NeuroMorph: A High-Temporal Resolution MEG Dataset for Morpheme-Based Linguistic Analysis
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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.
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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.