M 3 CV: A multi-subject, multi-session, and multi-task database for EEG-based biometrics challenge

• Published in: NeuroImage (Orlando, Fla.) Vol. 264; p. 119666
• Main Authors: Huang, Gan, Hu, Zhenxing, Chen, Weize, Zhang, Shaorong, Liang, Zhen, Li, Linling, Zhang, Li, Zhang, Zhiguo
• Format: Journal Article
• Language: English
• Published: United States Elsevier Limited 01.12.2022
• Subjects: Algorithms; Attention; Biometrics; Brain research; Brain-Computer Interfaces; Cognitive ability; Competition; Databases, Factual; Datasets; Deep learning; EEG; Electroencephalography; Electroencephalography - methods; Experiments; Humans; Learning algorithms; Machine Learning; Paradigms

EEG signals exhibit commonality and variability across subjects, sessions, and tasks. But most existing EEG studies focus on mean group effects (commonality) by averaging signals over trials and subjects. The substantial intra- and inter-subject variability of EEG have often been overlooked. The rec...