NeuroMorph: A High-Temporal Resolution MEG Dataset for Morpheme-Based Linguistic Analysis
[ presented at variable stimulus onset asynchronies (60-600 ms). The dataset comprises 31-channel EEG recordings at 1000 Hz acquired with BrainProducts BrainAmp DC, designed to evaluate Bayesian optimization strategies for automated selection of individually optimal stimulation parameters in brain-computer interface applications.
This dataset comprises simultaneous intracranial EEG, scalp EEG, and beamforming-reconstructed source data from fifteen epilepsy patients performing a verbal working memory task. Subjects completed a modified Sternberg task with temporally separated encoding, maintenance, and recall phases. The dataset includes electrode coordinates, anatomical labels, and trial-level behavioral information, enabling investigation of working memory mechanisms through multimodal electrophysiological recordings and source reconstruction.
…Two experimental paradigms were compared: (1) traditional cue-based with visual and…
…Complete a semi-automated driving task involving lane maintenance, following distance from…
…and Müller, H.J. (2010), Dimension-based attention modulates early visual processing…