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This dataset contains MEG phantom recordings designed to characterize deep brain stimulation (DBS) device-specific artefacts in magnetoencephalography. Using a Neuromag phantom setup, movement onset was captured with an accelerometer to assess artefact behavior associated with DBS hardware. The data support a study investigating how DBS devices affect MEG signal quality and interpretation.

Participants

4

Size

6.13 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains MEG recordings from a study investigating how the human brain compresses regular binary sound sequences in working memory, testing the language of thought hypothesis. Participants listened to hierarchically structured sequences of two sounds varying in complexity, quantified via minimal description length, while occasional deviant sounds probed their internalized knowledge of sequence structure. The study aimed to characterize how brain activity relates to sequence complexity and predictive processing.

Participants

19

Citations

5

Size

23.4 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset contains MEG data collected as part of the FLUX pipeline project, a standardized analysis and preprocessing pipeline for magnetoencephalography (MEG) research. The dataset was reorganized into BIDS format from an original OpenNeuro dataset to support reproducible MEG analysis workflows across multiple research sites.

Participants

1

Citations

41

Size

16.8 GB

Version

v1.0.0

Updated

Aug 19, 2026

This dataset comprises MEG recordings collected to investigate the sustained neural representations of personally familiar people and places during a cued recall task. Participants were cued to recall familiar individuals and locations while brain activity was measured to examine the temporal dynamics of memory-related representations.

Participants

30

Size

76.7 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 magnetoencephalography (MEG) recordings from a single infant subject participating in a study of auditory processing and phoneme learning, part of research investigating risk factors for dyslexia during sensitive periods of language development. The data support investigations into neural theta sampling and auditory deficits in infants at risk for dyslexia.

Participants

2

Citations

22

Size

1.78 GB

Version

v1.0.0

Updated

Aug 19, 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

Citations

17

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

Citations

6

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

Citations

1

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

Citations

27

Size

75.7 GB

Version

v1.0.0

Updated

Jul 10, 2026