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Huang Y, Zelmann R, Hadar P, Dezha-Peralta J, Richardson RM, Williams ZM, Cash SS, Keller CJ, Paulk AC. Theta-burst direct electrical stimulation remodels human brain networks. Nat Commun 2024; 15:6982. [PMID: 39143083 PMCID: PMC11324911 DOI: 10.1038/s41467-024-51443-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 08/07/2024] [Indexed: 08/16/2024] Open
Abstract
Theta-burst stimulation (TBS), a patterned brain stimulation technique that mimics rhythmic bursts of 3-8 Hz endogenous brain rhythms, has emerged as a promising therapeutic approach for treating a wide range of brain disorders, though the neural mechanism of TBS action remains poorly understood. We investigated the neural effects of TBS using intracranial EEG (iEEG) in 10 pre-surgical epilepsy participants undergoing intracranial monitoring. Here we show that individual bursts of direct electrical TBS at 29 frontal and temporal sites evoked strong neural responses spanning broad cortical regions. These responses exhibited dynamic local field potential voltage changes over the course of stimulation presentations, including either increasing or decreasing responses, suggestive of short-term plasticity. Stronger stimulation augmented the mean TBS response amplitude and spread with more recording sites demonstrating short-term plasticity. TBS responses were stimulation site-specific with stronger TBS responses observed in regions with strong baseline stimulation effective (cortico-cortical evoked potentials) and functional (low frequency phase locking) connectivity. Further, we could use these measures to predict stable and varying (e.g. short-term plasticity) TBS response locations. Future work may integrate pre-treatment connectivity alongside other biophysical factors to personalize stimulation parameters, thereby optimizing induction of neuroplasticity within disease-relevant brain networks.
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Affiliation(s)
- Yuhao Huang
- Department of Neurosurgery, Stanford University, Palo Alto, CA, USA
| | - Rina Zelmann
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Peter Hadar
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jaquelin Dezha-Peralta
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Ziv M Williams
- Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Sydney S Cash
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Corey J Keller
- Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA, USA.
- Wu Tsai Neurosciences Institute, Stanford University, Palo Alto, CA, USA.
- Veterans Affairs Palo Alto Healthcare System, and the Sierra Pacific Mental Illness, Research, Education, and Clinical Center (MIRECC), Palo Alto, CA, USA.
| | - Angelique C Paulk
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA.
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Schmid W, Danstrom IA, Crespo Echevarria M, Adkinson J, Mattar L, Banks GP, Sheth SA, Watrous AJ, Heilbronner SR, Bijanki KR, Alabastri A, Bartoli E. A biophysically constrained brain connectivity model based on stimulation-evoked potentials. J Neurosci Methods 2024; 405:110106. [PMID: 38453060 PMCID: PMC11233030 DOI: 10.1016/j.jneumeth.2024.110106] [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: 11/03/2023] [Revised: 01/24/2024] [Accepted: 03/04/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. NEW METHOD Using intracranial electrophysiology data recorded from a single patient undergoing stereo-electroencephalography (sEEG) evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D electrical conductivity to infer neural pathways from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. RESULTS The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlated with additional PEP features and displayed stable, weak correlations with tractography measures. COMPARISON WITH EXISTING METHOD Existing methods for estimating neural signal pathways are imaging-based and thus rely on anatomical inferences. CONCLUSIONS These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
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Affiliation(s)
- William Schmid
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA
| | - Isabel A Danstrom
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Maria Crespo Echevarria
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Joshua Adkinson
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Layth Mattar
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Garrett P Banks
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Andrew J Watrous
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Sarah R Heilbronner
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA
| | - Alessandro Alabastri
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston, TX 77005, USA.
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston, TX 77030, USA.
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Sarnthein J, Neidert MC. A profile on the WISE cortical strip for intraoperative neurophysiological monitoring. Expert Rev Med Devices 2024; 21:373-379. [PMID: 38629964 DOI: 10.1080/17434440.2024.2343421] [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: 11/20/2023] [Accepted: 04/11/2024] [Indexed: 05/31/2024]
Abstract
INTRODUCTION During intraoperative neurophysiological monitoring in neurosurgery, brain electrodes are placed to record electrocorticography or to inject current for direct cortical stimulation. A low impedance electrode may improve signal quality. AREAS COVERED We review here a brain electrode (WISE Cortical Strip, WCS®), where a thin polymer strip embeds platinum nanoparticles to create conductive electrode contacts. The low impedance contacts enable a high signal-to-noise ratio, allowing for better detection of small signals such as high-frequency oscillations (HFO). The softness of the WCS may hinder sliding the electrode under the dura or advancing it to deeper structures as the hippocampus but assures conformability with the cortex even in the resection cavity. We provide an extensive review on WCS including a market overview, an introduction to the device (mechanistics, cost aspects, performance standards, safety and contraindications) and an overview of the available pre- and post-approval data. EXPERT OPINION The WCS improves signal detection by lower impedance and better conformability to the cortex. The higher signal-to-noise ratio improves the detection of challenging signals. The softness of the electrode may be a disadvantage in some applications and an advantage in others.
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Affiliation(s)
- Johannes Sarnthein
- Klinik für Neurochirurgie, Universitätsspital Zürich, Universität Zürich, Zurich, Switzerland
- Klinisches Neurozentrum, Universitätsspital Zürich, Zurich, Switzerland
| | - Marian C Neidert
- Klinik für Neurochirurgie, Universitätsspital Zürich, Universität Zürich, Zurich, Switzerland
- Klinik für Neurochirurgie, Kantonsspital St. Gallen, St. Gallen, Switzerland
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Sivaraju A, Quraishi I, Collins E, McGrath H, Ramos A, Turk-Browne NB, Zaveri H, Damisah E, Spencer DD, Hirsch LJ. Systematic 1 Hz direct electrical stimulation for seizure induction: A reliable method for localizing seizure onset zone and predicting seizure freedom. Brain Stimul 2024; 17:339-345. [PMID: 38490472 DOI: 10.1016/j.brs.2024.03.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 02/21/2024] [Accepted: 03/12/2024] [Indexed: 03/17/2024] Open
Abstract
OBJECTIVE To prospectively investigate the utility of seizure induction using systematic 1 Hz stimulation by exploring its concordance with the spontaneous seizure onset zone (SOZ) and relation to surgical outcome; comparison with seizures induced by non-systematic 50 Hz stimulation was attempted as well. METHODS Prospective cohort study from 2018 to 2021 with ≥ 1 y post-surgery follow up at Yale New Haven Hospital. With 1 Hz, all or most of the gray matter contacts were stimulated at 1, 5, and 10 mA for 30-60s. With 50 Hz, selected gray matter contacts outside of the medial temporal regions were stimulated at 1-5 mA for 0.5-3s. Stimulation was bipolar, biphasic with 0.3 ms pulse width. The Yale Brain Atlas was used for data visualization. Variables were analyzed using Fisher's exact, χ2, or Mann-Whitney test. RESULTS Forty-one consecutive patients with refractory epilepsy undergoing intracranial EEG for localization of SOZ were included. Fifty-six percent (23/41) of patients undergoing 1 Hz stimulation had seizures induced, 83% (19/23) habitual (clinically and electrographically). Eighty two percent (23/28) of patients undergoing 50 Hz stimulation had seizures, 65% (15/23) habitual. Stimulation of medial temporal or insular regions with 1 Hz was more likely to induce seizures compared to other regions [15/32 (47%) vs. 2/41 (5%), p < 0.001]. Sixteen patients underwent resection; 11/16 were seizure free at one year and all 11 had habitual seizures induced by 1 Hz; 5/16 were not seizure free at one year and none of those 5 had seizures with 1 Hz (11/11 vs 0/5, p < 0.0001). No patients had convulsions with 1 Hz stimulation, but four did with 50 Hz (0/41 vs. 4/28, p = 0.02). SIGNIFICANCE Induction of habitual seizures with 1 Hz stimulation can reliably identify the SOZ, correlates with excellent surgical outcome if that area is resected, and may be superior (and safer) than 50 Hz for this purpose. However, seizure induction with 1 Hz was infrequent outside of the medial temporal and insular regions in this study.
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Affiliation(s)
- Adithya Sivaraju
- Comprehensive Epilepsy Center, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Imran Quraishi
- Comprehensive Epilepsy Center, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Evan Collins
- Comprehensive Epilepsy Center, Dept. of Neurosurgery, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Hari McGrath
- Comprehensive Epilepsy Center, Dept. of Neurosurgery, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Alexander Ramos
- Comprehensive Epilepsy Center, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA; MidAtlantic Epilepsy and Sleep Center, Dept of Neurology, Bethesda, MD, USA.
| | - Nicholas B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA; Wu Tsai Institute, Yale University, New Haven, CT, USA.
| | - Hitten Zaveri
- Comprehensive Epilepsy Center, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Eyiyemisi Damisah
- Comprehensive Epilepsy Center, Dept. of Neurosurgery, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Dennis D Spencer
- Comprehensive Epilepsy Center, Dept. of Neurosurgery, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
| | - Lawrence J Hirsch
- Comprehensive Epilepsy Center, Dept. of Neurology, School of Medicine, Yale University, Yale-New Haven Hospital, New Haven, CT, USA.
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Kobayashi K, Taylor KN, Shahabi H, Krishnan B, Joshi A, Mackow MJ, Feldman L, Zamzam O, Medani T, Bulacio J, Alexopoulos AV, Najm I, Bingaman W, Leahy RM, Nair DR. Effective connectivity relates seizure outcome to electrode placement in responsive neurostimulation. Brain Commun 2024; 6:fcae035. [PMID: 38390255 PMCID: PMC10882982 DOI: 10.1093/braincomms/fcae035] [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: 09/12/2022] [Revised: 09/06/2023] [Accepted: 02/19/2024] [Indexed: 02/24/2024] Open
Abstract
Responsive neurostimulation is a closed-loop neuromodulation therapy for drug resistant focal epilepsy. Responsive neurostimulation electrodes are placed near ictal onset zones so as to enable detection of epileptiform activity and deliver electrical stimulation. There is no standard approach for determining the optimal placement of responsive neurostimulation electrodes. Clinicians make this determination based on presurgical tests, such as MRI, EEG, magnetoencephalography, ictal single-photon emission computed tomography and intracranial EEG. Currently functional connectivity measures are not being used in determining the placement of responsive neurostimulation electrodes. Cortico-cortical evoked potentials are a measure of effective functional connectivity. Cortico-cortical evoked potentials are generated by direct single-pulse electrical stimulation and can be used to investigate cortico-cortical connections in vivo. We hypothesized that the presence of high amplitude cortico-cortical evoked potentials, recorded during intracranial EEG monitoring, near the eventual responsive neurostimulation contact sites is predictive of better outcomes from its therapy. We retrospectively reviewed 12 patients in whom cortico-cortical evoked potentials were obtained during stereoelectroencephalography evaluation and subsequently underwent responsive neurostimulation therapy. We studied the relationship between cortico-cortical evoked potentials, the eventual responsive neurostimulation electrode locations and seizure reduction. Directional connectivity indicated by cortico-cortical evoked potentials can categorize stereoelectroencephalography electrodes as either receiver nodes/in-degree (an area of greater inward connectivity) or projection nodes/out-degree (greater outward connectivity). The follow-up period for seizure reduction ranged from 1.3-4.8 years (median 2.7) after responsive neurostimulation therapy started. Stereoelectroencephalography electrodes closest to the eventual responsive neurostimulation contact site tended to show larger in-degree cortico-cortical evoked potentials, especially for the early latency cortico-cortical evoked potentials period (10-60 ms period) in six out of 12 patients. Stereoelectroencephalography electrodes closest to the responsive neurostimulation contacts (≤5 mm) also had greater significant out-degree in the early cortico-cortical evoked potentials latency period than those further away (≥10 mm) (P < 0.05). Additionally, significant correlation was noted between in-degree cortico-cortical evoked potentials and greater seizure reduction with responsive neurostimulation therapy at its most effective period (P < 0.05). These findings suggest that functional connectivity determined by cortico-cortical evoked potentials may provide additional information that could help guide the optimal placement of responsive neurostimulation electrodes.
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Affiliation(s)
- Katsuya Kobayashi
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Kenneth N Taylor
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Hossein Shahabi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Balu Krishnan
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Anand Joshi
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Michael J Mackow
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Lauren Feldman
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Omar Zamzam
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Takfarinas Medani
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Juan Bulacio
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | | | - Imad Najm
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - William Bingaman
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
| | - Richard M Leahy
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90007, USA
| | - Dileep R Nair
- Charles Shor Epilepsy Center, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
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Frauscher B, Mansilla D, Abdallah C, Astner-Rohracher A, Beniczky S, Brazdil M, Gnatkovsky V, Jacobs J, Kalamangalam G, Perucca P, Ryvlin P, Schuele S, Tao J, Wang Y, Zijlmans M, McGonigal A. Learn how to interpret and use intracranial EEG findings. Epileptic Disord 2024; 26:1-59. [PMID: 38116690 DOI: 10.1002/epd2.20190] [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: 07/18/2023] [Revised: 10/21/2023] [Accepted: 11/29/2023] [Indexed: 12/21/2023]
Abstract
Epilepsy surgery is the therapy of choice for many patients with drug-resistant focal epilepsy. Recognizing and describing ictal and interictal patterns with intracranial electroencephalography (EEG) recordings is important in order to most efficiently leverage advantages of this technique to accurately delineate the seizure-onset zone before undergoing surgery. In this seminar in epileptology, we address learning objective "1.4.11 Recognize and describe ictal and interictal patterns with intracranial recordings" of the International League against Epilepsy curriculum for epileptologists. We will review principal considerations of the implantation planning, summarize the literature for the most relevant ictal and interictal EEG patterns within and beyond the Berger frequency spectrum, review invasive stimulation for seizure and functional mapping, discuss caveats in the interpretation of intracranial EEG findings, provide an overview on special considerations in children and in subdural grids/strips, and review available quantitative/signal analysis approaches. To be as practically oriented as possible, we will provide a mini atlas of the most frequent EEG patterns, highlight pearls for its not infrequently challenging interpretation, and conclude with two illustrative case examples. This article shall serve as a useful learning resource for trainees in clinical neurophysiology/epileptology by providing a basic understanding on the concepts of invasive intracranial EEG.
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Affiliation(s)
- B Frauscher
- Department of Neurology, Duke University Medical Center and Department of Biomedical Engineering, Duke Pratt School of Engineering, Durham, North Carolina, USA
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Québec, Canada
| | - D Mansilla
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Québec, Canada
- Neurophysiology Unit, Institute of Neurosurgery Dr. Asenjo, Santiago, Chile
| | - C Abdallah
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Québec, Canada
| | - A Astner-Rohracher
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - S Beniczky
- Danish Epilepsy Centre, Dianalund, Denmark
- Aarhus University, Aarhus, Denmark
| | - M Brazdil
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Member of the ERN-EpiCARE, Brno, Czechia
- Behavioral and Social Neuroscience Research Group, Central European Institute of Technology, Masaryk University, Brno, Czechia
| | - V Gnatkovsky
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - J Jacobs
- Department of Paediatrics and Department of Neuroscience, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada
| | - G Kalamangalam
- Department of Neurology, University of Florida, Gainesville, Florida, USA
- Wilder Center for Epilepsy Research, University of Florida, Gainesville, Florida, USA
| | - P Perucca
- Epilepsy Research Centre, Department of Medicine (Austin Health), University of Melbourne, Melbourne, Victoria, Australia
- Bladin-Berkovic Comprehensive Epilepsy Program, Department of Neurology, Austin Health, Melbourne, Victoria, Australia
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
- Department of Neurology, Royal Melbourne Hospital, Melbourne, Victoria, Australia
| | - P Ryvlin
- Department of Clinical Neurosciences, CHUV, Lausanne University Hospital, Lausanne, Switzerland
| | - S Schuele
- Department of Neurology, Feinberg School of Medicine, Northwestern Memorial Hospital, Chicago, Illinois, USA
| | - J Tao
- Department of Neurology, The University of Chicago, Chicago, Illinois, USA
| | - Y Wang
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
- Wilder Center for Epilepsy Research, University of Florida, Gainesville, Florida, USA
| | - M Zijlmans
- Department of Neurology and Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, the Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
| | - A McGonigal
- Department of Neurosciences, Mater Misericordiae Hospital, Brisbane, Queensland, Australia
- Mater Research Institute, Faculty of Medicine, University of Queensland, St Lucia, Queensland, Australia
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Feys O, Wens V, Rovai A, Schuind S, Rikir E, Legros B, De Tiège X, Gaspard N. Delayed effective connectivity characterizes the epileptogenic zone during stereo-EEG. Clin Neurophysiol 2024; 158:59-68. [PMID: 38183887 DOI: 10.1016/j.clinph.2023.12.013] [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: 09/25/2023] [Revised: 11/11/2023] [Accepted: 12/19/2023] [Indexed: 01/08/2024]
Abstract
OBJECTIVE Single-pulse electrical stimulations (SPES) can elicit normal and abnormal responses that might characterize the epileptogenic zone, including spikes, high-frequency oscillations and cortico-cortical evoked potentials (CCEPs). In this study, we investigate their association with the epileptogenic zone during stereoelectroencephalography (SEEG) in 28 patients with refractory focal epilepsy. METHODS Characteristics of CCEPs (distance-corrected or -uncorrected latency, amplitude and the connectivity index) and the occurrence of spikes and ripples were assessed. Responses within the epileptogenic zone and within the non-involved zone were compared using receiver operating characteristics curves and analysis of variance (ANOVA) either in all patients, patients with well-delineated epileptogenic zone, and patients older than 15 years old. RESULTS We found an increase in distance-corrected CCEPs latency after stimulation within the epileptogenic zone (area under the curve = 0.71, 0.72, 0.70, ANOVA significant after false discovery rate correction). CONCLUSIONS The increased distance-corrected CCEPs latency suggests that neuronal propagation velocity is altered within the epileptogenic network. This association might reflect effective connectivity changes at cortico-cortical or cortico-subcortico-cortical levels. Other responses were not associated with the epileptogenic zone, including the CCEPs amplitude, the connectivity index, the occurrences of induced ripples and spikes. The discrepancy with previous descriptions may be explained by different spatial brain sampling between subdural and depth electrodes. SIGNIFICANCE Increased distance-corrected CCEPs latency, indicating delayed effective connectivity, characterizes the epileptogenic zone. This marker could be used to help tailor surgical resection limits after SEEG.
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Affiliation(s)
- Odile Feys
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Neurology, Bruxelles, Belgium; Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN(2)T), Bruxelles, Belgium.
| | - Vincent Wens
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN(2)T), Bruxelles, Belgium; Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Translational Neuroimaging, Bruxelles, Belgium
| | - Antonin Rovai
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN(2)T), Bruxelles, Belgium; Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Translational Neuroimaging, Bruxelles, Belgium
| | - Sophie Schuind
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Neurosurgery, Bruxelles, Belgium
| | - Estelle Rikir
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Neurology, Bruxelles, Belgium
| | - Benjamin Legros
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Neurology, Bruxelles, Belgium
| | - Xavier De Tiège
- Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratoire de Neuroanatomie et Neuroimagerie translationnelles (LN(2)T), Bruxelles, Belgium; Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Translational Neuroimaging, Bruxelles, Belgium
| | - Nicolas Gaspard
- Université libre de Bruxelles (ULB), Hôpital Universitaire de Bruxelles (HUB) - Hôpital Erasme, Department of Neurology, Bruxelles, Belgium; Université Libre de Bruxelles (ULB), ULB Neuroscience Institute (UNI), Laboratory of Experimental Neurology, Bruxelles, Belgium; Yale University, Department of Neurology, New Haven, CT, USA
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8
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Doss DJ, Johnson GW, Englot DJ. Imaging and Stereotactic Electroencephalography Functional Networks to Guide Epilepsy Surgery. Neurosurg Clin N Am 2024; 35:61-72. [PMID: 38000842 PMCID: PMC10676462 DOI: 10.1016/j.nec.2023.09.001] [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] [Indexed: 11/26/2023]
Abstract
Epilepsy surgery is a potentially curative treatment of drug-resistant epilepsy that has remained underutilized both due to inadequate referrals and incomplete localization hypotheses. The complexity of patients evaluated for epilepsy surgery has increased, thus new approaches are necessary to treat these patients. The paradigm of epilepsy surgery has evolved to match this challenge, now considering the entire seizure network with the goal of disrupting it through resection, ablation, neuromodulation, or a combination. The network paradigm has the potential to aid in identification of the seizure network as well as treatment selection.
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Affiliation(s)
- Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA
| | - Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, PMB 351631, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Vanderbilt University Institute of Imaging Science (VUIIS), 1161 21st Avenue South, Medical Center North AA-1105, Nashville, TN 37232, USA; Vanderbilt Institute for Surgery and Engineering (VISE), 1161 21st Avenue South, MCN S2323, Nashville, TN 37232, USA; Department of Neurological Surgery, Vanderbilt University Medical Center, 1161 21st Avenue South, T4224 Medical Center North, Nashville, TN 37232, USA; Department of Electrical and Computer Engineering, Vanderbilt University, PMB 351824, 2301 Vanderbilt Place, Nashville, TN 37235, USA; Department of Radiological Sciences, Vanderbilt University Medical Center, 1161 21st Avenue South, Nashville, TN 37232, USA.
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9
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Nozari E, Bertolero MA, Stiso J, Caciagli L, Cornblath EJ, He X, Mahadevan AS, Pappas GJ, Bassett DS. Macroscopic resting-state brain dynamics are best described by linear models. Nat Biomed Eng 2024; 8:68-84. [PMID: 38082179 PMCID: PMC11357987 DOI: 10.1038/s41551-023-01117-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 09/26/2023] [Indexed: 12/22/2023]
Abstract
It is typically assumed that large networks of neurons exhibit a large repertoire of nonlinear behaviours. Here we challenge this assumption by leveraging mathematical models derived from measurements of local field potentials via intracranial electroencephalography and of whole-brain blood-oxygen-level-dependent brain activity via functional magnetic resonance imaging. We used state-of-the-art linear and nonlinear families of models to describe spontaneous resting-state activity of 700 participants in the Human Connectome Project and 122 participants in the Restoring Active Memory project. We found that linear autoregressive models provide the best fit across both data types and three performance metrics: predictive power, computational complexity and the extent of the residual dynamics unexplained by the model. To explain this observation, we show that microscopic nonlinear dynamics can be counteracted or masked by four factors associated with macroscopic dynamics: averaging over space and over time, which are inherent to aggregated macroscopic brain activity, and observation noise and limited data samples, which stem from technological limitations. We therefore argue that easier-to-interpret linear models can faithfully describe macroscopic brain dynamics during resting-state conditions.
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Affiliation(s)
- Erfan Nozari
- Department of Mechanical Engineering, University of California, Riverside, CA, USA
- Department of Electrical and Computer Engineering, University of California, Riverside, CA, USA
- Department of Bioengineering, University of California, Riverside, CA, USA
| | - Maxwell A Bertolero
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Jennifer Stiso
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Lorenzo Caciagli
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Eli J Cornblath
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neuroscience, University of Pennsylvania, Philadelphia, PA, USA
| | - Xiaosong He
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Arun S Mahadevan
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA
| | - George J Pappas
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA
| | - Dani S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Santa Fe Institute, Santa Fe, NM, USA.
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10
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Frauscher B, Bartolomei F, Baud MO, Smith RJ, Worrell G, Lundstrom BN. Stimulation to probe, excite, and inhibit the epileptic brain. Epilepsia 2023; 64 Suppl 3:S49-S61. [PMID: 37194746 PMCID: PMC10654261 DOI: 10.1111/epi.17640] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/01/2023] [Accepted: 05/02/2023] [Indexed: 05/18/2023]
Abstract
Direct cortical stimulation has been applied in epilepsy for nearly a century and has experienced a renaissance, given unprecedented opportunities to probe, excite, and inhibit the human brain. Evidence suggests stimulation can increase diagnostic and therapeutic utility in patients with drug-resistant epilepsies. However, choosing appropriate stimulation parameters is not a trivial issue, and is further complicated by epilepsy being characterized by complex brain state dynamics. In this article derived from discussions at the ICTALS 2022 Conference (International Conference on Technology and Analysis for Seizures), we succinctly review the literature on cortical stimulation applied acutely and chronically to the epileptic brain for localization, monitoring, and therapeutic purposes. In particular, we discuss how stimulation is used to probe brain excitability, discuss evidence on the usefulness of stimulation to trigger and stop seizures, review therapeutic applications of stimulation, and finally discuss how stimulation parameters are impacted by brain dynamics. Although research has advanced considerably over the past decade, there are still significant hurdles to optimizing use of this technique. For example, it remains unclear to what extent short timescale diagnostic biomarkers can predict long-term outcomes and to what extent these biomarkers add information to already existing biomarkers from passive electroencephalographic recordings. Further questions include the extent to which closed loop stimulation offers advantages over open loop stimulation, what the optimal closed loop timescales may be, and whether biomarker-informed stimulation can lead to seizure freedom. The ultimate goal of bioelectronic medicine remains not just to stop seizures but rather to cure epilepsy and its comorbidities.
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Affiliation(s)
- Birgit Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, Montreal, Quebec, Canada
| | - Fabrice Bartolomei
- Institut de Neurosciences des Systèmes, Aix Marseille University, Marseille, France. AP-HM, Service de Neurophysiologie Clinique, Hôpital de la Timone, Marseille, France
| | - Maxime O. Baud
- Sleep-Wake-Epilepsy Center, NeuroTec and Center for Experimental Neurology, Department of Neurology, Inselspital Bern, University Hospital, University of Bern, Bern
| | - Rachel J. Smith
- University of Alabama at Birmingham, Electrical and Computer Engineering Department, Birmingham, Alabama, US. University of Alabama at Birmingham, Neuroengineering Program, Birmingham, Alabama, US
| | - Greg Worrell
- Department of Neurology, Mayo Clinic, Rochester, US
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11
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Schmid W, Danstrom IA, Echevarria MC, Adkinson J, Mattar L, Banks GP, Sheth SA, Watrous AJ, Heilbronner SR, Bijanki KR, Alabastri A, Bartoli E. A biophysically constrained brain connectivity model based on stimulation-evoked potentials. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.03.565525. [PMID: 37986830 PMCID: PMC10659345 DOI: 10.1101/2023.11.03.565525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Background Single-pulse electrical stimulation (SPES) is an established technique used to map functional effective connectivity networks in treatment-refractory epilepsy patients undergoing intracranial-electroencephalography monitoring. While the connectivity path between stimulation and recording sites has been explored through the integration of structural connectivity, there are substantial gaps, such that new modeling approaches may advance our understanding of connectivity derived from SPES studies. New Method Using intracranial electrophysiology data recorded from a single patient undergoing sEEG evaluation, we employ an automated detection method to identify early response components, C1, from pulse-evoked potentials (PEPs) induced by SPES. C1 components were utilized for a novel topology optimization method, modeling 3D conductivity propagation from stimulation sites. Additionally, PEP features were compared with tractography metrics, and model results were analyzed with respect to anatomical features. Results The proposed optimization model resolved conductivity paths with low error. Specific electrode contacts displaying high error correlated with anatomical complexities. The C1 component strongly correlates with additional PEP features and displayed stable, weak correlations with tractography measures. Comparison with existing methods Existing methods for estimating conductivity propagation are imaging-based and thus rely on anatomical inferences. Conclusions These results demonstrate that informing topology optimization methods with human intracranial SPES data is a feasible method for generating 3D conductivity maps linking electrical pathways with functional neural ensembles. PEP-estimated effective connectivity is correlated with but distinguished from structural connectivity. Modeled conductivity resolves connectivity pathways in the absence of anatomical priors.
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Affiliation(s)
- William Schmid
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston 77005, Texas, USA
| | - Isabel A. Danstrom
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Maria Crespo Echevarria
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Joshua Adkinson
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Layth Mattar
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Garrett P. Banks
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Andrew J. Watrous
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Sarah R. Heilbronner
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Kelly R. Bijanki
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
| | - Alessandro Alabastri
- Department of Electrical and Computer Engineering, Rice University, 6100 Main Street, Houston 77005, Texas, USA
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, 1 Baylor Plaza, Houston 77030, Texas, USA
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12
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Ojeda Valencia G, Gregg NM, Huang H, Lundstrom BN, Brinkmann BH, Pal Attia T, Van Gompel JJ, Bernstein MA, In MH, Huston J, Worrell GA, Miller KJ, Hermes D. Signatures of Electrical Stimulation Driven Network Interactions in the Human Limbic System. J Neurosci 2023; 43:6697-6711. [PMID: 37620159 PMCID: PMC10538586 DOI: 10.1523/jneurosci.2201-22.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 08/04/2023] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Stimulation-evoked signals are starting to be used as biomarkers to indicate the state and health of brain networks. The human limbic network, often targeted for brain stimulation therapy, is involved in emotion and memory processing. Previous anatomic, neurophysiological, and functional studies suggest distinct subsystems within the limbic network (Rolls, 2015). Studies using intracranial electrical stimulation, however, have emphasized the similarities of the evoked waveforms across the limbic network. We test whether these subsystems have distinct stimulation-driven signatures. In eight patients (four male, four female) with drug-resistant epilepsy, we stimulated the limbic system with single-pulse electrical stimulation. Reliable corticocortical evoked potentials (CCEPs) were measured between hippocampus and the posterior cingulate cortex (PCC) and between the amygdala and the anterior cingulate cortex (ACC). However, the CCEP waveform in the PCC after hippocampal stimulation showed a unique and reliable morphology, which we term the "limbic Hippocampus-Anterior nucleus of the thalamus-Posterior cingulate, HAP-wave." This limbic HAP-wave was visually distinct and separately decoded from the CCEP waveform in ACC after amygdala stimulation. Diffusion MRI data show that the measured end points in the PCC overlap with the end points of the parolfactory cingulum bundle rather than the parahippocampal cingulum, suggesting that the limbic HAP-wave may travel through fornix, mammillary bodies, and the anterior nucleus of the thalamus (ANT). This was further confirmed by stimulating the ANT, which evoked the same limbic HAP-wave but with an earlier latency. Limbic subsystems have unique stimulation-evoked signatures that may be used in the future to help network pathology diagnosis.SIGNIFICANCE STATEMENT The limbic system is often compromised in diverse clinical conditions, such as epilepsy or Alzheimer's disease, and characterizing its typical circuit responses may provide diagnostic insight. Stimulation-evoked waveforms have been used in the motor system to diagnose circuit pathology. We translate this framework to limbic subsystems using human intracranial stereo EEG (sEEG) recordings that measure deeper brain areas. Our sEEG recordings describe a stimulation-evoked waveform characteristic to the memory and spatial subsystem of the limbic network that we term the "limbic HAP-wave." The limbic HAP-wave follows anatomic white matter pathways from hippocampus to thalamus to the posterior cingulum and shows promise as a distinct biomarker of signaling in the human brain memory and spatial limbic network.
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Affiliation(s)
- Gabriela Ojeda Valencia
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Nicholas M Gregg
- Department of Neurology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Harvey Huang
- Mayo Clinic Medical Scientist Training Program, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Brian N Lundstrom
- Department of Neurology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | | | - Tal Pal Attia
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Jamie J Van Gompel
- Department of Neurologic Surgery, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Matt A Bernstein
- Department of Radiology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Myung-Ho In
- Department of Radiology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - John Huston
- Department of Radiology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Gregory A Worrell
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
- Department of Neurology, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Kai J Miller
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
- Department of Neurologic Surgery, Mayo Clinic Rochester, Rochester, Minnesota 55902
| | - Dora Hermes
- Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, Minnesota 55902
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13
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Cockle E, Rayner G, Malpas C, Alpitsis R, Rheims S, O'Brien TJ, Neal A. An international survey of SEEG cortical stimulation practices. Epilepsia Open 2023; 8:1084-1095. [PMID: 37437189 PMCID: PMC10472359 DOI: 10.1002/epi4.12790] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 07/02/2023] [Indexed: 07/14/2023] Open
Abstract
OBJECTIVE Cortical stimulation is an important component of stereoelectroencephalography (SEEG). Despite this, there is currently no standardized approach and significant heterogeneity in the literature regarding cortical stimulation practices. Via an international survey of SEEG clinicians, we sought to examine the spectrum of cortical stimulation practices to reveal areas of consensus and variability. METHODS A 68-item questionnaire was developed to understand cortical stimulation practices including neurostimulation parameters, interpretation of epileptogenicity, functional and cognitive assessment and subsequent surgical decisions. Multiple recruitment pathways were pursued, with the questionnaire distributed directly to 183 clinicians. RESULTS Responses were received from 56 clinicians across 17 countries with experience ranging from 2 to 60 years (M = 10.73, SD = 9.44). Neurostimulation parameters varied considerably, with maximum current ranging from 3 to 10 mA (M = 5.33, SD = 2.29) for 1 Hz and from 2 to 15 mA (M = 6.54, SD = 3.68) for 50 Hz stimulation. Charge density ranged from 8 to 200 μC/cm2 , with up to 43% of responders utilizing charge densities higher than recommended upper safety limits, i.e. 55 μC/cm2 . North American responders reported statistically significant higher maximum current (P < 0.001) for 1 Hz stimulation and lower pulse width for 1 and 50 Hz stimulation (P = 0.008, P < 0.001, respectively) compared to European responders. All clinicians evaluated language, speech, and motor function during cortical stimulation; in contrast, 42% assessed visuospatial or visual function, 29% memory, and 13% executive function. Striking differences were reported in approaches to assessment, classification of positive sites, and surgical decisions guided by cortical stimulation. Patterns of consistency were observed for interpretation of the localizing capacity of stimulated electroclinical seizures and auras, with habitual electroclinical seizures induced by 1 Hz stimulation considered the most localizing. SIGNIFICANCE SEEG cortical stimulation practices differed vastly across clinicians internationally, highlighting the need for consensus-based clinical guidelines. In particular, an internationally standardized approach to assessment, classification, and functional prognostication will provide a common clinical and research framework for optimizing outcomes for people with drug-resistant epilepsy.
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Affiliation(s)
- Emily Cockle
- Department of NeurologyAlfred HospitalMelbourneVictoriaAustralia
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
| | - Genevieve Rayner
- Department of NeurologyAlfred HospitalMelbourneVictoriaAustralia
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
- Melbourne School of Psychological SciencesUniversity of MelbourneParkvilleVictoriaAustralia
| | - Charles Malpas
- Department of NeurologyAlfred HospitalMelbourneVictoriaAustralia
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
- Melbourne School of Psychological SciencesUniversity of MelbourneParkvilleVictoriaAustralia
- Department of Medicine, Royal Melbourne HospitalUniversity of MelbourneParkvilleVictoriaAustralia
| | - Rubina Alpitsis
- Department of NeurologyAlfred HospitalMelbourneVictoriaAustralia
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
| | - Sylvain Rheims
- Lyon Neurosciences Research Center (Inserm U1028, CNRS UMR5292, Lyon 1 University)LyonFrance
- Department of Functional Neurology and EpileptologyHospices Civils de Lyon and Lyon 1 UniversityLyonFrance
- Epilepsy Institute and member of the ERN EpiCARELyonFrance
| | - Terence J O'Brien
- Department of NeurologyAlfred HospitalMelbourneVictoriaAustralia
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
| | - Andrew Neal
- Department of NeurologyAlfred HospitalMelbourneVictoriaAustralia
- Department of NeuroscienceMonash UniversityMelbourneVictoriaAustralia
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14
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Boerger TF, Pahapill P, Butts AM, Arocho-Quinones E, Raghavan M, Krucoff MO. Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities. Front Hum Neurosci 2023; 17:1170419. [PMID: 37520929 PMCID: PMC10372448 DOI: 10.3389/fnhum.2023.1170419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/16/2023] [Indexed: 08/01/2023] Open
Abstract
In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses.
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Affiliation(s)
- Timothy F. Boerger
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Peter Pahapill
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Alissa M. Butts
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
- Mayo Clinic, Rochester, MN, United States
| | - Elsa Arocho-Quinones
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Manoj Raghavan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Max O. Krucoff
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, United States
- Department of Biomedical Engineering, Medical College of Wisconsin, Marquette University, Milwaukee, WI, United States
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15
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Johnson GW, Doss DJ, Morgan VL, Paulo DL, Cai LY, Shless JS, Negi AS, Gummadavelli A, Kang H, Reddy SB, Naftel RP, Bick SK, Williams Roberson S, Dawant BM, Wallace MT, Englot DJ. The Interictal Suppression Hypothesis in focal epilepsy: network-level supporting evidence. Brain 2023; 146:2828-2845. [PMID: 36722219 PMCID: PMC10316780 DOI: 10.1093/brain/awad016] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 12/24/2022] [Accepted: 01/08/2023] [Indexed: 02/02/2023] Open
Abstract
Why are people with focal epilepsy not continuously having seizures? Previous neuronal signalling work has implicated gamma-aminobutyric acid balance as integral to seizure generation and termination, but is a high-level distributed brain network involved in suppressing seizures? Recent intracranial electrographic evidence has suggested that seizure-onset zones have increased inward connectivity that could be associated with interictal suppression of seizure activity. Accordingly, we hypothesize that seizure-onset zones are actively suppressed by the rest of the brain network during interictal states. Full testing of this hypothesis would require collaboration across multiple domains of neuroscience. We focused on partially testing this hypothesis at the electrographic network level within 81 individuals with drug-resistant focal epilepsy undergoing presurgical evaluation. We used intracranial electrographic resting-state and neurostimulation recordings to evaluate the network connectivity of seizure onset, early propagation and non-involved zones. We then used diffusion imaging to acquire estimates of white-matter connectivity to evaluate structure-function coupling effects on connectivity findings. Finally, we generated a resting-state classification model to assist clinicians in detecting seizure-onset and propagation zones without the need for multiple ictal recordings. Our findings indicate that seizure onset and early propagation zones demonstrate markedly increased inwards connectivity and decreased outwards connectivity using both resting-state (one-way ANOVA, P-value = 3.13 × 10-13) and neurostimulation analyses to evaluate evoked responses (one-way ANOVA, P-value = 2.5 × 10-3). When controlling for the distance between regions, the difference between inwards and outwards connectivity remained stable up to 80 mm between brain connections (two-way repeated measures ANOVA, group effect P-value of 2.6 × 10-12). Structure-function coupling analyses revealed that seizure-onset zones exhibit abnormally enhanced coupling (hypercoupling) of surrounding regions compared to presumably healthy tissue (two-way repeated measures ANOVA, interaction effect P-value of 9.76 × 10-21). Using these observations, our support vector classification models achieved a maximum held-out testing set accuracy of 92.0 ± 2.2% to classify early propagation and seizure-onset zones. These results suggest that seizure-onset zones are actively segregated and suppressed by a widespread brain network. Furthermore, this electrographically observed functional suppression is disproportionate to any observed structural connectivity alterations of the seizure-onset zones. These findings have implications for the identification of seizure-onset zones using only brief electrographic recordings to reduce patient morbidity and augment the presurgical evaluation of drug-resistant epilepsy. Further testing of the interictal suppression hypothesis can provide insight into potential new resective, ablative and neuromodulation approaches to improve surgical success rates in those suffering from drug-resistant focal epilepsy.
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Affiliation(s)
- Graham W Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Derek J Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Danika L Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Leon Y Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
| | - Jared S Shless
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Aarushi S Negi
- Department of Neuroscience, Vanderbilt University, Nashville, TN 37232, USA
| | - Abhijeet Gummadavelli
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Hakmook Kang
- Department of Biostatistics, Vanderbilt University, Nashville, TN 37232, USA
| | - Shilpa B Reddy
- Department of Pediatrics, Vanderbilt Children’s Hospital, Nashville, TN 37232, USA
| | - Robert P Naftel
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Sarah K Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | | | - Benoit M Dawant
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
| | - Mark T Wallace
- Department of Hearing and Speech Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychology, Vanderbilt University, Nashville, TN 37232, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - Dario J Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37235, USA
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Institute for Surgery and Engineering (VISE), Vanderbilt University, Nashville, TN 37235, USA
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, TN 37235, USA
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16
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Bernabei JM, Li A, Revell AY, Smith RJ, Gunnarsdottir KM, Ong IZ, Davis KA, Sinha N, Sarma S, Litt B. Quantitative approaches to guide epilepsy surgery from intracranial EEG. Brain 2023; 146:2248-2258. [PMID: 36623936 PMCID: PMC10232272 DOI: 10.1093/brain/awad007] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 12/11/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023] Open
Abstract
Over the past 10 years, the drive to improve outcomes from epilepsy surgery has stimulated widespread interest in methods to quantitatively guide epilepsy surgery from intracranial EEG (iEEG). Many patients fail to achieve seizure freedom, in part due to the challenges in subjective iEEG interpretation. To address this clinical need, quantitative iEEG analytics have been developed using a variety of approaches, spanning studies of seizures, interictal periods, and their transitions, and encompass a range of techniques including electrographic signal analysis, dynamical systems modeling, machine learning and graph theory. Unfortunately, many methods fail to generalize to new data and are sensitive to differences in pathology and electrode placement. Here, we critically review selected literature on computational methods of identifying the epileptogenic zone from iEEG. We highlight shared methodological challenges common to many studies in this field and propose ways that they can be addressed. One fundamental common pitfall is a lack of open-source, high-quality data, which we specifically address by sharing a centralized high-quality, well-annotated, multicentre dataset consisting of >100 patients to support larger and more rigorous studies. Ultimately, we provide a road map to help these tools reach clinical trials and hope to improve the lives of future patients.
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Affiliation(s)
- John M Bernabei
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Li
- Department of Computer Science, Columbia University, New York, NY 10027, USA
| | - Andrew Y Revell
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Neuroengineering Program, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Kristin M Gunnarsdottir
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Ian Z Ong
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kathryn A Davis
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nishant Sinha
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sridevi Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Brian Litt
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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17
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Hays MA, Kamali G, Koubeissi MZ, Sarma SV, Crone NE, Smith RJ, Kang JY. Towards optimizing single pulse electrical stimulation: High current intensity, short pulse width stimulation most effectively elicits evoked potentials. Brain Stimul 2023; 16:772-782. [PMID: 37141936 PMCID: PMC10330807 DOI: 10.1016/j.brs.2023.04.023] [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: 02/04/2023] [Revised: 04/21/2023] [Accepted: 04/26/2023] [Indexed: 05/06/2023] Open
Abstract
BACKGROUND While single pulse electrical stimulation (SPES) is increasingly used to study effective connectivity, the effects of varying stimulation parameters on the resulting cortico-cortical evoked potentials (CCEPs) have not been systematically explored. OBJECTIVE We sought to understand the interacting effects of stimulation pulse width, current intensity, and charge on CCEPs through an extensive testing of this parameter space and analysis of several response metrics. METHODS We conducted SPES in 11 patients undergoing intracranial EEG monitoring using five combinations of current intensity (1.5, 2.0, 3.0, 5.0, and 7.5 mA) and pulse width at each of three charges (0.750, 1.125, and 1.500 μC/phase) to study how CCEP amplitude, distribution, latency, morphology, and stimulus artifact amplitude vary with each parameter. RESULTS Stimulations with a greater charge or a greater current intensity and shorter pulse width at a given charge generally resulted in greater CCEP amplitudes and spatial distributions, shorter latencies, and increased waveform correlation. These effects interacted such that stimulations with the lowest charge and highest current intensities resulted in greater response amplitudes and spatial distributions than stimulations with the highest charge and lowest current intensities. Stimulus artifact amplitude increased with charge, but this could be mitigated by using shorter pulse widths. CONCLUSIONS Our results indicate that individual combinations of current intensity and pulse width, in addition to charge, are important determinants of CCEP magnitude, morphology, and spatial extent. Together, these findings suggest that high current intensity, short pulse width stimulations are optimal SPES settings for eliciting strong and consistent responses while minimizing charge.
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Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
| | - Golnoosh Kamali
- Johns Hopkins Technology Ventures, Johns Hopkins University, Baltimore, MD, USA
| | | | - Sridevi V Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL, USA; Department of Neuroengineering, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University, Baltimore, MD, USA
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18
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Shindhelm AC, Thio BJ, Sinha SR. Modeling the Impact of Electrode/Tissue Geometry on Electrical Stimulation in Stereo-EEG. J Clin Neurophysiol 2023; 40:339-349. [PMID: 34482315 DOI: 10.1097/wnp.0000000000000892] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
PURPOSE Electrical stimulation through depth electrodes is used to map function and seizure onset during stereoelectroencephalography in patients undergoing evaluation for epilepsy surgery. Factors such as electrode design, location, and orientation are expected to impact effects of electrical stimulation. METHODS We developed a steady-state finite element model of brain tissue including five layers (skull through white matter) and an implanted electrode to explore the impact of electrode design and placement on the activation of brain tissue by electrical stimulation. We calculated electric potentials, current densities, and volume of tissue activated ( Volact ) in response to constant current bipolar stimulation. We modeled two depth electrode designs (3.5- and 4.43-mm intercontact spacing) and varied electrode location and orientation. RESULTS The electrode with greater intercontact spacing produced 8% to 23% larger Volact (1% to 16% considering only gray matter). Vertical displacement of the electrodes by half intercontact space increased Volact for upward displacement (6% to 83% for all brain tissue or -5% to 96% gray matter only) and decreased Volact (1% to 16% or 24% to 49% gray matter only) for downward displacement. Rotating the electrode in the tissue by 30° to 60° with respect to the vertical axis increased Volact by 30% to 90% (20%-48% gray matter only). CONCLUSIONS Location and orientation of depth electrodes with respect to surrounding brain tissue have a large impact on the amount of tissue activated during electrical stimulation mapping in stereoelectroencephalography. Electrode design has an impact, although modest for commonly used designs. Individualization of stimulation intensity at each location remains critical, especially for avoiding false-negative results.
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Affiliation(s)
- Alexis C Shindhelm
- Department of Neurology, Duke University Medical Center, Durham, North Carolina; and
| | - Brandon J Thio
- Department of Biomedical Engineering, Duke University, Durham, North Carolina
| | - Saurabh R Sinha
- Department of Neurology, Duke University Medical Center, Durham, North Carolina; and
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19
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Cornblath EJ, Lucas A, Armstrong C, Greenblatt AS, Stein JM, Hadar PN, Raghupathi R, Marsh E, Litt B, Davis KA, Conrad EC. Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue. Epilepsia 2023; 64:1021-1034. [PMID: 36728906 PMCID: PMC10480141 DOI: 10.1111/epi.17528] [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: 09/18/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. METHODS We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. RESULTS We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SIGNIFICANCE These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.
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Affiliation(s)
- Eli J. Cornblath
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alfredo Lucas
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, Pennsylvania, USA
| | - Caren Armstrong
- Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Adam S. Greenblatt
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Joel M. Stein
- Department of Radiology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Peter N. Hadar
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramya Raghupathi
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Eric Marsh
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Brian Litt
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Kathryn A. Davis
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Erin C. Conrad
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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20
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Johnson GW, Cai LY, Doss DJ, Jiang JW, Negi AS, Narasimhan S, Paulo DL, González HFJ, Roberson SW, Bick SK, Chang CE, Morgan VL, Wallace MT, Englot DJ. Localizing seizure onset zones in surgical epilepsy with neurostimulation deep learning. J Neurosurg 2023; 138:1002-1007. [PMID: 36152321 PMCID: PMC10619627 DOI: 10.3171/2022.8.jns221321] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/04/2022] [Indexed: 12/24/2022]
Abstract
OBJECTIVE In drug-resistant temporal lobe epilepsy, automated tools for seizure onset zone (SOZ) localization that use brief interictal recordings could supplement presurgical evaluations and improve care. Thus, the authors sought to localize SOZs by training a multichannel convolutional neural network on stereoelectroencephalography (SEEG) cortico-cortical evoked potentials. METHODS The authors performed single-pulse electrical stimulation in 10 drug-resistant temporal lobe epilepsy patients implanted with SEEG. Using 500,000 unique poststimulation SEEG epochs, the authors trained a multichannel 1-dimensional convolutional neural network to determine whether an SOZ had been stimulated. RESULTS SOZs were classified with mean sensitivity of 78.1% and specificity of 74.6% according to leave-one-patient-out testing. To achieve maximum accuracy, the model required a 0- to 350-msec poststimulation time period. Post hoc analysis revealed that the model accurately classified unilateral versus bilateral mesial temporal lobe seizure onset, as well as neocortical SOZs. CONCLUSIONS This was the first demonstration, to the authors' knowledge, that a deep learning framework can be used to accurately classify SOZs with single-pulse electrical stimulation-evoked responses. These findings suggest that accurate classification of SOZs relies on a complex temporal evolution of evoked responses within 350 msec of stimulation. Validation in a larger data set could provide a practical clinical tool for the presurgical evaluation of drug-resistant epilepsy.
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Affiliation(s)
- Graham W. Johnson
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Leon Y. Cai
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Derek J. Doss
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Jasmine W. Jiang
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Aarushi S. Negi
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Saramati Narasimhan
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Danika L. Paulo
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Hernán F. J. González
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
| | - Shawniqua Williams Roberson
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sarah K. Bick
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Catie E. Chang
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville
| | - Victoria L. Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mark T. Wallace
- Department of Hearing & Speech Sciences, Vanderbilt University, Nashville
- Department of Psychology, Vanderbilt University, Nashville
- Departments of Psychiatry and Behavioral Sciences, Vanderbilt University, Nashville
- Department of Pharmacology, Vanderbilt University, Nashville
| | - Dario J. Englot
- Department of Biomedical Engineering, Vanderbilt University, Nashville
- Department of Electrical and Computer Engineering, Vanderbilt University, Nashville
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville
- Vanderbilt Institute for Surgery and Engineering, Vanderbilt University, Nashville
- Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee
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21
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Campbell JM, Davis TS, Anderson DN, Arain A, Inman CS, Smith EH, Rolston JD. Subsets of cortico-cortical evoked potentials propagate as traveling waves. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.27.534002. [PMID: 37034691 PMCID: PMC10081214 DOI: 10.1101/2023.03.27.534002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Emerging evidence suggests that the temporal dynamics of cortico-cortical evoked potentials (CCEPs) may be used to characterize the patterns of information flow between and within brain networks. At present, however, the spatiotemporal dynamics of CCEP propagation cortically and subcortically are incompletely understood. We hypothesized that CCEPs propagate as an evoked traveling wave emanating from the site of stimulation. To elicit CCEPs, we applied single-pulse stimulation to stereoelectroencephalography (SEEG) electrodes implanted in 21 adult patients with intractable epilepsy. For each robust CCEP, we measured the timing of the maximal descent in evoked local field potentials and broadband high-gamma power (70-150 Hz) envelopes relative to the distance between the recording and stimulation contacts using three different metrics (i.e., Euclidean distance, path length, geodesic distance), representing direct, subcortical, and transcortical propagation, respectively. Many evoked responses to single-pulse electrical stimulation appear to propagate as traveling waves (~17-30%), even in the sparsely sampled, three-dimensional SEEG space. These results provide new insights into the spatiotemporal dynamics of CCEP propagation.
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Affiliation(s)
- Justin M. Campbell
- MD-PhD Program, School of Medicine, University of Utah, Salt Lake City, UT, USA
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Tyler S. Davis
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Daria Nesterovich Anderson
- School of Biomedical Engineering, Faculty of Engineering, University of Sydney, Sydney, New South Wales, Australia
| | - Amir Arain
- Department of Neurology, University of Utah, Salt Lake City, UT, USA
| | - Cory S. Inman
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Psychology, University of Utah, Salt Lake City, UT, USA
| | - Elliot H. Smith
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - John D. Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
- Department of Neurosurgery, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA, USA
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Togo M, Matsumoto R, Usami K, Kobayashi K, Takeyama H, Nakae T, Shimotake A, Kikuchi T, Yoshida K, Matsuhashi M, Kunieda T, Miyamoto S, Takahashi R, Ikeda A. Distinct connectivity patterns in human medial parietal cortices: Evidence from standardized connectivity map using cortico-cortical evoked potential. Neuroimage 2022; 263:119639. [PMID: 36155245 DOI: 10.1016/j.neuroimage.2022.119639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 09/10/2022] [Accepted: 09/19/2022] [Indexed: 11/21/2022] Open
Abstract
The medial parietal cortices are components of the default mode network (DMN), which are active in the resting state. The medial parietal cortices include the precuneus and the dorsal posterior cingulate cortex (dPCC). Few studies have mentioned differences in the connectivity in the medial parietal cortices, and these differences have not yet been precisely elucidated. Electrophysiological connectivity is essential for understanding cortical function or functional differences. Since little is known about electrophysiological connections from the medial parietal cortices in humans, we evaluated distinct connectivity patterns in the medial parietal cortices by constructing a standardized connectivity map using cortico-cortical evoked potential (CCEP). This study included nine patients with partial epilepsy or a brain tumor who underwent chronic intracranial electrode placement covering the medial parietal cortices. Single-pulse electrical stimuli were delivered to the medial parietal cortices (38 pairs of electrodes). Responses were standardized using the z-score of the baseline activity, and a response density map was constructed in the Montreal Neurological Institutes (MNI) space. The precuneus tended to connect with the inferior parietal lobule (IPL), the occipital cortex, superior parietal lobule (SPL), and the dorsal premotor area (PMd) (the four most active regions, in descending order), while the dPCC tended to connect to the middle cingulate cortex, SPL, precuneus, and IPL. The connectivity pattern differs significantly between the precuneus and dPCC stimulation (p<0.05). Regarding each part of the medial parietal cortices, the distributions of parts of CCEP responses resembled those of the functional connectivity database. Based on how the dPCC was connected to the medial frontal area, SPL, and IPL, its connectivity pattern could not be explained by DMN alone, but suggested a mixture of DMN and the frontoparietal cognitive network. These findings improve our understanding of the connectivity profile within the medial parietal cortices. The electrophysiological connectivity is the basis of propagation of electrical activities in patients with epilepsy. In addition, it helps us to better understand the epileptic network arising from the medial parietal cortices.
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Affiliation(s)
- Masaya Togo
- Department of Neurology, Kyoto University Graduate School of Medicine, Japan; Division of Neurology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan
| | - Riki Matsumoto
- Department of Neurology, Kyoto University Graduate School of Medicine, Japan; Division of Neurology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, 650-0017, Japan.
| | - Kiyohide Usami
- Department of Neurology, Kyoto University Graduate School of Medicine, Japan
| | - Katsuya Kobayashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Japan
| | - Hirofumi Takeyama
- Department of Respiratory Care and Sleep Control Medicine, Kyoto University Graduate School of Medicine, Japan; Department of Neurology, Japanese Red Cross Otsu Hospital, Japan
| | - Takuro Nakae
- Department of Neurosurgery, Shiga General Hospital, Japan
| | - Akihiro Shimotake
- Department of Neurology, Kyoto University Graduate School of Medicine, Japan
| | - Takayuki Kikuchi
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Japan
| | - Masao Matsuhashi
- Departments of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
| | - Takeharu Kunieda
- Department of Neurosurgery, Ehime University Graduate School of Medicine, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Japan
| | - Akio Ikeda
- Departments of Epilepsy, Movement Disorders and Physiology, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Sakyo-ku, Kyoto, 606-8507, Japan
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23
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Samanta D. Recent developments in stereo electroencephalography monitoring for epilepsy surgery. Epilepsy Behav 2022; 135:108914. [PMID: 36116362 DOI: 10.1016/j.yebeh.2022.108914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 11/03/2022]
Abstract
Recently the utilization of the stereo electroencephalography (SEEG) method has exploded globally. It is now the preferred method of intracranial monitoring for epilepsy. Since its inception, the basic tenet of the SEEG method remains the same: strategic implantation of intracerebral electrodes based on a hypothesis grounded on anatomo-electroclinical correlation, interpretation of interictal and ictal abnormalities, and formation of a surgical plan based on these data. However, there are recent advancements in all these domains-electrodes implantations, data interpretation, and therapeutic strategy- that can make the SEEG a more accessible and effective approach. In this narrative review, these newer developments are discussed and summarized. Regarding implantation, efficient commercial robotic systems are now increasingly available, which are also more accurate in implanting electrodes. In terms of ictal and interictal abnormalities, newer studies focused on correlating these abnormalities with pathological substrates and surgical outcomes and analyzing high-frequency oscillations and cortical-subcortical connectivity. These abnormalities can now be further quantified using advanced tools (spectrum, spatiotemporal, connectivity analysis, and machine learning algorithms) for objective and efficient interpretation. Another aspect of recent development is renewed interest in SEEG-based electrical stimulation mapping (ESM). The SEEG-ESM has been used in defining epileptogenic networks, mapping eloquent cortex (primarily language), and analyzing cortico-cortical evoked potential. Regarding SEEG-guided direct therapeutic strategy, several clinical studies evaluated the use of radiofrequency thermocoagulation. As the emerging SEEG-based diagnosis and therapeutics are better evolved, treatments aimed at specific epileptogenic networks without compromising the eloquent cortex will become more easily accessible to improve the lives of individuals with drug-resistant epilepsy (DRE).
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Affiliation(s)
- Debopam Samanta
- Neurology Division, Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States.
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Dickey AS, Alwaki A, Kheder A, Willie JT, Drane DL, Pedersen NP. The Referential Montage Inadequately Localizes Corticocortical Evoked Potentials in Stereoelectroencephalography. J Clin Neurophysiol 2022; 39:412-418. [PMID: 33337663 PMCID: PMC10069706 DOI: 10.1097/wnp.0000000000000792] [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] [Indexed: 11/26/2022] Open
Abstract
PURPOSE Corticocortical evoked potentials (CCEPs) resulting from single pulse electrical stimulation are increasingly used to understand seizure networks, as well as normal brain connectivity. However, we observed that when using depth electrodes, traditional measures of CCEPs amplitude using a referential montage can be falsely localizing, often to white matter. METHODS We pooled 27 linear electrode arrays targeting the amygdala, hippocampus, or cingulate cortex from eight participants. Using postoperative imaging, we classified contacts as being in gray matter, white matter, or bordering each and measured the amplitude using the root-mean-squared deviation from baseline in a referential, common average, bipolar, or Laplacian montage. RESULTS Of 27 electrode contacts, 25 (93%) had a significantly higher mean amplitude when in gray matter than in white matter using a Laplacian montage, which was significantly more than the 12 of 27 electrodes (44%) when using a referential montage ( P = 0.0003, Fisher exact test). The area under the curve for a receiver operating characteristic classifying contacts as gray or white matter was significantly higher for either the Laplacian (0.79) or the bipolar (0.72) montage when compared with either the common average (0.56) or the referential (0.51) montage ( P ≤ 0.005, bootstrap). CONCLUSIONS Both the Laplacian and bipolar montages were superior to the common average or referential montage in localizing CCEPs to gray matter. These montages may be more appropriate for interpreting CCEPs when using depth electrodes than the referential montage, which has typically been used in prior studies of CCEPs with subdural grids.
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Affiliation(s)
- Adam S. Dickey
- Department of Neurology, Emory University and Emory Epilepsy Center, 101 Woodruff Circle, Atlanta, GA 30322, USA
| | - Abdulrahman Alwaki
- Department of Neurology, Emory University and Emory Epilepsy Center, 101 Woodruff Circle, Atlanta, GA 30322, USA
| | - Ammar Kheder
- Department of Neurology, Emory University and Emory Epilepsy Center, 101 Woodruff Circle, Atlanta, GA 30322, USA
- Children’s Pediatric Institute, Emory University and Children’s Healthcare of Atlanta
| | - Jon T. Willie
- Department of Neurology, Emory University and Emory Epilepsy Center, 101 Woodruff Circle, Atlanta, GA 30322, USA
- Department of Neurosurgery, Emory University, 101 Woodruff Circle, Atlanta, GA 30322, USA
- Emory Neuromodulation Technology Innovation Center, Emory University and Georgia Institute of Technology, 101 Woodruff Circle, Atlanta, GA 30322, USA
| | - Daniel L. Drane
- Department of Neurology, Emory University and Emory Epilepsy Center, 101 Woodruff Circle, Atlanta, GA 30322, USA
| | - Nigel P. Pedersen
- Department of Neurology, Emory University and Emory Epilepsy Center, 101 Woodruff Circle, Atlanta, GA 30322, USA
- Emory Neuromodulation Technology Innovation Center, Emory University and Georgia Institute of Technology, 101 Woodruff Circle, Atlanta, GA 30322, USA
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Lemaréchal JD, Jedynak M, Trebaul L, Boyer A, Tadel F, Bhattacharjee M, Deman P, Tuyisenge V, Ayoubian L, Hugues E, Chanteloup-Forêt B, Saubat C, Zouglech R, Reyes Mejia GC, Tourbier S, Hagmann P, Adam C, Barba C, Bartolomei F, Blauwblomme T, Curot J, Dubeau F, Francione S, Garcés M, Hirsch E, Landré E, Liu S, Maillard L, Metsähonkala EL, Mindruta I, Nica A, Pail M, Petrescu AM, Rheims S, Rocamora R, Schulze-Bonhage A, Szurhaj W, Taussig D, Valentin A, Wang H, Kahane P, George N, David O. A brain atlas of axonal and synaptic delays based on modelling of cortico-cortical evoked potentials. Brain 2021; 145:1653-1667. [PMID: 35416942 PMCID: PMC9166555 DOI: 10.1093/brain/awab362] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 08/03/2021] [Accepted: 08/14/2021] [Indexed: 11/16/2022] Open
Abstract
Epilepsy presurgical investigation may include focal intracortical single-pulse electrical stimulations with depth electrodes, which induce cortico-cortical evoked potentials at distant sites because of white matter connectivity. Cortico-cortical evoked potentials provide a unique window on functional brain networks because they contain sufficient information to infer dynamical properties of large-scale brain connectivity, such as preferred directionality and propagation latencies. Here, we developed a biologically informed modelling approach to estimate the neural physiological parameters of brain functional networks from the cortico-cortical evoked potentials recorded in a large multicentric database. Specifically, we considered each cortico-cortical evoked potential as the output of a transient stimulus entering the stimulated region, which directly propagated to the recording region. Both regions were modelled as coupled neural mass models, the parameters of which were estimated from the first cortico-cortical evoked potential component, occurring before 80 ms, using dynamic causal modelling and Bayesian model inversion. This methodology was applied to the data of 780 patients with epilepsy from the F-TRACT database, providing a total of 34 354 bipolar stimulations and 774 445 cortico-cortical evoked potentials. The cortical mapping of the local excitatory and inhibitory synaptic time constants and of the axonal conduction delays between cortical regions was obtained at the population level using anatomy-based averaging procedures, based on the Lausanne2008 and the HCP-MMP1 parcellation schemes, containing 130 and 360 parcels, respectively. To rule out brain maturation effects, a separate analysis was performed for older (>15 years) and younger patients (<15 years). In the group of older subjects, we found that the cortico-cortical axonal conduction delays between parcels were globally short (median = 10.2 ms) and only 16% were larger than 20 ms. This was associated to a median velocity of 3.9 m/s. Although a general lengthening of these delays with the distance between the stimulating and recording contacts was observed across the cortex, some regions were less affected by this rule, such as the insula for which almost all efferent and afferent connections were faster than 10 ms. Synaptic time constants were found to be shorter in the sensorimotor, medial occipital and latero-temporal regions, than in other cortical areas. Finally, we found that axonal conduction delays were significantly larger in the group of subjects younger than 15 years, which corroborates that brain maturation increases the speed of brain dynamics. To our knowledge, this study is the first to provide a local estimation of axonal conduction delays and synaptic time constants across the whole human cortex in vivo, based on intracerebral electrophysiological recordings.
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Affiliation(s)
- Jean-Didier Lemaréchal
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, Centre MEG-EEG and Experimental Neurosurgery Team, F-75013 Paris, France.,Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.,Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Maciej Jedynak
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Lena Trebaul
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Anthony Boyer
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - François Tadel
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Manik Bhattacharjee
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Pierre Deman
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Viateur Tuyisenge
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Leila Ayoubian
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Etienne Hugues
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | | | - Carole Saubat
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | - Raouf Zouglech
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France
| | | | - Sébastien Tourbier
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Patric Hagmann
- Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Claude Adam
- Department of Neurology, Epilepsy Unit, AP-HP, Hôpital de la Pitié Salpêtrière, F-75013 Paris, France
| | - Carmen Barba
- Neuroscience Department, Children's Hospital Meyer-University of Florence, Florence, Italy
| | - Fabrice Bartolomei
- Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France.,Service de Neurophysiologie Clinique, APHM, Hôpitaux de la Timone, Marseille, France
| | - Thomas Blauwblomme
- Department of Pediatric Neurosurgery, Hôpital Necker-Enfants Malades, Université Paris V Descartes, Sorbonne Paris Cité, Paris, France
| | - Jonathan Curot
- Department of Neurophysiological Explorations, CerCo, CNRS, UMR5549, Centre Hospitalier Universitaire de Toulouse and University of Toulouse, Toulouse, France
| | - François Dubeau
- Montreal Neurological Institute and Hospital, Montreal, Canada
| | - Stefano Francione
- 'Claudio Munari' Centre for Epilepsy Surgery; Neuroscience Department, GOM, Niguarda, Milano, Italy
| | - Mercedes Garcés
- Multidisciplinary Epilepsy Unit, Hospital Universitario y Politécnico La Fe, Valencia, Spain
| | - Edouard Hirsch
- University Hospital, Department of Neurology, Strasbourg, France
| | | | - Sinclair Liu
- Canton Sanjiu Brain Hospital Epilepsy Center, Jinan University, Guangzhou, China
| | - Louis Maillard
- Centre Hospitalier Universitaire de Nancy, Nancy, France
| | | | - Ioana Mindruta
- Neurology Department, University Emergency Hospital, Bucharest, Romania
| | - Anca Nica
- Neurology Department, CIC 1414, Rennes University Hospital; LTSI, INSERM U 1099, F-35000 Rennes, France
| | - Martin Pail
- Brno Epilepsy Center, Department of Neurology, St. Anne's University Hospital and Medical Faculty of Masaryk University, Brno, Czech Republic
| | | | - Sylvain Rheims
- Department of Functional Neurology and Epileptology, Hospices Civils de Lyon and Lyon's Neurosciences Research Center, INSERM U1028/CNRS UMR5292/Lyon 1 University, Lyon, France
| | - Rodrigo Rocamora
- Epilepsy Monitoring Unit, Department of Neurology, Hospital del Mar-IMIM, Barcelona, Spain
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - William Szurhaj
- Epilepsy Unit, Department of Clinical Neurophysiology, Lille University Medical Center, Lille, France
| | - Delphine Taussig
- Neurophysiology and Epilepsy Unit, Bicêtre Hospital, France.,Service de Neurochirurgie Pédiatrique, Fondation Rothschild, Paris, France
| | - Antonio Valentin
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), London, UK
| | - Haixiang Wang
- Yuquan Hospital Epilepsy Center, Tsinghua University, Beijing, China
| | - Philippe Kahane
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.,Neurology Department, CHU Grenoble Alpes, Grenoble, France
| | - Nathalie George
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, Centre MEG-EEG and Experimental Neurosurgery Team, F-75013 Paris, France
| | - Olivier David
- Université Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France.,Aix Marseille Université, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
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26
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Rachidi I, Minotti L, Martin G, Hoffmann D, Bastin J, David O, Kahane P. The Insula: A Stimulating Island of the Brain. Brain Sci 2021; 11:1533. [PMID: 34827532 PMCID: PMC8615692 DOI: 10.3390/brainsci11111533] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 11/07/2021] [Accepted: 11/12/2021] [Indexed: 11/16/2022] Open
Abstract
Direct cortical stimulation (DCS) in epilepsy surgery patients has a long history of functional brain mapping and seizure triggering. Here, we review its findings when applied to the insula in order to map the insular functions, evaluate its local and distant connections, and trigger seizures. Clinical responses to insular DCS are frequent and diverse, showing a partial segregation with spatial overlap, including a posterior somatosensory, auditory, and vestibular part, a central olfactory-gustatory region, and an anterior visceral and cognitive-emotional portion. The study of cortico-cortical evoked potentials (CCEPs) has shown that the anterior (resp. posterior) insula has a higher connectivity rate with itself than with the posterior (resp. anterior) insula, and that both the anterior and posterior insula are closely connected, notably between the homologous insular subdivisions. All insular gyri show extensive and complex ipsilateral and contralateral extra-insular connections, more anteriorly for the anterior insula and more posteriorly for the posterior insula. As a rule, CCEPs propagate first and with a higher probability around the insular DCS site, then to the homologous region, and later to more distal regions with fast cortico-cortical axonal conduction delays. Seizures elicited by insular DCS have rarely been specifically studied, but their rate does not seem to differ from those of other DCS studies. They are mainly provoked from the insular seizure onset zone but can also be triggered by stimulating intra- and extra-insular early propagation zones. Overall, in line with the neuroimaging studies, insular DCS studies converge on the view that the insula is a multimodal functional hub with a fast propagation of information, whose organization helps understand where insular seizures start and how they propagate.
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Affiliation(s)
- Inès Rachidi
- CHU Grenoble Alpes, 38000 Grenoble, France; (L.M.); (G.M.); (D.H.); (P.K.)
| | - Lorella Minotti
- CHU Grenoble Alpes, 38000 Grenoble, France; (L.M.); (G.M.); (D.H.); (P.K.)
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; (J.B.); (O.D.)
| | - Guillaume Martin
- CHU Grenoble Alpes, 38000 Grenoble, France; (L.M.); (G.M.); (D.H.); (P.K.)
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; (J.B.); (O.D.)
| | - Dominique Hoffmann
- CHU Grenoble Alpes, 38000 Grenoble, France; (L.M.); (G.M.); (D.H.); (P.K.)
| | - Julien Bastin
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; (J.B.); (O.D.)
| | - Olivier David
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; (J.B.); (O.D.)
| | - Philippe Kahane
- CHU Grenoble Alpes, 38000 Grenoble, France; (L.M.); (G.M.); (D.H.); (P.K.)
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut Neurosciences, 38000 Grenoble, France; (J.B.); (O.D.)
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27
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Hays MA, Smith RJ, Haridas B, Coogan C, Crone NE, Kang JY. Effects of stimulation intensity on intracranial cortico-cortical evoked potentials: A titration study. Clin Neurophysiol 2021; 132:2766-2777. [PMID: 34583119 DOI: 10.1016/j.clinph.2021.08.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/26/2021] [Accepted: 08/04/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE The aim of the present study was to investigate the optimal stimulation parameters for eliciting cortico-cortical evoked potentials (CCEPs) for mapping functional and epileptogenic networks. METHODS We studied 13 patients with refractory epilepsy undergoing intracranial EEG monitoring. We systematically titrated the intensity of single-pulse electrical stimulation at multiple sites to assess the effect of increasing current on salient features of CCEPs such as N1 potential magnitude, signal to noise ratio, waveform similarity, and spatial distribution of responses. Responses at each incremental stimulation setting were compared to each other and to a final set of responses at the maximum intensity used in each patient (3.5-10 mA, median 6 mA). RESULTS We found that with a biphasic 0.15 ms/phase pulse at least 2-4 mA is needed to differentiate between non-responsive and responsive sites, and that stimulation currents of 6-7 mA are needed to maximize amplitude and spatial distribution of N1 responses and stabilize waveform morphology. CONCLUSIONS We determined a minimum stimulation threshold necessary for eliciting CCEPs, as well as a point at which the current-dependent relationship of several response metrics all saturate. SIGNIFICANCE This titration study provides practical, immediate guidance on optimal stimulation parameters to study specific features of CCEPs, which have been increasingly used to map both functional and epileptic brain networks in humans.
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Affiliation(s)
- Mark A Hays
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Rachel J Smith
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Babitha Haridas
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Christopher Coogan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nathan E Crone
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joon Y Kang
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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28
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Manzouri F, Meisel C, Kunz L, Dümpelmann M, Stieglitz T, Schulze-Bonhage A. Low-frequency electrical stimulation reduces cortical excitability in the human brain. Neuroimage Clin 2021; 31:102778. [PMID: 34375883 PMCID: PMC8358685 DOI: 10.1016/j.nicl.2021.102778] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 07/02/2021] [Accepted: 07/25/2021] [Indexed: 12/03/2022]
Abstract
Effective seizure control remains challenging for about 30% of epilepsy patients who are resistant to present-day pharmacotherapy. Novel approaches that not only reduce the severity and frequency of seizures, but also have limited side effects are therefore desirable. Accordingly, various neuromodulation approaches such as cortical electrical stimulation have been implemented to reduce seizure burden; however, the underlying mechanisms are not completely understood. Given that the initiation and spread of epileptic seizures critically depend on cortical excitability, understanding the neuromodulatory effects of cortical electrical stimulation on cortical excitability levels is paramount. Based on observations that synchronization in the electrocorticogram closely tracks brain excitability level, the effects of low-frequency (1 Hz) intracranial brain stimulation on the levels of cortical phase synchronization before, during, and after 1 Hz electrical stimulation were assessed in twelve patients. Analysis of phase synchronization levels across three broad frequency bands (1-45 Hz, 55-95 Hz, and 105-195 Hz) revealed that in patients with stimulation sites in the neocortex, phase synchronization levels were significantly reduced within the 55-95 Hz and 105-195 Hz bands during post-stimulation intervals compared to baseline; this effect persisted for at least 30 min post-stimulation. Similar effects were observed when phase synchronization levels were examined in the classic frequency bands, whereby a significant reduction was found during the post-stimulation intervals in the alpha, beta, and gamma bands. The anatomical extent of these effects was then assessed. Analysis of the results from six patients with intracranial electrodes in both hemispheres indicated that reductions in phase synchronization in the 1-45 Hz and 55-95 Hz frequency ranges were more prominent in the stimulated hemisphere. Overall, these findings demonstrate that low-frequency electrical stimulation reduces phase synchronization and hence cortical excitability in the human brain. Low-frequency stimulation of the epileptic focus may therefore contribute to the prevention of impending epileptic seizures.
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Affiliation(s)
- Farrokh Manzouri
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany; BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany.
| | - Christian Meisel
- Department of Neurology, Charité- Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health, Berlin, Germany; Center for Stroke Research Berlin, Berlin, Germany
| | - Lukas Kunz
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany; Faculty of Biology, University of Freiburg, Freiburg, Germany; Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Matthias Dümpelmann
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - Thomas Stieglitz
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany; BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany
| | - Andreas Schulze-Bonhage
- Epilepsy Center, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; BrainLinks-BrainTools, University of Freiburg, Freiburg, Germany; Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Freiburg, Germany; Center for Basics in NeuroModulation, Faculty of Medicine, University of Freiburg, Freiburg, Germany
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29
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Khapov IV, Melikyan AG. [Stereoelectroencephalography (seeg): a brief historical review of modern deep electrode implantation methods used for diagnosis and treatment of epilepsy]. ZHURNAL VOPROSY NEĬROKHIRURGII IMENI N. N. BURDENKO 2021; 85:99-106. [PMID: 33864674 DOI: 10.17116/neiro20218502199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
More than 30% of patients with symptomatic epilepsy are resistant to drug therapy and therefore surgical treatment is the method of choice for such patients. Search and localization of the epileptogenic zone and all parts of the neural networks involved in stereotypic seizures are the most important objectives of pre-surgical evaluation and the prerequisite for the successful surgery. In the last decade, stereotactic implantation of multiple intracerebral multi-contact electrodes (SEEG) has been increasingly used for this purpose. The article includes a brief history of SEEG and a description of the major techniques for stereotactic implantation of electrodes. Information on accuracy (errors and deviations from planned target) and on complications are summarized. The data on the clinical value of the method and how these data affected the results of subsequent treatment are highlighted. The method of thermocoagulation and its results are briefly considered.
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Affiliation(s)
- I V Khapov
- Burdenko Neurosurgical Center, Moscow, Russia
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30
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Levinson LH, Caldwell DJ, Cronin JA, Houston B, Perlmutter SI, Weaver KE, Herron JA, Ojemann JG, Ko AL. Intraoperative Characterization of Subthalamic Nucleus-to-Cortex Evoked Potentials in Parkinson's Disease Deep Brain Stimulation. Front Hum Neurosci 2021; 15:590251. [PMID: 33776665 PMCID: PMC7990794 DOI: 10.3389/fnhum.2021.590251] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Accepted: 02/18/2021] [Indexed: 11/13/2022] Open
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a clinically effective tool for treating medically refractory Parkinson's disease (PD), but its neural mechanisms remain debated. Previous work has demonstrated that STN DBS results in evoked potentials (EPs) in the primary motor cortex (M1), suggesting that modulation of cortical physiology may be involved in its therapeutic effects. Due to technical challenges presented by high-amplitude DBS artifacts, these EPs are often measured in response to low-frequency stimulation, which is generally ineffective at PD symptom management. This study aims to characterize STN-to-cortex EPs seen during clinically relevant high-frequency STN DBS for PD. Intraoperatively, we applied STN DBS to 6 PD patients while recording electrocorticography (ECoG) from an electrode strip over the ipsilateral central sulcus. Using recently published techniques, we removed large stimulation artifacts to enable quantification of STN-to-cortex EPs. Two cortical EPs were observed - one synchronized with DBS onset and persisting during ongoing stimulation, and one immediately following DBS offset, here termed the "start" and the "end" EPs respectively. The start EP is, to our knowledge, the first long-latency cortical EP reported during ongoing high-frequency DBS. The start and end EPs differ in magnitude (p < 0.05) and latency (p < 0.001), and the end, but not the start, EP magnitude has a significant relationship (p < 0.001, adjusted for random effects of subject) to ongoing high gamma (80-150 Hz) power during the EP. These contrasts may suggest mechanistic or circuit differences in EP production during the two time periods. This represents a potential framework for relating DBS clinical efficacy to the effects of a variety of stimulation parameters on EPs.
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Affiliation(s)
- Lila H Levinson
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States
| | - David J Caldwell
- Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Bioengineering, University of Washington, Seattle, WA, United States
| | - Jeneva A Cronin
- Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Bioengineering, University of Washington, Seattle, WA, United States
| | - Brady Houston
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States
| | - Steve I Perlmutter
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Physiology and Biophysics, University of Washington, Seattle, WA, United States
| | - Kurt E Weaver
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Radiology, University of Washington, Seattle, WA, United States
| | - Jeffrey A Herron
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Neurological Surgery, University of Washington, Seattle, WA, United States
| | - Jeffrey G Ojemann
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Neurological Surgery, University of Washington, Seattle, WA, United States
| | - Andrew L Ko
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, United States.,Center for Neurotechnology, University of Washington, Seattle, WA, United States.,Department of Neurological Surgery, University of Washington, Seattle, WA, United States
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31
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Gronlier E, Vendramini E, Volle J, Wozniak-Kwasniewska A, Antón Santos N, Coizet V, Duveau V, David O. Single-pulse electrical stimulation methodology in freely moving rat. J Neurosci Methods 2021; 353:109092. [PMID: 33549638 DOI: 10.1016/j.jneumeth.2021.109092] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2020] [Revised: 01/15/2021] [Accepted: 02/01/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Cortico-cortical evoked potentials (CCEP) are becoming popular to infer brain connectivity and cortical excitability in implanted refractory epilepsy patients. Our goal was to transfer this methodology to the freely moving rodent. NEW METHOD CCEP were recorded on freely moving Sprague-Dawley rats, from cortical and subcortical areas using depth electrodes. Electrical stimulation was applied using 1 ms biphasic current pulse, cathodic first, at a frequency of 0.5 Hz, with intensities ranging from 0.2 to 0.8 mA. Data were then processed in a similar fashion to human clinical studies, which included epoch selection, artefact correction and smart averaging. RESULTS For a large range of tested intensities, we recorded CCEPs with very good signal to noise ratio and reproducibility between animals, without any behavioral modification. The CCEP were composed of different components according to recorded and stimulated sites, similarly to human recordings. COMPARISON WITH EXISTING METHODS We minimally adapted a clinically-motivated methodology to a freely moving rodent model to achieve high translational relevance of future preclinical studies. CONCLUSIONS Our results indicate that the CCEP methodology can be applied to freely moving rodents and transferred to preclinical research. This will be of interest to address various neuroscientific questions, in physiological and pathological conditions.
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Affiliation(s)
- Eloïse Gronlier
- SynapCell SAS, Saint-Ismier, France; Univ. Grenoble Alpes, Inserm, GIN, Grenoble Institut des Neurosciences, Grenoble, France.
| | - Estelle Vendramini
- Univ. Grenoble Alpes, Inserm, GIN, Grenoble Institut des Neurosciences, Grenoble, France
| | | | | | - Noelia Antón Santos
- Univ. Grenoble Alpes, Inserm, GIN, Grenoble Institut des Neurosciences, Grenoble, France
| | - Véronique Coizet
- Univ. Grenoble Alpes, Inserm, GIN, Grenoble Institut des Neurosciences, Grenoble, France
| | | | - Olivier David
- Univ. Grenoble Alpes, Inserm, GIN, Grenoble Institut des Neurosciences, Grenoble, France; Aix Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France
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32
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Kundu B, Davis TS, Philip B, Smith EH, Arain A, Peters A, Newman B, Butson CR, Rolston JD. A systematic exploration of parameters affecting evoked intracranial potentials in patients with epilepsy. Brain Stimul 2020; 13:1232-1244. [PMID: 32504827 PMCID: PMC7494632 DOI: 10.1016/j.brs.2020.06.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 05/27/2020] [Accepted: 06/01/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Brain activity is constrained by and evolves over a network of structural and functional connections. Corticocortical evoked potentials (CCEPs) have been used to measure this connectivity and to discern brain areas involved in both brain function and disease. However, how varying stimulation parameters influences the measured CCEP across brain areas has not been well characterized. OBJECTIVE To better understand the factors that influence the amplitude of the CCEPs as well as evoked gamma-band power (70-150 Hz) resulting from single-pulse stimulation via cortical surface and depth electrodes. METHODS CCEPs from 4370 stimulation-response channel pairs were recorded across a range of stimulation parameters and brain regions in 11 patients undergoing long-term monitoring for epilepsy. A generalized mixed-effects model was used to model cortical response amplitudes from 5 to 100 ms post-stimulation. RESULTS Stimulation levels <5.5 mA generated variable CCEPs with low amplitude and reduced spatial spread. Stimulation at ≥5.5 mA yielded a reliable and maximal CCEP across stimulation-response pairs over all regions. These findings were similar when examining the evoked gamma-band power. The amplitude of both measures was inversely correlated with distance. CCEPs and evoked gamma power were largest when measured in the hippocampus compared with other areas. Larger CCEP size and evoked gamma power were measured within the seizure onset zone compared with outside this zone. CONCLUSION These results will help guide future stimulation protocols directed at quantifying network connectivity across cognitive and disease states.
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Affiliation(s)
- Bornali Kundu
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA
| | - Tyler S Davis
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA
| | - Brian Philip
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA
| | - Elliot H Smith
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA
| | - Amir Arain
- Department of Neurology, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA
| | - Angela Peters
- Department of Neurology, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA
| | - Blake Newman
- Department of Neurology, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA
| | - Christopher R Butson
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
| | - John D Rolston
- Department of Neurosurgery, Clinical Neurosciences Center, University of Utah, Salt Lake City, UT, USA; Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, USA; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA.
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Kämpfer C, Racz A, Quesada CM, Elger CE, Surges R. Predictive value of electrically induced seizures for postsurgical seizure outcome. Clin Neurophysiol 2020; 131:2289-2297. [PMID: 32674959 DOI: 10.1016/j.clinph.2020.06.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE To determine whether semiological similarity of electrically induced seizures (EIS) and spontaneously occurring habitual seizures (SHS) is associated with postsurgical seizure outcome in patients undergoing invasive video-EEG monitoring (VEM) before resective epilepsy surgery. METHODS Data of patients undergoing invasive VEM were retrospectively reviewed and included if at least one EIS and SHS during VEM occurred and the brain region in which EIS were elicited was resected. Seizure outcome was evaluated at three follow-up (FU) visits after surgery (1, 2 years and last available FU) according to the classification by Engel and the International League Against Epilepsy (ILAE). The level of semiological similarity of EIS and SHS was rated blinded to the surgical outcome. Statistics were done using Fisher's exact test and a mixed linear-logistic regression model. RESULTS 65 patients were included. Postsurgical seizure freedom was achieved in 51% (ILAE class 1) and 58% (Engel class I) at last FU (median 36 months). Patients with identical EIS and SHS displayed significantly better postsurgical seizure outcomes (ILAE class 1 at last FU: 76% vs. 31%, p < 0.001; Engel class I: 83% vs. 39%, p < 0.001). CONCLUSION EIS are useful to confirm the location of the epileptogenic zone. A high level of similarity between EIS and SHS is associated with a favorable postsurgical seizure outcome. SIGNIFICANCE EIS may be used as an additional predictor of postsurgical outcome when counselling patients to proceed to resective epilepsy surgery.
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Affiliation(s)
- Christopher Kämpfer
- Department of Epileptology, University Hospital Bonn, Bonn, Germany; Department of Radiology, University Hospital Bonn, Bonn, Germany
| | - Attila Racz
- Department of Epileptology, University Hospital Bonn, Bonn, Germany
| | - Carlos M Quesada
- Department of Epileptology, University Hospital Bonn, Bonn, Germany; Department of Neurology, University Hospital Essen, Essen, Germany
| | | | - Rainer Surges
- Department of Epileptology, University Hospital Bonn, Bonn, Germany.
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Silverstein BH, Asano E, Sugiura A, Sonoda M, Lee MH, Jeong JW. Dynamic tractography: Integrating cortico-cortical evoked potentials and diffusion imaging. Neuroimage 2020; 215:116763. [PMID: 32294537 DOI: 10.1016/j.neuroimage.2020.116763] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 03/02/2020] [Accepted: 03/17/2020] [Indexed: 02/03/2023] Open
Abstract
INTRODUCTION Cortico-cortical evoked potentials (CCEPs) are utilized to identify effective networks in the human brain. Following single-pulse electrical stimulation of cortical electrodes, evoked responses are recorded from distant cortical areas. A negative deflection (N1) which occurs 10-50 ms post-stimulus is considered to be a marker for direct cortico-cortical connectivity. However, with CCEPs alone it is not possible to observe the white matter pathways that conduct the signal or accurately predict N1 amplitude and latency at downstream recoding sites. Here, we develop a new approach, termed "dynamic tractography," which integrates CCEP data with diffusion-weighted imaging (DWI) data collected from the same patients. This innovative method allows greater insights into cortico-cortical networks than provided by each method alone and may improve the understanding of large-scale networks that support cognitive functions. The dynamic tractography model produces several fundamental hypotheses which we investigate: 1) DWI-based pathlength predicts N1 latency; 2) DWI-based pathlength negatively predicts N1 voltage; and 3) fractional anisotropy (FA) along the white matter path predicts N1 propagation velocity. METHODS Twenty-three neurosurgical patients with drug-resistant epilepsy underwent both extraoperative CCEP recordings and preoperative DWI scans. Subdural grids of 3 mm diameter electrodes were used for stimulation and recording, with 98-128 eligible electrodes per patient. CCEPs were elicited by trains of 1 Hz stimuli with an intensity of 5 mA and recorded at a sample rate of 1 kHz. N1 peak and latency were defined as the maximum of a negative deflection within 10-50 ms post-stimulus with a z-score > 5 relative to baseline. Electrodes and DWI were coregistered to construct electrode connectomes for white matter quantification. RESULTS Clinical variables (age, sex, number of anti-epileptic drugs, handedness, and stimulated hemisphere) did not correlate with the key outcome measures (N1 peak amplitude, latency, velocity, or DWI pathlength). All subjects and electrodes were therefore pooled into a group-level analysis to determine overall patterns. As hypothesized, DWI path length positively predicted N1 latency (R2 = 0.81, β = 1.51, p = 4.76e-16) and negatively predicted N1 voltage (R2 = 0.79, β = -0.094, p = 9.30e-15), while FA predicted N1 propagation velocity (R2 = 0.35, β = 48.0, p = 0.001). CONCLUSION We have demonstrated that the strength and timing of the CCEP N1 is dependent on the properties of the underlying white matter network. Integrated CCEP and DWI visualization allows robust localization of intact axonal pathways which effectively interconnect eloquent cortex.
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Affiliation(s)
- Brian H Silverstein
- Translational Neuroscience Program, Wayne State University, Detroit, MI, USA
| | - Eishi Asano
- Translational Neuroscience Program, Wayne State University, Detroit, MI, USA; Dept. of Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA; Dept. of Neurology, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA
| | - Ayaka Sugiura
- Dept. of Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA
| | - Masaki Sonoda
- Dept. of Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA
| | - Min-Hee Lee
- Dept. of Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA; Translational Imaging Laboratory, Wayne State University, Detroit, MI, USA
| | - Jeong-Won Jeong
- Translational Neuroscience Program, Wayne State University, Detroit, MI, USA; Dept. of Pediatrics, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA; Dept. of Neurology, Wayne State University, Children's Hospital of Michigan, Detroit, MI, USA; Translational Imaging Laboratory, Wayne State University, Detroit, MI, USA.
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Prime D, Woolfe M, O'Keefe S, Rowlands D, Dionisio S. Quantifying volume conducted potential using stimulation artefact in cortico-cortical evoked potentials. J Neurosci Methods 2020; 337:108639. [PMID: 32156547 DOI: 10.1016/j.jneumeth.2020.108639] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Revised: 02/16/2020] [Accepted: 02/18/2020] [Indexed: 01/27/2023]
Abstract
BACKGROUND Cortico-cortical evoked potentials (CCEP) are a technique using low frequency stimulation to infer regions of cortical connectivity in patients undergoing Stereo-electroencephalographic (SEEG) monitoring for refractory epilepsy. Little attention has been given to volume conducted components of CCEP responses, and how they may inflate CCEP connectivity. NEW METHOD Using data from 37 SEEG-CCEPs patients, a novel method was developed to quantify stimulation artefact by measuring the peak-to-peak voltage difference in the first 10 ms after CCEP stimulation. Early responses to CCEP stimulation were also quantified by calculating the root mean square of the 10-100 ms period after each stimulation pulse. Both the early CCEP responses and amplitude of stimulation artefact were regressed by physical distance, stimulation waveform, stimulation intensity and tissue type to identify conduction related properties. RESULTS Both stimulation artefact and early responses were correlated strongly with the inverse square of the distance from the stimulating electrode. Once corrected for the inverse square distance from the electrode, stimulation artefact and CCEP responses showed a linear relationship, indicating a volume conducted component. COMPARISON WITH EXISTING METHODS This is the first study to use stimulation artefact to quantify volume conducted potentials, and is the first to quantify volume conducted potentials in SEEG. A single prior study utilizing electrocorticography has shown that parts of early CCEP responses are due to volume conduction. CONCLUSIONS The linear relationship between stimulation artefact amplitude and CCEP early responses, once corrected for distance, suggests that stimulation artefact can be used as a measure to quantify the volume conducted components.
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Affiliation(s)
- David Prime
- Griffith University School of Engineering, Nathan, QLD, Australia; Mater Advanced Epilepsy Unit, Brisbane, QLD, Australia.
| | - Matthew Woolfe
- Griffith University School of Engineering, Nathan, QLD, Australia; Mater Advanced Epilepsy Unit, Brisbane, QLD, Australia
| | - Steven O'Keefe
- Griffith University School of Engineering, Nathan, QLD, Australia
| | - David Rowlands
- Griffith University School of Engineering, Nathan, QLD, Australia
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Prime D, Woolfe M, Rowlands D, O'Keefe S, Dionisio S. Comparing connectivity metrics in cortico-cortical evoked potentials using synthetic cortical response patterns. J Neurosci Methods 2020; 334:108559. [PMID: 31927000 DOI: 10.1016/j.jneumeth.2019.108559] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2019] [Revised: 12/06/2019] [Accepted: 12/16/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND Cortico-Cortical Evoked Potentials (CCEPs) are a novel low frequency stimulation method used for brain mapping during intracranial epilepsy investigations. Only a handful of metrics have been applied to CCEP data to infer connectivity, and no comparison as to which is best has been performed. NEW METHOD We implement a novel method which involved superimposing synthetic cortical responses onto stereoelectroencephalographic (SEEG) data, and use this to compare several metric's ability to detect the simulated patterns. In this we compare two commonly employed metrics currently used in CCEP analysis against eight time series similarity metrics (TSSMs), which have been widely used in machine learning and pattern matching applications. RESULTS Root Mean Square (RMS), a metric commonly employed in CCEP analysis, was sensitive to a wide variety of response patterns, but insensitive to simulated epileptiform patterns. Autoregressive (AR) coefficients calculated by Burg's method were also sensitive to a wide range of patterns, but were extremely sensitive to epileptiform patterns. Other metrics which employed elastic warping techniques were less sensitive to the simulated response patterns. COMPARISON WITH EXISTING METHODS Our study is the first to compare CCEP connectivity metrics against one-another. Our results found that RMS, which has been used in many CCEP studies previously, was the most sensitive metric across a wide range of patterns. CONCLUSIONS Our novel method showed that RMS is a robust and sensitive measure, validating much of the findings of the SEEG-CCEP literature to date. Autoregressive coefficients may also be a useful metric to investigate epileptic networks.
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Affiliation(s)
- David Prime
- Griffith University School of Engineering and Built Environment, Nathan, QLD, Australia; Mater Advanced Epilepsy Unit, Brisbane, QLD, Australia.
| | - Matthew Woolfe
- Griffith University School of Engineering and Built Environment, Nathan, QLD, Australia; Mater Advanced Epilepsy Unit, Brisbane, QLD, Australia
| | - David Rowlands
- Griffith University School of Engineering and Built Environment, Nathan, QLD, Australia
| | - Steven O'Keefe
- Griffith University School of Engineering and Built Environment, Nathan, QLD, Australia
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Yu X, Ding P, Yuan L, Zhang J, Liang S, Zhang S, Liu N, Liang S. Cortico-Cortical Evoked Potentials in Children With Tuberous Sclerosis Complex Using Stereo-Electroencephalography. Front Neurol 2019; 10:1093. [PMID: 31736846 PMCID: PMC6828959 DOI: 10.3389/fneur.2019.01093] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Accepted: 09/30/2019] [Indexed: 01/14/2023] Open
Abstract
Objectives: Patients with tuberous sclerosis complex (TSC) present multiple cortical tubers in the brain, which are responsible for epilepsy. It is still difficult to localize the epileptogenic tuber. The value of cortico-cortical evoked potentials (CCEPs) was assessed in epileptogenic tuber localization in patients with TSC using stereo-electroencephalography (SEEG). Methods: Patients with TSC who underwent SEEG and CCEP examination in preoperative evaluation during 2014–2017 and reached postoperative seizure freedom at 1-year follow-up were enrolled in this study (n = 11). CCEPs were conducted by stimulating every two adjacent contacts of SEEG electrodes and recording on other contacts of SEEG electrodes in one epileptogenic tuber and its early-stage propagating tuber, and their perituberal cortexes in each patient. The CCEP was defined as positive when N1 and/or N2 wave presented, and then the occurrence rates of positive CCEPs were then compared among different tubers and perituberal regions. Results: Occurrence rates of positive CCEP from epileptogenic tubers to early propagating tubers and epileptogenic tubers to perituberal cortexes were 100%, which were significantly higher than the occurrence rates of CCEP between other locations. The occurrence rates of CCEP from peripheral portions of epileptogenic tubers to peripheral portions of early propagating tubers or perituberal cortexes were 100%, which were significant higher than the occurrence rates of CCEP from peripheral regions of early propagating tubers to peripheral portions of epileptogenic tubers, from the central part of early propagating tuber to central portions of epileptogenic tubers, or from perituberal cortexes to the center part of epileptogenic tubers. Conclusion: Epileptogenic tubers presented much more diffusive connectivity with other tubers and perituberal cortexes than any other connectivity relationships across propagating tubers, and the peripheral region of epileptogenic tubers presented the greatest connectivity with propagating tubers and perituberal cortexes. CCEP can be an effective tool in epileptogenic tuber localization in patients with TSC.
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Affiliation(s)
- Xiaoman Yu
- Department of Neurosurgery, Fourth Medical Center of People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Ping Ding
- Department of Neurosurgery, Fourth Medical Center of People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Liu Yuan
- Department of Neurosurgery, Fourth Medical Center of People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Juncheng Zhang
- Department of Neurosurgery, Affiliated Hospital of Jining Medical College, Jining, China
| | - Shuangshuang Liang
- Department of Neurosurgery, Fourth Medical Center of People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Shaohui Zhang
- Department of Neurosurgery, Fourth Medical Center of People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Na Liu
- Department of Neurosurgery, Fourth Medical Center of People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Shuli Liang
- Department of Functional Neurosurgery, Beijing Children's Hospital, Capital Medical University, Beijing, China
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Dionisio S, Mayoglou L, Cho SM, Prime D, Flanigan PM, Lega B, Mosher J, Leahy R, Gonzalez-Martinez J, Nair D. Connectivity of the human insula: A cortico-cortical evoked potential (CCEP) study. Cortex 2019; 120:419-442. [PMID: 31442863 DOI: 10.1016/j.cortex.2019.05.019] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Revised: 05/02/2019] [Accepted: 05/22/2019] [Indexed: 11/24/2022]
Abstract
OBJECTIVE The human insula is increasingly being implicated as a multimodal functional network hub involved in a large variety of complex functions. Due to its inconspicuous location and highly vascular anatomy, it has historically been difficult to study. Cortico-cortical evoked potentials (CCEPs), utilize low frequency stimulation to map cerebral networks. They were used to study connections of the human insula. METHODS CCEP data was acquired from each sub-region of the dominant and non-dominant insula in 30 patients who underwent stereo-EEG. Connectivity strength to the various cortical regions was obtained via a measure of root mean square (RMS), calculated from each gyrus of the insula and ranked into weighted means. RESULTS The results of all cumulative CCEP responses for each individual gyrus were represented by circro plots. Forty-nine individual CCEP pairs were stimulated across all the gyri from the right and left insula. In brief, the left insula contributed more greatly to language areas. Sensory function, pain, saliency processing and vestibular function were more heavily implicated from the right insula. Connections to the primary auditory cortex arose from both insula regions. Both posterior insula regions showed significant contralateral connectivity. Ipsilateral mesial temporal connections were seen from both insula regions. In visual function, we further report the novel finding of a direct connection between the right posterior insula and left visual cortex. SIGNIFICANCE The insula is a major multi-modal network hub with the cerebral cortex having major roles in language, sensation, auditory, visual, limbic and vestibular functions as well as saliency processing. In temporal lobe epilepsy surgery failure, the insula may be implicated as an extra temporal cause, due to the strong mesial temporal connectivity findings.
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Affiliation(s)
- Sasha Dionisio
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA; Epilepsy Centre, Mater Centre for Neurosciences, Brisbane, Australia.
| | - Lazarus Mayoglou
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA; Epilepsy Center, UPMC Hamot, Erie, PA, USA
| | - Sung-Min Cho
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA
| | - David Prime
- Epilepsy Centre, Mater Centre for Neurosciences, Brisbane, Australia; Griffith School of Electrical Engineering, Nathan Campus, QLD, Australia
| | - Patrick M Flanigan
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA
| | - Bradley Lega
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA; Neurological Surgery, University of Texas-Southwestern, Dallas, TX, USA
| | - John Mosher
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA
| | - Richard Leahy
- Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA
| | | | - Dileep Nair
- Epilepsy Center, Cleveland Clinic, Neurological Institute, Cleveland, OH, USA
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Carvallo A, Modolo J, Benquet P, Lagarde S, Bartolomei F, Wendling F. Biophysical Modeling for Brain Tissue Conductivity Estimation Using SEEG Electrodes. IEEE Trans Biomed Eng 2019; 66:1695-1704. [DOI: 10.1109/tbme.2018.2877931] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Comolatti R, Pigorini A, Casarotto S, Fecchio M, Faria G, Sarasso S, Rosanova M, Gosseries O, Boly M, Bodart O, Ledoux D, Brichant JF, Nobili L, Laureys S, Tononi G, Massimini M, Casali AG. A fast and general method to empirically estimate the complexity of brain responses to transcranial and intracranial stimulations. Brain Stimul 2019; 12:1280-1289. [PMID: 31133480 DOI: 10.1016/j.brs.2019.05.013] [Citation(s) in RCA: 58] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2018] [Revised: 05/11/2019] [Accepted: 05/13/2019] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND The Perturbational Complexity Index (PCI) was recently introduced to assess the capacity of thalamocortical circuits to engage in complex patterns of causal interactions. While showing high accuracy in detecting consciousness in brain-injured patients, PCI depends on elaborate experimental setups and offline processing, and has restricted applicability to other types of brain signals beyond transcranial magnetic stimulation and high-density EEG (TMS/hd-EEG) recordings. OBJECTIVE We aim to address these limitations by introducing PCIST, a fast method for estimating perturbational complexity of any given brain response signal. METHODS PCIST is based on dimensionality reduction and state transitions (ST) quantification of evoked potentials. The index was validated on a large dataset of TMS/hd-EEG recordings obtained from 108 healthy subjects and 108 brain-injured patients, and tested on sparse intracranial recordings (SEEG) of 9 patients undergoing intracranial single-pulse electrical stimulation (SPES) during wakefulness and sleep. RESULTS When calculated on TMS/hd-EEG potentials, PCIST performed with the same accuracy as the original PCI, while improving on the previous method by being computed in less than a second and requiring a simpler set-up. In SPES/SEEG signals, the index was able to quantify a systematic reduction of intracranial complexity during sleep, confirming the occurrence of state-dependent changes in the effective connectivity of thalamocortical circuits, as originally assessed through TMS/hd-EEG. CONCLUSIONS PCIST represents a fundamental advancement towards the implementation of a reliable and fast clinical tool for the bedside assessment of consciousness as well as a general measure to explore the neuronal mechanisms of loss/recovery of brain complexity across scales and models.
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Affiliation(s)
- Renzo Comolatti
- Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, 12231-280, Brazil
| | - Andrea Pigorini
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, 20157, Italy
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, 20157, Italy
| | - Matteo Fecchio
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, 20157, Italy
| | - Guilherme Faria
- Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, 12231-280, Brazil
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, 20157, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, 20157, Italy
| | - Olivia Gosseries
- GIGA-Consciousness, GIGA Research, University of Liège, Liège, 4000, Belgium; Coma Science Group, University Hospital of Liège, Liège, 4000, Belgium
| | - Mélanie Boly
- Department of Psychiatry, University of Wisconsin, Madison, 53719, USA
| | - Olivier Bodart
- GIGA-Consciousness, GIGA Research, University of Liège, Liège, 4000, Belgium; Coma Science Group, University Hospital of Liège, Liège, 4000, Belgium
| | - Didier Ledoux
- GIGA-Consciousness, GIGA Research, University of Liège, Liège, 4000, Belgium
| | - Jean-François Brichant
- Department of Anesthesia and Intensive Care Medicine, University Hospital of Liège, Liège, 4000, Belgium
| | - Lino Nobili
- Center of Epilepsy Surgery "C. Munari", Department of Neuroscience, Niguarda Hospital, Milan, 20162, Italy; Child Neuropsychiatry, IRCCS G. Gaslini, DINOGMI, University of Genoa, Genova, 16147, Italy
| | - Steven Laureys
- GIGA-Consciousness, GIGA Research, University of Liège, Liège, 4000, Belgium; Coma Science Group, University Hospital of Liège, Liège, 4000, Belgium
| | - Giulio Tononi
- Department of Psychiatry, University of Wisconsin, Madison, 53719, USA
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "Luigi Sacco", University of Milan, Milan, 20157, Italy; Istituto Di Ricovero e Cura a Carattere Scientifico, Fondazione Don Carlo Gnocchi, Milan, 20148, Italy
| | - Adenauer G Casali
- Institute of Science and Technology, Federal University of São Paulo, São José dos Campos, 12231-280, Brazil.
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Filipescu C, Lagarde S, Lambert I, Pizzo F, Trébuchon A, McGonigal A, Scavarda D, Carron R, Bartolomei F. The effect of medial pulvinar stimulation on temporal lobe seizures. Epilepsia 2019; 60:e25-e30. [DOI: 10.1111/epi.14677] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 01/02/2019] [Accepted: 01/29/2019] [Indexed: 01/08/2023]
Affiliation(s)
- Cristina Filipescu
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
| | - Stanislas Lagarde
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
| | - Isabelle Lambert
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
| | - Francesca Pizzo
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
| | - Agnès Trébuchon
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
| | - Aileen McGonigal
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
| | - Didier Scavarda
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
- Pediatric Neurosurgery Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
| | - Romain Carron
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
- Functional and Stereotactic Neurosurgery Assitance Publique Hôpitaux de Marseille Marseille France
| | - Fabrice Bartolomei
- Clinical Neurophysiology and Epileptology Department Timone Hospital Assitance Publique Hôpitaux de Marseille Marseille France
- National Institute of Health and Medical Research Institut de Neurosciences des Systèmes Aix‐Marseille University Marseille France
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