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Novel Noise Reduction Methods

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Magnetoencephalography

Abstract

Magnetoencephalography (MEG) is a noninvasive neuroimaging tool that offers a combination of excellent temporal and good spatial resolution, provided that the acquired signals have a high-enough signal-to-noise ratio. This requirement is often compromised as MEG signals are very weak and often masked by interfering signals from environmental noise sources present at most MEG sites. Even more challenging interference is encountered if the subject carries any magnetic material attached to the body, which is sometimes inevitable in clinical settings, e.g., due to therapeutic stimulators. Therefore, to enable reliable data analysis, it is very important to reduce the contribution of noise in MEG signals as efficiently as possible. In this chapter, we review the basic characteristics of MEG signals, give a short review on traditional approaches to suppress noise, and describe some examples of modern noise reduction methods. Specifically, we emphasize the usefulness of advanced mathematical algorithms applied on the multichannel MEG data.

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Authors and Affiliations

  1. Department of Physics, Institute for Learning and Brain Sciences (I-LABS), University of Washington, Seattle, WA, USA

    Samu Taulu

  2. MEGIN, Helsinki, Finland

    Juha Simola

  3. MEGIN (Elekta Oy), Helsinki, Finland

    Jukka Nenonen

  4. Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland

    Lauri Parkkonen

  5. MEGIN Oy, Helsinki, Finland

    Lauri Parkkonen

Authors
  1. Samu Taulu
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  2. Juha Simola
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  3. Jukka Nenonen
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  4. Lauri Parkkonen
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Corresponding author

Correspondence to Samu Taulu .

Editor information

Editors and Affiliations

  1. Faculty of Science, Department of Physics, University of Zagreb, Zagreb, Croatia

    Selma Supek

  2. Reno, NV, USA

    Cheryl J. Aine

Section Editor information

  1. Department of Radiology, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, MA, USA

    Seppo P. Ahlfors

  2. Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA

    Seppo P. Ahlfors

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Taulu, S., Simola, J., Nenonen, J., Parkkonen, L. (2019). Novel Noise Reduction Methods. In: Supek, S., Aine, C. (eds) Magnetoencephalography. Springer, Cham. https://doi.org/10.1007/978-3-030-00087-5_2

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