Novel Noise Reduction Methods

  • Samu TauluEmail author
  • Juha Simola
  • Jukka Nenonen
  • Lauri Parkkonen
Reference work entry


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.


Noise suppression Signal processing Magnetic shielding Signal space Multichannel measurement Interference Calibration accuracy Cross talk Signal space projection Signal space separation Active compensation Principal component analysis Independent component analysis Spatial filtering Artifact 


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Samu Taulu
    • 1
    Email author
  • Juha Simola
    • 2
  • Jukka Nenonen
    • 3
  • Lauri Parkkonen
    • 4
    • 5
  1. 1.Department of Physics, Institute for Learning and Brain Sciences (I-LABS)University of WashingtonSeattleUSA
  2. 2.MEGINHelsinkiFinland
  3. 3.MEGIN (Elekta Oy)HelsinkiFinland
  4. 4.Department of Neuroscience and Biomedical EngineeringAalto University School of ScienceEspooFinland
  5. 5.MEGIN OyHelsinkiFinland

Section editors and affiliations

  • Seppo P. Ahlfors
    • 1
    • 2
  1. 1.Department of Radiology, MGH/HST Athinoula A. Martinos Center for Biomedical ImagingMassachusetts General HospitalCharlestown, MAUSA
  2. 2.Harvard-MIT Division of Health Sciences and TechnologyCambridgeUSA

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