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Olaru M, Cernera S, Hahn A, Wozny TA, Anso J, de Hemptinne C, Little S, Neumann WJ, Abbasi-Asl R, Starr PA. Motor network gamma oscillations in chronic home recordings predict dyskinesia in Parkinson's disease. Brain 2024; 147:2038-2052. [PMID: 38195196 DOI: 10.1093/brain/awae004] [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: 08/09/2023] [Revised: 12/17/2023] [Accepted: 12/21/2023] [Indexed: 01/11/2024] Open
Abstract
In Parkinson's disease, imbalances between 'antikinetic' and 'prokinetic' patterns of neuronal oscillatory activity are related to motor dysfunction. Invasive brain recordings from the motor network have suggested that medical or surgical therapy can promote a prokinetic state by inducing narrowband gamma rhythms (65-90 Hz). Excessive narrowband gamma in the motor cortex promotes dyskinesia in rodent models, but the relationship between narrowband gamma and dyskinesia in humans has not been well established. To assess this relationship, we used a sensing-enabled deep brain stimulator system, attached to both motor cortex and basal ganglia (subthalamic or pallidal) leads, paired with wearable devices that continuously tracked motor signs in the contralateral upper limbs. We recorded 984 h of multisite field potentials in 30 hemispheres of 16 subjects with Parkinson's disease (2/16 female, mean age 57 ± 12 years) while at home on usual antiparkinsonian medications. Recordings were done 2-4 weeks after implantation, prior to starting therapeutic stimulation. Narrowband gamma was detected in the precentral gyrus, subthalamic nucleus or both structures on at least one side of 92% of subjects with a clinical history of dyskinesia. Narrowband gamma was not detected in the globus pallidus. Narrowband gamma spectral power in both structures co-fluctuated similarly with contralateral wearable dyskinesia scores (mean correlation coefficient of ρ = 0.48 with a range of 0.12-0.82 for cortex, ρ = 0.53 with a range of 0.5-0.77 for subthalamic nucleus). Stratification analysis showed the correlations were not driven by outlier values, and narrowband gamma could distinguish 'on' periods with dyskinesia from 'on' periods without dyskinesia. Time lag comparisons confirmed that gamma oscillations herald dyskinesia onset without a time lag in either structure when using 2-min epochs. A linear model incorporating the three oscillatory bands (beta, theta/alpha and narrowband gamma) increased the predictive power of dyskinesia for several subject hemispheres. We further identified spectrally distinct oscillations in the low gamma range (40-60 Hz) in three subjects, but the relationship of low gamma oscillations to dyskinesia was variable. Our findings support the hypothesis that excessive oscillatory activity at 65-90 Hz in the motor network tracks with dyskinesia similarly across both structures, without a detectable time lag. This rhythm may serve as a promising control signal for closed-loop deep brain stimulation using either cortical or subthalamic detection.
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Affiliation(s)
- Maria Olaru
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Stephanie Cernera
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Amelia Hahn
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Thomas A Wozny
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Juan Anso
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Coralie de Hemptinne
- Department of Neurology, University of Florida Gainesville, Gainesville, FL 32611, USA
| | - Simon Little
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - 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 10117, Germany
| | - Reza Abbasi-Asl
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Philip A Starr
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
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Quan Z, Li Y, Wang S. Multi-timescale neuromodulation strategy for closed-loop deep brain stimulation in Parkinson's disease. J Neural Eng 2024; 21:036006. [PMID: 38653252 DOI: 10.1088/1741-2552/ad4210] [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: 02/01/2024] [Accepted: 04/23/2024] [Indexed: 04/25/2024]
Abstract
Objective.Beta triggered closed-loop deep brain stimulation (DBS) shows great potential for improving the efficacy while reducing side effect for Parkinson's disease. However, there remain great challenges due to the dynamics and stochasticity of neural activities. In this study, we aimed to tune the amplitude of beta oscillations with different time scales taking into account influence of inherent variations in the basal ganglia-thalamus-cortical circuit.Approach. A dynamic basal ganglia-thalamus-cortical mean-field model was established to emulate the medication rhythm. Then, a dynamic target model was designed to embody the multi-timescale dynamic of beta power with milliseconds, seconds and minutes. Moreover, we proposed a closed-loop DBS strategy based on a proportional-integral-differential (PID) controller with the dynamic control target. In addition, the bounds of stimulation amplitude increments and different parameters of the dynamic target were considered to meet the clinical constraints. The performance of the proposed closed-loop strategy, including beta power modulation accuracy, mean stimulation amplitude, and stimulation variation were calculated to determine the PID parameters and evaluate neuromodulation performance in the computational dynamic mean-field model.Main results. The Results show that the dynamic basal ganglia-thalamus-cortical mean-field model simulated the medication rhythm with the fasted and the slowest rate. The dynamic control target reflected the temporal variation in beta power from milliseconds to minutes. With the proposed closed-loop strategy, the beta power tracked the dynamic target with a smoother stimulation sequence compared with closed-loop DBS with the constant target. Furthermore, the beta power could be modulated to track the control target under different long-term targets, modulation strengths, and bounds of the stimulation increment.Significance. This work provides a new method of closed-loop DBS for multi-timescale beta power modulation with clinical constraints.
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Affiliation(s)
- Zhaoyu Quan
- Academy for Engineering and Technology, Fudan University, Shanghai, People's Republic of China
- Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, People's Republic of China
- Engineering Research Center of AI & Robotics, Ministry of Education, Fudan University, Shanghai, People's Republic of China
| | - Yan Li
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Shanghai, Ministry of Education, People's Republic of China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China
- Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China
| | - Shouyan Wang
- Shanghai Engineering Research Center of AI & Robotics, Fudan University, Shanghai, People's Republic of China
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Shanghai, Ministry of Education, People's Republic of China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China
- Zhangjiang Fudan International Innovation Center, Shanghai, People's Republic of China
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3
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Li L, Zhang B, Zhao W, Sheng D, Yin L, Sheng X, Yao D. Multimodal Technologies for Closed-Loop Neural Modulation and Sensing. Adv Healthc Mater 2024:e2303289. [PMID: 38640468 DOI: 10.1002/adhm.202303289] [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: 09/27/2023] [Revised: 03/11/2024] [Indexed: 04/21/2024]
Abstract
Existing methods for studying neural circuits and treating neurological disorders are typically based on physical and chemical cues to manipulate and record neural activities. These approaches often involve predefined, rigid, and unchangeable signal patterns, which cannot be adjusted in real time according to the patient's condition or neural activities. With the continuous development of neural interfaces, conducting in vivo research on adaptive and modifiable treatments for neurological diseases and neural circuits is now possible. In this review, current and potential integration of various modalities to achieve precise, closed-loop modulation, and sensing in neural systems are summarized. Advanced materials, devices, or systems that generate or detect electrical, magnetic, optical, acoustic, or chemical signals are highlighted and utilized to interact with neural cells, tissues, and networks for closed-loop interrogation. Further, the significance of developing closed-loop techniques for diagnostics and treatment of neurological disorders such as epilepsy, depression, rehabilitation of spinal cord injury patients, and exploration of brain neural circuit functionality is elaborated.
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Affiliation(s)
- Lizhu Li
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and the Center for Medical Genetics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Bozhen Zhang
- School of Materials Science and Engineering, The Key Laboratory of Advanced Materials of Ministry of Education, State Key Laboratory of New Ceramics and Fine Processing, Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing, 100084, China
| | - Wenxin Zhao
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Institute for Precision Medicine, Laboratory of Flexible Electronics Technology, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China
| | - David Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Institute for Precision Medicine, Laboratory of Flexible Electronics Technology, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China
| | - Lan Yin
- School of Materials Science and Engineering, The Key Laboratory of Advanced Materials of Ministry of Education, State Key Laboratory of New Ceramics and Fine Processing, Laboratory of Flexible Electronics Technology, Tsinghua University, Beijing, 100084, China
| | - Xing Sheng
- Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Institute for Precision Medicine, Laboratory of Flexible Electronics Technology, IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, 100084, China
| | - Dezhong Yao
- Sichuan Provincial Key Laboratory for Human Disease Gene Study and the Center for Medical Genetics, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China
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Abdulbaki A, Doll T, Helgers S, Heissler HE, Voges J, Krauss JK, Schwabe K, Alam M. Subthalamic Nucleus Deep Brain Stimulation Restores Motor and Sensorimotor Cortical Neuronal Oscillatory Activity in the Free-Moving 6-Hydroxydopamine Lesion Rat Parkinson Model. Neuromodulation 2024; 27:489-499. [PMID: 37002052 DOI: 10.1016/j.neurom.2023.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 12/28/2022] [Accepted: 01/04/2023] [Indexed: 03/31/2023]
Abstract
OBJECTIVES Enhanced beta oscillations in cortical-basal ganglia (BG) thalamic circuitries have been linked to clinical symptoms of Parkinson's disease. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces beta band activity in BG regions, whereas little is known about activity in cortical regions. In this study, we investigated the effect of STN DBS on the spectral power of oscillatory activity in the motor cortex (MCtx) and sensorimotor cortex (SMCtx) by recording via an electrocorticogram (ECoG) array in free-moving 6-hydroxydopamine (6-OHDA) lesioned rats and sham-lesioned controls. MATERIALS AND METHODS Male Sprague-Dawley rats (250-350 g) were injected either with 6-OHDA or with saline in the right medial forebrain bundle, under general anesthesia. A stimulation electrode was then implanted in the ipsilateral STN, and an ECoG array was placed subdurally above the MCtx and SMCtx areas. Six days after the second surgery, the free-moving rats were individually recorded in three conditions: 1) basal activity, 2) during STN DBS, and 3) directly after STN DBS. RESULTS In 6-OHDA-lesioned rats (N = 8), the relative power of theta band activity was reduced, whereas activity of broad-range beta band (12-30 Hz) along with two different subbeta bands, that is, low (12-30 Hz) and high (20-30 Hz) beta band and gamma band, was higher in MCtx and SMCtx than in sham-lesioned controls (N = 7). This was, to some extent, reverted toward control level by STN DBS during and after stimulation. No major differences were found between contacts of the electrode grid or between MCtx and SMCtx. CONCLUSION Loss of nigrostriatal dopamine leads to abnormal oscillatory activity in both MCtx and SMCtx, which is compensated by STN stimulation, suggesting that parkinsonism-related oscillations in the cortex and BG are linked through their anatomic connections.
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Affiliation(s)
- Arif Abdulbaki
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany.
| | - Theodor Doll
- Fraunhofer Institute for Toxicology and Experimental Medicine, Hannover, Germany
| | - Simeon Helgers
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Hans E Heissler
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Jürgen Voges
- Department of Stereotactic Neurosurgery, University Hospital Magdeburg, Magdeburg, Germany
| | - Joachim K Krauss
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Kerstin Schwabe
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
| | - Mesbah Alam
- Hannover Medical School, Department of Neurosurgery, Hannover, Germany
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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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6
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Sermon JJ, Starr PA, Denison T, Duchet B. Pre-existing oscillatory activity as a condition for sub-harmonic entrainment of finely tuned gamma in Parkinson's disease. Brain Stimul 2024; 17:488-490. [PMID: 38685260 PMCID: PMC7615964 DOI: 10.1016/j.brs.2024.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 02/26/2024] [Indexed: 05/02/2024] Open
Affiliation(s)
- James J Sermon
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom; Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford, United Kingdom
| | - Philip A Starr
- Department of Neurological Surgery and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Timothy Denison
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom; Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford, Oxford, United Kingdom
| | - Benoit Duchet
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.
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Schmidt SL, Chowdhury AH, Mitchell KT, Peters JJ, Gao Q, Lee HJ, Genty K, Chow SC, Grill WM, Pajic M, Turner DA. At home adaptive dual target deep brain stimulation in Parkinson's disease with proportional control. Brain 2024; 147:911-922. [PMID: 38128546 PMCID: PMC10907084 DOI: 10.1093/brain/awad429] [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: 05/22/2023] [Revised: 10/24/2023] [Accepted: 11/18/2023] [Indexed: 12/23/2023] Open
Abstract
Continuous deep brain stimulation (cDBS) of the subthalamic nucleus (STN) or globus pallidus is an effective treatment for the motor symptoms of Parkinson's disease. The relative benefit of one region over the other is of great interest but cannot usually be compared in the same patient. Simultaneous DBS of both regions may synergistically increase the therapeutic benefit. Continuous DBS is limited by a lack of responsiveness to dynamic, fluctuating symptoms intrinsic to the disease. Adaptive DBS (aDBS) adjusts stimulation in response to biomarkers to improve efficacy, side effects, and efficiency. We combined bilateral DBS of both STN and globus pallidus (dual target DBS) in a prospective within-participant, clinical trial in six patients with Parkinson's disease (n = 6, 55-65 years, n = 2 females). Dual target cDBS was tested for Parkinson's disease symptom control annually over 2 years, measured by motor rating scales, on time without dyskinesia, and medication reduction. Random amplitude experiments probed system dynamics to estimate parameters for aDBS. We then implemented proportional-plus-integral aDBS using a novel distributed (off-implant) architecture. In the home setting, we collected tremor and dyskinesia scores as well as individualized β and DBS amplitudes. Dual target cDBS reduced motor symptoms as measured by Unified Parkinson's Disease Rating Scale (UPDRS) to a greater degree than either region alone (P < 0.05, linear mixed model) in the cohort. The amplitude of β-oscillations in the STN correlated to the speed of hand grasp movements for five of six participants (P < 0.05, Pearson correlation). Random amplitude experiments provided insight into temporal windowing to avoid stimulation artefacts and demonstrated a correlation between STN β amplitude and DBS amplitude. Proportional plus integral control of aDBS reduced average power, while preserving UPDRS III scores in the clinic (P = 0.28, Wilcoxon signed rank), and tremor and dyskinesia scores during blinded testing at home (n = 3, P > 0.05, Wilcoxon ranked sum). In the home setting, DBS power reductions were slight but significant. Dual target cDBS may offer an improvement in treatment of motor symptoms of Parkinson's disease over DBS of either the STN or globus pallidus alone. When combined with proportional plus integral aDBS, stimulation power may be reduced, while preserving the increased benefit of dual target DBS.
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Affiliation(s)
- Stephen L Schmidt
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Afsana H Chowdhury
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA
| | - Kyle T Mitchell
- Department of Neurology, Duke University Medical Center, Durham, NC 27710, USA
| | - Jennifer J Peters
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Qitong Gao
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA
| | - Hui-Jie Lee
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA
| | - Katherine Genty
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
| | - Shein-Chung Chow
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27710, USA
| | - Warren M Grill
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
| | - Miroslav Pajic
- Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA
| | - Dennis A Turner
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
- Department of Neurosurgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710, USA
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8
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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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9
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Verma AK, Nandakumar B, Acedillo K, Yu Y, Marshall E, Schneck D, Fiecas M, Wang J, MacKinnon CD, Howell MJ, Vitek JL, Johnson LA. Slow-wave sleep dysfunction in mild parkinsonism is associated with excessive beta and reduced delta oscillations in motor cortex. Front Neurosci 2024; 18:1338624. [PMID: 38449736 PMCID: PMC10915200 DOI: 10.3389/fnins.2024.1338624] [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: 11/14/2023] [Accepted: 01/17/2024] [Indexed: 03/08/2024] Open
Abstract
Increasing evidence suggests slow-wave sleep (SWS) dysfunction in Parkinson's disease (PD) is associated with faster disease progression, cognitive impairment, and excessive daytime sleepiness. Beta oscillations (8-35 Hz) in the basal ganglia thalamocortical (BGTC) network are thought to play a role in the development of cardinal motor signs of PD. The role cortical beta oscillations play in SWS dysfunction in the early stage of parkinsonism is not understood, however. To address this question, we used a within-subject design in a nonhuman primate (NHP) model of PD to record local field potentials from the primary motor cortex (MC) during sleep across normal and mild parkinsonian states. The MC is a critical node in the BGTC network, exhibits pathological oscillations with depletion in dopamine tone, and displays high amplitude slow oscillations during SWS. The MC is therefore an appropriate recording site to understand the neurophysiology of SWS dysfunction in parkinsonism. We observed a reduction in SWS quantity (p = 0.027) in the parkinsonian state compared to normal. The cortical delta (0.5-3 Hz) power was reduced (p = 0.038) whereas beta (8-35 Hz) power was elevated (p = 0.001) during SWS in the parkinsonian state compared to normal. Furthermore, SWS quantity positively correlated with delta power (r = 0.43, p = 0.037) and negatively correlated with beta power (r = -0.65, p < 0.001). Our findings support excessive beta oscillations as a mechanism for SWS dysfunction in mild parkinsonism and could inform the development of neuromodulation therapies for enhancing SWS in people with PD.
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Affiliation(s)
- Ajay K. Verma
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Bharadwaj Nandakumar
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Kit Acedillo
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Ying Yu
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Ethan Marshall
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - David Schneck
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, United States
| | - Mark Fiecas
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, United States
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Colum D. MacKinnon
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Michael J. Howell
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
| | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, United States
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10
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Milanowski J, Nuszkiewicz J, Lisewska B, Lisewski P, Szewczyk-Golec K. Adipokines, Vitamin D, and Selected Inflammatory Biomarkers among Parkinson's Disease Patients with and without Dyskinesia: A Preliminary Examination. Metabolites 2024; 14:106. [PMID: 38392998 PMCID: PMC10890066 DOI: 10.3390/metabo14020106] [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: 12/29/2023] [Revised: 02/01/2024] [Accepted: 02/02/2024] [Indexed: 02/25/2024] Open
Abstract
Parkinson's disease (PD), a widely recognized neurodegenerative disorder, is characterized by a spectrum of symptoms including motor fluctuations and dyskinesia. Neuroinflammation and dysregulation of adipokines are increasingly implicated in the progression of PD. This preliminary study investigated the levels of inflammatory biomarkers and adipokines, namely interleukin-6 (IL-6), tumor necrosis factor α (TNF-α), C-reactive protein (CRP), visfatin, progranulin, and 25(OH)-vitamin D in 52 PD patients, divided equally between those with and without dyskinesia and 26 healthy controls. Significant differences in the levels of IL-6, TNF-α, visfatin, and progranulin were noted between the groups. Patients with dyskinesia exhibited notably higher IL-6 levels compared to controls, and TNF-α was significantly elevated in both PD patient groups relative to the control group. Additionally, visfatin levels were higher in PD patients without dyskinesia as opposed to those with dyskinesia, and progranulin levels were elevated in the non-dyskinetic PD group compared to controls. The findings highlight the potential role of the examined biomarkers in the pathophysiology of PD. Changes in levels of the tested inflammatory biomarkers and adipokines might be associated with Parkinson's disease and its symptoms such as dyskinesia.
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Affiliation(s)
- Jan Milanowski
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 24 Karłowicza St., 85-092 Bydgoszcz, Poland
| | - Jarosław Nuszkiewicz
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 24 Karłowicza St., 85-092 Bydgoszcz, Poland
| | - Beata Lisewska
- Medical Center "Neuromed", 14 Jana Biziela St., 85-163 Bydgoszcz, Poland
| | - Paweł Lisewski
- Medical Center "Neuromed", 14 Jana Biziela St., 85-163 Bydgoszcz, Poland
| | - Karolina Szewczyk-Golec
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 24 Karłowicza St., 85-092 Bydgoszcz, Poland
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11
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Sellers KK, Cohen JL, Khambhati AN, Fan JM, Lee AM, Chang EF, Krystal AD. Closed-loop neurostimulation for the treatment of psychiatric disorders. Neuropsychopharmacology 2024; 49:163-178. [PMID: 37369777 PMCID: PMC10700557 DOI: 10.1038/s41386-023-01631-2] [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: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023]
Abstract
Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.
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Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joshua L Cohen
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
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12
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Todorov D, Schnitzler A, Hirschmann J. Parkinsonian rest tremor can be distinguished from voluntary hand movements based on subthalamic and cortical activity. Clin Neurophysiol 2024; 157:146-155. [PMID: 38030516 DOI: 10.1016/j.clinph.2023.10.018] [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: 02/23/2023] [Revised: 10/19/2023] [Accepted: 10/31/2023] [Indexed: 12/01/2023]
Abstract
OBJECTIVE To distinguish Parkinsonian rest tremor and different voluntary hand movements by analyzing brain activity. METHODS We re-analyzed magnetoencephalography and local field potential recordings from the subthalamic nucleus of six patients with Parkinson's disease. Data were obtained after withdrawal from dopaminergic medication (Med Off) and after administration of levodopa (Med On). Using gradient-boosted tree learning, we classified epochs as tremor, fist-clenching, forearm extension or tremor-free rest. RESULTS Subthalamic activity alone was insufficient for distinguishing the four different motor states (balanced accuracy mean: 38%, std: 7%). The combination of cortical and subthalamic features, in contrast, allowed for a much more accurate classification (balanced accuracy mean: 75%, std: 17%). Adding a single cortical area improved balanced accuracy by 17% on average, as compared to classification based on subthalamic activity alone. In most patients, the most informative cortical areas were sensorimotor cortical regions. Decoding performance was similar in Med On and Med Off. CONCLUSIONS Electrophysiological recordings allow for distinguishing several motor states, provided that cortical signals are monitored in addition to subthalamic activity. SIGNIFICANCE By combining cortical recordings, subcortical recordings and machine learning, adaptive deep brain stimulation systems might be able to detect tremor specifically and to respond adequately to several motor states.
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Affiliation(s)
- Dmitrii Todorov
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany; Centre de Recherche en Neurosciences de Lyon - Inserm U1028, 69675 Bron, France; Centre de Recerca Matemática, Campus UAB edifici C, 08193 Bellaterra, Barcelona, Spain
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany; Center for Movement Disorders and Neuromodulation, Department of Neurology Medical Faculty, Heinrich Heine University, 40225 Düsseldorf, Germany
| | - Jan Hirschmann
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany.
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13
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Guehl D, Guillaud E, Langbour N, Doat E, Auzou N, Courtin E, Branchard O, Engelhardt J, Benazzouz A, Eusebio A, Cuny E, Burbaud P. Usefulness of thalamic beta activity for closed-loop therapy in essential tremor. Sci Rep 2023; 13:22332. [PMID: 38102180 PMCID: PMC10724233 DOI: 10.1038/s41598-023-49511-5] [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: 05/18/2023] [Accepted: 12/08/2023] [Indexed: 12/17/2023] Open
Abstract
A partial loss of effectiveness of deep brain stimulation of the ventral intermediate nucleus of the thalamus (VIM) has been reported in some patients with essential tremor (ET), possibly due to habituation to permanent stimulation. This study focused on the evolution of VIM local-field potentials (LFPs) data over time to assess the long-term feasibility of closed-loop therapy based on thalamic activity. We performed recordings of thalamic LFPs in 10 patients with severe ET using the ACTIVA™ PC + S (Medtronic plc.) allowing both recordings and stimulation in the same region. Particular attention was paid to describing the evolution of LFPs over time from 3 to 24 months after surgery when the stimulation was Off. We demonstrated a significant decrease in high-beta LFPs amplitude during movements inducing tremor in comparison to the rest condition 3 months after surgery (1.91 ± 0.89 at rest vs. 1.27 ± 1.37 µV2/Hz during posture/action for N = 8/10 patients; p = 0.010), 12 months after surgery (2.92 ± 1.75 at rest vs. 2.12 ± 1.78 µV2/Hz during posture/action for N = 7/10 patients; p = 0.014) and 24 months after surgery (2.32 ± 0.35 at rest vs 0.75 ± 0.78 µV2/Hz during posture/action for 4/6 patients; p = 0.017). Among the patients who exhibited a significant decrease of high-beta LFP amplitude when stimulation was Off, this phenomenon was observed at least twice during the follow-up. Although the extent of this decrease in high-beta LFPs amplitude during movements inducing tremor may vary over time, this thalamic biomarker of movement could potentially be usable for closed-loop therapy in the long term.
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Affiliation(s)
- Dominique Guehl
- Service de Neurophysiologie Clinique de l'enfant et de l'adulte, Hôpital Pellegrin, Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France.
- Institut des Maladies Neurodégénératives, Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000, Bordeaux, France.
| | - Etienne Guillaud
- Institute of Cognitive and Integrative Neurosciences, Univ. Bordeaux, CNRS, INCIA, UMR 5287, F-33000, Bordeaux, France
| | - Nicolas Langbour
- Centre de Recherche en Psychiatrie, CH de la Milétrie, 86000, Poitiers, France
| | - Emilie Doat
- Institute of Cognitive and Integrative Neurosciences, Univ. Bordeaux, CNRS, INCIA, UMR 5287, F-33000, Bordeaux, France
| | - Nicolas Auzou
- Institut des Maladies Neurodégénératives Clinique (IMNc), Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France
| | - Edouard Courtin
- Service de Neurophysiologie Clinique de l'enfant et de l'adulte, Hôpital Pellegrin, Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France
| | | | | | - Abdelhamid Benazzouz
- Institut des Maladies Neurodégénératives, Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000, Bordeaux, France
| | - Alexandre Eusebio
- Department of Neurology and Movement Disorders, APHM, Hôpitaux Universitaire de Marseille, Marseille, France
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Univ, CNRS, Marseille, France
| | - Emmanuel Cuny
- Service de Neurochirurgie, CHU de Bordeaux, Bordeaux, France
| | - Pierre Burbaud
- Service de Neurophysiologie Clinique de l'enfant et de l'adulte, Hôpital Pellegrin, Pôle des Neurosciences Cliniques, CHU de Bordeaux, Bordeaux, France
- Institut des Maladies Neurodégénératives, Univ. Bordeaux, CNRS, IMN, UMR 5293, F-33000, Bordeaux, France
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14
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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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15
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Wilkins KB, Melbourne JA, Akella P, Bronte-Stewart HM. Unraveling the complexities of programming neural adaptive deep brain stimulation in Parkinson's disease. Front Hum Neurosci 2023; 17:1310393. [PMID: 38094147 PMCID: PMC10716917 DOI: 10.3389/fnhum.2023.1310393] [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: 10/09/2023] [Accepted: 11/09/2023] [Indexed: 02/01/2024] Open
Abstract
Over the past three decades, deep brain stimulation (DBS) for Parkinson's disease (PD) has been applied in a continuous open loop fashion, unresponsive to changes in a given patient's state or symptoms over the course of a day. Advances in recent neurostimulator technology enable the possibility for closed loop adaptive DBS (aDBS) for PD as a treatment option in the near future in which stimulation adjusts in a demand-based manner. Although aDBS offers great clinical potential for treatment of motor symptoms, it also brings with it the need for better understanding how to implement it in order to maximize its benefits. In this perspective, we outline considerations for programing several key parameters for aDBS based on our experience across several aDBS-capable research neurostimulators. At its core, aDBS hinges on successful identification of relevant biomarkers that can be measured reliably in real-time working in cohesion with a control policy that governs stimulation adaption. However, auxiliary parameters such as the window in which stimulation is allowed to adapt, as well as the rate it changes, can be just as impactful on performance and vary depending on the control policy and patient. A standardize protocol for programming aDBS will be crucial to ensuring its effective application in clinical practice.
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Affiliation(s)
- Kevin B. Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Jillian A. Melbourne
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Pranav Akella
- 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
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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16
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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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17
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Yu M, Sun P, Sun C, Jin WL. Bioelectronic medicine potentiates endogenous NSCs for neurodegenerative diseases. Trends Mol Med 2023; 29:886-896. [PMID: 37735022 DOI: 10.1016/j.molmed.2023.08.005] [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: 05/31/2023] [Revised: 08/14/2023] [Accepted: 08/16/2023] [Indexed: 09/23/2023]
Abstract
Neurodegenerative diseases (NDs) are commonly observed and while no therapy is universally applicable, cell-based therapies are promising. Stem cell transplantation has been investigated, but endogenous neural stem cells (eNSCs), despite their potential, especially with the development of bioelectronic medicine and biomaterials, remain understudied. Here, we compare stem cell transplantation therapy with eNSC-based therapy and summarize the combined use of eNSCs and developing technologies. The rapid development of implantable biomaterials has resulted in electronic stimulation becoming increasingly effective and decreasingly invasive. Thus, the combination of bioelectronic medicine and eNSCs has substantial potential for the treatment of NDs.
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Affiliation(s)
- Maifu Yu
- School of Life Science, Lanzhou University, Lanzhou 730000, China; Institute of Cancer Neuroscience, Medical Frontier Innovation Research Center, The First Hospital of Lanzhou University, The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China
| | - Pin Sun
- Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Changkai Sun
- Research & Educational Center for the Control Engineering of Translational Precision Medicine (R-ECCE-TPM), School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China.
| | - Wei-Lin Jin
- Institute of Cancer Neuroscience, Medical Frontier Innovation Research Center, The First Hospital of Lanzhou University, The First Clinical Medical College of Lanzhou University, Lanzhou 730000, China.
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Verma AK, Nandakumar B, Acedillo K, Yu Y, Marshall E, Schneck D, Fiecas M, Wang J, MacKinnon CD, Howell MJ, Vitek JL, Johnson LA. Excessive cortical beta oscillations are associated with slow-wave sleep dysfunction in mild parkinsonism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.28.564524. [PMID: 37961389 PMCID: PMC10634920 DOI: 10.1101/2023.10.28.564524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Increasing evidence associates slow-wave sleep (SWS) dysfunction with neurodegeneration. Using a within-subject design in the nonhuman primate model of Parkinson's disease (PD), we found that reduced SWS quantity in mild parkinsonism was accompanied by elevated beta and reduced delta power during SWS in the motor cortex. Our findings support excessive beta oscillations as a mechanism for SWS dysfunction and will inform development of neuromodulation therapies for enhancing SWS in PD.
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Affiliation(s)
- Ajay K. Verma
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | | | - Kit Acedillo
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Ying Yu
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Ethan Marshall
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - David Schneck
- Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - Mark Fiecas
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
| | - Jing Wang
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | | | - Michael J. Howell
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Jerrold L. Vitek
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
| | - Luke A. Johnson
- Department of Neurology, University of Minnesota, Minneapolis, MN, USA
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Palopoli-Trojani K, Schmidt SL, Baringer KD, Slotkin TA, Peters JJ, Turner DA, Grill WM. Temporally non-regular patterns of deep brain stimulation (DBS) enhance assessment of evoked potentials while maintaining motor symptom management in Parkinson's disease (PD). Brain Stimul 2023; 16:1630-1642. [PMID: 37863388 PMCID: PMC10872419 DOI: 10.1016/j.brs.2023.10.009] [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: 04/14/2023] [Revised: 09/25/2023] [Accepted: 10/11/2023] [Indexed: 10/22/2023] Open
Abstract
BACKGROUND Traditional deep brain stimulation (DBS) at fixed regular frequencies (>100 Hz) is effective in treating motor symptoms of Parkinson's disease (PD). Temporally non-regular patterns of DBS are a new parameter space that may help increase efficacy and efficiency. OBJECTIVE To compare the effects of temporally non-regular patterns of DBS to traditional regularly-spaced pulses. METHODS We simultaneously recorded local field potentials (LFP) and monitored motor symptoms (tremor and bradykinesia) in persons with PD during DBS in subthalamic nucleus (STN). We quantified both oscillatory activity and DBS local evoked potentials (DLEPs) from the LFP. RESULTS Temporally non-regular patterns were as effective as traditional pulse patterns in modulating motor symptoms, oscillatory activity, and DLEPs. Moreover, one of our novel patterns enabled recording of longer duration DLEPs during clinically effective stimulation. CONCLUSIONS Stimulation gaps of 50 ms can be used to increase efficiency and to enable regular assessment of long-duration DLEPs while maintaining effective symptom management. This may be a promising paradigm for closed-loop DBS with biomarker assessment during the gaps.
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Affiliation(s)
| | - Stephen L Schmidt
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Karley D Baringer
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Theodore A Slotkin
- Department of Pharmacology and Cancer Biology, Duke University Medical Center, USA
| | - Jennifer J Peters
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | - Dennis A Turner
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Neurobiology and Department of Neurosurgery, Duke University, Durham, NC, USA
| | - Warren M Grill
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Neurobiology and Department of Neurosurgery, Duke University, Durham, NC, USA; Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA.
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20
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Fleming JE, Senneff S, Lowery MM. Multivariable closed-loop control of deep brain stimulation for Parkinson's disease. J Neural Eng 2023; 20:056029. [PMID: 37733003 DOI: 10.1088/1741-2552/acfbfa] [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: 06/28/2022] [Accepted: 09/21/2023] [Indexed: 09/22/2023]
Abstract
Objective. Closed-loop deep brain stimulation (DBS) methods for Parkinson's disease (PD) to-date modulate either stimulation amplitude or frequency to control a single biomarker. While good performance has been demonstrated for symptoms that are correlated with the chosen biomarker, suboptimal regulation can occur for uncorrelated symptoms or when the relationship between biomarker and symptom varies. Control of stimulation-induced side-effects is typically not considered.Approach.A multivariable control architecture is presented to selectively target suppression of either tremor or subthalamic nucleus beta band oscillations. DBS pulse amplitude and duration are modulated to maintain amplitude below a threshold and avoid stimulation of distal large diameter axons associated with stimulation-induced side effects. A supervisor selects between a bank of controllers which modulate DBS pulse amplitude to control rest tremor or beta activity depending on the level of muscle electromyographic (EMG) activity detected. A secondary controller limits pulse amplitude and modulates pulse duration to target smaller diameter axons lying close to the electrode. The control architecture was investigated in a computational model of the PD motor network which simulated the cortico-basal ganglia network, motoneuron pool, EMG and muscle force signals.Main results.Good control of both rest tremor and beta activity was observed with reduced power delivered when compared with conventional open loop stimulation, The supervisor avoided over- or under-stimulation which occurred when using a single controller tuned to one biomarker. When DBS amplitude was constrained, the secondary controller maintained the efficacy of stimulation by increasing pulse duration to compensate for reduced amplitude. Dual parameter control delivered effective control of the target biomarkers, with additional savings in the power delivered.Significance.Non-linear multivariable control can enable targeted suppression of motor symptoms for PD patients. Moreover, dual parameter control facilitates automatic regulation of the stimulation therapeutic dosage to prevent overstimulation, whilst providing additional power savings.
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Affiliation(s)
- John E Fleming
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Mansfield Road, Oxford OX1 3TH, United Kingdom
| | - Sageanne Senneff
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
| | - Madeleine M Lowery
- Neuromuscular Systems Laboratory, UCD School of Electrical & Electronic Engineering, University College Dublin, Dublin, Ireland
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21
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Chhetri JK, Mei S, Wang C, Chan P. New horizons in Parkinson's disease in older populations. Age Ageing 2023; 52:afad186. [PMID: 37847793 DOI: 10.1093/ageing/afad186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 07/07/2023] [Indexed: 10/19/2023] Open
Abstract
Parkinson's disease (PD) is the second most common neurodegenerative disorder after Alzheimer's disease. Ageing is considered to be the greatest risk factor for PD, with a complex interplay between genetics and the environment. With population ageing, the prevalence of PD is expected to escalate worldwide; thus, it is of utmost importance to reduce the burden of PD. To date, there are no therapies to cure the disease, and current treatment strategies focus on the management of symptoms. Older adults often have multiple chronic diseases and geriatric syndromes, which further complicates the management of PD. Healthcare systems and care models necessary to address the broad needs of older PD patients are largely unavailable. In this New Horizon article, we discuss various aspects of PD from an ageing perspective, including disease management. We highlight recent advancements in PD therapies and discuss new care models with the potential to improve patient's quality of life.
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Affiliation(s)
- Jagadish K Chhetri
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Shanshan Mei
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Chaodong Wang
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Piu Chan
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- Key Laboratory for Neurodegenerative Disease of the Ministry of Education, Beijing Key Laboratory for Parkinson's Disease, Parkinson Disease Center of Beijing Institute for Brain Disorders, Beijing, China
- Clinical Center for Parkinson's Disease, Capital Medical University, Beijing, China
- Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing, China
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22
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Bi Y, Wang P, Yu J, Wang Z, Yang H, Deng Y, Guan J, Zhang W. Eltoprazine modulated gamma oscillations on ameliorating L-dopa-induced dyskinesia in rats. CNS Neurosci Ther 2023; 29:2998-3013. [PMID: 37122156 PMCID: PMC10493666 DOI: 10.1111/cns.14241] [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: 10/12/2022] [Revised: 03/30/2023] [Accepted: 04/17/2023] [Indexed: 05/02/2023] Open
Abstract
AIM Parkinson's disease (PD) is a pervasive neurodegenerative disease, and levodopa (L-dopa) is its preferred treatment. The pathophysiological mechanism of levodopa-induced dyskinesia (LID), the most common complication of long-term L-dopa administration, remains obscure. Accumulated evidence suggests that the dopaminergic as well as non-dopaminergic systems contribute to LID development. As a 5-hydroxytryptamine 1A/1B receptor agonist, eltoprazine ameliorates dyskinesia, although little is known about its electrophysiological mechanism. The aim of this study was to investigate the cumulative effects of chronic L-dopa administration and the potential mechanism of eltoprazine's amelioration of dyskinesia at the electrophysiological level in rats. METHODS Neural electrophysiological analysis techniques were conducted on the acquired local field potential (LFP) data from primary motor cortex (M1) and dorsolateral striatum (DLS) during different pathological states to obtain the information of power spectrum density, theta-gamma phase-amplitude coupling (PAC), and functional connectivity. Behavior tests and AIMs scoring were performed to verify PD model establishment and evaluate LID severity. RESULTS We detected exaggerated gamma activities in the dyskinetic state, with different features and impacts in distinct regions. Gamma oscillations in M1 were narrowband manner, whereas that in DLS had a broadband appearance. Striatal exaggerated theta-gamma PAC in the LID state contributed to broadband gamma oscillation, and aperiodic-corrected cortical beta power correlated robustly with aperiodic-corrected gamma power in M1. M1-DLS coherence and phase-locking values (PLVs) in the gamma band were enhanced following L-dopa administration. Eltoprazine intervention reduced gamma oscillations, theta-gamma PAC in the DLS, and coherence and PLVs in the gamma band to alleviate dyskinesia. CONCLUSION Excessive cortical gamma oscillation is a compelling clinical indicator of dyskinesia. The detection of enhanced PAC and functional connectivity of gamma-band oscillation can be used to guide and optimize deep brain stimulation parameters. Eltoprazine has potential clinical application for dyskinesia.
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Affiliation(s)
- Yuewei Bi
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Pengfei Wang
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Jianshen Yu
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Zhuyong Wang
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Hanjie Yang
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Yuhao Deng
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Jianwei Guan
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
| | - Wangming Zhang
- Neurosurgery Center, Department of Pediatric Neurosurgery, Guangdong Provincial Key Laboratory on Brain Function Repair and Regeneration, Zhujiang HospitalSouthern Medical UniversityGuangzhouChina
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23
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Venkatesh P, Wolfe C, Lega B. Neuromodulation of the anterior thalamus: Current approaches and opportunities for the future. CURRENT RESEARCH IN NEUROBIOLOGY 2023; 5:100109. [PMID: 38020810 PMCID: PMC10663132 DOI: 10.1016/j.crneur.2023.100109] [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: 05/14/2023] [Revised: 08/28/2023] [Accepted: 08/31/2023] [Indexed: 12/01/2023] Open
Abstract
The role of thalamocortical circuits in memory has driven a recent burst of scholarship, especially in animal models. Investigating this circuitry in humans is more challenging. And yet, the development of new recording and stimulation technologies deployed for clinical indications has created novel opportunities for data collection to elucidate the cognitive roles of thalamic structures. These technologies include stereoelectroencephalography (SEEG), deep brain stimulation (DBS), and responsive neurostimulation (RNS), all of which have been applied to memory-related thalamic regions, specifically for seizure localization and treatment. This review seeks to summarize the existing applications of neuromodulation of the anterior thalamic nuclei (ANT) and highlight several devices and their capabilities that can allow cognitive researchers to design experiments to assay its functionality. Our goal is to introduce to investigators, who may not be familiar with these clinical devices, the capabilities, and limitations of these tools for understanding the neurophysiology of the ANT as it pertains to memory and other behaviors. We also briefly cover the targeting of other thalamic regions including the centromedian (CM) nucleus, dorsomedial (DM) nucleus, and pulvinar, with associated potential avenues of experimentation.
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Affiliation(s)
- Pooja Venkatesh
- Department of Neurosurgery, University of Texas Southwestern, Dallas, TX, 75390, USA
| | - Cody Wolfe
- Department of Neurosurgery, University of Texas Southwestern, Dallas, TX, 75390, USA
| | - Bradley Lega
- Department of Neurosurgery, University of Texas Southwestern, Dallas, TX, 75390, USA
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24
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Binder T, Lange F, Pozzi N, Musacchio T, Daniels C, Odorfer T, Fricke P, Matthies C, Volkmann J, Capetian P. Feasibility of local field potential-guided programming for deep brain stimulation in Parkinson's disease: A comparison with clinical and neuro-imaging guided approaches in a randomized, controlled pilot trial. Brain Stimul 2023; 16:1243-1251. [PMID: 37619891 DOI: 10.1016/j.brs.2023.08.017] [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: 02/04/2023] [Revised: 08/17/2023] [Accepted: 08/18/2023] [Indexed: 08/26/2023] Open
Abstract
BACKGROUND Subthalamic nucleus deep brain stimulation (STN-DBS) is an effective treatment for advanced Parkinson's disease (PD). Clinical outcomes after DBS can be limited by poor programming, which remains a clinically driven, lengthy and iterative process. Electrophysiological recordings in PD patients undergoing STN-DBS have shown an association between STN spectral power in the beta frequency band (beta power) and the severity of clinical symptoms. New commercially-available DBS devices now enable the recording of STN beta oscillations in chronically-implanted PD patients, thereby allowing investigation into the use of beta power as a biomarker for DBS programming. OBJECTIVE To determine the potential advantages of beta-guided DBS programming over clinically and image-guided programming in terms of clinical efficacy and programming time. METHODS We conducted a randomized, blinded, three-arm, crossover clinical trial in eight Parkinson's patients with STN-DBS who were evaluated three months after DBS surgery. We compared clinical efficacy and time required for each DBS programming paradigm, as well as DBS parameters and total energy delivered between the three strategies (beta-, clinically- and image-guided). RESULTS All three programming methods showed similar clinical efficacy, but the time needed for programming was significantly shorter for beta- and image-guided programming compared to clinically-guided programming (p < 0.001). CONCLUSION Beta-guided programming may be a useful and more efficient approach to DBS programming in Parkinson's patients with STN-DBS. It takes significantly less time to program than traditional clinically-based programming, while providing similar symptom control. In addition, it is readily available within the clinical DBS programmer, making it a valuable tool for improving current clinical practice.
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Affiliation(s)
- Tobias Binder
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Florian Lange
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany.
| | - Nicolò Pozzi
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Thomas Musacchio
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Christine Daniels
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Thorsten Odorfer
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Patrick Fricke
- Department of Neurosurgery, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Cordula Matthies
- Department of Neurosurgery, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Philipp Capetian
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
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25
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Sermon JJ, Olaru M, Ansó J, Cernera S, Little S, Shcherbakova M, Bogacz R, Starr PA, Denison T, Duchet B. Sub-harmonic entrainment of cortical gamma oscillations to deep brain stimulation in Parkinson's disease: Model based predictions and validation in three human subjects. Brain Stimul 2023; 16:1412-1424. [PMID: 37683763 PMCID: PMC10635843 DOI: 10.1016/j.brs.2023.08.026] [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: 05/04/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/10/2023] Open
Abstract
OBJECTIVES The exact mechanisms of deep brain stimulation (DBS) are still an active area of investigation, in spite of its clinical successes. This is due in part to the lack of understanding of the effects of stimulation on neuronal rhythms. Entrainment of brain oscillations has been hypothesised as a potential mechanism of neuromodulation. A better understanding of entrainment might further inform existing methods of continuous DBS, and help refine algorithms for adaptive methods. The purpose of this study is to develop and test a theoretical framework to predict entrainment of cortical rhythms to DBS across a wide range of stimulation parameters. MATERIALS AND METHODS We fit a model of interacting neural populations to selected features characterising PD patients' off-stimulation finely-tuned gamma rhythm recorded through electrocorticography. Using the fitted models, we predict basal ganglia DBS parameters that would result in 1:2 entrainment, a special case of sub-harmonic entrainment observed in patients and predicted by theory. RESULTS We show that the neural circuit models fitted to patient data exhibit 1:2 entrainment when stimulation is provided across a range of stimulation parameters. Furthermore, we verify key features of the region of 1:2 entrainment in the stimulation frequency/amplitude space with follow-up recordings from the same patients, such as the loss of 1:2 entrainment above certain stimulation amplitudes. CONCLUSION Our results reveal that continuous, constant frequency DBS in patients may lead to nonlinear patterns of neuronal entrainment across stimulation parameters, and that these responses can be predicted by modelling. Should entrainment prove to be an important mechanism of therapeutic stimulation, our modelling framework may reduce the parameter space that clinicians must consider when programming devices for optimal benefit.
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Affiliation(s)
- James J Sermon
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK; MRC Brain Networks Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Maria Olaru
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Juan Ansó
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Stephanie Cernera
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Simon Little
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Maria Shcherbakova
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Rafal Bogacz
- MRC Brain Networks Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Philip A Starr
- Department of Neurological Surgery, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Timothy Denison
- Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK; MRC Brain Networks Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Benoit Duchet
- MRC Brain Networks Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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26
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Gerasimova SA, Beltyukova A, Fedulina A, Matveeva M, Lebedeva AV, Pisarchik AN. Living-Neuron-Based Autogenerator. SENSORS (BASEL, SWITZERLAND) 2023; 23:7016. [PMID: 37631552 PMCID: PMC10458024 DOI: 10.3390/s23167016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2023] [Revised: 08/01/2023] [Accepted: 08/05/2023] [Indexed: 08/27/2023]
Abstract
We present a novel closed-loop system designed to integrate biological and artificial neurons of the oscillatory type into a unified circuit. The system comprises an electronic circuit based on the FitzHugh-Nagumo model, which provides stimulation to living neurons in acute hippocampal mouse brain slices. The local field potentials generated by the living neurons trigger a transition in the FitzHugh-Nagumo circuit from an excitable state to an oscillatory mode, and in turn, the spikes produced by the electronic circuit synchronize with the living-neuron spikes. The key advantage of this hybrid electrobiological autogenerator lies in its capability to control biological neuron signals, which holds significant promise for diverse neuromorphic applications.
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Affiliation(s)
- Svetlana A. Gerasimova
- Department of Control Theory and System Dynamics, Neurotechnology Department, National Research Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
| | - Anna Beltyukova
- Department of Control Theory and System Dynamics, Neurotechnology Department, National Research Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
| | - Anastasia Fedulina
- Department of Control Theory and System Dynamics, Neurotechnology Department, National Research Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
| | - Maria Matveeva
- Department of Control Theory and System Dynamics, Neurotechnology Department, National Research Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
| | - Albina V. Lebedeva
- Department of Control Theory and System Dynamics, Neurotechnology Department, National Research Lobachevsky State University of Nizhny Novgorod, 603022 Nizhny Novgorod, Russia
| | - Alexander N. Pisarchik
- Center for Biomedical Technology, Universidad Politécnica de Madrid, Pozuelo de Alarcón, 28223 Madrid, Spain
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Oehrn CR, Cernera S, Hammer LH, Shcherbakova M, Yao J, Hahn A, Wang S, Ostrem JL, Little S, Starr PA. Personalized chronic adaptive deep brain stimulation outperforms conventional stimulation in Parkinson's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.03.23293450. [PMID: 37649907 PMCID: PMC10463549 DOI: 10.1101/2023.08.03.23293450] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
Abstract
Deep brain stimulation is a widely used therapy for Parkinson's disease (PD) but currently lacks dynamic responsiveness to changing clinical and neural states. Feedback control has the potential to improve therapeutic effectiveness, but optimal control strategy and additional benefits of "adaptive" neurostimulation are unclear. We implemented adaptive subthalamic nucleus stimulation, controlled by subthalamic or cortical signals, in three PD patients (five hemispheres) during normal daily life. We identified neurophysiological biomarkers of residual motor fluctuations using data-driven analyses of field potentials over a wide frequency range and varying stimulation amplitudes. Narrowband gamma oscillations (65-70 Hz) at either site emerged as the best control signal for sensing during stimulation. A blinded, randomized trial demonstrated improved motor symptoms and quality of life compared to clinically optimized standard stimulation. Our approach highlights the promise of personalized adaptive neurostimulation based on data-driven selection of control signals and may be applied to other neurological disorders.
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Affiliation(s)
- Carina R Oehrn
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Stephanie Cernera
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Lauren H Hammer
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
| | - Maria Shcherbakova
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Jiaang Yao
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
| | - Amelia Hahn
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Sarah Wang
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Jill L Ostrem
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Simon Little
- Department of Neurology, University of California, San Francisco, San Francisco, California, USA
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Philip A Starr
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- University of California, Berkeley - University of California, San Francisco Graduate Program in Bioengineering, Berkeley, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
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Alva L, Bernasconi E, Torrecillos F, Fischer P, Averna A, Bange M, Mostofi A, Pogosyan A, Ashkan K, Muthuraman M, Groppa S, Pereira EA, Tan H, Tinkhauser G. Clinical neurophysiological interrogation of motor slowing: A critical step towards tuning adaptive deep brain stimulation. Clin Neurophysiol 2023; 152:43-56. [PMID: 37285747 PMCID: PMC7615935 DOI: 10.1016/j.clinph.2023.04.013] [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: 08/23/2022] [Revised: 03/07/2023] [Accepted: 04/18/2023] [Indexed: 06/09/2023]
Abstract
OBJECTIVE Subthalamic nucleus (STN) beta activity (13-30 Hz) is the most accepted biomarker for adaptive deep brain stimulation (aDBS) for Parkinson's disease (PD). We hypothesize that different frequencies within the beta range may exhibit distinct temporal dynamics and, as a consequence, different relationships to motor slowing and adaptive stimulation patterns. We aim to highlight the need for an objective method to determine the aDBS feedback signal. METHODS STN LFPs were recorded in 15 PD patients at rest and while performing a cued motor task. The impact of beta bursts on motor performance was assessed for different beta candidate frequencies: the individual frequency strongest associated with motor slowing, the individual beta peak frequency, the frequency most modulated by movement execution, as well as the entire-, low- and high beta band. How these candidate frequencies differed in their bursting dynamics and theoretical aDBS stimulation patterns was further investigated. RESULTS The individual motor slowing frequency often differs from the individual beta peak or beta-related movement-modulation frequency. Minimal deviations from a selected target frequency as feedback signal for aDBS leads to a substantial drop in the burst overlapping and in the alignment of the theoretical onset of stimulation triggers (to ∼ 75% for 1 Hz, to ∼ 40% for 3 Hz deviation). CONCLUSIONS Clinical-temporal dynamics within the beta frequency range are highly diverse and deviating from a reference biomarker frequency can result in altered adaptive stimulation patterns. SIGNIFICANCE A clinical-neurophysiological interrogation could be helpful to determine the patient-specific feedback signal for aDBS.
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Affiliation(s)
- Laura Alva
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Elena Bernasconi
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Flavie Torrecillos
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Petra Fischer
- School of Physiology, Pharmacology & Neuroscience, University of Bristol, University Walk, BS8 1TD Bristol, United Kingdom
| | - Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Manuel Bange
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Abteen Mostofi
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, London SW17 0RE, United Kingdom
| | - Alek Pogosyan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Keyoumars Ashkan
- Department of Neurosurgery, King's College Hospital, King's College London, SE59RS, United Kingdom
| | - Muthuraman Muthuraman
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Sergiu Groppa
- Movement Disorders and Neurostimulation, Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, 55131 Mainz, Germany
| | - Erlick A Pereira
- Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's, University of London, London SW17 0RE, United Kingdom
| | - Huiling Tan
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland.
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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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30
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Bronte-Stewart H, Merola A. Hope vs. Hype: Closed loop technology will provide more meaningful improvement vs. directional leads in deep brain stimulation. Parkinsonism Relat Disord 2023:105452. [PMID: 37355400 DOI: 10.1016/j.parkreldis.2023.105452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 05/20/2023] [Indexed: 06/26/2023]
Affiliation(s)
- Helen Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford Comprehensive Movement Disorders Center, United States.
| | - Aristide Merola
- Center for Parkinson's Disease and Related Movement Disorders, Wexner Medical Center, The Ohio State University, Columbus, United States.
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31
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Franklin ME, Bennett C, Arboite M, Alvarez-Ciara A, Corrales N, Verdelus J, Dietrich WD, Keane RW, de Rivero Vaccari JP, Prasad A. Activation of inflammasomes and their effects on neuroinflammation at the microelectrode-tissue interface in intracortical implants. Biomaterials 2023; 297:122102. [PMID: 37015177 PMCID: PMC10614166 DOI: 10.1016/j.biomaterials.2023.122102] [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: 10/11/2022] [Revised: 03/16/2023] [Accepted: 03/23/2023] [Indexed: 03/30/2023]
Abstract
Invasive neuroprosthetics rely on microelectrodes (MEs) to record or stimulate the activity of large neuron assemblies. However, MEs are subjected to tissue reactivity in the central nervous system (CNS) due to the foreign body response (FBR) that contribute to chronic neuroinflammation and ultimately result in ME failure. An endogenous, acute set of mechanisms responsible for the recognition and targeting of foreign objects, called the innate immune response, immediately follows the ME implant-induced trauma. Inflammasomes are multiprotein structures that play a critical role in the initiation of an innate immune response following CNS injuries. The activation of inflammasomes facilitates a range of innate immune response cascades and results in neuroinflammation and programmed cell death. Despite our current understanding of inflammasomes, their roles in the context of neural device implantation remain unknown. In this study, we implanted a non-functional Utah electrode array (UEA) into the rat somatosensory cortex and studied the inflammasome signaling and the corresponding downstream effects on inflammatory cytokine expression and the inflammasome-mediated cell death mechanism of pyroptosis. Our results not only demonstrate the continuous activation of inflammasomes and their contribution to neuroinflammation at the electrode-tissue interface but also reveal the therapeutic potential of targeting inflammasomes to attenuate the FBR in invasive neuroprosthetics.
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Affiliation(s)
- Melissa E Franklin
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA
| | - Cassie Bennett
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA
| | - Maelle Arboite
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA
| | | | - Natalie Corrales
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA
| | - Jennifer Verdelus
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA
| | - W Dalton Dietrich
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA; Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL, USA; The Miami Project to Cure Paralysis, University of Miami, Miami, FL, USA
| | - Robert W Keane
- The Miami Project to Cure Paralysis, University of Miami, Miami, FL, USA; Department of Physiology and Biophysics, University of Miami Miller School of Medicine, Miami, FL, USA; Center for Cognitive Neuroscience and Aging University of Miami Miller School of Medicine, Miami, FL, USA
| | - Juan Pablo de Rivero Vaccari
- The Miami Project to Cure Paralysis, University of Miami, Miami, FL, USA; Department of Physiology and Biophysics, University of Miami Miller School of Medicine, Miami, FL, USA; Center for Cognitive Neuroscience and Aging University of Miami Miller School of Medicine, Miami, FL, USA
| | - Abhishek Prasad
- Department of Biomedical Engineering, University of Miami, Miami, FL, USA; The Miami Project to Cure Paralysis, University of Miami, Miami, FL, USA.
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32
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Radcliffe EM, Baumgartner AJ, Kern DS, Al Borno M, Ojemann S, Kramer DR, Thompson JA. Oscillatory beta dynamics inform biomarker-driven treatment optimization for Parkinson's disease. J Neurophysiol 2023; 129:1492-1504. [PMID: 37198135 DOI: 10.1152/jn.00055.2023] [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: 02/03/2023] [Revised: 04/23/2023] [Accepted: 05/17/2023] [Indexed: 05/19/2023] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons and dysregulation of the basal ganglia. Cardinal motor symptoms include bradykinesia, rigidity, and tremor. Deep brain stimulation (DBS) of select subcortical nuclei is standard of care for medication-refractory PD. Conventional open-loop DBS delivers continuous stimulation with fixed parameters that do not account for a patient's dynamic activity state or medication cycle. In comparison, closed-loop DBS, or adaptive DBS (aDBS), adjusts stimulation based on biomarker feedback that correlates with clinical state. Recent work has identified several neurophysiological biomarkers in local field potential recordings from PD patients, the most promising of which are 1) elevated beta (∼13-30 Hz) power in the subthalamic nucleus (STN), 2) increased beta synchrony throughout basal ganglia-thalamocortical circuits, notably observed as coupling between the STN beta phase and cortical broadband gamma (∼50-200 Hz) amplitude, and 3) prolonged beta bursts in the STN and cortex. In this review, we highlight relevant frequency and time domain features of STN beta measured in PD patients and summarize how spectral beta power, oscillatory beta synchrony, phase-amplitude coupling, and temporal beta bursting inform PD pathology, neurosurgical targeting, and DBS therapy. We then review how STN beta dynamics inform predictive, biomarker-driven aDBS approaches for optimizing PD treatment. We therefore provide clinically useful and actionable insight that can be applied toward aDBS implementation for PD.
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Affiliation(s)
- Erin M Radcliffe
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Alexander J Baumgartner
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Drew S Kern
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Mazen Al Borno
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Computer Science and Engineering, University of Colorado Denver, Denver, Colorado, United States
| | - Steven Ojemann
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - Daniel R Kramer
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
| | - John A Thompson
- Department of Neurosurgery, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Bioengineering, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- Department of Neurology, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
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33
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Neumann WJ, Gilron R, Little S, Tinkhauser G. Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation. Mov Disord 2023. [PMID: 37148553 DOI: 10.1002/mds.29415] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Revised: 03/27/2023] [Accepted: 04/05/2023] [Indexed: 05/08/2023] Open
Abstract
Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patient-specific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | | | - Simon Little
- Movement Disorders and Neuromodulation Centre, University of California San Francisco, San Francisco, California, USA
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
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Wang S, Zhu G, Shi L, Zhang C, Wu B, Yang A, Meng F, Jiang Y, Zhang J. Closed-Loop Adaptive Deep Brain Stimulation in Parkinson's Disease: Procedures to Achieve It and Future Perspectives. JOURNAL OF PARKINSON'S DISEASE 2023:JPD225053. [PMID: 37182899 DOI: 10.3233/jpd-225053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Parkinson's disease (PD) is a neurodegenerative disease with a heavy burden on patients, families, and society. Deep brain stimulation (DBS) can improve the symptoms of PD patients for whom medication is insufficient. However, current open-loop uninterrupted conventional DBS (cDBS) has inherent limitations, such as adverse effects, rapid battery consumption, and a need for frequent parameter adjustment. To overcome these shortcomings, adaptive DBS (aDBS) was proposed to provide responsive optimized stimulation for PD. This topic has attracted scientific interest, and a growing body of preclinical and clinical evidence has shown its benefits. However, both achievements and challenges have emerged in this novel field. To date, only limited reviews comprehensively analyzed the full framework and procedures for aDBS implementation. Herein, we review current preclinical and clinical data on aDBS for PD to discuss the full procedures for its achievement and to provide future perspectives on this treatment.
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Affiliation(s)
- Shu Wang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Shi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunkui Zhang
- Center of Cognition and Brain Science, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Bing Wu
- Center of Cognition and Brain Science, Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
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35
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Averna A, Debove I, Nowacki A, Peterman K, Duchet B, Sousa M, Bernasconi E, Alva L, Lachenmayer ML, Schuepbach M, Pollo C, Krack P, Nguyen TAK, Tinkhauser G. Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation. Mov Disord 2023; 38:818-830. [PMID: 36987385 PMCID: PMC7615852 DOI: 10.1002/mds.29381] [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: 11/01/2022] [Revised: 01/13/2023] [Accepted: 02/27/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN). OBJECTIVES The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS. METHODS STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS. RESULTS The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS. CONCLUSIONS The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Ines Debove
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Andreas Nowacki
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Katrin Peterman
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Mário Sousa
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Elena Bernasconi
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Laura Alva
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Martin L. Lachenmayer
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | | | - Claudio Pollo
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Paul Krack
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Thuy-Anh K. Nguyen
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
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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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Neumann WJ, Horn A, Kühn AA. Insights and opportunities for deep brain stimulation as a brain circuit intervention. Trends Neurosci 2023; 46:472-487. [PMID: 37105806 DOI: 10.1016/j.tins.2023.03.009] [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: 08/31/2022] [Revised: 03/13/2023] [Accepted: 03/17/2023] [Indexed: 04/29/2023]
Abstract
Deep brain stimulation (DBS) is an effective treatment and has provided unique insights into the dynamic circuit architecture of brain disorders. This Review illustrates our current understanding of the pathophysiology of movement disorders and their underlying brain circuits that are modulated with DBS. It proposes principles of pathological network synchronization patterns like beta activity (13-35 Hz) in Parkinson's disease. We describe alterations from microscale including local synaptic activity via modulation of mesoscale hypersynchronization to changes in whole-brain macroscale connectivity. Finally, an outlook on advances for clinical innovations in next-generation neurotechnology is provided: from preoperative connectomic targeting to feedback controlled closed-loop adaptive DBS as individualized network-specific brain circuit interventions.
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Affiliation(s)
- Wolf-Julian Neumann
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Berlin, Germany
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Berlin, Germany; Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA; MGH Neurosurgery & Center for Neurotechnology and Neurorecovery at MGH Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Andrea A Kühn
- Movement Disorders and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Bernstein Center for Computational Neuroscience, Humboldt Universität zu Berlin, Berlin, Germany; NeuroCure Clinical Research Centre, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany; Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany; DZNE, German Center for Degenerative Diseases, Berlin, Germany.
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38
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Bonizzato M, Guay Hottin R, Côté SL, Massai E, Choinière L, Macar U, Laferrière S, Sirpal P, Quessy S, Lajoie G, Martinez M, Dancause N. Autonomous optimization of neuroprosthetic stimulation parameters that drive the motor cortex and spinal cord outputs in rats and monkeys. Cell Rep Med 2023; 4:101008. [PMID: 37044093 PMCID: PMC10140617 DOI: 10.1016/j.xcrm.2023.101008] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 02/16/2023] [Accepted: 03/20/2023] [Indexed: 04/14/2023]
Abstract
Neural stimulation can alleviate paralysis and sensory deficits. Novel high-density neural interfaces can enable refined and multipronged neurostimulation interventions. To achieve this, it is essential to develop algorithmic frameworks capable of handling optimization in large parameter spaces. Here, we leveraged an algorithmic class, Gaussian-process (GP)-based Bayesian optimization (BO), to solve this problem. We show that GP-BO efficiently explores the neurostimulation space, outperforming other search strategies after testing only a fraction of the possible combinations. Through a series of real-time multi-dimensional neurostimulation experiments, we demonstrate optimization across diverse biological targets (brain, spinal cord), animal models (rats, non-human primates), in healthy subjects, and in neuroprosthetic intervention after injury, for both immediate and continual learning over multiple sessions. GP-BO can embed and improve "prior" expert/clinical knowledge to dramatically enhance its performance. These results advocate for broader establishment of learning agents as structural elements of neuroprosthetic design, enabling personalization and maximization of therapeutic effectiveness.
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Affiliation(s)
- Marco Bonizzato
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada; Department of Electrical Engineering and Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC H3T 1J4, Canada; CIUSSS du Nord-de-l'Île-de-Montréal, Montreal, QC H4J 1C5, Canada; Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada.
| | - Rose Guay Hottin
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada; Department of Electrical Engineering and Institute of Biomedical Engineering, Polytechnique Montréal, Montreal, QC H3T 1J4, Canada; Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada
| | - Sandrine L Côté
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Elena Massai
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Léo Choinière
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada; Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada
| | - Uzay Macar
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada; Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada
| | - Samuel Laferrière
- Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada; Computer Science Department, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Parikshat Sirpal
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada; Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada
| | - Stephan Quessy
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Guillaume Lajoie
- Mila - Québec AI Institute, Montreal, QC H2S 3H1, Canada; Mathematics and Statistics Department, Université de Montréal, Montreal, QC H3T 1J4, Canada
| | - Marina Martinez
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada; CIUSSS du Nord-de-l'Île-de-Montréal, Montreal, QC H4J 1C5, Canada
| | - Numa Dancause
- Department of Neurosciences and Centre interdisciplinaire de recherche sur le cerveau et l'apprentissage (CIRCA), Université de Montréal, Montreal, QC H3T 1J4, Canada.
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Cho H, Ojemann J, Herron J. Open Mind Neuromodulation Interface for the CorTec Brain Interchange (OMNI-BIC): an investigational distributed research platform for next-generation clinical neuromodulation research. INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING : [PROCEEDINGS]. INTERNATIONAL IEEE EMBS CONFERENCE ON NEURAL ENGINEERING 2023; 2023:10.1109/ner52421.2023.10123808. [PMID: 38807974 PMCID: PMC11131587 DOI: 10.1109/ner52421.2023.10123808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2024]
Abstract
The rise of adaptive stimulation approaches has shown great therapeutic promise in the growing field of neuromodulation. The discovery and growth of these novel adaptive stimulation paradigms has been largely concentrated around several implantable devices with research application programming interfaces (APIs) that allow for custom applications to be created for clinical neuromodulation studies. However, the sunsetting of devices and ongoing development of new platforms is leading to an increased fragmentation in the research environment- resulting in the reinvention of system features and the inability to leverage previous development efforts for future studies. The Open Mind Neuromodulation Interface (OMNI) is a previously proposed solution to address the weaknesses of the DLL-driven API approach of past neuromodulation research by utilizing an alternative gRPC-enabled microservice framework. Here, we introduce OMNI-BIC, an implementation of the OMNI framework to the CorTec Brain Interchange system. This paper describes the design and implementation of the OMNI-BIC software tools and demonstrates the framework's capabilities for implementing customized neuromodulation therapies for clinical investigations. Through the development and deployment of the OMNI-BIC system, we hope to improve future clinical studies with the Brain Interchange system and aid in continuing the growth and momentum of the exciting field of adaptive neuromodulation.
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Affiliation(s)
- Hanbin Cho
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA USA
| | - Jeffrey Ojemann
- Department of Neurological Surgery, University of Washington, Seattle, WA USA
| | - Jeffrey Herron
- Department of Neurological Surgery, University of Washington, Seattle, WA USA
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Duchet B, Sermon JJ, Weerasinghe G, Denison T, Bogacz R. How to entrain a selected neuronal rhythm but not others: open-loop dithered brain stimulation for selective entrainment. J Neural Eng 2023; 20:10.1088/1741-2552/acbc4a. [PMID: 36880684 PMCID: PMC7614323 DOI: 10.1088/1741-2552/acbc4a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Accepted: 02/15/2023] [Indexed: 03/08/2023]
Abstract
Objective.While brain stimulation therapies such as deep brain stimulation for Parkinson's disease (PD) can be effective, they have yet to reach their full potential across neurological disorders. Entraining neuronal rhythms using rhythmic brain stimulation has been suggested as a new therapeutic mechanism to restore neurotypical behaviour in conditions such as chronic pain, depression, and Alzheimer's disease. However, theoretical and experimental evidence indicate that brain stimulation can also entrain neuronal rhythms at sub- and super-harmonics, far from the stimulation frequency. Crucially, these counterintuitive effects could be harmful to patients, for example by triggering debilitating involuntary movements in PD. We therefore seek a principled approach to selectively promote rhythms close to the stimulation frequency, while avoiding potential harmful effects by preventing entrainment at sub- and super-harmonics.Approach.Our open-loop approach to selective entrainment, dithered stimulation, consists in adding white noise to the stimulation period.Main results.We theoretically establish the ability of dithered stimulation to selectively entrain a given brain rhythm, and verify its efficacy in simulations of uncoupled neural oscillators, and networks of coupled neural oscillators. Furthermore, we show that dithered stimulation can be implemented in neurostimulators with limited capabilities by toggling within a finite set of stimulation frequencies.Significance.Likely implementable across a variety of existing brain stimulation devices, dithering-based selective entrainment has potential to enable new brain stimulation therapies, as well as new neuroscientific research exploiting its ability to modulate higher-order entrainment.
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Affiliation(s)
- Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.,MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - James J Sermon
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.,MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.,Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford,Oxford, United Kingdom
| | - Gihan Weerasinghe
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.,MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Timothy Denison
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.,MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom.,Institute of Biomedical Engineering, Department of Engineering Sciences, University of Oxford,Oxford, United Kingdom
| | - Rafal Bogacz
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom.,MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
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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: 9] [Impact Index Per Article: 9.0] [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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An Q, Yin Z, Ma R, Fan H, Xu Y, Gan Y, Gao Y, Meng F, Yang A, Jiang Y, Zhu G, Zhang J. Adaptive deep brain stimulation for Parkinson's disease: looking back at the past decade on motor outcomes. J Neurol 2023; 270:1371-1387. [PMID: 36471098 DOI: 10.1007/s00415-022-11495-z] [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: 07/30/2022] [Revised: 11/15/2022] [Accepted: 11/17/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Adaptive deep brain stimulation (aDBS) has been reported to be an effective treatment for motor symptoms in patients with Parkinson's disease (PD). However, it remains unclear whether and in which motor domain aDBS provides greater/less benefits than conventional DBS (cDBS). OBJECTIVE To conduct a meta-analysis and systematic review to explore the improvement of the motor symptoms of PD patients undergoing aDBS and the comparison between aDBS and cDBS. METHODS Nineteen studies from PubMed, Embase, and the Cochrane Library database were eligible for the main analysis. Twelve studies used quantitative plus qualitative analysis; seven studies were only qualitatively analyzed. The efficacy of aDBS was evaluated and compared to cDBS through overall motor function improvements, changes in symptoms of rigidity-bradykinesia, dyskinesia, tremor, and speech function, and total electrical energy delivered (TEED). The overall motor improvement and TEED were investigated through meta-analyses, while other variables were investigated by systematic review. RESULTS Quantitative analysis showed that aDBS, with a reduction of TEED (55% of that of cDBS), significantly improved motor functions (33.9%, p < 0.01) and may be superior to cDBS in overall motor improvement (p = 0.002). However, significant publication bias was detected regarding the superiority (p = 0.006, Egger's test). In the qualitative analysis, rigidity-bradykinesia, dyskinesia, and speech function outcomes after aDBS and cDBS were comparable. Beta-based aDBS may not be as efficient as cDBS for tremor control. CONCLUSIONS aDBS can effectively relieve the clinical symptoms of advanced PD as did cDBS, at least in acute trials, delivering less stimulation than cDBS. Specific symptoms including tremor and axial disability remain to be compared between aDBS and cDBS in long-term studies.
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Affiliation(s)
- Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Houyou Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Yifei Gan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Yuan Gao
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Fangang Meng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China.
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China. .,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, No. 119 South 4th Ring West Road, Fengtai District, 100070, Beijing, China. .,Beijing Key Laboratory of Neurostimulation, Beijing, China.
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Kleinholdermann U, Bacara B, Timmermann L, Pedrosa DJ. Prediction of Movement Ratings and Deep Brain Stimulation Parameters in Idiopathic Parkinson's Disease. Neuromodulation 2023; 26:356-363. [PMID: 36396526 DOI: 10.1016/j.neurom.2022.09.010] [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: 06/06/2022] [Revised: 08/24/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Deep brain stimulation (DBS) parameter fine-tuning after lead implantation is laborious work because of the almost uncountable possible combinations. Patients and practitioners often gain the perception that assistive devices could be beneficial for adjusting settings effectively. OBJECTIVE We aimed at a proof-of-principle study to assess the benefits of noninvasive movement recordings as a means to predict best DBS settings. MATERIALS AND METHODS For this study, 32 patients with idiopathic Parkinson's disease, under chronic subthalamic nucleus stimulation with directional leads, were recorded. During monopolar review, each available contact was activated with currents between 0.5 and 5 mA, and diadochokinesia, rigidity, and tapping ability were rated clinically. Moreover, participants' movements were measured during four simple hand movement tasks while wearing a commercially available armband carrying an inertial measurement unit (IMU). We trained random forest models to learn the relations between clinical ratings, electrode settings, and movement features obtained from the IMU. RESULTS Firstly, we could show that clinical mobility ratings can be predicted from IMU features with correlations of up to r = 0.68 between true and predicted values. Secondly, these features also enabled a prediction of DBS parameters, which showed correlations of up to approximately r = 0.8 with clinically optimal DBS settings and were associated with congruent volumes of tissue activated. CONCLUSION Movement recordings from customer-grade mobile IMU carrying devices are promising candidates, not only for remote symptom assessment but also for closed-loop DBS parameter adjustment, and could thus extend the list of available aids for effective programming beyond imaging techniques.
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Affiliation(s)
- Urs Kleinholdermann
- Department of Neurology, University Hospital of Marburg and Gießen, Baldingerstraße, Marburg, Germany
| | - Bugrahan Bacara
- Department of Neurology, University Hospital of Marburg and Gießen, Baldingerstraße, Marburg, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital of Marburg and Gießen, Baldingerstraße, Marburg, Germany; Center of Mind, Brain and Behaviour, Philipps University Marburg, Hans-Meerwein-Straße, Marburg, Germany
| | - David J Pedrosa
- Department of Neurology, University Hospital of Marburg and Gießen, Baldingerstraße, Marburg, Germany; Center of Mind, Brain and Behaviour, Philipps University Marburg, Hans-Meerwein-Straße, Marburg, Germany.
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A systematic review of local field potential physiomarkers in Parkinson's disease: from clinical correlations to adaptive deep brain stimulation algorithms. J Neurol 2023; 270:1162-1177. [PMID: 36209243 PMCID: PMC9886603 DOI: 10.1007/s00415-022-11388-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 09/16/2022] [Indexed: 02/03/2023]
Abstract
Deep brain stimulation (DBS) treatment has proven effective in suppressing symptoms of rigidity, bradykinesia, and tremor in Parkinson's disease. Still, patients may suffer from disabling fluctuations in motor and non-motor symptom severity during the day. Conventional DBS treatment consists of continuous stimulation but can potentially be further optimised by adapting stimulation settings to the presence or absence of symptoms through closed-loop control. This critically relies on the use of 'physiomarkers' extracted from (neuro)physiological signals. Ideal physiomarkers for adaptive DBS (aDBS) are indicative of symptom severity, detectable in every patient, and technically suitable for implementation. In the last decades, much effort has been put into the detection of local field potential (LFP) physiomarkers and in their use in clinical practice. We conducted a research synthesis of the correlations that have been reported between LFP signal features and one or more specific PD motor symptoms. Features based on the spectral beta band (~ 13 to 30 Hz) explained ~ 17% of individual variability in bradykinesia and rigidity symptom severity. Limitations of beta band oscillations as physiomarker are discussed, and strategies for further improvement of aDBS are explored.
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Bahadori-Jahromi F, Salehi S, Madadi Asl M, Valizadeh A. Efficient suppression of parkinsonian beta oscillations in a closed-loop model of deep brain stimulation with amplitude modulation. Front Hum Neurosci 2023; 16:1013155. [PMID: 36776221 PMCID: PMC9908610 DOI: 10.3389/fnhum.2022.1013155] [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: 08/06/2022] [Accepted: 12/09/2022] [Indexed: 01/27/2023] Open
Abstract
Introduction Parkinson's disease (PD) is a movement disorder characterized by the pathological beta band (15-30 Hz) neural oscillations within the basal ganglia (BG). It is shown that the suppression of abnormal beta oscillations is correlated with the improvement of PD motor symptoms, which is a goal of standard therapies including deep brain stimulation (DBS). To overcome the stimulation-induced side effects and inefficiencies of conventional DBS (cDBS) and to reduce the administered stimulation current, closed-loop adaptive DBS (aDBS) techniques were developed. In this method, the frequency and/or amplitude of stimulation are modulated based on various disease biomarkers. Methods Here, by computational modeling of a cortico-BG-thalamic network in normal and PD conditions, we show that closed-loop aDBS of the subthalamic nucleus (STN) with amplitude modulation leads to a more effective suppression of pathological beta oscillations within the parkinsonian BG. Results Our results show that beta band neural oscillations are restored to their normal range and the reliability of the response of the thalamic neurons to motor cortex commands is retained due to aDBS with amplitude modulation. Furthermore, notably less stimulation current is administered during aDBS compared with cDBS due to a closed-loop control of stimulation amplitude based on the STN local field potential (LFP) beta activity. Discussion Efficient models of closed-loop stimulation may contribute to the clinical development of optimized aDBS techniques designed to reduce potential stimulation-induced side effects of cDBS in PD patients while leading to a better therapeutic outcome.
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Affiliation(s)
| | - Sina Salehi
- Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, Iran,*Correspondence: Sina Salehi ✉
| | - 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,Mojtaba Madadi Asl ✉
| | - Alireza Valizadeh
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran,Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
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Subthalamic beta bursts correlate with dopamine-dependent motor symptoms in 106 Parkinson's patients. NPJ Parkinsons Dis 2023; 9:2. [PMID: 36611027 PMCID: PMC9825387 DOI: 10.1038/s41531-022-00443-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 12/21/2022] [Indexed: 01/09/2023] Open
Abstract
Pathologically increased beta power has been described as a biomarker for Parkinson's disease (PD) and related to prolonged bursts of subthalamic beta synchronization. Here, we investigate the association between subthalamic beta dynamics and motor impairment in a cohort of 106 Parkinson's patients in the ON- and OFF-medication state, using two different methods of beta burst determination. We report a frequency-specific correlation of low beta power and burst duration with motor impairment OFF dopaminergic medication. Furthermore, reduction of power and burst duration correlated significantly with symptom alleviation through dopaminergic medication. Importantly, qualitatively similar results were yielded with two different methods of beta burst definition. Our findings validate the robustness of previous results on pathological changes in subcortical oscillations both in the frequency- as well as in the time-domain in the largest cohort of PD patients to date with important implications for next-generation adaptive deep brain stimulation control algorithms.
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Skovgård K, Barrientos SA, Petersson P, Halje P, Cenci MA. Distinctive Effects of D1 and D2 Receptor Agonists on Cortico-Basal Ganglia Oscillations in a Rodent Model of L-DOPA-Induced Dyskinesia. Neurotherapeutics 2023; 20:304-324. [PMID: 36344723 PMCID: PMC10119363 DOI: 10.1007/s13311-022-01309-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/19/2022] [Indexed: 11/09/2022] Open
Abstract
L-DOPA-induced dyskinesia (LID) in Parkinson's disease has been linked to oscillatory neuronal activities in the cortico-basal ganglia network. We set out to examine the pattern of cortico-basal ganglia oscillations induced by selective agonists of D1 and D2 receptors in a rat model of LID. Local field potentials were recorded in freely moving rats using large-scale electrodes targeting three motor cortical regions, dorsomedial and dorsolateral striatum, external globus pallidus, and substantial nigra pars reticulata. Abnormal involuntary movements were elicited by the D1 agonist SKF82958 or the D2 agonist sumanirole, while overall motor activity was quantified using video analysis (DeepLabCut). Both SKF82958 and sumanirole induced dyskinesia, although with significant differences in temporal course, overall severity, and body distribution. The D1 agonist induced prominent narrowband oscillations in the high gamma range (70-110 Hz) in all recorded structures except for the nigra reticulata. Additionally, the D1 agonist induced strong functional connectivity between the recorded structures and the phase analysis revealed that the primary motor cortex (forelimb area) was leading a supplementary motor area and striatum. Following treatment with the D2 agonist, narrowband gamma oscillations were detected only in forelimb motor cortex and dorsolateral striatum, while prominent oscillations in the theta band occurred in the globus pallidus and nigra reticulata. Our results reveal that the dyskinetic effects of D1 and D2 receptor agonists are associated with distinct patterns of cortico-basal ganglia oscillations, suggesting a recruitment of partially distinct networks.
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Affiliation(s)
- Katrine Skovgård
- Basal Ganglia Pathophysiology Unit, Department of Experimental Medical Science, Lund University, BMC A13, 221 84, Lund, Sweden
- The Group for Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - Sebastian A Barrientos
- The Group for Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Science, Lund University, Lund, Sweden
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Per Petersson
- The Group for Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Science, Lund University, Lund, Sweden
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
| | - Pär Halje
- The Group for Integrative Neurophysiology and Neurotechnology, Department of Experimental Medical Science, Lund University, Lund, Sweden
| | - M Angela Cenci
- Basal Ganglia Pathophysiology Unit, Department of Experimental Medical Science, Lund University, BMC A13, 221 84, Lund, Sweden.
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Wu D, Zhao B, Xie H, Xu Y, Yin Z, Bai Y, Fan H, Zhang Q, Liu D, Hu T, Jiang Y, An Q, Zhang X, Yang A, Zhang J. Profiling the low-beta characteristics of the subthalamic nucleus in early- and late-onset Parkinson's disease. Front Aging Neurosci 2023; 15:1114466. [PMID: 36875708 PMCID: PMC9978704 DOI: 10.3389/fnagi.2023.1114466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 01/30/2023] [Indexed: 02/18/2023] Open
Abstract
Objectives Low-beta oscillation (13-20 Hz) has rarely been studied in patients with early-onset Parkinson's disease (EOPD, age of onset ≤50 years). We aimed to explore the characteristics of low-beta oscillation in the subthalamic nucleus (STN) of patients with EOPD and investigate the differences between EOPD and late-onset Parkinson's disease (LOPD). Methods We enrolled 31 EOPD and 31 LOPD patients, who were matched using propensity score matching. Patients underwent bilateral STN deep brain stimulation (DBS). Local field potentials were recorded using intraoperative microelectrode recording. We analyzed the low-beta band parameters, including aperiodic/periodic components, beta burst, and phase-amplitude coupling. We compared low-beta band activity between EOPD and LOPD. Correlation analyses were performed between the low-beta parameters and clinical assessment results for each group. Results We found that the EOPD group had lower aperiodic parameters, including offset (p = 0.010) and exponent (p = 0.047). Low-beta burst analysis showed that EOPD patients had significantly higher average burst amplitude (p = 0.016) and longer average burst duration (p = 0.011). Furthermore, EOPD had higher proportion of long burst (500-650 ms, p = 0.008), while LOPD had higher proportion of short burst (200-350 ms, p = 0.007). There was a significant difference in phase-amplitude coupling values between low-beta phase and fast high frequency oscillation (300-460 Hz) amplitude (p = 0.019). Conclusion We found that low-beta activity in the STN of patients with EOPD had characteristics that varied when compared with LOPD, and provided electrophysiological evidence for different pathological mechanisms between the two types of PD. These differences need to be considered when applying adaptive DBS on patients of different ages.
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Affiliation(s)
- Delong Wu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Baotian Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hutao Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Houyou Fan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Quan Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Defeng Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Tianqi Hu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xin Zhang
- Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,Beijing Key Laboratory of Neurostimulation, Beijing, China.,Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
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49
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Belkacem AN, Jamil N, Khalid S, Alnajjar F. On closed-loop brain stimulation systems for improving the quality of life of patients with neurological disorders. Front Hum Neurosci 2023; 17:1085173. [PMID: 37033911 PMCID: PMC10076878 DOI: 10.3389/fnhum.2023.1085173] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/06/2023] [Indexed: 04/11/2023] Open
Abstract
Emerging brain technologies have significantly transformed human life in recent decades. For instance, the closed-loop brain-computer interface (BCI) is an advanced software-hardware system that interprets electrical signals from neurons, allowing communication with and control of the environment. The system then transmits these signals as controlled commands and provides feedback to the brain to execute specific tasks. This paper analyzes and presents the latest research on closed-loop BCI that utilizes electric/magnetic stimulation, optogenetic, and sonogenetic techniques. These techniques have demonstrated great potential in improving the quality of life for patients suffering from neurodegenerative or psychiatric diseases. We provide a comprehensive and systematic review of research on the modalities of closed-loop BCI in recent decades. To achieve this, the authors used a set of defined criteria to shortlist studies from well-known research databases into categories of brain stimulation techniques. These categories include deep brain stimulation, transcranial magnetic stimulation, transcranial direct-current stimulation, transcranial alternating-current stimulation, and optogenetics. These techniques have been useful in treating a wide range of disorders, such as Alzheimer's and Parkinson's disease, dementia, and depression. In total, 76 studies were shortlisted and analyzed to illustrate how closed-loop BCI can considerably improve, enhance, and restore specific brain functions. The analysis revealed that literature in the area has not adequately covered closed-loop BCI in the context of cognitive neural prosthetics and implanted neural devices. However, the authors demonstrate that the applications of closed-loop BCI are highly beneficial, and the technology is continually evolving to improve the lives of individuals with various ailments, including those with sensory-motor issues or cognitive deficiencies. By utilizing emerging techniques of stimulation, closed-loop BCI can safely improve patients' cognitive and affective skills, resulting in better healthcare outcomes.
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Affiliation(s)
- Abdelkader Nasreddine Belkacem
- Department of Computer and Network Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
- *Correspondence: Abdelkader Nasreddine Belkacem
| | - Nuraini Jamil
- Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
| | - Sumayya Khalid
- Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
| | - Fady Alnajjar
- Department of Computer Science and Software Engineering, College of Information Technology, UAE University, Al-Ain, United Arab Emirates
- Center for Brain Science, RIKEN, Saitama, Japan
- Fady Alnajjar
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50
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Peterson V, Merk T, Bush A, Nikulin V, Kühn AA, Neumann WJ, Richardson RM. Movement decoding using spatio-spectral features of cortical and subcortical local field potentials. Exp Neurol 2023; 359:114261. [PMID: 36349662 DOI: 10.1016/j.expneurol.2022.114261] [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: 01/31/2022] [Revised: 09/26/2022] [Accepted: 10/25/2022] [Indexed: 12/30/2022]
Abstract
The first commercially sensing enabled deep brain stimulation (DBS) devices for the treatment of movement disorders have recently become available. In the future, such devices could leverage machine learning based brain signal decoding strategies to individualize and adapt therapy in real-time. As multi-channel recordings become available, spatial information may provide an additional advantage for informing machine learning models. To investigate this concept, we compared decoding performances from single channels vs. spatial filtering techniques using intracerebral multitarget electrophysiology in Parkinson's disease patients undergoing DBS implantation. We investigated the feasibility of spatial filtering in invasive neurophysiology and the putative utility of combined cortical ECoG and subthalamic local field potential signals for decoding grip-force, a well-defined and continuous motor readout. We found that adding spatial information to the model can improve decoding (6% gain in decoding), but the spatial patterns and additional benefit was highly individual. Beyond decoding performance results, spatial filters and patterns can be used to obtain meaningful neurophysiological information about the brain networks involved in target behavior. Our results highlight the importance of individualized approaches for brain signal decoding, for which multielectrode recordings and spatial filtering can improve precision medicine approaches for clinical brain computer interfaces.
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Affiliation(s)
- Victoria Peterson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA.
| | - Timon Merk
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Alan Bush
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Vadim Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - R Mark Richardson
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, USA
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