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2015 | OriginalPaper | Chapter

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

Authors : Marina Paprika, Krešimir Friganović, Mario Cifrek

Published in: 6th European Conference of the International Federation for Medical and Biological Engineering

Publisher: Springer International Publishing

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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.

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Metadata
Title
Evaluation and Extraction of Mismatch Negativity through Independent Component Analysis and Wavelet Decomposition
Authors
Marina Paprika
Krešimir Friganović
Mario Cifrek
Copyright Year
2015
DOI
https://doi.org/10.1007/978-3-319-11128-5_24