Discover datasets

This dataset comprises EEG recordings from 39 Italian-speaking participants performing a picture-matching task under four cue conditions (Physical, Imagery, Literal, and Metaphorical), designed to investigate how mental representations generated by verbal and non-verbal cues influence the processing of subsequent target pictures. The study, part of the ERC-funded PROMENADE project, focuses on the neurocognitive processing of metaphorical versus literal language and mental imagery. EEG data were collected in long epochs around target picture onset, alongside behavioral accuracy and questionnaire-based measures of vocabulary and imagery ability.

Participants

39

Channels

58 (10-10)

Size

14.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from a picture-word interference (PWI) naming study conducted at San Diego State University's NeuroCognition Laboratory. Participants named line drawings of objects preceded by semantically related, identity-related, or unrelated English distractor words, while 32-channel EEG and vocal responses were recorded. The dataset supports investigation of lexical-semantic access and word retrieval processes during picture naming.

Participants

29

Channels

32 (10-10)

Size

2.28 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises intracranial EEG (iEEG) recordings from ten pediatric epilepsy patients undergoing intracranial monitoring for seizure localization, recorded while they performed a visuomotor task. Subjects completed five sessions of Speed Match, a finger-tapping visuomotor game on the Lumosity platform, during interictal periods. The dataset provides continuous iEEG signals along with trial timing information for finger tapping events, supporting research into visuomotor processing and cortical dynamics in epilepsy patients.

Participants

8

Size

818 MB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from 53 community participants performing a reinforcement learning task (3-armed bandit) featuring alcohol versus beverage cues, designed to examine aberrant cue-specific exploration behavior in hazardous drinkers compared to controls. Data were collected between 2019 and 2021 at the Clinical and Research Center for Learning (CRCL) at the University of New Mexico. The dataset is a preprocessed derivative generated using the NEMAR-pipeline, intended to support electrophysiological analyses of reward learning and cue reactivity in the context of alcohol use.

Participants

53

Channels

56 (10-10)

Size

5.65 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from twenty-nine participants who listened to song melodies and indicated when the melody felt familiar. Participants then attempted to identify each song and selected among multiple-choice song titles, receiving visual feedback on accuracy. The dataset includes synchronized audio reconstructions of the stimuli presented during EEG recording, supporting research on music familiarity, recognition, and associated neural correlates.

Participants

29

Channels

32

Citations

1

Size

7.61 GB

Version

v1.0.0

Updated

Aug 19, 2026

SeizeIT2 is a multicenter, prospective study validating the wearable Sensor Dot device for long-term epilepsy monitoring in adult and pediatric patients with refractory focal epilepsy. The dataset includes wearable EEG (behind-the-ear), ECG, EMG, and movement (accelerometer/gyroscope) recordings from 125 patients across five European epilepsy monitoring units, totaling approximately 11,640 hours of data and 886 recorded focal seizures. This BIDS-compliant version reorganizes the original SeizeIT2 data with BIDS-score compatible seizure annotations for use in epilepsy detection research.

Participants

125

Channels

2

Citations

3

Size

117 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset provides a BIDS-standardized version of simultaneously collected EEG and eye-tracking data from one subject, derived from the larger EEGEyeNet dataset. It supports research on eye movement prediction from electroencephalography and eye-tracking signals, following an established paradigm designed for benchmarking EEG-based eye movement decoding.

Participants

1

Channels

129 (egi-geodesic)

Citations

7

Size

43.6 MB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from a flanker word-reading task (Flankers-FAR) collected at the NeuroCognition Laboratory at San Diego State University. Participants viewed four-letter real words and pseudowords flanked by no flanker, identical flankers, or different flankers while EEG was recorded to examine lexical and attentional processing. The dataset includes behavioral responses collected via game controller during stimulus presentation.

Participants

48

Channels

32 (10-10)

Citations

1

Size

2.93 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from a flanker word/pseudoword lexical decision task collected at the NeuroCognition Laboratory in San Diego. Participants viewed four-letter real words and pseudowords flanked by identical, different, or no flanking words, while EEG was recorded to examine neural responses associated with lexical processing under flanker conditions. The dataset was collected under San Diego State University's IRB oversight.

Participants

60

Channels

32 (10-10)

Citations

1

Size

3.57 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from 127 young adults (18-30 years) collected alongside measures of childhood and adulthood socioeconomic status (SES), including educational attainment, income, food security, and neighborhood characteristics. EEG tasks were drawn from or adapted from the ERP CORE resource, designed to elicit neural activity related to perception, cognition, and action. The dataset also includes an ADHD symptoms checklist, enabling investigation of relationships between SES, ADHD symptoms, and neural activity in a socioeconomically diverse adult sample.

Participants

127

Channels

27

Citations

7

Size

10.6 GB

Version

v1.0.0

Updated

Aug 19, 2026