Residue iteration decomposition (RIDE): A new method to separate ERP components on the basis of latency variability in single trials

Guang Ouyang, Grit Herzmann, Changsong ZHOU*, Werner Sommer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

98 Citations (Scopus)

Abstract

Event-related brain potentials (ERPs) are important research tools because they provide insights into mental processing at high temporal resolution. Their usefulness, however, is limited by the need to average over a large number of trials, sacrificing information about the trial-by-trial variability of latencies or amplitudes of specific ERP components. Here we propose a novel method based on an iteration strategy of the residues of averaged ERPs (RIDE) to separate latency-variable component clusters. The separated component clusters can then serve as templates to estimate latencies in single trials with high precision. By applying RIDE to data from a face-priming experiment, we separate priming effects and show that they are robust against latency shifts and within-condition variability. RIDE is useful for a variety of data sets that show different degrees of variability and temporal overlap between ERP components.

Original languageEnglish
Pages (from-to)1631-1647
Number of pages17
JournalPsychophysiology
Volume48
Issue number12
DOIs
Publication statusPublished - Dec 2011

Scopus Subject Areas

  • Neuroscience(all)
  • Neuropsychology and Physiological Psychology
  • Experimental and Cognitive Psychology
  • Neurology
  • Endocrine and Autonomic Systems
  • Developmental Neuroscience
  • Cognitive Neuroscience
  • Biological Psychiatry

User-Defined Keywords

  • Component separation
  • Event-related potentials
  • Face recognition
  • Mental chronometry
  • Single-trial responses

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