Dataset of 37-subject EEG recordings using a low-cost mobile EEG headset during a semantic relatedness judgment task

Abstract

This data article presents electroencephalography (EEG) data and behavioral responses from a study examining the efficacy of a consumer-grade EEG headset (InteraXon Muse 2) in measuring the N400 component, a neural marker of semantic processing. These data are linked to the article “Exploring the Utility of the Muse Headset for Capturing the N400: Dependability and Single-Trial Analysis”. Data were collected from 37 adult native speakers of English while they completed a semantic relatedness judgment task. Participants were presented with pairs of words and asked to judge whether the word pairs were semantically related (e.g., "pedal-bike") or unrelated (e.g., "icing-bike"). This dataset provides raw and preprocessed EEG data, alongside behavioral data (accuracy, response times) and comprehensive metadata. The MATLAB scripts for EEG analysis and the Python code for stimulus presentation and data acquisition are also included. These data offer a valuable resource for researchers interested in exploring the potential of consumer-grade EEG for language research. They can also be used to further investigate electrophysiological markers of semantic processing under different analysis parameters or in conjunction with other publicly available datasets.