Discover datasets

This dataset contains electroencephalography (EEG) recordings from a repeated awakening study investigating the effects of propofol sedation on dreaming and the utility of complexity measures in capturing consciousness dynamics. Participants underwent multiple sedation-awakening cycles with EEG recordings during wakefulness (eyes open and closed), sedation, and transcranial magnetic stimulation sessions. The study aims to elucidate the relationship between EEG complexity measures and subjective dream experiences during pharmacological sedation.

Participants

21

Channels

65 (10-10)

Size

77.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises EEG recordings from an alphabetic decision task using Arial Light font, collected to investigate sub-letter orthographic processing through optimal transport modeling. Participants performed a letter discrimination task while EEG data were recorded and synchronized with behavioral responses and stimulus information. The dataset includes 6 participants with detailed annotations of recording issues and data quality markers.

Participants

16

Channels

64 (10-10)

Size

10.9 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains electroencephalographic (EEG) recordings from 23 participants performing a passive viewing task involving visual scenes with occluded and uncovered game pieces. Participants viewed scenes with varying numbers of visible and hidden objects to investigate neural responses to object numerosity under occlusion conditions. The study employed a factorial design with 640 trials across eight blocks, systematically manipulating the number of initially visible pieces (4 or 32) and uncovered pieces (0-32) to examine how the brain processes object quantity in partially occluded visual scenes.

Participants

23

Channels

60 (10-10)

Size

28.7 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Podcast ECoG dataset provides intracranial electrophysiological recordings from 9 participants with 1,330 electrodes during natural story listening. This dataset combines high spatiotemporal resolution human electrocorticography with a naturalistic language comprehension paradigm, including raw and preprocessed high-gamma data, auditory stimuli, word-level transcripts, and linguistic features from acoustic properties to large language model embeddings. The resource includes tutorials and serves as both a pedagogical tool and foundation for investigating neural mechanisms of narrative comprehension.

Participants

9

Size

14.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains neuroimaging data from a study investigating the neural mechanisms of expectation and conflict processing. The research examines how the brain anticipates and responds to conflicting stimuli, with implications for understanding cognitive control and decision-making processes. Data were collected from multiple participants and are formatted according to BIDS standards.

Participants

29

Channels

66 (10-10)

Size

62.8 GB

Version

v1.0.0

Updated

Jul 10, 2026

This event-related potential (ERP) study investigates neural mechanisms underlying the integration of fingerspelling, printed English words, and American Sign Language (ASL) signs in deaf readers. Using a priming paradigm with 300 prime-target pairs, the dataset captures electrophysiological responses to identity and translation primes across three modalities, providing insights into cross-modal language processing in the deaf population.

Participants

24

Channels

32 (10-10)

Size

2.62 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains intracranial electrophysiology recordings and behavioral data from a categorized free recall task with real-time closed-loop brain stimulation during encoding. Participants studied semantically organized word lists, performed distractor tasks, and freely recalled items while a machine learning classifier trained on prior sessions predicted subsequent memory performance and triggered stimulation for low-confidence encoding events. The study demonstrates the application of predictive neural decoding to modulate memory encoding through targeted electrical stimulation.

Participants

9

Size

12.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains intracranial electrophysiology recordings and behavioral data from a delayed free recall task with real-time closed-loop brain stimulation during encoding. Participants studied word lists, performed distractor arithmetic tasks, and freely recalled words while an L2 logistic regression classifier trained on encoding neural features guided stimulation delivery to optimize memory performance. Data were collected across multiple clinical sites as part of a collaborative memory research initiative.

Participants

18

Size

34.7 GB

Version

v1.0.0

Updated

Jul 10, 2026

The Bitbrain Open Access Sleep (BOAS) dataset comprises 128 nights of simultaneous polysomnography and wearable EEG recordings designed to validate emerging wearable sleep monitoring technologies against clinical gold-standard systems. The dataset includes comprehensive PSG recordings from a Micromed Brain Quick Plus Evolution system and synchronized wearable EEG data from a Bitbrain forehead headband, along with human expert consensus sleep stage annotations and AI-generated sleep scoring labels. This resource enables direct comparison and validation of wearable EEG performance for sleep stage classification in a diverse population sample.

Participants

128

Channels

2

Size

33.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises intracranial EEG recordings from 106 patients performing an auditory naming task. The recordings include event markers for stimulus onset/offset and response onset, with electrode coordinates provided in MNI-305 space. The dataset supports investigation of neural mechanisms underlying auditory language processing and naming through direct brain recordings.

Participants

106

Size

40.0 GB

Version

v1.0.0

Updated

Jul 10, 2026