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Accuracy of SEEG Source Localization: A Pilot Study Using Corticocortical Evoked Potentials.

Benjamin C Cox1,2, Rachel J Smith3, Ismail Mohamed4

  • 1Department of Neurology, University of Alabama at Birmingham, Birmingham, AL.

Journal of Clinical Neurophysiology : Official Publication of the American Electroencephalographic Society
|February 3, 2025
PubMed
Summary

This study evaluated EEG source localization algorithms for intracranial EEG (iEEG) using corticocortical evoked potentials. Minimum norm, L1 norm, LP norm, and SWARM algorithms showed the best performance for iEEG source localization.

Keywords:
Corticocortical evoked potentialsDrug-resistant epilepsyEEG source localizationEpilepsy surgeryStereotactic EEG

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Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Scalp EEG source localization is established for epilepsy, but its efficacy with intracranial EEG (iEEG) requires further study.
  • Sensor placement and spatial sampling differences may impact iEEG source localization accuracy.
  • Corticocortical evoked potentials offer a method to validate iEEG source localization algorithms due to known stimulation sites.

Purpose of the Study:

  • To evaluate the accuracy of 11 distributed EEG source localization algorithms using iEEG.
  • To compare the performance of these algorithms based on localization error and spatial dispersion.
  • To identify optimal algorithms for iEEG source localization in epilepsy.

Main Methods:

  • Recorded 205 sets of corticocortical evoked potentials from four epilepsy patients undergoing iEEG.
  • Analyzed averaged potentials using 11 distributed source algorithms.
  • Quantified localization error and spatial dispersion, comparing algorithms using Wilcoxon signed-rank tests.

Main Results:

  • Minimum norm, L1 norm, LP norm, sLORETA, SWARM, eLORETA, swLORETA, and ssLORETA demonstrated the least localization error (13.3–15.7 mm).
  • FOCUSS showed the smallest spatial dispersion (7.4 mm), followed by minimum norm, L1 norm, LP norm, and SWARM (20.8–28.3 mm).
  • Gray matter stimulation generally yielded lower localization error than white matter stimulation across most algorithms.

Conclusions:

  • Minimum norm, L1 norm, LP norm, and SWARM algorithms effectively localize iEEG corticocortical evoked potentials.
  • These algorithms exhibit favorable localization error and spatial dispersion for iEEG.
  • Further research with larger cohorts is recommended to validate these findings.