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Exploring the Variability of Single Trials in Somatosensory Evoked Responses Using Constrained Source Extraction and RMT
2008
IEEE Transactions on Biomedical Engineering
This paper describes the theoretical background of a new data-driven approach to encephalographic single-trial (ST) data analysis. Temporal constrained source extraction using sparse decomposition identifies signal topographies that closely match the shape characteristics of a reference signal, one response for each ST. The correlations between these ST topographies are computed for formal Correlation Matrix Analysis (CMA) based on Random Matrix Theory (RMT). The RMT-CMA provides clusters of
doi:10.1109/tbme.2008.915708
pmid:18334387
fatcat:fzqafxjinreqjlikzituj6axuy