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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

Citations

1

Size

99.3 GB

Version

v1.0.0

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)

Citations

53

Size

11.4 GB

Version

v1.0.0

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

v1.0.0

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)

Citations

61

Size

253 GB

Version

v1.0.0

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

v1.0.0

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

v1.0.0

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)

Citations

35

Size

20.7 GB

Version

v1.0.0

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

v1.0.0

Updated

Jul 10, 2026

This dataset comprises simultaneous EEG and fMRI recordings from 33 healthy human participants during sleep and wakefulness. The study captures coordinated electrophysiological and hemodynamic signals using a 32-channel MR-compatible EEG system synchronized with BOLD fMRI acquisition. The experimental protocol includes anatomical imaging, resting-state sessions before and after a visual-motor adaptation task, and multiple sleep sessions with corresponding sleep stage annotations. EEG signals provide direct measures of electrophysiological activity and sleep stage information, while fMRI captures hemodynamic responses, enabling investigation of the relationship between neural activity during sleep-wake transitions.

Participants

33

Citations

16

Size

86.5 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset combines high-density electroencephalography (128-channel HD-EEG) and mouse-tracking to examine dynamic decision-making processes in the human brain. Collected from 31 adults (ages 18-33), it includes resting-state and task-related EEG data acquired during food preference choices and semantic judgment tasks. The resource provides both raw and preprocessed EEG data with synchronized behavioral measures, enabling investigation of neural correlates underlying binary choice decisions.

Participants

31

Channels

129 (egi-geodesic)

Citations

5

Size

153 GB

Version

v1.0.0

Updated

Jul 22, 2026