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Recurrence Plots for Identifying Memory Components in Single-Trial EEGs

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Brain Informatics (BI 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6334))

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Abstract

The purpose of this study was to apply recurrence plots and recurrence quantification analysis (RQA) on event related potentials (ERPs) recorded during memory recognition tests. Data recorded during memory retrieval in four scalp region was used. Tow most important ERP’s components corresponding to memory retrieval, FN400 and LPC, were detected in recurrence plots computed for single-trial EEGs. In addition, the RQA was used to quantify changes in signal dynamic structure during memory retrieval, and measures of complexity as RQA variables were computed. Given the stimulus, amplitude of the RQA variables increases around 400ms, corresponding to dimension reduction of system. Furthermore, after 800ms these amplitudes decreased which can be as a consequence of an increase in system dimension and back to its basic state. The mean amplitude of Old items was more than New one.

Using this method, we found its ability to detect memory components of EEG signals and do a distinction between Old/ New items. In contrast with linear techniques recurrence plots and RQA do not need large number of recorded trials, and they can indicate changes in even single-trial EEGs. RQA can also show differences between old and new events in a memory process.

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Authors and Affiliations

  1. Department of Biomedical Engineering, Faculty of Engineering, Shahed University, Tehran, Iran

    Nasibeh Talebi & Ali Motie Nasrabadi

Authors
  1. Nasibeh Talebi
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  2. Ali Motie Nasrabadi
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, S4S 0A2, Regina, SK, Canada

    Yiyu Yao

  2. Rensselaer Polytechnic Institute, NY 12180, Troy, USA

    Ron Sun

  3. McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Tomaso Poggio

  4. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Jiming Liu

  5. Department of Life Science and Informatics, Maebashi Institute of Technology, 460-1 Kamisadori-Cho, 371.0816, Maebashi-City, Japan

    Ning Zhong

  6. York University, Toronto, ON, Canada

    Jimmy Huang

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© 2010 Springer-Verlag Berlin Heidelberg

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Talebi, N., Nasrabadi, A.M. (2010). Recurrence Plots for Identifying Memory Components in Single-Trial EEGs. In: Yao, Y., Sun, R., Poggio, T., Liu, J., Zhong, N., Huang, J. (eds) Brain Informatics. BI 2010. Lecture Notes in Computer Science(), vol 6334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15314-3_12

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  • DOI: https://doi.org/10.1007/978-3-642-15314-3_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15313-6

  • Online ISBN: 978-3-642-15314-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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