Overcoming limitations of the ERP method with Residue Iteration Decomposition (RIDE): A demonstration in go/no-go experiments
- This work was partially supported by the HKBU Strategic Development Fund and the Hong Kong Research Grants Council (HKBU 202710) to G.O. and C.Z., a grant by the German Academic Exchange Service (DAAD) to G.O., and a grant by the German Research Foundation to W.S. (So177/17-1). This research was conducted using the resources of the High Performance Cluster Computing Centre, Hong Kong Baptist University, which receives funding from Research Grant Council, University Grant Committee of the HKSAR and Hong Kong Baptist University.
Address correspondence to: Werner Sommer, Humboldt-Universität zu Berlin, Department of Psychology, Rudower Chaussee 18, D-12489 Berlin, Germany; E-mail: Werner.firstname.lastname@example.org; or Changsong Zhou, Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong; E-mail: email@example.com
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 Residue Iteration Decomposition (RIDE), demonstrated with data from representative go/no-go experiments. The overlap of N2 and P3 components in go/no-go data gives rise to spurious topographical localization of the no-go–N2 component. RIDE decomposes N2 and P3 based on their latency variability. The decomposition restored the N2 topography by removing the contamination from latency-variable late components. The RIDE-derived N2 and P3 give a clearer insight about their functional relevance in the go/no-go paradigm.