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Weiss SA, Sperling MR, Engel J, Liu A, Fried I, Wu C, Doyle W, Mikell C, Mofakham S, Salamon N, Sim MS, Bragin A, Staba R. Simulated resections and RNS placement can optimize post-operative seizure outcomes when guided by fast ripple networks. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.26.24304802. [PMID: 38585730 PMCID: PMC10996761 DOI: 10.1101/2024.03.26.24304802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
In medication-resistant epilepsy, the goal of epilepsy surgery is to make a patient seizure free with a resection/ablation that is as small as possible to minimize morbidity. The standard of care in planning the margins of epilepsy surgery involves electroclinical delineation of the seizure onset zone (SOZ) and incorporation of neuroimaging findings from MRI, PET, SPECT, and MEG modalities. Resecting cortical tissue generating high-frequency oscillations (HFOs) has been investigated as a more efficacious alternative to targeting the SOZ. In this study, we used a support vector machine (SVM), with four distinct fast ripple (FR: 350-600 Hz on oscillations, 200-600 Hz on spikes) metrics as factors. These metrics included the FR resection ratio (RR), a spatial FR network measure, and two temporal FR network measures. The SVM was trained by the value of these four factors with respect to the actual resection boundaries and actual seizure free labels of 18 patients with medically refractory focal epilepsy. Leave one out cross-validation of the trained SVM in this training set had an accuracy of 0.78. We next used a simulated iterative virtual resection targeting the FR sites that were highest rate and showed most temporal autonomy. The trained SVM utilized the four virtual FR metrics to predict virtual seizure freedom. In all but one of the nine patients seizure free after surgery, we found that the virtual resections sufficient for virtual seizure freedom were larger in volume (p<0.05). In nine patients who were not seizure free, a larger virtual resection made five virtually seizure free. We also examined 10 medically refractory focal epilepsy patients implanted with the responsive neurostimulator system (RNS) and virtually targeted the RNS stimulation contacts proximal to sites generating FR at highest rates to determine if the simulated value of the stimulated SOZ and stimulated FR metrics would trend toward those patients with a better seizure outcome. Our results suggest: 1) FR measures can accurately predict whether a resection, defined by the standard of care, will result in seizure freedom; 2) utilizing FR alone for planning an efficacious surgery can be associated with larger resections; 3) when FR metrics predict the standard of care resection will fail, amending the boundaries of the planned resection with certain FR generating sites may improve outcome; and 4) more work is required to determine if targeting RNS stimulation contact proximal to FR generating sites will improve seizure outcome.
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Affiliation(s)
- Shennan Aibel Weiss
- Dept. of Neurology, State University of New York Downstate, Brooklyn, New York 11203, USA
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York 11203, USA
- Dept. of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY, 11203 USA
| | - Michael R. Sperling
- Dept. of Neurology, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Jerome Engel
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
- Dept. of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
- Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Anli Liu
- Department of Neurology, NYU Grossman School of Medicine, New York, NY, 10016 USA
- Neuroscience Institute, NYU Langone Medical Center, New York, NY, 10016 USA
| | - Itzhak Fried
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Chengyuan Wu
- Dept. of Neuroradiology, Thomas Jefferson University, Philadelphia, PA, 19107, USA
- Dept. of Neurosurgery, Thomas Jefferson University, Philadelphia, PA 19107, USA
| | - Werner Doyle
- Department of Neurosurgery, NYU Grossman School of Medicine, New York, NY, 10016 USA
| | - Charles Mikell
- Department of Neurosurgery, State University of New York Stony Brook, Stony Brook, New York 11790, USA
| | - Sima Mofakham
- Department of Neurosurgery, State University of New York Stony Brook, Stony Brook, New York 11790, USA
| | - Noriko Salamon
- Dept. of Neuroradiology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Myung Shin Sim
- Dept. of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Anatol Bragin
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
| | - Richard Staba
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095, USA
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Pease M, Gupta K, Moshé SL, Correa DJ, Galanopoulou AS, Okonkwo DO, Gonzalez-Martinez J, Shutter L, Diaz-Arrastia R, Castellano JF. Insights into epileptogenesis from post-traumatic epilepsy. Nat Rev Neurol 2024; 20:298-312. [PMID: 38570704 DOI: 10.1038/s41582-024-00954-y] [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] [Accepted: 03/07/2024] [Indexed: 04/05/2024]
Abstract
Post-traumatic epilepsy (PTE) accounts for 5% of all epilepsies. The incidence of PTE after traumatic brain injury (TBI) depends on the severity of injury, approaching one in three in groups with the most severe injuries. The repeated seizures that characterize PTE impair neurological recovery and increase the risk of poor outcomes after TBI. Given this high risk of recurrent seizures and the relatively short latency period for their development after injury, PTE serves as a model disease to understand human epileptogenesis and trial novel anti-epileptogenic therapies. Epileptogenesis is the process whereby previously normal brain tissue becomes prone to recurrent abnormal electrical activity, ultimately resulting in seizures. In this Review, we describe the clinical course of PTE and highlight promising research into epileptogenesis and treatment using animal models of PTE. Clinical, imaging, EEG and fluid biomarkers are being developed to aid the identification of patients at high risk of PTE who might benefit from anti-epileptogenic therapies. Studies in preclinical models of PTE have identified tractable pathways and novel therapeutic strategies that can potentially prevent epilepsy, which remain to be validated in humans. In addition to improving outcomes after TBI, advances in PTE research are likely to provide therapeutic insights that are relevant to all epilepsies.
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Affiliation(s)
- Matthew Pease
- Department of Neurosurgery, Indiana University, Bloomington, IN, USA.
| | - Kunal Gupta
- Department of Neurosurgery, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Solomon L Moshé
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA
- Department of Neuroscience, Albert Einstein College of Medicine, New York, NY, USA
- Department of Paediatrics, Albert Einstein College of Medicine, New York, NY, USA
| | - Daniel J Correa
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA
| | - Aristea S Galanopoulou
- The Saul R. Korey Department of Neurology, Albert Einstein College of Medicine, New York, NY, USA
- Department of Neuroscience, Albert Einstein College of Medicine, New York, NY, USA
| | - David O Okonkwo
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Lori Shutter
- Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
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Ye H, Chen C, Weiss SA, Wang S. Pathological and Physiological High-frequency Oscillations on Electroencephalography in Patients with Epilepsy. Neurosci Bull 2024; 40:609-620. [PMID: 37999861 PMCID: PMC11127900 DOI: 10.1007/s12264-023-01150-6] [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: 05/21/2023] [Accepted: 09/28/2023] [Indexed: 11/25/2023] Open
Abstract
High-frequency oscillations (HFOs) encompass ripples (80 Hz-200 Hz) and fast ripples (200 Hz-600 Hz), serving as a promising biomarker for localizing the epileptogenic zone in epilepsy. Spontaneous fast ripples are always pathological, while ripples may be physiological or pathological. Distinguishing physiological from pathological ripples is important not only for designating epileptogenic brain regions, but also for investigations that study ripples in the context of memory encoding, consolidation, and recall in patients with epilepsy. Many studies have sought to identify distinguishing features between pathological and physiological ripples over the past two decades. Physiological and pathological ripples differ with respect to their spatial location, cellular mechanisms, morphology, and coupling with background electroencephalographic activity. Retrospective studies have demonstrated that differentiating between pathological and physiological ripples can improve surgical outcome prediction. In this review, we summarize the characteristics, differences, and applications of pathological and physiological HFOs and discuss strategies for their clinical translation.
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Affiliation(s)
- Hongyi Ye
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
| | - Cong Chen
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China
| | - Shennan A Weiss
- Department of Neurology, State University of New York Downstate, Brooklyn, NY, 11203, USA
- Department of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, NY, 11203, USA
- Department of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY, 11203, USA
| | - Shuang Wang
- Department of Neurology, Epilepsy Center, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310009, China.
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Weiss SA, Fried I, Engel J, Bragin A, Wang S, Sperling MR, Wong RK, Nir Y, Staba RJ. Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer. Epilepsia 2024; 65:362-377. [PMID: 38041560 PMCID: PMC10922301 DOI: 10.1111/epi.17845] [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: 08/03/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 12/03/2023]
Abstract
OBJECTIVE To confirm and investigate why pathological high-frequency oscillations (pHFOs), including ripples (80-200 Hz) and fast ripples (200-600 Hz), are generated during the UP-DOWN transition of the slow wave and if information transmission mediated by ripple temporal coupling is disrupted in the seizure-onset zone (SOZ). METHODS We isolated 217 total units from 175.95 intracranial electroencephalography (iEEG) contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the SOZ, HFOs and associated action potentials (APs) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross-correlograms. RESULTS At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p < < .001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p < < .001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d = .11-.83) and fast ripples (d = .36-.90) at the UP-DOWN transition (p < .05 f.d.r. corrected), respectively. By comparison, also in the SOZ, 6.6% (d = .14-.30) and 8.5% (d = .33-.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows that ripple and fast ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by >50% in the SOZ compared to the non-SOZ (N = 3). SIGNIFICANCE The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. Ripple temporal correlations across brain regions may be important in memory consolidation and are disrupted in the SOZ, perhaps by pHFO generation.
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Affiliation(s)
- Shennan A Weiss
- Dept. of Neurology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY, USA
| | - Itzhak Fried
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Jerome Engel
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
- Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Anatol Bragin
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | - Shuang Wang
- Depts of Neurology, Epilepsy Center, Second Affiliated Hospital of Medical College, Zhejiang University, Zhejiang, China
| | - Michael R. Sperling
- Depts. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Robert K.S. Wong
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
| | - Yuval Nir
- Department of Physiology and Pharmacology, Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
- Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
- The Sieratzki-Sagol Center for Sleep Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
| | - Richard J Staba
- Dept. of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
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Chvojka J, Prochazkova N, Rehorova M, Kudlacek J, Kylarova S, Kralikova M, Buran P, Weissova R, Balastik M, Jefferys JGR, Novak O, Jiruska P. Mouse model of focal cortical dysplasia type II generates a wide spectrum of high-frequency activities. Neurobiol Dis 2024; 190:106383. [PMID: 38114051 DOI: 10.1016/j.nbd.2023.106383] [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: 09/27/2023] [Revised: 12/04/2023] [Accepted: 12/13/2023] [Indexed: 12/21/2023] Open
Abstract
High-frequency oscillations (HFOs) represent an electrographic biomarker of endogenous epileptogenicity and seizure-generating tissue that proved clinically useful in presurgical planning and delineating the resection area. In the neocortex, the clinical observations on HFOs are not sufficiently supported by experimental studies stemming from a lack of realistic neocortical epilepsy models that could provide an explanation of the pathophysiological substrates of neocortical HFOs. In this study, we explored pathological epileptiform network phenomena, particularly HFOs, in a highly realistic murine model of neocortical epilepsy due to focal cortical dysplasia (FCD) type II. FCD was induced in mice by the expression of the human pathogenic mTOR gene mutation during embryonic stages of brain development. Electrographic recordings from multiple cortical regions in freely moving animals with FCD and epilepsy demonstrated that the FCD lesion generates HFOs from all frequency ranges, i.e., gamma, ripples, and fast ripples up to 800 Hz. Gamma-ripples were recorded almost exclusively in FCD animals, while fast ripples occurred in controls as well, although at a lower rate. Gamma-ripple activity is particularly valuable for localizing the FCD lesion, surpassing the utility of fast ripples that were also observed in control animals, although at significantly lower rates. Propagating HFOs occurred outside the FCD, and the contralateral cortex also generated HFOs independently of the FCD, pointing to a wider FCD network dysfunction. Optogenetic activation of neurons carrying mTOR mutation and expressing Channelrhodopsin-2 evoked fast ripple oscillations that displayed spectral and morphological profiles analogous to spontaneous oscillations. This study brings experimental evidence that FCD type II generates pathological HFOs across all frequency bands and provides information about the spatiotemporal properties of each HFO subtype in FCD. The study shows that mutated neurons represent a functionally interconnected and active component of the FCD network, as they can induce interictal epileptiform phenomena and HFOs.
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Affiliation(s)
- Jan Chvojka
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic; Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic
| | - Natalie Prochazkova
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Monika Rehorova
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jan Kudlacek
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Salome Kylarova
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Michaela Kralikova
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Peter Buran
- Laboratory of Molecular Neurobiology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Romana Weissova
- Laboratory of Molecular Neurobiology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - Martin Balastik
- Laboratory of Molecular Neurobiology, Institute of Physiology of the Czech Academy of Sciences, Prague, Czech Republic
| | - John G R Jefferys
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Ondrej Novak
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Premysl Jiruska
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic.
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6
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Weiss SA, Fried I, Engel J, Bragin A, Wang S, Sperling MR, Wong RK, Nir Y, Staba RJ. Pathological neurons generate ripples at the UP-DOWN transition disrupting information transfer. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.01.23293365. [PMID: 37609251 PMCID: PMC10441494 DOI: 10.1101/2023.08.01.23293365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Objective To confirm and investigate why pathological HFOs (pHFOs), including Ripples [80-200 Hz] and fast ripples [200-600 Hz], are generated during the UP-DOWN transition of the slow wave and if pHFOs interfere with information transmission. Methods We isolated 217 total units from 175.95 iEEG contact-hours of synchronized macro- and microelectrode recordings from 6 patients. Sleep slow oscillation (0.1-2 Hz) epochs were identified in the iEEG recording. iEEG HFOs that occurred superimposed on the slow wave were transformed to phasors and adjusted by the phase of maximum firing in nearby units (i.e., maximum UP). We tested whether, in the seizure onset zone (SOZ), HFOs and associated action potentials (AP) occur more often at the UP-DOWN transition. We also examined ripple temporal correlations using cross correlograms. Results At the group level in the SOZ, HFO and HFO-associated AP probability was highest during the UP-DOWN transition of slow wave excitability (p<<0.001). In the non-SOZ, HFO and HFO-associated AP was highest during the DOWN-UP transition (p<<0.001). At the unit level in the SOZ, 15.6% and 20% of units exhibited more robust firing during ripples (Cohen's d=0.11-0.83) and fast ripples (d=0.36-0.90) at the UP-DOWN transition (p<0.05 f.d.r corrected), respectively. By comparison, also in the SOZ, 6.6% (d=0.14-0.30) and 8.5% (d=0.33-0.41) of units had significantly less firing during ripples and fast ripples at the UP-DOWN transition, respectively. Additional data shows ripple temporal correlations, involving global slow waves, between the hippocampus, entorhinal cortex, and parahippocampal gyrus were reduced by ~50-80% in the SOZ compared to the non-SOZ (N=3). Significance The UP-DOWN transition of slow wave excitability facilitates the activation of pathological neurons to generate pHFOs. The pathological neurons and pHFOs disrupt ripple temporal correlations across brain regions that transfer information and may be important in memory consolidation.
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Affiliation(s)
- Shennan A Weiss
- Dept. of Neurology
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
- Dept. of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY, USA
| | | | - Jerome Engel
- Dept. of Neurology
- Dept. of Neurosurgery
- Dept. of Neurobiology
- Dept. of Psychiatry and Biobehavioral Sciences
- Brain Research Institute, David Geffen School of Medicine at UCLA, Los Angeles, California, 90095, USA
| | | | - Shuang Wang
- Depts of Neurology, Epilepsy Center, Second Affiliated Hospital of Medical College, Zhejiang University, Zhejiang, China
| | - Michael R. Sperling
- Depts. of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, 19107, USA
| | - Robert K.S. Wong
- Dept. of Physiology and Pharmacology, State University of New York Downstate, Brooklyn, New York, 11203 USA
| | - Yuval Nir
- Department of Physiology and Pharmacology, Sackler School of Medicine, Tel Aviv University, Tel Aviv 6997801, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv 6997801, Israel
- Department of Biomedical Engineering, Faculty of Engineering, Tel Aviv University, Tel Aviv 6997801, Israel
- The Sieratzki-Sagol Center for Sleep Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv 6423906, Israel
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Frauscher B, Bénar CG, Engel JJ, Grova C, Jacobs J, Kahane P, Wiebe S, Zjilmans M, Dubeau F. Neurophysiology, Neuropsychology, and Epilepsy, in 2022: Hills We Have Climbed and Hills Ahead. Neurophysiology in epilepsy. Epilepsy Behav 2023; 143:109221. [PMID: 37119580 DOI: 10.1016/j.yebeh.2023.109221] [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: 03/18/2023] [Revised: 04/04/2023] [Accepted: 04/06/2023] [Indexed: 05/01/2023]
Abstract
Since the discovery of the human electroencephalogram (EEG), neurophysiology techniques have become indispensable tools in our armamentarium to localize epileptic seizures. New signal analysis techniques and the prospects of artificial intelligence and big data will offer unprecedented opportunities to further advance the field in the near future, ultimately resulting in improved quality of life for many patients with drug-resistant epilepsy. This article summarizes selected presentations from Day 1 of the two-day symposium "Neurophysiology, Neuropsychology, Epilepsy, 2022: Hills We Have Climbed and the Hills Ahead". Day 1 was dedicated to highlighting and honoring the work of Dr. Jean Gotman, a pioneer in EEG, intracranial EEG, simultaneous EEG/ functional magnetic resonance imaging, and signal analysis of epilepsy. The program focused on two main research directions of Dr. Gotman, and was dedicated to "High-frequency oscillations, a new biomarker of epilepsy" and "Probing the epileptic focus from inside and outside". All talks were presented by colleagues and former trainees of Dr. Gotman. The extended summaries provide an overview of historical and current work in the neurophysiology of epilepsy with emphasis on novel EEG biomarkers of epilepsy and source imaging and concluded with an outlook on the future of epilepsy research, and what is needed to bring the field to the next level.
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Affiliation(s)
- B Frauscher
- Analytical Neurophysiology Lab, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada.
| | - C G Bénar
- Aix Marseille Univ, INSERM, INS, Inst Neurosci Syst, Marseille, France
| | - J Jr Engel
- David Geffen School of Medicine at UCLA, Los Angeles, CA, United States
| | - C Grova
- Multimodal Functional Imaging Lab, PERFORM Centre, Department of Physics, Concordia University, Montreal, QC, Canada; Multimodal Functional Imaging Lab, Biomedical Engineering Department, McGill University, QC, Canada; Montreal Neurological Institute and Hospital, Neurology and Neurosurgery Department, McGill University, Montreal, QC, Canada
| | - J Jacobs
- Department of Pediatric and Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - P Kahane
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institute Neurosciences, Department of Neurology, 38000 Grenoble, France
| | - S Wiebe
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - M Zjilmans
- Stichting Epilepsie Instellingen Nederland, The Netherlands; Brain Center, University Medical Center Utrecht, The Netherlands
| | - F Dubeau
- Montreal Neurological Institute and Hospital, Neurology and Neurosurgery Department, McGill University, Montreal, QC, Canada
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8
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Lawson J, LaVancher E, DeAlmeida M, Black BJ. Electrically-evoked oscillating calcium transients in mono- and co-cultures of iPSC glia and sensory neurons. Front Cell Neurosci 2023; 17:1094070. [PMID: 37006467 PMCID: PMC10060658 DOI: 10.3389/fncel.2023.1094070] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 02/17/2023] [Indexed: 03/18/2023] Open
Abstract
Activated glia are known to exhibit either neuroprotective or neurodegenerative effects, depending on their phenotype, while participating in chronic pain regulation. Until recently, it has been believed that satellite glial cells and astrocytes are electrically slight and process stimuli only through intracellular calcium flux that triggers downstream signaling mechanisms. Though glia do not exhibit action potentials, they do express both voltage- and ligand-gated ion channels that facilitate measurable calcium transients, a measure of their own phenotypic excitability, and support and modulate sensory neuron excitability through ion buffering and secretion of excitatory or inhibitory neuropeptides (i.e., paracrine signaling). We recently developed a model of acute and chronic nociception using co-cultures of iPSC sensory neurons (SN) and spinal astrocytes on microelectrode arrays (MEAs). Until recently, only neuronal extracellular activity has been recorded using MEAs with a high signal-to-noise ratio and in a non-invasive manner. Unfortunately, this method has limited compatibility with simultaneous calcium transient imaging techniques, which is the most common method for monitoring the phenotypic activity of astrocytes. Moreover, both dye-based and genetically encoded calcium indicator imaging rely on calcium chelation, affecting the culture’s long-term physiology. Therefore, it would be ideal to allow continuous and simultaneous direct phenotypic monitoring of both SNs and astrocytes in a high-to-moderate throughput non-invasive manner and would significantly advance the field of electrophysiology. Here, we characterize astrocytic oscillating calcium transients (OCa2+Ts) in mono- and co-cultures of iPSC astrocytes as well as iPSC SN-astrocyte co-cultures on 48 well plate MEAs. We demonstrate that astrocytes exhibit OCa2+Ts in an electrical stimulus amplitude- and duration-dependent manner. We show that OCa2+Ts can be pharmacologically inhibited with the gap junction antagonist, carbenoxolone (100 μM). Most importantly, we demonstrate that both neurons and glia can be phenotypically characterized in real time, repeatedly, over the duration of the culture. In total, our findings suggest that calcium transients in glial populations may serve as a stand-alone or supplemental screening technique for identifying potential analgesics or compounds targeting other glia-mediated pathologies.
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Sivaraju A, Hirsch LJ. Do acute EEG findings add to clinical features in predicting outcomes after status epilepticus and acute symptomatic seizures? Epilepsy Behav 2023; 141:109134. [PMID: 36848748 DOI: 10.1016/j.yebeh.2023.109134] [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: 10/14/2022] [Accepted: 02/02/2023] [Indexed: 02/27/2023]
Abstract
Status epilepticus is a potentially life-threatening medical emergency associated with poor functional outcomes. Improving our ability to accurately predict functional outcomes is beneficial to optimizing treatment strategies. Currently, there are four published status epilepticus scores in adults: STESS (Status Epilepticus Severity Score), EMSE (Epidemiology-Based Mortality Score in Status Epilepticus), END-IT (Encephalitis-Nonconvulsive-Diazepam resistance-Imaging-Tracheal intubation), and recently published ACD (Age-level of Consciousness-Duration of status epilepticus) score. The only available scale in the pediatric population is PEDSS (Pediatric CPC scale-EEG (normal vs abnormal)-Drug refractoriness-critical Sickness-Semiology). While these scores are useful research tools, currently there is little evidence to suggest their utility during real-time clinical care. Except for EMSE, none of the scores incorporate EEG findings for prognostication. Adding EEG features improves prognostic accuracy, as has been shown with the EMSE scale with and without the EEG component. Acute symptomatic seizures (AsyS) and early epileptiform abnormalities, especially nonconvulsive seizures, and periodic discharges, markedly increase the risk for subsequent unprovoked seizures. However, many of these patients may not need lifelong anti-seizure medications (ASMs). Continuous EEG monitoring shows that the majority of ASyS are nonconvulsive and can identify epileptic patterns. Dedicated specialty clinics for these patients, known as Post Acute Symptomatic Seizure (PASS) clinics, already exist in the United States. Post Acute Symptomatic Seizure clinics are ideal for both long-term clinical care and answering important research questions related to epileptogenesis, duration of ASM treatment required, and evolution of EEG findings. This topic was presented at the 8th London-Innsbruck Colloquium on Status Epilepticus and Acute Seizures held in September 2022. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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Affiliation(s)
- Adithya Sivaraju
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States.
| | - Lawrence J Hirsch
- Comprehensive Epilepsy Center, Department of Neurology, Yale University, New Haven, CT, United States
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10
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Chloride ion dysregulation in epileptogenic neuronal networks. Neurobiol Dis 2023; 177:106000. [PMID: 36638891 DOI: 10.1016/j.nbd.2023.106000] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/25/2022] [Accepted: 01/09/2023] [Indexed: 01/13/2023] Open
Abstract
GABA is the major inhibitory neurotransmitter in the mature CNS. When GABAA receptors are activated the membrane potential is driven towards hyperpolarization due to chloride entry into the neuron. However, chloride ion dysregulation that alters the ionic gradient can result in depolarizing GABAergic post-synaptic potentials instead. In this review, we highlight that GABAergic inhibition prevents and restrains focal seizures but then reexamine this notion in the context of evidence that a static and/or a dynamic chloride ion dysregulation, that increases intracellular chloride ion concentrations, promotes epileptiform activity and seizures. To reconcile these findings, we hypothesize that epileptogenic pathologically interconnected neuron (PIN) microcircuits, representing a small minority of neurons, exhibit static chloride dysregulation and should exhibit depolarizing inhibitory post-synaptic potentials (IPSPs). We speculate that chloride ion dysregulation and PIN cluster activation may generate fast ripples and epileptiform spikes as well as initiate the hypersynchronous seizure onset pattern and microseizures. Also, we discuss the genetic, molecular, and cellular players important in chloride dysregulation which regulate epileptogenesis and initiate the low-voltage fast seizure onset pattern. We conclude that chloride dysregulation in neuronal networks appears to be critical for epileptogenesis and seizure genesis, but feed-back and feed-forward inhibitory GABAergic neurotransmission plays an important role in preventing and restraining seizures as well.
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11
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Weiss SA, Fried I, Wu C, Sharan A, Rubinstein D, Engel J, Sperling MR, Staba RJ. Graph theoretical measures of fast ripple networks improve the accuracy of post-operative seizure outcome prediction. Sci Rep 2023; 13:367. [PMID: 36611059 PMCID: PMC9825369 DOI: 10.1038/s41598-022-27248-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 12/28/2022] [Indexed: 01/09/2023] Open
Abstract
Fast ripples (FR) are a biomarker of epileptogenic brain, but when larger portions of FR generating regions are resected seizure freedom is not always achieved. To evaluate and improve the diagnostic accuracy of FR resection for predicting seizure freedom we compared the FR resection ratio (RR) with FR network graph theoretical measures. In 23 patients FR were semi-automatically detected and quantified in stereo EEG recordings during sleep. MRI normalization and co-registration localized contacts and relation to resection margins. The number of FR, and graph theoretical measures, which were spatial (i.e., FR rate-distance radius) or temporal correlational (i.e., FR mutual information), were compared with the resection margins and with seizure outcome We found that the FR RR did not correlate with seizure-outcome (p > 0.05). In contrast, the FR rate-distance radius resected difference and the FR MI mean characteristic path length RR did correlate with seizure-outcome (p < 0.05). Retesting of positive FR RR patients using either FR rate-distance radius resected difference or the FR MI mean characteristic path length RR reduced seizure-free misclassifications from 44 to 22% and 17%, respectively. These results indicate that graph theoretical measures of FR networks can improve the diagnostic accuracy of the resection of FR events for predicting seizure freedom.
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Affiliation(s)
- Shennan A. Weiss
- grid.262863.b0000 0001 0693 2202Department of Neurology, State University of New York Downstate, Brooklyn, USA ,grid.262863.b0000 0001 0693 2202Department of Physiology and Pharmacology, State University of New York Downstate, 450 Clarkson Avenue, MSC 1213, Brooklyn, NY 11203 USA ,grid.422616.50000 0004 0443 7226Department of Neurology, New York City Health + Hospitals/Kings County, Brooklyn, NY USA
| | - Itzhak Fried
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, USA
| | - Chengyuan Wu
- grid.265008.90000 0001 2166 5843Department of Neuroradiology, Thomas Jefferson University, Philadelphia, USA ,grid.265008.90000 0001 2166 5843Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA 19107 USA
| | - Ashwini Sharan
- grid.265008.90000 0001 2166 5843Department of Neurosurgery, Thomas Jefferson University, Philadelphia, PA 19107 USA
| | - Daniel Rubinstein
- grid.265008.90000 0001 2166 5843Department of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, USA
| | - Jerome Engel
- grid.19006.3e0000 0000 9632 6718Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, USA ,grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, USA ,grid.19006.3e0000 0000 9632 6718Department of Neurobiology, David Geffen School of Medicine at UCLA, Los Angeles, USA ,grid.19006.3e0000 0000 9632 6718Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, USA ,grid.19006.3e0000 0000 9632 6718David Geffen School of Medicine at UCLA, Brain Research Institute, Los Angeles, CA 90095 USA
| | - Michael R. Sperling
- grid.265008.90000 0001 2166 5843Department of Neurology and Neuroscience, Thomas Jefferson University, Philadelphia, USA
| | - Richard J. Staba
- grid.19006.3e0000 0000 9632 6718Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, USA
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Rauchman SH, Zubair A, Jacob B, Rauchman D, Pinkhasov A, Placantonakis DG, Reiss AB. Traumatic brain injury: Mechanisms, manifestations, and visual sequelae. Front Neurosci 2023; 17:1090672. [PMID: 36908792 PMCID: PMC9995859 DOI: 10.3389/fnins.2023.1090672] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 02/06/2023] [Indexed: 02/25/2023] Open
Abstract
Traumatic brain injury (TBI) results when external physical forces impact the head with sufficient intensity to cause damage to the brain. TBI can be mild, moderate, or severe and may have long-term consequences including visual difficulties, cognitive deficits, headache, pain, sleep disturbances, and post-traumatic epilepsy. Disruption of the normal functioning of the brain leads to a cascade of effects with molecular and anatomical changes, persistent neuronal hyperexcitation, neuroinflammation, and neuronal loss. Destructive processes that occur at the cellular and molecular level lead to inflammation, oxidative stress, calcium dysregulation, and apoptosis. Vascular damage, ischemia and loss of blood brain barrier integrity contribute to destruction of brain tissue. This review focuses on the cellular damage incited during TBI and the frequently life-altering lasting effects of this destruction on vision, cognition, balance, and sleep. The wide range of visual complaints associated with TBI are addressed and repair processes where there is potential for intervention and neuronal preservation are highlighted.
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Affiliation(s)
| | - Aarij Zubair
- NYU Long Island School of Medicine, Mineola, NY, United States
| | - Benna Jacob
- NYU Long Island School of Medicine, Mineola, NY, United States
| | - Danielle Rauchman
- Department of Neuroscience, University of California, Santa Barbara, Santa Barbara, CA, United States
| | - Aaron Pinkhasov
- NYU Long Island School of Medicine, Mineola, NY, United States
| | | | - Allison B Reiss
- NYU Long Island School of Medicine, Mineola, NY, United States
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13
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Zhu F, Wang H, Li L, Bragin A, Cao D, Cheng Y. Intracranial electrophysiological recordings on a swine model of mesial temporal lobe epilepsy. Front Neurol 2023; 14:1077702. [PMID: 37139062 PMCID: PMC10150775 DOI: 10.3389/fneur.2023.1077702] [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: 10/27/2022] [Accepted: 03/20/2023] [Indexed: 05/05/2023] Open
Abstract
Objective To test the feasibility and reliability of intracranial electrophysiological recordings in an acute status epilepticus model on laboratory swine. Method Intrahippocampal injection of kainic acid (KA) was performed on 17 male Bama pigs (Sus scrofa domestica) weighing between 25 and 35 kg. Two stereoelectroencephalography (SEEG) electrodes with a total of 16 channels were implanted bilaterally along the sensorimotor cortex to the hippocampus. Brain electrical activity was recorded 2 h daily for 9-28 days. Three KA dosages were tested to evaluate the quantities capable of evoking status epilepticus. Local field potentials (LFPs) were recorded and compared before and after the KA injection. We quantified the epileptic patterns, including the interictal spikes, seizures, and high-frequency oscillations (HFOs), up to 4 weeks after the KA injection. Test-retest reliability using intraclass correlation coefficients (ICCs) were performed on interictal HFO rates to evaluate the recording stability of this model. Results The KA dosage test suggested that a 10 μl (1.0 μg/μl) intrahippocampal injection could successfully evoke status epilepticus lasting from 4 to 12 h. At this dosage, eight pigs (50% of total) had prolonged epileptic events (tonic-chronic seizures + interictal spikes n = 5, interictal spikes alone n = 3) in the later 4 weeks of the video-SEEG recording period. Four pigs (25% of total) had no epileptic activities, and another four (25%) had lost the cap or did not complete the experiments. Animals that showed epileptiform events were grouped as E + (n = 8) and the four animals showing no signs of epileptic events were grouped as E- (n = 4). A total of 46 electrophysiological seizures were captured in the 4-week post-KA period from 4 E + animals, with the earliest onset on day 9. The seizure durations ranged from 12 to 45 s. A significant increase of hippocampal HFOs rate (num/min) was observed in the E+ group during the post-KA period (weeks 1, 2,4, p < 0.05) compared to the baseline. But the E-showed no change or a decrease (in week 2, p = 0.43) compared to their baseline rate. The between-group comparison showed much higher HFO rates in E + vs. E - (F = 35, p < 0.01). The high ICC value [ICC (1, k) = 0.81, p < 0.05] quantified from the HFO rate suggested that this model had a stable measurement of HFOs during the four-week post-KA periods. Significance This study measured intracranial electrophysiological activity in a swine model of KA-induced mesial temporal lobe epilepsy (mTLE). Using the clinical SEEG electrode, we distinguished abnormal EEG patterns in the swine brain. The high test-retest reliability of HFO rates in the post-KA period suggests the utility of this model for studying mechanisms of epileptogenesis. The use of swine may provide satisfactory translational value for clinical epilepsy research.
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Affiliation(s)
- Fengjun Zhu
- Department of Neurosurgery, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China
- Department of Neurosurgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States
| | - Hanwen Wang
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States
| | - Lin Li
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States
- Department of Biomedical Engineering, University of North Texas, Denton, TX, United States
| | - Anatol Bragin
- Department of Neurology, University of California Los Angeles, Los Angeles, CA, United States
| | - Dezhi Cao
- Department of Neurosurgery, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China
- *Correspondence: Dezhi Cao,
| | - Yuan Cheng
- Department of Neurosurgery, Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Yuan Cheng,
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Low-Cost Platform for Multianimal Chronic Local Field Potential Video Monitoring with Graphical User Interface (GUI) for Seizure Detection and Behavioral Scoring. eNeuro 2022; 9:ENEURO.0283-22.2022. [PMID: 36192155 PMCID: PMC9581574 DOI: 10.1523/eneuro.0283-22.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/23/2022] [Accepted: 09/28/2022] [Indexed: 12/15/2022] Open
Abstract
Experiments employing chronic monitoring of neurophysiological signals and video are commonly used in studies of epilepsy to characterize behavioral correlates of seizures. Our objective was to design a low-cost platform that enables chronic monitoring of several animals simultaneously, synchronizes bilateral local field potential (LFP) and video streams in real time, and parses recorded data into manageable file sizes. We present a hardware solution leveraging Intan and Open Ephys acquisition systems and a software solution implemented in Bonsai. The platform was tested in 48-h continuous recordings simultaneously from multiple mice (male and female) with chronic epilepsy. To enable seizure detection and scoring, we developed a graphical user interface (GUI) that reads the data produced by our workflow and allows a user with no coding expertise to analyze events. Our Bonsai workflow was designed to maximize flexibility for a wide variety of experimental applications, and our use of the Open Ephys acquisition board would allow for scaling recordings up to 128 channels per animal.
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15
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Zhou Y, You J, Kumar U, Weiss SA, Bragin A, Engel J, Papadelis C, Li L. An approach for reliably identifying high-frequency oscillations and reducing false-positive detections. Epilepsia Open 2022; 7:674-686. [PMID: 36053171 PMCID: PMC9712470 DOI: 10.1002/epi4.12647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 08/31/2022] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE Aiming to improve the feasibility and reliability of using high-frequency oscillations (HFOs) for translational studies of epilepsy, we present a pipeline with features specifically designed to reject false positives for HFOs to improve the automatic HFO detector. METHODS We presented an integrated, multi-layered procedure capable of automatically rejecting HFOs from a variety of common false positives, such as motion, background signals, and sharp transients. This method utilizes a time-frequency contour approach that embeds three different layers including peak constraints, power thresholds, and morphological identification to discard false positives. Four experts were involved in rating detected HFO events that were randomly selected from different posttraumatic epilepsy (PTE) animals for a comprehensive evaluation. RESULTS The algorithm was run on 768-h recordings of intracranial electrodes in 48 PTE animals. A total of 453 917 HFOs were identified by initial HFO detection, of which 450 917 were implemented for HFO refinement and 203 531 events were retained. Random sampling was used to evaluate the performance of the detector. The HFO detection yielded an overall accuracy of 0.95 ± 0.03 , with precision, recall, and F1 scores of 0.92 ± 0.05 , 0.99 ± 0.01 , and 0.94 ± 0.03 , respectively. For the HFO classification, our algorithm obtained an accuracy of 0.97 ± 0.02 . For the inter-rater reliability of algorithm evaluation, the agreement among four experts was 0.94 ± 0.03 for HFO detection and 0.85 ± 0.04 for HFO classification. SIGNIFICANCE Our approach shows that a segregated pipeline design with a focus on false-positive rejection can improve the detection efficiency and provide reliable results. This pipeline does not require customization and uses fixed parameters, making it highly feasible and translatable for basic and clinical applications of epilepsy.
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Affiliation(s)
- Yufeng Zhou
- Department of Biomedical EngineeringUniversity of North TexasTexasUSA
| | - Jing You
- Department of Biomedical EngineeringUniversity of North TexasTexasUSA
| | - Udaya Kumar
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Shennan A Weiss
- Departments of Neurology, Department of Physiology and PharmacologyState University of New York DownstateBrooklynNew YorkUSA,Department of NeurologyNew York City Health + Hospitals/Kings CountyBrooklynNew YorkUSA
| | - Anatol Bragin
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA,Brain Research InstituteUniversity of CaliforniaLos AngelesCaliforniaUSA
| | - Jerome Engel
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA,Brain Research InstituteUniversity of CaliforniaLos AngelesCaliforniaUSA,Department of NeurobiologyDavid Geffen School of Medicine at UCLALos AngelesCaliforniaUSA,Department of Psychiatry and Biobehavioral SciencesDavid Geffen School of Medicine at UCLACaliforniaUSA
| | - Christos Papadelis
- Jane and John Justin Neurosciences CenterCook Children's Health Care SystemFort WorthTexasUSA,School of MedicineTexas Christian UniversityFort WorthTexasUSA,Department of BioengineeringUniversity of Texas at ArlingtonArlingtonTexasUSA
| | - Lin Li
- Department of Biomedical EngineeringUniversity of North TexasTexasUSA,Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA
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