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Zhai SR, Sarma SV, Gunnarsdottir K, Crone NE, Rouse AG, Cheng JJ, Kinsman MJ, Landazuri P, Uysal U, Ulloa CM, Cameron N, Inati S, Zaghloul KA, Boerwinkle VL, Wyckoff S, Barot N, González-Martínez JA, Kang JY, Smith RJ. Virtual stimulation of the interictal EEG network localizes the EZ as a measure of cortical excitability. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1425625. [PMID: 39229346 PMCID: PMC11368849 DOI: 10.3389/fnetp.2024.1425625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Accepted: 07/24/2024] [Indexed: 09/05/2024]
Abstract
Introduction: 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 in silico 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. Methods: 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. Results: 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%. Discussion: This study demonstrates how excitability determined via virtual stimulation can capture valuable information about the EZ from interictal intracranial EEG.
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Affiliation(s)
- Sophia R. Zhai
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Sridevi V. Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Kristin Gunnarsdottir
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, United States
| | - Nathan E. Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Adam G. Rouse
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS, United States
| | - Jennifer J. Cheng
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS, United States
| | - Michael J. Kinsman
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS, United States
| | - Patrick Landazuri
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS, United States
| | - Utku Uysal
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Carol M. Ulloa
- Department of Neurology, University of Kansas Medical Center, Kansas City, KS, United States
| | - Nathaniel Cameron
- Department of Neurosurgery, University of Kansas Medical Center, Kansas City, KS, United States
| | - Sara Inati
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Kareem A. Zaghloul
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, United States
| | - Varina L. Boerwinkle
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ, United States
| | - Sarah Wyckoff
- Barrow Neurological Institute, Phoenix Children’s Hospital, Phoenix, AZ, United States
| | - Niravkumar Barot
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | | | - Joon Y. Kang
- Department of Neurology, Johns Hopkins University, Baltimore, MD, United States
| | - Rachel June Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, United States
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Raghavan M, Pilet J, Carlson C, Anderson CT, Mueller W, Lew S, Ustine C, Shah-Basak P, Youssofzadeh V, Beardsley SA. Gamma amplitude-envelope correlations are strongly elevated within hyperexcitable networks in focal epilepsy. Sci Rep 2024; 14:17736. [PMID: 39085280 PMCID: PMC11291981 DOI: 10.1038/s41598-024-67120-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/08/2024] [Indexed: 08/02/2024] Open
Abstract
Methods to quantify cortical hyperexcitability are of enormous interest for mapping epileptic networks in patients with focal epilepsy. We hypothesize that, in the resting state, cortical hyperexcitability increases firing-rate correlations between neuronal populations within seizure onset zones (SOZs). This hypothesis predicts that in the gamma frequency band (40-200 Hz), amplitude envelope correlations (AECs), a relatively straightforward measure of functional connectivity, should be elevated within SOZs compared to other areas. To test this prediction, we analyzed archived samples of interictal electrocorticographic (ECoG) signals recorded from patients who became seizure-free after surgery targeting SOZs identified by multiday intracranial recordings. We show that in the gamma band, AECs between nodes within SOZs are markedly elevated relative to those elsewhere. AEC-based node strength, eigencentrality, and clustering coefficient are also robustly increased within the SOZ with maxima in the low-gamma band (permutation test Z-scores > 8) and yield moderate discriminability of the SOZ using ROC analysis (maximal mean AUC ~ 0.73). By contrast to AECs, phase locking values (PLVs), a measure of narrow-band phase coupling across sites, and PLV-based graph metrics discriminate the seizure onset nodes weakly. Our results suggest that gamma band AECs may provide a clinically useful marker of cortical hyperexcitability in focal epilepsy.
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Affiliation(s)
- Manoj Raghavan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA.
| | - Jared Pilet
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
| | - Chad Carlson
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | | | - Wade Mueller
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Sean Lew
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Candida Ustine
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Priyanka Shah-Basak
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Vahab Youssofzadeh
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Scott A Beardsley
- Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, USA
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Bröhl T, Rings T, Pukropski J, von Wrede R, Lehnertz K. The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 3:1338864. [PMID: 38293249 PMCID: PMC10825060 DOI: 10.3389/fnetp.2023.1338864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024]
Abstract
Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.
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Affiliation(s)
- Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Thorsten Rings
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Jan Pukropski
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
- Interdisciplinary Center for Complex Systems, University of Bonn, Bonn, Germany
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Rao VR, Rolston JD. Unearthing the mechanisms of responsive neurostimulation for epilepsy. COMMUNICATIONS MEDICINE 2023; 3:166. [PMID: 37974025 PMCID: PMC10654422 DOI: 10.1038/s43856-023-00401-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023] Open
Abstract
Responsive neurostimulation (RNS) is an effective therapy for people with drug-resistant focal epilepsy. In clinical trials, RNS therapy results in a meaningful reduction in median seizure frequency, but the response is highly variable across individuals, with many receiving minimal or no benefit. Understanding why this variability occurs will help improve use of RNS therapy. Here we advocate for a reexamination of the assumptions made about how RNS reduces seizures. This is now possible due to large patient cohorts having used this device, some long-term. Two foundational assumptions have been that the device's intracranial leads should target the seizure focus/foci directly, and that stimulation should be triggered only in response to detected epileptiform activity. Recent studies have called into question both hypotheses. Here, we discuss these exciting new studies and suggest future approaches to patient selection, lead placement, and device programming that could improve clinical outcomes.
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Affiliation(s)
- Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - John D Rolston
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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