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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.

Citations

1

Size

23.4 GB

Updated

Jun 24, 2026

[![DOI](https://img.shields.io/badge/DOI-10.82901%2Fnemar.on005346-blue…

Citations

2

Size

112 GB

Updated

Jun 26, 2026

This dataset comprises behavioral events and intracranial electrophysiological recordings from a categorized free recall task conducted across multiple clinical sites. Participants studied semantically organized word lists (12 items from 3 categories with paired exemplars), performed a distractor task, and freely recalled the words. The dataset includes monopolar and bipolar iEEG recordings with electrode localization information, supporting investigations of memory encoding and retrieval processes.

Citations

1

Size

477 GB

Updated

Jun 25, 2026

This dataset comprises multimodal physiological recordings from 86 participants during resting state and a digit span working memory task. It includes 64-channel EEG, electrocardiography, photoplethysmography, pupillometry, and behavioral performance data. The dataset enables investigation of neural and peripheral physiological correlates of cognitive load, working memory capacity, and cognitive overload detection across fine temporal scales.

Citations

54

Size

253 GB

Updated

Jun 22, 2026

Imported from OpenNeuro ds003190

Citations

1

Size

1.24 GB

Updated

May 23, 2026

This dataset comprises electroencephalographic (EEG) recordings collected during the presentation of stylized facial stimuli to investigate emotion detection and event-related potentials (ERPs). The study demonstrates that artificially enhanced faces with exaggerated visual features elicit enhanced N170 components compared to standard facial images, suggesting optimized stimulus design can improve neural correlates of emotion recognition. These findings have implications for affective brain-computer interface (BCI) development and emotion detection accuracy from EEG signals. Participant information has been anonymized.

Size

2.46 GB

Updated

Jun 24, 2026

Imported from OpenNeuro ds003645

Citations

83

Size

54.5 GB

Updated

May 16, 2026

Imported from OpenNeuro ds007262

Size

1.92 GB

Updated

May 16, 2026

THINGS-MEG is a large-scale magnetoencephalographic dataset comprising neural recordings from 4 participants viewing 22,448 unique photographic images representing 1,854 object concepts from the THINGS database across 12 sessions. This MEG dataset is part of the multimodal THINGS-data collection, which integrates MEG recordings with behavioral judgments and complementary neuroimaging modalities (fMRI, behavioral data) to enable comprehensive investigation of visual and semantic object processing. The dataset includes structural MRI for source localization and eye-tracking data, providing rich temporal measurements of object representations.

Size

1.03 TB

Updated

Jun 23, 2026

This event-related potential (ERP) study investigates semantic and syntactic language processing in deaf readers by examining neural responses to grammatical violations and semantic anomalies. Participants viewed 180 sentences presented in rapid serial visual presentation (RSVP) format while EEG was recorded, with conditions including subject-verb agreement violations, semantic violations, combined violations, word-order violations, and correct control sentences. The research provides insights into the neural mechanisms underlying language comprehension in deaf populations.

Citations

1

Size

8.52 GB

Updated

Jun 26, 2026