Evaluation and Extraction of Mismatch Negativity through Independent Component Analysis and Wavelet Decomposition

摘要

Mismatch negativity (MMN) is an event- related potential (ERP) which reflects the detection of a mismatch between the incoming deviant stimulus and the memory representation of the preceding standard stimuli. In this study MMN is elicited by the conventional oddball paradigm, so we focused on comparing procedures for extracting MMN and compared conventional difference wave (DW), Wavelet decomposition and independent component analysis (ICA) decomposition procedures. The main aim of this research is to extract and remove other evoked components (N1, P1) in order to eliminate their influence on MMN, since it can be overlapping. Wavelet decomposition of the grand averaged signal extracts components that do not contain information about MMN, but whose removal get clearly defined MMN. It has been shown that MMN extracted by ICA decomposition of standard and deviant stimuli, compared with DW, does not differ in latency for each participant.