Interaction Between Noise and Lesion Modeling Errors on EEG Source Localization Accuracy

Abstract

EEG dipole source reconstruction requires the assumption of a source model and of a conductive head model. Head-modeling errors and measurement noise in the EEG induce localization errors in the results of EEG source analysis. In this study effects of brain lesions on EEG dipole source localization have been investigated by computer simulation. We present a sensitivity study quantifying the effect on source localization accuracy of the interaction between the uncertainty in lesion conductivity assignment (LCA) and various levels of signal to noise ratio (SNR) in the EEGs. An inverse dipole fitting procedure, based on simulated noiseless EEG measurements and with SNR 5, 10 and 15, was carried out in 5 pathological situations, assuming an incorrect LCA ranging from a half to twice the real value. Incorrect LCA in noiseless conditions led to markedly wrong source reconstruction for high lesion conductivity values (localization errors up to 1.7 cm). We propose a method based on residual error analysis to improve lesion conductivity estimate. This procedure can identify lesion tissue conductivity with only a few percent error reducing the LE to value given by noise only.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411607

Entities

People

  • F. Vatta
  • P. Bruno
  • P. Inchingolo

Organizations

  • University of Trieste

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Abstracts
  • Accuracy
  • Conductivity
  • Data Processing
  • Data Sets
  • Electrical Properties
  • Electrodes
  • Errors
  • Inverse Problems
  • Military Research
  • Noise
  • Noise Reduction
  • Residuals
  • Sensitivity
  • Simulations
  • Universities
  • White Noise

Readers

  • Acoustical Oceanography.
  • Neuroscience
  • Regression Analysis.