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Waris A, Siraj M, Khan A, Lin J, Asim M, Alhumaydh FA. A Comprehensive Overview of the Current Status and Advancements in Various Treatment Strategies against Epilepsy. ACS Pharmacol Transl Sci 2024; 7:3729-3757. [PMID: 39698272 PMCID: PMC11650742 DOI: 10.1021/acsptsci.4c00494] [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: 08/16/2024] [Revised: 10/10/2024] [Accepted: 10/21/2024] [Indexed: 12/20/2024]
Abstract
Epilepsy affects more than 70 million individuals of all ages worldwide and remains one of the most severe chronic noncommunicable neurological diseases globally. Several neurotransmitters, membrane protein channels, receptors, enzymes, and, more recently noted, various pathways, such as inflammatory and mTORC complexes, play significant roles in the initiation and propagation of seizures. Over the past two decades, significant developments have been made in the diagnosis and treatment of epilepsy. Various pharmacological drugs with diverse mechanisms of action and other treatment options have been developed to control seizures and treat epilepsy. These options include surgical treatment, nanomedicine, gene therapy, natural products, nervous stimulation, a ketogenic diet, gut microbiota, etc., which are in various developmental stages. Despite a plethora of drugs and other treatment options, one-third of affected individuals are resistant to current medications, while the majority of approved drugs have severe side effects, and significant changes can occur, such as pharmacoresistance, effects on cognition, long-term problems, drug interactions, risks of poor adherence, specific effects for certain medications, and psychological complications. Therefore, the development of new drugs and other treatment options that have no or minimal adverse effects is needed to combat this deadly disease. In this Review, we comprehensively summarize and explain all of the treatment options that have been approved or are in developmental stages for epilepsy as well as their status in clinical trials and advancements.
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Affiliation(s)
- Abdul Waris
- Department
of Biomedical Science, City University of
Hong Kong, 999077 Hong Kong SAR
| | - Muhammad Siraj
- Department
of Biotechnology, Jeonbuk National University−Iksan
Campus, Jeonju 54896, South Korea
| | - Ayyaz Khan
- Department
of Biomedical Sciences and Institute for Medical Science, Jeonbuk National University Medical School, Jeonju 54907, South Korea
| | - Junyu Lin
- Department
of Neuroscience, City University of Hong
Kong, 999077 Hong Kong SAR
| | - Muhammad Asim
- Department
of Neuroscience, City University of Hong
Kong, 999077 Hong Kong SAR
| | - Fahad A. Alhumaydh
- Department
of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia
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2
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Josephson CB, Aronica E, Beniczky S, Boyce D, Cavalleri G, Denaxas S, French J, Jehi L, Koh H, Kwan P, McDonald C, Mitchell JW, Rampp S, Sadleir L, Sisodiya SM, Wang I, Wiebe S, Yasuda C, Youngerman B. Big data research is everyone's research-Making epilepsy data science accessible to the global community: Report of the ILAE big data commission. Epileptic Disord 2024; 26:733-752. [PMID: 39446076 DOI: 10.1002/epd2.20288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 07/24/2024] [Accepted: 09/04/2024] [Indexed: 10/25/2024]
Abstract
Epilepsy care generates multiple sources of high-dimensional data, including clinical, imaging, electroencephalographic, genomic, and neuropsychological information, that are collected routinely to establish the diagnosis and guide management. Thanks to high-performance computing, sophisticated graphics processing units, and advanced analytics, we are now on the cusp of being able to use these data to significantly improve individualized care for people with epilepsy. Despite this, many clinicians, health care providers, and people with epilepsy are apprehensive about implementing Big Data and accompanying technologies such as artificial intelligence (AI). Practical, ethical, privacy, and climate issues represent real and enduring concerns that have yet to be completely resolved. Similarly, Big Data and AI-related biases have the potential to exacerbate local and global disparities. These are highly germane concerns to the field of epilepsy, given its high burden in developing nations and areas of socioeconomic deprivation. This educational paper from the International League Against Epilepsy's (ILAE) Big Data Commission aims to help clinicians caring for people with epilepsy become familiar with how Big Data is collected and processed, how they are applied to studies using AI, and outline the immense potential positive impact Big Data can have on diagnosis and management.
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Affiliation(s)
- Colin B Josephson
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Alberta, Canada
- O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada
- Centre for Health Informatics, University of Calgary, Calgary, Alberta, Canada
- Institute for Health Informatics, University College London, London, UK
| | - Eleonora Aronica
- Department of (Neuro)Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Stichting Epilepsie Instellingen Nederland (SEIN), Heemstede, The Netherlands
| | - Sandor Beniczky
- Department of Neurology, Albert Szent-Györgyi Medical School, University of Szeged, Szeged, Hungary
- Department of Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark
- Department of Clinical Medicine, Aarhus University and Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Danielle Boyce
- Tufts University School of Medicine, Boston, Massachusetts, USA
- Johns Hopkins University Biomedical Informatics and Data Science Section, Baltimore, Maryland, USA
- West Chester University Department of Public Policy and Administration, West Chester, Pennsylvania, USA
| | - Gianpiero Cavalleri
- School of Pharmacy and Biomolecular Sciences, The Royal College of Surgeons in Ireland, Dublin, Ireland
- FutureNeuro SFI Research Centre, The Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Spiros Denaxas
- Institute for Health Informatics, University College London, London, UK
- British Heart Foundation Data Science Center, Health Data Research UK, London, UK
| | - Jacqueline French
- Department of Neurology, Grossman School of Medicine, New York University, New York, New York, USA
| | - Lara Jehi
- Epilepsy Center, Cleveland Clinic, Cleveland, Ohio, USA
- Center for Computational Life Sciences, Cleveland, Ohio, USA
| | - Hyunyong Koh
- Harvard Brain Science Initiative, Harvard University, Boston, Massachusetts, USA
| | - Patrick Kwan
- Department of Neuroscience, School of Translational Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
- Department of Neurology, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Carrie McDonald
- Department of Radiation Medicine and Applied Sciences & Psychiatry, University of California, San Diego, California, USA
| | - James W Mitchell
- Institute of Systems, Molecular and Integrative Biology (ISMIB), University of Liverpool, Liverpool, UK
- Department of Neurology, The Walton Cetnre NHS Foundation Trust, Liverpool, UK
| | - Stefan Rampp
- Department of Neurosurgery and Department of Neuroradiology, University Hospital Erlangen, Department of Neurosurgery, University Hospital Halle (Saale), Halle (Saale), Germany
| | - Lynette Sadleir
- Department of Paediatrics and Child Health, University of Otago, Wellington, New Zealand
| | - Sanjay M Sisodiya
- Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, London WC1N 3BG and Chalfont Centre for Epilepsy, London, UK
| | - Irene Wang
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, Ohio, USA
| | - Samuel Wiebe
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada
- Department of Community Health Sciences, Cumming School of Medicine, University of Calgary, Alberta, Canada
- O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada
- Clinical Research Unit, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - Clarissa Yasuda
- Department of Neurology, University of Campinas, Campinas, Brazil
| | - Brett Youngerman
- Department of Neurological Surgery, Columbia University Vagelos College of Physicians and Surgeons, New York, New York, USA
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3
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Herbozo Contreras LF, Truong ND, Eshraghian JK, Xu Z, Huang Z, Bersani–Veroni TV, Aguilar I, Leung WH, Nikpour A, Kavehei O. Neuromorphic neuromodulation: Towards the next generation of closed-loop neurostimulation. PNAS NEXUS 2024; 3:pgae488. [PMID: 39554511 PMCID: PMC11565243 DOI: 10.1093/pnasnexus/pgae488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/03/2024] [Accepted: 10/02/2024] [Indexed: 11/19/2024]
Abstract
Neuromodulation techniques have emerged as promising approaches for treating a wide range of neurological disorders, precisely delivering electrical stimulation to modulate abnormal neuronal activity. While leveraging the unique capabilities of AI holds immense potential for responsive neurostimulation, it appears as an extremely challenging proposition where real-time (low-latency) processing, low-power consumption, and heat constraints are limiting factors. The use of sophisticated AI-driven models for personalized neurostimulation depends on the back-telemetry of data to external systems (e.g. cloud-based medical mesosystems and ecosystems). While this can be a solution, integrating continuous learning within implantable neuromodulation devices for several applications, such as seizure prediction in epilepsy, is an open question. We believe neuromorphic architectures hold an outstanding potential to open new avenues for sophisticated on-chip analysis of neural signals and AI-driven personalized treatments. With more than three orders of magnitude reduction in the total data required for data processing and feature extraction, the high power- and memory-efficiency of neuromorphic computing to hardware-firmware co-design can be considered as the solution-in-the-making to resource-constraint implantable neuromodulation systems. This perspective introduces the concept of Neuromorphic Neuromodulation, a new breed of closed-loop responsive feedback system. It highlights its potential to revolutionize implantable brain-machine microsystems for patient-specific treatment.
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Affiliation(s)
| | - Nhan Duy Truong
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia
- Sydney Nano Institute, The University of Sydney, Sydney, NSW 2006, Australia
| | - Jason K Eshraghian
- Department of Electrical and Computer Engineering, University of California, Santa Cruz 95064, USA
| | - Zhangyu Xu
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia
| | - Zhaojing Huang
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia
| | | | - Isabelle Aguilar
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia
| | - Wing Hang Leung
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia
| | - Armin Nikpour
- Central Clinical School, The University of Sydney, Sydney, NSW 2006, Australia
| | - Omid Kavehei
- School of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia
- Sydney Nano Institute, The University of Sydney, Sydney, NSW 2006, Australia
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4
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Salama H, Salama A, Oscher L, Jallo GI, Shimony N. The role of neuromodulation in the management of drug-resistant epilepsy. Neurol Sci 2024; 45:4243-4268. [PMID: 38642321 DOI: 10.1007/s10072-024-07513-9] [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: 11/15/2023] [Accepted: 04/02/2024] [Indexed: 04/22/2024]
Abstract
Drug-resistant epilepsy (DRE) poses significant challenges in terms of effective management and seizure control. Neuromodulation techniques have emerged as promising solutions for individuals who are unresponsive to pharmacological treatments, especially for those who are not good surgical candidates for surgical resection or laser interstitial therapy (LiTT). Currently, there are three neuromodulation techniques that are FDA-approved for the management of DRE. These include vagus nerve stimulation (VNS), deep brain stimulation (DBS), and responsive neurostimulation (RNS). Device selection, optimal time, and DBS and RNS target selection can also be challenging. In general, the number and localizability of the epileptic foci, alongside the comorbidities manifested by the patients, substantially influence the selection process. In the past, the general axiom was that DBS and VNS can be used for generalized and localized focal seizures, while RNS is typically reserved for patients with one or two highly localized epileptic foci, especially if they are in eloquent areas of the brain. Nowadays, with the advance in our understanding of thalamic involvement in DRE, RNS is also very effective for general non-focal epilepsy. In this review, we will discuss the underlying mechanisms of action, patient selection criteria, and the evidence supporting the use of each technique. Additionally, we explore emerging technologies and novel approaches in neuromodulation, such as closed-loop systems. Moreover, we examine the challenges and limitations associated with neuromodulation therapies, including adverse effects, complications, and the need for further long-term studies. This comprehensive review aims to provide valuable insights on present and future use of neuromodulation.
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Affiliation(s)
- HusamEddin Salama
- Al-Quds University-School of Medicine, Abu Dis, Jerusalem, Palestine
| | - Ahmed Salama
- Al-Quds University-School of Medicine, Abu Dis, Jerusalem, Palestine
| | - Logan Oscher
- Department of Neurosurgery, Institute for Brain Protection Sciences, Johns Hopkins All Children's Hospital, 600 5th Street South, St. Petersburg, FL, 33701, USA
| | - George I Jallo
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA.
- Department of Neurosurgery, Institute for Brain Protection Sciences, Johns Hopkins All Children's Hospital, 600 5th Street South, St. Petersburg, FL, 33701, USA.
| | - Nir Shimony
- Department of Neurosurgery, Johns Hopkins University, Baltimore, MD, USA
- Department of Surgery, St. Jude Children's Research Hospital, Memphis, TN, USA
- Le Bonheur Neuroscience Institute, Le Bonheur Children's Hospital, Memphis, TN, USA
- Department of Neurosurgery, University of Tennessee Health Science Center, Memphis, TN, USA
- Semmes-Murphey Clinic, Memphis, TN, USA
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Schulze-Bonhage A, Nitsche MA, Rotter S, Focke NK, Rao VR. Neurostimulation targeting the epileptic focus: Current understanding and perspectives for treatment. Seizure 2024; 117:183-192. [PMID: 38452614 DOI: 10.1016/j.seizure.2024.03.001] [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: 02/06/2024] [Revised: 02/29/2024] [Accepted: 03/02/2024] [Indexed: 03/09/2024] Open
Abstract
For the one third of people with epilepsy whose seizures are not controlled with medications, targeting the seizure focus with neurostimulation can be an effective therapeutic strategy. In this focused review, we summarize a discussion of targeted neurostimulation modalities during a workshop held in Frankfurt, Germany in September 2023. Topics covered include: available devices for seizure focus stimulation; alternating current (AC) and direct current (DC) stimulation to reduce focal cortical excitability; modeling approaches to simulate DC stimulation; reconciling the efficacy of focal stimulation with the network theory of epilepsy; and the emerging concept of 'neurostimulation zones,' which are defined as cortical regions where focal stimulation is most effective for reducing seizures and which may or may not directly involve the seizure onset zone. By combining experimental data, modeling results, and clinical outcome analysis, rational selection of target regions and stimulation parameters is increasingly feasible, paving the way for a broader use of neurostimulation for epilepsy in the future.
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Affiliation(s)
- Andreas Schulze-Bonhage
- Epilepsy Center, University Medical Center, University of Freiburg, Germany; European Reference Network EpiCare, Belgium; NeuroModul Basic, University of Freiburg, Freiburg, Germany.
| | - Michael A Nitsche
- Dept. Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors, Dortmund, Germany; Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, Germany; German Center for Mental Health (DZPG), Germany
| | - Stefan Rotter
- Bernstein Center Freiburg & Faculty of Biology, University of Freiburg, Germany
| | - Niels K Focke
- Epilepsy Center, Clinic for Neurology, University Medical Center Göttingen, Germany
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, USA
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Privitera MD, Mendoza LC, Carrazana E, Rabinowicz AL. Intracerebral electrographic activity following a single dose of diazepam nasal spray: A pilot study. Epilepsia Open 2024; 9:380-387. [PMID: 38131286 PMCID: PMC10839290 DOI: 10.1002/epi4.12890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 12/11/2023] [Accepted: 12/18/2023] [Indexed: 12/23/2023] Open
Abstract
OBJECTIVE Rescue benzodiazepine medication can be used to treat seizure clusters, which are intermittent, stereotypic episodes of frequent seizure activity that are distinct from a patient's usual seizure pattern. The NeuroPace RNS® System is a device that detects abnormal electrographic activity through intracranial electrodes and administers electrical stimulation to control seizures. Reductions in electrographic activity over days to weeks have been associated with the longer-term efficacy of daily antiseizure medications (ASMs). In this pilot study, electrographic activity over hours to days was examined to assess the impact of a single dose of a proven rescue therapy (diazepam nasal spray) with a rapid onset of action. METHODS Adult volunteers (>18 years old) with clinically indicated RNS (stable settings and ASM usage) received a weight-based dose of diazepam nasal spray in the absence of a clinical seizure. Descriptive statistics for a number of detections and a sum of durations of detections at 10-min, hourly, and 24-h intervals during the 7-day (predose) baseline period were calculated. Post-dose detections at each time interval were compared with the respective baseline-detection intervals using a 1 SD threshold. The number of long episodes that occurred after dosing also were compared with the baseline. RESULTS Five participants were enrolled, and four completed the study; the excluded participant had recurrent seizures during the study. There were no consistent changes (difference >1 SD) in detections between post-dose and mean baseline values. Although variability was high (1 SD was often near or exceeded the mean), three participants showed possible trends for reductions in one or more electrographic variables following treatment. SIGNIFICANCE RNS-assessed electrographic detections and durations were not shown to be sensitive measures of short-term effects associated with a single dose of rescue medication in this small group of participants. The variability of detections may have masked a measurable drug effect. PLAIN LANGUAGE SUMMARY Rescue drugs are used to treat seizure clusters. Responsive neurostimulation (RNS) devices detect and record epilepsy brain waves and then send a pulse to help stop seizures. This pilot study looked at whether one dose of a rescue treatment changes brain activity detected by RNS. There was a very wide range of detections, which made it difficult to see if or how the drug changed brain activity. New studies should look at other types of brain activity, multiple doses, and larger patient groups.
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Affiliation(s)
- Michael D. Privitera
- Department of NeurologyUniversity of Cincinnati College of MedicineCincinnatiOhioUSA
| | - Lucy C. Mendoza
- Department of NeurologyUniversity of Cincinnati College of MedicineCincinnatiOhioUSA
| | - Enrique Carrazana
- Neurelis, Inc.San DiegoCaliforniaUSA
- John A. Burns School of MedicineUniversity of HawaiiHonoluluHawaiiUSA
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Rao VR, Rolston JD. Unearthing the mechanisms of responsive neurostimulation for epilepsy. COMMUNICATIONS MEDICINE 2023; 3:166. [PMID: 37974025 PMCID: PMC10654422 DOI: 10.1038/s43856-023-00401-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 11/03/2023] [Indexed: 11/19/2023] Open
Abstract
Responsive neurostimulation (RNS) is an effective therapy for people with drug-resistant focal epilepsy. In clinical trials, RNS therapy results in a meaningful reduction in median seizure frequency, but the response is highly variable across individuals, with many receiving minimal or no benefit. Understanding why this variability occurs will help improve use of RNS therapy. Here we advocate for a reexamination of the assumptions made about how RNS reduces seizures. This is now possible due to large patient cohorts having used this device, some long-term. Two foundational assumptions have been that the device's intracranial leads should target the seizure focus/foci directly, and that stimulation should be triggered only in response to detected epileptiform activity. Recent studies have called into question both hypotheses. Here, we discuss these exciting new studies and suggest future approaches to patient selection, lead placement, and device programming that could improve clinical outcomes.
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Affiliation(s)
- Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
| | - John D Rolston
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Schmidt R, Welzel B, Löscher W. Effects of season, daytime, sex, and stress on the incidence, latency, frequency, severity, and duration of neonatal seizures in a rat model of birth asphyxia. Epilepsy Behav 2023; 147:109415. [PMID: 37729684 DOI: 10.1016/j.yebeh.2023.109415] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 08/14/2023] [Accepted: 08/19/2023] [Indexed: 09/22/2023]
Abstract
Neonatal seizures are common in newborn infants after birth asphyxia. They occur more frequently in male than female neonates, but it is not known whether sex also affects seizure severity or duration. Furthermore, although stress and diurnal, ultradian, circadian, or multidien cycles are known to affect epileptic seizures in adults, their potential impact on neonatal seizures is not understood. This prompted us to examine the effects of season, daytime, sex, and stress on neonatal seizures in a rat model of birth asphyxia. Seizures monitored in 176 rat pups exposed to asphyxia on 40 experimental days performed over 3 years were evaluated. All rat pups exhibited seizures when exposed to asphyxia at postnatal day 11 (P11), which in terms of cortical development corresponds to term human babies. A first examination of these data indicated a seasonal variation, with the highest seizure severity in the spring. Sex and daytime did not affect seizure characteristics. However, when rat pups were subdivided into animals that were exposed to acute (short-term) stress after asphyxia (restraint and i.p. injection of vehicle) and animals that were not exposed to this stress, the seizures in stress-exposed rats were more severe but less frequent. Acute stress induced an increase in hippocampal microglia density in sham-exposed rat pups, which may have an additive effect on microglia activation induced by asphyxia. When seasonal data were separately analyzed for stress-exposed vs. non-stress-exposed rat pups, no significant seasonal variation was observed. This study illustrates that without a detailed analysis of all factors, the data would have erroneously indicated significant seasonal variability in the severity of neonatal seizures. Instead, the study demonstrates that even mild, short-lasting postnatal stress has a profound effect on asphyxia-induced seizures, most likely by increasing the activity of the hypothalamic-pituitary-adrenal axis. It will be interesting to examine how postnatal stress affects the treatment and adverse outcomes of birth asphyxia and neonatal seizures in the rat model used here.
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Affiliation(s)
- Ricardo Schmidt
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, Germany; Center for Systems Neuroscience Hannover, Germany
| | - Björn Welzel
- Center for Systems Neuroscience Hannover, Germany
| | - Wolfgang Löscher
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, Germany; Center for Systems Neuroscience Hannover, Germany; Translational Neuropharmacology Lab, NIFE, Department of Experimental Otology of the ENT Clinics, Hannover Medical School, Hannover, Germany.
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Zhang F, Yang Y, Xin Y, Sun Y, Wang C, Zhu J, Tang T, Zhang J, Xu K. Efficacy of different strategies of responsive neurostimulation on seizure control and their association with acute neurophysiological effects in rats. Epilepsy Behav 2023; 143:109212. [PMID: 37172446 DOI: 10.1016/j.yebeh.2023.109212] [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: 03/08/2023] [Accepted: 04/01/2023] [Indexed: 05/15/2023]
Abstract
Responsive neurostimulation (RNS) has shown promising but limited efficacy in the treatment of drug-resistant epilepsy. The clinical utility of RNS is hindered by the incomplete understanding of the mechanism behind its therapeutic effects. Thus, assessing the acute effects of responsive stimulation (AERS) based on intracranial EEG recordings in the temporal lobe epilepsy rat model may provide a better understanding of the potential therapeutic mechanisms underlying the antiepileptic effect of RNS. Furthermore, clarifying the correlation between AERS and seizure severity may help guide the optimization of RNS parameter settings. In this study, RNS with high (130 Hz) and low frequencies (5 Hz) was applied to the subiculum (SUB) and CA1. To quantify the changes induced by RNS, we calculated the AERS during synchronization by Granger causality and analyzed the band power ratio in the classic power band after different stimulations were delivered in the interictal and seizure onset periods, respectively. This demonstrates that only targets combined with an appropriate stimulation frequency could be efficient for seizure control. High-frequency stimulation of CA1 significantly shortened the ongoing seizure duration, which may be causally related to increased synchronization after stimulation. Both high-frequency stimulation of the CA1 and low-frequency stimulation delivered to the SUB reduced seizure frequency, and the reduced seizure risk may correlate with the change in power ratio near the theta band. It indicated that different stimulations may control seizures in diverse manners, perhaps with disparate mechanisms. More focus should be placed on understanding the correlation between seizure severity and synchronization and rhythm around theta bands to simplify the process of parameter optimization.
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Affiliation(s)
- Fang Zhang
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Yufang Yang
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Yanjie Xin
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Yuting Sun
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Chang Wang
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Junming Zhu
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, China; Department of Neurosurgery, Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang University, Zhejiang, China
| | - Tao Tang
- Zhejiang Lab, Hangzhou 311100, China
| | - Jianmin Zhang
- The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, China; Department of Neurosurgery, Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang University, Zhejiang, China
| | - Kedi Xu
- Qiushi Academy for Advanced Studies (QAAS), Zhejiang University, Hangzhou, China; The State Key Lab of Brain-Machine Intelligence, Zhejiang University, Hangzhou, China; The MOE Frontier Science Center for Brain Science and Brain-machine Integration, China; Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Key Laboratory of Biomedical Engineering of Education Ministry, Department of Biomedical Engineering, Zhejiang University, Hangzhou, China.
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10
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Boddeti U, McAfee D, Khan A, Bachani M, Ksendzovsky A. Responsive Neurostimulation for Seizure Control: Current Status and Future Directions. Biomedicines 2022; 10:2677. [PMID: 36359197 PMCID: PMC9687706 DOI: 10.3390/biomedicines10112677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 10/13/2022] [Accepted: 10/15/2022] [Indexed: 10/29/2023] Open
Abstract
Electrocorticography (ECoG) data are commonly obtained during drug-resistant epilepsy (DRE) workup, in which subdural grids and stereotaxic depth electrodes are placed on the cortex for weeks at a time, with the goal of elucidating seizure origination. ECoG data can also be recorded from neuromodulatory devices, such as responsive neurostimulation (RNS), which involves the placement of electrodes deep in the brain. Of the neuromodulatory devices, RNS is the first to use recorded ECoG data to direct the delivery of electrical stimulation in order to control seizures. In this review, we first introduced the clinical management for epilepsy, and discussed the steps from seizure onset to surgical intervention. We then reviewed studies discussing the emergence and therapeutic mechanism behind RNS, and discussed why RNS may be underperforming despite an improved seizure detection mechanism. We discussed the potential utility of incorporating machine learning techniques to improve seizure detection in RNS, and the necessity to change RNS targets for stimulation, in order to account for the network theory of epilepsy. We concluded by commenting on the current and future status of neuromodulation in managing epilepsy, and the role of predictive algorithms to improve outcomes.
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Affiliation(s)
- Ujwal Boddeti
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Darrian McAfee
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Anas Khan
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Muzna Bachani
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Alexander Ksendzovsky
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD 21201, USA
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11
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Löscher W, Worrell GA. Novel subscalp and intracranial devices to wirelessly record and analyze continuous EEG in unsedated, behaving dogs in their natural environments: A new paradigm in canine epilepsy research. Front Vet Sci 2022; 9:1014269. [PMID: 36337210 PMCID: PMC9631025 DOI: 10.3389/fvets.2022.1014269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/26/2022] [Indexed: 11/25/2022] Open
Abstract
Epilepsy is characterized by unprovoked, recurrent seizures and is a common neurologic disorder in dogs and humans. Roughly 1/3 of canines and humans with epilepsy prove to be drug-resistant and continue to have sporadic seizures despite taking daily anti-seizure medications. The optimization of pharmacologic therapy is often limited by inaccurate seizure diaries and medication side effects. Electroencephalography (EEG) has long been a cornerstone of diagnosis and classification in human epilepsy, but because of several technical challenges has played a smaller clinical role in canine epilepsy. The interictal (between seizures) and ictal (seizure) EEG recorded from the epileptic mammalian brain shows characteristic electrophysiologic biomarkers that are very useful for clinical management. A fundamental engineering gap for both humans and canines with epilepsy has been the challenge of obtaining continuous long-term EEG in the patients' natural environment. We are now on the cusp of a revolution where continuous long-term EEG from behaving canines and humans will be available to guide clinicians in the diagnosis and optimal treatment of their patients. Here we review some of the devices that have recently emerged for obtaining long-term EEG in ambulatory subjects living in their natural environments.
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Affiliation(s)
- Wolfgang Löscher
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine, Hanover, Germany
- Center for Systems Neuroscience, Hanover, Germany
- *Correspondence: Wolfgang Löscher
| | - Gregory A. Worrell
- Bioelectronics Neurophysiology and Engineering Laboratory, Department of Neurology, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
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12
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Haneef Z, Yang K, Sheth SA, Aloor FZ, Aazhang B, Krishnan V, Karakas C. Sub-scalp electroencephalography: A next-generation technique to study human neurophysiology. Clin Neurophysiol 2022; 141:77-87. [PMID: 35907381 DOI: 10.1016/j.clinph.2022.07.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Revised: 06/20/2022] [Accepted: 07/03/2022] [Indexed: 11/29/2022]
Abstract
Sub-scalp electroencephalography (ssEEG) is emerging as a promising technology in ultra-long-term electroencephalography (EEG) recordings. Given the diversity of devices available in this nascent field, uncertainty persists about its utility in epilepsy evaluation. This review critically dissects the many proposed utilities of ssEEG devices including (1) seizure quantification, (2) seizure characterization, (3) seizure lateralization, (4) seizure localization, (5) seizure alarms, (6) seizure forecasting, (7) biomarker discovery, (8) sleep medicine, and (9) responsive stimulation. The different ssEEG devices in development have individual design philosophies with unique strengths and limitations. There are devices offering primarily unilateral recordings (24/7 EEGTM SubQ, NeuroviewTM, Soenia® UltimateEEG™), bilateral recordings (Minder™, Epios™), and even those with responsive stimulation capability (EASEE®). We synthesize the current knowledge of these ssEEG systems. We review the (1) ssEEG devices, (2) use case scenarios, (3) challenges and (4) suggest a roadmap for ideal ssEEG designs.
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Affiliation(s)
- Zulfi Haneef
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA.
| | - Kaiyuan Yang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA.
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Fuad Z Aloor
- Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
| | - Behnaam Aazhang
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
| | - Vaishnav Krishnan
- Department of Neurology, Baylor College of Medicine, Houston, TX 77030, USA; Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
| | - Cemal Karakas
- Division of Pediatric Neurology, Department of Neurology, University of Louisville, Louisville, KY 40202, USA; Norton Children's Neuroscience Institute, Louisville, KY 40241, USA
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13
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Wheless JW, Friedman D, Krauss GL, Rao VR, Sperling MR, Carrazana E, Rabinowicz AL. Future Opportunities for Research in Rescue Treatments. Epilepsia 2022; 63 Suppl 1:S55-S68. [PMID: 35822912 PMCID: PMC9541657 DOI: 10.1111/epi.17363] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 06/16/2022] [Accepted: 07/11/2022] [Indexed: 11/30/2022]
Abstract
Clinical studies of rescue medications for seizure clusters are limited and are designed to satisfy regulatory requirements, which may not fully consider the needs of the diverse patient population that experiences seizure clusters or utilize rescue medication. The purpose of this narrative review is to examine the factors that contribute to, or may influence the quality of, seizure cluster research with a goal of improving clinical practice. We address five areas of unmet needs and provide advice for how they could enhance future trials of seizure cluster treatments. The topics addressed in this article are: (1) unaddressed end points to pursue in future studies, (2) roles for devices to enhance rescue medication clinical development programs, (3) tools to study seizure cluster prediction and prevention, (4) the value of other designs for seizure cluster studies, and (5) unique challenges of future trial paradigms for seizure clusters. By focusing on novel end points and technologies with value to patients, caregivers, and clinicians, data obtained from future studies can benefit the diverse patient population that experiences seizure clusters, providing more effective, appropriate care as well as alleviating demands on health care resources.
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Affiliation(s)
- James W Wheless
- Le Bonheur Children's Hospital, University of Tennessee Health Science Center, Memphis, Tennessee, USA
| | - Daniel Friedman
- New York University Grossman School of Medicine, New York, New York, USA
| | - Gregory L Krauss
- Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Vikram R Rao
- University of California, San Francisco, California, USA
| | | | - Enrique Carrazana
- Neurelis, San Diego, California, USA.,John A. Burns School of Medicine, University of Hawaii, Honolulu, Hawaii, USA
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Abstract
Epilepsy is a common neurological disease in both humans and domestic dogs, making dogs an ideal translational model of epilepsy. In both species, epilepsy is a complex brain disease characterized by an enduring predisposition to generate spontaneous recurrent epileptic seizures. Furthermore, as in humans, status epilepticus is one of the more common neurological emergencies in dogs with epilepsy. In both species, epilepsy is not a single disease but a group of disorders characterized by a broad array of clinical signs, age of onset, and underlying causes. Brain imaging suggests that the limbic system, including the hippocampus and cingulate gyrus, is often affected in canine epilepsy, which could explain the high incidence of comorbid behavioral problems such as anxiety and cognitive alterations. Resistance to antiseizure medications is a significant problem in both canine and human epilepsy, so dogs can be used to study mechanisms of drug resistance and develop novel therapeutic strategies to benefit both species. Importantly, dogs are large enough to accommodate intracranial EEG and responsive neurostimulation devices designed for humans. Studies in epileptic dogs with such devices have reported ictal and interictal events that are remarkably similar to those occurring in human epilepsy. Continuous (24/7) EEG recordings in a select group of epileptic dogs for >1 year have provided a rich dataset of unprecedented length for studying seizure periodicities and developing new methods for seizure forecasting. The data presented in this review substantiate that canine epilepsy is an excellent translational model for several facets of epilepsy research. Furthermore, several techniques of inducing seizures in laboratory dogs are discussed as related to therapeutic advances. Importantly, the development of vagus nerve stimulation as a novel therapy for drug-resistant epilepsy in people was based on a series of studies in dogs with induced seizures. Dogs with naturally occurring or induced seizures provide excellent large-animal models to bridge the translational gap between rodents and humans in the development of novel therapies. Furthermore, because the dog is not only a preclinical species for human medicine but also a potential patient and pet, research on this species serves both veterinary and human medicine.
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Affiliation(s)
- Wolfgang Löscher
- Department of Pharmacology, Toxicology and Pharmacy, University of Veterinary Medicine, Hannover, Germany
- Center for Systems Neuroscience, Hannover, Germany
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Chiang S, Fan JM, Rao VR. Bilateral temporal lobe epilepsy: How many seizures are required in chronic ambulatory electrocorticography to estimate the laterality ratio? Epilepsia 2022; 63:199-208. [PMID: 34723396 PMCID: PMC9056258 DOI: 10.1111/epi.17113] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 10/17/2021] [Accepted: 10/18/2021] [Indexed: 11/30/2022]
Abstract
OBJECTIVE This study was undertaken to measure the duration of chronic electrocorticography (ECoG) needed to attain stable estimates of the seizure laterality ratio in patients with drug-resistant bilateral temporal lobe epilepsy (BTLE). METHODS We studied 13 patients with drug-resistant BTLE who were implanted for at least 1 year with a responsive neurostimulation device (RNS System) that provides chronic ambulatory ECoG. Bootstrap analysis and nonlinear regression were applied to model the relationship between chronic ECoG duration and the probability of capturing at least one seizure. Laterality of electrographic seizures in chronic ECoG was compared with the seizure laterality ratio from Phase 1 scalp video-electroencephalographic (vEEG) monitoring. The Kaplan-Meier estimator was used to evaluate time to seizure laterality ratio convergence. RESULTS Seizure laterality ratios from Phase 1 scalp vEEG monitoring correlated poorly with those from RNS chronic ECoG (r = .31, p = .30). Across the 13 patients, average electrographic seizure frequencies ranged from 1.4 seizures/month to 5.1 seizures/day. A 50% probability of recording at least one electrographic seizure required 9.1 days of chronic ECoG, and 90% probability required 44.3 days of chronic ECoG. A median recording duration of 150.9 days (5 months), corresponding to a median of 16 seizures, was needed before confidence intervals for the seizure laterality ratio reliably contained the long-term value. The median recording duration before the point estimate of the seizure laterality ratio converged to a stationary value was 236.8 days (7.9 months). SIGNIFICANCE RNS chronic ECoG overcomes temporal sampling limitations intrinsic to inpatient Phase 1 vEEG evaluations. In patients with drug-resistant BTLE, approximately 8 months of chronic RNS ECoG are needed to precisely estimate the seizure laterality ratio, with 75% of people with BTLE achieving convergence after 1 year of RNS recording. For individuals who are candidates for unilateral resection based on seizure laterality, optimized recording duration may help avert morbidity associated with delay to definitive treatment.
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Affiliation(s)
- Sharon Chiang
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Joline M Fan
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Vikram R Rao
- Department of Neurology and Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
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16
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Das RR, Goss AL, Richie MB, Rao VR. ANA Podcasts & Webinars: Neuromodulation in Epilepsy. Ann Neurol 2021; 91:176-177. [PMID: 34825406 DOI: 10.1002/ana.26276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 11/19/2021] [Indexed: 11/09/2022]
Affiliation(s)
- Rohit R Das
- University of Texas Southwestern Medical Center, Dallas, TX
| | - Adeline L Goss
- Department of Neurology, Highland Hospital, San Francisco, CA
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