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Related Experiment Videos

Model selection in electromagnetic source analysis with an application to VEFs.

Lourens J Waldorp1, Hilde M Huizenga, Raoul P P P Grasman

  • 1Department of Psychology, University of Amsterdam, The Netherlands. waldorp@psy.uva.nl

IEEE Transactions on Bio-Medical Engineering
|October 11, 2002
PubMed
Summary

Determining the correct number of electromagnetic sources for EEG/MEG analysis is crucial. New model selection procedures (MSPs) like the adjusted Hotelling

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Area of Science:

  • Neuroscience
  • Biophysics
  • Signal Processing

Background:

  • Accurate electromagnetic source analysis requires determining the optimal number of sources.
  • Electroencephalography (EEG) and magnetoencephalography (MEG) data analysis relies on effective model selection procedures (MSPs).

Purpose of the Study:

  • To evaluate the effectiveness of existing and novel MSPs for estimating the number of sources in EEG/MEG data.
  • To compare MSP performance under various source configurations (close/distant) and noise conditions (correlated/uncorrelated).

Main Methods:

  • Simulation of EEG/MEG data with varying numbers of sources and noise types.
  • Application and comparison of several MSPs, including residual variance, adjusted Hotelling's test, Bayes information criterion, and Wald test.

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  • Validation using empirical visual evoked field data.

    • Main Results:

    • The commonly used residual variance MSP is often ineffective, tending to overestimate the number of sources.
    • The adjusted Hotelling's test, Bayes information criterion, and Wald test on source amplitudes demonstrate superior effectiveness.
    • The choice of the best MSP depends on whether a conservative or liberal approach is desired.

    Conclusions:

    • The adjusted Hotelling's test is recommended for conservative source number estimation.
    • Bayes information criterion and the Wald test are suitable for more liberal source number estimation.
    • These findings provide guidance for selecting appropriate MSPs in electromagnetic source analysis.