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Overcoming limitations of the ERP method with R esidue I teration D ecomposition ( RIDE ): A demonstration in go/no‐go experiments
Author(s) -
Ouyang Guang,
Schacht Annekathrin,
Zhou Changsong,
Sommer Werner
Publication year - 2013
Publication title -
psychophysiology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.661
H-Index - 156
eISSN - 1469-8986
pISSN - 0048-5772
DOI - 10.1111/psyp.12004
Subject(s) - latency (audio) , spurious relationship , psychology , event related potential , computer science , cognition , neuroscience , telecommunications , machine learning
Abstract The usefulness of the event‐related potential ( ERP ) method can be compromised by violations of the underlying assumptions, for example, confounding variations of latency and amplitude of ERP components within and between conditions. Here we show how the ERP subtraction method might yield misleading information due to latency variability of ERP components. We propose a solution to this problem by correcting for latency variability using R esidue I teration D ecomposition ( RIDE ), demonstrated with data from representative go/no‐go experiments. The overlap of N 2 and P 3 components in go/no‐go data gives rise to spurious topographical localization of the no‐go– N 2 component. RIDE decomposes N 2 and P 3 based on their latency variability. The decomposition restored the N 2 topography by removing the contamination from latency‐variable late components. The RIDE ‐derived N 2 and P 3 give a clearer insight about their functional relevance in the go/no‐go paradigm.