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This multi-session dataset comprises simultaneous EEG-fMRI recordings from 24 healthy adults (ages 18-35) performing a sustained attention task (GradCPT) and resting state with online experience sampling. The dataset includes 31-channel cortical EEG (plus 4 carbon wire loop sensors and 1 ECG channel for a total of 36 recorded channels) with carbon wire loop sensors for artifact removal, concurrent fMRI, ECG, behavioral responses, and multi-dimensional experience sampling ratings assessing thought contents and processes. Approximately 1 hour 20 minutes of data were collected per participant per session across two sessions, enabling investigation of neural correlates of spontaneous cognitive processes including mind-wandering and attentional fluctuations. All structural MRI images were defaced for privacy. Note: One session (sub-003_ses-001) contains incomplete data collection with 3 runs instead of the standard 4 runs due to time constraints.

Participants

24

Channels

31 (10-10)

Size

115 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises resting-state and task-based EEG recordings from 100 participants designed to investigate hemispheric asymmetries in electroencephalographic activity. The study examines the association between N1 lateralization and alpha asymmetry across multiple cognitive domains including word recognition, face processing, emotion perception, and visual object categorization. Participants completed approximately 8 minutes of resting-state EEG with alternating eyes-open and eyes-closed periods, followed by four randomized tasks involving stimulus-response paradigms with counterbalanced hand responses.

Participants

100

Channels

32 (10-10)

Size

11.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

This multimodal dataset comprises synchronized EEG, ECG, and pupillometry recordings from 18 participants performing an n-back working memory task with four difficulty levels (1-back through 4-back). The study employed a combined mobile EEG+ECG system and Pupil Labs eye tracker synchronized via Lab Streaming Layer, capturing cognitive workload modulation across task difficulty. Raw XDF recordings were converted to BIDS format with EEG in BrainVision format, pupil data exported as TSV files, and task events aligned to EEG start time. The dataset includes 19-channel EEG at 250 Hz, 3-lead ECG, and asynchronous pupil tracking, with detailed task event annotations and participant exclusion metadata.

Participants

18

Channels

19 (10-20)

Size

2.13 GB

Version

v1.0.0

Updated

Jul 10, 2026

This EEG dataset contains neural recordings from 34 participants performing a visual object recognition task using a curated stimulus set of 242 images (121 challenge and 121 control images). Participants viewed sequences of 14 images presented for 200 ms each with 100 ms interstimulus intervals and performed a detection task. The dataset includes time-resolved decoding analyses examining adaptive recruitment of cortical recurrence mechanisms during visual object recognition.

Participants

34

Channels

63 (10-10)

Citations

1

Size

59.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings acquired during non-REM sleep from patients undergoing clinical monitoring. The data were collected to investigate high-frequency activity patterns and develop comprehensive models of neural oscillations during sleep, contributing to understanding of intracranial electrophysiology and sleep neuroscience.

Participants

65

Size

33.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings acquired during non-REM sleep from patients undergoing clinical monitoring. The data were collected to investigate high-frequency activity patterns and develop comprehensive models of neural oscillations during sleep, as described in Hatano et al. (in press). This represents part 3 of a multi-part iEEG high-frequency activity modeling study.

Participants

103

Size

32.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings acquired during non-REM sleep from multiple subjects. The data were collected to develop and validate a comprehensive model of high-frequency activity (HFA) in epilepsy research. This represents part 1 of a multi-part dataset designed to characterize neural oscillations and their clinical significance during sleep states.

Participants

65

Size

33.8 GB

Version

v1.0.0

Updated

Jul 10, 2026

SUBEMOcondEEG1 is a neurophysiological dataset comprising EEG, pupillometry, and behavioral data from 28 healthy participants (final sample after quality control from 32 initial volunteers; 4 excluded due to low signal-to-noise ratio on electrophysiological data) engaged in a fear conditioning paradigm with auditory stimuli. The study investigates emotional learning through three phases (Pre-Conditioning, Conditioning, and Extinction) using voices with varying acoustic properties (high and low amplitude modulation) paired or unpaired with aversive white noise. This dataset provides multimodal measurements of physiological and behavioral responses during fear acquisition and extinction.

Participants

28

Channels

68 (10-10)

Size

21.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

A long-term intracranial electroencephalography (iEEG) dataset from 8 epilepsy patients implanted with responsive neurostimulation (RNS) devices, comprising bilateral recordings from epileptic lesion areas. Each recording captures 90 seconds of dual-channel iEEG centered on stimulation events, with detailed stimulation parameters and seizure event markers. The dataset enables investigation of seizure onset pattern evolution and iEEG characteristic changes following electrical stimulation therapy.

Participants

8

Size

491 MB

Version

v1.0.0

Updated

Jul 10, 2026

This EEG dataset investigates how attended information is maintained in working memory despite varying cognitive load expectations. Participants performed a color-recall task with two memory screens presenting studied and novel objects under conditions of high or low anticipated load. The study examines neural correlates of working memory maintenance and the effects of load expectation on memory-related brain activity, using event-related potentials and spectral analysis of EEG signals.

Participants

41

Channels

32 (egi-geodesic)

Size

11.3 GB

Version

v1.0.0

Updated

Jul 10, 2026