Abstract
BackgroundFor various reasons, the brain response activities in electroencephalography (EEG) signals are not perfectly synchronized between trials with respect to event markers—a problem commonly referred to as latency jitter. Experimental technologies have been greatly advanced to reduce technical timing errors and thereby reduce jitter. However, there remain intrinsic sources of jitter that are difficult to remove. The problem becomes more complicated when multiple sub-components possess different degrees and features of jitter. The jitter issue renders trial-averaged ERP inaccurate and even misleading. Effective methods for correcting ERP distortion due to latency jitter are needed. New MethodThis study developed a simple and easy-to-use method and toolbox for correcting ERP jitter based on simple signal processing theories, named ReSync. ReSync can be used to correct multiple overlapping ERP sub-components with different degrees of jitter (including static sub-components) without their affecting each other. ResultsThe theories, principles, technical details, and limitations of ReSync are presented in this paper, along with a series of simulation and real data examples used to evaluate and validate the method. Comparison with Existing MethodsReSync was conceptually compared with previous methods in the literature that are related to tackling of the jitter issue from theoretical, methodological, and technical perspectives. ConclusionsProviding a novel approach to latency jitter estimation with automatic dominant frequency identification and integrated decomposition and reconstruction, the ReSync method was validated using both simulation and empirical data, and demonstrated to be an effective jitter-correction approach with implementational simplicity.
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