Discover datasets

This dataset contains EEG and eye-tracking recordings from 30 participants who searched for objects in naturalistic scenes and intentionally memorized others, followed by a surprise recognition memory test. The study examines the 'search superiority effect,' testing whether incidentally encoded memories differ qualitatively from intentional ones through recollection and familiarity processes indexed by FN400 and late parietal ERP components. Behavioral remember-know judgments and ROC analyses were used alongside EEG measures to disentangle these memory processes.

Participants

30

Channels

61

Citations

1

Size

17.0 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises magnetoencephalography (MEG) recordings of auditory single word recognition in human subjects. Participants listened to isolated words while neural activity was recorded, providing insights into the temporal dynamics of auditory word comprehension. The dataset is described in Gaston et al. (2022) 'Auditory word comprehension is less incremental in isolated words' published in Neurobiology of Language. The dataset includes raw MEG data, stimulus information, and associated metadata organized according to the Brain Imaging Data Structure (BIDS) standard. This is a NEMAR-converted version of OpenNeuro dataset ds004276.

Participants

19

Citations

1

Size

11.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains EEG recordings from a color change detection task, organized according to the Brain Imaging Data Structure (BIDS) standard. It is intended to support research on visual attention and perceptual change detection processes.

Participants

24

Size

13.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

A multicenter intracranial electroencephalography (iEEG) dataset comprising segmented 3-second single-channel clips from epilepsy patients, annotated for graphoelement classification and artifact detection. The dataset includes clinical metadata such as seizure onset zone (SOZ) flags, electrode anatomy, and reviewer annotations, making it suitable for developing and validating automated signal classification algorithms in clinical neurophysiology.

Participants

14

Size

20.8 GB

Version

v1.0.2

Updated

Jul 10, 2026

This dataset comprises electroencephalography (EEG) recordings investigating the neural correlates of syntactic structure and lexical properties using frequency tagging methodology. Participants were presented with linguistic stimuli while EEG activity was recorded to identify frequency-specific neural responses associated with different linguistic features. The dataset provides raw neurophysiological data suitable for studying the temporal dynamics of language processing at the neural level.

Participants

34

Citations

1

Size

195 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset comprises event-related potential (ERP) recordings from 13 healthy subjects performing a visual matrix speller task using a calibrationless brain-computer interface approach. The study introduces learning from label proportions (LLP), an unsupervised classification method that exploits known target/non-target stimulus ratios to enable online BCI operation without prior calibration. Subjects performed copy-spelling tasks using a 6×7 character grid across three sessions, achieving 84.5% character accuracy without labeled training data.

Participants

13

Channels

31 (10-10)

Citations

46

HED

v8.4.0

Size

5.15 GB

Version

v1.0.2

Updated

Aug 18, 2026

This dataset contains continuous 64-channel scalp EEG recordings from 12 right-handed subjects performing a visual attention task designed to examine dimension-based attentional modulation of early visual processing. The data include independent component analysis (ICA) decompositions with expert-annotated component labels, originally collected for a study on visual attention and later reused for research on automatic classification of independent components. The dataset was converted to BIDS format from the original recordings with permission from the original authors.

Participants

12

Channels

64 (10-10)

Citations

35

Size

5.63 GB

Version

v1.0.0

Updated

Aug 19, 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 contains EEG recordings from 53 participants performing a bilateral change-detection task designed to examine how perceptual grouping by color repetition influences distinct stages of visual working memory processing. Event-related potential markers (N2pc, CDA, N2, FN400) are used to temporally isolate encoding, maintenance, comparison, and decision-making stages. The dataset was collected at Louisiana State University and is structured according to the BIDS-EEG standard.

Participants

53

Channels

64 (10-10)

Size

269 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises high-density and sparse functional near-infrared spectroscopy (fNIRS) measurements acquired during a Word-Color Stroop task. The study investigates whether high-density multi-distance fNIRS configurations enhance detection of brain activity compared to conventional sparse probe arrangements. Raw neuroimaging data from multiple participants are provided in BIDS format to support reproducible analysis of cognitive control mechanisms.

Participants

17

Size

169 MB

Version

v1.0.0

Updated

Jul 10, 2026