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Chauhan K, Neiman AB, Tass PA. Synaptic reorganization of synchronized neuronal networks with synaptic weight and structural plasticity. PLoS Comput Biol 2024; 20:e1012261. [PMID: 38980898 DOI: 10.1371/journal.pcbi.1012261] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 06/20/2024] [Indexed: 07/11/2024] Open
Abstract
Abnormally strong neural synchronization may impair brain function, as observed in several brain disorders. We computationally study how neuronal dynamics, synaptic weights, and network structure co-emerge, in particular, during (de)synchronization processes and how they are affected by external perturbation. To investigate the impact of different types of plasticity mechanisms, we combine a network of excitatory integrate-and-fire neurons with different synaptic weight and/or structural plasticity mechanisms: (i) only spike-timing-dependent plasticity (STDP), (ii) only homeostatic structural plasticity (hSP), i.e., without weight-dependent pruning and without STDP, (iii) a combination of STDP and hSP, i.e., without weight-dependent pruning, and (iv) a combination of STDP and structural plasticity (SP) that includes hSP and weight-dependent pruning. To accommodate the diverse time scales of neuronal firing, STDP, and SP, we introduce a simple stochastic SP model, enabling detailed numerical analyses. With tools from network theory, we reveal that structural reorganization may remarkably enhance the network's level of synchrony. When weaker contacts are preferentially eliminated by weight-dependent pruning, synchrony is achieved with significantly sparser connections than in randomly structured networks in the STDP-only model. In particular, the strengthening of contacts from neurons with higher natural firing rates to those with lower rates and the weakening of contacts in the opposite direction, followed by selective removal of weak contacts, allows for strong synchrony with fewer connections. This activity-led network reorganization results in the emergence of degree-frequency, degree-degree correlations, and a mixture of degree assortativity. We compare the stimulation-induced desynchronization of synchronized states in the STDP-only model (i) with the desynchronization of models (iii) and (iv). The latter require stimuli of significantly higher intensity to achieve long-term desynchronization. These findings may inform future pre-clinical and clinical studies with invasive or non-invasive stimulus modalities aiming at inducing long-lasting relief of symptoms, e.g., in Parkinson's disease.
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Affiliation(s)
- Kanishk Chauhan
- Department of Physics and Astronomy, Ohio University, Athens, Ohio, United States of America
- Neuroscience Program, Ohio University, Athens, Ohio, United States of America
| | - Alexander B Neiman
- Department of Physics and Astronomy, Ohio University, Athens, Ohio, United States of America
- Neuroscience Program, Ohio University, Athens, Ohio, United States of America
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, California, United States of America
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Wu Y, Hu K, Liu S. Computational models advance deep brain stimulation for Parkinson's disease. NETWORK (BRISTOL, ENGLAND) 2024:1-32. [PMID: 38923890 DOI: 10.1080/0954898x.2024.2361799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 05/25/2024] [Indexed: 06/28/2024]
Abstract
Deep brain stimulation(DBS) has become an effective intervention for advanced Parkinson's disease(PD), but the exact mechanism of DBS is still unclear. In this review, we discuss the history of DBS, the anatomy and internal architecture of the basal ganglia (BG), the abnormal pathological changes of the BG in PD, and how computational models can help understand and advance DBS. We also describe two types of models: mathematical theoretical models and clinical predictive models. Mathematical theoretical models simulate neurons or neural networks of BG to shed light on the mechanistic principle underlying DBS, while clinical predictive models focus more on patients' outcomes, helping to adapt treatment plans for each patient and advance novel electrode designs. Finally, we provide insights and an outlook on future technologies.
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Affiliation(s)
- Yongtong Wu
- School of Mathematics, South China University of Technology, Guangzhou, Guangdong, China
| | - Kejia Hu
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shenquan Liu
- School of Mathematics, South China University of Technology, Guangzhou, Guangdong, China
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Kromer JA, Tass PA. Simulated dataset on coordinated reset stimulation of homogeneous and inhomogeneous networks of excitatory leaky integrate-and-fire neurons with spike-timing-dependent plasticity. Data Brief 2024; 54:110345. [PMID: 38586130 PMCID: PMC10998034 DOI: 10.1016/j.dib.2024.110345] [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: 02/08/2024] [Accepted: 03/12/2024] [Indexed: 04/09/2024] Open
Abstract
We present simulated data on coordinated reset stimulation (CRS) of plastic neuronal networks. The neuronal network consists of excitatory leaky integrate-and-fire neurons and plasticity is implemented as spike-timing-dependent plasticity (STDP). A synchronized state with strong synaptic connectivity and a desynchronized state with weak synaptic connectivity coexist. CRS may drive the network from the synchronized state into a desynchronized state inducing long-lasting desynchronization effects that persist after cessation of stimulation. This is used to model brain stimulation-induced transitions between a pathological state, with abnormally strong neuronal synchrony, and a physiological state, e.g., in Parkinson's disease. During CRS, a sequence of stimuli is delivered to multiple stimulation sites - called CR sequence. We present simulated data for the analysis of long-lasting desynchronization effects of CRS with shuffled CR sequences versus non-shuffled CR sequences in which the order of stimulus deliveries to the sites remains unchanged throughout the entire stimulation period. Such data are presented for networks with homogeneous synaptic connectivity and networks with inhomogeneous synaptic connectivity. Homogeneous synaptic connectivity refers to a network in which the probability of a synaptic connection does not depend on the pre- and postsynaptic neurons' locations. In contrast, inhomogeneous synaptic connectivity refers to a network in which the probability of a synaptic connection depends on the neurons' locations. The presented neuronal network model was used to analyse the impact of the CR sequences and their shuffling on the long-lasting effects of CRS [1].
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Affiliation(s)
- Justus A Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, United States of America
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, CA, United States of America
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Kromer JA, Tass PA. Coordinated reset stimulation of plastic neural networks with spatially dependent synaptic connections. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1351815. [PMID: 38863734 PMCID: PMC11165135 DOI: 10.3389/fnetp.2024.1351815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/15/2024] [Indexed: 06/13/2024]
Abstract
Background Abnormal neuronal synchrony is associated with several neurological disorders, including Parkinson's disease (PD), essential tremor, dystonia, and epilepsy. Coordinated reset (CR) stimulation was developed computationally to counteract abnormal neuronal synchrony. During CR stimulation, phase-shifted stimuli are delivered to multiple stimulation sites. Computational studies in plastic neural networks reported that CR stimulation drove the networks into an attractor of a stable desynchronized state by down-regulating synaptic connections, which led to long-lasting desynchronization effects that outlasted stimulation. Later, corresponding long-lasting desynchronization and therapeutic effects were found in animal models of PD and PD patients. To date, it is unclear how spatially dependent synaptic connections, as typically observed in the brain, shape CR-induced synaptic downregulation and long-lasting effects. Methods We performed numerical simulations of networks of leaky integrate-and-fire neurons with spike-timing-dependent plasticity and spatially dependent synaptic connections to study and further improve acute and long-term responses to CR stimulation. Results The characteristic length scale of synaptic connections relative to the distance between stimulation sites plays a key role in CR parameter adjustment. In networks with short synaptic length scales, a substantial synaptic downregulation can be achieved by selecting appropriate stimulus-related parameters, such as the stimulus amplitude and shape, regardless of the employed spatiotemporal pattern of stimulus deliveries. Complex stimulus shapes can induce local connectivity patterns in the vicinity of the stimulation sites. In contrast, in networks with longer synaptic length scales, the spatiotemporal sequence of stimulus deliveries is of major importance for synaptic downregulation. In particular, rapid shuffling of the stimulus sequence is advantageous for synaptic downregulation. Conclusion Our results suggest that CR stimulation parameters can be adjusted to synaptic connectivity to further improve the long-lasting effects. Furthermore, shuffling of CR sequences is advantageous for long-lasting desynchronization effects. Our work provides important hypotheses on CR parameter selection for future preclinical and clinical studies.
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Affiliation(s)
- Justus A. Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
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Kumbhare D, Rajagopal M, Toms J, Freelin A, Weistroffer G, McComb N, Karnam S, Azghadi A, Murnane KS, Baron MS, Holloway KL. Deep Brain Stimulation of Nucleus Basalis of Meynert improves learning in rat model of dementia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588271. [PMID: 38645266 PMCID: PMC11030230 DOI: 10.1101/2024.04.05.588271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background Deep brain stimulation (DBS) of the nucleus basalis of Meynert (NBM) has been preliminarily investigated as a potential treatment for dementia. The degeneration of NBM cholinergic neurons is a pathological feature of many forms of dementia. Although stimulation of the NBM has been demonstrated to improve learning, the ideal parameters for NBM stimulation have not been elucidated. This study assesses the differential effects of varying stimulation patterns and duration on learning in a dementia rat model. Methods 192-IgG-saporin (or vehicle) was injected into the NBM to produce dementia in rats. Next, all rats underwent unilateral implantation of a DBS electrode in the NBM. The experimental groups consisted of i-normal, ii-untreated demented, and iii-demented rats receiving NBM DBS. The stimulation paradigms included testing different modes (tonic and burst) and durations (1-hr, 5-hrs, and 24-hrs/day) over 10 daily sessions. Memory was assessed pre- and post-stimulation using two established learning paradigms: novel object recognition (NOR) and auditory operant chamber learning. Results Both normal and stimulated rats demonstrated improved performance in NOR and auditory learning as compared to the unstimulated demented group. The burst stimulation groups performed better than the tonic stimulated group. Increasing the daily stimulation duration to 24-hr did not further improve cognitive performance in an auditory recognition task and degraded the results on a NOR task as compared with 5-hr. Conclusion The present findings suggest that naturalistic NBM burst DBS may offer a potential effective therapy for treating dementia and suggests potential strategies for the reevaluation of current human NBM stimulation paradigms.
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Ng PR, Bush A, Vissani M, McIntyre CC, Richardson RM. Biophysical Principles and Computational Modeling of Deep Brain Stimulation. Neuromodulation 2024; 27:422-439. [PMID: 37204360 DOI: 10.1016/j.neurom.2023.04.471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 04/02/2023] [Accepted: 04/24/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community. OBJECTIVE In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS. RESULTS Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response. CONCLUSION This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.
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Affiliation(s)
| | - Alan Bush
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Matteo Vissani
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, Duke University, Durham, NC, USA
| | - Robert Mark Richardson
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
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Kromer JA, Tass PA. Sequences and their shuffling may crucially impact coordinated reset stimulation - A theoretical study. Brain Stimul 2024; 17:194-196. [PMID: 38346587 DOI: 10.1016/j.brs.2024.02.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 01/29/2024] [Accepted: 02/05/2024] [Indexed: 02/22/2024] Open
Affiliation(s)
- Justus A Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, USA.
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, CA, USA
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Johnson KA, Dosenbach NUF, Gordon EM, Welle CG, Wilkins KB, Bronte-Stewart HM, Voon V, Morishita T, Sakai Y, Merner AR, Lázaro-Muñoz G, Williamson T, Horn A, Gilron R, O'Keeffe J, Gittis AH, Neumann WJ, Little S, Provenza NR, Sheth SA, Fasano A, Holt-Becker AB, Raike RS, Moore L, Pathak YJ, Greene D, Marceglia S, Krinke L, Tan H, Bergman H, Pötter-Nerger M, Sun B, Cabrera LY, McIntyre CC, Harel N, Mayberg HS, Krystal AD, Pouratian N, Starr PA, Foote KD, Okun MS, Wong JK. Proceedings of the 11th Annual Deep Brain Stimulation Think Tank: pushing the forefront of neuromodulation with functional network mapping, biomarkers for adaptive DBS, bioethical dilemmas, AI-guided neuromodulation, and translational advancements. Front Hum Neurosci 2024; 18:1320806. [PMID: 38450221 PMCID: PMC10915873 DOI: 10.3389/fnhum.2024.1320806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/05/2024] [Indexed: 03/08/2024] Open
Abstract
The Deep Brain Stimulation (DBS) Think Tank XI was held on August 9-11, 2023 in Gainesville, Florida with the theme of "Pushing the Forefront of Neuromodulation". The keynote speaker was Dr. Nico Dosenbach from Washington University in St. Louis, Missouri. He presented his research recently published in Nature inn a collaboration with Dr. Evan Gordon to identify and characterize the somato-cognitive action network (SCAN), which has redefined the motor homunculus and has led to new hypotheses about the integrative networks underpinning therapeutic DBS. The DBS Think Tank was founded in 2012 and provides an open platform where clinicians, engineers, and researchers (from industry and academia) can freely discuss current and emerging DBS technologies, as well as logistical and ethical issues facing the field. The group estimated that globally more than 263,000 DBS devices have been implanted for neurological and neuropsychiatric disorders. This year's meeting was focused on advances in the following areas: cutting-edge translational neuromodulation, cutting-edge physiology, advances in neuromodulation from Europe and Asia, neuroethical dilemmas, artificial intelligence and computational modeling, time scales in DBS for mood disorders, and advances in future neuromodulation devices.
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Affiliation(s)
- Kara A. Johnson
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Nico U. F. Dosenbach
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Evan M. Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Cristin G. Welle
- Department of Physiology and Biophysics, University of Colorado School of Medicine, Aurora, CO, United States
- Department of Neurosurgery, University of Colorado School of Medicine, Aurora, CO, United States
| | - Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Helen M. Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Valerie Voon
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Takashi Morishita
- Department of Neurosurgery, Fukuoka University Faculty of Medicine, Fukuoka, Japan
| | - Yuki Sakai
- ATR Brain Information Communication Research Laboratory Group, Kyoto, Japan
- Department of Psychiatry, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Amanda R. Merner
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
| | - Gabriel Lázaro-Muñoz
- Center for Bioethics, Harvard Medical School, Boston, MA, United States
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Theresa Williamson
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States
| | - Andreas Horn
- Department of Neurology, Center for Brain Circuit Therapeutics, Harvard Medical School, Brigham & Women's Hospital, Boston, MA, United States
- MGH Neurosurgery and Center for Neurotechnology and Neurorecovery (CNTR) at MGH Neurology Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany
| | | | | | - Aryn H. Gittis
- Biological Sciences and Center for Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt- Universität zu Berlin, Berlin, Germany
| | - Simon Little
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Nicole R. Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Sameer A. Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease, Division of Neurology, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network (UHN), University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, Toronto, ON, Canada
| | - Abbey B. Holt-Becker
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Robert S. Raike
- Restorative Therapies Group Implantables, Research, and Core Technology, Medtronic Inc., Minneapolis, MN, United States
| | - Lisa Moore
- Boston Scientific Neuromodulation Corporation, Valencia, CA, United States
| | | | - David Greene
- NeuroPace, Inc., Mountain View, CA, United States
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Lothar Krinke
- Newronika SPA, Milan, Italy
- Department of Neuroscience, West Virginia University, Morgantown, WV, United States
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Hagai Bergman
- Edmond and Lily Safar Center (ELSC) for Brain Research and Department of Medical Neurobiology (Physiology), Institute of Medical Research Israel-Canada, Hebrew University of Jerusalem, Jerusalem, Israel
- Department of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel
| | - Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Laura Y. Cabrera
- Neuroethics, Department of Engineering Science and Mechanics, Philosophy, and Bioethics, and the Rock Ethics Institute, Pennsylvania State University, State College, PA, United States
| | - Cameron C. McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, United States
- Department of Neurosurgery, Duke University, Durham, NC, United States
| | - Noam Harel
- Department of Radiology, Center for Magnetic Resonance Research, University of Minnesota, Minneapolis, MN, United States
| | - Helen S. Mayberg
- Department of Neurology, Neurosurgery, Psychiatry, and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Andrew D. Krystal
- Departments of Psychiatry and Behavioral Science and Neurology, University of California, San Francisco, San Francisco, CA, United States
| | - Nader Pouratian
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Philip A. Starr
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, United States
| | - Kelly D. Foote
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurosurgery, University of Florida, Gainesville, FL, United States
| | - Michael S. Okun
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
| | - Joshua K. Wong
- Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
- Department of Neurology, University of Florida, Gainesville, FL, United States
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Rosenblum M. Feedback control of collective dynamics in an oscillator population with time-dependent connectivity. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1358146. [PMID: 38371453 PMCID: PMC10869593 DOI: 10.3389/fnetp.2024.1358146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 01/23/2024] [Indexed: 02/20/2024]
Abstract
We present a numerical study of pulsatile feedback-based control of synchrony level in a highly-interconnected oscillatory network. We focus on a nontrivial case when the system is close to the synchronization transition point and exhibits collective rhythm with strong amplitude modulation. We pay special attention to technical but essential steps like causal real-time extraction of the signal of interest from a noisy measurement and estimation of instantaneous phase and amplitude. The feedback loop's parameters are tuned automatically to suppress synchrony. Though the study is motivated by neuroscience, the results are relevant to controlling oscillatory activity in ensembles of various natures and, thus, to the rapidly developing field of network physiology.
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Affiliation(s)
- Michael Rosenblum
- Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany
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10
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Zeng Z, Huang P, Lin Z, Pan Y, Wan X, Zhang C, Sun B, Li D. Rescue subthalamic stimulation after unsatisfactory outcome of pallidal stimulation in Parkinson's disease: a case series and review. Front Aging Neurosci 2024; 15:1323541. [PMID: 38264547 PMCID: PMC10803461 DOI: 10.3389/fnagi.2023.1323541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 12/20/2023] [Indexed: 01/25/2024] Open
Abstract
Background Subthalamic nucleus (STN) and globus pallidus interna (GPi) are two main structures primarily targeted by deep brain stimulation (DBS) to treat advanced Parkinson's disease (PD). A subset of cases with unsatisfactory outcomes may benefit from rescue DBS surgery targeting another structure, while these patients' characteristics have not been well described and this phenomenon has not been well reviewed. Methods This monocentric retrospective study included patients with PD, who underwent rescue STN DBS following an unsatisfactory outcome of the initial bilateral GPi DBS in a retrospective manner. A short review of the current literature was conducted to report the clinical outcome of rescue DBS surgeries. Results Eight patients were identified, and six of them were included in this study. The rescue STN DBS was performed 19.8 months after the initial GPi DBS. After 8.8 months from the rescue STN DBS, patients showed a significant off-medication improvement by 29.2% in motor symptoms compared to initial GPi DBS. Non-motor symptoms and the health-related quality of life were also significantly improved. Conclusion Our findings suggest that the rescue STN DBS may improve off-medication motor and non-motor symptoms and quality of life in patients with failure of initial GPi DBS. The short review of the current literature showed that the target switching from GPi to STN was mainly due to poor initial outcomes and was performed by target substitution, whereas the switching from STN to GPi was mainly due to a gradual waning of benefits, long-term axial symptoms, dyskinesia, and dystonia and was performed by target addition.
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Affiliation(s)
| | | | | | | | | | | | | | - Dianyou Li
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Widge AS. Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity. Neuropsychopharmacology 2024; 49:138-149. [PMID: 37415081 PMCID: PMC10700701 DOI: 10.1038/s41386-023-01643-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 05/28/2023] [Accepted: 06/20/2023] [Indexed: 07/08/2023]
Abstract
Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.
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Affiliation(s)
- Alik S Widge
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
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12
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Xu W, Wang J, Li XN, Liang J, Song L, Wu Y, Liu Z, Sun B, Li WG. Neuronal and synaptic adaptations underlying the benefits of deep brain stimulation for Parkinson's disease. Transl Neurodegener 2023; 12:55. [PMID: 38037124 PMCID: PMC10688037 DOI: 10.1186/s40035-023-00390-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/19/2023] [Indexed: 12/02/2023] Open
Abstract
Deep brain stimulation (DBS) is a well-established and effective treatment for patients with advanced Parkinson's disease (PD), yet its underlying mechanisms remain enigmatic. Optogenetics, primarily conducted in animal models, provides a unique approach that allows cell type- and projection-specific modulation that mirrors the frequency-dependent stimulus effects of DBS. Opto-DBS research in animal models plays a pivotal role in unraveling the neuronal and synaptic adaptations that contribute to the efficacy of DBS in PD treatment. DBS-induced neuronal responses rely on a complex interplay between the distributions of presynaptic inputs, frequency-dependent synaptic depression, and the intrinsic excitability of postsynaptic neurons. This orchestration leads to conversion of firing patterns, enabling both antidromic and orthodromic modulation of neural circuits. Understanding these mechanisms is vital for decoding position- and programming-dependent effects of DBS. Furthermore, patterned stimulation is emerging as a promising strategy yielding long-lasting therapeutic benefits. Research on the neuronal and synaptic adaptations to DBS may pave the way for the development of more enduring and precise modulation patterns. Advanced technologies, such as adaptive DBS or directional electrodes, can also be integrated for circuit-specific neuromodulation. These insights hold the potential to greatly improve the effectiveness of DBS and advance PD treatment to new levels.
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Affiliation(s)
- Wenying Xu
- Department of Rehabilitation Medicine, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jie Wang
- Department of Rehabilitation Medicine, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
- Department of Neurology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China
| | - Xin-Ni Li
- Department of Rehabilitation Medicine, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Jingxue Liang
- Department of Rehabilitation Medicine, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
- Department of Neurology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China
| | - Lu Song
- Department of Neurology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China
| | - Yi Wu
- Department of Rehabilitation Medicine, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China
| | - Zhenguo Liu
- Department of Neurology, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
| | - Bomin Sun
- Department of Neurosurgery, Center for Functional Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Wei-Guang Li
- Department of Rehabilitation Medicine, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology and Ministry of Education Frontiers Center for Brain Science, Fudan University, Shanghai, 200032, China.
- Ministry of Education-Shanghai Key Laboratory for Children's Environmental Health, Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 200092, China.
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Sandoval-Pistorius SS, Hacker ML, Waters AC, Wang J, Provenza NR, de Hemptinne C, Johnson KA, Morrison MA, Cernera S. Advances in Deep Brain Stimulation: From Mechanisms to Applications. J Neurosci 2023; 43:7575-7586. [PMID: 37940596 PMCID: PMC10634582 DOI: 10.1523/jneurosci.1427-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Revised: 08/14/2023] [Accepted: 08/15/2023] [Indexed: 11/10/2023] Open
Abstract
Deep brain stimulation (DBS) is an effective therapy for various neurologic and neuropsychiatric disorders, involving chronic implantation of electrodes into target brain regions for electrical stimulation delivery. Despite its safety and efficacy, DBS remains an underutilized therapy. Advances in the field of DBS, including in technology, mechanistic understanding, and applications have the potential to expand access and use of DBS, while also improving clinical outcomes. Developments in DBS technology, such as MRI compatibility and bidirectional DBS systems capable of sensing neural activity while providing therapeutic stimulation, have enabled advances in our understanding of DBS mechanisms and its application. In this review, we summarize recent work exploring DBS modulation of target networks. We also cover current work focusing on improved programming and the development of novel stimulation paradigms that go beyond current standards of DBS, many of which are enabled by sensing-enabled DBS systems and have the potential to expand access to DBS.
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Affiliation(s)
| | - Mallory L Hacker
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232
| | - Allison C Waters
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York 10029
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York 10029
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, Minnesota 55455
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas 77030
| | - Coralie de Hemptinne
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida 32608
| | - Kara A Johnson
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, Florida 32608
| | - Melanie A Morrison
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Stephanie Cernera
- Department of Neurological Surgery, University of California-San Francisco, San Francisco, California 94143
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14
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Gülke E, Horn MA, Caffier J, Pinnschmidt H, Hamel W, Moll CKE, Gulberti A, Pötter-Nerger M. Comparison of subthalamic unilateral and bilateral theta burst deep brain stimulation in Parkinson's disease. Front Hum Neurosci 2023; 17:1233565. [PMID: 37868697 PMCID: PMC10585145 DOI: 10.3389/fnhum.2023.1233565] [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: 09/18/2023] [Indexed: 10/24/2023] Open
Abstract
High-frequency, conventional deep brain stimulation (DBS) of the subthalamic nucleus (STN) in Parkinson's disease (PD) is usually applied bilaterally under the assumption of additive effects due to interhemispheric crosstalk. Theta burst stimulation (TBS-DBS) represents a new patterned stimulation mode with 5 Hz interburst and 200 Hz intraburst frequency, whose stimulation effects in a bilateral mode compared to unilateral are unknown. This single-center study evaluated acute motor effects of the most affected, contralateral body side in 17 PD patients with unilateral subthalamic TBS-DBS and 11 PD patients with bilateral TBS-DBS. Compared to therapy absence, both unilateral and bilateral TBS-DBS significantly improved (p < 0.05) lateralized Movement Disorder Society-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III) scores. Bilateral TBS-DBS revealed only slight, but not significant additional effects in comparison to unilateral TBS-DBS on total lateralized motor scores, but on the subitem lower limb rigidity. These results indicate that bilateral TBS-DBS has limited additive beneficial effects compared to unilateral TBS-DBS in the short term.
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Affiliation(s)
- Eileen Gülke
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Martin A. Horn
- Department of Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Julian Caffier
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hans Pinnschmidt
- Institute of Medical Biometry and Epidemiology, University Medical Center, Hamburg-Eppendorf, Hamburg, Germany
| | - Wolfgang Hamel
- Department of Neurosurgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Christian K. E. Moll
- Institute of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Alessandro Gulberti
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Monika Pötter-Nerger
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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15
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Bosley KM, Luo Z, Amoozegar S, Acedillo K, Nakajima K, Johnson LA, Vitek JL, Wang J. Effect of subthalamic coordinated reset deep brain stimulation on Parkinsonian gait. Front Neuroinform 2023; 17:1185723. [PMID: 37692361 PMCID: PMC10483836 DOI: 10.3389/fninf.2023.1185723] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 08/01/2023] [Indexed: 09/12/2023] Open
Abstract
Introduction Coordinated Reset Deep Brain Stimulation (CR DBS) is a novel DBS approach for treating Parkinson's disease (PD) that uses lower levels of burst stimulation through multiple contacts of the DBS lead. Though CR DBS has been demonstrated to have sustained therapeutic effects on rigidity, tremor, bradykinesia, and akinesia following cessation of stimulation, i.e., carryover effect, its effect on Parkinsonian gait has not been well studied. Impaired gait is a disabling symptom of PD, often associated with a higher risk of falling and a reduced quality of life. The goal of this study was to explore the carryover effect of subthalamic CR DBS on Parkinsonian gait. Methods Three non-human primates (NHPs) were rendered Parkinsonian and implanted with a DBS lead in the subthalamic nucleus (STN). For each animal, STN CR DBS was delivered for several hours per day across five consecutive days. A clinical rating scale modified for NHP use (mUPDRS) was administered every morning to monitor the carryover effect of CR DBS on rigidity, tremor, akinesia, and bradykinesia. Gait was assessed quantitatively before and after STN CR DBS. The stride length and swing speed were calculated and compared to the baseline, pre-stimulation condition. Results In all three animals, carryover improvements in rigidity, bradykinesia, and akinesia were observed after CR DBS. Increased swing speed was observed in all the animals; however, improvement in stride length was only observed in NHP B2. In addition, STN CR DBS using two different burst frequencies was evaluated in NHP B2, and differential effects on the mUPDRS score and gait were observed. Discussion Although preliminary, our results indicate that STN CR DBS can improve Parkinsonian gait together with other motor signs when stimulation parameters are properly selected. This study further supports the continued development of CR DBS as a novel therapy for PD and highlights the importance of parameter selection in its clinical application.
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Affiliation(s)
- Kai M. Bosley
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Ziling Luo
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Sana Amoozegar
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Kit Acedillo
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Kanon Nakajima
- Neuroscience Program, Macalester College, Saint Paul, MN, United States
| | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
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16
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Kromer JA, Bokil H, Tass PA. Synaptic network structure shapes cortically evoked spatio-temporal responses of STN and GPe neurons in a computational model. Front Neuroinform 2023; 17:1217786. [PMID: 37675246 PMCID: PMC10477454 DOI: 10.3389/fninf.2023.1217786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/31/2023] [Indexed: 09/08/2023] Open
Abstract
Introduction The basal ganglia (BG) are involved in motor control and play an essential role in movement disorders such as hemiballismus, dystonia, and Parkinson's disease. Neurons in the motor part of the BG respond to passive movement or stimulation of different body parts and to stimulation of corresponding cortical regions. Experimental evidence suggests that the BG are organized somatotopically, i.e., specific areas of the body are associated with specific regions in the BG nuclei. Signals related to the same body part that propagate along different pathways converge onto the same BG neurons, leading to characteristic shapes of cortically evoked responses. This suggests the existence of functional channels that allow for the processing of different motor commands or information related to different body parts in parallel. Neurological disorders such as Parkinson's disease are associated with pathological activity in the BG and impaired synaptic connectivity, together with reorganization of somatotopic maps. One hypothesis is that motor symptoms are, at least partly, caused by an impairment of network structure perturbing the organization of functional channels. Methods We developed a computational model of the STN-GPe circuit, a central part of the BG. By removing individual synaptic connections, we analyzed the contribution of signals propagating along different pathways to cortically evoked responses. We studied how evoked responses are affected by systematic changes in the network structure. To quantify the BG's organization in the form of functional channels, we suggested a two-site stimulation protocol. Results Our model reproduced the cortically evoked responses of STN and GPe neurons and the contributions of different pathways suggested by experimental studies. Cortical stimulation evokes spatio-temporal response patterns that are linked to the underlying synaptic network structure. Our two-site stimulation protocol yielded an approximate functional channel width. Discussion/conclusion The presented results provide insight into the organization of BG synaptic connectivity, which is important for the development of computational models. The synaptic network structure strongly affects the processing of cortical signals and may impact the generation of pathological rhythms. Our work may motivate further experiments to analyze the network structure of BG nuclei and their organization in functional channels.
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Affiliation(s)
- Justus A. Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Hemant Bokil
- Boston Scientific Neuromodulation, Valencia, CA, United States
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
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17
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Duchet B, Bick C, Byrne Á. Mean-Field Approximations With Adaptive Coupling for Networks With Spike-Timing-Dependent Plasticity. Neural Comput 2023; 35:1481-1528. [PMID: 37437202 PMCID: PMC10422128 DOI: 10.1162/neco_a_01601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2022] [Accepted: 04/26/2023] [Indexed: 07/14/2023]
Abstract
Understanding the effect of spike-timing-dependent plasticity (STDP) is key to elucidating how neural networks change over long timescales and to design interventions aimed at modulating such networks in neurological disorders. However, progress is restricted by the significant computational cost associated with simulating neural network models with STDP and by the lack of low-dimensional description that could provide analytical insights. Phase-difference-dependent plasticity (PDDP) rules approximate STDP in phase oscillator networks, which prescribe synaptic changes based on phase differences of neuron pairs rather than differences in spike timing. Here we construct mean-field approximations for phase oscillator networks with STDP to describe part of the phase space for this very high-dimensional system. We first show that single-harmonic PDDP rules can approximate a simple form of symmetric STDP, while multiharmonic rules are required to accurately approximate causal STDP. We then derive exact expressions for the evolution of the average PDDP coupling weight in terms of network synchrony. For adaptive networks of Kuramoto oscillators that form clusters, we formulate a family of low-dimensional descriptions based on the mean-field dynamics of each cluster and average coupling weights between and within clusters. Finally, we show that such a two-cluster mean-field model can be fitted to synthetic data to provide a low-dimensional approximation of a full adaptive network with symmetric STDP. Our framework represents a step toward a low-dimensional description of adaptive networks with STDP, and could for example inform the development of new therapies aimed at maximizing the long-lasting effects of brain stimulation.
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Affiliation(s)
- Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford X3 9DU, U.K
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford X1 3TH, U.K.
| | - Christian Bick
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam 1081 HV, the Netherlands
- Amsterdam Neuroscience-Systems and Network Neuroscience, Amsterdam 1081 HV, the Netherlands
- Mathematical Institute, University of Oxford, Oxford X2 6GG, U.K.
| | - Áine Byrne
- School of Mathematics and Statistics, University College Dublin, Dublin D04 V1W8, Ireland
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18
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Rusheen AE, Jensen MA, Gregg NM, Kaufmann TJ, VanGompel JJ, Lee KH, Klassen BT, Miller KJ. Preliminary Experience with a Four-Lead Implantable Pulse Generator for Deep Brain Stimulation. Stereotact Funct Neurosurg 2023; 101:254-264. [PMID: 37454656 DOI: 10.1159/000530782] [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: 12/14/2022] [Accepted: 04/07/2023] [Indexed: 07/18/2023]
Abstract
BACKGROUND Implantable pulse generators (IPGs) store energy and deliver electrical impulses for deep brain stimulation (DBS) to treat neurological and psychiatric disorders. IPGs have evolved over time to meet the demands of expanding clinical indications and more nuanced therapeutic approaches. OBJECTIVES The aim of this study was to examine the workflow of the first 4-lead IPG for DBS in patients with complex disease. METHOD The engineering capabilities, clinical use cases, and surgical technique are described in a cohort of 12 patients with epilepsy, essential tremor, Parkinson's disease, mixed tremor, and Tourette's syndrome with comorbid obsessive-compulsive disorder between July 2021 and July 2022. RESULTS This system is a rechargeable 32-channel, 4-port system with independent current control that can be connected to 8 contact linear or directionally segmented leads. The system is ideal for patients with mixed disease or those with multiple severe symptoms amenable to >2 lead implantations. A multidisciplinary team including neurologists, radiologists, and neurosurgeons is necessary to safely plan the procedure. There were no serious intraoperative or postoperative adverse events. One patient required revision surgery for bowstringing. CONCLUSIONS This new 4-lead IPG represents an important new tool for DBS surgery with the ability to expand lead implantation paradigms for patients with complex disease.
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Affiliation(s)
- Aaron Elliott Rusheen
- Medical Scientist Training Program, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael A Jensen
- Medical Scientist Training Program, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | | | | | - Jamie J VanGompel
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA
| | - Kendall H Lee
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
| | - Bryan T Klassen
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Kai Joshua Miller
- Department of Neurological Surgery, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, USA
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19
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Bravo M, Joon HL, Fallon J, Iansek R, Shoushtarian M. Towards non-invasive peripheral stimulation as a treatment for Parkinson's disease gait. 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: 38083474 DOI: 10.1109/embc40787.2023.10340670] [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
Non-invasive coordinated reset stimulation (CRS) to the hands has been shown to improve motor ability in Parkinson's patients, but not specific for gait disturbances. The overall aim of the project is the application of vibrotactile CRS to the feet to improve gait impairments in Parkinson's disease. As a first step towards this objective, we showed that vibrotactile stimulation to the feet can elicit a cortical response and have identified differences in younger and older individuals. Our findings suggest the potential for non-invasive peripheral stimulation as a therapeutic technique.Clinical Relevance- This is an important step towards developing a non-invasive stimulation technique for the management of gait disturbances in Parkinson's disease.
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20
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Sawicki J, Berner R, Loos SAM, Anvari M, Bader R, Barfuss W, Botta N, Brede N, Franović I, Gauthier DJ, Goldt S, Hajizadeh A, Hövel P, Karin O, Lorenz-Spreen P, Miehl C, Mölter J, Olmi S, Schöll E, Seif A, Tass PA, Volpe G, Yanchuk S, Kurths J. Perspectives on adaptive dynamical systems. CHAOS (WOODBURY, N.Y.) 2023; 33:071501. [PMID: 37486668 DOI: 10.1063/5.0147231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/24/2023] [Indexed: 07/25/2023]
Abstract
Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.
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Affiliation(s)
- Jakub Sawicki
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Rico Berner
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Sarah A M Loos
- DAMTP, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, United Kingdom
| | - Mehrnaz Anvari
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53757 Sankt-Augustin, Germany
| | - Rolf Bader
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Wolfram Barfuss
- Transdisciplinary Research Area: Sustainable Futures, University of Bonn, 53113 Bonn, Germany
- Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
| | - Nicola Botta
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science and Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Nuria Brede
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science, University of Potsdam, An der Bahn 2, 14476 Potsdam, Germany
| | - Igor Franović
- Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
| | - Daniel J Gauthier
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Sebastian Goldt
- Department of Physics, International School of Advanced Studies (SISSA), Trieste, Italy
| | - Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Philipp Hövel
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Omer Karin
- Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
| | - Philipp Lorenz-Spreen
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Christoph Miehl
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Jan Mölter
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, 85748 Garching bei München, Germany
| | - Simona Olmi
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Eckehard Schöll
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Alireza Seif
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, California 94304, USA
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Serhiy Yanchuk
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
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Najera RA, Mahavadi AK, Khan AU, Boddeti U, Del Bene VA, Walker HC, Bentley JN. Alternative patterns of deep brain stimulation in neurologic and neuropsychiatric disorders. Front Neuroinform 2023; 17:1156818. [PMID: 37415779 PMCID: PMC10320008 DOI: 10.3389/fninf.2023.1156818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 06/06/2023] [Indexed: 07/08/2023] Open
Abstract
Deep brain stimulation (DBS) is a widely used clinical therapy that modulates neuronal firing in subcortical structures, eliciting downstream network effects. Its effectiveness is determined by electrode geometry and location as well as adjustable stimulation parameters including pulse width, interstimulus interval, frequency, and amplitude. These parameters are often determined empirically during clinical or intraoperative programming and can be altered to an almost unlimited number of combinations. Conventional high-frequency stimulation uses a continuous high-frequency square-wave pulse (typically 130-160 Hz), but other stimulation patterns may prove efficacious, such as continuous or bursting theta-frequencies, variable frequencies, and coordinated reset stimulation. Here we summarize the current landscape and potential clinical applications for novel stimulation patterns.
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Affiliation(s)
- Ricardo A. Najera
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Anil K. Mahavadi
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Anas U. Khan
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Ujwal Boddeti
- Department of Neurosurgery, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Victor A. Del Bene
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Harrison C. Walker
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - J. Nicole Bentley
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
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22
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Cota VR, Cançado SAV, Moraes MFD. On temporal scale-free non-periodic stimulation and its mechanisms as an infinite improbability drive of the brain's functional connectogram. Front Neuroinform 2023; 17:1173597. [PMID: 37293579 PMCID: PMC10244597 DOI: 10.3389/fninf.2023.1173597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 05/02/2023] [Indexed: 06/10/2023] Open
Abstract
Rationalized development of electrical stimulation (ES) therapy is of paramount importance. Not only it will foster new techniques and technologies with increased levels of safety, efficacy, and efficiency, but it will also facilitate the translation from basic research to clinical practice. For such endeavor, design of new technologies must dialogue with state-of-the-art neuroscientific knowledge. By its turn, neuroscience is transitioning-a movement started a couple of decades earlier-into adopting a new conceptual framework for brain architecture, in which time and thus temporal patterns plays a central role in the neuronal representation of sampled data from the world. This article discusses how neuroscience has evolved to understand the importance of brain rhythms in the overall functional architecture of the nervous system and, consequently, that neuromodulation research should embrace this new conceptual framework. Based on such support, we revisit the literature on standard (fixed-frequency pulsatile stimuli) and mostly non-standard patterns of ES to put forward our own rationale on how temporally complex stimulation schemes may impact neuromodulation strategies. We then proceed to present a low frequency, on average (thus low energy), scale-free temporally randomized ES pattern for the treatment of experimental epilepsy, devised by our group and termed NPS (Non-periodic Stimulation). The approach has been shown to have robust anticonvulsant effects in different animal models of acute and chronic seizures (displaying dysfunctional hyperexcitable tissue), while also preserving neural function. In our understanding, accumulated mechanistic evidence suggests such a beneficial mechanism of action may be due to the natural-like characteristic of a scale-free temporal pattern that may robustly compete with aberrant epileptiform activity for the recruitment of neural circuits. Delivering temporally patterned or random stimuli within specific phases of the underlying oscillations (i.e., those involved in the communication within and across brain regions) could both potentiate and disrupt the formation of neuronal assemblies with random probability. The usage of infinite improbability drive here is obviously a reference to the "The Hitchhiker's Guide to the Galaxy" comedy science fiction classic, written by Douglas Adams. The parallel is that dynamically driving brain functional connectogram, through neuromodulation, in a manner that would not favor any specific neuronal assembly and/or circuit, could re-stabilize a system that is transitioning to fall under the control of a single attractor. We conclude by discussing future avenues of investigation and their potentially disruptive impact on neurotechnology, with a particular interest in NPS implications in neural plasticity, motor rehabilitation, and its potential for clinical translation.
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Affiliation(s)
- Vinícius Rosa Cota
- Rehab Technologies - INAIL Lab, Istituto Italiano di Tecnologia, Genoa, Italy
- Laboratory of Neuroengineering and Neuroscience, Department of Electrical Engineering, Federal University of São João del-Rei, São João del Rei, Brazil
| | - Sérgio Augusto Vieira Cançado
- Núcleo Avançado de Tratamento das Epilepsias (NATE), Felício Rocho Hospital, Fundação Felice Rosso, Belo Horizonte, Brazil
| | - Márcio Flávio Dutra Moraes
- Department of Physiology and Biophysics, Núcleo de Neurociências, Federal University of Minas Gerais, Belo Horizonte, Brazil
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23
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Widge AS. Closed-Loop Deep Brain Stimulation for Psychiatric Disorders. Harv Rev Psychiatry 2023; 31:162-171. [PMID: 37171475 PMCID: PMC10188203 DOI: 10.1097/hrp.0000000000000367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/13/2023]
Abstract
ABSTRACT Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.
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Affiliation(s)
- Alik S Widge
- From the Department of Psychiatry & Behavioral Sciences and Medical Discovery Team on Addictions, University of Minnesota
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24
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Madadi Asl M, Valizadeh A, Tass PA. Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity. PLoS Comput Biol 2023; 19:e1010853. [PMID: 36724144 PMCID: PMC9891531 DOI: 10.1371/journal.pcbi.1010853] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 01/05/2023] [Indexed: 02/02/2023] Open
Abstract
The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.
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Affiliation(s)
- Mojtaba Madadi Asl
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
| | - Alireza Valizadeh
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States of America
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25
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Asp AJ, Chintaluru Y, Hillan S, Lujan JL. Targeted neuroplasticity in spatiotemporally patterned invasive neuromodulation therapies for improving clinical outcomes. Front Neuroinform 2023; 17:1150157. [PMID: 37035718 PMCID: PMC10080034 DOI: 10.3389/fninf.2023.1150157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Affiliation(s)
- Anders J. Asp
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - Yaswanth Chintaluru
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States
- Department of Neurology and Neurosurgery, University of Colorado Anschutz School of Medicine, Aurora, CO, United States
| | - Sydney Hillan
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Rochester, MN, United States
| | - J. Luis Lujan
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, United States
- Department of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, MN, United States
- *Correspondence: J. Luis Lujan
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26
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Ratas I, Pyragas K. Interplay of different synchronization modes and synaptic plasticity in a system of class I neurons. Sci Rep 2022; 12:19631. [PMID: 36385488 PMCID: PMC9668974 DOI: 10.1038/s41598-022-24001-2] [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: 05/31/2022] [Accepted: 11/08/2022] [Indexed: 11/17/2022] Open
Abstract
We analyze the effect of spike-timing-dependent plasticity (STDP) on a system of pulse-coupled class I neurons. Our research begins with a system of two mutually connected quadratic integrate-and-fire (QIF) neurons, which are canonical representatives of class I neurons. Along with various asymptotic modes previously observed in other neuronal models with plastic synapses, we found a stable synchronous mode characterized by unidirectional link from a slower neuron to a faster neuron. In this frequency-locked mode, the faster neuron emits multiple spikes per cycle of the slower neuron. We analytically obtain the Arnold tongues for this mode without STDP and with STDP. We also consider larger plastic networks of QIF neurons and show that the detected mode can manifest itself in such a way that slow neurons become pacemakers. As a result, slow and fast neurons can form large synchronous clusters that generate low-frequency oscillations. We demonstrate the generality of the results obtained with two connected QIF neurons using Wang-Buzsáki and Morris-Lecar biophysically plausible class I neuron models.
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Affiliation(s)
- Irmantas Ratas
- grid.425985.7Center for Physical Sciences and Technology, 10257 Vilnius, Lithuania
| | - Kestutis Pyragas
- grid.425985.7Center for Physical Sciences and Technology, 10257 Vilnius, Lithuania
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27
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Kromer JA, Tass PA. Synaptic reshaping of plastic neuronal networks by periodic multichannel stimulation with single-pulse and burst stimuli. PLoS Comput Biol 2022; 18:e1010568. [PMID: 36327232 PMCID: PMC9632832 DOI: 10.1371/journal.pcbi.1010568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 09/14/2022] [Indexed: 11/06/2022] Open
Abstract
Synaptic dysfunction is associated with several brain disorders, including Alzheimer's disease, Parkinson's disease (PD) and obsessive compulsive disorder (OCD). Utilizing synaptic plasticity, brain stimulation is capable of reshaping synaptic connectivity. This may pave the way for novel therapies that specifically counteract pathological synaptic connectivity. For instance, in PD, novel multichannel coordinated reset stimulation (CRS) was designed to counteract neuronal synchrony and down-regulate pathological synaptic connectivity. CRS was shown to entail long-lasting therapeutic aftereffects in PD patients and related animal models. This is in marked contrast to conventional deep brain stimulation (DBS) therapy, where PD symptoms return shortly after stimulation ceases. In the present paper, we study synaptic reshaping by periodic multichannel stimulation (PMCS) in networks of leaky integrate-and-fire (LIF) neurons with spike-timing-dependent plasticity (STDP). During PMCS, phase-shifted periodic stimulus trains are delivered to segregated neuronal subpopulations. Harnessing STDP, PMCS leads to changes of the synaptic network structure. We found that the PMCS-induced changes of the network structure depend on both the phase lags between stimuli and the shape of individual stimuli. Single-pulse stimuli and burst stimuli with low intraburst frequency down-regulate synapses between neurons receiving stimuli simultaneously. In contrast, burst stimuli with high intraburst frequency up-regulate these synapses. We derive theoretical approximations of the stimulation-induced network structure. This enables us to formulate stimulation strategies for inducing a variety of network structures. Our results provide testable hypotheses for future pre-clinical and clinical studies and suggest that periodic multichannel stimulation may be suitable for reshaping plastic neuronal networks to counteract pathological synaptic connectivity. Furthermore, we provide novel insight on how the stimulus type may affect the long-lasting outcome of conventional DBS. This may strongly impact parameter adjustment procedures for clinical DBS, which, so far, primarily focused on acute effects of stimulation.
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Affiliation(s)
- Justus A Kromer
- Department of Neurosurgery, Stanford University, Stanford, California, United States of America
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, California, United States of America
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28
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Campbell BA, Favi Bocca L, Escobar Sanabria D, Almeida J, Rammo R, Nagel SJ, Machado AG, Baker KB. The impact of pulse timing on cortical and subthalamic nucleus deep brain stimulation evoked potentials. Front Hum Neurosci 2022; 16:1009223. [PMID: 36204716 PMCID: PMC9532054 DOI: 10.3389/fnhum.2022.1009223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 08/31/2022] [Indexed: 11/13/2022] Open
Abstract
The impact of pulse timing is an important factor in our understanding of how to effectively modulate the basal ganglia thalamocortical (BGTC) circuit. Single pulse low-frequency DBS-evoked potentials generated through electrical stimulation of the subthalamic nucleus (STN) provide insight into circuit activation, but how the long-latency components change as a function of pulse timing is not well-understood. We investigated how timing between stimulation pulses delivered in the STN region influence the neural activity in the STN and cortex. DBS leads implanted in the STN of five patients with Parkinson's disease were temporarily externalized, allowing for the delivery of paired pulses with inter-pulse intervals (IPIs) ranging from 0.2 to 10 ms. Neural activation was measured through local field potential (LFP) recordings from the DBS lead and scalp EEG. DBS-evoked potentials were computed using contacts positioned in dorsolateral STN as determined through co-registered post-operative imaging. We quantified the degree to which distinct IPIs influenced the amplitude of evoked responses across frequencies and time using the wavelet transform and power spectral density curves. The beta frequency content of the DBS evoked responses in the STN and scalp EEG increased as a function of pulse-interval timing. Pulse intervals <1.0 ms apart were associated with minimal to no change in the evoked response. IPIs from 1.5 to 3.0 ms yielded a significant increase in the evoked response, while those >4 ms produced modest, but non-significant growth. Beta frequency activity in the scalp EEG and STN LFP response was maximal when IPIs were between 1.5 and 4.0 ms. These results demonstrate that long-latency components of DBS-evoked responses are pre-dominantly in the beta frequency range and that pulse interval timing impacts the level of BGTC circuit activation.
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Affiliation(s)
- Brett A. Campbell
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Leonardo Favi Bocca
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - David Escobar Sanabria
- Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Julio Almeida
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Richard Rammo
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Sean J. Nagel
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Andre G. Machado
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- Department of Neurosurgery, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Kenneth B. Baker
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Center for Neurological Restoration, Neurological Institute, Cleveland Clinic, Cleveland, OH, United States
- *Correspondence: Kenneth B. Baker
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29
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Chauhan K, Khaledi-Nasab A, Neiman AB, Tass PA. Dynamics of phase oscillator networks with synaptic weight and structural plasticity. Sci Rep 2022; 12:15003. [PMID: 36056151 PMCID: PMC9440105 DOI: 10.1038/s41598-022-19417-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 08/29/2022] [Indexed: 11/08/2022] Open
Abstract
We study the dynamics of Kuramoto oscillator networks with two distinct adaptation processes, one varying the coupling strengths and the other altering the network structure. Such systems model certain networks of oscillatory neurons where the neuronal dynamics, synaptic weights, and network structure interact with and shape each other. We model synaptic weight adaptation with spike-timing-dependent plasticity (STDP) that runs on a longer time scale than neuronal spiking. Structural changes that include addition and elimination of contacts occur at yet a longer time scale than the weight adaptations. First, we study the steady-state dynamics of Kuramoto networks that are bistable and can settle in synchronized or desynchronized states. To compare the impact of adding structural plasticity, we contrast the network with only STDP to one with a combination of STDP and structural plasticity. We show that the inclusion of structural plasticity optimizes the synchronized state of a network by allowing for synchronization with fewer links than a network with STDP alone. With non-identical units in the network, the addition of structural plasticity leads to the emergence of correlations between the oscillators' natural frequencies and node degrees. In the desynchronized regime, the structural plasticity decreases the number of contacts, leading to a sparse network. In this way, adding structural plasticity strengthens both synchronized and desynchronized states of a network. Second, we use desynchronizing coordinated reset stimulation and synchronizing periodic stimulation to induce desynchronized and synchronized states, respectively. Our findings indicate that a network with a combination of STDP and structural plasticity may require stronger and longer stimulation to switch between the states than a network with STDP only.
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Affiliation(s)
- Kanishk Chauhan
- Department of Physics and Astronomy, Ohio University, Athens, OH, 45701, USA.
- Neuroscience Program, Ohio University, Athens, OH, 45701, USA.
| | - Ali Khaledi-Nasab
- Department of Neurosurgery, Stanford University, Stanford, CA, 94305, USA
| | - Alexander B Neiman
- Department of Physics and Astronomy, Ohio University, Athens, OH, 45701, USA
- Neuroscience Program, Ohio University, Athens, OH, 45701, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, CA, 94305, USA
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30
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Long-lasting effects of subthalamic nucleus coordinated reset deep brain stimulation in the non-human primate model of parkinsonism: A case report. Brain Stimul 2022; 15:598-600. [DOI: 10.1016/j.brs.2022.04.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/30/2021] [Accepted: 04/03/2022] [Indexed: 11/19/2022] Open
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31
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Toth K, Wilson D. Control of coupled neural oscillations using near-periodic inputs. CHAOS (WOODBURY, N.Y.) 2022; 32:033130. [PMID: 35364826 DOI: 10.1063/5.0076508] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/25/2021] [Accepted: 02/22/2022] [Indexed: 06/14/2023]
Abstract
Deep brain stimulation (DBS) is a commonly used treatment for medication resistant Parkinson's disease and is an emerging treatment for other neurological disorders. More recently, phase-specific adaptive DBS (aDBS), whereby the application of stimulation is locked to a particular phase of tremor, has been proposed as a strategy to improve therapeutic efficacy and decrease side effects. In this work, in the context of these phase-specific aDBS strategies, we investigate the dynamical behavior of large populations of coupled neurons in response to near-periodic stimulation, namely, stimulation that is periodic except for a slowly changing amplitude and phase offset that can be used to coordinate the timing of applied input with a specified phase of model oscillations. Using an adaptive phase-amplitude reduction strategy, we illustrate that for a large population of oscillatory neurons, the temporal evolution of the associated phase distribution in response to near-periodic forcing can be captured using a reduced order model with four state variables. Subsequently, we devise and validate a closed-loop control strategy to disrupt synchronization caused by coupling. Additionally, we identify strategies for implementing the proposed control strategy in situations where underlying model equations are unavailable by estimating the necessary terms of the reduced order equations in real-time from observables.
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Affiliation(s)
- Kaitlyn Toth
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee 37996, USA
| | - Dan Wilson
- Department of Electrical Engineering and Computer Science, University of Tennessee, Knoxville, Tennessee 37996, USA
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32
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Wang J, Fergus SP, Johnson LA, Nebeck SD, Zhang J, Kulkarni S, Bokil H, Molnar GF, Vitek JL. Shuffling Improves the Acute and Carryover Effect of Subthalamic Coordinated Reset Deep Brain Stimulation. Front Neurol 2022; 13:716046. [PMID: 35250798 PMCID: PMC8894645 DOI: 10.3389/fneur.2022.716046] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 01/18/2022] [Indexed: 02/05/2023] Open
Abstract
Coordinated reset deep brain stimulation (CR DBS) in the subthalamic nucleus (STN) has been demonstrated effective for the treatment of the motor signs associated with Parkinson's disease (PD). A critical CR parameter is an order in which stimulation is delivered across contacts. The relative effect of alternating vs. not alternating this order, i.e., shuffling vs. non-shuffling, however, has not been evaluated in vivo. The objective of this study is to compare the effect of shuffled vs. non-shuffled STN CR DBS on Parkinsonian motor signs. Two Parkinsonian non-human primates were implanted with a DBS lead in the STN. The effects of STN CR DBS with and without shuffling were compared with the traditional isochronal DBS (tDBS) using a within-subject design. For each stimulation setting, DBS was delivered for 2 or 4 h/day for 5 consecutive days. The severity of PD was assessed using a modified clinical rating scale immediately before, during, and 1 h after DBS, as well as on days following the discontinuation of the 5 days of daily stimulation, i.e., carryover effect. Shuffled STN CR DBS produced greater acute and carryover improvements on Parkinsonian motor signs compared with non-shuffled CR. Moreover, this difference was more pronounced when more effective stimulation intensity and burst frequency settings were used. tDBS showed limited carryover effects. Given the significant effect of shuffling on the effectiveness of CR DBS, it will be critical for future studies to further define the relative role of different CR parameters for the clinical implementation of this novel stimulation paradigm.
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Affiliation(s)
- Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States,*Correspondence: Jing Wang
| | - Sinta P. Fergus
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Shane D. Nebeck
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jianyu Zhang
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | | | - Hemant Bokil
- Boston Scientific Neuromodulation, Valencia, CA, United States
| | - Gregory F. Molnar
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States,Jerrold L. Vitek
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33
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Khaledi-Nasab A, Kromer JA, Tass PA. Long-Lasting Desynchronization of Plastic Neuronal Networks by Double-Random Coordinated Reset Stimulation. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:864859. [PMID: 36926109 PMCID: PMC10013062 DOI: 10.3389/fnetp.2022.864859] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Accepted: 03/18/2022] [Indexed: 11/13/2022]
Abstract
Hypersynchrony of neuronal activity is associated with several neurological disorders, including essential tremor and Parkinson's disease (PD). Chronic high-frequency deep brain stimulation (HF DBS) is the standard of care for medically refractory PD. Symptoms may effectively be suppressed by HF DBS, but return shortly after cessation of stimulation. Coordinated reset (CR) stimulation is a theory-based stimulation technique that was designed to specifically counteract neuronal synchrony by desynchronization. During CR, phase-shifted stimuli are delivered to multiple neuronal subpopulations. Computational studies on CR stimulation of plastic neuronal networks revealed long-lasting desynchronization effects obtained by down-regulating abnormal synaptic connectivity. This way, networks are moved into attractors of stable desynchronized states such that stimulation-induced desynchronization persists after cessation of stimulation. Preclinical and clinical studies confirmed corresponding long-lasting therapeutic and desynchronizing effects in PD. As PD symptoms are associated with different pathological synchronous rhythms, stimulation-induced long-lasting desynchronization effects should favorably be robust to variations of the stimulation frequency. Recent computational studies suggested that this robustness can be improved by randomizing the timings of stimulus deliveries. We study the long-lasting effects of CR stimulation with randomized stimulus amplitudes and/or randomized stimulus timing in networks of leaky integrate-and-fire (LIF) neurons with spike-timing-dependent plasticity. Performing computer simulations and analytical calculations, we study long-lasting desynchronization effects of CR with and without randomization of stimulus amplitudes alone, randomization of stimulus times alone as well as the combination of both. Varying the CR stimulation frequency (with respect to the frequency of abnormal target rhythm) and the number of separately stimulated neuronal subpopulations, we reveal parameter regions and related mechanisms where the two qualitatively different randomization mechanisms improve the robustness of long-lasting desynchronization effects of CR. In particular, for clinically relevant parameter ranges double-random CR stimulation, i.e., CR stimulation with the specific combination of stimulus amplitude randomization and stimulus time randomization, may outperform regular CR stimulation with respect to long-lasting desynchronization. In addition, our results provide the first evidence that an effective reduction of the overall stimulation current by stimulus amplitude randomization may improve the frequency robustness of long-lasting therapeutic effects of brain stimulation.
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Affiliation(s)
- Ali Khaledi-Nasab
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Justus A Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
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34
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Madadi Asl M, Vahabie AH, Valizadeh A, Tass PA. Spike-Timing-Dependent Plasticity Mediated by Dopamine and its Role in Parkinson's Disease Pathophysiology. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:817524. [PMID: 36926058 PMCID: PMC10013044 DOI: 10.3389/fnetp.2022.817524] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 02/08/2022] [Indexed: 01/05/2023]
Abstract
Parkinson's disease (PD) is a multi-systemic neurodegenerative brain disorder. Motor symptoms of PD are linked to the significant dopamine (DA) loss in substantia nigra pars compacta (SNc) followed by basal ganglia (BG) circuit dysfunction. Increasing experimental and computational evidence indicates that (synaptic) plasticity plays a key role in the emergence of PD-related pathological changes following DA loss. Spike-timing-dependent plasticity (STDP) mediated by DA provides a mechanistic model for synaptic plasticity to modify synaptic connections within the BG according to the neuronal activity. To shed light on how DA-mediated STDP can shape neuronal activity and synaptic connectivity in the PD condition, we reviewed experimental and computational findings addressing the modulatory effect of DA on STDP as well as other plasticity mechanisms and discussed their potential role in PD pathophysiology and related network dynamics and connectivity. In particular, reshaping of STDP profiles together with other plasticity-mediated processes following DA loss may abnormally modify synaptic connections in competing pathways of the BG. The cascade of plasticity-induced maladaptive or compensatory changes can impair the excitation-inhibition balance towards the BG output nuclei, leading to the emergence of pathological activity-connectivity patterns in PD. Pre-clinical, clinical as well as computational studies reviewed here provide an understanding of the impact of synaptic plasticity and other plasticity mechanisms on PD pathophysiology, especially PD-related network activity and connectivity, after DA loss. This review may provide further insights into the abnormal structure-function relationship within the BG contributing to the emergence of pathological states in PD. Specifically, this review is intended to provide detailed information for the development of computational network models for PD, serving as testbeds for the development and optimization of invasive and non-invasive brain stimulation techniques. Computationally derived hypotheses may accelerate the development of therapeutic stimulation techniques and potentially reduce the number of related animal experiments.
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Affiliation(s)
- Mojtaba Madadi Asl
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
| | - Abdol-Hossein Vahabie
- School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.,Department of Psychology, Faculty of Psychology and Education, University of Tehran, Tehran, Iran
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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35
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Tass PA. Vibrotactile coordinated reset stimulation for the treatment of Parkinson's disease. Neural Regen Res 2021; 17:1495-1497. [PMID: 34916431 PMCID: PMC8771098 DOI: 10.4103/1673-5374.329001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Affiliation(s)
- Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, USA
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36
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Pfeifer KJ, Cook AJ, Yankulova JK, Mortimer BJP, Erickson-DiRenzo E, Dhall R, Montaser-Kouhsari L, Tass PA. Clinical Efficacy and Dosing of Vibrotactile Coordinated Reset Stimulation in Motor and Non-motor Symptoms of Parkinson's Disease: A Study Protocol. Front Neurol 2021; 12:758481. [PMID: 34867742 PMCID: PMC8636796 DOI: 10.3389/fneur.2021.758481] [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: 08/14/2021] [Accepted: 10/12/2021] [Indexed: 11/13/2022] Open
Abstract
Enhanced neuronal synchronization of the subthalamic nucleus (STN) is commonly found in PD patients and corresponds to decreased motor ability. Coordinated reset (CR) was developed to decouple synchronized states causing long lasting desynchronization of neural networks. Vibrotactile CR stimulation (vCR) was developed as non-invasive therapeutic that delivers gentle vibrations to the fingertips. A previous study has shown that vCR can desynchronize abnormal brain rhythms within the sensorimotor cortex of PD patients, corresponding to sustained motor relief after 3 months of daily treatment. To further develop vCR, we created a protocol that has two phases. Study 1, a double blinded randomized sham-controlled study, is designed to address motor and non-motor symptoms, sensorimotor integration, and potential calibration methods. Study 2 examines dosing effects of vCR using a remote study design. In Study 1, we will perform a 7-month double-blind sham-controlled study including 30 PD patients randomly placed into an active vCR or inactive (sham) vCR condition. Patients will receive stimulation for 4 h a day in 2-h blocks for 6 months followed by a 1-month pause in stimulation to assess long lasting effects. Our primary outcome measure is the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III off medication after 6 months of treatment. Secondary measures include a freezing of gait (FOG) questionnaire, objective motor evaluations, sensorimotor electroencephalography (EEG) results, a vibratory temporal discrimination task (VTDT), non-motor symptom evaluations/tests such as sleep, smell, speech, quality of life measurements and Levodopa Equivalent Daily Dose (LEDD). Patients will be evaluated at baseline, 3, 6, and 7 months. In the second, unblinded study phase (Study 2), all patients will be given the option to receive active vCR stimulation at a reduced dose for an additional 6 months remotely. The remote MDS-UPDRS part III off medication will be our primary outcome measure. Secondary measures include sleep, quality of life, objective motor evaluations, FOG and LEDD. Patients will be evaluated in the same time periods as the first study. Results from this study will provide clinical efficacy of vCR and help validate our investigational vibrotactile device for the purpose of obtaining FDA clearance. Clinical Trial Registration: ClinicalTrials.gov, identifier: NCT04877015.
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Affiliation(s)
- Kristina J. Pfeifer
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Alex J. Cook
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | - Jessica K. Yankulova
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
| | | | - Elizabeth Erickson-DiRenzo
- Department of Otolarygology Head and Neck Surgery/Laryngology Division, Stanford University School of Medicine, Stanford, CA, United States
| | - Rohit Dhall
- Department of Neurology, Center for Neurodegenerative Disorders, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - Leila Montaser-Kouhsari
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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37
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Marceglia S, Guidetti M, Harmsen IE, Loh A, Meoni S, Foffani G, Lozano AM, Volkmann J, Moro E, Priori A. Deep brain stimulation: is it time to change gears by closing the loop? J Neural Eng 2021; 18. [PMID: 34678794 DOI: 10.1088/1741-2552/ac3267] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Accepted: 10/22/2021] [Indexed: 11/12/2022]
Abstract
Objective.Adaptive deep brain stimulation (aDBS) is a form of invasive stimulation that was conceived to overcome the technical limitations of traditional DBS, which delivers continuous stimulation of the target structure without considering patients' symptoms or status in real-time. Instead, aDBS delivers on-demand, contingency-based stimulation. So far, aDBS has been tested in several neurological conditions, and will be soon extensively studied to translate it into clinical practice. However, an exhaustive description of technical aspects is still missing.Approach.in this topical review, we summarize the knowledge about the current (and future) aDBS approach and control algorithms to deliver the stimulation, as reference for a deeper undestending of aDBS model.Main results.We discuss the conceptual and functional model of aDBS, which is based on the sensing module (that assesses the feedback variable), the control module (which interpretes the variable and elaborates the new stimulation parameters), and the stimulation module (that controls the delivery of stimulation), considering both the historical perspective and the state-of-the-art of available biomarkers.Significance.aDBS modulates neuronal circuits based on clinically relevant biofeedback signals in real-time. First developed in the mid-2000s, many groups have worked on improving closed-loop DBS technology. The field is now at a point in conducting large-scale randomized clinical trials to translate aDBS into clinical practice. As we move towards implanting brain-computer interfaces in patients, it will be important to understand the technical aspects of aDBS.
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Affiliation(s)
- Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, 34127 Trieste, Italy
| | - Matteo Guidetti
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy.,Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | - Irene E Harmsen
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Aaron Loh
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Sara Meoni
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy.,Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France.,Grenoble Institute of Neurosciences, INSERM U1216, University Grenoble Alpes, Grenoble, France
| | - Guglielmo Foffani
- HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain.,Hospital Nacional de Parapléjicos, SESCAM, Toledo, Spain
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada.,Krembil Research Institute, University Health Network, Toronto, Ontario, Canada
| | - Jens Volkmann
- Department of Neurology, University of Wurzburg, Wurzburg, Germany
| | - Elena Moro
- Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France.,Grenoble Institute of Neurosciences, INSERM U1216, University Grenoble Alpes, Grenoble, France
| | - Alberto Priori
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, 20142 Milan, Italy.,ASST Santi Paolo e Carlo, 20142 Milan, Italy
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Spix TA, Nanivadekar S, Toong N, Kaplow IM, Isett BR, Goksen Y, Pfenning AR, Gittis AH. Population-specific neuromodulation prolongs therapeutic benefits of deep brain stimulation. Science 2021; 374:201-206. [PMID: 34618556 PMCID: PMC11098594 DOI: 10.1126/science.abi7852] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Symptoms of neurological diseases emerge through the dysfunction of neural circuits whose diffuse and intertwined architectures pose serious challenges for delivering therapies. Deep brain stimulation (DBS) improves Parkinson’s disease symptoms acutely but does not differentiate between neuronal circuits, and its effects decay rapidly if stimulation is discontinued. Recent findings suggest that optogenetic manipulation of distinct neuronal subpopulations in the external globus pallidus (GPe) provides long-lasting therapeutic effects in dopamine-depleted (DD) mice. We used synaptic differences to excite parvalbumin-expressing GPe neurons and inhibit lim-homeobox-6–expressing GPe neurons simultaneously using brief bursts of electrical stimulation. In DD mice, circuit-inspired DBS provided long-lasting therapeutic benefits that far exceeded those induced by conventional DBS, extending several hours after stimulation. These results establish the feasibility of transforming knowledge of circuit architecture into translatable therapeutic approaches.
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Affiliation(s)
- Teresa A. Spix
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Shruti Nanivadekar
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Carnegie Mellon University, Pittsburgh, PA, USA
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Noelle Toong
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Irene M. Kaplow
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Brian R. Isett
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Yazel Goksen
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Andreas R. Pfenning
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Aryn H. Gittis
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
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Manos T, Diaz-Pier S, Tass PA. Long-Term Desynchronization by Coordinated Reset Stimulation in a Neural Network Model With Synaptic and Structural Plasticity. Front Physiol 2021; 12:716556. [PMID: 34566681 PMCID: PMC8455881 DOI: 10.3389/fphys.2021.716556] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 08/16/2021] [Indexed: 11/16/2022] Open
Abstract
Several brain disorders are characterized by abnormal neuronal synchronization. To specifically counteract abnormal neuronal synchrony and, hence, related symptoms, coordinated reset (CR) stimulation was computationally developed. In principle, successive epochs of synchronizing and desynchronizing stimulation may reversibly move neural networks with plastic synapses back and forth between stable regimes with synchronized and desynchronized firing. Computationally derived predictions have been verified in pre-clinical and clinical studies, paving the way for novel therapies. However, as yet, computational models were not able to reproduce the clinically observed increase of desynchronizing effects of regularly administered CR stimulation intermingled by long stimulation-free epochs. We show that this clinically important phenomenon can be computationally reproduced by taking into account structural plasticity (SP), a mechanism that deletes or generates synapses in order to homeostatically adapt the firing rates of neurons to a set point-like target firing rate in the course of days to months. If we assume that CR stimulation favorably reduces the target firing rate of SP, the desynchronizing effects of CR stimulation increase after long stimulation-free epochs, in accordance with clinically observed phenomena. Our study highlights the pivotal role of stimulation- and dosing-induced modulation of homeostatic set points in therapeutic processes.
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Affiliation(s)
- Thanos Manos
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany.,Medical Faculty, Institute of Systems Neuroscience, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Laboratoire de Physique Théorique et Modélisation, CNRS, UMR 8089, CY Cergy Paris Université, Cergy-Pontoise Cedex, France
| | - Sandra Diaz-Pier
- Simulation & Data Lab Neuroscience, Institute for Advanced Simulation, Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, JARA, Jülich, Germany
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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40
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Khaledi-Nasab A, Kromer JA, Tass PA. Long-Lasting Desynchronization Effects of Coordinated Reset Stimulation Improved by Random Jitters. Front Physiol 2021; 12:719680. [PMID: 34630142 PMCID: PMC8497886 DOI: 10.3389/fphys.2021.719680] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 08/12/2021] [Indexed: 12/30/2022] Open
Abstract
Abnormally strong synchronized activity is related to several neurological disorders, including essential tremor, epilepsy, and Parkinson's disease. Chronic high-frequency deep brain stimulation (HF DBS) is an established treatment for advanced Parkinson's disease. To reduce the delivered integral electrical current, novel theory-based stimulation techniques such as coordinated reset (CR) stimulation directly counteract the abnormal synchronous firing by delivering phase-shifted stimuli through multiple stimulation sites. In computational studies in neuronal networks with spike-timing-dependent plasticity (STDP), it was shown that CR stimulation down-regulates synaptic weights and drives the network into an attractor of a stable desynchronized state. This led to desynchronization effects that outlasted the stimulation. Corresponding long-lasting therapeutic effects were observed in preclinical and clinical studies. Computational studies suggest that long-lasting effects of CR stimulation depend on the adjustment of the stimulation frequency to the dominant synchronous rhythm. This may limit clinical applicability as different pathological rhythms may coexist. To increase the robustness of the long-lasting effects, we study randomized versions of CR stimulation in networks of leaky integrate-and-fire neurons with STDP. Randomization is obtained by adding random jitters to the stimulation times and by shuffling the sequence of stimulation site activations. We study the corresponding long-lasting effects using analytical calculations and computer simulations. We show that random jitters increase the robustness of long-lasting effects with respect to changes of the number of stimulation sites and the stimulation frequency. In contrast, shuffling does not increase parameter robustness of long-lasting effects. Studying the relation between acute, acute after-, and long-lasting effects of stimulation, we find that both acute after- and long-lasting effects are strongly determined by the stimulation-induced synaptic reshaping, whereas acute effects solely depend on the statistics of administered stimuli. We find that the stimulation duration is another important parameter, as effective stimulation only entails long-lasting effects after a sufficient stimulation duration. Our results show that long-lasting therapeutic effects of CR stimulation with random jitters are more robust than those of regular CR stimulation. This might reduce the parameter adjustment time in future clinical trials and make CR with random jitters more suitable for treating brain disorders with abnormal synchronization in multiple frequency bands.
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Affiliation(s)
- Ali Khaledi-Nasab
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Justus A Kromer
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
| | - Peter A Tass
- Department of Neurosurgery, Stanford University, Stanford, CA, United States
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Patel B, Chiu S, Wong JK, Patterson A, Deeb W, Burns M, Zeilman P, Wagle-Shukla A, Almeida L, Okun MS, Ramirez-Zamora A. Deep brain stimulation programming strategies: segmented leads, independent current sources, and future technology. Expert Rev Med Devices 2021; 18:875-891. [PMID: 34329566 DOI: 10.1080/17434440.2021.1962286] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Introduction: Advances in neuromodulation and deep brain stimulation (DBS) technologies have facilitated opportunities for improved clinical benefit and side effect management. However, new technologies have added complexity to clinic-based DBS programming.Areas covered: In this article, we review basic basal ganglia physiology, proposed mechanisms of action and technical aspects of DBS. We discuss novel DBS technologies for movement disorders including the role of advanced imaging software, lead design, IPG design, novel programming techniques including directional stimulation and coordinated reset neuromodulation. Additional topics include the use of potential biomarkers, such as local field potentials, electrocorticography, and adaptive stimulation. We will also discuss future directions including optogenetically inspired DBS.Expert opinion: The introduction of DBS for the management of movement disorders has expanded treatment options. In parallel with our improved understanding of brain physiology and neuroanatomy, new technologies have emerged to address challenges associated with neuromodulation, including variable effectiveness, side-effects, and programming complexity. Advanced functional neuroanatomy, improved imaging, real-time neurophysiology, improved electrode designs, and novel programming techniques have collectively been driving improvements in DBS outcomes.
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Affiliation(s)
- Bhavana Patel
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Shannon Chiu
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Joshua K Wong
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Addie Patterson
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Wissam Deeb
- Department of Neurology, University of Massachusetts College of Medicine, Worcester, MA, USA
| | - Matthew Burns
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Pamela Zeilman
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA
| | - Aparna Wagle-Shukla
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Leonardo Almeida
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Michael S Okun
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
| | - Adolfo Ramirez-Zamora
- Department of Neurology, University of Florida College of Medicine, Gainesville, FL, USA.,Norman Fixel Institute for Neurological Diseases, . Gainesville, FL, USA
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42
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Priori A, Maiorana N, Dini M, Guidetti M, Marceglia S, Ferrucci R. Adaptive deep brain stimulation (aDBS). INTERNATIONAL REVIEW OF NEUROBIOLOGY 2021; 159:111-127. [PMID: 34446243 DOI: 10.1016/bs.irn.2021.06.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Deep brain stimulation is an established technique for the treatment of movement disorders related to neurodegenerative diseases such as Parkinson's disease (PD) and essential tremor (ET). Its application seems also feasible for the treatment of neuropsychiatric disorders such as treatment resistant depression (TRD) and Tourette's syndrome (TS). In a typical deep brain stimulation system, the amount of current delivered to the patients is constant and regulated by the physician. Conversely, an adaptive deep brain stimulation system (aDBS) is a closed loop system that adjusts the stimulation parameters according to biomarkers which reflect the patient's clinical state. In this chapter, we examined the main issues related to aDBS systems, which are both clinical and technological in nature. From a clinical point of view, we have reported the major findings related to symptoms management using aDBS and principal findings in animal models, showing that the implementation of closed loop adaptive deep brain stimulation can ameliorate symptom management in neurodegenerative disorders. From the technological point of view, we reported the major advances related to aDBS system design and implementation, such as noise filtering methods, biomarkers recording and processing to adjust pulse delivery. To date, aDBS systems represent a major evolution in brain stimulation, further developments are needed to maximize the efficacy of this technique and to expand its use in a wide range of neuropsychiatric disorders.
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Affiliation(s)
- Alberto Priori
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy.
| | - Natale Maiorana
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
| | - Michelangelo Dini
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
| | - Matteo Guidetti
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, Trieste, Italy
| | - Roberta Ferrucci
- Department of Health Science, Aldo Ravelli Center, University of Milan, Milan, Italy
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Searchfield GD, Sanders PJ, Doborjeh Z, Doborjeh M, Boldu R, Sun K, Barde A. A State-of-Art Review of Digital Technologies for the Next Generation of Tinnitus Therapeutics. Front Digit Health 2021; 3:724370. [PMID: 34713191 PMCID: PMC8522011 DOI: 10.3389/fdgth.2021.724370] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2021] [Accepted: 07/12/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Digital processing has enabled the development of several generations of technology for tinnitus therapy. The first digital generation was comprised of digital Hearing Aids (HAs) and personal digital music players implementing already established sound-based therapies, as well as text based information on the internet. In the second generation Smart-phone applications (apps) alone or in conjunction with HAs resulted in more therapy options for users to select from. The 3rd generation of digital tinnitus technologies began with the emergence of many novel, largely neurophysiologically-inspired, treatment theories that drove development of processing; enabled through HAs, apps, the internet and stand-alone devices. We are now of the cusp of a 4th generation that will incorporate physiological sensors, multiple transducers and AI to personalize therapies. Aim: To review technologies that will enable the next generations of digital therapies for tinnitus. Methods: A "state-of-the-art" review was undertaken to answer the question: what digital technology could be applied to tinnitus therapy in the next 10 years? Google Scholar and PubMed were searched for the 10-year period 2011-2021. The search strategy used the following key words: "tinnitus" and ["HA," "personalized therapy," "AI" (and "methods" or "applications"), "Virtual reality," "Games," "Sensors" and "Transducers"], and "Hearables." Snowballing was used to expand the search from the identified papers. The results of the review were cataloged and organized into themes. Results: This paper identified digital technologies and research on the development of smart therapies for tinnitus. AI methods that could have tinnitus applications are identified and discussed. The potential of personalized treatments and the benefits of being able to gather data in ecologically valid settings are outlined. Conclusions: There is a huge scope for the application of digital technology to tinnitus therapy, but the uncertain mechanisms underpinning tinnitus present a challenge and many posited therapeutic approaches may not be successful. Personalized AI modeling based on biometric measures obtained through various sensor types, and assessments of individual psychology and lifestyles should result in the development of smart therapy platforms for tinnitus.
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Affiliation(s)
- Grant D. Searchfield
- Section of Audiology, The University of Auckland, Auckland, New Zealand
- Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Philip J. Sanders
- Section of Audiology, The University of Auckland, Auckland, New Zealand
- Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Zohreh Doborjeh
- Section of Audiology, The University of Auckland, Auckland, New Zealand
- Eisdell Moore Centre, The University of Auckland, Auckland, New Zealand
- Centre for Brain Research, The University of Auckland, Auckland, New Zealand
| | - Maryam Doborjeh
- School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland, New Zealand
| | - Roger Boldu
- Augmented Human Laboratory, Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
| | - Kevin Sun
- Section of Audiology, The University of Auckland, Auckland, New Zealand
| | - Amit Barde
- Empathic Computing Laboratory, Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand
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Guidetti M, Marceglia S, Loh A, Harmsen IE, Meoni S, Foffani G, Lozano AM, Moro E, Volkmann J, Priori A. Clinical perspectives of adaptive deep brain stimulation. Brain Stimul 2021; 14:1238-1247. [PMID: 34371211 DOI: 10.1016/j.brs.2021.07.063] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Revised: 06/01/2021] [Accepted: 07/31/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The application of stimulators implanted directly over deep brain structures (i.e., deep brain stimulation, DBS) was developed in the late 1980s and has since become a mainstream option to treat several neurological conditions. Conventional DBS involves the continuous stimulation of the target structure, which is an approach that cannot adapt to patients' changing symptoms or functional status in real-time. At the beginning of 2000, a more sophisticated form of stimulation was conceived to overcome these limitations. Adaptive deep brain stimulation (aDBS) employs on-demand, contingency-based stimulation to stimulate only when needed. So far, aDBS has been tested in several pathological conditions in animal and human models. OBJECTIVE To review the current findings obtained from application of aDBS to animal and human models that highlights effects on motor, cognitive and psychiatric behaviors. FINDINGS while aDBS has shown promising results in the treatment of Parkinson's disease and essential tremor, the possibility of its use in less common DBS indications, such as cognitive and psychiatric disorders (Alzheimer's disease, obsessive-compulsive disorder, post-traumatic stress disorder) is still challenging. CONCLUSIONS While aDBS seems to be effective to treat movement disorders (Parkinson's disease and essential tremor), its role in cognitive and psychiatric disorders is to be determined, although neurophysiological assumptions are promising.
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Affiliation(s)
- Matteo Guidetti
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, Via Antonio di Rudinì, 8, 20142, Milan, Italy; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Piazza Leonardo da Vinci, 32, 20133, Milan, Italy.
| | - Sara Marceglia
- Department of Engineering and Architecture, University of Trieste, 34127, Trieste, Italy.
| | - Aaron Loh
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada; Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.
| | - Irene E Harmsen
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada; Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.
| | - Sara Meoni
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, Via Antonio di Rudinì, 8, 20142, Milan, Italy; Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France; Grenoble Institute of Neurosciences, INSERM U1216, University Grenoble Alpes, Grenoble, France.
| | - Guglielmo Foffani
- HM CINAC (Centro Integral de Neurociencias Abarca Campal), Hospital Universitario HM Puerta del Sur, HM Hospitales, Madrid, Spain; Hospital Nacional de Parapléjicos, SESCAM, Toledo, Spain.
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada; Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.
| | - Elena Moro
- Movement Disorders Unit, Division of Neurology, CHU Grenoble Alpes, Grenoble, France; Grenoble Institute of Neurosciences, INSERM U1216, University Grenoble Alpes, Grenoble, France.
| | - Jens Volkmann
- Department of Neurology, University of Wurzburg, Germany.
| | - Alberto Priori
- Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, Department of Health Sciences, University of Milan, Via Antonio di Rudinì, 8, 20142, Milan, Italy; ASST Santi Paolo e Carlo, Milan, Italy.
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45
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Weerasinghe G, Duchet B, Bick C, Bogacz R. Optimal closed-loop deep brain stimulation using multiple independently controlled contacts. PLoS Comput Biol 2021; 17:e1009281. [PMID: 34358224 PMCID: PMC8405008 DOI: 10.1371/journal.pcbi.1009281] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 08/30/2021] [Accepted: 07/15/2021] [Indexed: 11/18/2022] Open
Abstract
Deep brain stimulation (DBS) is a well-established treatment option for a variety of neurological disorders, including Parkinson’s disease and essential tremor. The symptoms of these disorders are known to be associated with pathological synchronous neural activity in the basal ganglia and thalamus. It is hypothesised that DBS acts to desynchronise this activity, leading to an overall reduction in symptoms. Electrodes with multiple independently controllable contacts are a recent development in DBS technology which have the potential to target one or more pathological regions with greater precision, reducing side effects and potentially increasing both the efficacy and efficiency of the treatment. The increased complexity of these systems, however, motivates the need to understand the effects of DBS when applied to multiple regions or neural populations within the brain. On the basis of a theoretical model, our paper addresses the question of how to best apply DBS to multiple neural populations to maximally desynchronise brain activity. Central to this are analytical expressions, which we derive, that predict how the symptom severity should change when stimulation is applied. Using these expressions, we construct a closed-loop DBS strategy describing how stimulation should be delivered to individual contacts using the phases and amplitudes of feedback signals. We simulate our method and compare it against two others found in the literature: coordinated reset and phase-locked stimulation. We also investigate the conditions for which our strategy is expected to yield the most benefit. In this paper we use computer models of brain tissue to derive an optimal control algorithm for a recently developed new generation of deep brain stimulation (DBS) devices. DBS is a treatment for a variety of neurological disorders including Parkinson’s disease, essential tremor, depression and pain. There is a growing amount of evidence to suggest that delivering stimulation according to feedback from patients, or closed-loop, has the potential to improve the efficacy, efficiency and side effects of the treatment. An important recent development in DBS technology are electrodes with multiple independently controllable contacts and this paper is a theoretical study into the effects of using this new technology. On the basis of a theoretical model, we devise a closed-loop strategy and address the question of how to best apply DBS across multiple contacts to maximally desynchronise neural populations. We demonstrate using numerical simulation that, for the systems we consider, our methods are more effective than two well-known alternatives, namely phase-locked stimulation and coordinated reset. We also predict that the benefits of using multiple contacts should depend strongly on the intrinsic neuronal response. The insights from this work should lead to a better understanding of how to implement and optimise closed-loop multi-contact DBS systems which in turn should lead to more effective and efficient DBS treatments.
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Affiliation(s)
- Gihan Weerasinghe
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
- * E-mail:
| | - Benoit Duchet
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Christian Bick
- Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Systems and Network Neuroscience, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Mathematical Institute, University of Oxford, Oxford, United Kingdom
- Department of Mathematics, University of Exeter, Exeter, United Kingdom
| | - Rafal Bogacz
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
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Kremer NI, Pauwels RWJ, Pozzi NG, Lange F, Roothans J, Volkmann J, Reich MM. Deep Brain Stimulation for Tremor: Update on Long-Term Outcomes, Target Considerations and Future Directions. J Clin Med 2021; 10:3468. [PMID: 34441763 PMCID: PMC8397098 DOI: 10.3390/jcm10163468] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 07/29/2021] [Accepted: 08/03/2021] [Indexed: 01/11/2023] Open
Abstract
Deep brain stimulation (DBS) of the thalamic ventral intermediate nucleus is one of the main advanced neurosurgical treatments for drug-resistant tremor. However, not every patient may be eligible for this procedure. Nowadays, various other functional neurosurgical procedures are available. In particular cases, radiofrequency thalamotomy, focused ultrasound and radiosurgery are proven alternatives to DBS. Besides, other DBS targets, such as the posterior subthalamic area (PSA) or the dentato-rubro-thalamic tract (DRT), may be appraised as well. In this review, the clinical characteristics and pathophysiology of tremor syndromes, as well as long-term outcomes of DBS in different targets, will be summarized. The effectiveness and safety of lesioning procedures will be discussed, and an evidence-based clinical treatment approach for patients with drug-resistant tremor will be presented. Lastly, the future directions in the treatment of severe tremor syndromes will be elaborated.
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Affiliation(s)
- Naomi I. Kremer
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (N.I.K.); (R.W.J.P.)
- Department of Neurology, University Hospital and Julius-Maximilian-University, 97080 Wuerzburg, Germany; (N.G.P.); (F.L.); (J.R.); (J.V.)
| | - Rik W. J. Pauwels
- Department of Neurosurgery, University Medical Center Groningen, University of Groningen, 9713 GZ Groningen, The Netherlands; (N.I.K.); (R.W.J.P.)
| | - Nicolò G. Pozzi
- Department of Neurology, University Hospital and Julius-Maximilian-University, 97080 Wuerzburg, Germany; (N.G.P.); (F.L.); (J.R.); (J.V.)
| | - Florian Lange
- Department of Neurology, University Hospital and Julius-Maximilian-University, 97080 Wuerzburg, Germany; (N.G.P.); (F.L.); (J.R.); (J.V.)
| | - Jonas Roothans
- Department of Neurology, University Hospital and Julius-Maximilian-University, 97080 Wuerzburg, Germany; (N.G.P.); (F.L.); (J.R.); (J.V.)
| | - Jens Volkmann
- Department of Neurology, University Hospital and Julius-Maximilian-University, 97080 Wuerzburg, Germany; (N.G.P.); (F.L.); (J.R.); (J.V.)
| | - Martin M. Reich
- Department of Neurology, University Hospital and Julius-Maximilian-University, 97080 Wuerzburg, Germany; (N.G.P.); (F.L.); (J.R.); (J.V.)
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Merola A, Singh J, Reeves K, Changizi B, Goetz S, Rossi L, Pallavaram S, Carcieri S, Harel N, Shaikhouni A, Sammartino F, Krishna V, Verhagen L, Dalm B. New Frontiers for Deep Brain Stimulation: Directionality, Sensing Technologies, Remote Programming, Robotic Stereotactic Assistance, Asleep Procedures, and Connectomics. Front Neurol 2021; 12:694747. [PMID: 34367055 PMCID: PMC8340024 DOI: 10.3389/fneur.2021.694747] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 06/14/2021] [Indexed: 11/21/2022] Open
Abstract
Over the last few years, while expanding its clinical indications from movement disorders to epilepsy and psychiatry, the field of deep brain stimulation (DBS) has seen significant innovations. Hardware developments have introduced directional leads to stimulate specific brain targets and sensing electrodes to determine optimal settings via feedback from local field potentials. In addition, variable-frequency stimulation and asynchronous high-frequency pulse trains have introduced new programming paradigms to efficiently desynchronize pathological neural circuitry and regulate dysfunctional brain networks not responsive to conventional settings. Overall, these innovations have provided clinicians with more anatomically accurate programming and closed-looped feedback to identify optimal strategies for neuromodulation. Simultaneously, software developments have simplified programming algorithms, introduced platforms for DBS remote management via telemedicine, and tools for estimating the volume of tissue activated within and outside the DBS targets. Finally, the surgical accuracy has improved thanks to intraoperative magnetic resonance or computerized tomography guidance, network-based imaging for DBS planning and targeting, and robotic-assisted surgery for ultra-accurate, millimetric lead placement. These technological and imaging advances have collectively optimized DBS outcomes and allowed “asleep” DBS procedures. Still, the short- and long-term outcomes of different implantable devices, surgical techniques, and asleep vs. awake procedures remain to be clarified. This expert review summarizes and critically discusses these recent innovations and their potential impact on the DBS field.
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Affiliation(s)
- Aristide Merola
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Jaysingh Singh
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Kevin Reeves
- Department of Psychiatry, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Barbara Changizi
- Department of Neurology, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Steven Goetz
- Medtronic PLC Neuromodulation, Minneapolis, MN, United States
| | | | | | | | - Noam Harel
- Center for Magnetic Resonance Research, University of Minnesota Medical School, Minneapolis, MN, United States
| | - Ammar Shaikhouni
- Department of Neurosurgery, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Francesco Sammartino
- Department of Neurosurgery, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Vibhor Krishna
- Department of Neurosurgery, The Ohio State University Wexner Medical Center, Columbus, OH, United States
| | - Leo Verhagen
- Movement Disorder Section, Department of Neurological Sciences, Rush University, Chicago, IL, United States
| | - Brian Dalm
- Department of Neurosurgery, The Ohio State University Wexner Medical Center, Columbus, OH, United States
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48
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Matchen TD, Moehlis J. Leveraging deep learning to control neural oscillators. BIOLOGICAL CYBERNETICS 2021; 115:219-235. [PMID: 33909165 DOI: 10.1007/s00422-021-00874-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Accepted: 04/10/2021] [Indexed: 06/12/2023]
Abstract
Modulation of the firing times of neural oscillators has long been an important control objective, with applications including Parkinson's disease, Tourette's syndrome, epilepsy, and learning. One common goal for such modulation is desynchronization, wherein two or more oscillators are stimulated to transition from firing in phase with each other to firing out of phase. The optimization of such stimuli has been well studied, but this typically relies on either a reduction of the dimensionality of the system or complete knowledge of the parameters and state of the system. This limits the applicability of results to real problems in neural control. Here, we present a trained artificial neural network capable of accurately estimating the effects of square-wave stimuli on neurons using minimal output information from the neuron. We then apply the results of this network to solve several related control problems in desynchronization, including desynchronizing pairs of neurons and achieving clustered subpopulations of neurons in the presence of coupling and noise.
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Affiliation(s)
- Timothy D Matchen
- Department of Mechanical Engineering, University of California, Santa Barbara, CA, 93106, USA.
| | - Jeff Moehlis
- Department of Mechanical Engineering, Program in Dynamical Neuroscience, University of California, Santa Barbara, CA, 93106, USA
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Pathak YJ, Greenleaf W, Verhagen Metman L, Kubben P, Sarma S, Pepin B, Lautner D, DeBates S, Benison AM, Balasingh B, Ross E. Digital Health Integration With Neuromodulation Therapies: The Future of Patient-Centric Innovation in Neuromodulation. Front Digit Health 2021; 3:618959. [PMID: 34713096 PMCID: PMC8521905 DOI: 10.3389/fdgth.2021.618959] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2020] [Accepted: 04/12/2021] [Indexed: 01/30/2023] Open
Abstract
Digital health can drive patient-centric innovation in neuromodulation by leveraging current tools to identify response predictors and digital biomarkers. Iterative technological evolution has led us to an ideal point to integrate digital health with neuromodulation. Here, we provide an overview of the digital health building-blocks, the status of advanced neuromodulation technologies, and future applications for neuromodulation with digital health integration.
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Affiliation(s)
| | - Walter Greenleaf
- Department of Communication, Stanford University, Stanford, CA, United States
| | - Leo Verhagen Metman
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, United States
| | - Pieter Kubben
- Department of Neurosurgery, Maastricht University Medical Center, Maastricht, Netherlands
| | - Sridevi Sarma
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | | | | | | | | | | | - Erika Ross
- Abbott Neuromodulation, Plano, TX, United States
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50
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Latorre A, Rocchi L, Sadnicka A. The Expanding Horizon of Neural Stimulation for Hyperkinetic Movement Disorders. Front Neurol 2021; 12:669690. [PMID: 34054710 PMCID: PMC8160223 DOI: 10.3389/fneur.2021.669690] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 04/19/2021] [Indexed: 11/13/2022] Open
Abstract
Novel methods of neural stimulation are transforming the management of hyperkinetic movement disorders. In this review the diversity of approach available is showcased. We first describe the most commonly used features that can be extracted from oscillatory activity of the central nervous system, and how these can be combined with an expanding range of non-invasive and invasive brain stimulation techniques. We then shift our focus to the periphery using tremor and Tourette's syndrome to illustrate the utility of peripheral biomarkers and interventions. Finally, we discuss current innovations which are changing the landscape of stimulation strategy by integrating technological advances and the use of machine learning to drive optimization.
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Affiliation(s)
- Anna Latorre
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom
| | - Lorenzo Rocchi
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom.,Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
| | - Anna Sadnicka
- Department of Clinical and Movement Neurosciences, University College London, London, United Kingdom.,Motor Control and Neuromodulation Group, St George's University of London, London, United Kingdom
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