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An Introduction to EEG Source Analysis with an Illustration of a Study on Error-Related Potentials

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Guide to Brain-Computer Music Interfacing

Abstract

Over the last twenty years, blind source separation (BSS) has become a fundamental signal processing tool in the study of human electroencephalography (EEG), other biological data, as well as in many other signal processing domains such as speech, images, geophysics, and wireless. This chapter introduces a short review of brain volume conduction theory, demonstrating that BSS modeling is grounded on current physiological knowledge. Then, it illustrates a general BSS scheme requiring the estimation of second-order statistics (SOS) only. A simple and efficient implementation based on the approximate joint diagonalization of covariance matrices (AJDC) is described. The method operates in the same way in the time or frequency domain (or both at the same time) and is capable of modeling explicitly physiological and experimental source of variations with remarkable flexibility. Finally, this chapter provides a specific example illustrating the analysis of a new experimental study on error-related potentials.

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Notes

  1. 1.

    Such processes are called colored, in opposition to iid processes, which are called white.

  2. 2.

    This paper does not consider SOS but fourth-order statistics; however, the algorithms are based on approximate joint diagonalization of matrices which are the slices of the tensor of fourth-order cumulants and thus can be used for SOS matrices as well.

  3. 3.

    Two vectors are collinear if they are equal out of a scaling factor, that is, the energy profile is proportional.

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Authors and Affiliations

  1. GIPSA-lab, CNRS and Grenoble University, 11 rue des Mathématiques, Domaine universitaire—BP 46, Grenoble, 38402, France

    Marco Congedo, Sandra Rousseau & Christian Jutten

Authors
  1. Marco Congedo
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  2. Sandra Rousseau
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  3. Christian Jutten
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Correspondence to Marco Congedo .

Editor information

Editors and Affiliations

  1. Interdisciplinary Centre for Computer Music Research (ICCMR), Plymouth University, Plymouth, United Kingdom

    Eduardo Reck Miranda

  2. Immersion, Bordeaux, France

    Julien Castet

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Congedo, M., Rousseau, S., Jutten, C. (2014). An Introduction to EEG Source Analysis with an Illustration of a Study on Error-Related Potentials. In: Miranda, E., Castet, J. (eds) Guide to Brain-Computer Music Interfacing. Springer, London. https://doi.org/10.1007/978-1-4471-6584-2_8

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  • DOI: https://doi.org/10.1007/978-1-4471-6584-2_8

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