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

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Intelligent Data Engineering and Automated Learning - IDEAL 2009 (IDEAL 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5788))

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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.

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Author information

Authors and Affiliations

  1. Bernstein Center for Computational Neuroscience Göttingen, Germany

    Matthias Ihrke, Hecke Schrobsdorff & J. Michael Herrmann

  2. MPI for Dynamics and Self-Organization, Bunsenstr. 10, 37073, Göttingen, Germany

    Matthias Ihrke & Hecke Schrobsdorff

  3. Institute for Perception, Action and Behaviour, University of Edinburgh, Informatics Forum, 10 Crichton Street, Edinburgh, EH8 9AB, U.K.

    J. Michael Herrmann

Authors
  1. Matthias Ihrke
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  2. Hecke Schrobsdorff
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  3. J. Michael Herrmann
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Editor information

Editors and Affiliations

  1. Escuela Politécnica Superior, Universidad de Burgos, Calle Francisco de Vitoria, S/N, Edifico C, 09006, Burgos, Spain

    Emilio Corchado

  2. School of Electrical and Electronic Engineering, University of Manchester, Sackville Street Building, Sackville Street, M60 1QD, Manchester, UK

    Hujun Yin

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Ihrke, M., Schrobsdorff, H., Herrmann, J.M. (2009). Recurrence-Based Synchronization of Single Trials for EEG-Data Analysis. In: Corchado, E., Yin, H. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2009. IDEAL 2009. Lecture Notes in Computer Science, vol 5788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04394-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-04394-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04393-2

  • Online ISBN: 978-3-642-04394-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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