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Recurrence-Based Synchronization of Single Trials for EEG-Data Analysis

  • Matthias Ihrke
  • Hecke Schrobsdorff
  • J. Michael Herrmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5788)

Abstract

We introduce a method based on nonlinear system analysis to synchronize single-trial event-related potentials (ERPs) prior to averaging in order to account for trial-to-trial variability in processing speed. Results from artificial and real ERP-data are presented and our algorithm is shown to outperform existing solutions. The presented algorithms are available for download.

Keywords

Negative Priming Single Trial Dynamic Time Warping Distortion Function Recurrence Plot 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Matthias Ihrke
    • 1
    • 2
  • Hecke Schrobsdorff
    • 1
    • 2
  • J. Michael Herrmann
    • 1
    • 3
  1. 1.Bernstein Center for Computational Neuroscience GöttingenGermany
  2. 2.MPI for Dynamics and Self-OrganizationGöttingenGermany
  3. 3.Institute for Perception, Action and BehaviourUniversity of EdinburghEdinburghU.K.

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