Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Forward and Inverse Problems of MEG/EEG

  • Sylvain Baillet
Living reference work entry
DOI: https://doi.org/10.1007/978-1-4614-7320-6_529-1


The quantitative analysis of scalp MEG and EEG data continues to generate a very diverse body of research based on the characterization of time-resolved brain activity. Some questions however require a more direct assessment of the anatomical substrate of cerebral dynamics. In many cases, modeling the neural generators of scalp MEG/EEG data is the method of choice. From a methodological standpoint, MEG/EEG source modeling is an “inverse problem”: a ubiquitous concept in many fields, from medical imaging to geophysics (Tarantola 2004). It builds a framework that helps conceptualize and formalize the fact that, in experimental sciences, models are confronted with observations to test a set of hypotheses and/or to estimate some parameters that were originally unknown. Parameters are quantities that can be changed without fundamentally invalidating the theoretical model. Predicting observations from a model with a given set of parameters is called forwardmodeling. The...


Boundary Element Method Inverse Modeling Head Model Equivalent Current Dipole Neural Source 
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Further Reading

  1. Stenroos M, Hunold A, Haueisen J (2014) Comparison of three-shell and simplified volume conductor models in magnetoencephalography. NeuroimageGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Sylvain Baillet
    • 1
  1. 1.McConnell Brain Imaging Centre, Montreal Neurological InstituteMcGill UniversityMontrealCanada