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

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.