bioelectric potentials; brain-computer interfaces; electroencephalography; filtering theory; magnetoencephalography; medical signal processing; signal denoising; BCI experiment; P300 responses; brain dynamics; brain-computer interfacing; data-driven approach; event sequence recognition; event-related potential recognition; high density magnetoencephalography data; high density sensor arrays; high-density MEG recording; hypothesis-driven channel selection; information transfer rate improvement; initial decoding approach; noise reduction; signal extraction; single trial potentials; spatiotemporal filters; Brain modeling; Correlation; Decoding; Electroencephalography; Signal to noise ratio; Yttrium;
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机译:一种用于识别高密度mEG记录中事件相关电位的高效解码器