Virtual stimulation of the interictal EEG network localizes the EZ as a measure of cortical excitability

<b>Introduction:</b> For patients with drug-resistant epilepsy, successful localization and surgical treatment of the epileptogenic zone (EZ) can bring seizure freedom. However, surgical success rates vary widely because there are currently no clinically validated biomarkers of the EZ. Highly epileptogenic regions often display increased levels of cortical excitability, which can be probed using single-pulse electrical stimulation (SPES), where brief pulses of electrical current are delivered to brain tissue. It has been shown that high-amplitude responses to SPES can localize EZ regions, indicating a decreased threshold of excitability. However, performing extensive SPES in the epilepsy monitoring unit (EMU) is time-consuming. Thus, we built patient-specific <i>in silico</i> dynamical network models from interictal intracranial EEG (iEEG) to test whether virtual stimulation could reveal information about the underlying network to identify highly excitable brain regions similar to physical stimulation of the brain. <b>Methods:</b> We performed virtual stimulation in 69 patients that were evaluated at five centers and assessed for clinical outcome 1 year post surgery. We further investigated differences in observed SPES iEEG responses of 14 patients stratified by surgical outcome. <b>Results:</b> Clinically-labeled EZ cortical regions exhibited higher excitability from virtual stimulation than non-EZ regions with most significant differences in successful patients and little difference in failure patients. These trends were also observed in responses to extensive SPES performed in the EMU. Finally, when excitability was used to predict whether a channel is in the EZ or not, the classifier achieved an accuracy of 91%. <b>Discussion:</b> This study demonstrates how excitability determined via virtual stimulation can capture valuable information about the EZ from interictal intracranial EEG.

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Publication Details

Journal
Frontiers in Network Physiology
Published
2024-08-20
DOI
https://doi.org/10.3389/fnetp.2024.1425625
Citations
2
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.69

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article

Virtual stimulation of the interictal EEG network localizes the EZ as a measure of cortical excitability

Varina L. Boerwinkle, Sarah N. Wyckoff, Jorge Alvaro Gonzalez-Martinez, Sara K. Inati et al.
2 citations
Frontiers in Network Physiology
EEG and Brain-Computer Interfaces
0.69
article

Virtual stimulation of the interictal EEG network localizes the EZ as a measure of cortical excitability

Varina L. Boerwinkle, Sarah N. Wyckoff, Jorge Alvaro Gonzalez-Martinez, Sara K. Inati, Rachel J. Smith, Michael Kinsman, Patrick Landazuri, Niravkumar Barot, Kareem A. Zaghloul, Adam G. Rouse, Nathan E. Crone, Sophia R. Zhai, Nathaniel Cameron, Jennifer J. Cheng, Carol M. Ulloa, Kristin M. Gunnarsdottir, Joon Y. Kang, Sridevi V. Sarma, Utku Uysal
article en
2 citations

Abstract

<b>Introduction:</b> For patients with drug-resistant epilepsy, successful localization and surgical treatment of the epileptogenic zone (EZ) can bring seizure freedom. However, surgical success rates vary widely because there are currently no clinically validated biomarkers of the EZ. Highly epileptogenic regions often display increased levels of cortical excitability, which can be probed using single-pulse electrical stimulation (SPES), where brief pulses of electrical current are delivered to brain tissue. It has been shown that high-amplitude responses to SPES can localize EZ regions, indicating a decreased threshold of excitability. However, performing extensive SPES in the epilepsy monitoring unit (EMU) is time-consuming. Thus, we built patient-specific <i>in silico</i> dynamical network models from interictal intracranial EEG (iEEG) to test whether virtual stimulation could reveal information about the underlying network to identify highly excitable brain regions similar to physical stimulation of the brain. <b>Methods:</b> We performed virtual stimulation in 69 patients that were evaluated at five centers and assessed for clinical outcome 1 year post surgery. We further investigated differences in observed SPES iEEG responses of 14 patients stratified by surgical outcome. <b>Results:</b> Clinically-labeled EZ cortical regions exhibited higher excitability from virtual stimulation than non-EZ regions with most significant differences in successful patients and little difference in failure patients. These trends were also observed in responses to extensive SPES performed in the EMU. Finally, when excitability was used to predict whether a channel is in the EZ or not, the classifier achieved an accuracy of 91%. <b>Discussion:</b> This study demonstrates how excitability determined via virtual stimulation can capture valuable information about the EZ from interictal intracranial EEG.

Frontiers in Network PhysiologyVol. 4
National Institutes of Health (US), Barrow Neurological Institute (US), Johns Hopkins University (US), University of Pittsburgh (US), University of Alabama at Birmingham (US), National Institute of Neurological Disorders and Stroke (US), Phoenix Children's Hospital (US), University of Kansas Medical Center (US)
Citizens United for Research in Epilepsy, Oak Ridge Associated Universities, Epilepsy Society, National Institutes of Health
Openalex Percentile: Top 31%
EEG and Brain-Computer Interfaces
0.69
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