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This dataset contains electroencephalographic (EEG) recordings from 24 participants performing object classification and passive viewing tasks in Experiment 1 of a study investigating how the brain represents object movement and aliveness. Participants classified static images of objects with varying capacities for movement (moving/non-moving) and animacy (alive/not alive) as either alive or capable of movement. The study demonstrates that movement capacity is a significant organizational principle in visual object representation, independent of animacy.

Participants

24

Size

82.2 GB

Version

vv1.0.0

Updated

Jul 10, 2026

A multicenter interictal intracranial electroencephalography (iEEG) dataset from patients with epilepsy, comprising de-identified recordings from six clinical centers: the National Institutes of Health, Johns Hopkins Hospital, University of Miami Florida Jackson Memorial Hospital, Kansas University Medical Center, University of Pittsburgh Medical Center, and Cleveland Clinic (with data from the latter three centers restricted due to institutional data sharing limitations). The dataset includes annotations of sleep and awake states and features processed derivatives including source-sink connectivity analysis and high-frequency oscillation detection. This resource supports investigation of electrophysiological markers of the epileptogenic zone.

Participants

39

Citations

3

Size

5.13 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG (iEEG) recordings from 12 epilepsy surgery patients enrolled in the RESPect (Registry for Epilepsy Surgery Patients) study at the University Medical Center of Utrecht. The collection includes intraoperative electrocorticography (ECoG) recordings from six patients and long-term iEEG monitoring data from six patients (three with ECoG and three with stereo-encephalography). All data are organized according to the Brain Imaging Data Structure (BIDS) specification to facilitate standardized access and analysis of clinical neurophysiology data. This dataset is derived from the larger RESPect iEEG collection and has been curated for BIDS compliance.

Participants

6

Size

99.0 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from 19 participants performing a cyber-physical systems task involving prediction error processing with multimodal sensory stimulation. Participants received visual, vibrotactile, and electrical muscle stimulation (EMS) across three experimental blocks while their brain activity was recorded using a 63-channel high-density EEG system. The study investigates neural responses to prediction errors in a haptic interaction task with varying levels of sensory realism.

Participants

19

Channels

63 (10-10)

Size

11.3 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG (iEEG) recordings from 12 epilepsy surgery patients enrolled in the RESPect (Registry for Epilepsy Surgery Patients) study at the University Medical Center of Utrecht. The collection includes both intraoperative electrocorticography (ECoG) recordings from six patients and long-term iEEG monitoring data from six patients (three ECoG, three stereo-encephalography). All data are organized according to the Brain Imaging Data Structure (BIDS) specification to facilitate standardized access and analysis of clinical neurophysiology data.

Participants

6

Size

2.60 GB

Version

vv1.0.0

Updated

Jul 22, 2026

This dataset comprises multimodal physiological recordings from 86 participants during resting state and a digit span working memory task. It includes 64-channel EEG, electrocardiography, photoplethysmography, pupillometry, and behavioral performance data. The dataset enables investigation of neural and peripheral physiological correlates of cognitive load, working memory capacity, and cognitive overload detection across fine temporal scales.

Participants

86

Channels

63 (10-10)

Size

253 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This EEG dataset comprises recordings from 25 college-age participants performing a reinforcement learning task with affective feedback, collected in 2018 at the Clinical Research Center Laboratory (CRCL) at the University of New Mexico. The study investigates the reward positivity component of the event-related potential and its sensitivity to affective liking during probabilistic learning. The dataset includes raw EEG data, behavioral task parameters, and analysis scripts supporting the published findings in Cognitive, Affective, & Behavioral Neuroscience.

Participants

25

Channels

66 (10-10)

Size

5.82 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from a single healthy participant exposed to multisensory stimulation at gamma frequencies (40Hz). The experiment investigates brain entrainment responses to three stimulus modalities: auditory (5kHz carrier amplitude-modulated at 40Hz), visual (20Hz flickering white LED array), and combined audio-visual stimulation. Each stimulus epoch lasted 40 seconds and was recorded using 19 monopolar EEG channels at 500Hz sampling rate. The study aims to characterize synchronized brain oscillations induced by different sensory modalities, with potential implications for understanding gamma entrainment mechanisms relevant to neurodegenerative diseases such as Alzheimer's disease.

Participants

1

Channels

19 (10-20)

Size

17.0 MB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises resting-state electroencephalography (EEG) recordings from 111 healthy control subjects acquired using a BioSemi ActiveTwo system with 64 electrodes. Subjects were recorded during four minutes of continuous EEG with eyes closed, with some subjects undergoing repeat recordings at a later timepoint. The dataset includes both raw EEG data rereferenced to average reference and a derived cleaned dataset preprocessed with an automated pipeline, along with demographic and cognitive test data.

Participants

111

Channels

64 (10-10)

Size

20.7 GB

Version

vv1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 20 Indian participants listening to 12 songs spanning diverse genres, from Indian Classical to Goth Rock. Participants rated their familiarity and enjoyment of each song on a 5-point scale following passive listening. The dataset provides neurophysiological measures of music perception and aesthetic response across genre diversity.

Participants

20

Channels

129 (egi-geodesic)

Citations

3

Size

10.1 GB

Version

vv1.0.0

Updated

Jul 10, 2026