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Azeem A, Abdallah C, von Ellenrieder N, El Kosseifi C, Frauscher B, Gotman J. Explaining slow seizure propagation with white matter tractography. Brain 2024; 147:3458-3470. [PMID: 38875488 PMCID: PMC11449139 DOI: 10.1093/brain/awae192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 04/11/2024] [Accepted: 05/16/2024] [Indexed: 06/16/2024] Open
Abstract
Epileptic seizures recorded with stereo-EEG can take a fraction of a second or several seconds to propagate from one region to another. What explains such propagation patterns? We combine tractography and stereo-EEG to determine the relationship between seizure propagation and the white matter architecture and to describe seizure propagation mechanisms. Patient-specific spatiotemporal seizure propagation maps were combined with tractography from diffusion imaging of matched subjects from the Human Connectome Project. The onset of seizure activity was marked on a channel-by-channel basis by two board-certified neurologists for all channels involved in the seizure. We measured the tract connectivity (number of tracts) between regions-of-interest pairs among the seizure onset zone, regions of seizure spread and non-involved regions. We also investigated how tract-connected the seizure onset zone is to regions of early seizure spread compared with regions of late spread. Comparisons were made after correcting for differences in distance. Sixty-nine seizures were marked across 26 patients with drug-resistant epilepsy; 11 were seizure free after surgery (Engel IA) and 15 were not (Engel IB-Engel IV). The seizure onset zone was more tract-connected to regions of seizure spread than to non-involved regions (P < 0.0001); however, regions of seizure spread were not differentially tract-connected to other regions of seizure spread compared with non-involved regions. In seizure-free patients only, regions of seizure spread were more tract-connected to the seizure onset zone than to other regions of spread (P < 0.0001). Over the temporal evolution of a seizure, the seizure onset zone was significantly more tract-connected to regions of early spread compared with regions of late spread in seizure-free patients only (P < 0.0001). By integrating information on structure, we demonstrate that seizure propagation is likely to be mediated by white matter tracts. The pattern of connectivity between seizure onset zone, regions of spread and non-involved regions demonstrates that the onset zone might be largely responsible for seizures propagating throughout the brain, rather than seizures propagating to intermediate points, from which further propagation takes place. Our findings also suggest that seizure propagation over seconds might be the result of a continuous bombardment of action potentials from the seizure onset zone to regions of spread. In non-seizure-free patients, the paucity of tracts from the presumed seizure onset zone to regions of spread suggests that the onset zone was missed. Fully understanding the structure-propagation relationship might eventually provide insight into selecting the correct targets for epilepsy surgery.
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Affiliation(s)
- Abdullah Azeem
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, Canada
| | - Chifaou Abdallah
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, Canada
| | - Nicolás von Ellenrieder
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, Canada
| | - Charbel El Kosseifi
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, Canada
| | - Birgit Frauscher
- Department of Neurology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Jean Gotman
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC H3A 2B4, Canada
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Azeem A, von Ellenrieder N, Royer J, Frauscher B, Bernhardt B, Gotman J. Integration of white matter architecture to stereo-EEG better describes epileptic spike propagation. Clin Neurophysiol 2023; 146:135-146. [PMID: 36379837 DOI: 10.1016/j.clinph.2022.10.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 10/12/2022] [Accepted: 10/27/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Stereo-electroencephalography (SEEG)-derived epilepsy networks are used to better understand a patient's epilepsy; however, a unimodal approach provides an incomplete picture. We combine tractography and SEEG to determine the relationship between spike propagation and the white matter architecture and to improve our understanding of spike propagation mechanisms. METHODS Probablistic tractography from diffusion imaging (dMRI) of matched subjects from the Human Connectome Project (HCP) was combined with patient-specific SEEG-derived spike propagation networks. Two regions-of-interest (ROIs) with a significant spike propagation relationship constituted a Propagation Pair. RESULTS In 56 of 59 patients, Propagation Pairs were more often tract-connected as compared to all ROI pairs (p < 0.01; d = -1.91). The degree of spike propagation between tract-connected ROIs was greater (39 ± 21%) compared to tract-unconnected ROIs (31 ± 18%; p < 0.0001). Within the same network, ROIs receiving propagation earlier were more often tract-connected to the source (59.7%) as compared to late receivers (25.4%; p < 0.0001). CONCLUSIONS Brain regions involved in spike propagation are more likely to be connected by white matter tracts. Between nodes, presence of tracts suggests a direct course of propagation, whereas the absence of tracts suggests an indirect course of propagation. SIGNIFICANCE We demonstrate a logical and consistent relationship between spike propagation and the white matter architecture.
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Affiliation(s)
- Abdullah Azeem
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, Canada.
| | - Nicolás von Ellenrieder
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Jessica Royer
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Birgit Frauscher
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, Canada; Department of Neurology & Neurosurgery, Montreal Neurological Hospital, Montréal, QC, Canada
| | - Boris Bernhardt
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Jean Gotman
- Department of Neurology & Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, Canada
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Fujimoto A, Matsumaru Y, Masuda Y, Marushima A, Hosoo H, Araki K, Ishikawa E. Endovascular Electroencephalogram Records Simultaneous Subdural Electrode-Detectable, Scalp Electrode-Undetectable Interictal Epileptiform Discharges. Brain Sci 2022; 12:309. [PMID: 35326265 PMCID: PMC8946704 DOI: 10.3390/brainsci12030309] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/03/2022] Open
Abstract
INTRODUCTION We hypothesized that an endovascular electroencephalogram (eEEG) can detect subdural electrode (SDE)-detectable, scalp EEG-undetectable epileptiform discharges. The purpose of this study is, therefore, to measure SDE-detectable, scalp EEG-undetectable epileptiform discharges by an eEEG on a pig. METHODS A pig under general anesthesia was utilized to measure an artificially generated epileptic field by an eEEG that was able to be detected by an SDE, but not a scalp EEG as a primary outcome. We also compared the phase lag of each epileptiform discharge that was detected by the eEEG and SDE as a secondary outcome. RESULTS The eEEG electrode detected 113 (97%) epileptiform discharges (97% sensitivity). Epileptiform discharges that were localized within the three contacts (contacts two, three and four), but not spread to other parts, were detected by the eEEG with a 92% sensitivity. The latency between peaks of the eEEG and right SDE earliest epileptiform discharge ranged from 0 to 48 ms (mean, 13.3 ms; median, 11 ms; standard deviation, 9.0 ms). CONCLUSION In a pig, an eEEG could detect epileptiform discharges that an SDE could detect, but that a scalp EEG could not.
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Affiliation(s)
- Ayataka Fujimoto
- Comprehensive Epilepsy Center, Seirei Hamamatsu General Hospital, Shizuoka 988-056, Japan;
- School of Rehabilitation Sciences, Seirei Christopher University, Shizuoka 988-056, Japan
| | - Yuji Matsumaru
- Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8575, Japan; (Y.M.); (A.M.); (H.H.); (K.A.); (E.I.)
- E.P. Medical Inc., 403 Nihonbashi-Life-Science Building, 2-3-11, Honcho, Nihonbashi, Chuo-ku, Tokyo 103-0023, Japan
| | - Yosuke Masuda
- Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8575, Japan; (Y.M.); (A.M.); (H.H.); (K.A.); (E.I.)
| | - Aiki Marushima
- Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8575, Japan; (Y.M.); (A.M.); (H.H.); (K.A.); (E.I.)
| | - Hisayuki Hosoo
- Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8575, Japan; (Y.M.); (A.M.); (H.H.); (K.A.); (E.I.)
| | - Kota Araki
- Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8575, Japan; (Y.M.); (A.M.); (H.H.); (K.A.); (E.I.)
| | - Eiichi Ishikawa
- Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8575, Japan; (Y.M.); (A.M.); (H.H.); (K.A.); (E.I.)
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Titov O, Bykanov A, Pitskhelauri D, Danilov G. Neuromonitoring of the language pathways using cortico-cortical evoked potentials: a systematic review and meta-analysis. Neurosurg Rev 2022; 45:1883-1894. [PMID: 35031897 DOI: 10.1007/s10143-021-01718-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 11/18/2021] [Accepted: 12/08/2021] [Indexed: 10/19/2022]
Abstract
Cortico-cortical evoked potentials (CCEPs) are a surge in activity of one cortical zone caused by stimulation of another cortical zone. Recording of CCEP may be a useful method of intraoperative monitoring of the brain pathways, particularly of the language-related tracts. We aimed to conduct a systematic review and meta-analysis, dedicated to the clinical question: Does the CCEP recording effectively predict the postoperative speech deficits in neurosurgical patients? We conducted language-restricted PubMed, Google Scholar, Scopus, and Cochrane database search for eligible studies of CCEP published until March 2021. There were 4 articles (3 case series and 1 case report), which met our inclusion/exclusion criteria. A total of 32 patients (30 cases of tumors and 2 cavernomas) included in the analysis were divided into two cohorts - quantitative and qualitative, in accordance with the method of evaluating changes in the amplitude of CCEP after the lesion resection and postoperative alterations in speech function. Quantitative variables were studied using the Spearman rank correlation coefficient. Categorical variables were compared in groups by Fisher's exact test. We found a strong positive correlation between the decrease in the N1 wave amplitude and the severity of postoperative speech deficits (quantitative cohort: r = 0.57, p = 0.01; qualitative cohort: p = 0.02). Thus, the CCEP method using the N1 wave amplitude as a marker enables to effectively predict postoperative speech outcomes. Nevertheless, the low level of evidence for the included works indicated the necessity for additional research on this issue.
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Affiliation(s)
- Oleg Titov
- Burdenko Neurosurgery Center, Moscow, Russia. .,OPEN BRAIN - Neurosurgical Laboratory of Open Access, Moscow, Russia.
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Yamao Y, Matsumoto R, Kikuchi T, Yoshida K, Kunieda T, Miyamoto S. Intraoperative Brain Mapping by Cortico-Cortical Evoked Potential. Front Hum Neurosci 2021; 15:635453. [PMID: 33679353 PMCID: PMC7930065 DOI: 10.3389/fnhum.2021.635453] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 01/21/2021] [Indexed: 12/04/2022] Open
Abstract
To preserve postoperative brain function, it is important for neurosurgeons to fully understand the brain's structure, vasculature, and function. Intraoperative high-frequency electrical stimulation during awake craniotomy is the gold standard for mapping the function of the cortices and white matter; however, this method can only map the "focal" functions and cannot monitor large-scale cortical networks in real-time. Recently, an in vivo electrophysiological method using cortico-cortical evoked potentials (CCEPs) induced by single-pulse electrical cortical stimulation has been developed in an extraoperative setting. By using the CCEP connectivity pattern intraoperatively, mapping and real-time monitoring of the dorsal language pathway is available. This intraoperative CCEP method also allows for mapping of the frontal aslant tract, another language pathway, and detection of connectivity between the primary and supplementary motor areas in the frontal lobe network. Intraoperative CCEP mapping has also demonstrated connectivity between the frontal and temporal lobes, likely via the ventral language pathway. Establishing intraoperative electrophysiological monitoring is clinically useful for preserving brain function, even under general anesthesia. This CCEP technique demonstrates potential clinical applications for mapping and monitoring large-scale cortical networks.
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Affiliation(s)
- Yukihiro Yamao
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Riki Matsumoto
- Division of Neurology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Takayuki Kikuchi
- Division of Neurology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Ehime University Graduate School of Medicine, Toon, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, Japan
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Kamada K, Kapeller C, Takeuchi F, Gruenwald J, Guger C. Tailor-Made Surgery Based on Functional Networks for Intractable Epilepsy. Front Neurol 2020; 11:73. [PMID: 32117032 PMCID: PMC7031351 DOI: 10.3389/fneur.2020.00073] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 01/21/2020] [Indexed: 12/13/2022] Open
Abstract
Normal and pathological networks related to seizure propagation have got attention to elucide complex seizure semiology and contribute to diagnosis and surgical monitoring in epilepsy treatment. Since focal and generalized epileptogenic syndromes abnormalities might involve multiple foci and large-scale networks, we applied electrophysiolpgy (cortco-cortico evoked potential; CCEP), and tractography to make detailed diagnosis for complex syndrome. All 14 epilepsy patients with no or little abnormality on images investigations underwent subdural grid implantation for epilepsy diagnosis. To perform quick network analysis, we recorded and analyzed high gamma activity (HGA) of epileptogenic activity and CCEPs to identify pathological activity distribution and network connectivity. [Results] Pathological CCEPs showed two negative deflections consisting of early (>40 ms) and late (>150 ms) components in electrically stable circumstance at bed side and early CCEPs appeared in 57% of the patients. On the basis of the CCEP findings, tractography detected anatomical connections. Early components of pathological CCEPs diminished after complete disconnection of tractoography-based fibers between the foci in seven of eight cases. One case with residual pathological CCEPs showed poorer outcome. Thirteen (92.8%) patients with or without CCEPs who underwent network surgery had favorable prognosis except for a case with wide traumatic epilepsy. Intraoperative CCEP measurements and HGA mapping enabled visualization of pathological networks and clinical impotence as a biomarker to improve functional prognosis. HGA/CCEP recording should shed light on pathological and complex propagation for epilepsy surgery.
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Affiliation(s)
- Kyousuke Kamada
- Department of Neurosurgery, Megumino Hospital, Eniwa, Japan.,ATR Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Christoph Kapeller
- g.tec Guger Technologies OG/g.tec Medical Engineering GmbH, Schiedlberg, Austria
| | - Fumiya Takeuchi
- Department of Research Promotion Center, Asahikawa Medical University, Asahikawa, Japan
| | - Johannes Gruenwald
- g.tec Guger Technologies OG/g.tec Medical Engineering GmbH, Schiedlberg, Austria
| | - Christoph Guger
- g.tec Guger Technologies OG/g.tec Medical Engineering GmbH, Schiedlberg, Austria
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Vincent MA, Bonnetblanc F, Mandonnet E, Boyer A, Duffau H, Guiraud D. Measuring the electrophysiological effects of direct electrical stimulation after awake brain surgery. J Neural Eng 2020; 17:016047. [DOI: 10.1088/1741-2552/ab5cdd] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Huggins JE, Guger C, Aarnoutse E, Allison B, Anderson CW, Bedrick S, Besio W, Chavarriaga R, Collinger JL, Do AH, Herff C, Hohmann M, Kinsella M, Lee K, Lotte F, Müller-Putz G, Nijholt A, Pels E, Peters B, Putze F, Rupp R, Schalk G, Scott S, Tangermann M, Tubig P, Zander T. Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation. BRAIN-COMPUTER INTERFACES 2019; 6:71-101. [PMID: 33033729 PMCID: PMC7539697 DOI: 10.1080/2326263x.2019.1697163] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Accepted: 10/30/2019] [Indexed: 12/11/2022]
Abstract
The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics in BCI (also called brain-machine interface) research. Workshops covered foundational topics such as hardware development and signal analysis algorithms, new and imaginative topics such as BCI for virtual reality and multi-brain BCIs, and translational topics such as clinical applications and ethical assumptions of BCI development. BCI research is expanding in the diversity of applications and populations for whom those applications are being developed. BCI applications are moving toward clinical readiness as researchers struggle with the practical considerations to make sure that BCI translational efforts will be successful. This paper summarizes each workshop, providing an overview of the topic of discussion, references for additional information, and identifying future issues for research and development that resulted from the interactions and discussion at the workshop.
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Affiliation(s)
- Jane E Huggins
- Department of Physical Medicine and Rehabilitation, Department of Biomedical Engineering, Neuroscience Graduate Program, University of Michigan, Ann Arbor, Michigan, United States, 325 East Eisenhower, Room 3017; Ann Arbor, Michigan 48108-5744
| | - Christoph Guger
- g.tec medical engineering GmbH/Guger Technologies OG, Austria, Sierningstrasse 14, 4521 Schiedlberg, Austria
| | - Erik Aarnoutse
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Brendan Allison
- Dept. of Cognitive Science, Mail Code 0515, University of California at San Diego, La Jolla, United States
| | - Charles W Anderson
- Department of Computer Science, Molecular, Cellular and Integrative Neurosience Program, Colorado State University, Fort Collins, CO 80523
| | - Steven Bedrick
- Center for Spoken Language Understanding, Oregon Health & Science University, Portland, OR 97239
| | - Walter Besio
- Department of Electrical, Computer, & Biomedical Engineering and Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, Rhode Island, USA, CREmedical Corp. Kingston, Rhode Island, USA
| | - Ricardo Chavarriaga
- Defitech Chair in Brain-Machine Interface (CNBI), Center for Neuroprosthetics, Ecole Polytechnique Fédérale de Lausanne - EPFL, Switzerland
| | - Jennifer L Collinger
- University of Pittsburgh, Department of Physical Medicine and Rehabilitation, VA Pittsburgh Healthcare System, Department of Veterans Affairs, 3520 5th Ave, Pittsburgh, PA, 15213
| | - An H Do
- UC Irvine Brain Computer Interface Lab, Department of Neurology, University of California, Irvine
| | - Christian Herff
- School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Matthias Hohmann
- Max Planck Institute for Intelligent Systems, Department for Empirical Inference, Max-Planck-Ring 4, 72074 Tübingen, Germany
| | - Michelle Kinsella
- Oregon Health & Science University, Institute on Development & Disability, 707 SW Gaines St, #1290, Portland, OR 97239
| | - Kyuhwa Lee
- Swiss Federal Institute of Technology in Lausanne-EPFL
| | - Fabien Lotte
- Inria Bordeaux Sud-Ouest, LaBRI (Univ. Bordeaux/CNRS/Bordeaux INP), 200 avenue de la vieille tour, 33405, Talence Cedex, France
| | | | - Anton Nijholt
- Faculty EEMCS, University of Twente, Enschede, The Netherlands
| | - Elmar Pels
- UMC Utrecht Brain Center, Department of Neurology & Neurosurgery, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The Netherlands
| | - Betts Peters
- Oregon Health & Science University, Institute on Development & Disability, 707 SW Gaines St, #1290, Portland, OR 97239
| | - Felix Putze
- University of Bremen, Germany, Cognitive Systems Lab, University of Bremen, Enrique-Schmidt-Straße 5 (Cartesium), 28359 Bremen
| | - Rüdiger Rupp
- Spinal Cord Injury Center, Heidelberg University Hospital
| | - Gerwin Schalk
- National Center for Adaptive Neurotechnologies, Wadsworth Center, NYS Dept. of Health, Dept. of Neurology, Albany Medical College, Dept. of Biomed. Sci., State Univ. of New York at Albany, Center for Medical Sciences 2003, 150 New Scotland Avenue, Albany, New York 12208
| | - Stephanie Scott
- Department of Media Communications, Colorado State University, Fort Collins, CO 80523
| | - Michael Tangermann
- Brain State Decoding Lab, Cluster of Excellence BrainLinks-BrainTools, Computer Science Dept., University of Freiburg, Germany, Autonomous Intelligent Systems Lab, Computer Science Dept., University of Freiburg, Germany
| | - Paul Tubig
- Department of Philosophy, Center for Neurotechnology, University of Washington, Savery Hall, Room 361, Seattle, WA 98195
| | - Thorsten Zander
- Team PhyPA, Biological Psychology and Neuroergonomics, Technische Universität Berlin, Berlin, Germany, 7 Zander Laboratories B.V., Amsterdam, The Netherlands
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Zhao C, Liang Y, Li C, Gao R, Wei J, Zuo R, Zhong Y, Ren Z, Geng X, Zhang G, Zhang X. Localization of Epileptogenic Zone Based on Cortico-Cortical Evoked Potential (CCEP): A Feature Extraction and Graph Theory Approach. Front Neuroinform 2019; 13:31. [PMID: 31068798 PMCID: PMC6491865 DOI: 10.3389/fninf.2019.00031] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 04/03/2019] [Indexed: 01/01/2023] Open
Abstract
Objective Epilepsy is a chronic brain disease, which is prone to relapse and affects individuals of all ages worldwide, particularly the very young and elderly. Up to one-third of these patients are medically intractable and require resection surgery. However, the outcomes of epilepsy surgery rely upon the clear identification of epileptogenic zone (EZ). The combination of cortico-cortical evoked potential (CCEP) and electrocorticography (ECoG) provides an opportunity to observe the connectivity of human brain network and more comprehensive information that may help the clinicians localize the epileptogenic focus more precisely. However, there is no standard analysis method in the clinical application of CCEPs, especially for the quantitative analysis of abnormal connectivity of epileptic networks. The aim of this paper was to present an approach on the batch processing of CCEPs and provide information relating to the localization of EZ for clinical study. Methods Eight medically intractable epilepsy patients were included in this study. Each patient was implanted with subdural grid electrodes and electrical stimulations were applied directly to their cortex to induce CCEPs. After signal preprocessing, we constructed three effective brain networks at different spatial scales for each patient, regarding the amplitudes of CCEPs as the connection weights. Graph theory was then applied to analyze the brain network topology of epileptic patients, and the topological metrics of EZ and non-EZ (NEZ) were compared. Results The effective connectivity network reconstructed from CCEPs was asymmetric, both the number and the amplitudes of effective CCEPs decreased with increasing distance between stimulating and recording sites. Besides, the distribution of CCEP responses was associated with the locations of EZ which tended to have higher degree centrality (DC) and nodal shortest path length (NLP) than NEZ. Conclusion Our results indicated that the brain networks of epileptics were asymmetric and mainly composed of short-distance connections. The DC and NLP were highly consistent to the distribution of the EZ, and these topological parameters have great potential to be readily applied to the clinical localization of the EZ.
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Affiliation(s)
- Cui Zhao
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Ying Liang
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Chunlin Li
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Runshi Gao
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jing Wei
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Rui Zuo
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Yihua Zhong
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Zhaohui Ren
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Xinling Geng
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
| | - Guojun Zhang
- Department of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xu Zhang
- Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, China.,School of Biomedical Engineering, Capital Medical University, Beijing, China
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A quantitative method for evaluating cortical responses to electrical stimulation. J Neurosci Methods 2018; 311:67-75. [PMID: 30292823 DOI: 10.1016/j.jneumeth.2018.09.034] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 09/05/2018] [Accepted: 09/06/2018] [Indexed: 12/27/2022]
Abstract
BACKGROUND Electrical stimulation of the cortex using subdurally implanted electrodes can causally reveal structural connectivity by eliciting cortico-cortical evoked potentials (CCEPs). While many studies have demonstrated the potential value of CCEPs, the methods to evaluate them were often relatively subjective, did not consider potential artifacts, and did not lend themselves to systematic scientific investigations. NEW METHOD We developed an automated and quantitative method called SIGNI (Stimulation-Induced Gamma-based Network Identification) to evaluate cortical population-level responses to electrical stimulation that minimizes the impact of electrical artifacts. We applied SIGNI to electrocorticographic (ECoG) data from eight human subjects who were implanted with a total of 978 subdural electrodes. Across the eight subjects, we delivered 92 trains of approximately 200 discrete electrical stimuli each (amplitude 4-15 mA) to a total of 64 electrode pairs. RESULTS We verified SIGNI's efficacy by demonstrating a relationship between the magnitude of evoked cortical activity and stimulation amplitude, as well as between the latency of evoked cortical activity and the distance from the stimulated locations. CONCLUSIONS SIGNI reveals the timing and amplitude of cortical responses to electrical stimulation as well as the structural connectivity supporting these responses. With these properties, it enables exploration of new and important questions about the neurophysiology of cortical communication and may also be useful for pre-surgical planning.
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