Restoring Latency-Variable ERP Components from Single Trials: A New Approach to ERP Analysis with Residue Iteration Decomposition (RIDE)?
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1
Hong Kong Baptist University, Department of Physics and Centre for Nonlinear Studies and The Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, China
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2
Humboldt-Universität zu Berlin, Department of Psychology, Germany
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3
Hong Kong Baptist University, Department of Physics and Centre for Nonlinear Studies and The Beijing–Hong Kong–Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, China
The conventional average event-related potential (ERP) is a straightforward method to remove noise and reveal sensory, cognitive, and motoric components. However, due to trial-to-trial variability in the timing of cognitive sub-processes, components in the average ERP may be only more or less blurred representations of the brain activities reflecting specific cognitive sub-processes. Furthermore, rich dynamic information in single trials is lost by averaging. A more appropriate method of ERP analysis can be built on a model taking into account the single trial latency variability of specific ERP sub-components. Here we propose a model in which ERPs are composed of several temporally overlapping component clusters that are (a) synchronized to stimuli or responses or (b) non-synchronized to external events and variable in latency. Based on this model we developed a new method for the decomposition and reconstruction of ERPs, Residue Iteration Decomposition (RIDE). We describe the principles of RIDE and compare it with other temporal and spatial ERP decomposition methods, showing that 1) RIDE overcomes several major problems in existing decomposition methods, 2) obtains latency-corrected waveforms and topographies for each sub-component, and 3) retrieves single trial latency and amplitude information for each separated component. RIDE has been tested with several datasets yielding highly consistent results across participants, conditions, and experimental paradigms. RIDE can also reconstruct average ERPs by latency-correcting the separated single trial component clusters. RIDE-reconstructed ERPs may be a promising new approach in ERP research as it greatly enhances the waveforms of conventional ERPs blurred by latency variability, resolving a notorious problem in many research areas, such as, aging, psychopathology, cognition, and individual differences.
Keywords:
ERP,
ERP decomposition methods,
latency correction,
latency variability,
Residue Iteration Decomposition
Conference:
XII International Conference on Cognitive Neuroscience (ICON-XII), Brisbane, Queensland, Australia, 27 Jul - 31 Jul, 2014.
Presentation Type:
Poster
Topic:
Methods Development
Citation:
Ouyang
G,
Sommer
W and
Zhou
C
(2015). Restoring Latency-Variable ERP Components from Single Trials: A New Approach to ERP Analysis with Residue Iteration Decomposition (RIDE)?.
Conference Abstract:
XII International Conference on Cognitive Neuroscience (ICON-XII).
doi: 10.3389/conf.fnhum.2015.217.00256
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Received:
19 Feb 2015;
Published Online:
24 Apr 2015.
*
Correspondence:
Dr. Guang Ouyang, Hong Kong Baptist University, Department of Physics and Centre for Nonlinear Studies and The Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong, China, guang.ouyang@gmail.com
Dr. Changsong Zhou, Hong Kong Baptist University, Department of Physics and Centre for Nonlinear Studies and The Beijing–Hong Kong–Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong, China, cszhou@hkbu.edu.hk