Discover datasets

This dataset comprises pooled electrooculography (EOG) data from 41 participants across two studies investigating the relationship between eye blinks and attention during a competing speaker paradigm. Participants performed selective auditory attention tasks while listening to competing audiobooks, with experimental conditions varying between studies regarding sound presentation (omnidirectional versus beamforming). The dataset integrates EOG recordings from Jaeger et al. (2020) and Holtze et al. (2021) to enable comparative analysis of oculomotor behavior during dichotic listening tasks.

Participants

41

Channels

7 (egi-geodesic)

Citations

2

Size

8.01 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography recordings from 16 subjects viewing rapid serial visual presentations of gabor-like stimuli at two presentation rates (6.67 Hz and 20 Hz). Participants performed a concurrent fixation color change detection task while EEG data were acquired. The study investigates the dynamics of visual feature coding and neural mechanisms underlying perception and feature integration.

Participants

16

Citations

27

Size

69.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises Auditory Brainstem Response (ABR) recordings from 22 healthy young adults (ages 22.7 ± 5.1 years) obtained during continuous presentation of music and speech stimuli. Using a deconvolution method applied to EEG data collected from June to August 2021, the study investigates subcortical and cortical neural responses to different acoustic categories. The dataset includes raw EEG recordings in BrainVision format, stimulus files, and detailed event metadata enabling analysis of neural differentiation between music and speech processing. Two subjects (014 and 021) were excluded due to self-withdrawal and technical data collection issues, respectively.

Participants

22

Channels

34 (10-10)

Citations

21

Size

213 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Ear-EEG Sleep Monitoring 2017 (EESM17) dataset comprises nightly polysomnographic recordings from 9 healthy participants, combining conventional EEG, EOG, and chin EMG with 14 ear-EEG electrodes. The dataset includes both wake-state recordings (subjects relaxing before sleep) and sleep-state recordings (overnight monitoring at participants' homes), with sleep scoring initiated at lights out. This resource enables investigation of ear-based EEG for sleep monitoring applications.

Participants

9

Channels

34 (other)

Citations

95

Size

12.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises concurrent EEG and EMG recordings collected during a visual perception task examining symmetry detection and affective responses. Participants viewed visual patterns and made judgments about pattern regularity following stimulus offset, providing insights into the neural and physiological correlates of symmetry perception.

Participants

24

Channels

64 (other)

Citations

91

Size

2.69 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings from an experiment investigating how stylized, exaggerated facial images enhance event-related potential (ERP) features relevant to emotion detection. The study demonstrates that artificially modified human faces elicit a stronger N170 component compared to natural faces, informing the design of affective brain-computer interfaces (BCIs). Participant identifying information has been removed for anonymization.

Participants

26

Channels

28 (10-10)

Size

2.46 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG data from a reinforcement learning probabilistic selection task (PST) administered to 50 healthy adult participants, half of whom underwent a sad mood manipulation and half a happy mood manipulation prior to task performance. The task, adapted from a published probabilistic selection paradigm, included training and testing phases with mood induction occurring before each training block. Data were collected between 2019 and 2021 at the Cognitive Rhythms and Computation Lab at the University of New Mexico to study the interaction between mood states and reinforcement learning processes.

Participants

50

Channels

66 (10-10)

Citations

1

Size

18.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises electroencephalography (EEG) recordings from 50 healthy control participants performing a reinforcement learning task under two mood conditions: sad mood manipulation (n=25) and neutral mood manipulation (n=25). The task included training and testing phases adapted from established reinforcement learning paradigms. Data were collected between 2019-2021 at the Cognitive Rhythms and Computation Lab at the University of New Mexico to investigate the effects of mood state on learning and decision-making processes.

Participants

50

Channels

66 (10-10)

Citations

1

Size

9.81 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings from 13 participants performing semantic imagination and perception tasks across visual and auditory modalities. Participants were presented with stimuli from three semantically dissimilar categories (guitar, flower, penguin) in pictorial, orthographic, and auditory formats. The dataset includes raw, preprocessed, and epoched EEG data acquired using a 124-channel ANT-Neuro system, providing a resource for investigating neural correlates of semantic processing and cross-modal perception.

Participants

12

Channels

124 (10-05)

Citations

1

Size

79.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises two reversal learning tasks designed to investigate differential neural processing of reward gain and punishment avoidance. Participants performed parallel tasks using distinct reinforcers: monetary reward (gain/non-gain outcomes) and primary threat avoidance (noise burst avoidance/application), with noise intensity individually titrated to match subjective value of monetary rewards. The dataset enables investigation of how the brain differentially encodes appetitive versus aversive learning contingencies.

Participants

26

Channels

66 (10-10)

Citations

20

Size

31.5 GB

Version

v1.0.0

Updated

Jul 10, 2026