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Yin Z, Yuan T, Yang A, Xu Y, Zhu G, An Q, Ma R, Gan Y, Shi L, Bai Y, Zhang N, Wang C, Jiang Y, Meng F, Neumann WJ, Tan H, Zhang JG. Contribution of basal ganglia activity to REM sleep disorder in Parkinson's disease. J Neurol Neurosurg Psychiatry 2024:jnnp-2023-332014. [PMID: 38641368 DOI: 10.1136/jnnp-2023-332014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 03/14/2024] [Indexed: 04/21/2024]
Abstract
BACKGROUND Rapid eye movement (REM) sleep behaviour disorder (RBD) is one of the most common sleep problems and represents a key prodromal marker in Parkinson's disease (PD). It remains unclear whether and how basal ganglia nuclei, structures that are directly involved in the pathology of PD, are implicated in the occurrence of RBD. METHOD Here, in parallel with whole-night video polysomnography, we recorded local field potentials from two major basal ganglia structures, the globus pallidus internus and subthalamic nucleus, in two cohorts of patients with PD who had varied severity of RBD. Basal ganglia oscillatory patterns during RBD and REM sleep without atonia were analysed and compared with another age-matched cohort of patients with dystonia that served as controls. RESULTS We found that beta power in both basal ganglia nuclei was specifically elevated during REM sleep without atonia in patients with PD, but not in dystonia. Basal ganglia beta power during REM sleep positively correlated with the extent of atonia loss, with beta elevation preceding the activation of chin electromyogram activities by ~200 ms. The connectivity between basal ganglia beta power and chin muscular activities during REM sleep was significantly correlated with the clinical severity of RBD in PD. CONCLUSIONS These findings support that basal ganglia activities are associated with if not directly contribute to the occurrence of RBD in PD. Our study expands the understanding of the role basal ganglia played in RBD and may foster improved therapies for RBD by interrupting the basal ganglia-muscular communication during REM sleep in PD.
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Affiliation(s)
- Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Campus Mitte, Charite - Universitatsmedizin Berlin, Berlin, Germany
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yifei Gan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Shi
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yutong Bai
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ning Zhang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunxue Wang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Campus Mitte, Charite - Universitatsmedizin Berlin, Berlin, Germany
| | - Huiling Tan
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
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Kamo H, Oyama G, Yamasaki Y, Nagayama T, Nawashiro R, Hattori N. A proof of concept: digital diary using 24-hour monitoring using wearable device for patients with Parkinson's disease in nursing homes. Front Neurol 2024; 15:1356042. [PMID: 38660090 PMCID: PMC11041395 DOI: 10.3389/fneur.2024.1356042] [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: 12/14/2023] [Accepted: 02/26/2024] [Indexed: 04/26/2024] Open
Abstract
Introduction In the advanced stages of Parkinson's disease (PD), motor complications such as wearing-off and dyskinesia are problematic and vary daily. These symptoms need to be monitored precisely to provide adequate care for patients with advanced PD. Methods This study used wearable devices to explore biomarkers for motor complications by measuring multiple biomarkers in patients with PD residing in facilities and combining them with lifestyle and clinical assessments. Data on the pulse rate and activity index (metabolic equivalents) were collected from 12 patients over 30 days. Results The pulse rate and activity index during the off- and on-periods and dyskinesia were analyzed for two participants; the pulse rate and activity index did not show any particular trend in each participant; however, the pulse rate/activity index was significantly greater in the off-state compared to that in the dyskinesia and on-states, and this index in the dyskinesia state was significantly greater than that in the on-state in both participants. Conclusion These results suggest the pulse rate and activity index combination would be a useful indicator of wearing-off and dyskinesia and that biometric information from wearable devices may function as a digital diary. Accumulating more cases and collecting additional data are necessary to verify our findings.
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Affiliation(s)
- Hikaru Kamo
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
| | - Genko Oyama
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
- Department of Home Medical Care System, Based on Information and Communication Technology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Drug Development for Parkinson's Disease, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of PRO-Based Integrated Data Analysis in Neurological Disorders, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Research and Therapeutics for Movement Disorders, Juntendo University Graduate School of Medicine, Tokyo, Japan
| | - Yui Yamasaki
- Sunwels Company Limited, Chiyoda-ku, Tokyo, Japan
| | | | | | - Nobutaka Hattori
- Department of Neurology, Juntendo University School of Medicine, Tokyo, Japan
- Department of Home Medical Care System, Based on Information and Communication Technology, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of Drug Development for Parkinson's Disease, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Department of PRO-Based Integrated Data Analysis in Neurological Disorders, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Research and Therapeutics for Movement Disorders, Juntendo University Graduate School of Medicine, Tokyo, Japan
- Research Institute of Disease of Old Age, Graduate School of Medicine, Juntendo University, Tokyo, Japan
- Neurodegenerative Disorders Collaborative Laboratory, RIKEN Center for Brain Science, Saitama, Japan
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3
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Wiesman AI, da Silva Castanheira J, Fon EA, Baillet S. Alterations of Cortical Structure and Neurophysiology in Parkinson's Disease Are Aligned with Neurochemical Systems. Ann Neurol 2024; 95:802-816. [PMID: 38146745 PMCID: PMC11023768 DOI: 10.1002/ana.26871] [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: 12/23/2023] [Accepted: 12/23/2023] [Indexed: 12/27/2023]
Abstract
OBJECTIVE Parkinson's disease (PD) affects the structural integrity and neurophysiological signaling of the cortex. These alterations are related to the motor and cognitive symptoms of the disease. How these changes are related to the neurochemical systems of the cortex is unknown. METHODS We used T1-weighted magnetic resonance imaging (MRI) and magnetoencephalography (MEG) to measure cortical thickness and task-free neurophysiological activity in patients with idiopathic PD (nMEG = 79, nMRI = 65) and matched healthy controls (nMEG = 65, nMRI = 37). Using linear mixed-effects models, we examined the topographical alignment of cortical structural and neurophysiological alterations in PD with cortical atlases of 19 neurotransmitter receptor and transporter densities. RESULTS We found that neurophysiological alterations in PD occur primarily in brain regions rich in acetylcholinergic, serotonergic, and glutamatergic systems, with protective implications for cognitive and psychiatric symptoms. In contrast, cortical thinning occurs preferentially in regions rich in noradrenergic systems, and the strength of this alignment relates to motor deficits. INTERPRETATION This study shows that the spatial organization of neurophysiological and structural alterations in PD is relevant for nonmotor and motor impairments. The data also advance the identification of the neurochemical systems implicated. The approach uses novel nested atlas modeling methodology that is transferrable to research in other neurological and neuropsychiatric diseases and syndromes. ANN NEUROL 2024;95:802-816.
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Affiliation(s)
- Alex I. Wiesman
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | | | - Edward A. Fon
- Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Montreal, Canada
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4
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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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Lin S, Jiang J, Huang K, Li L, He X, Du P, Wu Y, Liu J, Li X, Huang Z, Zhou Z, Yu Y, Gao J, Lei M, Wu H. Advanced Electrode Technologies for Noninvasive Brain-Computer Interfaces. ACS NANO 2023; 17:24487-24513. [PMID: 38064282 DOI: 10.1021/acsnano.3c06781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Brain-computer interfaces (BCIs) have garnered significant attention in recent years due to their potential applications in medical, assistive, and communication technologies. Building on this, noninvasive BCIs stand out as they provide a safe and user-friendly method for interacting with the human brain. In this work, we provide a comprehensive overview of the latest developments and advancements in material, design, and application of noninvasive BCIs electrode technology. We also explore the challenges and limitations currently faced by noninvasive BCI electrode technology and sketch out the technological roadmap from three dimensions: Materials and Design; Performances; Mode and Function. We aim to unite research efforts within the field of noninvasive BCI electrode technology, focusing on the consolidation of shared goals and fostering integrated development strategies among a diverse array of multidisciplinary researchers.
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Affiliation(s)
- Sen Lin
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jingjing Jiang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Kai Huang
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Lei Li
- National Engineering Research Center of Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
| | - Xian He
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Peng Du
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Yufeng Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
| | - Junchen Liu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xilin Li
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
- Advanced Institute for Brain and Intelligence, Guangxi University, Nanning 530004, China
| | - Zhibao Huang
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Zenan Zhou
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Yuanhang Yu
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Jiaxin Gao
- School of Physical Science and Technology, Guangxi University, Nanning 530004, China
| | - Ming Lei
- State Key Laboratory of Information Photonics and Optical Communications and School of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Hui Wu
- State Key Laboratory of New Ceramics and Fine Processing, School of Materials Science and Engineering, Tsinghua University, Beijing 100084, China
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Wiesman AI, da Silva Castanheira J, Degroot C, Fon EA, Baillet S, Network QP. Adverse and compensatory neurophysiological slowing in Parkinson's disease. Prog Neurobiol 2023; 231:102538. [PMID: 37832713 PMCID: PMC10872886 DOI: 10.1016/j.pneurobio.2023.102538] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 10/15/2023]
Abstract
Patients with Parkinson's disease (PD) exhibit multifaceted changes in neurophysiological brain activity, hypothesized to represent a global cortical slowing effect. Using task-free magnetoencephalography and extensive clinical assessments, we found that neurophysiological slowing in PD is differentially associated with motor and non-motor symptoms along a sagittal gradient over the cortical anatomy. In superior parietal regions, neurophysiological slowing reflects an adverse effect and scales with cognitive and motor impairments, while across the inferior frontal cortex, neurophysiological slowing is compatible with a compensatory role. This adverse-to-compensatory gradient is sensitive to individual clinical profiles, such as drug regimens and laterality of symptoms; it is also aligned with the topography of neurotransmitter and transporter systems relevant to PD. We conclude that neurophysiological slowing in patients with PD signals both deleterious and protective mechanisms of the disease, from posterior to anterior regions across the cortex, respectively, with functional and clinical relevance to motor and cognitive symptoms.
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Affiliation(s)
- Alex I Wiesman
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
| | | | - Clotilde Degroot
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Edward A Fon
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada.
| | - Quebec Parkinson Network
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Canada
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7
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Rizzo R, Wang JWJL, DePold Hohler A, Holsapple JW, Vaou OE, Ivanov PC. Dynamic networks of cortico-muscular interactions in sleep and neurodegenerative disorders. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1168677. [PMID: 37744179 PMCID: PMC10512188 DOI: 10.3389/fnetp.2023.1168677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 08/09/2023] [Indexed: 09/26/2023]
Abstract
The brain plays central role in regulating physiological systems, including the skeleto-muscular and locomotor system. Studies of cortico-muscular coordination have primarily focused on associations between movement tasks and dynamics of specific brain waves. However, the brain-muscle functional networks of synchronous coordination among brain waves and muscle activity rhythms that underlie locomotor control remain unknown. Here we address the following fundamental questions: what are the structure and dynamics of cortico-muscular networks; whether specific brain waves are main network mediators in locomotor control; how the hierarchical network organization relates to distinct physiological states under autonomic regulation such as wake, sleep, sleep stages; and how network dynamics are altered with neurodegenerative disorders. We study the interactions between all physiologically relevant brain waves across cortical locations with distinct rhythms in leg and chin muscle activity in healthy and Parkinson's disease (PD) subjects. Utilizing Network Physiology framework and time delay stability approach, we find that 1) each physiological state is characterized by a unique network of cortico-muscular interactions with specific hierarchical organization and profile of links strength; 2) particular brain waves play role as main mediators in cortico-muscular interactions during each state; 3) PD leads to muscle-specific breakdown of cortico-muscular networks, altering the sleep-stage stratification pattern in network connectivity and links strength. In healthy subjects cortico-muscular networks exhibit a pronounced stratification with stronger links during wake and light sleep, and weaker links during REM and deep sleep. In contrast, network interactions reorganize in PD with decline in connectivity and links strength during wake and non-REM sleep, and increase during REM, leading to markedly different stratification with gradual decline in network links strength from wake to REM, light and deep sleep. Further, we find that wake and sleep stages are characterized by specific links strength profiles, which are altered with PD, indicating disruption in the synchronous activity and network communication among brain waves and muscle rhythms. Our findings demonstrate the presence of previously unrecognized functional networks and basic principles of brain control of locomotion, with potential clinical implications for novel network-based biomarkers for early detection of Parkinson's and neurodegenerative disorders, movement, and sleep disorders.
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Affiliation(s)
- Rossella Rizzo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Jilin W. J. L. Wang
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
| | - Anna DePold Hohler
- Department of Neurology, Steward St. Elizabeth’s Medical Center, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - James W. Holsapple
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA, United States
| | - Okeanis E. Vaou
- Department of Neurology, Steward St. Elizabeth’s Medical Center, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Plamen Ch. Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women Hospital, Boston, MA, United States
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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Boon LI, Hillebrand A, Schoonheim MM, Twisk JW, Stam CJ, Berendse HW. Cortical and Subcortical Changes in MEG Activity Reflect Parkinson's Progression over a Period of 7 Years. Brain Topogr 2023:10.1007/s10548-023-00965-w. [PMID: 37154884 DOI: 10.1007/s10548-023-00965-w] [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: 10/25/2022] [Accepted: 04/15/2023] [Indexed: 05/10/2023]
Abstract
In this study of early functional changes in Parkinson's disease (PD), we aimed to provide a comprehensive assessment of the development of changes in both cortical and subcortical neurophysiological brain activity, including their association with clinical measures of disease severity. Repeated resting-state MEG recordings and clinical assessments were obtained in the context of a unique longitudinal cohort study over a seven-year period using a multiple longitudinal design. We used linear mixed-models to analyze the relationship between neurophysiological (spectral power and functional connectivity) and clinical data. At baseline, early-stage (drug-naïve) PD patients demonstrated spectral slowing compared to healthy controls in both subcortical and cortical brain regions, most outspoken in the latter. Over time, spectral slowing progressed in strong association with clinical measures of disease progression (cognitive and motor). Global functional connectivity was not different between groups at baseline and hardly changed over time. Therefore, investigation of associations with clinical measures of disease progression were not deemed useful. An analysis of individual connections demonstrated differences between groups at baseline (higher frontal theta, lower parieto-occipital alpha2 band functional connectivity) and over time in PD patients (increase in frontal delta and theta band functional connectivity). Our results suggest that spectral measures are promising candidates in the search for non-invasive markers of both early-stage PD and of the ongoing disease process.
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Affiliation(s)
- Lennard I Boon
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands.
| | - Arjan Hillebrand
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Jos W Twisk
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Cornelis J Stam
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
- Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Henk W Berendse
- Department of Neurology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
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Wilkins KB, Kehnemouyi YM, Petrucci MN, Anderson RW, Parker JE, Trager MH, Neuville RS, Koop MM, Velisar A, Blumenfeld Z, Quinn EJ, Bronte-Stewart HM. Bradykinesia and Its Progression Are Related to Interhemispheric Beta Coherence. Ann Neurol 2023; 93:1029-1039. [PMID: 36641645 PMCID: PMC10191890 DOI: 10.1002/ana.26605] [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: 09/12/2022] [Revised: 12/05/2022] [Accepted: 01/09/2023] [Indexed: 01/16/2023]
Abstract
OBJECTIVE Bradykinesia is the major cardinal motor sign of Parkinson disease (PD), but its neural underpinnings are unclear. The goal of this study was to examine whether changes in bradykinesia following long-term subthalamic nucleus (STN) deep brain stimulation (DBS) are linked to local STN beta (13-30 Hz) dynamics or a wider bilateral network dysfunction. METHODS Twenty-one individuals with PD implanted with sensing neurostimulators (Activa® PC + S, Medtronic, PLC) in the STN participated in a longitudinal 'washout' therapy study every three to 6 months for an average of 3 years. At each visit, participants were withdrawn from medication (12/24/48 hours) and had DBS turned off (>60 minutes) before completing a repetitive wrist-flexion extension task, a validated quantitative assessment of bradykinesia, while local field potentials were recorded. Local STN beta dynamics were investigated via beta power and burst duration, while interhemispheric beta synchrony was assessed with STN-STN beta coherence. RESULTS Higher interhemispheric STN beta coherence, but not contralateral beta power or burst duration, was significantly associated with worse bradykinesia. Bradykinesia worsened off therapy over time. Interhemispheric STN-STN beta coherence also increased over time, whereas beta power and burst duration remained stable. The observed change in bradykinesia was related to the change in interhemispheric beta coherence, with greater increases in synchrony associated with further worsening of bradykinesia. INTERPRETATION Together, these findings implicate interhemispheric beta synchrony as a neural correlate of the progression of bradykinesia following chronic STN DBS. This could imply the existence of a pathological bilateral network contributing to bradykinesia in PD. ANN NEUROL 2023;93:1029-1039.
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Affiliation(s)
- Kevin B Wilkins
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
| | - Yasmine M Kehnemouyi
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, CA, United States
| | - Matthew N Petrucci
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, CA, United States
| | - Ross W Anderson
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Neurosurgery, Kaiser Permanente, Redwood City, CA, United States
| | - Jordan E Parker
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Psychology, University of California, Los Angeles, CA, United States
| | - Megan H Trager
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Columbia University Irving Medical Center, New York, NY, United States
| | - Raumin S Neuville
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- The University of California School of Medicine, Irvine, CA, United States
| | - Mandy M Koop
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Cleveland Clinic, Cleveland, OH, United States
| | - Anca Velisar
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- The Smith-Kettlewell Eye Research Institute, San Francisco, CA, United States
| | - Zack Blumenfeld
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, United States
- University of Southern California, Keck School of Medicine, Los Angeles, CA, United States
| | - Emma J Quinn
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Credit Karma, San Francisco, CA, United States
| | - Helen M Bronte-Stewart
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, United States
- Department of Bioengineering, Stanford Schools of Engineering & Medicine, Stanford, CA, United States
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States
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Wiesman AI, Donhauser PW, Degroot C, Diab S, Kousaie S, Fon EA, Klein D, Baillet S. Aberrant neurophysiological signaling associated with speech impairments in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:61. [PMID: 37059749 PMCID: PMC10104849 DOI: 10.1038/s41531-023-00495-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 03/16/2023] [Indexed: 04/16/2023] Open
Abstract
Difficulty producing intelligible speech is a debilitating symptom of Parkinson's disease (PD). Yet, both the robust evaluation of speech impairments and the identification of the affected brain systems are challenging. Using task-free magnetoencephalography, we examine the spectral and spatial definitions of the functional neuropathology underlying reduced speech quality in patients with PD using a new approach to characterize speech impairments and a novel brain-imaging marker. We found that the interactive scoring of speech impairments in PD (N = 59) is reliable across non-expert raters, and better related to the hallmark motor and cognitive impairments of PD than automatically-extracted acoustical features. By relating these speech impairment ratings to neurophysiological deviations from healthy adults (N = 65), we show that articulation impairments in patients with PD are associated with aberrant activity in the left inferior frontal cortex, and that functional connectivity of this region with somatomotor cortices mediates the influence of cognitive decline on speech deficits.
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Affiliation(s)
- Alex I Wiesman
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montreal, QC, Canada
| | - Peter W Donhauser
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montreal, QC, Canada
- Ernst Strüngmann Institute for Neuroscience, Frankfurt, Germany
| | - Clotilde Degroot
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montreal, QC, Canada
| | - Sabrina Diab
- Department of Psychology, Université du Québec à Montréal, Montréal, QC, Canada
| | - Shanna Kousaie
- School of Psychology, University of Ottawa, Ottawa, ON, Canada
| | - Edward A Fon
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montreal, QC, Canada
| | - Denise Klein
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montreal, QC, Canada.
- Center for Research on Brain, Language and Music, McGill University, Montreal, QC, Canada.
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, 3801 Rue University, Montreal, QC, Canada.
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11
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Sun S, Wang X, Shi X, Fang H, Sun Y, Li M, Han H, He Q, Wang X, Zhang X, Zhu ZW, Chen F, Wang M. Neural pathway connectivity and discharge changes between M1 and STN in hemiparkinsonian rats. Brain Res Bull 2023; 196:1-19. [PMID: 36878325 DOI: 10.1016/j.brainresbull.2023.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 02/27/2023] [Accepted: 03/03/2023] [Indexed: 03/07/2023]
Abstract
Alterations of electrophysiological activities, such as changed spike firing rates, reshaping the firing patterns, and aberrant frequency oscillations between the subthalamic nucleus (STN) and the primary motor cortex (M1), are thought to contribute to motor impairment in Parkinson's disease (PD). However, the alterations of electrophysiological characteristics of STN and M1 in PD are still unclear, especially under specific treadmill movement. To examine the relationship between electrophysiological activity in the STN-M1 pathway, extracellular spike trains and local field potential (LFPs) of STN and M1 were simultaneously recorded during resting and movement in unilateral 6-hydroxydopamine (6-OHDA) lesioned rats. The results showed that the identified STN neurons and M1 neurons exhibited abnormal neuronal activity after dopamine loss. The dopamine depletion altered the LFP power in STN and M1 whatever in rest or movement states. Furthermore, the enhanced synchronization of LFP oscillations after dopamine loss was found in 12-35 Hz (beta frequencies) between the STN and M1 during rest and movement. In addition, STN neurons were phase-locked firing to M1 oscillations at 12-35 Hz during rest epochs in 6-OHDA lesioned rats. The dopamine depletion also impaired the anatomical connectivity between the M1 and STN by injecting anterograde neuroanatomical tracing virus into M1 in control and PD rats. Collectively, impairment of' electrophysiological activity and anatomical connectivity in the M1-STN pathway may be the basis for dysfunction of the cortico-basal ganglia circuit, correlating with motor symptoms of PD.
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Affiliation(s)
- Shuang Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Xuenan Wang
- Shandong Institute of Brain Science and Brain-inspired Research, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan 250117, China
| | - Xiaoman Shi
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Heyi Fang
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Yue Sun
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Min Li
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Hongyu Han
- Weifang Middle School, Weifang 261031, China
| | - Qin He
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Xiaojun Wang
- The First Hospital Affiliated with Shandong First Medicine University, Jinan 250014, China
| | - Xiao Zhang
- Editorial Department of Journal, Shandong Jianzhu University, Jinan 250014, China
| | - Zhi Wei Zhu
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China
| | - Feiyu Chen
- School of International Education, Qilu University of Technology, Jinan 250014, China.
| | - Min Wang
- Key Laboratory of Animal Resistance Biology of Shandong Province, College of Life Science, Shandong Normal University, 88# Wenhua Road, Jinan 250014, China.
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12
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van Wijk BCM, Neumann WJ, Kroneberg D, Horn A, Irmen F, Sander TH, Wang Q, Litvak V, Kühn AA. Functional connectivity maps of theta/alpha and beta coherence within the subthalamic nucleus region. Neuroimage 2022; 257:119320. [PMID: 35580809 DOI: 10.1016/j.neuroimage.2022.119320] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Revised: 05/10/2022] [Accepted: 05/12/2022] [Indexed: 11/29/2022] Open
Abstract
The subthalamic nucleus (STN) is a primary target for deep brain stimulation in Parkinson's disease (PD). Although small in size, the STN is commonly partitioned into sensorimotor, cognitive/associative, and limbic subregions based on its structural connectivity profile to cortical areas. We investigated whether such a regional specialization is also supported by functional connectivity between local field potential recordings and simultaneous magnetoencephalography. Using a novel data set of 21 PD patients, we replicated previously reported cortico-STN coherence networks in the theta/alpha and beta frequency ranges, and looked for the spatial distribution of these networks within the STN region. Although theta/alpha and beta coherence peaks were both observed in on-medication recordings from electrode contacts at several locations within and around the STN, sites with theta/alpha coherence peaks were situated at significantly more inferior MNI coordinates than beta coherence peaks. Sites with only theta/alpha coherence peaks, i.e. without distinct beta coherence, were mostly located near the border of sensorimotor and cognitive/associative subregions as defined by a tractography-based atlas of the STN. Peak coherence values were largely unaltered by the medication state of the subject, however, theta/alpha peaks were more often identified in recordings obtained after administration of dopaminergic medication. Our findings suggest the existence of a frequency-specific topography of cortico-STN coherence within the STN, albeit with considerable spatial overlap between functional networks. Consequently, optimization of deep brain stimulation targeting might remain a trade-off between alleviating motor symptoms and avoiding adverse neuropsychiatric side effects.
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Affiliation(s)
- Bernadette C M van Wijk
- Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, the Netherlands; Integrative Model-based Cognitive Neuroscience Research Unit, Department of Psychology, University of Amsterdam, the Netherlands; Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; Wellcome Centre for Human Neuroimaging, University College London, UK.
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Daniel Kroneberg
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Andreas Horn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; Center for Brain Circuit Therapeutics, Department of Neurology, Brigham & Women's Hospital, Harvard Medical School, Boston, USA; MGH Neurosurgery & Center for Neurotechnology and Neurorecovery (CNTR), MGH Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, USA
| | - Friederike Irmen
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | | | - Qiang Wang
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, University College London, UK
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany; NeuroCure Clinical Research Centre, Charité - Universitätsmedizin Berlin, Germany; DZNE, German Center for Degenerative Diseases, Berlin, Germany
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13
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Hirschmann J, Steina A, Vesper J, Florin E, Schnitzler A. Neuronal oscillations predict deep brain stimulation outcome in Parkinson's disease. Brain Stimul 2022; 15:792-802. [PMID: 35568311 DOI: 10.1016/j.brs.2022.05.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 05/06/2022] [Accepted: 05/07/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Neuronal oscillations are linked to symptoms of Parkinson's disease. This relation can be exploited for optimizing deep brain stimulation (DBS), e.g. by informing a device or human about the optimal location, time and intensity of stimulation. Whether oscillations predict individual DBS outcome is not clear so far. OBJECTIVE To predict motor symptom improvement from subthalamic power and subthalamo-cortical coherence. METHODS We applied machine learning techniques to simultaneously recorded magnetoencephalography and local field potential data from 36 patients with Parkinson's disease. Gradient-boosted tree learning was applied in combination with feature importance analysis to generate and understand out-of-sample predictions. RESULTS A few features sufficed for making accurate predictions. A model operating on five coherence features, for example, achieved correlations of r > 0.8 between actual and predicted outcomes. Coherence comprised more information in less features than subthalamic power, although in general their information content was comparable. Both signals predicted akinesia/rigidity reduction best. The most important local feature was subthalamic high-beta power (20-35 Hz). The most important connectivity features were subthalamo-parietal coherence in the very high frequency band (>200 Hz) and subthalamo-parietal coherence in low-gamma band (36-60 Hz). Successful prediction was not due to the model inferring distance to target or symptom severity from neuronal oscillations. CONCLUSION This study demonstrates for the first time that neuronal oscillations are predictive of DBS outcome. Coherence between subthalamic and parietal oscillations are particularly informative. These results highlight the clinical relevance of inter-areal synchrony in basal ganglia-cortex loops and might facilitate further improvements of DBS in the future.
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Affiliation(s)
- Jan Hirschmann
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany.
| | - Alexandra Steina
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
| | - Jan Vesper
- Functional Neurosurgery and Stereotaxy, Department of Neurosurgery, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany; Center for Movement Disorders and Neuromodulation, Department of Neurology, Medical Faculty, Heinrich Heine University, 40225, Düsseldorf, Germany
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14
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Zhang J, Villringer A, Nikulin VV. Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson’s Disease: An EEG Study. Front Aging Neurosci 2022; 14:846017. [PMID: 35572144 PMCID: PMC9106139 DOI: 10.3389/fnagi.2022.846017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Dopaminergic medication for Parkinson’s disease (PD) modulates neuronal oscillations and functional connectivity (FC) across the basal ganglia-thalamic-cortical circuit. However, the non-oscillatory component of the neuronal activity, potentially indicating a state of excitation/inhibition balance, has not yet been investigated and previous studies have shown inconsistent changes of cortico-cortical connectivity as a response to dopaminergic medication. To further elucidate changes of regional non-oscillatory component of the neuronal power spectra, FC, and to determine which aspects of network organization obtained with graph theory respond to dopaminergic medication, we analyzed a resting-state electroencephalography (EEG) dataset including 15 PD patients during OFF and ON medication conditions. We found that the spectral slope, typically used to quantify the broadband non-oscillatory component of power spectra, steepened particularly in the left central region in the ON compared to OFF condition. In addition, using lagged coherence as a FC measure, we found that the FC in the beta frequency range between centro-parietal and frontal regions was enhanced in the ON compared to the OFF condition. After applying graph theory analysis, we observed that at the lower level of topology the node degree was increased, particularly in the centro-parietal area. Yet, results showed no significant difference in global topological organization between the two conditions: either in global efficiency or clustering coefficient for measuring global and local integration, respectively. Interestingly, we found a close association between local/global spectral slope and functional network global efficiency in the OFF condition, suggesting a crucial role of local non-oscillatory dynamics in forming the functional global integration which characterizes PD. These results provide further evidence and a more complete picture for the engagement of multiple cortical regions at various levels in response to dopaminergic medication in PD.
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Affiliation(s)
- Juanli Zhang
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
- *Correspondence: Juanli Zhang,
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Vadim V. Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Neurophysics Group, Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
- Vadim V. Nikulin,
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15
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Oscillatory waveform sharpness asymmetry changes in motor thalamus and motor cortex in a rat model of Parkinson's disease. Exp Neurol 2022; 354:114089. [DOI: 10.1016/j.expneurol.2022.114089] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 04/01/2022] [Accepted: 04/17/2022] [Indexed: 11/23/2022]
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16
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Bore JC, Toth C, Campbell BA, Cho H, Pucci F, Hogue O, Machado AG, Baker KB. Consistent Changes in Cortico-Subthalamic Directed Connectivity Are Associated With the Induction of Parkinsonism in a Chronically Recorded Non-human Primate Model. Front Neurosci 2022; 16:831055. [PMID: 35310095 PMCID: PMC8930827 DOI: 10.3389/fnins.2022.831055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/31/2022] [Indexed: 11/23/2022] Open
Abstract
Parkinson’s disease is a neurological disease with cardinal motor signs including bradykinesia and tremor. Although beta-band hypersynchrony in the cortico-basal ganglia network is thought to contribute to disease manifestation, the resulting effects on network connectivity are unclear. We examined local field potentials from a non-human primate across the naïve, mild, and moderate disease states (model was asymmetric, left-hemispheric dominant) and probed power spectral density as well as cortico-cortical and cortico-subthalamic connectivity using both coherence and Granger causality, which measure undirected and directed effective connectivity, respectively. Our network included the left subthalamic nucleus (L-STN), bilateral primary motor cortices (L-M1, R-M1), and bilateral premotor cortices (L-PMC, R-PMC). Results showed two distinct peaks (Peak A at 5–20 Hz, Peak B at 25–45 Hz) across all analyses. Power and coherence analyses showed widespread increases in power and connectivity in both the Peak A and Peak B bands with disease progression. For Granger causality, increases in Peak B connectivity and decreases in Peak A connectivity were associated with the disease. Induction of mild disease was associated with several changes in connectivity: (1) the cortico-subthalamic connectivity in the descending direction (L-PMC to L-STN) decreased in the Peak A range while the reciprocal, ascending connectivity (L-STN to L-PMC) increased in the Peak B range; this may play a role in generating beta-band hypersynchrony in the cortex, (2) both L-M1 to L-PMC and R-M1 to R-PMC causalities increased, which may either be compensatory or a pathologic effect of disease, and (3) a decrease in connectivity occurred from the R-PMC to R-M1. The only significant change seen between mild and moderate disease was increased right cortical connectivity, which may reflect compensation for the left-hemispheric dominant moderate disease state.
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Affiliation(s)
- Joyce Chelangat Bore
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Carmen Toth
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Brett A. Campbell
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States
| | - Hanbin Cho
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
| | - Francesco Pucci
- Center for Neurological Restoration, Cleveland Clinic, Neurological Institute, Cleveland, OH, United States
- Department of Neurosurgery, Cleveland Clinic, Neurological Institute, Cleveland, OH, United States
| | - Olivia Hogue
- Center for Neurological Restoration, Cleveland Clinic, Neurological Institute, Cleveland, OH, United States
| | - Andre G. Machado
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Center for Neurological Restoration, Cleveland Clinic, Neurological Institute, Cleveland, OH, United States
- Department of Neurosurgery, Cleveland Clinic, Neurological Institute, Cleveland, OH, United States
| | - Kenneth B. Baker
- Department of Neurosciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States
- Center for Neurological Restoration, Cleveland Clinic, Neurological Institute, Cleveland, OH, United States
- *Correspondence: Kenneth B. Baker,
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17
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Pozzi NG, Isaias IU. Adaptive deep brain stimulation: Retuning Parkinson's disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:273-284. [PMID: 35034741 DOI: 10.1016/b978-0-12-819410-2.00015-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
A brain-machine interface represents a promising therapeutic avenue for the treatment of many neurologic conditions. Deep brain stimulation (DBS) is an invasive, neuro-modulatory tool that can improve different neurologic disorders by delivering electric stimulation to selected brain areas. DBS is particularly successful in advanced Parkinson's disease (PD), where it allows sustained improvement of motor symptoms. However, this approach is still poorly standardized, with variable clinical outcomes. To achieve an optimal therapeutic effect, novel adaptive DBS (aDBS) systems are being developed. These devices operate by adapting stimulation parameters in response to an input signal that can represent symptoms, motor activity, or other behavioral features. Emerging evidence suggests greater efficacy with fewer adverse effects during aDBS compared with conventional DBS. We address this topic by discussing the basics principles of aDBS, reviewing current evidence, and tackling the many challenges posed by aDBS for PD.
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Affiliation(s)
- Nicoló G Pozzi
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany
| | - Ioannis U Isaias
- Department of Neurology, University Hospital Würzburg and Julius Maximilian University Würzburg, Würzburg, Germany.
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18
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Cosentino G, Todisco M, Blandini F. Noninvasive neuromodulation in Parkinson's disease: Neuroplasticity implication and therapeutic perspectives. HANDBOOK OF CLINICAL NEUROLOGY 2022; 184:185-198. [PMID: 35034733 DOI: 10.1016/b978-0-12-819410-2.00010-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Noninvasive brain stimulation techniques can be used to study in vivo the changes of cortical activity and plasticity in subjects with Parkinson's disease (PD). Also, an increasing number of studies have suggested a potential therapeutic effect of these techniques. High-frequency repetitive transcranial magnetic stimulation (rTMS) and anodal transcranial direct current stimulation (tDCS) represent the most used stimulation paradigms to treat motor and nonmotor symptoms of PD. Both techniques can enhance cortical activity, compensating for its reduction related to subcortical dysfunction in PD. However, the use of suboptimal stimulation parameters can lead to therapeutic failure. Clinical studies are warranted to clarify in PD the additional effects of these stimulation techniques on pharmacologic and neurorehabilitation treatments.
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Affiliation(s)
- Giuseppe Cosentino
- Translational Neurophysiology Research Unit, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Massimiliano Todisco
- Translational Neurophysiology Research Unit, IRCCS Mondino Foundation, Pavia, Italy; Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; Movement Disorders Research Center, IRCCS Mondino Foundation, Pavia, Italy.
| | - Fabio Blandini
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy; Movement Disorders Research Center, IRCCS Mondino Foundation, Pavia, Italy
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19
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Choi GS, Yun JY, Hwang S, Kim SE, Kim JY, Im CH, Lee HW. Can Corticomuscular Coherence Differentiate between REM Sleep Behavior Disorder with or without Parkinsonism? J Clin Med 2021; 10:jcm10235585. [PMID: 34884285 PMCID: PMC8658120 DOI: 10.3390/jcm10235585] [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: 10/11/2021] [Revised: 11/21/2021] [Accepted: 11/23/2021] [Indexed: 11/16/2022] Open
Abstract
REM sleep behavior disorder (RBD) could be a predictor of Parkinsonism even before development of typical motor symptoms. This study aims to characterize clinical features and corticomuscular and corticocortical coherence (CMC and CCC, respectively) during sleep in RBD patients with or without Parkinsonism. We enrolled a total of 105 subjects, including 20 controls, 54 iRBD, and 31 RBD+P patients, patients who were diagnosed as idiopathic RBD (iRBD) and RBD with Parkinsonism (RBD+P) in our neurology department. We analyzed muscle atonia index (MAI) and CMC between EEG and chin/limb muscle electromyography (EMG) and CCC during different sleep stages. Although differences in the CMC of iRBD group were observed only during REM sleep, MAI differences between groups were noted during both REM and NREM N2 stage sleep. During REM sleep, CMC was higher and MAI was reduced in iRBD patients compared to controls (p = 0.001, p < 0.001, respectively). Interestingly, MAI was more reduced in RBD+P compared to iRBD patients. In comparison, CCC was higher in iRBD patients compared to controls whereas CCC was lower in RBD+P groups compared to control and iRBD groups in various frequency bands during both NREM N2 and REM sleep stages. Among them, increased CMC during REM sleep revealed correlation between clinical severities of RBD symptoms. Our findings indicate that MAI, CMC, and CCC showed distinctive features in iRBD and RBD+P patients compared to controls, suggesting potential usefulness to understand possible links between these diseases.
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Affiliation(s)
- Gyeong Seon Choi
- Department of Neurology, Ewha Womans University School of Medicine, Seoul 07985, Korea; (G.S.C.); (J.Y.Y.); (S.H.)
- Department of Neurology, Bundang Jesaeng General Hospital, Seongnam 13590, Korea
| | - Ji Young Yun
- Department of Neurology, Ewha Womans University School of Medicine, Seoul 07985, Korea; (G.S.C.); (J.Y.Y.); (S.H.)
- Department of Medical Science, Ewha Womans University School of Medicine, Seoul 07804, Korea;
| | - Sungeun Hwang
- Department of Neurology, Ewha Womans University School of Medicine, Seoul 07985, Korea; (G.S.C.); (J.Y.Y.); (S.H.)
| | - Song E. Kim
- Department of Medical Science, Ewha Womans University School of Medicine, Seoul 07804, Korea;
| | - Jeong-Yeon Kim
- Department of Biomedical Engineering, Hanyang University School of Engineering, Seoul 04763, Korea; (J.-Y.K.); (C.-H.I.)
| | - Chang-Hwan Im
- Department of Biomedical Engineering, Hanyang University School of Engineering, Seoul 04763, Korea; (J.-Y.K.); (C.-H.I.)
| | - Hyang Woon Lee
- Department of Neurology, Ewha Womans University School of Medicine, Seoul 07985, Korea; (G.S.C.); (J.Y.Y.); (S.H.)
- Department of Medical Science, Ewha Womans University School of Medicine, Seoul 07804, Korea;
- Computational Medicine, Graduate Program in System Health Science & Engineering, Ewha Womans University, Seoul 03765, Korea
- Correspondence: ; Tel.: +82-2-2650-2673
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20
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Sobczak A, Repplinger S, Bauch EM, Brueggemann N, Lohse C, Hinrichs H, Buentjen L, Voges J, Zaehle T, Bunzeck N. Anticipating social incentives recruits alpha-beta oscillations in the human substantia nigra and invigorates behavior across the life span. Neuroimage 2021; 245:118696. [PMID: 34732325 DOI: 10.1016/j.neuroimage.2021.118696] [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: 06/23/2021] [Revised: 10/22/2021] [Accepted: 10/29/2021] [Indexed: 11/19/2022] Open
Abstract
Anticipating social and non-social incentives recruits shared brain structures and promotes behavior. However, little is known about possible age-related behavioral changes, and how the human substantia nigra (SN) signals positive and negative social information. Therefore, we recorded intracranial electroencephalography (iEEG) from the SN of Parkinson's Disease (PD) patients (n = 12, intraoperative, OFF medication) in combination with a social incentive delay task including photos of neutral, positive or negative human gestures and mimics as feedback. We also tested a group of non-operated PD patients (n = 24, ON and OFF medication), and a sample of healthy young (n = 51) and older (n = 52) adults with behavioral readouts only. Behaviorally, the anticipation of both positive and negative social feedback equally accelerated response times in contrast to neutral social feedback in healthy young and older adults. Although this effect was not significant in the group of operated PD patients - most likely due to the small sample size - iEEG recordings in their SN showed a significant increase in alpha-beta power (9-20 Hz) from 300 to 600 ms after cue onset again for both positive and negative cues. Finally, in non-operated PD patients, the behavioral effect was not modulated by medication status (ON vs OFF medication) suggesting that other processes than dopaminergic neuromodulation play a role in driving invigoration by social incentives. Together, our findings provide novel and direct evidence for a role of the SN in processing positive and negative social information via specific oscillatory mechanisms in the alpha-beta range, and they suggest that anticipating social value in simple cue-outcome associations is intact in healthy aging and PD.
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Affiliation(s)
- Alexandra Sobczak
- Department of Psychology, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany.
| | - Stefan Repplinger
- Departments of Neurology and Stereotactic Neurosurgery, Otto-von-Guericke University, Leipziger Straße 44, Magdeburg 39120, Germany; International Graduate School ABINEP, Otto-von-Guericke-University, Leipziger Straße 44, Magdeburg 39120, Germany
| | - Eva M Bauch
- Department of Psychology, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany
| | - Norbert Brueggemann
- International Graduate School ABINEP, Otto-von-Guericke-University, Leipziger Straße 44, Magdeburg 39120, Germany; Department of Neurology, University Medical Center Schleswig-Holstein, Ratzeburger Allee 160, Lübeck 23562, Germany; Institute of Neurogenetics, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany; Center of Brain, Behavior and Metabolism, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany
| | - Christina Lohse
- Department of Neurology, University Medical Center Schleswig-Holstein, Ratzeburger Allee 160, Lübeck 23562, Germany
| | - Hermann Hinrichs
- Departments of Neurology and Stereotactic Neurosurgery, Otto-von-Guericke University, Leipziger Straße 44, Magdeburg 39120, Germany
| | - Lars Buentjen
- Departments of Neurology and Stereotactic Neurosurgery, Otto-von-Guericke University, Leipziger Straße 44, Magdeburg 39120, Germany
| | - Juergen Voges
- Departments of Neurology and Stereotactic Neurosurgery, Otto-von-Guericke University, Leipziger Straße 44, Magdeburg 39120, Germany
| | - Tino Zaehle
- Departments of Neurology and Stereotactic Neurosurgery, Otto-von-Guericke University, Leipziger Straße 44, Magdeburg 39120, Germany; Center for Behavioral Brain Sciences (CBBS), 39106, Magdeburg
| | - Nico Bunzeck
- Department of Psychology, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany; Center of Brain, Behavior and Metabolism, University of Lübeck, Ratzeburger Allee 160, Lübeck 23562, Germany.
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21
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Muthuraman M, Palotai M, Jávor-Duray B, Kelemen A, Koirala N, Halász L, Erőss L, Fekete G, Bognár L, Deuschl G, Tamás G. Frequency-specific network activity predicts bradykinesia severity in Parkinson's disease. Neuroimage Clin 2021; 32:102857. [PMID: 34662779 PMCID: PMC8526781 DOI: 10.1016/j.nicl.2021.102857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 09/15/2021] [Accepted: 10/12/2021] [Indexed: 11/18/2022]
Abstract
OBJECTIVE Bradykinesia has been associated with beta and gamma band interactions in the basal ganglia-thalamo-cortical circuit in Parkinson's disease. In this present cross-sectional study, we aimed to search for neural networks with electroencephalography whose frequency-specific actions may predict bradykinesia. METHODS Twenty Parkinsonian patients treated with bilateral subthalamic stimulation were first prescreened while we selected four levels of contralateral stimulation (0: OFF, 1-3: decreasing symptoms to ON state) individually, based on kinematics. In the screening period, we performed 64-channel electroencephalography measurements simultaneously with electromyography and motion detection during a resting state, finger tapping, hand grasping tasks, and pronation-supination of the arm, with the four levels of contralateral stimulation. We analyzed spectral power at the low (13-20 Hz) and high (21-30 Hz) beta frequency bands and low (31-60 Hz) and high (61-100 Hz) gamma frequency bands using the dynamic imaging of coherent sources. Structural equation modelling estimated causal relationships between the slope of changes in network beta and gamma activities and the slope of changes in bradykinesia measures. RESULTS Activity in different subnetworks, including predominantly the primary motor and premotor cortex, the subthalamic nucleus predicted the slopes in amplitude and speed while switching between stimulation levels. These subnetwork dynamics on their preferred frequencies predicted distinct types and parameters of the movement only on the contralateral side. DISCUSSION Concurrent subnetworks affected in bradykinesia and their activity changes in the different frequency bands are specific to the type and parameters of the movement; and the primary motor and premotor cortex are common nodes.
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Affiliation(s)
- Muthuraman Muthuraman
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany
| | - Marcell Palotai
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | | | - Andrea Kelemen
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Nabin Koirala
- Movement Disorders, Imaging and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Mainz, Germany; Haskins Laboratories, New Haven, USA
| | - László Halász
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Loránd Erőss
- National Institute of Clinical Neurosciences, Budapest, Hungary
| | - Gábor Fekete
- Department of Neurosurgery, University of Debrecen, Debrecen, Hungary
| | - László Bognár
- Department of Neurosurgery, University of Debrecen, Debrecen, Hungary
| | - Günther Deuschl
- Department of Neurology, Christian-Albrechts University, Kiel, Germany
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary.
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22
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Mottaghi S, Kohl S, Biemann D, Liebana S, Montaño Crespo RE, Buchholz O, Wilson M, Klaus C, Uchenik M, Münkel C, Schmidt R, Hofmann UG. Bilateral Intracranial Beta Activity During Forced and Spontaneous Movements in a 6-OHDA Hemi-PD Rat Model. Front Neurosci 2021; 15:700672. [PMID: 34456673 PMCID: PMC8397450 DOI: 10.3389/fnins.2021.700672] [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: 04/26/2021] [Accepted: 07/20/2021] [Indexed: 11/26/2022] Open
Abstract
Cortico-basal ganglia beta oscillations (13–30 Hz) are assumed to be involved in motor impairments in Parkinson’s Disease (PD), especially in bradykinesia and rigidity. Various studies have utilized the unilateral 6-hydroxydopamine (6-OHDA) rat PD model to further investigate PD and test novel treatments. However, a detailed behavioral and electrophysiological characterization of the model, including analyses of popular PD treatments such as DBS, has not been documented in the literature. We hence challenged the 6-OHDA rat hemi-PD model with a series of experiments (i.e., cylinder test, open field test, and rotarod test) aimed at assessing the motor impairments, analyzing the effects of Deep Brain Stimulation (DBS), and identifying under which conditions excessive beta oscillations occur. We found that 6-OHDA hemi-PD rats presented an impaired performance in all experiments compared to the sham group, and DBS could improve their overall performance. Across all the experiments and behaviors, the power in the high beta band was observed to be an important biomarker for PD as it showed differences between healthy and lesioned hemispheres and between 6-OHDA-lesioned and sham rats. This all shows that the 6-OHDA hemi-PD model accurately represents many of the motor and electrophysiological symptoms of PD and makes it a useful tool for the pre-clinical testing of new treatments when low β (13–21 Hz) and high β (21–30 Hz) frequency bands are considered separately.
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Affiliation(s)
- Soheil Mottaghi
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Technical Faculty, University of Freiburg, Freiburg, Germany
| | - Sandra Kohl
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Dirk Biemann
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Samuel Liebana
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom.,Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom
| | - Ruth Eneida Montaño Crespo
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Oliver Buchholz
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Mareike Wilson
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Carolin Klaus
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michelle Uchenik
- Biomedical Department, Faculty of Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Christian Münkel
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Robert Schmidt
- Department of Psychology, The University of Sheffield, Sheffield, United Kingdom
| | - Ulrich G Hofmann
- Neuroelectronic Systems, Department of Neurosurgery, Medical Center, University of Freiburg, Freiburg, Germany.,Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Technical Faculty, University of Freiburg, Freiburg, Germany
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23
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Sharma A, Vidaurre D, Vesper J, Schnitzler A, Florin E. Differential dopaminergic modulation of spontaneous cortico-subthalamic activity in Parkinson's disease. eLife 2021; 10:66057. [PMID: 34085932 PMCID: PMC8177893 DOI: 10.7554/elife.66057] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/12/2021] [Indexed: 11/20/2022] Open
Abstract
Pathological oscillations including elevated beta activity in the subthalamic nucleus (STN) and between STN and cortical areas are a hallmark of neural activity in Parkinson’s disease (PD). Oscillations also play an important role in normal physiological processes and serve distinct functional roles at different points in time. We characterised the effect of dopaminergic medication on oscillatory whole-brain networks in PD in a time-resolved manner by employing a hidden Markov model on combined STN local field potentials and magnetoencephalography (MEG) recordings from 17 PD patients. Dopaminergic medication led to coherence within the medial and orbitofrontal cortex in the delta/theta frequency range. This is in line with known side effects of dopamine treatment such as deteriorated executive functions in PD. In addition, dopamine caused the beta band activity to switch from an STN-mediated motor network to a frontoparietal-mediated one. In contrast, dopamine did not modify local STN–STN coherence in PD. STN–STN synchrony emerged both on and off medication. By providing electrophysiological evidence for the differential effects of dopaminergic medication on the discovered networks, our findings open further avenues for electrical and pharmacological interventions in PD.
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Affiliation(s)
- Abhinav Sharma
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Diego Vidaurre
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Department of Clinical Health, Aarhus University, Aarhus, Denmark
| | - Jan Vesper
- Department of Neurosurgery, University Hospital Düsseldorf, Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany.,Department of Neurology, Center for Movement Disorders and Neuromodulation, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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24
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Peña E, Mohammad TM, Almohammed F, AlOtaibi T, Nahrir S, Khan S, Poghosyan V, Johnson MD, Bajwa JA. Individual Magnetoencephalography Response Profiles to Short-Duration L-Dopa in Parkinson's Disease. Front Hum Neurosci 2021; 15:640591. [PMID: 33790752 PMCID: PMC8005574 DOI: 10.3389/fnhum.2021.640591] [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: 12/11/2020] [Accepted: 02/23/2021] [Indexed: 11/24/2022] Open
Abstract
Clinical responses to dopamine replacement therapy for individuals with Parkinson’s disease (PD) are often difficult to predict. We characterized changes in MDS-UPDRS motor factor scores resulting from a short-duration L-Dopa response (SDR), and investigated how the inter-subject clinical differences could be predicted from motor cortical magnetoencephalography (MEG). MDS-UPDRS motor factor scores and resting-state MEG recordings were collected during SDR from twenty individuals with a PD diagnosis. We used a novel subject-specific strategy based on linear support vector machines to quantify motor cortical oscillatory frequency profiles that best predicted medication state. Motor cortical profiles differed substantially across individuals and showed consistency across multiple data folds. There was a linear relationship between classification accuracy and SDR of lower limb bradykinesia, although this relationship did not persist after multiple comparison correction, suggesting that combinations of spectral power features alone are insufficient to predict clinical state. Factor score analysis of therapeutic response and novel subject-specific machine learning approaches based on subject-specific neuroimaging provide tools to predict outcomes of therapies for PD.
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Affiliation(s)
- Edgar Peña
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Tareq M Mohammad
- National Neuroscience Nursing Administration, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Fedaa Almohammed
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Tahani AlOtaibi
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Shahpar Nahrir
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Sheraz Khan
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Massachusetts Institute of Technology, Boston, MA, United States.,McGovern Institute for Brain Research, Massachusetts Institute of Technology (MIT), Cambridge, MA, United States
| | - Vahe Poghosyan
- Department of Neurophysiology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
| | - Matthew D Johnson
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, United States
| | - Jawad A Bajwa
- Department of Neurology, National Neuroscience Institute, King Fahad Medical City, Riyadh, Saudi Arabia
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25
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Boon LI, Potters WV, Zoon TJC, van den Heuvel OA, Prent N, de Bie RMA, Bot M, Schuurman PR, van den Munckhof P, Geurtsen GJ, Hillebrand A, Stam CJ, van Rootselaar AF, Berendse HW. Structural and functional correlates of subthalamic deep brain stimulation-induced apathy in Parkinson's disease. Brain Stimul 2020; 14:192-201. [PMID: 33385593 DOI: 10.1016/j.brs.2020.12.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 11/15/2020] [Accepted: 12/21/2020] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Notwithstanding the large improvement in motor function in Parkinson's disease (PD) patients treated with deep brain stimulation (DBS), apathy may increase. Postoperative apathy cannot always be related to a dose reduction of dopaminergic medication and stimulation itself may play a role. OBJECTIVE We studied whether apathy in DBS-treated PD patients could be a stimulation effect. METHODS In 26 PD patients we acquired apathy scores before and >6 months after DBS of the subthalamic nucleus (STN). Magnetoencephalography recordings (ON and OFF stimulation) were performed ≥6 months after DBS placement. Change in apathy severity was correlated with (i) improvement in motor function and dose reduction of dopaminergic medication, (ii) stimulation location (merged MRI and CT-scans) and (iii) stimulation-related changes in functional connectivity of brain regions that have an alleged role in apathy. RESULTS Average apathy severity significantly increased after DBS (p < 0.001) and the number of patients considered apathetic increased from two to nine. Change in apathy severity did not correlate with improvement in motor function or dose reduction of dopaminergic medication. For the left hemisphere, increase in apathy was associated with a more dorsolateral stimulation location (p = 0.010). The increase in apathy severity correlated with a decrease in alpha1 functional connectivity of the dorsolateral prefrontal cortex (p = 0.006), but not with changes of the medial orbitofrontal or the anterior cingulate cortex. CONCLUSIONS The present observations suggest that apathy after STN-DBS is not necessarily related to dose reductions of dopaminergic medication, but may be an effect of the stimulation itself. This highlights the importance of determining optimal DBS settings based on both motor and non-motor symptoms.
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Affiliation(s)
- Lennard I Boon
- Amsterdam UMC, Vrije Universiteit Amsterdam, Neurology, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Clinical Neurophysiology and Magnetoencephalography Centre, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands; Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands.
| | - Wouter V Potters
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Thomas J C Zoon
- Amsterdam UMC, University of Amsterdam, Psychiatry, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Odile A van den Heuvel
- Amsterdam UMC, Vrije Universiteit Amsterdam, Psychiatry, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Naomi Prent
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Rob M A de Bie
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Maarten Bot
- Amsterdam UMC, University of Amsterdam, Neurosurgery, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - P Richard Schuurman
- Amsterdam UMC, University of Amsterdam, Neurosurgery, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Pepijn van den Munckhof
- Amsterdam UMC, University of Amsterdam, Neurosurgery, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Gert J Geurtsen
- Amsterdam UMC, University of Amsterdam, Medical Psychology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Arjan Hillebrand
- Amsterdam UMC, Vrije Universiteit Amsterdam, Clinical Neurophysiology and Magnetoencephalography Centre, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Clinical Neurophysiology and Magnetoencephalography Centre, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands
| | - Anne-Fleur van Rootselaar
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Henk W Berendse
- Amsterdam UMC, Vrije Universiteit Amsterdam, Neurology, Amsterdam Neuroscience, De Boelelaan, 1117, Amsterdam, the Netherlands
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26
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Özkurt TE, Akram H, Zrinzo L, Limousin P, Foltynie T, Oswal A, Litvak V. Identification of nonlinear features in cortical and subcortical signals of Parkinson's Disease patients via a novel efficient measure. Neuroimage 2020; 223:117356. [PMID: 32916287 PMCID: PMC8417768 DOI: 10.1016/j.neuroimage.2020.117356] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 07/31/2020] [Accepted: 09/04/2020] [Indexed: 11/25/2022] Open
Abstract
This study offers a novel and efficient measure based on a higher order version of autocorrelative signal memory that can identify nonlinearities in a single time series. The suggested method was applied to simultaneously recorded subthalamic nucleus (STN) local field potentials (LFP) and magnetoencephalography (MEG) from fourteen Parkinson's Disease (PD) patients who underwent surgery for deep brain stimulation. Recordings were obtained during rest for both OFF and ON dopaminergic medication states. We analyzed the bilateral LFP channels that had the maximum beta power in the OFF state and the cortical sources that had the maximum coherence with the selected LFP channels in the alpha band. Our findings revealed the inherent nonlinearity in the PD data as subcortical high beta (20-30 Hz) band and cortical alpha (8-12 Hz) band activities. While the former was discernible without medication (p=0.015), the latter was induced upon the dopaminergic medication (p<6.10-4). The degree of subthalamic nonlinearity was correlated with contralateral tremor severity (r=0.45, p=0.02). Conversely, for the cortical signals nonlinearity was present for the ON medication state with a peak in the alpha band and correlated with contralateral akinesia and rigidity (r=0.46, p=0.02). This correlation appeared to be independent from that of alpha power and the two measures combined explained 34 % of the variance in contralateral akinesia scores. Our findings suggest that particular frequency bands and brain regions display nonlinear features closely associated with distinct motor symptoms and functions.
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Affiliation(s)
- Tolga Esat Özkurt
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK; Middle East Technical University, Department of Health Informatics, Graduate School of Informatics, Ankara, Turkey.
| | - Harith Akram
- Department of Clinical and Movement Neurosciences, UCL Institute of Neurology and The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Ludvic Zrinzo
- Department of Clinical and Movement Neurosciences, UCL Institute of Neurology and The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Patricia Limousin
- Department of Clinical and Movement Neurosciences, UCL Institute of Neurology and The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Tom Foltynie
- Department of Clinical and Movement Neurosciences, UCL Institute of Neurology and The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
| | - Ashwini Oswal
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK; Department of Clinical Neurology, John Radcliffe Hospital, Oxford, UK
| | - Vladimir Litvak
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK
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27
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Primary motor cortex in Parkinson's disease: Functional changes and opportunities for neurostimulation. Neurobiol Dis 2020; 147:105159. [PMID: 33152506 DOI: 10.1016/j.nbd.2020.105159] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/30/2020] [Accepted: 10/31/2020] [Indexed: 02/07/2023] Open
Abstract
Movement abnormalities of Parkinson's disease (PD) arise from disordered neural activity in multiple interconnected brain structures. The planning and execution of movement requires recruitment of a heterogeneous collection of pyramidal projection neurons in the primary motor cortex (M1). The neural representations of movement in M1 single-cell and field potential recordings are directly and indirectly influenced by the midbrain dopaminergic neurons that degenerate in PD. This review examines M1 functional alterations in PD as uncovered by electrophysiological recordings and neurostimulation studies in patients and experimental animal models. Dysfunction of the parkinsonian M1 depends on the severity and/or duration of dopamine-depletion and the species examined, and is expressed as alterations in movement-related firing dynamics; functional reorganisation of local circuits; and changes in field potential beta oscillations. Neurostimulation methods that modulate M1 activity directly (e.g., transcranial magnetic stimulation) or indirectly (subthalamic nucleus deep brain stimulation) improve motor function in PD patients, showing that targeted neuromodulation of M1 is a realistic therapy. We argue that the therapeutic profile of M1 neurostimulation is likely to be greatly enhanced with alternative technologies that permit cell-type specific control and incorporate feedback from electrophysiological biomarkers measured locally.
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28
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Horn A, Fox MD. Opportunities of connectomic neuromodulation. Neuroimage 2020; 221:117180. [PMID: 32702488 PMCID: PMC7847552 DOI: 10.1016/j.neuroimage.2020.117180] [Citation(s) in RCA: 89] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 06/12/2020] [Accepted: 07/16/2020] [Indexed: 12/14/2022] Open
Abstract
The process of altering neural activity - neuromodulation - has long been used to treat patients with brain disorders and answer scientific questions. Deep brain stimulation in particular has provided clinical benefit to over 150,000 patients. However, our understanding of how neuromodulation impacts the brain is evolving. Instead of focusing on the local impact at the stimulation site itself, we are considering the remote impact on brain regions connected to the stimulation site. Brain connectivity information derived from advanced magnetic resonance imaging data can be used to identify these connections and better understand clinical and behavioral effects of neuromodulation. In this article, we review studies combining neuromodulation and brain connectomics, highlighting opportunities where this approach may prove particularly valuable. We focus on deep brain stimulation, but show that the same principles can be applied to other forms of neuromodulation, such as transcranial magnetic stimulation and MRI-guided focused ultrasound. We outline future perspectives and provide testable hypotheses for future work.
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Affiliation(s)
- Andreas Horn
- Neurology Department, Movement Disorders and Neuromodulation Sectio Charité - University Medicine Berlin,, Charitéplatz 1, D-10117 Berlin, Germany.
| | - Michael D Fox
- Berenson-Allen Center for Non-invasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, United States; Martinos Center for Biomedical Imaging, Departments of Neurology and Radiology, Harvard Medical School and Massachusetts General Hospital, United States; Center for Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Harvard Medical School and Brigham and Women's Hospital, United States.
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Litvak V, Florin E, Tamás G, Groppa S, Muthuraman M. EEG and MEG primers for tracking DBS network effects. Neuroimage 2020; 224:117447. [PMID: 33059051 DOI: 10.1016/j.neuroimage.2020.117447] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 10/08/2020] [Accepted: 10/08/2020] [Indexed: 10/23/2022] Open
Abstract
Deep brain stimulation (DBS) is an effective treatment method for a range of neurological and psychiatric disorders. It involves implantation of stimulating electrodes in a precisely guided fashion into subcortical structures and, at a later stage, chronic stimulation of these structures with an implantable pulse generator. While the DBS surgery makes it possible to both record brain activity and stimulate parts of the brain that are difficult to reach with non-invasive techniques, electroencephalography (EEG) and magnetoencephalography (MEG) provide complementary information from other brain areas, which can be used to characterize brain networks targeted through DBS. This requires, however, the careful consideration of different types of artifacts in the data acquisition and the subsequent analyses. Here, we review both the technical issues associated with EEG/MEG recordings in DBS patients and the experimental findings to date. One major line of research is simultaneous recording of local field potentials (LFPs) from DBS targets and EEG/MEG. These studies revealed a set of cortico-subcortical coherent networks functioning at distinguishable physiological frequencies. Specific network responses were linked to clinical state, task or stimulation parameters. Another experimental approach is mapping of DBS-targeted networks in chronically implanted patients by recording EEG/MEG responses during stimulation. One can track responses evoked by single stimulation pulses or bursts as well as brain state shifts caused by DBS. These studies have the potential to provide biomarkers for network responses that can be adapted to guide stereotactic implantation or optimization of stimulation parameters. This is especially important for diseases where the clinical effect of DBS is delayed or develops slowly over time. The same biomarkers could also potentially be utilized for the online control of DBS network effects in the new generation of closed-loop stimulators that are currently entering clinical use. Through future studies, the use of network biomarkers may facilitate the integration of circuit physiology into clinical decision making.
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Affiliation(s)
- Vladimir Litvak
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, UK
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Gertrúd Tamás
- Department of Neurology, Semmelweis University, Budapest, Hungary
| | - Sergiu Groppa
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany
| | - Muthuraman Muthuraman
- Movement disorders and Neurostimulation, Biomedical Statistics and Multimodal Signal Processing Unit, Department of Neurology, University Medical Center of the Johannes Gutenberg University, Langenbeckstrasse 1, 55131 Mainz, Germany.
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Effect of Parkinson's disease and two therapeutic interventions on muscle activity during walking: a systematic review. NPJ PARKINSONS DISEASE 2020; 6:22. [PMID: 32964107 PMCID: PMC7481232 DOI: 10.1038/s41531-020-00119-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 07/09/2020] [Indexed: 12/26/2022]
Abstract
Gait deficits are a common feature of Parkinson’s disease (PD) and predictors of future motor and cognitive impairment. Understanding how muscle activity contributes to gait impairment and effects of therapeutic interventions on motor behaviour is crucial for identifying potential biomarkers and developing rehabilitation strategies. This article reviews sixteen studies that investigate the electromyographic (EMG) activity of lower limb muscles in people with PD during walking and reports on their quality. The weight of evidence establishing differences in motor activity between people with PD and healthy older adults (HOAs) is considered. Additionally, the effect of dopaminergic medication and deep brain stimulation (DBS) on modifying motor activity is assessed. Results indicated greater proximal and decreased distal activity of lower limb muscles during walking in individuals with PD compared to HOA. Dopaminergic medication was associated with increased distal lower limb muscle activity whereas subthalamic nucleus DBS increased activity of both proximal and distal lower limb muscles. Tibialis anterior was impacted most by the interventions. Quality of the studies was not strong, with a median score of 61%. Most studies investigated only distal muscles, involved small sample sizes, extracted limited EMG features and lacked rigorous signal processing. Few studies related changes in motor activity with functional gait measures. Understanding mechanisms underpinning gait impairment in PD is essential for development of personalised rehabilitative interventions. Recommendations for future studies include greater participant numbers, recording more functionally diverse muscles, applying multi-muscle analyses, and relating EMG to functional gait measures.
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Liu H, Temel Y, Boonstra J, Hescham S. The effect of fornix deep brain stimulation in brain diseases. Cell Mol Life Sci 2020; 77:3279-3291. [PMID: 31974655 PMCID: PMC7426306 DOI: 10.1007/s00018-020-03456-4] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 11/17/2019] [Accepted: 01/08/2020] [Indexed: 01/02/2023]
Abstract
Deep brain stimulation is used to alleviate symptoms of neurological and psychiatric disorders including Parkinson's disease, epilepsy, and obsessive-compulsive-disorder. Electrically stimulating limbic structures has been of great interest, and in particular, the region of the fornix. We conducted a systematic search for studies that reported clinical and preclinical outcomes of deep brain stimulation within the fornix up to July 2019. We identified 13 studies (7 clinical, 6 preclinical) that examined the effects of fornix stimulation in Alzheimer's disease (n = 9), traumatic brain injury (n = 2), Rett syndrome (n = 1), and temporal lobe epilepsy (n = 1). Overall, fornix stimulation can lead to decreased rates of cognitive decline (in humans), enhanced memory (in humans and animals), visuo-spatial memorization (in humans and animals), and improving verbal recollection (in humans). While the exact mechanisms of action are not completely understood, studies suggest fornix DBS to be involved with increased functional connectivity and neurotransmitter levels, as well as enhanced neuroplasticity.
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Affiliation(s)
- Huajie Liu
- Department of Neurosurgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
- European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands
| | - Yasin Temel
- Department of Neurosurgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
- European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands
| | - Jackson Boonstra
- Department of Neurosurgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands
- European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands
| | - Sarah Hescham
- Department of Neurosurgery, Maastricht University Medical Center, PO Box 5800, 6202 AZ, Maastricht, The Netherlands.
- European Graduate School of Neuroscience (EURON), Maastricht University, Maastricht, The Netherlands.
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Kandemir AL, Litvak V, Florin E. The comparative performance of DBS artefact rejection methods for MEG recordings. Neuroimage 2020; 219:117057. [PMID: 32540355 PMCID: PMC7443703 DOI: 10.1016/j.neuroimage.2020.117057] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Revised: 06/05/2020] [Accepted: 06/11/2020] [Indexed: 01/01/2023] Open
Abstract
Deep brain stimulation (DBS) can be a very efficient treatment option for movement disorders and psychiatric diseases. To better understand DBS mechanisms, brain activity can be recorded using magnetoencephalography (MEG) with the stimulator turned on. However, DBS produces large artefacts compromising MEG data quality due to both the applied current and the movement of wires connecting the stimulator with the electrode. To filter out these artefacts, several methods to suppress the DBS artefact have been proposed in the literature. A comparative study evaluating each method’s effectiveness, however, is missing so far. In this study, we evaluate the performance of four artefact rejection methods on MEG data from phantom recordings with DBS acquired with an Elekta Neuromag and a CTF system: (i) Hampel-filter, (ii) spectral signal space projection (S3P), (iii) independent component analysis with mutual information (ICA-MI), and (iv) temporal signal space separation (tSSS). In the sensor space, the largest increase in signal-to-noise (SNR) ratio was achieved by ICA-MI, while the best correspondence in terms of source activations was obtained by tSSS. LCMV beamforming alone was not sufficient to suppress the DBS-induced artefacts. Phantom MEG measurement with Elekta Neuromag and CTF MEG system with DBS. Systematic comparison of cleaning algorithms to remove DBS artefact from MEG data. Sensor level ICA-MI yielded the best results. Source level: tSSS provided the best correspondence to recording without DBS.
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Affiliation(s)
- Ahmet Levent Kandemir
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, 12 Queen Square, London, UK
| | - Esther Florin
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany.
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33
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Cao C, Li D, Zhan S, Zhang C, Sun B, Litvak V. L-dopa treatment increases oscillatory power in the motor cortex of Parkinson's disease patients. Neuroimage Clin 2020; 26:102255. [PMID: 32361482 PMCID: PMC7195547 DOI: 10.1016/j.nicl.2020.102255] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2019] [Revised: 03/06/2020] [Accepted: 03/23/2020] [Indexed: 10/26/2022]
Abstract
Parkinson's disease (PD) is a movement disorder caused by dopaminergic neurodegeneration. Levodopa (L-dopa) is an effective medication for alleviating motor symptoms in PD that has been shown previously to reduce subcortical beta (13-30 Hz) oscillations. How L-dopa influences oscillations in the motor cortex is unclear. In this study, 21 PD patients were recorded with magnetoencephalography (MEG) in L-dopa ON and OFF states. Oscillatory components of resting-state power spectra were compared between the two states and the significant effect was localized using beamforming. Unified Parkinson's Disease Rating Scale (UPDRS) III akinesia and rigidity sub-scores for the most affected hemibody were correlated with source power values for the contralateral hemisphere. An L-dopa-induced power increase was found over the central sensors significant in the 18-30 Hz range (F(1,20) > 14.8, PFWE corr < 0.05, cluster size inference with P = 0.001 cluster-forming threshold). Beamforming localization of this effect revealed distinct peaks at the bilateral sensorimotor cortex. A significant correlation between the magnitude of L-dopa induced 18-30 Hz oscillatory motor-cortical power increase and the degree of improvement in contralateral akinesia and rigidity was found (F(2, 19) = 4.9, pone-tailed = 0.02, R2 = 0.2). Power in the same range was also inversely correlated with combined akinesia and rigidity scores in the L-dopa OFF state (F(2, 19) = 9.2, ptwo-tailed = 0.007, R2 = 0.33) but not in the L-dopa ON state (F(2, 19) = 0.27, ptwo-tailed = 0.6, R2 = 0.01). These results suggest that the role of motor cortical beta oscillations in PD is distinct from that of subcortical beta.
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Affiliation(s)
- Chunyan Cao
- Department of Neurosurgery, Affiliated Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200025, China; Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Dianyou Li
- Department of Neurosurgery, Affiliated Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200025, China
| | - Shikun Zhan
- Department of Neurosurgery, Affiliated Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200025, China
| | - Chencheng Zhang
- Department of Neurosurgery, Affiliated Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200025, China
| | - Bomin Sun
- Department of Neurosurgery, Affiliated Ruijin Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, 200025, China.
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK.
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Boon LI, Hillebrand A, Potters WV, de Bie RMA, Prent N, Bot M, Schuurman PR, Stam CJ, van Rootselaar AF, Berendse HW. Motor effects of deep brain stimulation correlate with increased functional connectivity in Parkinson's disease: An MEG study. Neuroimage Clin 2020; 26:102225. [PMID: 32120294 PMCID: PMC7049661 DOI: 10.1016/j.nicl.2020.102225] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Revised: 01/27/2020] [Accepted: 02/20/2020] [Indexed: 11/06/2022]
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an established symptomatic treatment in Parkinson's disease, yet its mechanism of action is not fully understood. Locally in the STN, stimulation lowers beta band power, in parallel with symptom relief. Therefore, beta band oscillations are sometimes referred to as "anti-kinetic". However, in recent studies functional interactions have been observed beyond the STN, which we hypothesized to reflect clinical effects of DBS. Resting-state, whole-brain magnetoencephalography (MEG) recordings and assessments on motor function were obtained in 18 Parkinson's disease patients with bilateral STN-DBS, on and off stimulation. For each brain region, we estimated source-space spectral power and functional connectivity with the rest of the brain. Stimulation led to an increase in average peak frequency and a suppression of absolute band power (delta to low-beta band) in the sensorimotor cortices. Significant changes (decreases and increases) in low-beta band functional connectivity were observed upon stimulation. Improvement in bradykinesia/rigidity was significantly related to increases in alpha2 and low-beta band functional connectivity (of sensorimotor regions, the cortex as a whole, and subcortical regions). By contrast, tremor improvement did not correlate with changes in functional connectivity. Our results highlight the distributed effects of DBS on the resting-state brain and suggest that DBS-related improvements in rigidity and bradykinesia, but not tremor, may be mediated by an increase in alpha2 and low-beta functional connectivity. Beyond the local effects of DBS in and around the STN, functional connectivity changes in these frequency bands might therefore be considered as "pro-kinetic".
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Affiliation(s)
- Lennard I Boon
- Amsterdam UMC, Vrije Universiteit Amsterdam, Neurology, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands; Amsterdam UMC, Vrije Universiteit Amsterdam, Clinical Neurophysiology and Magnetoencephalography Centre, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands.
| | - Arjan Hillebrand
- Amsterdam UMC, Vrije Universiteit Amsterdam, Clinical Neurophysiology and Magnetoencephalography Centre, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Wouter V Potters
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Rob M A de Bie
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Naomi Prent
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Maarten Bot
- Amsterdam UMC, University of Amsterdam, Neurosurgery, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - P Richard Schuurman
- Amsterdam UMC, University of Amsterdam, Neurosurgery, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Cornelis J Stam
- Amsterdam UMC, Vrije Universiteit Amsterdam, Clinical Neurophysiology and Magnetoencephalography Centre, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Anne-Fleur van Rootselaar
- Amsterdam UMC, University of Amsterdam, Neurology and Clinical Neurophysiology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands
| | - Henk W Berendse
- Amsterdam UMC, Vrije Universiteit Amsterdam, Neurology, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, the Netherlands
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35
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Corticomuscular control of walking in older people and people with Parkinson's disease. Sci Rep 2020; 10:2980. [PMID: 32076045 PMCID: PMC7031238 DOI: 10.1038/s41598-020-59810-w] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 01/30/2020] [Indexed: 12/29/2022] Open
Abstract
Changes in human gait resulting from ageing or neurodegenerative diseases are multifactorial. Here we assess the effects of age and Parkinson’s disease (PD) on corticospinal activity recorded during treadmill and overground walking. Electroencephalography (EEG) from 10 electrodes and electromyography (EMG) from bilateral tibialis anterior muscles were acquired from 22 healthy young, 24 healthy older and 20 adults with PD. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence were assessed for EEG from bilateral sensorimotor cortices and EMG during the double-support phase of the gait cycle. CMC and EMG power at low beta frequencies (13–21 Hz) was significantly decreased in older and PD participants compared to young people, but there was no difference between older and PD groups. Older and PD participants spent shorter time in the swing phase than young individuals. These findings indicate age-related changes in the temporal coordination of gait. The decrease in low-beta CMC suggests reduced cortical input to spinal motor neurons in older people during the double-support phase. We also observed multiple changes in electrophysiological measures at low-gamma frequencies during treadmill compared to overground walking, indicating task-dependent differences in corticospinal locomotor control. These findings may be affected by artefacts and should be interpreted with caution.
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36
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Schneider L, Seeger V, Timmermann L, Florin E. Electrophysiological resting state networks of predominantly akinetic-rigid Parkinson patients: Effects of dopamine therapy. NEUROIMAGE-CLINICAL 2020; 25:102147. [PMID: 31954989 PMCID: PMC6965744 DOI: 10.1016/j.nicl.2019.102147] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 11/21/2019] [Accepted: 12/21/2019] [Indexed: 11/25/2022]
Abstract
Analysis of whole-brain frequency-specific resting state networks with EEG. Comparison of dopamine medication ON and OFF state in Parkinson patients. Parkinson patients show distinct frequency-specific network alterations. Motor network at beta frequencies is re-instated after dopamine medication.
Parkinson's disease (PD) causes both motor and non-motor symptoms, which can partially be reversed by dopamine therapy. These symptoms as well as the effect of dopamine may be explained by distinct alterations in whole-brain architecture. We used functional connectivity (FC) and in particular resting state network (RSN) analysis to identify such whole-brain alterations in a frequency-specific manner. In addition, we hypothesized that standard dopaminergic medication would have a normalizing effect on these whole brain alterations. We recorded resting-state EEGs of 19 PD patients in the medical OFF and ON states, and of 12 healthy age-matched controls. The PD patients were either of akinetic-rigid or mixed subtype. We extracted RSNs with independent component analysis in the source space for five frequency bands. Within the sensorimotor network (SMN) the supplementary motor area (SMA) showed decreased FC in the OFF state compared to healthy controls. This finding was reversed after dopamine administration. Furthermore, in the OFF state no stable SMN beta component could be identified. The default mode network showed alterations due to PD independent of the medication state. The visual network was altered in the OFF state, and reinstated to a pattern similar to healthy controls by medication. In conclusion, PD causes distinct RSN alterations, which are partly reversed after levodopa administration. The changes within the SMN are of particular interest, because they broaden the pathophysiological understanding of PD. Our results identify the SMA as a central network hub affected in PD and a crucial effector of dopamine therapy.
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Affiliation(s)
- Lukas Schneider
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany
| | - Valentin Seeger
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany; Department of Neurology, University Hospital Marburg, Baldingerstrasse, 35043 Marburg, Germany
| | - Esther Florin
- Department of Neurology, University Hospital Cologne, Kerpener Strasse 62, 50937 Köln, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University Düsseldorf, Universitätsstr. 1, 40225 Düsseldorf, Germany.
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37
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Xiao R, Malekmohammadi M, Pouratian N, Hu X. Characterization of pallidocortical motor network in Parkinson's disease through complex network analysis. J Neural Eng 2019; 16:066034. [PMID: 31505469 DOI: 10.1088/1741-2552/ab4341] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) has been demonstrated by numerous clinical trials to be an advanced therapy for selected patients with Parkinson's disease (PD), while its maximal therapeutic effect is capped by the inadequate understanding of the precise neuronal mechanisms underlying PD. Recordings from multichannel electrodes placed in subcortical and cortical regions of the basal ganglia-thalamocortical (BGTC) motor network during DBS surgical procedures can provide rich physiologic information from accessible network nodes. However, most investigations focus on presumed spatio-spectral points of interest, neither fully utilizing the richness of spatial, spectral and temporal aspects of the multivariate signals nor making discoveries in the context of all possible candidates. In addition, aggregated network-level information has been missed out. APPROACH We use complex network analysis to characterize functional network characteristics of the pallidocortical subcircuit of the BGTC motor network in PD at rest and with movement. The network matrix was constructed using distinct frequency bands at each anatomic recording site as virtual nodes and spectral connectivity (through phase-amplitude coupling and coherence) as network edges. MAIN RESULTS We confirm the critical roles of beta bands and provide additional evidence on their differential functional roles in the pallidocortical motor network. Moreover, significant changes (p < 0.05) in network functional segregation and integration between rest and movement conditions are revealed for the first time. More importantly, movement-dependent modulation of these network metrics are significantly correlated with hemibody unified PD rating scales (UPDRS), providing network-level perspectives of the pallidocortical motor network pertaining to PD symptoms (p < 0.05). SIGNIFICANCE Findings in the present study provide network-level understanding of neuronal mechanisms in the pallidocortical motor network underlying PD. It is also highly plausible that the demonstrated approach can be applied in other important subcircuits towards a comprehensive understanding of the BGTC motor network.
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Affiliation(s)
- Ran Xiao
- Department of Physiological Nursing, University of California, San Francisco, CA, United States of America
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38
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Ramirez Pasos UE, Steigerwald F, Reich MM, Matthies C, Volkmann J, Reese R. Levodopa Modulates Functional Connectivity in the Upper Beta Band Between Subthalamic Nucleus and Muscle Activity in Tonic and Phasic Motor Activity Patterns in Parkinson's Disease. Front Hum Neurosci 2019; 13:223. [PMID: 31312129 PMCID: PMC6614179 DOI: 10.3389/fnhum.2019.00223] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 06/18/2019] [Indexed: 01/10/2023] Open
Abstract
Introduction: Striatal dopamine depletion disrupts basal ganglia function and causes Parkinson's disease (PD). The pathophysiology of the dopamine-dependent relationship between basal ganglia signaling and motor control, however, is not fully understood. We obtained simultaneous recordings of local field potentials (LFPs) from the subthalamic nucleus (STN) and electromyograms (EMGs) in patients with PD to investigate the impact of dopaminergic state and movement on long-range beta functional connectivity between basal ganglia and lower motor neurons. Methods: Eight PD patients were investigated 3 months after implantation of a deep brain stimulation (DBS)-system capable of recording LFPs via chronically-implanted leads (Medtronic, ACTIVA PC+S®). We analyzed STN spectral power and its coherence with EMG in the context of two different movement paradigms (tonic wrist extension vs. alternating wrist extension and flexion) and the effect of levodopa (L-Dopa) intake using an unbiased data-driven approach to determine regions of interest (ROI). Results: Two ROIs capturing prominent coherence within a grand average coherogram were identified. A trend of a dopamine effect was observed for the first ROI (50-150 ms after movement start) with higher STN-EMG coherence in medicated patients. Concerning the second ROI (300-500 ms after movement start), an interaction effect of L-Dopa medication and movement task was observed with higher coherence in the isometric contraction task compared to alternating movements in the medication ON state, a pattern which was reversed in L-Dopa OFF. Discussion: L-Dopa medication may normalize functional connectivity between remote structures of the motor system with increased upper beta coherence reflecting a physiological restriction of the amount of information conveyed between remote structures. This may be necessary to maintain simple movements like isometric contraction. Our study adds dynamic properties to the complex interplay between STN spectral beta power and the nucleus' functional connectivity to remote structures of the motor system as a function of movement and dopaminergic state. This may help to identify markers of neuronal activity relevant for more individualized programming of DBS therapy.
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Affiliation(s)
| | - Frank Steigerwald
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Martin M Reich
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Cordula Matthies
- Department of Neurosurgery, University Hospital Würzburg, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - René Reese
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany.,Department of Neurology, University of Rostock, Rostock, Germany
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39
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Evangelisti S, Pittau F, Testa C, Rizzo G, Gramegna LL, Ferri L, Coito A, Cortelli P, Calandra-Buonaura G, Bisquoli F, Bianchini C, Manners DN, Talozzi L, Tonon C, Lodi R, Tinuper P. L-Dopa Modulation of Brain Connectivity in Parkinson's Disease Patients: A Pilot EEG-fMRI Study. Front Neurosci 2019; 13:611. [PMID: 31258465 PMCID: PMC6587436 DOI: 10.3389/fnins.2019.00611] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Accepted: 05/28/2019] [Indexed: 01/08/2023] Open
Abstract
Studies of functional neurosurgery and electroencephalography in Parkinson's disease have demonstrated abnormally synchronous activity between basal ganglia and motor cortex. Functional neuroimaging studies investigated brain dysfunction during motor task or resting state and primarily have shown altered patterns of activation and connectivity for motor areas. L-dopa administration relatively normalized these functional alterations. The aim of this pilot study was to examine the effects of L-dopa administration on functional connectivity in early-stage PD, as revealed by simultaneous recording of functional magnetic resonance imaging (fMRI) and electroencephalographic (EEG) data. Six patients with diagnosis of probable PD underwent EEG-fMRI acquisitions (1.5 T MR scanner and 64-channel cap) before and immediately after the intake of L-dopa. Regions of interest in the primary motor and sensorimotor regions were used for resting state fMRI analysis. From the EEG data, weighted partial directed coherence was computed in the inverse space after the removal of gradient and cardioballistic artifacts. fMRI results showed that the intake of L-dopa increased functional connectivity within the sensorimotor network, and between motor areas and both attention and default mode networks. EEG connectivity among regions of the motor network did not change significantly, while regions of the default mode network showed a strong tendency to increase their outflow toward the rest of the brain. This pilot study provided a first insight into the potentiality of simultaneous EEG-fMRI acquisitions in PD patients, showing for both techniques the analogous direction of increased connectivity after L-dopa intake, mainly involving motor, dorsal attention and default mode networks.
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Affiliation(s)
- Stefania Evangelisti
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
| | - Francesca Pittau
- EEG and Epilepsy Unit, Geneva University Hospitals, Geneva, Switzerland
| | - Claudia Testa
- Department of Physics and Astronomy, University of Bologna, Bologna, Italy
| | - Giovanni Rizzo
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Laura Ludovica Gramegna
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Lorenzo Ferri
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
| | - Ana Coito
- Functional Brain Mapping Lab, Department of Fundamental Neurosciences, University of Geneva, Geneva, Switzerland
| | - Pietro Cortelli
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Giovanna Calandra-Buonaura
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Fabio Bisquoli
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Claudio Bianchini
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
| | - David Neil Manners
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
| | - Lia Talozzi
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy
| | - Caterina Tonon
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Raffaele Lodi
- Functional MR Unit, Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Paolo Tinuper
- Department of Biomedical and NeuroMotor Sciences, University of Bologna, Bologna, Italy.,IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
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40
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Direct comparison of oscillatory activity in the motor system of Parkinson’s disease and dystonia: A review of the literature and meta-analysis. Clin Neurophysiol 2019; 130:917-924. [DOI: 10.1016/j.clinph.2019.02.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 01/29/2019] [Accepted: 02/16/2019] [Indexed: 12/12/2022]
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41
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Cao C, Huang P, Wang T, Zhan S, Liu W, Pan Y, Wu Y, Li H, Sun B, Li D, Litvak V. Cortico-subthalamic Coherence in a Patient With Dystonia Induced by Chorea-Acanthocytosis: A Case Report. Front Hum Neurosci 2019; 13:163. [PMID: 31191273 PMCID: PMC6548057 DOI: 10.3389/fnhum.2019.00163] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Accepted: 05/03/2019] [Indexed: 02/01/2023] Open
Abstract
The subthalamic nucleus (STN) is a common target for deep brain stimulation (DBS) treatment in Parkinson's disease (PD) but much less frequently targeted for other disorders. Here we report the results of simultaneous local field potential (LFP) recordings and magnetoencephalography (MEG) in a single patient who was implanted bilaterally in the STN for the treatment of dystonia induced by chorea-acanthocytosis. Consistent with the previous results in PD, the dystonia patient showed significant subthalamo-cortical coherence in the high beta band (28-35 Hz) on both sides localized to the mesial sensorimotor areas. In addition, on the right side, significant coherence was found in the theta-alpha band (4-12 Hz) that localized to the medial prefrontal cortex with the peak in the anterior cingulate gyrus. Comparison of STN power spectra with a previously reported PD cohort showed increased power in the theta and alpha bands and decreased power in the low beta band in dystonia which is consistent with most of the previous studies. The present report extends the range of disorders for which cortico-subthalamic oscillatory connectivity has been characterized. Our results strengthen the evidence that at least some of the subthalamo-cortical oscillatory coherent networks are a feature of the healthy brain, although we do not rule out that coherence magnitude could be affected by disease.
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Affiliation(s)
- Chunyan Cao
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Peng Huang
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Tao Wang
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Shikun Zhan
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Wei Liu
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Yixin Pan
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Yiwen Wu
- Department of Neurology, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Hongxia Li
- Department of Neurology, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Bomin Sun
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Dianyou Li
- Department of Functional Neurosurgery, Affiliated Ruijin Hospital, School of Medicine, Shanghai JiaoTong University, Shanghai, China
| | - Vladimir Litvak
- Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, United Kingdom
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42
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Boon LI, Geraedts VJ, Hillebrand A, Tannemaat MR, Contarino MF, Stam CJ, Berendse HW. A systematic review of MEG-based studies in Parkinson's disease: The motor system and beyond. Hum Brain Mapp 2019; 40:2827-2848. [PMID: 30843285 PMCID: PMC6594068 DOI: 10.1002/hbm.24562] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 01/27/2019] [Accepted: 02/13/2019] [Indexed: 01/29/2023] Open
Abstract
Parkinson's disease (PD) is accompanied by functional changes throughout the brain, including changes in the electromagnetic activity recorded with magnetoencephalography (MEG). An integrated overview of these changes, its relationship with clinical symptoms, and the influence of treatment is currently missing. Therefore, we systematically reviewed the MEG studies that have examined oscillatory activity and functional connectivity in the PD‐affected brain. The available articles could be separated into motor network‐focused and whole‐brain focused studies. Motor network studies revealed PD‐related changes in beta band (13–30 Hz) neurophysiological activity within and between several of its components, although it remains elusive to what extent these changes underlie clinical motor symptoms. In whole‐brain studies PD‐related oscillatory slowing and decrease in functional connectivity correlated with cognitive decline and less strongly with other markers of disease progression. Both approaches offer a different perspective on PD‐specific disease mechanisms and could therefore complement each other. Combining the merits of both approaches will improve the setup and interpretation of future studies, which is essential for a better understanding of the disease process itself and the pathophysiological mechanisms underlying specific PD symptoms, as well as for the potential to use MEG in clinical care.
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Affiliation(s)
- Lennard I Boon
- Amsterdam UMC, location VUmc, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Victor J Geraedts
- Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands.,Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Arjan Hillebrand
- Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Martijn R Tannemaat
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands
| | - Maria Fiorella Contarino
- Department of Neurology, Leiden University Medical Center, Leiden, the Netherlands.,Department of Neurology, Haga Teaching Hospital, The Hague, The Netherlands
| | - Cornelis J Stam
- Amsterdam UMC, location VUmc, Department of Clinical Neurophysiology and Magnetoencephalography Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Henk W Berendse
- Amsterdam UMC, location VUmc, Department of Neurology, Amsterdam Neuroscience, Amsterdam, the Netherlands
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43
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Müller EJ, Robinson PA. Suppression of Parkinsonian Beta Oscillations by Deep Brain Stimulation: Determination of Effective Protocols. Front Comput Neurosci 2018; 12:98. [PMID: 30618692 PMCID: PMC6297248 DOI: 10.3389/fncom.2018.00098] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2018] [Accepted: 11/26/2018] [Indexed: 01/05/2023] Open
Abstract
A neural field model of the corticothalamic-basal ganglia system is developed that describes enhanced beta activity within subthalamic and pallidal circuits in Parkinson's disease (PD) via system resonances. A model of deep brain stimulation (DBS) of typical clinical targets, the subthalamic nucleus (STN) and globus pallidus internus (GPi), is added and studied for several distinct stimulation protocols that are used for treatment of the motor symptoms of PD and that reduce pathological beta band activity (13-30 Hz) in the corticothalamic-basal ganglia network. The resulting impact of DBS on enhanced beta activity in the STN and GPi, as well as cortico-subthalamic and cortico-pallidal coherence, are studied. Both STN-DBS and GPi-DBS are found to be effective for suppressing peak STN and GPi power in the beta band, with GPi-DBS being slightly more effective in both the STN and the GPi for all stimulus protocols tested. The largest decrease in cortico-STN coherence is observed during STN-DBS, whereas GPi-DBS is most effective for reducing cortico-GPi coherence. A reduction of the pathologically large STN connection strengths that define the parkinsonian state results in enhanced 6 Hz activity and could thus represent a compensatory mechanism that has the side effect of driving parkinsonian tremor-like oscillations. This model provides a method for systematically testing effective DBS protocols that agrees with experimental and clinical findings. Furthermore, the model suggests GPi-DBS and STN-DBS have distinct impacts on elevated synchronization between the basal ganglia and motor cortex in PD.
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Affiliation(s)
- Eli J Müller
- School of Physics, The University of Sydney, Sydney, NSW, Australia.,Center for Integrative Brain Function, The University of Sydney, Sydney, NSW, Australia
| | - Peter A Robinson
- School of Physics, The University of Sydney, Sydney, NSW, Australia.,Center for Integrative Brain Function, The University of Sydney, Sydney, NSW, Australia
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44
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Malekmohammadi M, Shahriari Y, AuYong N, O’Keeffe A, Bordelon Y, Hu X, Pouratian N. Pallidal stimulation in Parkinson disease differentially modulates local and network β activity. J Neural Eng 2018; 15:056016. [PMID: 29972146 PMCID: PMC6125208 DOI: 10.1088/1741-2552/aad0fb] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
β hypersynchrony within the basal ganglia-thalamocortical (BGTC) network has been suggested as a hallmark of Parkinson disease (PD) pathophysiology. Subthalamic nucleus (STN)-DBS has been shown to alter cortical-subcortical synchronization. It is unclear whether this is a generalizable phenomenon of therapeutic stimulation across targets. OBJECTIVES We aimed to evaluate whether DBS of the globus pallidus internus (GPi) results in cortical-subcortical desynchronization, despite the lack of monosynaptic connections between GPi and sensorimotor cortex. APPROACH We recorded local field potentials from the GPi and electrocorticographic signals from the ipsilateral sensorimotor cortex, off medications in nine PD patients, undergoing DBS implantation. We analyzed both local oscillatory power and functional connectivity (coherence and debiased weighted phase lag index (dWPLI)) with and without stimulation while subjects were resting with eyes open. MAIN RESULTS DBS significantly suppressed low β power within the GPi (-26.98% ± 15.14%), p < 0.05) without modulation of sensorimotor cortical β power (low or high). In contrast, stimulation suppressed pallidocortical high β coherence (-38.89% ± 6.19%, p = 0.02) and dWPLI (-61.40% ± 8.75%, p = 0.02). Changes in cortical-subcortical functional connectivity were spatially specific to the motor cortex. SIGNIFICANCE We highlight the role of DBS in desynchronizing network activity, particularly in the high β band. The current study of GPi-DBS suggests these network-level effects are not necessarily dependent and potentially may be independent of the hyperdirect pathway. Importantly, these results draw a sharp distinction between the potential significance of low β oscillations locally within the basal ganglia and high β oscillations across the BGTC motor circuit.
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Affiliation(s)
| | - Yalda Shahriari
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, RI, USA
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
| | - Nicholas AuYong
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Andrew O’Keeffe
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
| | - Yvette Bordelon
- Department of Neurology, University of California, Los Angeles, CA, USA
| | - Xiao Hu
- Department of Physiological Nursing, University of California, San Francisco, CA, USA
| | - Nader Pouratian
- Department of Neurosurgery, University of California, Los Angeles, CA, USA
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45
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Cheng FY, Yang YR, Wu YR, Lu CF, Cheng SJ, Wang RY. Beta event-related desynchronization can be enhanced by different training programs and is correlated with improved postural control in individuals with Parkinson's disease. IEEE Trans Neural Syst Rehabil Eng 2018; 26:1957-1964. [PMID: 30183638 DOI: 10.1109/tnsre.2018.2868140] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
BACKGROUND AND OBJECTIVE The purpose of this study was to investigate the effects of a specific exercise (SE) training program focusing on balance and muscle strengthening and a turning-based treadmill (TT) training program on cortical desynchronization and postural control in Parkinson's disease (PD). METHODS Eighteen patients with PD were recruited and randomly assigned to the SE group, TT training group or control exercise (CE) group and participated in 12 30-min training sessions focusing on balance and strengthening, turning-based treadmill training, or general exercise training, respectively, followed by 10 minutes of over-ground walking in each session for 4 to 6 weeks. The outcomes included alpha event-related desynchronization (ERD), beta ERD, postural control ability indicated by postural instability and gait disorder (PIGD), the step/quick turn test (SQT), and the sensory organization test (SOT). All measurements were assessed at baseline and after training. RESULTS The results (n=6 for each group) showed that both the SE and TT groups had improved beta ERD, but not alpha ERD, in the Cz area, PIGD score, and turn sway/time in the SQT compared with the CE group. Furthermore, postural control ability was positively correlated with beta ERD in the Cz area. However, there was no significant correlation between SOT total score and alpha ERD in the Cz area. CONCLUSIONS This study showed that beta ERD in the central area and postural control can be improved with balance training, along with lower extremity muscle strengthening exercise and turning-based treadmill training, in patients with PD. Furthermore, improvement in beta ERD in the central area correlated with improvements in postural control ability. This trial was registered at http://www.anzctr.org.au/ (ACTRN12616000198426).
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46
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Hari R, Baillet S, Barnes G, Burgess R, Forss N, Gross J, Hämäläinen M, Jensen O, Kakigi R, Mauguière F, Nakasato N, Puce A, Romani GL, Schnitzler A, Taulu S. IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG). Clin Neurophysiol 2018; 129:1720-1747. [PMID: 29724661 PMCID: PMC6045462 DOI: 10.1016/j.clinph.2018.03.042] [Citation(s) in RCA: 84] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2017] [Revised: 03/18/2018] [Accepted: 03/24/2018] [Indexed: 12/22/2022]
Abstract
Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG.
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Affiliation(s)
- Riitta Hari
- Department of Art, Aalto University, Helsinki, Finland.
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Gareth Barnes
- Wellcome Centre for Human Neuroimaging, University College of London, London, UK
| | - Richard Burgess
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Nina Forss
- Clinical Neuroscience, Neurology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Joachim Gross
- Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow, UK; Institute for Biomagnetism and Biosignalanalysis, University of Muenster, Germany
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Ole Jensen
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Ryusuke Kakigi
- Department of Integrative Physiology, National Institute of Physiological Sciences, Okazaki, Japan
| | - François Mauguière
- Department of Functional Neurology and Epileptology, Neurological Hospital & University of Lyon, Lyon, France
| | | | - Aina Puce
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Gian-Luca Romani
- Department of Neuroscience, Imaging and Clinical Sciences, Università degli Studi G. D'Annunzio, Chieti, Italy
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, and Department of Neurology, Heinrich-Heine-University, Düsseldorf, Germany
| | - Samu Taulu
- Institute for Learning & Brain Sciences, University of Washington, Seattle, WA, USA; Department of Physics, University of Washington, Seattle, WA, USA
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47
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Luoma J, Pekkonen E, Airaksinen K, Helle L, Nurminen J, Taulu S, Mäkelä JP. Spontaneous sensorimotor cortical activity is suppressed by deep brain stimulation in patients with advanced Parkinson's disease. Neurosci Lett 2018; 683:48-53. [PMID: 29940326 DOI: 10.1016/j.neulet.2018.06.041] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 06/20/2018] [Accepted: 06/21/2018] [Indexed: 11/17/2022]
Abstract
Advanced Parkinson's disease (PD) is characterized by an excessive oscillatory beta band activity in the subthalamic nucleus (STN). Deep brain stimulation (DBS) of STN alleviates motor symptoms in PD and suppresses the STN beta band activity. The effect of DBS on cortical sensorimotor activity is more ambiguous; both increases and decreases of beta band activity have been reported. Non-invasive studies with simultaneous DBS are problematic due to DBS-induced artifacts. We recorded magnetoencephalography (MEG) from 16 advanced PD patients with and without STN DBS during rest and wrist extension. The strong magnetic artifacts related to stimulation were removed by temporal signal space separation. MEG oscillatory activity at 5-25 Hz was suppressed during DBS in a widespread frontoparietal region, including the sensorimotor cortex identified by the cortico-muscular coherence. The strength of suppression did not correlate with clinical improvement. Our results indicate that alpha and beta band oscillations are suppressed at the frontoparietal cortex by STN DBS in PD.
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Affiliation(s)
- Jarkko Luoma
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
| | - Eero Pekkonen
- Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Helsinki, Finland
| | - Katja Airaksinen
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland; Department of Neurology, Helsinki University Hospital and Department of Clinical Neurosciences (Neurology), University of Helsinki, Helsinki, Finland
| | - Liisa Helle
- Elekta Oy, Helsinki, Finland; Department of Neuroscience and Biomedical Engineering, Aalto University School of Science, Espoo, Finland
| | - Jussi Nurminen
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland
| | - Samu Taulu
- Institute for Learning & Brain Sciences, University of Washington, Seattle, USA; Department of Physics, University of Washington, Seattle, USA
| | - Jyrki P Mäkelä
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki and Helsinki University Hospital, Finland.
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48
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Harmsen IE, Rowland NC, Wennberg RA, Lozano AM. Characterizing the effects of deep brain stimulation with magnetoencephalography: A review. Brain Stimul 2018; 11:481-491. [PMID: 29331287 DOI: 10.1016/j.brs.2017.12.016] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2017] [Revised: 12/26/2017] [Accepted: 12/28/2017] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) is an important form of neuromodulation that is being applied to patients with motor, mood, or cognitive circuit disorders. Despite the efficacy and widespread use of DBS, the precise mechanisms by which it works remain unknown. Over the last decade, magnetoencephalography (MEG) has become an important functional neuroimaging technique used to study DBS. OBJECTIVE This review summarizes the literature related to the use of MEG to characterize the effects of DBS. METHODS Peer reviewed literature on DBS-MEG was obtained by searching the publicly accessible literature databases available on PubMed. The abstracts of all reports were scanned and publications which combined DBS-MEG in human subjects were selected for review. RESULTS A total of 32 publications met the selection criteria, and included studies which applied DBS for Parkinson's disease, dystonia, chronic pain, phantom limb pain, cluster headache, and epilepsy. DBS-MEG studies provided valuable insights into network connectivity, pathological coupling, and the modulatory effects of DBS. CONCLUSIONS As DBS-MEG research continues to develop, we can expect to gain a better understanding of diverse pathophysiological networks and their response to DBS. This knowledge will improve treatment efficacy, reduce side-effects, reveal optimal surgical targets, and advance the development of closed-loop neuromodulation.
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Affiliation(s)
- Irene E Harmsen
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada; Toronto Western Research Institute, Krembil Discovery Tower, University Health Network, Toronto, Ontario, Canada.
| | - Nathan C Rowland
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, USA
| | - Richard A Wennberg
- Mitchell Goldhar Magnetoencephalography Unit, Krembil Neuroscience Centre, Toronto Western Hospital, Toronto, Ontario, Canada; Division of Neurology, Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Ontario, Canada; Toronto Western Research Institute, Krembil Discovery Tower, University Health Network, Toronto, Ontario, Canada
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49
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Yang Y, Dewald JPA, van der Helm FCT, Schouten AC. Unveiling neural coupling within the sensorimotor system: directionality and nonlinearity. Eur J Neurosci 2017; 48:2407-2415. [PMID: 28887885 PMCID: PMC6221113 DOI: 10.1111/ejn.13692] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2017] [Revised: 08/18/2017] [Accepted: 09/05/2017] [Indexed: 01/09/2023]
Abstract
Neural coupling between the central nervous system and the periphery is essential for the neural control of movement. Corticomuscular coherence is a popular linear technique to assess synchronised oscillatory activity in the sensorimotor system. This oscillatory coupling originates from ascending somatosensory feedback and descending motor commands. However, corticomuscular coherence cannot separate this bidirectionality. Furthermore, the sensorimotor system is nonlinear, resulting in cross‐frequency coupling. Cross‐frequency oscillations cannot be assessed nor exploited by linear measures. Here, we emphasise the need of novel coupling measures, which provide directionality and acknowledge nonlinearity, to unveil neural coupling in the sensorimotor system. We highlight recent advances in the field and argue that assessing directionality and nonlinearity of neural coupling will break new ground in the study of the control of movement in healthy and neurologically impaired individuals.
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Affiliation(s)
- Yuan Yang
- Neuromuscular Control Laboratory, Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands.,Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Julius P A Dewald
- Neuromuscular Control Laboratory, Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands.,Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.,Department of Biomedical Engineering, McCormick school of Engineering, Northwestern University, Evanston, IL, USA
| | - Frans C T van der Helm
- Neuromuscular Control Laboratory, Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands.,Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA
| | - Alfred C Schouten
- Neuromuscular Control Laboratory, Department of Biomechanical Engineering, Delft University of Technology, Delft, The Netherlands.,Department of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, 60611, USA.,MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands
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50
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Hirschmann J, Schoffelen JM, Schnitzler A, van Gerven MAJ. Parkinsonian rest tremor can be detected accurately based on neuronal oscillations recorded from the subthalamic nucleus. Clin Neurophysiol 2017; 128:2029-2036. [PMID: 28841506 DOI: 10.1016/j.clinph.2017.07.419] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Revised: 05/23/2017] [Accepted: 07/25/2017] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To investigate the possibility of tremor detection based on deep brain activity. METHODS We re-analyzed recordings of local field potentials (LFPs) from the subthalamic nucleus in 10 PD patients (12 body sides) with spontaneously fluctuating rest tremor. Power in several frequency bands was estimated and used as input to Hidden Markov Models (HMMs) which classified short data segments as either tremor-free rest or rest tremor. HMMs were compared to direct threshold application to individual power features. RESULTS Applying a threshold directly to band-limited power was insufficient for tremor detection (mean area under the curve [AUC] of receiver operating characteristic: 0.64, STD: 0.19). Multi-feature HMMs, in contrast, allowed for accurate detection (mean AUC: 0.82, STD: 0.15), using four power features obtained from a single contact pair. Within-patient training yielded better accuracy than across-patient training (0.84vs. 0.78, p=0.03), yet tremor could often be detected accurately with either approach. High frequency oscillations (>200Hz) were the best performing individual feature. CONCLUSIONS LFP-based markers of tremor are robust enough to allow for accurate tremor detection in short data segments, provided that appropriate statistical models are used. SIGNIFICANCE LFP-based markers of tremor could be useful control signals for closed-loop deep brain stimulation.
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Affiliation(s)
- J Hirschmann
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Germany.
| | - J M Schoffelen
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
| | - A Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Germany; Center for Movement Disorders and Neuromodulation, Medical Faculty, University Hospital Düsseldorf, Germany
| | - M A J van Gerven
- Radboud University, Donders Institute for Brain, Cognition and Behaviour, Nijmegen, The Netherlands
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