Validating EEG source imaging using intracranial electrical stimulation

Abstract

Electrical source imaging is used in the presurgical epilepsy evaluation and in cognitive neurosciences to localize neuronal sources of brain potentials recorded on EEG. This study evaluates spatial accuracy of electrical source imaging for known sources, using electrical stimulation potentials recorded on simultaneous stereo-EEG and 37-electrode scalp EEG, and identifies factors determining the localization error. In 11 patients undergoing simultaneous stereo-EEG and 37-electrode scalp EEG recordings, sequential series of 99-110 biphasic pulses (2-millisecond pulse width) were applied by bipolar electrical stimulation on adjacent contacts of implanted stereo-EEG electrodes. The scalp EEG correlates of stimulation potentials were recorded with a sampling rate of 30 kHz. Electrical source imaging of averaged stimulation potentials was calculated utilizing a dipole source model of peak stimulation potentials based on individual four compartment finite element method head models with various skull conductivities (range from 0.0413 to 0.001 S/m). Fitted dipoles with goodness of fit of ≥80% were included into the analysis. The localization error was calculated using Euclidean distance between the estimated dipoles and the center point of adjacent stimulating contacts. A total of 3,619 stimulation locations, respectively dipole localizations, were included in the evaluation. Mean localization errors ranged from 10.3 to 26 mm, depending on source depth and selected skull conductivity. The mean localization error increased with an increase of source depth (r (3,617) = [0.19], P = 0.000) and decreased with an increase of skull conductivity (r (3,617) = [-0.26], P = 0.000). High skull conductivities (0.0413-0.0118 S/m) yielded significantly lower localization errors for all source depths. For superficial sources (<20 mm from inner skull), all skull conductivities yielded insignificantly different localization error. However, for deeper sources, in particular > 40 mm, high skull conductivities of 0.0413 and 0.0206 S/m yielded significantly lower localization errors. In relation to stimulation locations, the majority of estimated dipoles moved outward-forward-downward to inward-forward-downward with a decrease of source depth and an increase of skull conductivity. Multivariate analysis revealed that an increase of source depth, number of skull holes, and white matter volume, while decrease of skull conductivity independently led to higher localization error. This evaluation of electrical source imaging accuracy using artificial patterns with high signal to noise ratio supports its application in presurgical epilepsy evaluation and cognitive neurosciences. In our artificial potentials model, optimizing the selected skull conductivity minimized the localization error. Future studies should examine if this accounts for true neural signals.

Semiautomated electric source imaging determines epileptogenicity of encephaloceles in temporal lobe epilepsy

“…The yield of ESI could likely be enhanced through the utilization of improved head models or alternative scalp EEG setups with comprehensive coverage of the temporal pole. Additionally, the spatial accuracy of ESI might be further improved by employing a more detailed finite element head model and individualized conductivity thresholds 42 . An open question remains regarding the possibility of replacing sphenoidal electrodes with scalp EEG setups that comprehensively cover the temporal pole 35 .…”

“…Additionally, the spatial accuracy of ESI might be further improved by employing a more detailed finite element head model and individualized conductivity thresholds. 42 An open question remains regarding the possibility of replacing sphenoidal electrodes with scalp EEG setups that comprehensively cover the temporal pole. 35 It is possible that evenly spaced scalp EEG setups with higher electrode counts and better whole brain coverage could offer more precise tracing of IED propagation paths and aid presurgical evaluations for variable pathologies.…”

How to assess the accuracy of volume conduction models? A validation study with stereotactic EEG data

“…One indirect way to validate volume conduction models is to compare source reconstruction results with known intracranial sources, in terms of source location, magnitude, and orientation. In several studies (e.g., in Cohen et al, 1990 ; Murakami et al, 2016 ; Mikulan et al, 2020 ; Unnwongse et al, 2023 ), such validation has been performed without, nevertheless, studying the influence of the forward model accuracy on the source reconstruction results. In contrast, Leahy et al ( 1998 ) performed such validation in a three-layered human phantom, concluding that the influence of using a realistic head model instead of a sphere for computing the forward solution was found to be minimal on the location mismatch.…”

Recent advances in clinical electroencephalography

“…One of the challenges validating ESI is the lack of a perfect gold standard for the localization, since all approaches have advantages and disadvantages. This was circumvented by analyzing the location of single pulse electric stimulation [11,12]. Although this is an artificial signal (as opposed to epileptiform discharges generated in the cortical neurons), the location of the source (i.e., the cortically placed electrode contacts) is certain, and these studies provide important information about the accuracy and biophysical limitations of ESI.…”