Discover datasets

This dataset comprises intracranial EEG (iEEG) recordings collected during non-REM sleep from patients undergoing clinical evaluation for epilepsy surgery. The data were acquired across multiple institutions and are part of a broader study modeling high-frequency activity (HFA) in the human brain. This dataset represents part 3 of a comprehensive iEEG HFA modeling project.

Participants

103

Size

32.6 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises intracranial EEG (iEEG) recordings acquired during non-REM sleep from patients undergoing epilepsy monitoring across multiple clinical sites. The data were collected to support a comprehensive model of high-frequency activity (HFA) reported in Hatano et al. (in press). It is part one of a larger multi-part dataset release.

Participants

65

Size

33.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG, pupillometry, and behavioral data from 28 healthy adult participants who underwent an auditory fear conditioning paradigm consisting of Pre-Conditioning, Conditioning, and Extinction phases. During the task, participants localized the spatial origin of voices differing in amplitude modulation while some voice stimuli were paired with an aversive white noise unconditioned stimulus. The dataset supports investigation of the neural, autonomic, and behavioral correlates of fear learning and extinction.

Participants

28

Channels

68 (10-10)

Size

21.6 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises long-term intracranial EEG (iEEG) recordings from 8 epilepsy patients implanted with responsive neurostimulation (RNS) devices, recorded from bilateral epileptic lesion areas over periods exceeding six months. Each recording captures dual-channel iEEG activity around electrical stimulation events, including pre- and post-stimulation periods, with associated stimulation parameters and event markers. The dataset is intended to support analysis of seizure onset pattern alterations during epilepsy progression and iEEG characteristic changes following electrical stimulation.

Participants

8

Citations

1

Size

498 MB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises EEG recordings from a working memory experiment investigating whether previously studied (learned) information is actively maintained in working memory or remains passively accessible. Participants performed a visual working memory task involving memorization and probing of colored objects under varying expectations of memory load (extra-load vs low-load), while EEG was recorded to assess neural indices of active storage and attentional allocation. The study addresses how anticipated memory load influences the encoding and retrieval of studied versus novel information.

Participants

41

Channels

32 (egi-geodesic)

Size

11.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains raw and processed EEG recordings from participants performing silent visual reading of naturalistic narrative stories, investigating auditory representations of words during silent reading. Data include BrainVision-format EEG recordings organized according to BIDS, along with derivative processed EEG signals, metadata linking sessions to stories and runs, and word-level feature embeddings.

Participants

10

Channels

63 (10-10)

Size

35.3 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains intracranial electrophysiological recordings from the auditory cortex of macaque monkeys, collected to investigate neural responses in the auditory system. The data were acquired by Kajikawa and Schroeder and are mirrored on NEMAR from OpenNeuro under the DISC data collection.

Participants

3

Citations

3

Size

13.9 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains de-identified resting-state EEG recordings from individuals with Parkinson's disease and age-matched healthy controls, collected to investigate whether EEG signals can predict mortality outcomes. Each subject is labeled as either 'living' or 'deceased' in the participants file, with no additional demographic or clinical information provided. The dataset is intended to support research on EEG biomarkers of mortality risk and machine learning classification approaches in Parkinson's disease populations.

Participants

94

Channels

63 (10-10)

Citations

3

Size

1.74 GB

Version

v1.0.0

Updated

Aug 19, 2026

FOODEEG is an open dataset of electroencephalographic (EEG) and behavioural responses to food images from 117 participants across two testing sessions. Session 1 involved a food categorisation task with continuous EEG recording, while Session 2 comprised a food go/no-go task and a food paired choice task, along with questionnaires on dietary style and eating motivations. The dataset also includes normative ratings on 22 food attributes collected from an independent online sample (N = 624), providing a rich resource for studying neural and behavioural correlates of food-related decision-making.

Participants

117

Size

91.1 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains EEG recordings from a study investigating virtual reality (VR)-based augmentation of compassion cultivation training (CCT). Participants engaged with an immersive VR social environment called Compassion Island, implemented in AltspaceVR, which included a meditation hall, a garden, and a clinic setting where they interacted with live-actor-controlled avatars. The dataset captures neural responses associated with guided meditation, compassion visualization exercises, and simulated social interactions designed to cultivate compassion.

Participants

10

Channels

64 (10-10)

Size

919 MB

Version

v1.0.0

Updated

Aug 19, 2026