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Compensation for Speed-of-Processing Effects in EEG-Data Analysis

  • Matthias Ihrke
  • Hecke Schrobsdorff
  • J. Michael Herrmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5326)

Abstract

We study averaging schemes that are specifically adapted to the analysis of electroencephalographic data for the purpose of interpreting temporal information from single trials. We find that a natural assumption about processing speed in the subjects yields a complex but nevertheless robust algorithm for the analysis of electrophysiological data.

Keywords

Negative Priming Dynamic Time Warping Subdivision Scheme Biological Cybernetic Late Positive Complex 
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 2008

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 Edinburgh Informatics ForumEdinburghU.K.

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