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Lewis S, Radcliffe E, Ojemann S, Kramer DR, Hirt L, Case M, Holt-Becker AB, Raike R, Kern DS, Thompson JA. Pilot Study to Investigate the Use of In-Clinic Sensing to Identify Optimal Stimulation Parameters for Deep Brain Stimulation Therapy in Parkinson's Disease. Neuromodulation 2024; 27:509-519. [PMID: 36797194 DOI: 10.1016/j.neurom.2023.01.006] [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: 10/26/2022] [Revised: 12/19/2022] [Accepted: 01/09/2023] [Indexed: 02/16/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) programming is time intensive. Recent advances in sensing technology of local field potentials (LFPs) may enable improvements. Few studies have compared the use of this technology with standard of care. OBJECTIVE/HYPOTHESIS Sensing technology of subthalamic nucleus (STN) DBS leads in Parkinson's disease (PD) is reliable and predicts the optimal contacts and settings as predicted by clinical assessment. MATERIALS AND METHODS Five subjects with PD (n = 9 hemispheres) with bilateral STN DBS and sensing capable battery replacement were recruited. An LFP sensing review of all bipolar contact pairs was performed three times. Contact with the maximal beta peak power (MBP) was then clinically assessed in a double-blinded fashion, and five conditions were tested: 1) entry settings, 2) off stimulation, 3) MBP at 30 μs, 4) MBP at 60 μs, and 5) MBP at 90 μs. RESULTS Contact and frequency of the MBP power in all hemispheres did not differ across sessions. The entry settings matched with the contact with the MBP power in 5 of 9 hemispheres. No clinical difference was evident in the stimulation conditions. The clinician and subject preferred settings determined by MBP power in 7 of 9 and 5 of 7 hemispheres, respectively. CONCLUSIONS This study indicates that STN LFPs in PD recorded directly from contacts of the DBS lead provide consistent recordings across the frequency range and a reliably detected beta peak. Furthermore, programming based on the MBP power provides at least clinical equivalence to standard of care programming with STN DBS.
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Affiliation(s)
- Sydnei Lewis
- Biomedical Engineering, University of Colorado Boulder, Boulder, CO, USA
| | - Erin Radcliffe
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Daniel R Kramer
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Lisa Hirt
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Michelle Case
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic, Plc, Minneapolis, MN, USA
| | - Abbey B Holt-Becker
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic, Plc, Minneapolis, MN, USA
| | - Robert Raike
- Brain Modulation Business, Neuromodulation Operating Unit, Medtronic, Plc, Minneapolis, MN, USA
| | - Drew S Kern
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - John A Thompson
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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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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Chua MMJ, Vissani M, Liu DD, Schaper FLWVJ, Warren AEL, Caston R, Dworetzky BA, Bubrick EJ, Sarkis RA, Cosgrove GR, Rolston JD. Initial case series of a novel sensing deep brain stimulation device in drug-resistant epilepsy and consistent identification of alpha/beta oscillatory activity: A feasibility study. Epilepsia 2023; 64:2586-2603. [PMID: 37483140 DOI: 10.1111/epi.17722] [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: 03/27/2023] [Revised: 07/18/2023] [Accepted: 07/18/2023] [Indexed: 07/25/2023]
Abstract
OBJECTIVE Here, we report a retrospective, single-center experience with a novel deep brain stimulation (DBS) device capable of chronic local field potential (LFP) recording in drug-resistant epilepsy (DRE) and explore potential electrophysiological biomarkers that may aid DBS programming and outcome tracking. METHODS Five patients with DRE underwent thalamic DBS, targeting either the bilateral anterior (n = 3) or centromedian (n = 2) nuclei. Postoperative electrode lead localizations were visualized in Lead-DBS software. Local field potentials recorded over 12-18 months were tracked, and changes in power were associated with patient events, medication changes, and stimulation. We utilized a combination of lead localization, in-clinic broadband LFP recordings, real-time LFP response to stimulation, and chronic recordings to guide DBS programming. RESULTS Four patients (80%) experienced a >50% reduction in seizure frequency, whereas one patient had no significant reduction. Peaks in the alpha and/or beta frequency range were observed in the thalamic LFPs of each patient. Stimulation suppressed these LFP peaks in a dose-dependent manner. Chronic timeline data identified changes in LFP amplitude associated with stimulation, seizure occurrences, and medication changes. We also noticed a circadian pattern of LFP amplitudes in all patients. Button-presses during seizure events via a mobile application served as a digital seizure diary and were associated with elevations in LFP power. SIGNIFICANCE We describe an initial cohort of patients with DRE utilizing a novel sensing DBS device to characterize potential LFP biomarkers of epilepsy that may be associated with seizure control after DBS in DRE. We also present a new workflow utilizing the Percept device that may optimize DBS programming using real-time and chronic LFP recording.
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Affiliation(s)
- Melissa M J Chua
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Matteo Vissani
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - David D Liu
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Frederic L W V J Schaper
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Aaron E L Warren
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rose Caston
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
| | - Barbara A Dworetzky
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ellen J Bubrick
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rani A Sarkis
- Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - John D Rolston
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Biomedical Engineering, University of Utah, Salt Lake City, Utah, USA
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah, USA
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Chandrabhatla AS, Pomeraniec IJ, Horgan TM, Wat EK, Ksendzovsky A. Landscape and future directions of machine learning applications in closed-loop brain stimulation. NPJ Digit Med 2023; 6:79. [PMID: 37106034 PMCID: PMC10140375 DOI: 10.1038/s41746-023-00779-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 02/17/2023] [Indexed: 04/29/2023] Open
Abstract
Brain stimulation (BStim) encompasses multiple modalities (e.g., deep brain stimulation, responsive neurostimulation) that utilize electrodes implanted in deep brain structures to treat neurological disorders. Currently, BStim is primarily used to treat movement disorders such as Parkinson's, though indications are expanding to include neuropsychiatric disorders like depression and schizophrenia. Traditional BStim systems are "open-loop" and deliver constant electrical stimulation based on manually-determined parameters. Advancements in BStim have enabled development of "closed-loop" systems that analyze neural biomarkers (e.g., local field potentials in the sub-thalamic nucleus) and adjust electrical modulation in a dynamic, patient-specific, and energy efficient manner. These closed-loop systems enable real-time, context-specific stimulation adjustment to reduce symptom burden. Machine learning (ML) has emerged as a vital component in designing these closed-loop systems as ML models can predict / identify presence of disease symptoms based on neural activity and adaptively learn to modulate stimulation. We queried the US National Library of Medicine PubMed database to understand the role of ML in developing closed-loop BStim systems to treat epilepsy, movement disorders, and neuropsychiatric disorders. Both neural and non-neural network ML algorithms have successfully been leveraged to create closed-loop systems that perform comparably to open-loop systems. For disorders in which the underlying neural pathophysiology is relatively well understood (e.g., Parkinson's, essential tremor), most work has involved refining ML models that can classify neural signals as aberrant or normal. The same is seen for epilepsy, where most current research has focused on identifying optimal ML model design and integrating closed-loop systems into existing devices. For neuropsychiatric disorders, where the underlying pathologic neural circuitry is still being investigated, research is focused on identifying biomarkers (e.g., local field potentials from brain nuclei) that ML models can use to identify onset of symptoms and stratify severity of disease.
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Affiliation(s)
- Anirudha S Chandrabhatla
- School of Medicine, University of Virginia Health Sciences Center, Charlottesville, VA, 22903, USA
| | - I Jonathan Pomeraniec
- Surgical Neurology Branch, National Institutes of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20892, USA.
- Department of Neurosurgery, University of Virginia Health Sciences Center, Charlottesville, VA, 22903, USA.
| | - Taylor M Horgan
- School of Medicine, University of Virginia Health Sciences Center, Charlottesville, VA, 22903, USA
| | - Elizabeth K Wat
- School of Medicine, University of Virginia Health Sciences Center, Charlottesville, VA, 22903, USA
| | - Alexander Ksendzovsky
- Department of Neurosurgery, University of Maryland Medical System, Baltimore, MD, 21201, USA
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A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans. Nat Neurosci 2023; 26:517-527. [PMID: 36804647 PMCID: PMC9991917 DOI: 10.1038/s41593-023-01260-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 01/17/2023] [Indexed: 02/22/2023]
Abstract
Advances in technologies that can record and stimulate deep brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the development of novel therapies for neurological and psychiatric disorders. Further progress, however, has been hindered by device limitations in that recording of single-neuron activity during freely moving behaviors in humans has not been possible. Additionally, implantable neurostimulation devices, currently approved for human use, have limited stimulation programmability and restricted full-duplex bidirectional capability. In this study, we developed a wearable bidirectional closed-loop neuromodulation system (Neuro-stack) and used it to record single-neuron and local field potential activity during stationary and ambulatory behavior in humans. Together with a highly flexible and customizable stimulation capability, the Neuro-stack provides an opportunity to investigate the neurophysiological basis of disease, develop improved responsive neuromodulation therapies, explore brain function during naturalistic behaviors in humans and, consequently, bridge decades of neuroscientific findings across species.
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6
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Liang YW, Lai ML, Chiu FM, Tseng HY, Lo YC, Li SJ, Chang CW, Chen PC, Chen YY. Experimental Verification for Numerical Simulation of Thalamic Stimulation-Evoked Calcium-Sensitive Fluorescence and Electrophysiology with Self-Assembled Multifunctional Optrode. BIOSENSORS 2023; 13:265. [PMID: 36832031 PMCID: PMC9953878 DOI: 10.3390/bios13020265] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/07/2023] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
Owing to its capacity to eliminate a long-standing methodological limitation, fiber photometry can assist research gaining novel insight into neural systems. Fiber photometry can reveal artifact-free neural activity under deep brain stimulation (DBS). Although evoking neural potential with DBS is an effective method for mediating neural activity and neural function, the relationship between DBS-evoked neural Ca2+ change and DBS-evoked neural electrophysiology remains unknown. Therefore, in this study, a self-assembled optrode was demonstrated as a DBS stimulator and an optical biosensor capable of concurrently recording Ca2+ fluorescence and electrophysiological signals. Before the in vivo experiment, the volume of tissue activated (VTA) was estimated, and the simulated Ca2+ signals were presented using Monte Carlo (MC) simulation to approach the realistic in vivo environment. When VTA and the simulated Ca2+ signals were combined, the distribution of simulated Ca2+ fluorescence signals matched the VTA region. In addition, the in vivo experiment revealed a correlation between the local field potential (LFP) and the Ca2+ fluorescence signal in the evoked region, revealing the relationship between electrophysiology and the performance of neural Ca2+ concentration behavior. Concurrent with the VTA volume, simulated Ca2+ intensity, and the in vivo experiment, these data suggested that the behavior of neural electrophysiology was consistent with the phenomenon of Ca2+ influx to neurons.
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Affiliation(s)
- Yao-Wen Liang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Ming-Liang Lai
- Graduate Institute of Intellectual Property, National Taipei University of Technology, Taipei 10608, Taiwan
| | - Feng-Mao Chiu
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Hsin-Yi Tseng
- The Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University and National Health Research Institutes, Taipei 11031, Taiwan
| | - Yu-Chun Lo
- The Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Ssu-Ju Li
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Ching-Wen Chang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Po-Chuan Chen
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - You-Yin Chen
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- The Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
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Tiruvadi V, James S, Howell B, Obatusin M, Crowell A, Riva-Posse P, Gross RE, McIntyre CC, Mayberg HS, Butera R. Mitigating Mismatch Compression in Differential Local Field Potentials. IEEE Trans Neural Syst Rehabil Eng 2023; 31:68-77. [PMID: 36288215 PMCID: PMC10784110 DOI: 10.1109/tnsre.2022.3217469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Deep brain stimulation (DBS) devices capable of measuring differential local field potentials ( ∂ LFP) enable neural recordings alongside clinical therapy. Efforts to identify oscillatory correlates of various brain disorders, or disease readouts, are growing but must proceed carefully to ensure readouts are not distorted by brain environment. In this report we identified, characterized, and mitigated a major source of distortion in ∂ LFP that we introduce as mismatch compression (MC). Using in vivo, in silico, and in vitro models of MC, we showed that impedance mismatches in the two recording electrodes can yield incomplete rejection of stimulation artifact and subsequent gain compression that distorts oscillatory power. We then developed and validated an opensource mitigation pipeline that mitigates the distortions arising from MC. This work enables more reliable oscillatory readouts for adaptive DBS applications.
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van Rheede JJ, Feldmann LK, Busch JL, Fleming JE, Mathiopoulou V, Denison T, Sharott A, Kühn AA. Diurnal modulation of subthalamic beta oscillatory power in Parkinson’s disease patients during deep brain stimulation. NPJ Parkinsons Dis 2022; 8:88. [PMID: 35804160 PMCID: PMC9270436 DOI: 10.1038/s41531-022-00350-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/10/2022] [Indexed: 11/09/2022] Open
Abstract
Beta-band activity in the subthalamic local field potential (LFP) is correlated with Parkinson’s disease (PD) symptom severity and is the therapeutic target of deep brain stimulation (DBS). While beta fluctuations in PD patients are well characterized on shorter timescales, it is not known how beta activity evolves around the diurnal cycle, outside a clinical setting. Here, we obtained chronic recordings (34 ± 13 days) of subthalamic beta power in PD patients implanted with the Percept DBS device during high-frequency DBS and analysed their diurnal properties as well as sensitivity to artifacts. Time of day explained 41 ± 9% of the variance in beta power (p < 0.001 in all patients), with increased beta during the day and reduced beta at night. Certain movements affected LFP quality, which may have contributed to diurnal patterns in some patients. Future DBS algorithms may benefit from taking such diurnal and artifactual fluctuations in beta power into account.
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9
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Chen PL, Chen YC, Tu PH, Liu TC, Chen MC, Wu HT, Yeap MC, Yeh CH, Lu CS, Chen CC. Subthalamic high-beta oscillation informs the outcome of deep brain stimulation in patients with Parkinson's disease. Front Hum Neurosci 2022; 16:958521. [PMID: 36158623 PMCID: PMC9493001 DOI: 10.3389/fnhum.2022.958521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe therapeutic effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) is related to the modulation of pathological neural activities, particularly the synchronization in the β band (13–35 Hz). However, whether the local β activity in the STN region can directly predict the stimulation outcome remains unclear.ObjectiveWe tested the hypothesis that low-β (13–20 Hz) and/or high-β (20–35 Hz) band activities recorded from the STN region can predict DBS efficacy.MethodsLocal field potentials (LFPs) were recorded in 26 patients undergoing deep brain stimulation surgery in the subthalamic nucleus area. Recordings were made after the implantation of the DBS electrode prior to its connection to a stimulator. The maximum normalized powers in the theta (4–7 Hz), alpha (7–13 Hz), low-β (13–20 Hz), high-β (20–35 Hz), and low-γ (40–55 Hz) subbands in the postoperatively recorded LFP were correlated with the stimulation-induced improvement in contralateral tremor or bradykinesia–rigidity. The distance between the contact selected for stimulation and the contact with the maximum subband power was correlated with the stimulation efficacy. Following the identification of the potential predictors by the significant correlations, a multiple regression analysis was performed to evaluate their effect on the outcome.ResultsThe maximum high-β power was positively correlated with bradykinesia–rigidity improvement (rs = 0.549, p < 0.0001). The distance to the contact with maximum high-β power was negatively correlated with bradykinesia–rigidity improvement (rs = −0.452, p < 0.001). No significant correlation was observed with low-β power. The maximum high-β power and the distance to the contact with maximum high-β power were both significant predictors for bradykinesia–rigidity improvement in the multiple regression analysis, explaining 37.4% of the variance altogether. Tremor improvement was not significantly correlated with any frequency.ConclusionHigh-β oscillations, but not low-β oscillations, recorded from the STN region with the DBS lead can inform stimulation-induced improvement in contralateral bradykinesia–rigidity in patients with PD. High-β oscillations can help refine electrode targeting and inform contact selection for DBS therapy.
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Affiliation(s)
- Po-Lin Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Yi-Chieh Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Po-Hsun Tu
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Tzu-Chi Liu
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Department of Mathematics, National Taiwan University, Taipei, Taiwan
| | - Min-Chi Chen
- Department of Public Health, Biostatistics Consulting Center, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Hau-Tieng Wu
- Department of Mathematics, Duke University, Durham, NC, United States
- Department of Statistical Science, Duke University, Durham, NC, United States
| | - Mun-Chun Yeap
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chih-Hua Yeh
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Neuroradiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chin-Song Lu
- Professor Lu Neurological Clinic, Taoyuan, Taiwan
| | - Chiung-Chu Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- *Correspondence: Chiung-Chu Chen
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10
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Warsi NM, Yan H, Wong SM, Yau I, Breitbart S, Go C, Gorodetsky C, Fasano A, Kalia SK, Rutka JT, Vaughan K, Ibrahim GM. Vagus Nerve Stimulation Modulates Phase-Amplitude Coupling in Thalamic Local Field Potentials. Neuromodulation 2022; 26:601-606. [PMID: 35840521 DOI: 10.1016/j.neurom.2022.05.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 04/26/2022] [Accepted: 05/12/2022] [Indexed: 11/17/2022]
Abstract
OBJECTIVE The antiseizure effects of vagus nerve stimulation (VNS) are thought to be mediated by the modulation of afferent thalamocortical circuitry. Cross-frequency phase-amplitude coupling (PAC) is a mechanism of hierarchical network coordination across multiple spatiotemporal scales. In this study, we leverage local field potential (LFP) recordings from the centromedian (CM) (n = 3) and anterior (ATN) (n = 2) nuclei in five patients with tandem thalamic deep brain stimulation and VNS to study neurophysiological changes in the thalamus in response to VNS. MATERIALS AND METHODS Bipolar LFP data were recorded from contact pairs spanning target nuclei in VNS "on" and "off" states. RESULTS Active VNS was associated with increased PAC between theta, alpha, and beta phase and gamma amplitude in CM (q < 0.05). Within the ATN, PAC changes also were observed, although these were less robust. In both nuclei, active VNS also modulated interhemispheric bithalamic functional connectivity. CONCLUSIONS We report that VNS is associated with enhanced PAC and coordinated interhemispheric interactions within and between thalamic nuclei, respectively. These findings advance understanding of putative neurophysiological effects of acute VNS and contextualize previous animal and human studies showing distributed cortical synchronization after VNS.
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Affiliation(s)
- Nebras M Warsi
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada
| | - Han Yan
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada; Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Simeon M Wong
- Department of Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Ivanna Yau
- Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Sara Breitbart
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Cristina Go
- Division of Neurology, Hospital for Sick Children, Toronto, Ontario, Canada
| | | | - Alfonso Fasano
- Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, UHN, Toronto, Ontario, Canada; Division of Neurology, University of Toronto, Toronto, Ontario, Canada
| | - Suneil K Kalia
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, Ontario, Canada
| | - James T Rutka
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Kerry Vaughan
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada
| | - George M Ibrahim
- Division of Neurosurgery, Hospital for Sick Children, Toronto, Ontario, Canada; Department of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada; Department of Neuroscience and Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada.
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11
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Toward therapeutic electrophysiology: beta-band suppression as a biomarker in chronic local field potential recordings. NPJ Parkinsons Dis 2022; 8:44. [PMID: 35440571 PMCID: PMC9018912 DOI: 10.1038/s41531-022-00301-2] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 03/04/2022] [Indexed: 11/08/2022] Open
Abstract
Adaptive deep brain stimulation (aDBS) is a promising concept for feedback-based neurostimulation, with the potential of clinical implementation with the sensing-enabled Percept neurostimulator. We aim to characterize chronic electrophysiological activity during stimulation and to validate beta-band activity as a biomarker for bradykinesia. Subthalamic activity was recorded during stepwise stimulation amplitude increase OFF medication in 10 Parkinson's patients during rest and finger tapping. Offline analysis of wavelet-transformed beta-band activity and assessment of inter-variable relationships in linear mixed effects models were implemented. There was a stepwise suppression of low-beta activity with increasing stimulation intensity (p = 0.002). Low-beta power was negatively correlated with movement speed and predictive for velocity improvements (p < 0.001), stimulation amplitude for beta suppression (p < 0.001). Here, we characterize beta-band modulation as a chronic biomarker for motor performance. Our investigations support the use of electrophysiology in therapy optimization, providing evidence for the use of biomarker analysis for clinical aDBS.
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Swinnen BEKS, Buijink AW, Piña-Fuentes D, de Bie RMA, Beudel M. Diving into the Subcortex: The Potential of Chronic Subcortical Sensing for Unravelling Basal Ganglia Function and Optimization of Deep Brain STIMULATION. Neuroimage 2022; 254:119147. [PMID: 35346837 DOI: 10.1016/j.neuroimage.2022.119147] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 03/23/2022] [Accepted: 03/24/2022] [Indexed: 11/18/2022] Open
Abstract
Subcortical structures are a relative neurophysiological 'terra incognita' owing to their location within the skull. While perioperative subcortical sensing has been performed for more than 20 years, the neurophysiology of the basal ganglia in the home setting has remained almost unexplored. However, with the recent advent of implantable pulse generators (IPG) that are able to record neural activity, the opportunity to chronically record local field potentials (LFPs) directly from electrodes implanted for deep brain stimulation opens up. This allows for a breakthrough of chronic subcortical sensing into fundamental research and clinical practice. In this review an extensive overview of the current state of subcortical sensing is provided. The widespread potential of chronic subcortical sensing for investigational and clinical use is discussed. Finally, status and future perspectives of the most promising application of chronic subcortical sensing -i.e., adaptive deep brain stimulation (aDBS)- are discussed in the context of movement disorders. The development of aDBS based on both chronic subcortical and cortical sensing has the potential to dramatically change clinical practice and the life of patients with movement disorders. However, several barriers still stand in the way of clinical implementation. Advancements regarding IPG and lead technology, physiomarkers, and aDBS algorithms as well as harnessing artificial intelligence, multimodality and sensing in the naturalistic setting are needed to bring aDBS to clinical practice.
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Affiliation(s)
- Bart E K S Swinnen
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland.
| | - Arthur W Buijink
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
| | - Dan Piña-Fuentes
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
| | - Rob M A de Bie
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
| | - Martijn Beudel
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical, Centers, Amsterdam Neuroscience, University of Amsterdam, PO Box 22660, Amsterdam 1100DD, the Netherland
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Pozzi NG, Isaias IU. Adaptive deep brain stimulation: Retuning Parkinson's disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:273-284. [PMID: 35034741 DOI: 10.1016/b978-0-12-819410-2.00015-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.
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Affiliation(s)
- Nicoló G Pozzi
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany
| | - Ioannis U Isaias
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
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Arlotti M, Colombo M, Bonfanti A, Mandat T, Lanotte MM, Pirola E, Borellini L, Rampini P, Eleopra R, Rinaldo S, Romito L, Janssen MLF, Priori A, Marceglia S. A New Implantable Closed-Loop Clinical Neural Interface: First Application in Parkinson's Disease. Front Neurosci 2021; 15:763235. [PMID: 34949982 PMCID: PMC8689059 DOI: 10.3389/fnins.2021.763235] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Accepted: 11/04/2021] [Indexed: 11/13/2022] Open
Abstract
Deep brain stimulation (DBS) is used for the treatment of movement disorders, including Parkinson’s disease, dystonia, and essential tremor, and has shown clinical benefits in other brain disorders. A natural path for the improvement of this technique is to continuously observe the stimulation effects on patient symptoms and neurophysiological markers. This requires the evolution of conventional deep brain stimulators to bidirectional interfaces, able to record, process, store, and wirelessly communicate neural signals in a robust and reliable fashion. Here, we present the architecture, design, and first use of an implantable stimulation and sensing interface (AlphaDBSR System) characterized by artifact-free recording and distributed data management protocols. Its application in three patients with Parkinson’s disease (clinical trial n. NCT04681534) is shown as a proof of functioning of a clinically viable implanted brain-computer interface (BCI) for adaptive DBS. Reliable artifact free-recordings, and chronic long-term data and neural signal management are in place.
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Affiliation(s)
| | | | - Andrea Bonfanti
- Newronika SpA, Milan, Italy.,Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
| | - Tomasz Mandat
- Narodowy Instytut Onkologii im. Marii Skłodowskiej-Curie, Warsaw, Poland
| | - Michele Maria Lanotte
- Department of Neuroscience, University of Torino, Torino, Italy.,AOU Città della Salute e della Scienza, Molinette Hospital, Turin, Italy
| | - Elena Pirola
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Linda Borellini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Paolo Rampini
- Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy
| | - Roberto Eleopra
- Movement Disorders Unit, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Sara Rinaldo
- Movement Disorders Unit, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Luigi Romito
- Movement Disorders Unit, Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico C. Besta, Milan, Italy
| | - Marcus L F Janssen
- Department of Neurology and Clinical Neurophysiology, Maastricht University Medical Center, Maastricht, Netherlands.,Faculty of Health, Medicine and Life Sciences, School for Mental Health and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Alberto Priori
- Department of Health Sciences, Aldo Ravelli Research Center for Neurotechnology and Experimental Neurotherapeutics, University of Milan, Milan, Italy
| | - Sara Marceglia
- Dipartimento di Ingegneria e Architettura, Università degli Studi di Trieste, Trieste, Italy
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