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Alfihed S, Majrashi M, Ansary M, Alshamrani N, Albrahim SH, Alsolami A, Alamari HA, Zaman A, Almutairi D, Kurdi A, Alzaydi MM, Tabbakh T, Al-Otaibi F. Non-Invasive Brain Sensing Technologies for Modulation of Neurological Disorders. BIOSENSORS 2024; 14:335. [PMID: 39056611 PMCID: PMC11274405 DOI: 10.3390/bios14070335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2024] [Revised: 07/01/2024] [Accepted: 07/06/2024] [Indexed: 07/28/2024]
Abstract
The non-invasive brain sensing modulation technology field is experiencing rapid development, with new techniques constantly emerging. This study delves into the field of non-invasive brain neuromodulation, a safer and potentially effective approach for treating a spectrum of neurological and psychiatric disorders. Unlike traditional deep brain stimulation (DBS) surgery, non-invasive techniques employ ultrasound, electrical currents, and electromagnetic field stimulation to stimulate the brain from outside the skull, thereby eliminating surgery risks and enhancing patient comfort. This study explores the mechanisms of various modalities, including transcranial direct current stimulation (tDCS) and transcranial magnetic stimulation (TMS), highlighting their potential to address chronic pain, anxiety, Parkinson's disease, and depression. We also probe into the concept of closed-loop neuromodulation, which personalizes stimulation based on real-time brain activity. While we acknowledge the limitations of current technologies, our study concludes by proposing future research avenues to advance this rapidly evolving field with its immense potential to revolutionize neurological and psychiatric care and lay the foundation for the continuing advancement of innovative non-invasive brain sensing technologies.
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Affiliation(s)
- Salman Alfihed
- Microelectronics and Semiconductor Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia; (S.A.)
| | - Majed Majrashi
- Bioengineering Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia
| | - Muhammad Ansary
- Neuroscience Center Research Unit, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia
| | - Naif Alshamrani
- Microelectronics and Semiconductor Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia; (S.A.)
| | - Shahad H. Albrahim
- Bioengineering Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia
| | - Abdulrahman Alsolami
- Microelectronics and Semiconductor Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia; (S.A.)
| | - Hala A. Alamari
- Bioengineering Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia
| | - Adnan Zaman
- Microelectronics and Semiconductor Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia; (S.A.)
| | - Dhaifallah Almutairi
- Microelectronics and Semiconductor Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia; (S.A.)
| | - Abdulaziz Kurdi
- Advanced Materials Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia;
| | - Mai M. Alzaydi
- Bioengineering Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia
| | - Thamer Tabbakh
- Microelectronics and Semiconductor Institute, King Abdulaziz City for Science and Technology (KACST), Riyadh 11442, Saudi Arabia; (S.A.)
| | - Faisal Al-Otaibi
- Neuroscience Center Research Unit, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia
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Zafeiropoulos S, Ahmed U, Bikou A, Mughrabi IT, Stavrakis S, Zanos S. Vagus nerve stimulation for cardiovascular diseases: Is there light at the end of the tunnel? Trends Cardiovasc Med 2024; 34:327-337. [PMID: 37506989 DOI: 10.1016/j.tcm.2023.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 06/12/2023] [Accepted: 07/17/2023] [Indexed: 07/30/2023]
Abstract
Autonomic dysfunction and chronic inflammation contribute to the pathogenesis and progression of several cardiovascular diseases (CVD), such as heart failure with preserved ejection fraction, atherosclerotic CVD, pulmonary arterial hypertension, and atrial fibrillation. The vagus nerve provides parasympathetic innervation to the heart, vessels, and lungs, and is also implicated in the neural control of inflammation through a neuroimmune pathway involving the spleen. Stimulation of the vagus nerve (VNS) can in principle restore autonomic balance and suppress inflammation, with potential therapeutic benefits in these diseases. Although VNS ameliorated CVD in several animal models, early human studies have demonstrated variable efficacy. The purpose of this review is to discuss the rationale behind the use of VNS in the treatment of CVD, to critically review animal and human studies of VNS in CVD, and to propose possible means to overcome the challenges in the clinical translation of VNS in CVD.
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Affiliation(s)
- Stefanos Zafeiropoulos
- Elmezzi Graduate School of Molecular Medicine at Northwell Health, Manhasset, NY, USA; Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Umair Ahmed
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Alexia Bikou
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Ibrahim T Mughrabi
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - Stavros Stavrakis
- Heart Rhythm Institute, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Stavros Zanos
- Elmezzi Graduate School of Molecular Medicine at Northwell Health, Manhasset, NY, USA; Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, USA.
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3
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Karthika V, Badrinathan Sridharan, Nam JW, Kim D, Gyun Lim H. Neuromodulation by nanozymes and ultrasound during Alzheimer's disease management. J Nanobiotechnology 2024; 22:139. [PMID: 38555420 PMCID: PMC10981335 DOI: 10.1186/s12951-024-02406-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 03/18/2024] [Indexed: 04/02/2024] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disorder with complex pathogenesis and effective clinical treatment strategies for this disease remain elusive. Interestingly, nanomedicines are under extensive investigation for AD management. Currently, existing redox molecules show highly bioactive property but suffer from instability and high production costs, limiting clinical application for neurological diseases. Compared with natural enzymes, artificial enzymes show high stability, long-lasting catalytic activity, and versatile enzyme-like properties. Further, the selectivity and performance of artificial enzymes can be modulated for neuroinflammation treatments through external stimuli. In this review, we focus on the latest developments of metal, metal oxide, carbon-based and polymer based nanozymes and their catalytic mechanisms. Recent developments in nanozymes for diagnosing and treating AD are emphasized, especially focusing on their potential to regulate pathogenic factors and target sites. Various applications of nanozymes with different stimuli-responsive features were discussed, particularly focusing on nanozymes for treating oxidative stress-related neurological diseases. Noninvasiveness and focused application to deep body regions makes ultrasound (US) an attractive trigger mechanism for nanomedicine. Since a complete cure for AD remains distant, this review outlines the potential of US responsive nanozymes to develop future therapeutic approaches for this chronic neurodegenerative disease and its emergence in AD management.
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Affiliation(s)
- Viswanathan Karthika
- Department of Biomedical Engineering, Pukyong National University, Busan, 48513, Republic of Korea
| | - Badrinathan Sridharan
- Department of Biomedical Engineering, Pukyong National University, Busan, 48513, Republic of Korea
| | - Ji Won Nam
- Industry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, Republic of Korea
| | - Daehun Kim
- Industry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, Republic of Korea
| | - Hae Gyun Lim
- Department of Biomedical Engineering, Pukyong National University, Busan, 48513, Republic of Korea.
- Industry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, Republic of Korea.
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4
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Li L, Liu C, Pan W, Wang W, Jin W, Ren Y, Ma X. Repetitive Transcranial Magnetic Stimulation for Working Memory Deficits in Schizophrenia: A Systematic Review of Randomized Controlled Trials. Neuropsychiatr Dis Treat 2024; 20:649-662. [PMID: 38528855 PMCID: PMC10962363 DOI: 10.2147/ndt.s450303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/15/2024] [Indexed: 03/27/2024] Open
Abstract
Working memory (WM) deficits are a significant component of neurocognitive impairment in individuals with schizophrenia (SCZ). Two previous meta-analyses, conducted on randomized controlled trials (RCTs), examined the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in addressing WM deficits in individuals diagnosed with SCZ. However, the conclusions drawn from these analyses were inconsistent. Additionally, the commonly used random effects (RE) models might underestimate statistical errors, attributing a significant portion of perceived heterogeneity between studies to variations in study quality. Therefore, this review utilized both RE and quality effects (QE) models to assess relevant RCTs comparing TMS with sham intervention in terms of clinical outcomes. A comprehensive literature search was conducted using PubMed and Scopus databases, resulting in the inclusion of 13 studies for data synthesis. Overall, regardless of whether the RE or QE model was used, eligible RCTs suggested that the TMS and sham groups exhibited comparable therapeutic effects after treatment. The current state of research regarding the use of rTMS as a treatment for WM deficits in patients with SCZ remains in its preliminary phase. Furthermore, concerning the mechanism of action, the activation of brain regions focused on the dorsolateral prefrontal cortex and alterations in gamma oscillations may hold significant relevance in the therapeutic application of rTMS for addressing WM impairments. Finally, we believe that the application of closed-loop neuromodulation may contribute to the optimization of rTMS for WM impairment in patients with SCZ.
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Affiliation(s)
- Li Li
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Chaomeng Liu
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Weigang Pan
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Wen Wang
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Wenqing Jin
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Yanping Ren
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
| | - Xin Ma
- The National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, People’s Republic of China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, People’s Republic of China
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Carè M, Chiappalone M, Cota VR. Personalized strategies of neurostimulation: from static biomarkers to dynamic closed-loop assessment of neural function. Front Neurosci 2024; 18:1363128. [PMID: 38516316 PMCID: PMC10954825 DOI: 10.3389/fnins.2024.1363128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 02/22/2024] [Indexed: 03/23/2024] Open
Abstract
Despite considerable advancement of first choice treatment (pharmacological, physical therapy, etc.) over many decades, neurological disorders still represent a major portion of the worldwide disease burden. Particularly concerning, the trend is that this scenario will worsen given an ever expanding and aging population. The many different methods of brain stimulation (electrical, magnetic, etc.) are, on the other hand, one of the most promising alternatives to mitigate the suffering of patients and families when conventional treatment fall short of delivering efficacious treatment. With applications in virtually all neurological conditions, neurostimulation has seen considerable success in providing relief of symptoms. On the other hand, a large variability of therapeutic outcomes has also been observed, particularly in the usage of non-invasive brain stimulation (NIBS) modalities. Borrowing inspiration and concepts from its pharmacological counterpart and empowered by unprecedented neurotechnological advancement, the neurostimulation field has seen in recent years a widespread of methods aimed at the personalization of its parameters, based on biomarkers of the individuals being treated. The rationale is that, by taking into account important factors influencing the outcome, personalized stimulation can yield a much-improved therapy. Here, we review the literature to delineate the state-of-the-art of personalized stimulation, while also considering the important aspects of the type of informing parameter (anatomy, function, hybrid), invasiveness, and level of development (pre-clinical experimentation versus clinical trials). Moreover, by reviewing relevant literature on closed loop neuroengineering solutions in general and on activity dependent stimulation method in particular, we put forward the idea that improved personalization may be achieved when the method is able to track in real time brain dynamics and adjust its stimulation parameters accordingly. We conclude that such approaches have great potential of promoting the recovery of lost functions and enhance the quality of life for patients.
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Affiliation(s)
- Marta Carè
- IRCCS Ospedale Policlinico San Martino, Genova, Italy
| | - Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, Genova, Italy
- Rehab Technologies Lab, Istituto Italiano di Tecnologia, Genova, Italy
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6
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Jia Q, Liu Y, Lv S, Wang Y, Jiao P, Xu W, Xu Z, Wang M, Cai X. Wireless closed-loop deep brain stimulation using microelectrode array probes. J Zhejiang Univ Sci B 2024:1-21. [PMID: 38423536 DOI: 10.1631/jzus.b2300400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 08/25/2023] [Indexed: 03/02/2024]
Abstract
Deep brain stimulation (DBS), including optical stimulation and electrical stimulation, has been demonstrated considerable value in exploring pathological brain activity and developing treatments for neural disorders. Advances in DBS microsystems based on implantable microelectrode array (MEA) probes have opened up new opportunities for closed-loop DBS (CL-DBS) in situ. This technology can be used to detect damaged brain circuits and test the therapeutic potential for modulating the output of these circuits in a variety of diseases simultaneously. Despite the success and rapid utilization of MEA probe-based CL-DBS microsystems, key challenges, including excessive wired communication, need to be urgently resolved. In this review, we considered recent advances in MEA probe-based wireless CL-DBS microsystems and outlined the major issues and promising prospects in this field. This technology has the potential to offer novel therapeutic options for psychiatric disorders in the future.
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Affiliation(s)
- Qianli Jia
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shiya Lv
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiding Wang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peiyao Jiao
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaojie Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mixia Wang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China.
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China. ,
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China. ,
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Su PYP, Arle J, Poree L. Closing the loop and raising the bar: Automated control systems in neuromodulation. Pain Pract 2024; 24:177-185. [PMID: 37638532 DOI: 10.1111/papr.13290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/04/2023] [Indexed: 08/29/2023]
Abstract
INTRODUCTION Neuromodulation has emerged as a promising therapy for the management of chronic pain, movement disorders, and other neurological conditions. Spinal cord stimulation (SCS) is a widely used form of neuromodulation that involves the delivery of electrical impulses to the spinal cord to modulate the transmission of pain signals to the brain. In recent years, there has been increasing interest in the use of automation systems to improve the efficacy and safety of SCS. This narrative review summarizes the status of Food and Drug Administration-approved autonomous neuromodulation devices including closed loop, feedforward, and feedback systems. The review discusses the advantages and disadvantages of each system and focuses specifically on the use of these systems for SCS. It is important for clinicians to understand the expanding role of automation in neuromodulation in order to select appropriate therapies founded on automation systems to the specific needs of the patient and the underlying condition. CONCLUSION The review also provides insights into the current state of the art in neuromodulation automation systems and discusses potential future directions for research in this field.
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Affiliation(s)
- Po-Yi Paul Su
- Department of Anesthesia, University of California San Francisco, San Francisco, California, USA
| | | | - Lawrence Poree
- Department of Anesthesia, University of California San Francisco, San Francisco, California, USA
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Güemes Gonzalez A, Carnicer-Lombarte A, Hilton S, Malliaras G. A multivariate physiological model of vagus nerve signalling during metabolic challenges in anaesthetised rats for diabetes treatment. J Neural Eng 2023; 20:056033. [PMID: 37757803 DOI: 10.1088/1741-2552/acfdcd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 09/27/2023] [Indexed: 09/29/2023]
Abstract
Objective.This study aims to develop a comprehensive decoding framework to create a multivariate physiological model of vagus nerve transmission that reveals the complex interactions between the nervous and metabolic systems.Approach.Vagus nerve activity was recorded in female Sprague-Dawley rats using gold hook microwires implanted around the left cervical vagus nerve. The rats were divided into three experimental cohorts (intact nerve, ligation nerve for recording afferent activation, and ligation for recording efferent activation) and metabolic challenges were administered to change glucose levels while recording the nerve activity. The decoding methodology involved various techniques, including continuous wavelet transformation, extraction of breathing rate (BR), and correlation of neural metrics with physiological signals.Main results.Decrease in glucose level was consistently negatively correlated with an increase in the firing activity of the intact vagus nerve that was found to be conveyed by both afferent and efferent pathways, with the afferent response being more similar to the one on the intact nerve. A larger variability was observed in the sensory and motor responses to hyperglycaemia. A novel strategy to extract the BR over time based on inter-burst-interval is also presented. The vagus afferent was found to encode breathing information through amplitude and firing rate modulation. Modulations of the signal amplitude were also observed due to changes in heart rate in the intact and efferent recordings, highlighting the parasympathetic control of the heart.Significance.The analytical framework presented in this study provides an integrative understanding that considers the relationship between metabolic, cardiac, and breathing signals and contributes to the development of a multivariable physiological model for the transmission of vagus nerve signals. This work progresses toward the development of closed-loop neuro-metabolic therapeutic systems for diabetes.
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Affiliation(s)
- Amparo Güemes Gonzalez
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, United Kingdom
| | - Alejandro Carnicer-Lombarte
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, United Kingdom
| | - Sam Hilton
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, United Kingdom
| | - George Malliaras
- Electrical Engineering Division, Department of Engineering, University of Cambridge, Cambridge, CB3 0FA, United Kingdom
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Ghosh S, Sinha JK, Ghosh S, Sharma H, Bhaskar R, Narayanan KB. A Comprehensive Review of Emerging Trends and Innovative Therapies in Epilepsy Management. Brain Sci 2023; 13:1305. [PMID: 37759906 PMCID: PMC10527076 DOI: 10.3390/brainsci13091305] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 09/09/2023] [Accepted: 09/10/2023] [Indexed: 09/29/2023] Open
Abstract
Epilepsy is a complex neurological disorder affecting millions worldwide, with a substantial number of patients facing drug-resistant epilepsy. This comprehensive review explores innovative therapies for epilepsy management, focusing on their principles, clinical evidence, and potential applications. Traditional antiseizure medications (ASMs) form the cornerstone of epilepsy treatment, but their limitations necessitate alternative approaches. The review delves into cutting-edge therapies such as responsive neurostimulation (RNS), vagus nerve stimulation (VNS), and deep brain stimulation (DBS), highlighting their mechanisms of action and promising clinical outcomes. Additionally, the potential of gene therapies and optogenetics in epilepsy research is discussed, revealing groundbreaking findings that shed light on seizure mechanisms. Insights into cannabidiol (CBD) and the ketogenic diet as adjunctive therapies further broaden the spectrum of epilepsy management. Challenges in achieving seizure control with traditional therapies, including treatment resistance and individual variability, are addressed. The importance of staying updated with emerging trends in epilepsy management is emphasized, along with the hope for improved therapeutic options. Future research directions, such as combining therapies, AI applications, and non-invasive optogenetics, hold promise for personalized and effective epilepsy treatment. As the field advances, collaboration among researchers of natural and synthetic biochemistry, clinicians from different streams and various forms of medicine, and patients will drive progress toward better seizure control and a higher quality of life for individuals living with epilepsy.
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Affiliation(s)
- Shampa Ghosh
- GloNeuro, Sector 107, Vishwakarma Road, Noida 201301, India
- ICMR—National Institute of Nutrition, Tarnaka, Hyderabad 500007, India
| | | | - Soumya Ghosh
- GloNeuro, Sector 107, Vishwakarma Road, Noida 201301, India
| | | | - Rakesh Bhaskar
- School of Chemical Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Republic of Korea
| | - Kannan Badri Narayanan
- School of Chemical Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Republic of Korea
- Research Institute of Cell Culture, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Republic of Korea
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Bonanno M, Calabrò RS. Bridging the Gap between Basic Research and Clinical Practice: The Growing Role of Translational Neurorehabilitation. MEDICINES (BASEL, SWITZERLAND) 2023; 10:45. [PMID: 37623809 PMCID: PMC10456256 DOI: 10.3390/medicines10080045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 07/25/2023] [Accepted: 07/28/2023] [Indexed: 08/26/2023]
Abstract
Translational neuroscience is intended as a holistic approach in the field of brain disorders, starting from the basic research of cerebral morphology and with the function of implementing it into clinical practice. This concept can be applied to the rehabilitation field to promote promising results that positively influence the patient's quality of life. The last decades have seen great scientific and technological improvements in the field of neurorehabilitation. In this paper, we discuss the main issues related to translational neurorehabilitation, from basic research to current clinical practice, and we also suggest possible future scenarios.
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Affiliation(s)
| | - Rocco Salvatore Calabrò
- IRCCS Centro Neurolesi “Bonino-Pulejox”, Via Palermo, SS 113, C. da Casazza, 98124 Messina, Italy;
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Chang YC, Chao PH, Kuan YM, Huang CJ, Chen LF, Mao WC, Su TP, Chen SH, Wei CS. Delay Analysis in Closed-Loop EEG Phase-Triggered Transcranial Magnetic Stimulation. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083335 DOI: 10.1109/embc40787.2023.10340744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The recent development of closed-loop EEG phase-triggered transcranial magnetic stimulation (TMS) has advanced potential applications of adaptive neuromodulation based on the current brain state. Closed-loop TMS involves instantaneous acquisition of the EEG rhythm, timing prediction of the target phase, and triggering of TMS. However, the accuracy of EEG phase prediction algorithms is largely influenced by the system's transport delay, and their relationship is rarely considered in related work. This paper proposes a delay analysis that considers the delay of the closed-loop EEG phase-triggered TMS system as a primary factor in the validation of phase prediction algorithms. An in-silico validation using real EEG data was performed to compare the performance of commonly used algorithms. The experimental results indicate a significant influence of the total delay on the algorithm performance, and the performance ranking among algorithms varies at different levels of delay. We conclude that the delay analysis framework should be widely adopted in the design and validation of phase prediction algorithms for closed-loop EEG phase-triggered TMS systems.
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12
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Won SM, Cai L, Gutruf P, Rogers JA. Wireless and battery-free technologies for neuroengineering. Nat Biomed Eng 2023; 7:405-423. [PMID: 33686282 PMCID: PMC8423863 DOI: 10.1038/s41551-021-00683-3] [Citation(s) in RCA: 96] [Impact Index Per Article: 96.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 12/28/2020] [Indexed: 12/16/2022]
Abstract
Tethered and battery-powered devices that interface with neural tissues can restrict natural motions and prevent social interactions in animal models, thereby limiting the utility of these devices in behavioural neuroscience research. In this Review Article, we discuss recent progress in the development of miniaturized and ultralightweight devices as neuroengineering platforms that are wireless, battery-free and fully implantable, with capabilities that match or exceed those of wired or battery-powered alternatives. Such classes of advanced neural interfaces with optical, electrical or fluidic functionality can also combine recording and stimulation modalities for closed-loop applications in basic studies or in the practical treatment of abnormal physiological processes.
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Affiliation(s)
- Sang Min Won
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Le Cai
- Biomedical Engineering, College of Engineering, The University of Arizona, Tucson, AZ, USA
| | - Philipp Gutruf
- Biomedical Engineering, College of Engineering, The University of Arizona, Tucson, AZ, USA.
- Bio5 Institute and Neuroscience GIDP, University of Arizona, Tucson, AZ, USA.
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA.
| | - John A Rogers
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA.
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
- Center for Advanced Molecular Imaging, Northwestern University, Evanston, IL, USA.
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.
- Department of Chemistry, Northwestern University, Evanston, IL, USA.
- Department of Neurological Surgery, Northwestern University, Evanston, IL, USA.
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA.
- Simpson Querrey Institute for BioNanotechnology, Northwestern University, Evanston, IL, USA.
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13
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Chiappalone M, Cota VR, Carè M, Di Florio M, Beaubois R, Buccelli S, Barban F, Brofiga M, Averna A, Bonacini F, Guggenmos DJ, Bornat Y, Massobrio P, Bonifazi P, Levi T. Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering. Brain Sci 2022; 12:1578. [PMID: 36421904 PMCID: PMC9688667 DOI: 10.3390/brainsci12111578] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/09/2022] [Accepted: 11/17/2022] [Indexed: 08/27/2023] Open
Abstract
Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system.
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Affiliation(s)
- Michela Chiappalone
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Vinicius R. Cota
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Marta Carè
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Mattia Di Florio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Romain Beaubois
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Stefano Buccelli
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Federico Barban
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- Rehab Technologies, Istituto Italiano di Tecnologia, 16163 Genova, Italy
| | - Martina Brofiga
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - Alberto Averna
- Department of Neurology, Bern University Hospital, University of Bern, 3012 Bern, Switzerland
| | - Francesco Bonacini
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
| | - David J. Guggenmos
- Department of Rehabilitation Medicine, University of Kansas Medical Center, Kansas City, KS 66103, USA
- Landon Center on Aging, University of Kansas Medical Center, Kansas City, KS 66103, USA
| | - Yannick Bornat
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
| | - Paolo Massobrio
- Department of Informatics, Bioengineering, Robotics System Engineering (DIBRIS), University of Genova, 16145 Genova, Italy
- National Institute for Nuclear Physics (INFN), 16146 Genova, Italy
| | - Paolo Bonifazi
- IKERBASQUE, The Basque Fundation, 48009 Bilbao, Spain
- Biocruces Health Research Institute, 48903 Barakaldo, Spain
| | - Timothée Levi
- IMS Laboratory, CNRS UMR 5218, University of Bordeaux, 33405 Talence, France
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14
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Fedotchev AI. Correction of Stress-Induced States Using Sensory Stimulation Automatically Modulated by Endogenous Human Rhythms. NEUROSCIENCE AND BEHAVIORAL PHYSIOLOGY 2022; 52:947-952. [PMID: 36373061 PMCID: PMC9638486 DOI: 10.1007/s11055-022-01322-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Accepted: 04/26/2021] [Indexed: 06/16/2023]
Abstract
This article considers the dynamics of the development of a potential approach to correcting stress-induced states in humans, i.e., adaptive neurostimulation. The approach consists of presenting sensory stimulation automatically modulated by intrinsic rhythmic human processes such as the respiratory rhythm, the heartbeat rhythm, and electroencephalograph (EEG) rhythms. Many examples have shown that real-time self-adjustment of the stimulation parameters by these rhythms leads to a high level personalization of therapeutic stimulation and increases in its efficacy in suppressing stress-induced states. The publications reviewed here point to the advantages of this approach for developing innovatory technologies using complex feedback from endogenous human rhythms to correct a wide spectrum of functional disorders.
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Affiliation(s)
- A I Fedotchev
- Institute of Cell Biophysics, Russian Academy of Sciences, Pushchino, Russia
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15
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Chen M, Chen Z, Xiao X, Zhou L, Fu R, Jiang X, Pang M, Xia J. Corticospinal circuit neuroplasticity may involve silent synapses: Implications for functional recovery facilitated by neuromodulation after spinal cord injury. IBRO Neurosci Rep 2022; 14:185-194. [PMID: 36824667 PMCID: PMC9941655 DOI: 10.1016/j.ibneur.2022.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/15/2022] [Indexed: 10/15/2022] Open
Abstract
Spinal cord injury (SCI) leads to devastating physical consequences, such as severe sensorimotor dysfunction even lifetime disability, by damaging the corticospinal system. The conventional opinion that SCI is intractable due to the poor regeneration of neurons in the adult central nervous system (CNS) needs to be revisited as the CNS is capable of considerable plasticity, which underlie recovery from neural injury. Substantial spontaneous neuroplasticity has been demonstrated in the corticospinal motor circuitry following SCI. Some of these plastic changes appear to be beneficial while others are detrimental toward locomotor function recovery after SCI. The beneficial corticospinal plasticity in the spared corticospinal circuits can be harnessed therapeutically by multiple contemporary neuromodulatory approaches, especially the electrical stimulation-based modalities, in an activity-dependent manner to improve functional outcomes in post-SCI rehabilitation. Silent synapse generation and unsilencing contribute to profound neuroplasticity that is implicated in a variety of neurological disorders, thus they may be involved in the corticospinal motor circuit neuroplasticity following SCI. Exploring the underlying mechanisms of silent synapse-mediated neuroplasticity in the corticospinal motor circuitry that may be exploited by neuromodulation will inform a novel direction for optimizing therapeutic repair strategies and rehabilitative interventions in SCI patients.
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Key Words
- AMPARs, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors
- BDNF, brain-derived neurotrophic factor
- BMIs, brain-machine interfaces
- CPG, central pattern generator
- CST, corticospinal tract
- Corticospinal motor circuitry
- DBS, deep brain stimulation
- ESS, epidural spinal stimulation
- MEPs, motor-evoked potentials
- NHPs, non-human primates
- NMDARs, N-methyl-d-aspartate receptors
- Neuromodulation
- Neuroplasticity
- PSNs, propriospinal neurons
- Rehabilitation
- SCI, spinal cord injury
- STDP, spike timing-dependent plasticity
- Silent synapses
- Spinal cord injury
- TBS, theta burst stimulation
- TMS, transcranial magnetic stimulation
- TrkB, tropomyosin-related kinase B
- cTBS, continuous TBS
- iTBS, intermittent TBS
- mTOR, mammalian target of rapamycin
- rTMS, repetitive TMS
- tDCS, transcranial direct current stimulation
- tcSCS, transcutaneous spinal cord stimulation
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Affiliation(s)
- Mingcong Chen
- Department of Orthopedics and Traumatology, Shenzhen University General Hospital, Shenzhen, Guangdong 518055, China
| | - Zuxin Chen
- Shenzhen Key Laboratory of Drug Addiction, Shenzhen Neher Neural Plasticity Laboratory, the Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences (CAS); Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, Guangdong 518055, China
| | - Xiao Xiao
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Ministry of Education; Behavioral and Cognitive Neuroscience Center, Institute of Science and Technology for Brain-Inspired Intelligence; MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China
| | - Libing Zhou
- Guangdong-Hongkong-Macau CNS Regeneration Institute of Jinan University, Key Laboratory of CNS Regeneration (Jinan University)-Ministry of Education, Guangzhou, Guangdong 510632, China
| | - Rao Fu
- Department of Anatomy, School of Medicine, Sun Yat-sen University, Shenzhen, Guangdong 518100, China
| | - Xian Jiang
- Institute of Neurological and Psychiatric Disorder, Shenzhen Bay laboratory, Shenzhen, Guangdong 518000, China
| | - Mao Pang
- Department of Spine Surgery, the Third Affiliated Hospital of Sun Yat-sen University, Guangdong Provincial Center for Engineering and Technology Research of Minimally Invasive Spine Surgery, Guangzhou, Guangdong 510630, China
| | - Jianxun Xia
- Department of Basic Medical Sciences, Yunkang School of Medicine and Health, Nanfang College, Guangzhou, Guangdong 510970, China,Corresponding author.
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16
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Pollina L, Vallone F, Ottaviani MM, Strauss I, Carlucci L, Recchia FA, Micera S, Moccia S. A lightweight learning-based decoding algorithm for intraneural vagus nerve activity classification in pigs. J Neural Eng 2022; 19. [PMID: 35896098 DOI: 10.1088/1741-2552/ac84ab] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Accepted: 07/27/2022] [Indexed: 11/12/2022]
Abstract
OBJECTIVE Bioelectronic medicine is an emerging field that aims at developing closed-loop neuromodulation protocols for the autonomic nervous system (ANS) to treat a wide range of disorders. When designing a closed-loop protocol for real time modulation of the ANS, the computational execution time and the memory and power demands of the decoding step are important factors to consider. In the context of cardiovascular and respiratory diseases, these requirements may partially explain why closed-loop clinical neuromodulation protocols that adapt stimulation parameters on patient's clinical characteristics are currently missing. APPROACH Here, we developed a lightweight learning-based decoder for the classification of cardiovascular and respiratory functional challenges from neural signals acquired through intraneural electrodes implanted in the cervical vagus nerve (VN) of 5 anaesthetized pigs. Our algorithm is based on signal temporal windowing, 9 handcrafted features, and Random Forest (RF) model for classification. Temporal windowing ranging from 50 ms to 1 sec, compatible in duration with cardio-respiratory dynamics, was applied to the data in order to mimic a pseudo real-time scenario. MAIN RESULTS We were able to achieve high balanced accuracy (BA) values over the whole range of temporal windowing duration. We identified 500 ms as the optimal temporal windowing duration for both BA values and computational execution time processing, achieving more than 86% for BA and a computational execution time of only ∼6.8 ms. Our algorithm outperformed in terms of balanced accuracy and computational execution time a state of the art decoding algorithm tested on the same dataset [1]. We found that RF outperformed other machine learning models such as Support Vector Machines, K-Nearest Neighbors, and Multi-Layer Perceptrons. SIGNIFICANCE Our approach could represent an important step towards the implementation of a closed-loop neuromodulation protocol relying on a single intraneural interface able to perform real-time decoding tasks and selective modulation of the VN.
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Affiliation(s)
- Leonardo Pollina
- Sant'Anna School of Advanced Studies, P.za Martiri della Liberta', 33, Pisa, 56127, ITALY
| | - Fabio Vallone
- Sant'Anna School of Advanced Studies, P.za Martiri della Liberta', 33, Pisa, 56127, ITALY
| | - Matteo M Ottaviani
- Scuola Superiore Sant'Anna, Istituto di Scienze Della Vita (ISV), P.za Martiri della Liberta', 33, Pisa, 56127, ITALY
| | - Ivo Strauss
- Scuola Superiore Sant'Anna, P.za Martiri della Libertà 33, Pisa, 56127, ITALY
| | - Lucia Carlucci
- Scuola Superiore Sant'Anna, Istituto di Scienze Della Vita (ISV), P.zza Martiri della Libertà 33, Pisa, 56127, ITALY
| | - Fabio A Recchia
- Scuola Superiore Sant'Anna, Istituto di Scienze Della Vita (ISV), P.za Martiri della Libertà 33, Pisa, 56127, ITALY
| | - Silvestro Micera
- Scuola Superiore Sant'Anna, P.za Martiri della Liberta', 33, Pisa, Toscana, 56127, ITALY
| | - Sara Moccia
- Scuola Superiore Sant'Anna, P.za Martiri della Liberta', 33, Pisa, 56127, ITALY
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17
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Pollina L, Vallone F, Ottaviani MM, Strauss I, Recchia FA, Moccia S, Micera S. A fast and accurate learning-based decoding algorithm for the classification of cardiovascular and respiratory challenges using intraneural electrodes in the pig vagus nerve. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:1757-1760. [PMID: 36085876 DOI: 10.1109/embc48229.2022.9871818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Bioelectronic medicine is a new approach for developing closed-loop neuromodulation protocols on the peripheral nervous system (PNS) to treat a wide range of disorders currently treated with pharmacological approaches. Algorithms need to have low computational cost in order to acquire, process and model data for the modulation of the PNS in real time. Here, we present a fast learning-based decoding algorithm for the classification of cardiovascular and respiratory functional alterations (i.e., challenges) by using neural signals recorded from intraneural electrodes implanted in the vagus nerve of 5 pigs. Our algorithm relies on 9 handcrafted features, extracted following signal temporal windowing, and a multi-layer perceptron (MLP) for feature classification. We achieved fast and accurate classification of the challenges, with a computational time for feature extraction and prediction lower than 1.5 ms. The MLP achieved a balanced accuracy higher than 80 % for all recordings. Our algorithm could represent a step towards the development of a closed-loop system based on a single intraneural interface with both the potential of real time classification and selective modulation of the PNS.
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18
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Wada M, Noda Y, Iwata Y, Tsugawa S, Yoshida K, Tani H, Hirano Y, Koike S, Sasabayashi D, Katayama H, Plitman E, Ohi K, Ueno F, Caravaggio F, Koizumi T, Gerretsen P, Suzuki T, Uchida H, Müller DJ, Mimura M, Remington G, Grace AA, Graff-Guerrero A, Nakajima S. Dopaminergic dysfunction and excitatory/inhibitory imbalance in treatment-resistant schizophrenia and novel neuromodulatory treatment. Mol Psychiatry 2022; 27:2950-2967. [PMID: 35444257 DOI: 10.1038/s41380-022-01572-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/31/2022] [Accepted: 04/07/2022] [Indexed: 12/13/2022]
Abstract
Antipsychotic drugs are the mainstay in the treatment of schizophrenia. However, one-third of patients do not show adequate improvement in positive symptoms with non-clozapine antipsychotics. Additionally, approximately half of them show poor response to clozapine, electroconvulsive therapy, or other augmentation strategies. However, the development of novel treatment for these conditions is difficult due to the complex and heterogenous pathophysiology of treatment-resistant schizophrenia (TRS). Therefore, this review provides key findings, potential treatments, and a roadmap for future research in this area. First, we review the neurobiological pathophysiology of TRS, particularly the dopaminergic, glutamatergic, and GABAergic pathways. Next, the limitations of existing and promising treatments are presented. Specifically, this article focuses on the therapeutic potential of neuromodulation, including electroconvulsive therapy, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, and deep brain stimulation. Finally, we propose multivariate analyses that integrate various perspectives of the pathogenesis, such as dopaminergic dysfunction and excitatory/inhibitory imbalance, thereby elucidating the heterogeneity of TRS that could not be obtained by conventional statistics. These analyses can in turn lead to a precision medicine approach with closed-loop neuromodulation targeting the detected pathophysiology of TRS.
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Affiliation(s)
- Masataka Wada
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yoshihiro Noda
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yusuke Iwata
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Sakiko Tsugawa
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Kazunari Yoshida
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Azrieli Adult Neurodevelopmental Centre, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Hideaki Tani
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Yoji Hirano
- Department of Neuropsychiatry, Kyushu University, Fukuoka, Japan.,Neural Dynamics Laboratory, Research Service, VA Boston Healthcare System, and Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Shinsuke Koike
- Center for Evolutionary Cognitive Sciences, Graduate School of Art and Sciences, The University of Tokyo, Tokyo, Japan
| | - Daiki Sasabayashi
- Department of Neuropsychiatry, University of Toyama Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan.,Research Center for Idling Brain Science, University of Toyama, Toyama, Japan
| | - Haruyuki Katayama
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Eric Plitman
- Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Kazutaka Ohi
- Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
| | - Fumihiko Ueno
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Fernando Caravaggio
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada
| | - Teruki Koizumi
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan.,Department of Psychiatry, National Hospital Organization Shimofusa Psychiatric Medical Center, Chiba, Japan
| | - Philip Gerretsen
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Takefumi Suzuki
- Department of Neuropsychiatry, University of Yamanashi Faculty of Medicine, Yamanashi, Japan
| | - Hiroyuki Uchida
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Daniel J Müller
- Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Masaru Mimura
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan
| | - Gary Remington
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Anthony A Grace
- Departments of Neuroscience, Psychiatry and Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ariel Graff-Guerrero
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.,Institute of Medical Science, University of Toronto, Toronto, ON, Canada.,Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Shinichiro Nakajima
- Department of Neuropsychiatry, Keio University, School of Medicine, Tokyo, Japan. .,Brain Health Imaging Centre, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
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19
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Closed-Loop Systems in Neuromodulation. Neurosurg Clin N Am 2022; 33:297-303. [DOI: 10.1016/j.nec.2022.02.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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20
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Wang L, Wang Y, Wang Y, Wang F, Zhang J, Li S, Wu M, Li L, Rong P. Transcutaneous auricular vagus nerve stimulators: a review of past, present and future devices. Expert Rev Med Devices 2021; 19:43-61. [PMID: 34937487 DOI: 10.1080/17434440.2022.2020095] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION As an emerging neuromodulation therapy, transcutaneous auricular vagus nerve stimulation (taVNS) has been proven to be safe and effective for epilepsy, major depressive disorders, insomnia, glucose metabolic disorders, pain, stroke, post stroke rehabilitation, anxiety, fear, cognitive impairment, cardiovascular disorders, tinnitus, Prader-Willi Syndrome and COVID-19. AREAS COVERED Although the history of taVNS is only two decades, the devices carrying taVNS technique have been constantly updated. Especially in recent years, the development of taVNS devices has presented a new trend. To conclude, the development of taVNS devices has entered a new era, thus the update speed and quality of taVNS devices will be considerably improved in the future. This article reviewed the history and classification of taVNS devices. EXPERT OPINION The correlation between the effectiveness and stimulation parameters from taVNS devices still remains unclear. There is a lack of standard or harmonization among different taVNS devices. Strategies, including further comparative research and establishment of standard, have been recommended in this article to promote the future development of taVNS devices.
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Affiliation(s)
- Lei Wang
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Yu Wang
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Yifei Wang
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Fang Wang
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Jinling Zhang
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Shaoyuan Li
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Mozheng Wu
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Liang Li
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
| | - Peijing Rong
- Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing 100700, China
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21
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Eiber CD, Payne SC, Biscola NP, Havton LA, Keast JR, Osborne PB, Fallon JB. Computational modelling of nerve stimulation and recording with peripheral visceral neural interfaces. J Neural Eng 2021; 18. [PMID: 34740201 DOI: 10.1088/1741-2552/ac36e2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2021] [Accepted: 11/05/2021] [Indexed: 12/30/2022]
Abstract
Objective.Neuromodulation of visceral nerves is being intensively studied for treating a wide range of conditions, but effective translation requires increasing the efficacy and predictability of neural interface performance. Here we use computational models of rat visceral nerve to predict how neuroanatomical variability could affect both electrical stimulation and recording with an experimental planar neural interface.Approach.We developed a hybrid computational pipeline,VisceralNerveEnsembleRecording andStimulation (ViNERS), to couple finite-element modelling of extracellular electrical fields with biophysical simulations of individual axons. Anatomical properties of fascicles and axons in rat pelvic and vagus nerves were measured or obtained from public datasets. To validate ViNERS, we simulated pelvic nerve stimulation and recording with an experimental four-electrode planar array.Main results.Axon diameters measured from pelvic nerve were used to model a population of myelinated and unmyelinated axons and simulate recordings of electrically evoked single-unit field potentials (SUFPs). Across visceral nerve fascicles of increasing size, our simulations predicted an increase in stimulation threshold and a decrease in SUFP amplitude. Simulated threshold changes were dominated by changes in perineurium thickness, which correlates with fascicle diameter. We also demonstrated that ViNERS could simulate recordings of electrically-evoked compound action potentials (ECAPs) that were qualitatively similar to pelvic nerve recording made with the array used for simulation.Significance.We introduce ViNERS as a new open-source computational tool for modelling large-scale stimulation and recording from visceral nerves. ViNERS predicts how neuroanatomical variation in rat pelvic nerve affects stimulation and recording with an experimental planar electrode array. We show ViNERS can simulate ECAPS that capture features of our recordings, but our results suggest the underlying NEURON models need to be further refined and specifically adapted to accurately simulate visceral nerve axons.
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Affiliation(s)
- Calvin D Eiber
- Department of Anatomy and Physiology, The University of Melbourne, Victoria, Australia
| | - Sophie C Payne
- Bionics Institute, East Melbourne, Victoria, Australia.,Medical Bionics Department, The University of Melbourne, Victoria, Australia
| | - Natalia P Biscola
- Icahn School of Medicine at Mount Sinai, New York, United States of America
| | - Leif A Havton
- Icahn School of Medicine at Mount Sinai, New York, United States of America
| | - Janet R Keast
- Department of Anatomy and Physiology, The University of Melbourne, Victoria, Australia
| | - Peregrine B Osborne
- Department of Anatomy and Physiology, The University of Melbourne, Victoria, Australia
| | - James B Fallon
- Bionics Institute, East Melbourne, Victoria, Australia.,Medical Bionics Department, The University of Melbourne, Victoria, Australia
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22
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Rembado I, Song W, Su DK, Levari A, Shupe LE, Perlmutter S, Fetz E, Zanos S. Cortical Responses to Vagus Nerve Stimulation Are Modulated by Brain State in Nonhuman Primates. Cereb Cortex 2021; 31:5289-5307. [PMID: 34151377 PMCID: PMC8567998 DOI: 10.1093/cercor/bhab158] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2020] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 01/30/2023] Open
Abstract
Vagus nerve stimulation (VNS) has been tested as therapy for several brain disorders and as a means to modulate cortical excitability and brain plasticity. Cortical effects of VNS, manifesting as vagal-evoked potentials (VEPs), are thought to arise from activation of ascending cholinergic and noradrenergic systems. However, it is unknown whether those effects are modulated by brain state at the time of stimulation. In 2 freely behaving macaque monkeys, we delivered short trains of 5 pulses to the left cervical vagus nerve at different frequencies (5-300 Hz) while recording local field potentials (LFPs) from sites in contralateral prefrontal, sensorimotor and parietal cortical areas. Brain states were inferred from spectral components of LFPs and the presence of overt movement: active awake, resting awake, REM sleep and NREM sleep. VNS elicited VEPs in all sampled cortical areas. VEPs comprised early (<70 ms), intermediate (70-250 ms) and late (>250 ms) components. The magnitude of the intermediate and late components was largest during NREM sleep and smallest during wakefulness, whereas that of the early component was not modulated by brain state. VEPs during NREM were larger for stimuli delivered at the depolarized phase of ongoing delta oscillations. Higher pulsing frequencies generated larger VEPs. These short VNS trains did not affect brain state transitions during wakefulness or sleep. Our findings suggest that ongoing brain state modulates the evoked effects of VNS on cortical activity. This has implications for the role of ongoing cortical activity and brain state in shaping cortical responses to peripheral stimuli, for the modulation of vagal interoceptive signaling by cortical activity, and for the dose calibration of VNS therapies.
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Affiliation(s)
- Irene Rembado
- MindScope Program, Allen Institute, 615 Westlake Ave N., Seattle, WA 98103, USA
| | - Weiguo Song
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset NY 11030, USA
| | - David K Su
- Providence Regional Medical Center Cranial Joint and Spine Clinic, Everett, WA 98201, USA
| | - Ariel Levari
- Department of Physiology & Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Larry E Shupe
- Department of Physiology & Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Steve Perlmutter
- Department of Physiology & Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Eberhard Fetz
- Department of Physiology & Biophysics, University of Washington, Seattle, WA 98195, USA
| | - Stavros Zanos
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset NY 11030, USA
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23
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Vallone F, Ottaviani MM, Dedola F, Cutrone A, Romeni S, Panarese AM, Bernini F, Cracchiolo M, Strauss I, Gabisonia K, Gorgodze N, Mazzoni A, Recchia FA, Micera S. Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals. J Neural Eng 2021; 18. [PMID: 34153949 DOI: 10.1088/1741-2552/ac0d42] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 06/21/2021] [Indexed: 12/15/2022]
Abstract
Objective. Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop VN stimulation (VNS) would be crucial to increase effectiveness of this approach. Therefore, the extrapolation of useful physiological information from VN electrical activity would represent an invaluable source for single-target applications. Here, we present an advanced decoding algorithm novel to VN studies and properly detecting different functional changes from VN signals.Approach. VN signals were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. We developed a decoding algorithm that combines discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees.Main results. The new decoding algorithm robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. Interestingly our findings suggest that electrodes positioning plays an important role on decoding performances. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles.Significance. This study represents an important step towards the comprehension of VN signaling, paving the way for the development of effective closed-loop VNS systems.
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Affiliation(s)
- Fabio Vallone
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Matteo Maria Ottaviani
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy.,Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Francesca Dedola
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Annarita Cutrone
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Simone Romeni
- Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
| | - Adele Macrí Panarese
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Fabio Bernini
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Marina Cracchiolo
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Ivo Strauss
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Khatia Gabisonia
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Nikoloz Gorgodze
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Fondazione Toscana Gabriele Monasterio, Pisa, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy
| | - Fabio A Recchia
- Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy.,Fondazione Toscana Gabriele Monasterio, Pisa, Italy.,Department of Physiology, Cardiovascular Research Center, Lewis Katz School of Medicine at Temple University, Philadelphia, PA, United States of America
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and Artificial Intelligence, Scuola Superiore Sant'Anna, Pisa, Italy.,Bertarelli Foundation Chair in Translational Neural Engineering, Center for Neuroprosthetics and Institute of Bioengineering, Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
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24
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Datta-Chaudhuri T, Zanos T, Chang EH, Olofsson PS, Bickel S, Bouton C, Grande D, Rieth L, Aranow C, Bloom O, Mehta AD, Civillico G, Stevens MM, Głowacki E, Bettinger C, Schüettler M, Puleo C, Rennaker R, Mohanta S, Carnevale D, Conde SV, Bonaz B, Chernoff D, Kapa S, Berggren M, Ludwig K, Zanos S, Miller L, Weber D, Yoshor D, Steinman L, Chavan SS, Pavlov VA, Al-Abed Y, Tracey KJ. The Fourth Bioelectronic Medicine Summit "Technology Targeting Molecular Mechanisms": current progress, challenges, and charting the future. Bioelectron Med 2021; 7:7. [PMID: 34024277 PMCID: PMC8142479 DOI: 10.1186/s42234-021-00068-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 04/04/2021] [Indexed: 02/06/2023] Open
Abstract
There is a broad and growing interest in Bioelectronic Medicine, a dynamic field that continues to generate new approaches in disease treatment. The fourth bioelectronic medicine summit "Technology targeting molecular mechanisms" took place on September 23 and 24, 2020. This virtual meeting was hosted by the Feinstein Institutes for Medical Research, Northwell Health. The summit called international attention to Bioelectronic Medicine as a platform for new developments in science, technology, and healthcare. The meeting was an arena for exchanging new ideas and seeding potential collaborations involving teams in academia and industry. The summit provided a forum for leaders in the field to discuss current progress, challenges, and future developments in Bioelectronic Medicine. The main topics discussed at the summit are outlined here.
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Affiliation(s)
| | - Theodoros Zanos
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Eric H. Chang
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | | | - Stephan Bickel
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Chad Bouton
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Daniel Grande
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Loren Rieth
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
- University of Utah, Salt Lake City, UT USA
| | - Cynthia Aranow
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Ona Bloom
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Ashesh D. Mehta
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | | | | | | | | | | | | | | | - Saroj Mohanta
- Institute for Cardiovascular Prevention, Ludwig-Maximilians-University, Munich, Germany
| | - Daniela Carnevale
- Sapienza University of Rome, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Silvia V. Conde
- CEDOC, Nova Medical School, Faculdade de Ciências Médicas, Lisbon, Portugal
| | - Bruno Bonaz
- University of Grenoble Alpes, INSERM, Grenoble, France
| | | | | | | | - Kip Ludwig
- University of Wisconsin, Madison, WI USA
| | - Stavros Zanos
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Larry Miller
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Doug Weber
- Carnegie Mellon University, Pittsburgh, PA USA
| | | | | | - Sangeeta S. Chavan
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Valentin A. Pavlov
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Yousef Al-Abed
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
| | - Kevin J. Tracey
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY USA
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25
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Fedotchev A, Parin S, Polevaya S, Zemlianaia A. Human Body Rhythms in the Development of Non-Invasive Methods of Closed-Loop Adaptive Neurostimulation. J Pers Med 2021; 11:437. [PMID: 34065196 PMCID: PMC8161182 DOI: 10.3390/jpm11050437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 05/17/2021] [Accepted: 05/18/2021] [Indexed: 11/21/2022] Open
Abstract
The creation and improvement of non-invasive closed-loop brain stimulation technologies represent an exciting and rapidly expanding field of neuroscience. To identify the appropriate way to close the feedback loop in adaptive neurostimulation procedures, it was previously proposed to use on-line automatic sensory stimulation with the parameters modulated by the patient's own rhythmical processes, such as respiratory rate, heart rate, and electroencephalogram (EEG) rhythms. The current paper aims to analyze several recent studies demonstrating further development in this line of research. The advantages of using automatic closed-loop feedback from human endogenous rhythms in non-invasive adaptive neurostimulation procedures have been demonstrated for relaxation assistance, for the correction of stress-induced functional disturbances, for anxiety management, and for the cognitive rehabilitation of an individual. Several distinctive features of the approach are noted to delineate its further development.
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Affiliation(s)
- Alexander Fedotchev
- Institute of Cell Biophysics, Russian Academy of Sciences, 3 Institutskaya St., Pushchino, 142290 Moscow Region, Russia
| | - Sergey Parin
- Lobachevsky State University of Nizhni Novgorod, 23 Prospekt Gagarina, 603950 Nizhny Novgorod, Russia; (S.P.); (S.P.)
| | - Sofia Polevaya
- Lobachevsky State University of Nizhni Novgorod, 23 Prospekt Gagarina, 603950 Nizhny Novgorod, Russia; (S.P.); (S.P.)
| | - Anna Zemlianaia
- Moscow Research Institute of Psychiatry, Branch of the Serbsky’ National Medical Research Center of Psychiatry and Narcology, Russian Ministry of Health, 3 Poteshnaya St., 107076 Moscow, Russia;
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26
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Tan SZK, Neoh J, Lawrence AJ, Wu EX, Lim LW. Prelimbic Cortical Stimulation Improves Spatial Memory Through Distinct Patterns of Hippocampal Gene Expression in Aged Rats. Neurotherapeutics 2020; 17:2054-2068. [PMID: 32816221 PMCID: PMC7851284 DOI: 10.1007/s13311-020-00913-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Dementia poses major health challenges worldwide, yet current treatments are faced with issues of efficacy and toxicity. Deep brain stimulation (DBS) is a promising non-pharmacological treatment for dementia, but most DBS studies use young healthy animals, which may not be aetiologically relevant. In this study, we used an aged rat model in which cognitive decline occurs through a natural ageing process. We used a Morris water maze (MWM) to determine the effects of prelimbic cortex (PrL) DBS on memory in aged rats. To investigate the underlying mechanisms of the effects of DBS, we carried out microarray, quantitative PCR analysis, and mass spectrometry to detect gene expression and neurotransmitter changes in the hippocampus. We showed PrL DBS improved the performance in MWM, with related distinct patterns of gene expression involving G protein-coupled receptor pathways. We further found neurotransmitter changes in the dorsal hippocampus, which corroborated and extended the microarray findings. Our results suggest that non-neurogenesis pathways play roles in the effects of DBS. Further studies are needed to investigate the effects of DBS on memory beyond neurogenesis and to consider the highlighted pathways suggested by our data.
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Affiliation(s)
- Shawn Zheng Kai Tan
- Neuromodulation Laboratory, School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR China
| | - Joveen Neoh
- Neuromodulation Laboratory, School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR China
| | - Andrew John Lawrence
- Behavioural Neuroscience Division, Florey Institute of Neuroscience and Mental Health, Parkville, VIC Australia
| | - Ed Xuekui Wu
- Department of Electrical and Electronic Engineering, The University of Hong Kong, Hong Kong, SAR China
| | - Lee Wei Lim
- Neuromodulation Laboratory, School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, SAR China
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27
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Chang YC, Cracchiolo M, Ahmed U, Mughrabi I, Gabalski A, Daytz A, Rieth L, Becker L, Datta-Chaudhuri T, Al-Abed Y, Zanos TP, Zanos S. Quantitative estimation of nerve fiber engagement by vagus nerve stimulation using physiological markers. Brain Stimul 2020; 13:1617-1630. [PMID: 32956868 DOI: 10.1016/j.brs.2020.09.002] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Revised: 07/31/2020] [Accepted: 09/04/2020] [Indexed: 11/29/2022] Open
Abstract
BACKGROUND Cervical vagus nerve stimulation (VNS) is an emerging bioelectronic treatment for brain, metabolic, cardiovascular and immune disorders. Its desired and off-target effects are mediated by different nerve fiber populations and knowledge of their engagement could guide calibration and monitoring of VNS therapies. OBJECTIVE Stimulus-evoked compound action potentials (eCAPs) directly provide fiber engagement information but are currently not feasible in humans. A method to estimate fiber engagement through common, noninvasive physiological readouts could be used in place of eCAP measurements. METHODS In anesthetized rats, we recorded eCAPs while registering acute physiological response markers to VNS: cervical electromyography (EMG), changes in heart rate (ΔHR) and breathing interval (ΔBI). Quantitative models were established to capture the relationship between A-, B- and C-fiber type activation and those markers, and to quantitatively estimate fiber activation from physiological markers and stimulation parameters. RESULTS In bivariate analyses, we found that EMG correlates with A-fiber, ΔHR with B-fiber and ΔBI with C-fiber activation, in agreement with known physiological functions of the vagus. We compiled multivariate models for quantitative estimation of fiber engagement from these markers and stimulation parameters. Finally, we compiled frequency gain models that allow estimation of fiber engagement at a wide range of VNS frequencies. Our models, after calibration in humans, could provide noninvasive estimation of fiber engagement in current and future therapeutic applications of VNS.
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Affiliation(s)
- Yao-Chuan Chang
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Marina Cracchiolo
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA; The BioRobotics Institute and Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, Pisa, 56127, Italy
| | - Umair Ahmed
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Ibrahim Mughrabi
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Arielle Gabalski
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Anna Daytz
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Loren Rieth
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Lance Becker
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Timir Datta-Chaudhuri
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Yousef Al-Abed
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Theodoros P Zanos
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA
| | - Stavros Zanos
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY, 11030, USA.
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28
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Nagel SJ, Hsieh J, Machado AG, Frizon LA, Howard MA, Gillies GT, Wilson S. Biomarker Optimization of Spinal Cord Stimulation Therapies. Neuromodulation 2020; 24:3-12. [PMID: 32881257 DOI: 10.1111/ner.13252] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 06/18/2020] [Accepted: 06/29/2020] [Indexed: 11/30/2022]
Abstract
OBJECTIVES We are in the process of designing and testing an intradural stimulation device that will shorten the distance between the location of the electrode array and the targeted neural tissue, thus improving the efficacy of electrical current delivery. Identifying a biomarker that accurately reflects the response to this intervention is highly valued because of the potential to optimize interventional parameters or predict a response before it is clinically measurable. In this report, we summarize the findings pertaining to the study of biomarkers so that we and others will have an up-to-date reference that critically evaluates the current approaches and select one or several for testing during the development of our device. MATERIALS AND METHODS We have conducted a broad survey of the existing literature to catalogue the biomarkers that could be coupled to intradural spinal cord stimulation. We describe in detail some of the most promising biomarkers, existing limitations, and suitability to managing chronic pain. RESULTS Chronic, intractable pain is an all-encompassing condition that is incurable. Many treatments for managing chronic pain are nonspecific in action and intermittently administered; therefore, patients are particularly susceptible to large fluctuations in pain control over the course of a day. The absence of a reliable biomarker challenges assessment of therapeutic efficacy and contributes to either incomplete and inconsistent pain relief or, alternatively, intolerable side effects. Fluctuations in metabolites or inflammatory markers, signals captured during dynamic imaging, and genomics will likely have a role in governing how a device is modulated. CONCLUSIONS Efforts to identify one or more biomarkers are well underway with some preliminary evidence supporting their efficacy. This has far-reaching implications, including improved outcomes, fewer adverse events, harmonization of treatment and individuals, performance gains, and cost savings. We anticipate that novel biomarkers will be used widely to manage chronic pain.
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Affiliation(s)
- Sean J Nagel
- Center for Neurological Restoration, Cleveland Clinic, Cleveland, OH, USA
| | - Jason Hsieh
- Center for Neurological Restoration, Cleveland Clinic, Cleveland, OH, USA
| | - Andre G Machado
- Center for Neurological Restoration, Cleveland Clinic, Cleveland, OH, USA
| | - Leonardo A Frizon
- Department of Neurosurgery, Hospital Marcelino Champagnat, Curitiba, PR, Brazil
| | - Matthew A Howard
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
| | - George T Gillies
- Department of Mechanical and Aerospace Engineering, University of Virginia, Charlottesville, VA, USA
| | - Saul Wilson
- Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, USA
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29
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Beuter A, Balossier A, Vassal F, Hemm S, Volpert V. Cortical stimulation in aphasia following ischemic stroke: toward model-guided electrical neuromodulation. BIOLOGICAL CYBERNETICS 2020; 114:5-21. [PMID: 32020368 DOI: 10.1007/s00422-020-00818-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Accepted: 01/28/2020] [Indexed: 06/10/2023]
Abstract
The aim of this paper is to integrate different bodies of research including brain traveling waves, brain neuromodulation, neural field modeling and post-stroke language disorders in order to explore the opportunity of implementing model-guided, cortical neuromodulation for the treatment of post-stroke aphasia. Worldwide according to WHO, strokes are the second leading cause of death and the third leading cause of disability. In ischemic stroke, there is not enough blood supply to provide enough oxygen and nutrients to parts of the brain, while in hemorrhagic stroke, there is bleeding within the enclosed cranial cavity. The present paper focuses on ischemic stroke. We first review accumulating observations of traveling waves occurring spontaneously or triggered by external stimuli in healthy subjects as well as in patients with brain disorders. We examine the putative functions of these waves and focus on post-stroke aphasia observed when brain language networks become fragmented and/or partly silent, thus perturbing the progression of traveling waves across perilesional areas. Secondly, we focus on a simplified model based on the current literature in the field and describe cortical traveling wave dynamics and their modulation. This model uses a biophysically realistic integro-differential equation describing spatially distributed and synaptically coupled neural networks producing traveling wave solutions. The model is used to calculate wave parameters (speed, amplitude and/or frequency) and to guide the reconstruction of the perturbed wave. A stimulation term is included in the model to restore wave propagation to a reasonably good level. Thirdly, we examine various issues related to the implementation model-guided neuromodulation in the treatment of post-stroke aphasia given that closed-loop invasive brain stimulation studies have recently produced encouraging results. Finally, we suggest that modulating traveling waves by acting selectively and dynamically across space and time to facilitate wave propagation is a promising therapeutic strategy especially at a time when a new generation of closed-loop cortical stimulation systems is about to arrive on the market.
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Affiliation(s)
- Anne Beuter
- Bordeaux INP, University of Bordeaux, Bordeaux, France.
| | - Anne Balossier
- Service de neurochirurgie fonctionnelle et stéréotaxique, AP-HM La Timone, Aix-Marseille University, Marseille, France
| | - François Vassal
- INSERM U1028 Neuropain, UMR 5292, Centre de Recherche en Neurosciences, Universités Lyon 1 et Saint-Etienne, Saint-Étienne, France
- Service de Neurochirurgie, Hôpital Nord, Centre Hospitalier Universitaire de Saint-Etienne, Saint-Étienne, France
| | - Simone Hemm
- School of Life Sciences, Institute for Medical Engineering and Medical Informatics, University of Applied Sciences and Arts Northwestern Switzerland, 4132, Muttenz, Switzerland
| | - Vitaly Volpert
- Institut Camille Jordan, UMR 5208 CNRS, University Lyon 1, 69622, Villeurbanne, France
- INRIA Team Dracula, INRIA Lyon La Doua, 69603, Villeurbanne, France
- People's Friendship University of Russia (RUDN University), Miklukho-Maklaya St, Moscow, Russian Federation, 117198
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30
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Ntiloudi D, Qanud K, Tomaio JN, Giannakoulas G, Al-Abed Y, Zanos S. Pulmonary arterial hypertension: the case for a bioelectronic treatment. Bioelectron Med 2019; 5:20. [PMID: 32232109 PMCID: PMC7098229 DOI: 10.1186/s42234-019-0036-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Accepted: 11/08/2019] [Indexed: 12/16/2022] Open
Abstract
Pulmonary arterial hypertension (PAH) is a rare disease of unknown etiology that progresses to right ventricular failure. It has a complex pathophysiology, which involves an imbalance between vasoconstrictive and vasodilative processes in the pulmonary circulation, pulmonary vasoconstriction, vascular and right ventricular remodeling, systemic inflammation, and autonomic imbalance, with a reduced parasympathetic and increased sympathetic tone. Current pharmacological treatments for PAH include several classes of drugs that target signaling pathways in vascular biology and cardiovascular physiology, but they can have severe unwanted effects and they do not typically stop the progression of the disease. Pulmonary artery denervation has been tested clinically as a method to suppress sympathetic overactivation, however it is a nonspecific and irreversible intervention. Bioelectronic medicine, in particular vagus nerve stimulation (VNS), has been used in cardiovascular disorders like arrhythmias, heart failure and arterial hypertension and could, in principle, be tested as a treatment in PAH. VNS can produce pulmonary vasodilation and renormalize right ventricular function, via activation of pulmonary and cardiac vagal fibers. It can suppress systemic inflammation, via activation of fibers that innervate the spleen. Finally, VNS can gradually restore the balance between parasympathetic and sympathetic tone by regulating autonomic reflexes. Preclinical studies support the feasibility of using VNS in PAH. However, there are challenges with such an approach, arising from the need to affect a relatively small number of relevant vagal fibers, and the potential for unwanted cardiac and noncardiac effects of VNS in this sensitive patient population.
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Affiliation(s)
- Despοina Ntiloudi
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY 11030 USA.,2Department of Cardiology, AHEPA University Hospital, Thessaloniki, Greece
| | - Khaled Qanud
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY 11030 USA
| | - Jacquelyn-Nicole Tomaio
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY 11030 USA
| | | | - Yousef Al-Abed
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY 11030 USA
| | - Stavros Zanos
- Institute of Bioelectronic Medicine, Feinstein Institutes for Medical Research, Manhasset, NY 11030 USA
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