.33 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings from 14 epilepsy patients implanted with clinical surface and depth electrodes, collected during visual stimulation tasks between 2017-2020. Participants viewed grayscale patterns with varied spatial and temporal properties, as well as color images from six semantic categories, while performing a fixation task. The dataset includes raw voltage data, common-average-referenced recordings, broadband responses, preprocessed epochs, and surface reconstructions with electrode localizations, enabling investigation of neural dynamics in human visual cortex.

Participants

14

Size

57.9 GB

Version

vv1.0.0

Updated

Jul 22, 2026

This randomized controlled trial investigates the differential effects of forward and backward span training on working memory capacity. Event-related potentials (ERPs) were recorded during a distractor version of the change detection task at pre-, mid-, and post-test timepoints, while behavioral measures were collected from additional cognitive tasks. The study demonstrates that both training types enhance working memory maintenance compared to control conditions, with backward span training providing superior benefits for interference control based on ERP indices.

Participants

71

Size

77.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 21 participants learning to perform two distinct drumming patterns at three different tempos using keyboard responses. Participants received real-time visual feedback indicating response timing accuracy (early, on-time, or late) relative to target durations. The study investigates motor learning and timing control during sequential pattern acquisition, with detailed event markers capturing metronome beats, response types, and feedback outcomes across 72 trials per participant.

Participants

21

Channels

31 (10-10)

Size

4.76 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This EEG dataset comprises electrophysiological recordings from 57 obese and non-obese preadolescents performing a stop-signal task, designed to investigate the effect of obesity on inhibitory control mechanisms. Data were acquired using a 128-channel Geodesic Hydrocell Sensor Net system and include participant demographics (age, gender, BMI, weight status). The study employs event-related potential analysis to examine neural correlates of response inhibition across weight status groups.

Participants

57

Channels

128 (egi-geodesic)

Size

23.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from twelve participants performing three learning tasks with varying reward contingencies. Participants learned cue-response mappings for colored shape stimuli with feedback validity manipulated across conditions (50% for low-value cues, 80% for high-value cues). The study investigates how average task value influences learning and neural processing during reinforcement learning.

Participants

12

Channels

31 (10-10)

Size

4.00 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset contains electrophysiological recordings from rat somatosensory cortex using DISC (Distributed Intracortical Silicon Electrodes) microelectrode arrays during whisker stimulation. Anesthetized rats received air puffer stimulation to individual whiskers while neural activity was recorded, providing validation data for DISC technology in primary sensory cortex.

Participants

8

Size

188 GB

Version

vv1.0.0

Updated

Jul 10, 2026

The BCIT Traffic Complexity dataset comprises extended neurophysiological recordings during simulated driving tasks designed to assess fatigue-related performance changes. Participants performed continuous driving in a simulator while EEG, eye tracking, and vehicle performance data were collected simultaneously. The study manipulated visual complexity and perturbation frequency to investigate driver fatigue biomarkers and brain-behavior interactions during sustained attention tasks.

Participants

29

Channels

64 (10-10)

HED

v8.0.0

Size

17.5 GB

Version

vv1.0.0

Updated

Jul 10, 2026