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Updated: May 10, 2026

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
Published on: November 1, 2019
Forward and inverse electroencephalographic modeling in health and in acute traumatic brain injury
Andrei Irimia1, S Y Matthew Goh, Carinna M Torgerson
1Laboratory of Neuro Imaging, Department of Neurology, University of California, Los Angeles, CA 90095, USA.
Objective:
EEG source localization is demonstrated in three cases of acute traumatic brain injury (TBI) with progressive lesion loads using anatomically faithful models of the head which account for pathology.
Methods:
Multimodal magnetic resonance imaging (MRI) volumes were used to generate head models via the finite element method (FEM). A total of 25 tissue types-including 6 types accounting for pathology-were included. To determine the effects of TBI upon source localization accuracy, a minimum-norm operator was used to perform inverse localization and to determine the accuracy of the latter.
Results:
The importance of using a more comprehensive number of tissue types is confirmed in both health and in TBI. Pathology omission is found to cause substantial inaccuracies in EEG forward matrix calculations, with lead field sensitivity being underestimated by as much as ≈ 200% in (peri-) contusional regions when TBI-related changes are ignored. Failing to account for such conductivity changes is found to misestimate substantial localization error by up to 35 mm.
Conclusions:
Changes in head conductivity profiles should be accounted for when performing EEG modeling in acute TBI.
Significance:
Given the challenges of inverse localization in TBI, this framework can benefit neurotrauma patients by providing useful insights on pathophysiology.
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