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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

This dataset comprises EEG recordings from 25 college-age participants performing a reinforcement learning task with affective feedback. Collected in 2019 at the University of New Mexico's Clinical Research Center Lab, the data were acquired to investigate the sensitivity of the reward positivity (RewP) component to affective liking during probabilistic learning. This represents Experiment #2 of a study examining neural correlates of reward processing and emotional valuation in decision-making. This is a re-hosted version of OpenNeuro dataset ds003753.

Participants

25

Channels

66 (10-10)

Citations

1

Size

4.62 GB

Version

v1.0.0

Updated

Jul 22, 2026

The Dataset on Emotion with Naturalistic Stimuli (DENS) comprises multimodal physiological recordings from 40 participants exposed to emotionally evocative video stimuli. The dataset includes concurrent EEG, ECG, and EMG measurements alongside behavioral self-assessment ratings across multiple emotion dimensions (valence, arousal, dominance, liking, familiarity, relevance, and emotion category). This resource supports research on emotion recognition, affective neuroscience, and the neural correlates of emotional responses to naturalistic, contextually-rich stimuli.

Participants

40

Channels

128

Citations

4

Size

4.46 GB

Version

v1.0.0

Updated

Jul 10, 2026

A longitudinal EEG dataset from 13 infants recorded at 4, 8, and 12 months of age, comprising 48 recording sessions. The dataset includes test-retest reliability assessments at 4 months (11 infants with complete longitudinal data, 2 infants with reliability data only) and was used to develop and validate APPLESEED, an automated preprocessing pipeline for estimating scale-wise entropy from pediatric EEG data. This example dataset accompanies the 2022 APPLESEED pipeline publication in Developmental Cognitive Neuroscience and demonstrates the application of entropy-based EEG analysis methods in early human development. The dataset is part of a larger longitudinal study initially described in Puglia et al. (2020).

Participants

13

Channels

32 (10-10)

Citations

14

Size

10.2 GB

Version

v1.0.0

Updated

Jul 10, 2026