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This dataset contains magnetoencephalography (MEG) recordings from participants listening to hierarchically structured binary sound sequences of varying complexity. The study tests the language of thought hypothesis by examining how the human brain compresses regular sequences in working memory using recursive structures. Brain activity was recorded while participants processed sequences requiring different levels of complexity (transition probabilities, chunking, or nested structures) and responded to occasional deviant sounds probing sequence knowledge. Note: This dataset contains MEG data only; fMRI data from the same study are archived separately.

Participants

19

Size

23.4 GB

Version

v1.0.0

Updated

Jul 10, 2026

FLUX is a comprehensive pipeline for magnetoencephalography (MEG) data analysis, providing standardized workflows for processing and analyzing MEG recordings. This dataset demonstrates the application of the FLUX pipeline to MEG neuroimaging data organized according to the Brain Imaging Data Structure (BIDS) standard, facilitating reproducible and transparent MEG analysis across research groups. The dataset is derived from OpenNeuro ds004346 and contains MEG recordings with anatomical data.

Participants

1

Size

15.0 GB

Version

v1.0.0

Updated

Jul 10, 2026

This dataset contains neuroimaging data from a cued recall task investigating sustained neural representations of personally familiar people and places. Participants were cued to recall specific individuals and locations while MEG data were recorded, enabling investigation of how the brain maintains and represents autobiographical memories of social and spatial information.

Participants

30

Size

76.7 GB

Version

v1.0.0

Updated

Jul 10, 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

Size

11.6 GB

Version

v1.0.0

Updated

Jul 10, 2026

This MEG dataset contains neuroimaging data from a single infant subject collected to investigate auditory processing and language development in children at risk for dyslexia. The data were acquired during a linguistic sensitive period and are used to examine the relationship between early auditory deficits and future language outcomes, as well as theta oscillatory activity during native phoneme learning.

Participants

2

Size

1.78 GB

Version

v1.0.0

Updated

Jul 10, 2026

This magnetoencephalography (MEG) dataset comprises neuroimaging data collected to establish standardized protocols for cross-site pooling of MEG data. The dataset demonstrates the application of BIDS formatting to MEG neuroimaging, facilitating data harmonization and reproducible analysis across multiple research institutions.

Participants

9

Size

77.2 GB

Version

v1.0.0

Updated

Jul 10, 2026

A synchronized multimodal neuroimaging dataset containing concurrent fMRI and MEG recordings from 12 Mandarin Chinese speakers during naturalistic story listening, supplemented with high-resolution structural imaging, diffusion MRI, and resting-state fMRI. The dataset includes rich linguistic annotations of stimuli encompassing word frequencies, syntactic structures, temporal alignments, and embeddings from multiple pre-trained language models, enabling comprehensive investigation of neural mechanisms underlying language processing.

Participants

12

Size

1.36 TB

Version

v1.0.0

Updated

Jul 22, 2026

BRAR_NQ is a neuroimaging dataset investigating the neural correlates of Quranic recitation through EEG recordings. The dataset explores the brain's reward and anti-reward circuitry in response to melodic recitation of the Noble Quran, combining electroencephalography to map neural activity patterns associated with this unique auditory-linguistic stimulus.

Participants

30

Size

78.3 GB

Version

v1.0.0

Updated

Jul 10, 2026

A magnetoencephalography dataset from 13 participants performing audiovisual multisensory tasks, including causality judgment, temporal order judgment, and unimodal localizer conditions. The dataset comprises 1500 trials of audiovisual sequences with simultaneous behavioral recordings and structural MRI, designed to investigate neural mechanisms of multisensory correlation computations using time-resolved encoding models.

Participants

14

Size

75.1 GB

Version

v1.0.0

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