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Jung T, Zeng N, Fabbri JD, Eichler G, Li Z, Zabeh E, Das A, Willeke K, Wingel KE, Dubey A, Huq R, Sharma M, Hu Y, Ramakrishnan G, Tien K, Mantovani P, Parihar A, Yin H, Oswalt D, Misdorp A, Uguz I, Shinn T, Rodriguez GJ, Nealley C, Sanborn S, Gonzales I, Roukes M, Knecht J, Yoshor D, Canoll P, Spinazzi E, Carloni LP, Pesaran B, Patel S, Jacobs J, Youngerman B, Cotton RJ, Tolias A, Shepard KL. Stable, chronic in-vivo recordings from a fully wireless subdural-contained 65,536-electrode brain-computer interface device. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.05.17.594333. [PMID: 38798494 PMCID: PMC11118429 DOI: 10.1101/2024.05.17.594333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Minimally invasive, high-bandwidth brain-computer-interface (BCI) devices can revolutionize human applications. With orders-of-magnitude improvements in volumetric efficiency over other BCI technologies, we developed a 50-μm-thick, mechanically flexible micro-electrocorticography (μECoG) BCI, integrating a 256×256 array of electrodes, signal processing, data telemetry, and wireless powering on a single complementary metal-oxide-semiconductor (CMOS) substrate containing 65,536 recording channels, from which we can simultaneously record a selectable subset of up to 1024 channels at a given time. Fully implanted below the dura, our chip is wirelessly powered, communicating bi-directionally with an external relay station outside the body. We demonstrated chronic, reliable recordings for up to two weeks in pigs and up to two months in behaving non-human primates from somatosensory, motor, and visual cortices, decoding brain signals at high spatiotemporal resolution.
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Affiliation(s)
- Taesung Jung
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Nanyu Zeng
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Jason D. Fabbri
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Guy Eichler
- Department of Computer Science, Columbia University; New York, NY 10027, USA
| | - Zhe Li
- Department of Ophthalmology, Byers Eye Institute, Stanford University; Stanford, CA 94305, USA
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
| | - Erfan Zabeh
- Department of Biomedical Engineering, Columbia University; New York, NY 10027, USA
| | - Anup Das
- Department of Biomedical Engineering, Columbia University; New York, NY 10027, USA
| | - Konstantin Willeke
- Department of Ophthalmology, Byers Eye Institute, Stanford University; Stanford, CA 94305, USA
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
- Institute of Computer Science and Campus Institute Data Science, University of Göttingen; Germany
| | - Katie E. Wingel
- Center for Neural Science, New York University; New York, NY 10003, USA
- Department of Neurosurgery, University of Pennsylvania; Philadelphia PA 19118, USA
| | - Agrita Dubey
- Center for Neural Science, New York University; New York, NY 10003, USA
- Department of Neurosurgery, University of Pennsylvania; Philadelphia PA 19118, USA
| | - Rizwan Huq
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Mohit Sharma
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Yaoxing Hu
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Girish Ramakrishnan
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Kevin Tien
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Paolo Mantovani
- Department of Computer Science, Columbia University; New York, NY 10027, USA
| | - Abhinav Parihar
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Heyu Yin
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Denise Oswalt
- Department of Neurosurgery, University of Pennsylvania; Philadelphia PA 19118, USA
- Department of Neuroscience, University of Pennsylvania; Philadelphia, PA 19118, USA
- Department of Bioengineering, University of Pennsylvania; Philadelphia, PA 19118, USA
| | - Alexander Misdorp
- Department of Computer Science, Columbia University; New York, NY 10027, USA
| | - Ilke Uguz
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
| | - Tori Shinn
- Department of Bioengineering, University of Pennsylvania; Philadelphia, PA 19118, USA
| | - Gabrielle J. Rodriguez
- Department of Ophthalmology, Byers Eye Institute, Stanford University; Stanford, CA 94305, USA
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
| | - Cate Nealley
- Department of Ophthalmology, Byers Eye Institute, Stanford University; Stanford, CA 94305, USA
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
| | - Sophia Sanborn
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
| | - Ian Gonzales
- Department of Neurological Surgery, Columbia University; New York, NY 10032, USA
| | - Michael Roukes
- Departments of Physics, Applied Physics, and Bioengineering, Caltech; Pasadena, CA 91125, USA
| | - Jeffrey Knecht
- Lincoln Laboratory, Massachusetts Institute of Technology; Lexington, MA 02421, USA
| | - Daniel Yoshor
- Department of Neurosurgery, University of Pennsylvania; Philadelphia PA 19118, USA
| | - Peter Canoll
- Department of Pathology and Cell Biology, Columbia University; New York, NY 10032, USA
| | - Eleonora Spinazzi
- Department of Neurological Surgery, Columbia University; New York, NY 10032, USA
| | - Luca P. Carloni
- Department of Computer Science, Columbia University; New York, NY 10027, USA
| | - Bijan Pesaran
- Center for Neural Science, New York University; New York, NY 10003, USA
- Department of Neurosurgery, University of Pennsylvania; Philadelphia PA 19118, USA
- Department of Neuroscience, University of Pennsylvania; Philadelphia, PA 19118, USA
- Department of Bioengineering, University of Pennsylvania; Philadelphia, PA 19118, USA
| | - Saumil Patel
- Department of Ophthalmology, Byers Eye Institute, Stanford University; Stanford, CA 94305, USA
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
| | - Joshua Jacobs
- Department of Biomedical Engineering, Columbia University; New York, NY 10027, USA
- Department of Neurological Surgery, Columbia University; New York, NY 10032, USA
| | - Brett Youngerman
- Department of Neurological Surgery, Columbia University; New York, NY 10032, USA
| | - R. James Cotton
- Shirley Ryan Ability Labs; Chicago, IL, USA
- Department of Physical Medicine and Rehabilitation, Northwestern University; Chicago, IL, USA
| | - Andreas Tolias
- Department of Ophthalmology, Byers Eye Institute, Stanford University; Stanford, CA 94305, USA
- Stanford Bio-X, Stanford University, Stanford University; Stanford, CA 94304, USA
- Wu Tsai Neurosciences Institute, Stanford University; Stanford, CA 94304, USA
- Center for Neuroscience and Artificial Intelligence, Department of Neuroscience, Baylor College of Medicine; Houston, TX 77030, USA
- Department of Electrical Engineering, Stanford University; Stanford, CA 94304, USA
| | - Kenneth L. Shepard
- Department of Electrical Engineering, Columbia University; New York, NY 10027, USA
- Department of Biomedical Engineering, Columbia University; New York, NY 10027, USA
- Department of Neurological Surgery, Columbia University; New York, NY 10032, USA
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Nguyen T, Ivanisevic M, Giles A, Kurukumbi M. A Dilemma: Electrographic Seizure Activity in the Absence of Clinically Perceptible Seizures and the Ethical Challenges of Medical Decision-Making. Cureus 2025; 17:e80331. [PMID: 40206934 PMCID: PMC11980009 DOI: 10.7759/cureus.80331] [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] [Accepted: 03/10/2025] [Indexed: 04/11/2025] Open
Abstract
A 37-year-old male with refractory left temporal epilepsy was admitted to the epilepsy monitoring unit to examine correlates of observable clinical seizure activity, those captured by responsive neurostimulation system (RNS) and continuous video electroencephalogram (cvEEG). The patient was diagnosed at age three, was on three anti-epileptic drugs, with an RNS implant since 2020 and was admitted to the epilepsy monitoring unit. The patient reported no seizures since 2019. cvEEG and RNS data were collected, and a comprehensive neuropsychological evaluation was conducted. cvEEG revealed brief electrographic activity originating from the left and right anterior temporal regions, occurring mainly on the left side. The activity was characterized ictally by prominent anterior temporal sharp waves, with a left-sided predominance. RNS data showed similar results but recorded electrographic activity in excess of cvEEG. Although clinical and electrographic manifestations tend to be stereotyped for seizures, there were no behavioral observations of clinical seizures during these recorded electrographic seizures on RNS data. The patient also reported no seizures. Neuropsychological results showed impairment across multiple cognitive domains. This case report highlights the need for a more detailed approach to determining allowable electrographic activity since these thresholds directly impact restrictions on patients with epilepsy. Highly sensitive measurement tools may better detect seizures, but in isolation, they cannot fully convey a complete picture of the patient's status without other data and clinical indicators. Data from emerging technology must be weighed in conjunction with clinical symptoms to optimize patient safety, quality of life, and outcomes.
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Affiliation(s)
- Thi Nguyen
- Neurology, University of Virginia School of Medicine, Charlottesville, USA
| | | | - Anne Giles
- Inova Neuroscience Institute, Inova Health System, Falls Church, USA
| | - Mohan Kurukumbi
- Inova Neuroscience Institute, Inova Health System, Falls Church, USA
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Shan B, Dai Y, Liu Q, Hou C, Wang Y, Wei P, Zhao G. Advances in the Treatment of Epilepsy by Electrostimulation of the Pulvinar. J Integr Neurosci 2025; 24:22572. [PMID: 40018771 DOI: 10.31083/jin22572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 07/20/2024] [Accepted: 08/20/2024] [Indexed: 03/01/2025] Open
Abstract
Neuroregulatory therapy, encompassing deep brain stimulation and responsive neurostimulation, is increasingly gaining attention for the treatment of drug-resistant temporal and occipital lobe epilepsy. Beyond the approved anterior nucleus of the thalamus, the pulvinar nucleus of the thalamus is a potential stimulation target. Through a confluence of animal studies, electrophysiological research, and imaging studies, the pulvinar has been identified as having extensive connections with the visual cortex, prefrontal cortex, limbic regions, and multimodal sensory associative areas, playing a pivotal role in multisensory integration and serving as a propagation node in both generalized and focal epilepsy. This review synthesizes recent research on the pulvinar in relation to cortical and epileptic networks, as well as the efficacy of neuroregulatory therapy targeting the pulvinar in the treatment of temporal and occipital lobe epilepsy. Further research is warranted to elucidate the differential therapeutic effects of stimulating various subregions of the pulvinar and the specific mechanisms underlying the treatment of epilepsy through pulvinar stimulation.
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Affiliation(s)
- Bingyang Shan
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
| | - Yang Dai
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
| | - Quanlei Liu
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
| | - Changkai Hou
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
| | - Yihe Wang
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
| | - Penghu Wei
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
| | - Guoguang Zhao
- Department of Neurosurgery, Xuanwu Hospital Capital Medical University, 100053 Beijing, China
- Clinical Research Center for Epilepsy Capital Medical University, 100053 Beijing, China
- Beijing Municipal Geriatric Medical Research Center, 100053 Beijing, China
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OLeary G, Koerner J, Kanchwala M, Filho JS, Xu J, Valiante TA, Genov R. BrainForest: Neuromorphic Multiplier-Less Bit-Serial Weight-Memory-Optimized 1024-Tree Brain-State Classification Processor. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2025; 19:55-67. [PMID: 39412966 DOI: 10.1109/tbcas.2024.3481160] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2024]
Abstract
Personalized brain implants have the potential to revolutionize the treatment of neurological disorders and augment cognition. Medical implants that deliver therapeutic stimulation in response to detected seizures have already been deployed for the treatment of epilepsy. These devices require low-power integrated circuits for life-long operation. This constraint impedes the integration of machine-learning driven classifiers that could improve treatment outcomes. This paper introduces BrainForest, a neuromorphic multiplier-less bit-serial weight-memory-optimized brain-state classification processor. The architecture achieves state-of-the-art energy efficiency using two layers of neuron models to implement the spectral and temporal functions needed for classification: 1) resonate-and-fire neurons are used to extract physiological signal band energy EEG biomarkers 2) leaky integrator neurons are used to build multi-timescale representations for classification. Sparse neural model firing activity is used to clock-gate device logic, thereby decreasing power consumption by 93%. An energy-optimized 1024-tree boosted decision forest performs the classification used to trigger stimulation in response to detected pathological brain states. The IC is implemented in 65nm CMOS with state-of-the-art power consumption (best case: 9.6µW, typical: 118µW), achieving a seizure sensitivity of 97.5% with a false detection rate of 2.08 per hour.
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Mushtaq O, Grezenko H, Rehman A, Sher H, Sher Z, Anyang Kaakyire D, Hanifullah S, Dabas M, Saleh G, Shehryar A, Khan I. Role of Responsive Neurostimulation in Managing Drug-Resistant Epilepsy: A Systematic Review of Clinical Outcomes. Cureus 2024; 16:e68032. [PMID: 39347167 PMCID: PMC11431993 DOI: 10.7759/cureus.68032] [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] [Accepted: 08/28/2024] [Indexed: 10/01/2024] Open
Abstract
Drug-resistant epilepsy remains a substantial challenge in neurology, affecting patients who do not respond to conventional antiepileptic drugs. Responsive neurostimulation (RNS) has emerged as a promising therapeutic approach, yet comprehensive reviews synthesizing its clinical outcomes are sparse. This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and involved a comprehensive database search through PubMed, Medline, Embase, the Cochrane Library, and Scopus, covering literature up to April 2024. The review targeted peer-reviewed articles evaluating the efficacy, safety, and quality of life impacts of RNS in patients with drug-resistant epilepsy. Key inclusion criteria encompassed clinical trials, cohort studies, and meta-analyses, while exclusion criteria included non-peer-reviewed and irrelevant studies. We identified five studies meeting our inclusion criteria. These studies collectively demonstrated that RNS significantly reduces seizure frequency and improves quality of life, while maintaining a favorable safety profile. Despite small sample sizes and potential selection biases, the benefits of RNS appeared consistent across diverse patient demographics. RNS represents a viable and effective treatment option for drug-resistant epilepsy, offering significant improvements in seizure control and patient quality of life. Future research should focus on long-term outcomes and refining patient selection to optimize the therapeutic benefits of RNS. The integration of RNS into standard epilepsy management protocols is recommended based on current evidence.
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Affiliation(s)
- Omid Mushtaq
- Diagnostic and Interventional Radiology, Sakarya University Faculty of Medicine, Sakarya, TUR
| | - Han Grezenko
- Medicine and Surgery, Guangxi Medical University, Nanning, CHN
- Translational Neuroscience, Barrow Neurological Institute, Phoenix, USA
| | | | - Hamza Sher
- Internal Medicine, Islamic International Medical College, Rawalpindi, PAK
| | - Zarrar Sher
- Internal Medicine, Tehsil Headquarter Hospital (THQ) Hospital Kotli Sattian, Rawalpindi, PAK
| | | | | | | | - Ghaida Saleh
- Internal Medicine, University of Khartoum, Khartoum, SDN
| | | | - Isa Khan
- Internal Medicine, Nishtar Medical University, Multan, PAK
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Reed EA, June Smith R, Kang JY, Sarma SV. Patient-Specific Electrical Stimulation to Effectively Suppress Seizures using a Data-Driven Dynamical Network Model. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2024; 2024:1-5. [PMID: 40039313 DOI: 10.1109/embc53108.2024.10782540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2025]
Abstract
Seizure suppression is critical for enhancing the quality of life for patients with epilepsy. However, nearly 15 million patients have medically refractory epilepsy, meaning their seizures cannot be suppressed with medication. Electrical stimulation therapy is an alternative therapy to suppress seizures. However, determining where and how to stimulate remains an open problem. Currently, physicians rely on trial-and-error, which is inefficient. In this work, we present a data-driven patient-specific method that identifies the best location to stimulate and designs the stimulation signal to suppress seizures by leveraging the patient's cortico-cortical evoked potentials (CCEPs). Specifically, we construct transfer function models from the CCEPs recordings and plot the magnitude response versus frequency. From this bode plot, we obtain the frequency that minimizes the magnitude response in the seizure onset zone (SOZ) channels. In silico, we demonstrate that our method suppresses signals in the clinically annotated SOZ by up to 81%. Our method lays the groundwork for neurostimulation to be an effective treatment for medically refractory epilepsy. Future work will focus on prospectively validating this method in the clinic.
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Hong R, Zheng T, Marra V, Yang D, Liu JK. Multi-scale modelling of the epileptic brain: advantages of computational therapy exploration. J Neural Eng 2024; 21:021002. [PMID: 38621378 DOI: 10.1088/1741-2552/ad3eb4] [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: 08/29/2023] [Accepted: 04/15/2024] [Indexed: 04/17/2024]
Abstract
Objective: Epilepsy is a complex disease spanning across multiple scales, from ion channels in neurons to neuronal circuits across the entire brain. Over the past decades, computational models have been used to describe the pathophysiological activity of the epileptic brain from different aspects. Traditionally, each computational model can aid in optimizing therapeutic interventions, therefore, providing a particular view to design strategies for treating epilepsy. As a result, most studies are concerned with generating specific models of the epileptic brain that can help us understand the certain machinery of the pathological state. Those specific models vary in complexity and biological accuracy, with system-level models often lacking biological details.Approach: Here, we review various types of computational model of epilepsy and discuss their potential for different therapeutic approaches and scenarios, including drug discovery, surgical strategies, brain stimulation, and seizure prediction. We propose that we need to consider an integrated approach with a unified modelling framework across multiple scales to understand the epileptic brain. Our proposal is based on the recent increase in computational power, which has opened up the possibility of unifying those specific epileptic models into simulations with an unprecedented level of detail.Main results: A multi-scale epilepsy model can bridge the gap between biologically detailed models, used to address molecular and cellular questions, and brain-wide models based on abstract models which can account for complex neurological and behavioural observations.Significance: With these efforts, we move toward the next generation of epileptic brain models capable of connecting cellular features, such as ion channel properties, with standard clinical measures such as seizure severity.
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Affiliation(s)
- Rongqi Hong
- School of Computer Science, Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
| | - Tingting Zheng
- School of Computer Science, Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
| | | | - Dongping Yang
- Research Centre for Frontier Fundamental Studies, Zhejiang Lab, Hangzhou, People's Republic of China
| | - Jian K Liu
- School of Computer Science, Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
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Richie J, Letner JG, Mclane-Svoboda A, Huan Y, Ghaffari DH, Valle ED, Patel PR, Chiel HJ, Pelled G, Weiland JD, Chestek CA. Fabrication and Validation of Sub-Cellular Carbon Fiber Electrodes. IEEE Trans Neural Syst Rehabil Eng 2024; 32:739-749. [PMID: 38294928 PMCID: PMC10919889 DOI: 10.1109/tnsre.2024.3360866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Abstract
Multielectrode arrays for interfacing with neurons are of great interest for a wide range of medical applications. However, current electrodes cause damage over time. Ultra small carbon fibers help to address issues but controlling the electrode site geometry is difficult. Here we propose a methodology to create small, pointed fiber electrodes (SPFe). We compare the SPFe to previously made blowtorched fibers in characterization. The SPFe result in small site sizes [Formula: see text] with consistently sharp points (20.8 ± 7.64°). Additionally, these electrodes were able to record and/or stimulate neurons multiple animal models including rat cortex, mouse retina, Aplysia ganglia and octopus axial cord. In rat cortex, these electrodes recorded significantly higher peak amplitudes than the traditional blowtorched fibers. These SPFe may be applicable to a wide range of applications requiring a highly specific interface with individual neurons.
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Paterno R, Vu T, Hsieh C, Baraban SC. Host brain environmental influences on transplanted medial ganglionic eminence progenitors. Sci Rep 2024; 14:3610. [PMID: 38351191 PMCID: PMC10864292 DOI: 10.1038/s41598-024-52478-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Accepted: 01/19/2024] [Indexed: 02/16/2024] Open
Abstract
Interneuron progenitor transplantation can ameliorate disease symptoms in a variety of neurological disorders. The strategy is based on transplantation of embryonic medial ganglionic eminence (MGE) progenitors. Elucidating how host brain environment influences the integration of interneuron progenitors is critical for optimizing this strategy across different disease states. Here, we systematically evaluated the influence of age and brain region on survival, migration, and differentiation of transplant-derived cells. We find that early postnatal MGE transplantation yields superior survival and more extensive migratory capabilities compared to transplantation during the juvenile or adult stages. MGE progenitors migrate more widely in the cortex compared to the hippocampus. Maturation to interneuron subtypes is regulated by age and brain region. MGE progenitors transplanted into the dentate gyrus sub-region of the early postnatal hippocampus can differentiate into astrocytes. Our results suggest that the host brain environment critically regulates survival, spatial distribution, and maturation of MGE-derived interneurons following transplantation. These findings inform and enable optimal conditions for interneuron transplant therapies.
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Affiliation(s)
- Rosalia Paterno
- Department of Neurological Surgery and Weill Institute of Neuroscience, University of California, 513 Parnassus Ave, Health Science East, E840, San Francisco, CA, 94143, USA.
| | - Thy Vu
- Department of Neurological Surgery and Weill Institute of Neuroscience, University of California, 513 Parnassus Ave, Health Science East, E840, San Francisco, CA, 94143, USA
| | - Caroline Hsieh
- Department of Neurological Surgery and Weill Institute of Neuroscience, University of California, 513 Parnassus Ave, Health Science East, E840, San Francisco, CA, 94143, USA
| | - Scott C Baraban
- Department of Neurological Surgery and Weill Institute of Neuroscience, University of California, 513 Parnassus Ave, Health Science East, E840, San Francisco, CA, 94143, USA
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Katlowitz KA, Curry DJ, Weiner HL. Novel Surgical Approaches in Childhood Epilepsy: Laser, Brain Stimulation, and Focused Ultrasound. Adv Tech Stand Neurosurg 2024; 49:291-306. [PMID: 38700689 DOI: 10.1007/978-3-031-42398-7_13] [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] [Indexed: 06/01/2024]
Abstract
Pediatric epilepsy has a worldwide prevalence of approximately 1% (Berg et al., Handb Clin Neurol 111:391-398, 2013) and is associated with not only lower quality of life but also long-term deficits in executive function, significant psychosocial stressors, poor cognitive outcomes, and developmental delays (Schraegle and Titus, Epilepsy Behav 62:20-26, 2016; Puka and Smith, Epilepsia 56:873-881, 2015). With approximately one-third of patients resistant to medical control, surgical intervention can offer a cure or palliation to decrease the disease burden and improve neurological development. Despite its potential, epilepsy surgery is drastically underutilized. Even today only 1% of the millions of epilepsy patients are referred annually for neurosurgical evaluation, and the average delay between diagnosis of Drug Resistant Epilepsy (DRE) and surgical intervention is approximately 20 years in adults and 5 years in children (Solli et al., Epilepsia 61:1352-1364, 2020). It is still estimated that only one-third of surgical candidates undergo operative intervention (Pestana Knight et al., Epilepsia 56:375, 2015). In contrast to the stable to declining rates of adult epilepsy surgery (Englot et al., Neurology 78:1200-1206, 2012; Neligan et al., Epilepsia 54:e62-e65, 2013), rates of pediatric surgery are rising (Pestana Knight et al., Epilepsia 56:375, 2015). Innovations in surgical approaches to epilepsy not only minimize potential complications but also expand the definition of a surgical candidate. In this chapter, three alternatives to classical resection are presented. First, laser ablation provides a minimally invasive approach to focal lesions. Next, both central and peripheral nervous system stimulation can interrupt seizure networks without creating permanent lesions. Lastly, focused ultrasound is discussed as a potential new avenue not only for ablation but also modulation of small, deep foci within seizure networks. A better understanding of the potential surgical options can guide patients and providers to explore all treatment avenues.
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Affiliation(s)
- Kalman A Katlowitz
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
- Department of Neurosurgery, Texas Children's Hospital, Houston, TX, USA
| | - Daniel J Curry
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
- Department of Neurosurgery, Texas Children's Hospital, Houston, TX, USA
| | - Howard L Weiner
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.
- Department of Neurosurgery, Texas Children's Hospital, Houston, TX, USA.
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Cornelssen C, Finlinson E, Rolston JD, Wilcox KS. Ultrasonic therapies for seizures and drug-resistant epilepsy. Front Neurol 2023; 14:1301956. [PMID: 38162441 PMCID: PMC10756913 DOI: 10.3389/fneur.2023.1301956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/09/2023] [Indexed: 01/03/2024] Open
Abstract
Ultrasonic therapy is an increasingly promising approach for the treatment of seizures and drug-resistant epilepsy (DRE). Therapeutic focused ultrasound (FUS) uses thermal or nonthermal energy to either ablate neural tissue or modulate neural activity through high- or low-intensity FUS (HIFU, LIFU), respectively. Both HIFU and LIFU approaches have been investigated for reducing seizure activity in DRE, and additional FUS applications include disrupting the blood-brain barrier in the presence of microbubbles for targeted-drug delivery to the seizure foci. Here, we review the preclinical and clinical studies that have used FUS to treat seizures. Additionally, we review effective FUS parameters and consider limitations and future directions of FUS with respect to the treatment of DRE. While detailed studies to optimize FUS applications are ongoing, FUS has established itself as a potential noninvasive alternative for the treatment of DRE and other neurological disorders.
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Affiliation(s)
- Carena Cornelssen
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, United States
| | - Eli Finlinson
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, United States
| | - John D. Rolston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Neurosurgery, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, United States
| | - Karen S. Wilcox
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, United States
- Department of Pharmacology and Toxicology, University of Utah, Salt Lake City, UT, United States
- Interdepartmental Program in Neuroscience, University of Utah, Salt Lake City, UT, United States
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Bernabei JM, Li A, Revell AY, Smith RJ, Gunnarsdottir KM, Ong IZ, Davis KA, Sinha N, Sarma S, Litt B. Quantitative approaches to guide epilepsy surgery from intracranial EEG. Brain 2023; 146:2248-2258. [PMID: 36623936 PMCID: PMC10232272 DOI: 10.1093/brain/awad007] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 12/11/2022] [Accepted: 12/28/2022] [Indexed: 01/11/2023] Open
Abstract
Over the past 10 years, the drive to improve outcomes from epilepsy surgery has stimulated widespread interest in methods to quantitatively guide epilepsy surgery from intracranial EEG (iEEG). Many patients fail to achieve seizure freedom, in part due to the challenges in subjective iEEG interpretation. To address this clinical need, quantitative iEEG analytics have been developed using a variety of approaches, spanning studies of seizures, interictal periods, and their transitions, and encompass a range of techniques including electrographic signal analysis, dynamical systems modeling, machine learning and graph theory. Unfortunately, many methods fail to generalize to new data and are sensitive to differences in pathology and electrode placement. Here, we critically review selected literature on computational methods of identifying the epileptogenic zone from iEEG. We highlight shared methodological challenges common to many studies in this field and propose ways that they can be addressed. One fundamental common pitfall is a lack of open-source, high-quality data, which we specifically address by sharing a centralized high-quality, well-annotated, multicentre dataset consisting of >100 patients to support larger and more rigorous studies. Ultimately, we provide a road map to help these tools reach clinical trials and hope to improve the lives of future patients.
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Affiliation(s)
- John M Bernabei
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Li
- Department of Computer Science, Columbia University, New York, NY 10027, USA
| | - Andrew Y Revell
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Rachel J Smith
- Department of Electrical and Computer Engineering, University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Neuroengineering Program, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Kristin M Gunnarsdottir
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Ian Z Ong
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kathryn A Davis
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nishant Sinha
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sridevi Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Brian Litt
- Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering & Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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Rogowski B, Miller A, Saway BF, Wessell J, Rowland NC, Lena JR, Vandergrift WA. Vasospasm secondary to responsive neurostimulator placement: a previously unreported complication. Illustrative case. JOURNAL OF NEUROSURGERY. CASE LESSONS 2023; 5:CASE22435. [PMID: 37249138 PMCID: PMC10550669 DOI: 10.3171/case22435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 03/28/2023] [Indexed: 05/31/2023]
Abstract
BACKGROUND The Responsive Neurostimulation (RNS) system is an implantable device for patients with drug-resistant epilepsy who are not candidates for resection of a seizure focus. As a relatively new therapeutic, the full spectrum of adverse effects has yet to be determined. A literature review revealed no previous reports of cerebral vasospasm following RNS implantation. OBSERVATIONS A 35-year-old man developed severe angiographic and clinical vasospasm following bilateral mesial temporal lobe RNS implantation. He initially presented with concerns for status epilepticus 8 days after implantation. On hospital day 3, a decline in his clinical examination prompted imaging studies that revealed a left middle cerebral artery (MCA) stroke with angiographic evidence of severe vasospasm of the left internal carotid artery (ICA), MCA, anterior cerebral artery (ACA), and right ICA and ACA. Despite improvements in angiographic vasospasm after appropriate treatment, a thrombus developed in the posterior M2 branch, requiring mechanical thrombectomy. Ultimately, the patient was stabilized and discharged to a rehabilitation facility with residual cognitive and motor deficits. LESSONS Cerebral vasospasm as a cause of ischemic stroke after uneventful RNS implantation is exceedingly rare, yet demands particular attention given the potential for severe consequences and the growing number of patients receiving RNS devices.
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Affiliation(s)
- Brandon Rogowski
- College of Medicine, Drexel University, Philadelphia, Pennsylvania
| | - Aaron Miller
- College of Osteopathic Medicine, New York Institute of Technology, Glen Head, New York
| | - Brian F. Saway
- Department of Neurosurgery, Medical University of South Carolina, Charleston, South Carolina; and
| | - Jeffrey Wessell
- Department of Neurosurgery, Medical University of South Carolina, Charleston, South Carolina; and
| | - Nathan C. Rowland
- Department of Neurosurgery, Medical University of South Carolina, Charleston, South Carolina; and
- College of Medicine, Medical University of South Carolina, Charleston, South Carolina
| | - Jonathan Ross Lena
- Department of Neurosurgery, Medical University of South Carolina, Charleston, South Carolina; and
- College of Medicine, Medical University of South Carolina, Charleston, South Carolina
| | - William A. Vandergrift
- Department of Neurosurgery, Medical University of South Carolina, Charleston, South Carolina; and
- College of Medicine, Medical University of South Carolina, Charleston, South Carolina
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14
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Cornblath EJ, Lucas A, Armstrong C, Greenblatt AS, Stein JM, Hadar PN, Raghupathi R, Marsh E, Litt B, Davis KA, Conrad EC. Quantifying trial-by-trial variability during cortico-cortical evoked potential mapping of epileptogenic tissue. Epilepsia 2023; 64:1021-1034. [PMID: 36728906 PMCID: PMC10480141 DOI: 10.1111/epi.17528] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2022] [Revised: 01/31/2023] [Accepted: 02/01/2023] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Measuring cortico-cortical evoked potentials (CCEPs) is a promising tool for mapping epileptic networks, but it is not known how variability in brain state and stimulation technique might impact the use of CCEPs for epilepsy localization. We test the hypotheses that (1) CCEPs demonstrate systematic variability across trials and (2) CCEP amplitudes depend on the timing of stimulation with respect to endogenous, low-frequency oscillations. METHODS We studied 11 patients who underwent CCEP mapping after stereo-electroencephalography electrode implantation for surgical evaluation of drug-resistant epilepsy. Evoked potentials were measured from all electrodes after each pulse of a 30 s, 1 Hz bipolar stimulation train. We quantified monotonic trends, phase dependence, and standard deviation (SD) of N1 (15-50 ms post-stimulation) and N2 (50-300 ms post-stimulation) amplitudes across the 30 stimulation trials for each patient. We used linear regression to quantify the relationship between measures of CCEP variability and the clinical seizure-onset zone (SOZ) or interictal spike rates. RESULTS We found that N1 and N2 waveforms exhibited both positive and negative monotonic trends in amplitude across trials. SOZ electrodes and electrodes with high interictal spike rates had lower N1 and N2 amplitudes with higher SD across trials. Monotonic trends of N1 and N2 amplitude were more positive when stimulating from an area with higher interictal spike rate. We also found intermittent synchronization of trial-level N1 amplitude with low-frequency phase in the hippocampus, which did not localize the SOZ. SIGNIFICANCE These findings suggest that standard approaches for CCEP mapping, which involve computing a trial-averaged response over a .2-1 Hz stimulation train, may be masking inter-trial variability that localizes to epileptogenic tissue. We also found that CCEP N1 amplitudes synchronize with ongoing low-frequency oscillations in the hippocampus. Further targeted experiments are needed to determine whether phase-locked stimulation could have a role in localizing epileptogenic tissue.
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Affiliation(s)
- Eli J. Cornblath
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Alfredo Lucas
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Bioengineering, School of Engineering & Applied Science, Philadelphia, Pennsylvania, USA
| | - Caren Armstrong
- Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Adam S. Greenblatt
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Joel M. Stein
- Department of Radiology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Peter N. Hadar
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ramya Raghupathi
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Eric Marsh
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Pediatric Epilepsy Program, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Brian Litt
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Kathryn A. Davis
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Erin C. Conrad
- Department of Neurology, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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15
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Asp AJ, Chintaluru Y, Hillan S, Lujan JL. Targeted neuroplasticity in spatiotemporally patterned invasive neuromodulation therapies for improving clinical outcomes. Front Neuroinform 2023; 17:1150157. [PMID: 37035718 PMCID: PMC10080034 DOI: 10.3389/fninf.2023.1150157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Affiliation(s)
- Anders J. Asp
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - Yaswanth Chintaluru
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States
- Department of Neurology and Neurosurgery, University of Colorado Anschutz School of Medicine, Aurora, CO, United States
| | - Sydney Hillan
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - J. Luis Lujan
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
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16
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Shamim D, Nwabueze O, Uysal U. Beyond Resection: Neuromodulation and Minimally Invasive Epilepsy Surgery. Noro Psikiyatr Ars 2022; 59:S81-S90. [PMID: 36578991 PMCID: PMC9767135 DOI: 10.29399/npa.28181] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 10/03/2022] [Indexed: 11/06/2022] Open
Abstract
Epilepsy is a common neurological disease impacting both patients and healthcare systems. Approximately one third of patients have drug-resistant epilepsy (DRE) and are candidates for surgical options. However, only a small percentage undergo surgical treatment due to factors such as patient misconception/fear of surgery, healthcare disparities in epilepsy care, complex presurgical evaluation, primary care knowledge gap, and lack of systemic structures to allow effective coordination between referring physician and surgical epilepsy centers. Resective surgical treatments are superior to medication management for DRE patients in terms of seizure outcomes but may be less palatable to patients. There have been major advancements in minimally invasive surgeries (MIS) and neuromodulation techniques that may allay these concerns. Both epilepsy MIS and neuromodulation have shown promising seizure outcomes while minimizing complications. Minimally invasive methods include Laser Interstitial Thermal Therapy (LITT), RadioFrequency Ablation (RFA), Stereotactic RadioSurgery (SRS). Neuromodulation methods, which are more palliative, include Vagus Nerve Stimulation (VNS), Deep Brain Stimulation (DBS), and Responsive Neurostimulation System (RNS). This review will discuss the role of these techniques in varied epilepsy subtypes, their effectiveness in improving seizure control, and adverse outcomes.
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Affiliation(s)
- Daniah Shamim
- University of Kansas Medical Center, Department of Neurology, Kansas City, KS, USA
| | - Obiefuna Nwabueze
- University of Kansas Medical Center, Department of Neurology, Kansas City, KS, USA
| | - Utku Uysal
- University of Kansas Medical Center, Department of Neurology, Kansas City, KS, USA,Correspondence Address: Utku Uysal, MS University of Kansas School of Medicine 4000 Cambridge Street Mailstop 1065 Kansas City, KS 66160, USA • E-mail:
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17
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Dincer A, Herendeen J, Oster J, Kryzanski J. Resection of an occipital lobe epileptogenic network resulting in improvement of a visual field deficit: illustrative case. JOURNAL OF NEUROSURGERY. CASE LESSONS 2022; 4:CASE22210. [PMID: 36254354 PMCID: PMC9576032 DOI: 10.3171/case22210] [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: 05/10/2022] [Accepted: 07/28/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND Drug-resistant epilepsy leads to significant morbidity and mortality. Epilepsy surgery for resection of seizure foci is underused, particularly when a seizure focus is located in eloquent cortex. Epileptogenic networks may lead to neurological deficits out of proportion to a causative lesion. Disruption of the network may lead not only to seizure freedom but also reversal of a neurological deficit. OBSERVATIONS A 32-year-old male with new-onset generalized tonic-clonic seizure was found to have an occipital lobe cavernous malformation. On visual field testing, he was found to have a right-sided hemianopsia. He did not tolerate antiepileptic drugs and had a significant decline in quality of life. Resection was planned using intraoperative electrocorticography to remove the cavernous malformation and disrupt the epileptogenic network. Immediate and delayed postoperative visual field testing demonstrated improvement of the visual field deficit, with near resolution of the deficit 6 weeks postoperatively. LESSONS Epilepsy networks in eloquent cortex may cause deficits that improve after the causative lesion is resected and the network disrupted, a concept that is underreported in the literature. A subset of patients with frequent epileptiform activity and preoperative deficits may experience postoperative neurological improvement along with relief of seizures.
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Affiliation(s)
| | | | - Joel Oster
- Neurology, Tufts Medical Center, Boston, Massachusetts
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18
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Al-Bakri AF, Martinek R, Pelc M, Zygarlicki J, Kawala-Sterniuk A. Implementation of a Morphological Filter for Removing Spikes from the Epileptic Brain Signals to Improve Identification Ripples. SENSORS (BASEL, SWITZERLAND) 2022; 22:7522. [PMID: 36236621 PMCID: PMC9571066 DOI: 10.3390/s22197522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 09/20/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
Epilepsy is a very common disease affecting at least 1% of the population, comprising a number of over 50 million people. As many patients suffer from the drug-resistant version, the number of potential treatment methods is very small. However, since not only the treatment of epilepsy, but also its proper diagnosis or observation of brain signals from recordings are important research areas, in this paper, we address this very problem by developing a reliable technique for removing spikes and sharp transients from the baseline of the brain signal using a morphological filter. This allows much more precise identification of the so-called epileptic zone, which can then be resected, which is one of the methods of epilepsy treatment. We used eight patients with 5 KHz data set and depended upon the Staba 2002 algorithm as a reference to detect the ripples. We found that the average sensitivity and false detection rate of our technique are significant, and they are ∼94% and ∼14%, respectively.
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Affiliation(s)
- Amir F. Al-Bakri
- Department of Biomedical Engineering, College of Engineering, University of Babylon, Hillah 51001, Iraq
| | - Radek Martinek
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
- Department of Cybernetics and Biomedical Engineering, VSB-Technical University Ostrava—FEECS, 708 00 Ostrava–Poruba, Czech Republic
| | - Mariusz Pelc
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
- School of Computing and Mathematical Sciences, University of Greenwich, Park Row, London SE10 9LS, UK
| | - Jarosław Zygarlicki
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
| | - Aleksandra Kawala-Sterniuk
- Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, 45-758 Opole, Poland
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Lima LSD, Loyola V, Bicca JVML, Faro L, Vale CLC, Lotufo Denucci B, Mortari MR. Innovative treatments for epilepsy: Venom peptides, cannabinoids, and neurostimulation. J Neurosci Res 2022; 100:1969-1986. [PMID: 35934922 DOI: 10.1002/jnr.25114] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Revised: 07/13/2022] [Accepted: 07/22/2022] [Indexed: 11/07/2022]
Abstract
Antiepileptic drugs have been successfully treating epilepsy and providing individuals sustained seizure freedom. However, about 30% of the patients with epilepsy present drug resistance, which means they are not responsive to the pharmacological treatment. Considering this, it becomes extremely relevant to pursue alternative therapeutic approaches, in order to provide appropriate treatment for those patients and also improve their quality of life. In the light of that, this review aims to discuss some innovative options for the treatment of epilepsy, which are currently under investigation, addressing strategies that go from therapeutic compounds to clinical procedures. For instance, peptides derived from animal venoms, such as wasps, spiders, and scorpions, demonstrate to be promising antiepileptic molecules, acting on a variety of targets. Other options are cannabinoids and compounds that modulate the endocannabinoid system, since it is now known that this network is involved in the pathophysiology of epilepsy. Furthermore, neurostimulation is another strategy, being an alternative clinical procedure for drug-resistant patients who are not eligible for palliative surgeries.
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Affiliation(s)
- Larissa Silva de Lima
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
| | - Vinícius Loyola
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
| | - João Victor Montenegro Luzardo Bicca
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
| | - Lucas Faro
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
| | - Camilla Lepesqueur Costa Vale
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
| | - Bruna Lotufo Denucci
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
| | - Márcia Renata Mortari
- Laboratory of Neuropharmacology, Department of Physiological Sciences, Institute of Biological Sciences, University of Brasilia, Brasilia, Brazil
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20
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Feigen CM, Eskandar EN. Responsive Thalamic Neurostimulation: A Systematic Review of a Promising Approach for Refractory Epilepsy. Front Hum Neurosci 2022; 16:910345. [PMID: 35865353 PMCID: PMC9294465 DOI: 10.3389/fnhum.2022.910345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 05/25/2022] [Indexed: 11/13/2022] Open
Abstract
Introduction Responsive neurostimulation is an evolving therapeutic option for patients with treatment-refractory epilepsy. Open-loop, continuous stimulation of the anterior thalamic nuclei is the only approved modality, yet chronic stimulation rarely induces complete seizure remission and is associated with neuropsychiatric adverse effects. Accounts of off-label responsive stimulation in thalamic nuclei describe significant improvements in patients who have failed multiple drug regimens, vagal nerve stimulation, and other invasive measures. This systematic review surveys the currently available data supporting the use of responsive thalamic neurostimulation in primary and secondary generalized, treatment-refractory epilepsy. Materials and Methods A systematic review was performed using the following combination of keywords and controlled vocabulary: (“Seizures”[Mesh] AND “Thalamus”[Mesh] AND “Deep Brain Stimulation”[Mesh]) OR (responsive neurostim* AND (thalamus[MeSH])) OR [responsive neurostimulation AND thalamus AND (epilepsy OR seizures)]. In addition, a search of the publications listed under the PubMed “cited by” tab was performed for all publications that passed title/abstract screening in addition to manually searching their reference lists. Results Ten publications were identified describing a total of 29 subjects with a broad range of epilepsy disorders treated with closed-loop thalamic neurostimulation. The median age of subjects was 31 years old (range 10–65 years). Of the 29 subjects, 15 were stimulated in the anterior, 11 in the centromedian, and 3 in the pulvinar nuclei. Excluding 5 subjects who were treated for 1 month or less, median time on stimulation was 19 months (range 2.4–54 months). Of these subjects, 17/24 experienced greater than or equal to 50%, 11/24 least 75%, and 9/24 at least 90% reduction in seizures. Although a minority of patients did not exhibit significant clinical improvement by follow-up, there was a general trend of increasing treatment efficacy with longer periods on closed-loop thalamic stimulation. Conclusion The data supporting off-label closed-loop thalamic stimulation for refractory epilepsy is limited to 29 adult and pediatric patients, many of whom experienced significant improvement in seizure duration and frequency. This encouraging progress must be verified in larger studies.
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21
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Silverio AA, Silverio LAA. Developments in Deep Brain Stimulators for Successful Aging Towards Smart Devices—An Overview. FRONTIERS IN AGING 2022; 3:848219. [PMID: 35821845 PMCID: PMC9261350 DOI: 10.3389/fragi.2022.848219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 03/15/2022] [Indexed: 12/02/2022]
Abstract
This work provides an overview of the present state-of-the-art in the development of deep brain Deep Brain Stimulation (DBS) and how such devices alleviate motor and cognitive disorders for a successful aging. This work reviews chronic diseases that are addressable via DBS, reporting also the treatment efficacies. The underlying mechanism for DBS is also reported. A discussion on hardware developments focusing on DBS control paradigms is included specifically the open- and closed-loop “smart” control implementations. Furthermore, developments towards a “smart” DBS, while considering the design challenges, current state of the art, and constraints, are also presented. This work also showcased different methods, using ambient energy scavenging, that offer alternative solutions to prolong the battery life of the DBS device. These are geared towards a low maintenance, semi-autonomous, and less disruptive device to be used by the elderly patient suffering from motor and cognitive disorders.
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Affiliation(s)
- Angelito A. Silverio
- Department of Electronics Engineering, University of Santo Tomas, Manila, Philippines
- Research Center for the Natural and Applied Sciences, University of Santo Tomas, Manila, Philippines
- *Correspondence: Angelito A. Silverio,
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22
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Afra P, Adamolekun B, Aydemir S, Watson GDR. Evolution of the Vagus Nerve Stimulation (VNS) Therapy System Technology for Drug-Resistant Epilepsy. FRONTIERS IN MEDICAL TECHNOLOGY 2022; 3:696543. [PMID: 35047938 PMCID: PMC8757869 DOI: 10.3389/fmedt.2021.696543] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Accepted: 06/10/2021] [Indexed: 12/14/2022] Open
Abstract
The vagus nerve stimulation (VNS) Therapy® System is the first FDA-approved medical device therapy for the treatment of drug-resistant epilepsy. Over the past two decades, the technology has evolved through multiple iterations resulting in software-related updates and implantable lead and generator hardware improvements. Healthcare providers today commonly encounter a range of single- and dual-pin generators (models 100, 101, 102, 102R, 103, 104, 105, 106, 1000) and related programming systems (models 250, 3000), all of which have their own subtle, but practical differences. It can therefore be a daunting task to go through the manuals of these implant models for comparison, some of which are not readily available. In this review, we highlight the technological evolution of the VNS Therapy System with respect to device approval milestones and provide a comparison of conventional open-loop vs. the latest closed-loop generator models. Battery longevity projections and an in-depth examination of stimulation mode interactions are also presented to further differentiate amongst generator models.
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Affiliation(s)
- Pegah Afra
- Department of Neurology, Weill-Cornell Medicine, New York, NY, United States.,Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, United States
| | - Bola Adamolekun
- Department of Neurology, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Seyhmus Aydemir
- Department of Neurology, Weill-Cornell Medicine, New York, NY, United States
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Rincon N, Barr D, Velez-Ruiz N. Neuromodulation in Drug Resistant Epilepsy. Aging Dis 2021; 12:1070-1080. [PMID: 34221550 PMCID: PMC8219496 DOI: 10.14336/ad.2021.0211] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 02/11/2021] [Indexed: 12/26/2022] Open
Abstract
Epilepsy affects approximately 70 million people worldwide, and it is a significant contributor to the global burden of neurological disorders. Despite the advent of new AEDs, drug resistant-epilepsy continues to affect 30-40% of PWE. Once identified as having drug-resistant epilepsy, these patients should be referred to a comprehensive epilepsy center for evaluation to establish if they are candidates for potential curative surgeries. Unfortunately, a large proportion of patients with drug-resistant epilepsy are poor surgical candidates due to a seizure focus located in eloquent cortex, multifocal epilepsy or inability to identify the zone of ictal onset. An alternative treatment modality for these patients is neuromodulation. Here we present the evidence, indications and safety considerations for the neuromodulation therapies in vagal nerve stimulation (VNS), responsive neurostimulation (RNS), or deep brain stimulation (DBS).
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Affiliation(s)
- Natalia Rincon
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Donald Barr
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Naymee Velez-Ruiz
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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24
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Fregni F, El-Hagrassy MM, Pacheco-Barrios K, Carvalho S, Leite J, Simis M, Brunelin J, Nakamura-Palacios EM, Marangolo P, Venkatasubramanian G, San-Juan D, Caumo W, Bikson M, Brunoni AR. Evidence-Based Guidelines and Secondary Meta-Analysis for the Use of Transcranial Direct Current Stimulation in Neurological and Psychiatric Disorders. Int J Neuropsychopharmacol 2021; 24:256-313. [PMID: 32710772 PMCID: PMC8059493 DOI: 10.1093/ijnp/pyaa051] [Citation(s) in RCA: 321] [Impact Index Per Article: 80.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 07/21/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Transcranial direct current stimulation has shown promising clinical results, leading to increased demand for an evidence-based review on its clinical effects. OBJECTIVE We convened a team of transcranial direct current stimulation experts to conduct a systematic review of clinical trials with more than 1 session of stimulation testing: pain, Parkinson's disease motor function and cognition, stroke motor function and language, epilepsy, major depressive disorder, obsessive compulsive disorder, Tourette syndrome, schizophrenia, and drug addiction. METHODS Experts were asked to conduct this systematic review according to the search methodology from PRISMA guidelines. Recommendations on efficacy were categorized into Levels A (definitely effective), B (probably effective), C (possibly effective), or no recommendation. We assessed risk of bias for all included studies to confirm whether results were driven by potentially biased studies. RESULTS Although most of the clinical trials have been designed as proof-of-concept trials, some of the indications analyzed in this review can be considered as definitely effective (Level A), such as depression, and probably effective (Level B), such as neuropathic pain, fibromyalgia, migraine, post-operative patient-controlled analgesia and pain, Parkinson's disease (motor and cognition), stroke (motor), epilepsy, schizophrenia, and alcohol addiction. Assessment of bias showed that most of the studies had low risk of biases, and sensitivity analysis for bias did not change these results. Effect sizes vary from 0.01 to 0.70 and were significant in about 8 conditions, with the largest effect size being in postoperative acute pain and smaller in stroke motor recovery (nonsignificant when combined with robotic therapy). CONCLUSION All recommendations listed here are based on current published PubMed-indexed data. Despite high levels of evidence in some conditions, it must be underscored that effect sizes and duration of effects are often limited; thus, real clinical impact needs to be further determined with different study designs.
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Affiliation(s)
- Felipe Fregni
- Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Boston, Massachusetts
| | - Mirret M El-Hagrassy
- Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Boston, Massachusetts
| | - Kevin Pacheco-Barrios
- Neuromodulation Center and Center for Clinical Research Learning, Spaulding Rehabilitation Hospital and Massachusetts General Hospital, Boston, Massachusetts
- Universidad San Ignacio de Loyola, Vicerrectorado de Investigación, Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud, Lima, Peru
| | - Sandra Carvalho
- Neurotherapeutics and experimental Psychopathology Group (NEP), Psychological Neuroscience Laboratory, CIPsi, School of Psychology, University of Minho, Campus de Gualtar, Braga, Portugal
| | - Jorge Leite
- I2P-Portucalense Institute for Psychology, Universidade Portucalense, Porto, Portugal
| | - Marcel Simis
- Physical and Rehabilitation Medicine Institute of the University of Sao Paulo Medical School General Hospital, Sao Paulo, Brazil
| | - Jerome Brunelin
- CH Le Vinatier, PSYR2 team, Lyon Neuroscience Research Center, UCB Lyon 1, Bron, France
| | - Ester Miyuki Nakamura-Palacios
- Laboratory of Cognitive Sciences and Neuropsychopharmacology, Department of Physiological Sciences, Federal University of Espírito Santo, Espírito Santo, Brasil (Dr Nakamura-Palacios)
| | - Paola Marangolo
- Dipartimento di Studi Umanistici, Università Federico II, Naples, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Ganesan Venkatasubramanian
- Translational Psychiatry Laboratory, Department of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Daniel San-Juan
- Neurophysiology Department, National Institute of Neurology and Neurosurgery Manuel Velasco Suárez, Mexico City, Mexico
| | - Wolnei Caumo
- Post-Graduate Program in Medical Sciences, School of Medicine, Universidade Federal do Rio Grande do Sul (UFRGS) Surgery Department, School of Medicine, UFRGS; Pain and Palliative Care Service at Hospital de Clínicas de Porto Alegre (HCPA) Laboratory of Pain and Neuromodulation at HCPA, Porto Alegre, Brazil
| | - Marom Bikson
- Department of Biomedical Engineering, The City College of New York of CUNY, New York, New York
| | - André R Brunoni
- Service of Interdisciplinary Neuromodulation, Laboratory of Neurosciences (LIM-27), Department and Institute of Psychiatry & Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil
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25
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Venkatesh P, Sneider D, Danish M, Sisterson ND, Zaher N, Urban A, Grover P, Richardson RM, Kokkinos V. Quantifying a frequency modulation response biomarker in responsive neurostimulation. J Neural Eng 2021; 18. [PMID: 33691289 DOI: 10.1088/1741-2552/abed82] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Accepted: 03/10/2021] [Indexed: 11/11/2022]
Abstract
Objective.Responsive neurostimulation (RNS) is an effective treatment for controlling seizures in patients with drug-resistant focal epilepsy who are not suitable candidates for resection surgery. A lack of tools for detecting and characterizing potential response biomarkers, however, contributes to a limited understanding of mechanisms by which RNS improves seizure control. We developed a method to quantify ictal frequency modulation, previously identified as a biomarker of clinical responsiveness to RNS.Approach.Frequency modulation is characterized by shifts in power across spectral bands during ictal events, over several months of neurostimulation. This effect was quantified by partitioning each seizure pattern into segments with distinct spectral content and measuring the extent of change from the baseline distribution of spectral content using the squared earth mover's distance.Main results.We analyzed intracranial electroencephalography data from 13 patients who received RNS therapy, six of whom exhibited frequency modulation on expert evaluation. Patients in the frequency modulation group had, on average, significantly larger and more sustained changes in their squared earth mover's distances (mean = 13.97 × 10-3± 1.197 × 10-3). In contrast, those patients without expert-identified frequency modulation exhibited statistically insignificant or negligible distances (mean = 4.994 × 10-3± 0.732 × 10-3).Significance.This method is the first step towards a quantitative, feedback-driven system for systematically optimizing RNS stimulation parameters, with an ultimate goal of truly personalized closed-loop therapy for epilepsy.
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Affiliation(s)
- Praveen Venkatesh
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Daniel Sneider
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Mohammed Danish
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - Nathaniel D Sisterson
- Department of Neurosurgery, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, United States of America
| | - Naoir Zaher
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Alexandra Urban
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Pulkit Grover
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, United States of America
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, United States of America.,Harvard Medical School, Boston, MA, United States of America
| | - Vasileios Kokkinos
- Department of Neurosurgery, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114, United States of America.,Harvard Medical School, Boston, MA, United States of America
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26
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George R, Chiappalone M, Giugliano M, Levi T, Vassanelli S, Partzsch J, Mayr C. Plasticity and Adaptation in Neuromorphic Biohybrid Systems. iScience 2020; 23:101589. [PMID: 33083749 PMCID: PMC7554028 DOI: 10.1016/j.isci.2020.101589] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Neuromorphic systems take inspiration from the principles of biological information processing to form hardware platforms that enable the large-scale implementation of neural networks. The recent years have seen both advances in the theoretical aspects of spiking neural networks for their use in classification and control tasks and a progress in electrophysiological methods that is pushing the frontiers of intelligent neural interfacing and signal processing technologies. At the forefront of these new technologies, artificial and biological neural networks are tightly coupled, offering a novel "biohybrid" experimental framework for engineers and neurophysiologists. Indeed, biohybrid systems can constitute a new class of neuroprostheses opening important perspectives in the treatment of neurological disorders. Moreover, the use of biologically plausible learning rules allows forming an overall fault-tolerant system of co-developing subsystems. To identify opportunities and challenges in neuromorphic biohybrid systems, we discuss the field from the perspectives of neurobiology, computational neuroscience, and neuromorphic engineering.
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Affiliation(s)
- Richard George
- Department of Electrical Engineering and Information Technology, Technical University of Dresden, Dresden, Germany
| | | | - Michele Giugliano
- Neuroscience Area, International School of Advanced Studies, Trieste, Italy
| | - Timothée Levi
- Laboratoire de l’Intégration du Matéeriau au Systéme, University of Bordeaux, Bordeaux, France
- LIMMS/CNRS, Institute of Industrial Science, The University of Tokyo, Tokyo, Japan
| | - Stefano Vassanelli
- Department of Biomedical Sciences and Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Johannes Partzsch
- Department of Electrical Engineering and Information Technology, Technical University of Dresden, Dresden, Germany
| | - Christian Mayr
- Department of Electrical Engineering and Information Technology, Technical University of Dresden, Dresden, Germany
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27
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Ranjandish R, Schmid A. A Review of Microelectronic Systems and Circuit Techniques for Electrical Neural Recording Aimed at Closed-Loop Epilepsy Control. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5716. [PMID: 33050032 PMCID: PMC7583980 DOI: 10.3390/s20195716] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2020] [Revised: 09/07/2020] [Accepted: 10/02/2020] [Indexed: 12/21/2022]
Abstract
Closed-loop implantable electronics offer a new trend in therapeutic systems aimed at controlling some neurological diseases such as epilepsy. Seizures are detected and electrical stimulation applied to the brain or groups of nerves. To this aim, the signal recording chain must be very carefully designed so as to operate in low-power and low-latency, while enhancing the probability of correct event detection. This paper reviews the electrical characteristics of the target brain signals pertaining to epilepsy detection. Commercial systems are presented and discussed. Finally, the major blocks of the signal acquisition chain are presented with a focus on the circuit architecture and a careful attention to solutions to issues related to data acquisition from multi-channel arrays of cortical sensors.
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Affiliation(s)
- Reza Ranjandish
- Department of Information Technology and Electrical Engineering, ETH Zürich, CH-8092 Zürich, Switzerland;
| | - Alexandre Schmid
- Institute of Electrical Engineering, EPF Lausanne, CH-1015 Lausanne, Switzerland
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28
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Foit NA, Bernasconi A, Ladbon-Bernasconi N. Contributions of Imaging to Neuromodulatory Treatment of Drug-Refractory Epilepsy. Brain Sci 2020; 10:E700. [PMID: 33023078 PMCID: PMC7601437 DOI: 10.3390/brainsci10100700] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 09/23/2020] [Accepted: 09/26/2020] [Indexed: 12/17/2022] Open
Abstract
Epilepsy affects about 1% of the world's population, and up to 30% of all patients will ultimately not achieve freedom from seizures with anticonvulsive medication alone. While surgical resection of a magnetic resonance imaging (MRI) -identifiable lesion remains the first-line treatment option for drug-refractory epilepsy, surgery cannot be offered to all. Neuromodulatory therapy targeting "seizures" instead of "epilepsy" has emerged as a valuable treatment option for these patients, including invasive procedures such as deep brain stimulation (DBS), responsive neurostimulation (RNS) and peripheral approaches such as vagus nerve stimulation (VNS). The purpose of this review is to provide in-depth information on current concepts and evidence on network-level aspects of drug-refractory epilepsy. We reviewed the current evidence gained from studies utilizing advanced imaging methodology, with a specific focus on their contributions to neuromodulatory therapy.
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Affiliation(s)
- Niels Alexander Foit
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A2B4, Canada; (A.B.); (N.L.-B.)
- Department of Neurosurgery, Medical Center–University of Freiburg, Faculty of Medicine, D-79106 Freiburg, Germany
| | - Andrea Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A2B4, Canada; (A.B.); (N.L.-B.)
| | - Neda Ladbon-Bernasconi
- Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC H3A2B4, Canada; (A.B.); (N.L.-B.)
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29
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Trevathan JK, Asp AJ, Nicolai EN, Trevathan JM, Kremer NA, Kozai TDY, Cheng D, Schachter MJ, Nassi JJ, Otte SL, Parker JG, Lujan JL, Ludwig KA. Calcium imaging in freely-moving mice during electrical stimulation of deep brain structures. J Neural Eng 2020; 18:10.1088/1741-2552/abb7a4. [PMID: 32916665 PMCID: PMC8485730 DOI: 10.1088/1741-2552/abb7a4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
After decades of study in humans and animal models, there remains a lack of consensus regarding how the action of electrical stimulation on neuronal and non-neuronal elements - e.g. neuropil, cell bodies, glial cells, etc. - leads to the therapeutic effects of neuromodulation therapies. To further our understanding of neuromodulation therapies, there is a critical need for novel methodological approaches using state-of-the-art neuroscience tools to study neuromodulation therapy in preclinical models of disease. In this manuscript we outline one such approach combining chronic behaving single-photon microendoscope recordings in a pathological mouse model with electrical stimulation of a common deep brain stimulation (DBS) target. We describe in detail the steps necessary to realize this approach, as well as discuss key considerations for extending this experimental paradigm to other DBS targets for different therapeutic indications. Additionally, we make recommendations from our experience on implementing and validating the required combination of procedures that includes: the induction of a pathological model (6-OHDA model of Parkinson's disease) through an injection procedure, the injection of the viral vector to induce GCaMP expression, the implantation of the GRIN lens and stimulation electrode, and the installation of a baseplate for mounting the microendoscope. We proactively identify unique data analysis confounds occurring due to the combination of electrical stimulation and optical recordings and outline an approach to address these confounds. In order to validate the technical feasibility of this unique combination of experimental methods, we present data to demonstrate that 1) despite the complex multifaceted surgical procedures, chronic optical recordings of hundreds of cells combined with stimulation is achievable over week long periods 2) this approach enables measurement of differences in DBS evoked neural activity between anesthetized and awake conditions and 3) this combination of techniques can be used to measure electrical stimulation induced changes in neural activity during behavior in a pathological mouse model. These findings are presented to underscore the feasibility and potential utility of minimally constrained optical recordings to elucidate the mechanisms of DBS therapies in animal models of disease.
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Affiliation(s)
- James K Trevathan
- Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN 55905, United States of America
| | - Anders J Asp
- Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN 55905, United States of America
| | - Evan N Nicolai
- Mayo Clinic Graduate School of Biomedical Sciences, Rochester, MN 55905, United States of America
| | - Jonathan M Trevathan
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, United States of America
| | - Nicholas A Kremer
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, United States of America
| | - Takashi DY Kozai
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213, United States of America
- Center for the Neural Basis of Cognition, University of Pittsburgh and Carnegie Mellon University, Pittsburgh, PA 15213, United States of America
- McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15213, United States of America
- NeuroTech Center of the University of Pittsburgh Brain Institute, Pittsburgh, PA 15213, United States of America
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA 15213, United States of America
| | - David Cheng
- Inscopix, Palo Alto, CA, United States of America
| | | | | | | | - Jones G Parker
- CNC Program, Stanford University, Stanford, CA, United States of America
| | - J Luis Lujan
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, United States of America
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN 55905, United States of America
- These authors contributed equally
| | - Kip A Ludwig
- Department of Bioengineering, University of Wisconsin, Madison, WI 53706, United States of America
- Department of Neurological Surgery, University of Wisconsin, Madison, WI 53706, United States of America
- These authors contributed equally
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30
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Stieger KC, Eles JR, Ludwig KA, Kozai TDY. In vivo microstimulation with cathodic and anodic asymmetric waveforms modulates spatiotemporal calcium dynamics in cortical neuropil and pyramidal neurons of male mice. J Neurosci Res 2020; 98:2072-2095. [PMID: 32592267 DOI: 10.1002/jnr.24676] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2019] [Revised: 05/26/2020] [Accepted: 05/27/2020] [Indexed: 12/12/2022]
Abstract
Electrical stimulation has been critical in the development of an understanding of brain function and disease. Despite its widespread use and obvious clinical potential, the mechanisms governing stimulation in the cortex remain largely unexplored in the context of pulse parameters. Modeling studies have suggested that modulation of stimulation pulse waveform may be able to control the probability of neuronal activation to selectively stimulate either cell bodies or passing fibers depending on the leading polarity. Thus, asymmetric waveforms with equal charge per phase (i.e., increasing the leading phase duration and proportionately decreasing the amplitude) may be able to activate a more spatially localized or distributed population of neurons if the leading phase is cathodic or anodic, respectively. Here, we use two-photon and mesoscale calcium imaging of GCaMP6s expressed in excitatory pyramidal neurons of male mice to investigate the role of pulse polarity and waveform asymmetry on the spatiotemporal properties of direct neuronal activation with 10-Hz electrical stimulation. We demonstrate that increasing cathodic asymmetry effectively reduces neuronal activation and results in a more spatially localized subpopulation of activated neurons without sacrificing the density of activated neurons around the electrode. Conversely, increasing anodic asymmetry increases the spatial spread of activation and highly resembles spatiotemporal calcium activity induced by conventional symmetric cathodic stimulation. These results suggest that stimulation polarity and asymmetry can be used to modulate the spatiotemporal dynamics of neuronal activity thus increasing the effective parameter space of electrical stimulation to restore sensation and study circuit dynamics.
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Affiliation(s)
- Kevin C Stieger
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Center for the Neural Basis of Cognition, University of Pittsburgh, Carnegie Mellon University, Pittsburgh, PA, USA
| | - James R Eles
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kip A Ludwig
- Department of Biomedical Engineering, University of Wisconsin Madison, Madison, WI, USA.,Department of Neurological Surgery, University of Wisconsin Madison, Madison, WI, USA.,Wisconsin Institute for Translational Neuroengineering (WITNe), Madison, WI, USA
| | - Takashi D Y Kozai
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.,Center for the Neural Basis of Cognition, University of Pittsburgh, Carnegie Mellon University, Pittsburgh, PA, USA.,Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA.,McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, USA.,NeuroTech Center, University of Pittsburgh Brain Institute, Pittsburgh, PA, USA
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31
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Kokkinos V, Sisterson ND, Wozny TA, Richardson RM. Association of Closed-Loop Brain Stimulation Neurophysiological Features With Seizure Control Among Patients With Focal Epilepsy. JAMA Neurol 2020; 76:800-808. [PMID: 30985902 DOI: 10.1001/jamaneurol.2019.0658] [Citation(s) in RCA: 90] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Importance A bidirectional brain-computer interface that performs neurostimulation has been shown to improve seizure control in patients with refractory epilepsy, but the therapeutic mechanism is unknown. Objective To investigate whether electrographic effects of responsive neurostimulation (RNS), identified in electrocorticographic (ECOG) recordings from the device, are associated with patient outcomes. Design, Setting, and Participants Retrospective review of ECOG recordings and accompanying clinical meta-data from 11 consecutive patients with focal epilepsy who were implanted with a neurostimulation system between January 28, 2015, and June 6, 2017, with 22 to 112 weeks of follow-up. Recorded ECOG data were obtained from the manufacturer; additional system-generated meta-data, including recording and detection settings, were collected directly from the manufacturer's management system using an in-house, custom-built platform. Electrographic seizure patterns were identified in RNS recordings and evaluated in the time-frequency domain, which was locked to the onset of the seizure pattern. Main Outcomes and Measures Patterns of electrophysiological modulation were identified and then classified according to their latency of onset in relation to triggered stimulation events. Seizure control after RNS implantation was assessed by 3 main variables: mean frequency of seizure occurrence, estimated mean severity of seizures, and mean duration of seizures. Overall seizure outcomes were evaluated by the extended Personal Impact of Epilepsy Scale questionnaires, a patient-reported outcome measure of 3 domains (seizure characteristics, medication adverse effects, and quality of life), with a range of possible scores from 0 to 300 in which lower scores indicate worse status, and the Engel scale, which comprises 4 classes (I-IV) in which lower numbers indicate greater improvement. Results Electrocorticographic data from 11 patients (8 female; mean [range] age, 35 [19-65] years; mean [range] duration of epilepsy, 19 [5-37] years) were analyzed. Two main categories of electrophysiological signatures of stimulation-induced modulation of the seizure network were discovered: direct and indirect effects. Direct effects included ictal inhibition and early frequency modulation but were not associated with improved clinical outcomes (odds ratio [OR], 0.67; 95% CI, 0.06-7.35; P > .99). Only indirect effects-those occurring remote from triggered stimulation-were associated with improved clinical outcomes (OR, infinity; 95% CI, -infinity to infinity; P = .02). These indirect effects included spontaneous ictal inhibition, frequency modulation, fragmentation, and ictal duration modulation. Conclusions and Relevance These findings suggest that RNS effectiveness may be explained by long-term, stimulation-induced modulation of seizure network activity rather than by direct effects on each detected seizure.
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Affiliation(s)
- Vasileios Kokkinos
- Brain Modulation Laboratory, Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.,University of Pittsburgh Comprehensive Epilepsy Center, Pittsburgh, Pennsylvania
| | - Nathaniel D Sisterson
- Medical student, Brain Modulation Laboratory, Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Thomas A Wozny
- Brain Modulation Laboratory, Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - R Mark Richardson
- Brain Modulation Laboratory, Department of Neurological Surgery, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.,University of Pittsburgh Comprehensive Epilepsy Center, Pittsburgh, Pennsylvania.,University of Pittsburgh Brain Institute, Pittsburgh, Pennsylvania
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32
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Kini LG, Bernabei JM, Mikhail F, Hadar P, Shah P, Khambhati AN, Oechsel K, Archer R, Boccanfuso J, Conrad E, Shinohara RT, Stein JM, Das S, Kheder A, Lucas TH, Davis KA, Bassett DS, Litt B. Virtual resection predicts surgical outcome for drug-resistant epilepsy. Brain 2020; 142:3892-3905. [PMID: 31599323 DOI: 10.1093/brain/awz303] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Revised: 07/11/2019] [Accepted: 08/08/2019] [Indexed: 12/13/2022] Open
Abstract
Patients with drug-resistant epilepsy often require surgery to become seizure-free. While laser ablation and implantable stimulation devices have lowered the morbidity of these procedures, seizure-free rates have not dramatically improved, particularly for patients without focal lesions. This is in part because it is often unclear where to intervene in these cases. To address this clinical need, several research groups have published methods to map epileptic networks but applying them to improve patient care remains a challenge. In this study we advance clinical translation of these methods by: (i) presenting and sharing a robust pipeline to rigorously quantify the boundaries of the resection zone and determining which intracranial EEG electrodes lie within it; (ii) validating a brain network model on a retrospective cohort of 28 patients with drug-resistant epilepsy implanted with intracranial electrodes prior to surgical resection; and (iii) sharing all neuroimaging, annotated electrophysiology, and clinical metadata to facilitate future collaboration. Our network methods accurately forecast whether patients are likely to benefit from surgical intervention based on synchronizability of intracranial EEG (area under the receiver operating characteristic curve of 0.89) and provide novel information that traditional electrographic features do not. We further report that removing synchronizing brain regions is associated with improved clinical outcome, and postulate that sparing desynchronizing regions may further be beneficial. Our findings suggest that data-driven network-based methods can identify patients likely to benefit from resective or ablative therapy, and perhaps prevent invasive interventions in those unlikely to do so.
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Affiliation(s)
- Lohith G Kini
- Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - John M Bernabei
- Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Fadi Mikhail
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Peter Hadar
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Preya Shah
- Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California San Francisco, San Francisco CA 94143, USA
| | - Kelly Oechsel
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Ryan Archer
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Jacqueline Boccanfuso
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Erin Conrad
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia PA 19104, USA.,Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia PA 19104, USA
| | - Joel M Stein
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Sandhitsu Das
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Ammar Kheder
- Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Timothy H Lucas
- Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Danielle S Bassett
- Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Physics and Astronomy, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Psychiatry, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
| | - Brian Litt
- Department of Bioengineering, University of Pennsylvania, Philadelphia PA 19104, USA.,Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurology, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA.,Department of Neurosurgery, Hospital of the University of Pennsylvania, Philadelphia PA 19104, USA
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Pearce K, Dixon L, D'Arco F, Pujar S, Das K, Tahir Z, Tisdall M, Mankad K. Epilepsy surgery in children: what the radiologist needs to know. Neuroradiology 2020; 62:1061-1078. [PMID: 32435887 DOI: 10.1007/s00234-020-02448-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 03/27/2020] [Indexed: 12/18/2022]
Abstract
This review updates the radiologist on current epilepsy surgery practice in children, with a specific focus on the role of imaging in pre-surgical work-up, current and novel surgical techniques, expected post-surgical imaging appearances and important post-operative complications. A comprehensive review of the current and emerging international practices in paediatric epilepsy surgical planning and post-operative imaging is provided with details on case-based radiological findings. A detailed discussion of the pathophysiology and imaging features of different epileptogenic lesions will not be discussed as this is not the objective of this paper. Epilepsy surgery can be an effective method to control seizures in certain children with drug-resistant focal epilepsy. Early surgery in selected appropriate cases can lead to improved cognitive and developmental outcome. Advances in neurosurgical techniques, imaging and neuroanaesthesia have driven a parallel expansion in the array of epilepsy conditions which are potentially treatable with surgery. The range of surgical options is now wide, including minimally invasive ablative procedures for small lesions such as hypothalamic hamartomata, resections for focal lesions like hippocampal sclerosis and complex disconnective surgeries for multilobar conditions like Sturge Weber Syndrome and diffuse cortical malformations. An awareness of the surgical thinking when planning epilepsy surgery in children, and the practical knowledge of the operative steps involved will promote more accurate radiology reporting of the post-operative scan.
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Affiliation(s)
- Kirsten Pearce
- Department of Radiology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Luke Dixon
- Department of Radiology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Felice D'Arco
- Department of Radiology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Suresh Pujar
- Department of Neurology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Krishna Das
- Department of Neurology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Zubair Tahir
- Department of Neurosurgery, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Martin Tisdall
- Department of Neurosurgery, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK
| | - Kshitij Mankad
- Department of Radiology, Great Ormond Street Hospital NHS Foundation Trust, Great Ormond St, London, WC1N 3JH, UK.
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Gadgil N, Muir M, Lopresti MA, Lam SK. An update on pediatric surgical epilepsy: Part II. Surg Neurol Int 2019; 10:258. [PMID: 31893159 PMCID: PMC6935971 DOI: 10.25259/sni_418_2019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 11/22/2019] [Indexed: 12/29/2022] Open
Abstract
Background: Recent advances may allow surgical options for pediatric patients with refractory epilepsy not previously deemed surgical candidates. This review outlines major technological developments in the field of pediatric surgical epilepsy. Methods: The literature was comprehensively reviewed and summarized pertaining to stereotactic electroencephalography (sEEG), laser ablation, focused ultrasound (FUS), responsive neurostimulation (RNS), and deep brain stimulation (DBS) in pediatric epilepsy patients. Results: sEEG allows improved seizure localization in patients with widespread, bilateral, or deep-seated epileptic foci. Laser ablation may be used for destruction of deep-seated epileptic foci close to eloquent structures; FUS has a similar potential application. RNS is a palliative option for patients with eloquent, multiple, or broad epileptogenic foci. DBS is another palliative approach in children unsuitable for respective surgery. Conclusion: The landscape of pediatric epilepsy is changing due to improved diagnostic and treatment options for patients with refractory seizures. These interventions may improve seizure outcomes and decrease surgical morbidity, though further research is needed to define the appropriate role for each modality.
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Affiliation(s)
- Nisha Gadgil
- Department of Neurosurgery, Division of Pediatric Neurosurgery, Baylor College of Medicine/Texas Children's Hospital, Houston, Texas
| | - Matthew Muir
- Department of Neurosurgery, Division of Pediatric Neurosurgery, Baylor College of Medicine/Texas Children's Hospital, Houston, Texas
| | - Melissa A Lopresti
- Department of Neurosurgery, Division of Pediatric Neurosurgery, Baylor College of Medicine/Texas Children's Hospital, Houston, Texas
| | - Sandi K Lam
- Department of Neurosurgery, Division of Pediatric Neurosurgery, Northwestern University Feinberg School of Medicine/Ann and Robert H Lurie Children's Hospital, Chicago, IL, USA
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Streng ML, Krook-Magnuson E. Excitation, but not inhibition, of the fastigial nucleus provides powerful control over temporal lobe seizures. J Physiol 2019; 598:171-187. [PMID: 31682010 DOI: 10.1113/jp278747] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Accepted: 10/21/2019] [Indexed: 12/13/2022] Open
Abstract
KEY POINTS On-demand optogenetic inhibition of glutamatergic neurons in the fastigial nucleus of the cerebellum does not alter hippocampal seizures in a mouse model of temporal lobe epilepsy. In contrast, on-demand optogenetic excitation of glutamatergic neurons in the fastigial nucleus successfully inhibits hippocampal seizures. With this approach, even a single 50 ms pulse of light is able to significantly inhibit seizures. On-demand optogenetic excitation of glutamatergic fastigial neurons either ipsilateral or contralateral to the seizure focus is able to inhibit seizures. Selective excitation of glutamatergic nuclear neurons provides greater seizure inhibition than broadly exciting nuclear neurons without cell-type specificity. ABSTRACT Temporal lobe epilepsy is the most common form of epilepsy in adults, but current treatment options provide limited efficacy, leaving as many as one-third of patients with uncontrolled seizures. Recently, attention has shifted towards more closed-loop therapies for seizure control, and on-demand optogenetic modulation of the cerebellar cortex was shown to be highly effective at attenuating hippocampal seizures. Intriguingly, both optogenetic excitation and inhibition of cerebellar cortical output neurons, Purkinje cells, attenuated seizures. The mechanisms by which the cerebellum impacts seizures, however, are unknown. In the present study, we targeted the immediate downstream projection of vermal Purkinje cells - the fastigial nucleus - in order to determine whether increases and/or decreases in fastigial output can underlie seizure cessation. Though Purkinje cell input to fastigial neurons is inhibitory, direct optogenetic inhibition of the fastigial nucleus had no effect on seizure duration. Conversely, however, fastigial excitation robustly attenuated hippocampal seizures. Seizure cessation was achieved at multiple stimulation frequencies, regardless of laterality relative to seizure focus, and even with single light pulses. Seizure inhibition was greater when selectively targeting glutamatergic fastigial neurons than when an approach that lacked cell-type specificity was used. Together, these results suggest that stimulating excitatory neurons in the fastigial nucleus may be a promising approach for therapeutic intervention in temporal lobe epilepsy.
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Affiliation(s)
- Martha L Streng
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
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Bigelow MD, Kouzani AZ. Neural stimulation systems for the control of refractory epilepsy: a review. J Neuroeng Rehabil 2019; 16:126. [PMID: 31665058 PMCID: PMC6820988 DOI: 10.1186/s12984-019-0605-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2019] [Accepted: 10/10/2019] [Indexed: 12/18/2022] Open
Abstract
Epilepsy affects nearly 1% of the world's population. A third of epilepsy patients suffer from a kind of epilepsy that cannot be controlled by current medications. For those where surgery is not an option, neurostimulation may be the only alternative to bring relief, improve quality of life, and avoid secondary injury to these patients. Until recently, open loop neurostimulation was the only alternative for these patients. However, for those whose epilepsy is applicable, the medical approval of the responsive neural stimulation and the closed loop vagal nerve stimulation systems have been a step forward in the battle against uncontrolled epilepsy. Nonetheless, improvements can be made to the existing systems and alternative systems can be developed to further improve the quality of life of sufferers of the debilitating condition. In this paper, we first present a brief overview of epilepsy as a disease. Next, we look at the current state of biomarker research in respect to sensing and predicting epileptic seizures. Then, we present the current state of open loop neural stimulation systems. We follow this by investigating the currently approved, and some of the recent experimental, closed loop systems documented in the literature. Finally, we provide discussions on the current state of neural stimulation systems for controlling epilepsy, and directions for future studies.
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Affiliation(s)
- Matthew D Bigelow
- School of Engineering, Deakin University, Geelong, Victoria, 3216, Australia
| | - Abbas Z Kouzani
- School of Engineering, Deakin University, Geelong, Victoria, 3216, Australia.
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Starnes K, Miller K, Wong-Kisiel L, Lundstrom BN. A Review of Neurostimulation for Epilepsy in Pediatrics. Brain Sci 2019; 9:brainsci9100283. [PMID: 31635298 PMCID: PMC6826633 DOI: 10.3390/brainsci9100283] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/14/2019] [Accepted: 10/17/2019] [Indexed: 12/16/2022] Open
Abstract
Neurostimulation for epilepsy refers to the application of electricity to affect the central nervous system, with the goal of reducing seizure frequency and severity. We review the available evidence for the use of neurostimulation to treat pediatric epilepsy, including vagus nerve stimulation (VNS), responsive neurostimulation (RNS), deep brain stimulation (DBS), chronic subthreshold cortical stimulation (CSCS), transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS). We consider possible mechanisms of action and safety concerns, and we propose a methodology for selecting between available options. In general, we find neurostimulation is safe and effective, although any high quality evidence applying neurostimulation to pediatrics is lacking. Further research is needed to understand neuromodulatory systems, and to identify biomarkers of response in order to establish optimal stimulation paradigms.
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Affiliation(s)
- Keith Starnes
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA.
| | - Kai Miller
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA.
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Wellman SM, Li L, Yaxiaer Y, McNamara I, Kozai TDY. Revealing Spatial and Temporal Patterns of Cell Death, Glial Proliferation, and Blood-Brain Barrier Dysfunction Around Implanted Intracortical Neural Interfaces. Front Neurosci 2019; 13:493. [PMID: 31191216 PMCID: PMC6546924 DOI: 10.3389/fnins.2019.00493] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Accepted: 04/29/2019] [Indexed: 12/11/2022] Open
Abstract
Improving the long-term performance of neural electrode interfaces requires overcoming severe biological reactions such as neuronal cell death, glial cell activation, and vascular damage in the presence of implanted intracortical devices. Past studies traditionally observe neurons, microglia, astrocytes, and blood-brain barrier (BBB) disruption around inserted microelectrode arrays. However, analysis of these factors alone yields poor correlation between tissue inflammation and device performance. Additionally, these studies often overlook significant biological responses that can occur during acute implantation injury. The current study employs additional histological markers that provide novel information about neglected tissue components-oligodendrocytes and their myelin structures, oligodendrocyte precursor cells, and BBB -associated pericytes-during the foreign body response to inserted devices at 1, 3, 7, and 28 days post-insertion. Our results reveal unique temporal and spatial patterns of neuronal and oligodendrocyte cell loss, axonal and myelin reorganization, glial cell reactivity, and pericyte deficiency both acutely and chronically around implanted devices. Furthermore, probing for immunohistochemical markers that highlight mechanisms of cell death or patterns of proliferation and differentiation have provided new insight into inflammatory tissue dynamics around implanted intracortical electrode arrays.
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Affiliation(s)
- Steven M. Wellman
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Lehong Li
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yalikun Yaxiaer
- Eberly College of Science, Pennsylvania State University, University Park, PA, United States
| | - Ingrid McNamara
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Takashi D. Y. Kozai
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
- Center for Neuroscience, University of Pittsburgh, Pittsburgh, PA, United States
- McGowan Institute of Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA, United States
- NeuroTech Center, University of Pittsburgh Brain Institute, Pittsburgh, PA, United States
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Hell F, Palleis C, Mehrkens JH, Koeglsperger T, Bötzel K. Deep Brain Stimulation Programming 2.0: Future Perspectives for Target Identification and Adaptive Closed Loop Stimulation. Front Neurol 2019; 10:314. [PMID: 31001196 PMCID: PMC6456744 DOI: 10.3389/fneur.2019.00314] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 03/12/2019] [Indexed: 12/28/2022] Open
Abstract
Deep brain stimulation has developed into an established treatment for movement disorders and is being actively investigated for numerous other neurological as well as psychiatric disorders. An accurate electrode placement in the target area and the effective programming of DBS devices are considered the most important factors for the individual outcome. Recent research in humans highlights the relevance of widespread networks connected to specific DBS targets. Improving the targeting of anatomical and functional networks involved in the generation of pathological neural activity will improve the clinical DBS effect and limit side-effects. Here, we offer a comprehensive overview over the latest research on target structures and targeting strategies in DBS. In addition, we provide a detailed synopsis of novel technologies that will support DBS programming and parameter selection in the future, with a particular focus on closed-loop stimulation and associated biofeedback signals.
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Affiliation(s)
- Franz Hell
- Department of Neurology, Ludwig Maximilians University, Munich, Germany
- Graduate School of Systemic Neurosciences, Ludwig Maximilians University, Munich, Germany
| | - Carla Palleis
- Department of Neurology, Ludwig Maximilians University, Munich, Germany
- Department of Translational Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Jan H. Mehrkens
- Department of Neurosurgery, Ludwig Maximilians University, Munich, Germany
| | - Thomas Koeglsperger
- Department of Neurology, Ludwig Maximilians University, Munich, Germany
- Department of Translational Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Kai Bötzel
- Department of Neurology, Ludwig Maximilians University, Munich, Germany
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40
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Stanslaski S, Herron J, Chouinard T, Bourget D, Isaacson B, Kremen V, Opri E, Drew W, Brinkmann BH, Gunduz A, Adamski T, Worrell GA, Denison T. A Chronically Implantable Neural Coprocessor for Investigating the Treatment of Neurological Disorders. IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS 2018; 12:1230-1245. [PMID: 30418885 PMCID: PMC6415546 DOI: 10.1109/tbcas.2018.2880148] [Citation(s) in RCA: 116] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Developing new tools to better understand disorders of the nervous system, with a goal to more effectively treat them, is an active area of bioelectronic medicine research. Future tools must be flexible and configurable, given the evolving understanding of both neuromodulation mechanisms and how to configure a system for optimal clinical outcomes. We describe a system, the Summit RC+S "neural coprocessor," that attempts to bring the capability and flexibility of a microprocessor to a prosthesis embedded within the nervous system. This paper describes the updated system architecture for the Summit RC+S system, the five custom integrated circuits required for bi-directional neural interfacing, the supporting firmware/software ecosystem, and the verification and validation activities to prepare for human implantation. Emphasis is placed on design changes motivated by experience with the CE-marked Activa PC+S research tool; specifically, enhancement of sense-stim performance for improved bi-directional communication to the nervous system, implementation of rechargeable technology to extend device longevity, and application of MICS-band telemetry for algorithm development and data management. The technology was validated in a chronic treatment paradigm for canines with naturally occurring epilepsy, including free ambulation in the home environment, which represents a typical use case for future human protocols.
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41
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Abstract
The current paradigm for treatment of epilepsy begins with trials of antiepileptic drugs, followed by evaluation for resective brain surgery in drug-resistant patients. If surgery is not possible or fails to control seizures, some patients benefit from implanted neurostimulation devices. In addition to their therapeutic benefit, some of these devices have diagnostic capability enabling recordings of brain activity with unprecedented chronicity. Two recent studies using different devices for chronic EEG (i.e., over months to years) yielded convergent findings of daily and multiday cycles of brain activity that help explain seizure timing. Knowledge of these patient-specific cycles can be leveraged to gauge and forecast seizure risk, empowering patients to adopt risk-stratified treatment strategies and behavioral modifications. We review evidence that epilepsy is a cyclical disorder, and we argue that implanted monitoring devices should be offered earlier in the treatment paradigm. Chronic EEG would allow pharmacologic treatments tailored to days of high seizure risk-here termed chronotherapy-and would help characterize long timescale seizure dynamics to improve subsequent surgical planning. Coupled with neuromodulation, the proposed approach could improve quality of life for patients and decrease the number ultimately requiring resective surgery. We outline challenges for chronic monitoring and seizure forecasting that demand close collaboration among engineers, neurosurgeons, and neurologists.
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Affiliation(s)
- Maxime O Baud
- From the Sleep-Wake-Epilepsy Center and Center for Experimental Neurology, Department of Neurology (M.O.B.), Inselspital, Bern University Hospital, University of Bern; Wyss Center for Bio- and Neuro-engineering (M.O.B.), Geneva, Switzerland; and Department of Neurology and Weill Institute for Neurosciences (V.R.R.), University of California, San Francisco.
| | - Vikram R Rao
- From the Sleep-Wake-Epilepsy Center and Center for Experimental Neurology, Department of Neurology (M.O.B.), Inselspital, Bern University Hospital, University of Bern; Wyss Center for Bio- and Neuro-engineering (M.O.B.), Geneva, Switzerland; and Department of Neurology and Weill Institute for Neurosciences (V.R.R.), University of California, San Francisco
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42
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Chronically Implanted Intracranial Electrodes: Tissue Reaction and Electrical Changes. MICROMACHINES 2018; 9:mi9090430. [PMID: 30424363 PMCID: PMC6187588 DOI: 10.3390/mi9090430] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Revised: 08/13/2018] [Accepted: 08/22/2018] [Indexed: 12/28/2022]
Abstract
The brain-electrode interface is arguably one of the most important areas of study in neuroscience today. A stronger foundation in this topic will allow us to probe the architecture of the brain in unprecedented functional detail and augment our ability to intervene in disease states. Over many years, significant progress has been made in this field, but some obstacles have remained elusive—notably preventing glial encapsulation and electrode degradation. In this review, we discuss the tissue response to electrode implantation on acute and chronic timescales, the electrical changes that occur in electrode systems over time, and strategies that are being investigated in order to minimize the tissue response to implantation and maximize functional electrode longevity. We also highlight the current and future clinical applications and relevance of electrode technology.
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43
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Zhao X, Lhatoo SD. Seizure detection: do current devices work? And when can they be useful? Curr Neurol Neurosci Rep 2018; 18:40. [PMID: 29796939 DOI: 10.1007/s11910-018-0849-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
PURPOSE OF REVIEW The unpredictability and apparent randomness of epileptic seizures is one of the most vexing aspects of epilepsy. Methods or devices capable of detecting seizures may help prevent injury or even death and significantly improve quality of life. Here, we summarize and evaluate currently available, unimodal, or polymodal detection systems for epileptic seizures, mainly in the ambulatory setting. RECENT FINDINGS There are two broad categories of detection devices: EEG-based and non-EEG-based systems. Wireless wearable EEG devices are now available both in research and commercial arenas. Neuro-stimulation devices are currently evolving and initial experiences of these show potential promise. As for non-EEG devices, different detecting systems show different sensitivity according to the different patient and seizure types. Regardless, when used in combination, these modalities may complement each other to increase positive predictive value. Although some devices with high sensitivity are promising, practical widespread use of such detection systems is still some way away. More research and experience are needed to evaluate the most efficient and integrated systems, to allow for better approaches to detection and prediction of seizures. The concept of closed-loop systems and prompt intervention may substantially improve quality of life for patients and carers.
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Affiliation(s)
- Xiuhe Zhao
- Epilepsy Center, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH, 44106, USA.,Neurology Department, Qilu Hospital of Shandong University, 107 Wenhuaxi Road, Jinan, 250012, Shandong Province, China
| | - Samden D Lhatoo
- Epilepsy Center, University Hospitals Cleveland Medical Center, 11100 Euclid Avenue, Cleveland, OH, 44106, USA. .,NIH/NINDS Center for SUDEP Research, Boston, MA, USA.
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Panuccio G, Semprini M, Natale L, Buccelli S, Colombi I, Chiappalone M. Progress in Neuroengineering for brain repair: New challenges and open issues. Brain Neurosci Adv 2018; 2:2398212818776475. [PMID: 32166141 PMCID: PMC7058228 DOI: 10.1177/2398212818776475] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Accepted: 04/19/2018] [Indexed: 01/01/2023] Open
Abstract
Background In recent years, biomedical devices have proven to be able to target also different neurological disorders. Given the rapid ageing of the population and the increase of invalidating diseases affecting the central nervous system, there is a growing demand for biomedical devices of immediate clinical use. However, to reach useful therapeutic results, these tools need a multidisciplinary approach and a continuous dialogue between neuroscience and engineering, a field that is named neuroengineering. This is because it is fundamental to understand how to read and perturb the neural code in order to produce a significant clinical outcome. Results In this review, we first highlight the importance of developing novel neurotechnological devices for brain repair and the major challenges expected in the next years. We describe the different types of brain repair strategies being developed in basic and clinical research and provide a brief overview of recent advances in artificial intelligence that have the potential to improve the devices themselves. We conclude by providing our perspective on their implementation to humans and the ethical issues that can arise. Conclusions Neuroengineering approaches promise to be at the core of future developments for clinical applications in brain repair, where the boundary between biology and artificial intelligence will become increasingly less pronounced.
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Affiliation(s)
- Gabriella Panuccio
- Department of Neuroscience and Brain Technologies (NBT), Istituto Italiano di Tecnologia (IIT), Genova, Italy
| | | | - Lorenzo Natale
- iCub Facility, Istituto Italiano di Tecnologia, Genova, Italy
| | - Stefano Buccelli
- Department of Neuroscience and Brain Technologies (NBT), Istituto Italiano di Tecnologia (IIT), Genova, Italy.,Rehab Technologies, Istituto Italiano di Tecnologia, Genova, Italy.,Dipartimento di Neuroscienze, riabilitazione, oftalmologia, genetica e scienze materno-infantili (DINOGMI), University of Genova, Genova, Italy
| | - Ilaria Colombi
- Department of Neuroscience and Brain Technologies (NBT), Istituto Italiano di Tecnologia (IIT), Genova, Italy.,Rehab Technologies, Istituto Italiano di Tecnologia, Genova, Italy.,Dipartimento di Neuroscienze, riabilitazione, oftalmologia, genetica e scienze materno-infantili (DINOGMI), University of Genova, Genova, Italy
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Abstract
Neurological disorders are the leading cause of global disability. However, for most people around the world, current neurological care is poor. In low-income countries, most individuals lack access to proper neurological care, and in high-income countries, distance and disability limit access. With the global proliferation of smartphones, teleneurology - the use of technology to provide neurological care and education remotely - has the potential to improve and increase access to care for billions of people. Telestroke has already fulfilled this promise, but teleneurology applications for chronic conditions are still in their infancy. Similarly, few studies have explored the capabilities of mobile technologies such as smartphones and wearable sensors, which can guide care by providing objective, frequent, real-world assessments of patients. In low-income settings, teleneurology can increase the capacity of local care systems through professional development, diagnostic support and consultative services. In high-income settings, teleneurology is likely to promote the expansion and migration of neurological care away from institutions, incorporate systems of asynchronous communication (such as e-mail), integrate clinicians with diverse skill sets and reach new populations. Inertia, outdated policies and social barriers - especially the digital divide - will slow this progress at considerable cost. However, a future increasingly will be possible in which neurological care can be accessed by anyone, anywhere. Here, we examine the emerging evidence regarding the benefits of teleneurology for chronic conditions, its role and risks in low-income countries and the promise of mobile technologies to measure disease status and deliver care. We conclude by discussing the future trends, barriers and timing for the adoption of teleneurology.
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46
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Moore BD, Aron AR, Tandon N. Closed-loop intracranial stimulation alters movement timing in humans. Brain Stimul 2018; 11:886-895. [PMID: 29598890 DOI: 10.1016/j.brs.2018.03.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Revised: 02/20/2018] [Accepted: 03/06/2018] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND A prime objective driving the recent development of human neural prosthetics is to stimulate neural circuits in a manner time-locked to ongoing brain activity. The human supplementary motor area (SMA) is a particularly useful target for this objective because it displays characteristic neural activity just prior to voluntary movement. OBJECTIVE Here, we tested a method that detected activity in the human SMA related to impending movement and then delivered cortical stimulation with intracranial electrodes to influence the timing of movement. METHODS We conducted experiments in nine patients with electrodes implanted for epilepsy localization: five patients with SMA electrodes and four control patients with electrodes outside the SMA. In the first experiment, electrocorticographic (ECoG) recordings were used to localize the electrode of interest during a task involving bimanual finger movements. In the second experiment, a real-time sense-and-stimulate (SAS) system was implemented that delivered an electrical stimulus when pre-movement gamma power exceeded a threshold. RESULTS Stimulation based on real-time detection of this supra-threshold activity resulted in significant slowing of motor behavior in all of the cases where stimulation was carried out in the SMA patients but in none of the patients where stimulation was performed at the control site. CONCLUSIONS The neurophysiological correlates of impending movement can be used to trigger a closed loop stimulation device and influence ongoing motor behavior in a manner imperceptible to the subject. This is the first report of a human closed loop system designed to alter movement using direct cortical recordings and direct stimulation.
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Affiliation(s)
- Bartlett D Moore
- Vivian L Smith Department of Neurosurgery, McGovern Medical School, Houston, TX, 77030, USA
| | - Adam R Aron
- Department of Psychology, University of California, San Diego, La Jolla, CA, 92093, USA
| | - Nitin Tandon
- Vivian L Smith Department of Neurosurgery, McGovern Medical School, Houston, TX, 77030, USA; Mischer Neurosciences Institute, Memorial Hermann Hospital, Texas Medical Center, Houston, TX, 77030, USA.
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Abstract
The revolution in theory, swift technological developments, and invention of new devices have driven tremendous progress in neurostimulation as a third‐line treatment for epilepsy. Over the past decades, neurostimulation took its place in the field of epilepsy as an advanced treatment technique and opened up a new world. Numerous animal studies have proven the physical efficacy of stimulation of the brain and peripheral nerves. Based on this optimistic fundamental research, new advanced techniques are being explored in clinical practice. Over the past century, drawing on the benefits brought about by vagus nerve stimulation for the treatment of epilepsy, various new neurostimulation modalities have been developed to control seizures. Clinical studies including case reports, case series, and clinical trials have been booming in the past several years. This article gives a comprehensive review of most of these clinical studies. In addition to highlighting the advantages of neurostimulation for the treatment of epilepsy, concerns with this modality and future development directions are also discussed. The biggest advantage of neurostimulation over pharmacological treatments for epilepsy is the modulation of the epilepsy network by delivering stimuli at a specific target or the “hub.” Conversely, however, a lack of knowledge of epilepsy networks and the mechanisms of neurostimulation may hinder further development. Therefore, theoretical research on the mechanism of epileptogenesis and epilepsy networks is needed in the future. Within the multiple modalities of neuromodulation, the final choice should be made after full discussion with a multidisciplinary team at a presurgical conference. Furthermore, the establishment of a neurostimulation system with standardized parameters and rigorous guidelines is another important issue. To achieve this goal, a worldwide collaboration of epilepsy centers is also suggested in the future.
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Affiliation(s)
- Yicong Lin
- Department of Neurology Xuanwu Hospital Capital Medical University Beijing China.,Beijing Key Laboratory of Neuromodulation Beijing China.,Center of Epilepsy Beijing Institute for Brain Disorders Capital Medical University Beijing China
| | - Yuping Wang
- Department of Neurology Xuanwu Hospital Capital Medical University Beijing China.,Beijing Key Laboratory of Neuromodulation Beijing China.,Center of Epilepsy Beijing Institute for Brain Disorders Capital Medical University Beijing China
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