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Chu HY, Smith Y, Lytton WW, Grafton S, Villalba R, Masilamoni G, Wichmann T. Dysfunction of motor cortices in Parkinson's disease. Cereb Cortex 2024; 34:bhae294. [PMID: 39066504 PMCID: PMC11281850 DOI: 10.1093/cercor/bhae294] [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: 02/18/2024] [Revised: 06/26/2024] [Accepted: 07/19/2024] [Indexed: 07/28/2024] Open
Abstract
The cerebral cortex has long been thought to be involved in the pathophysiology of motor symptoms of Parkinson's disease. The impaired cortical function is believed to be a direct and immediate effect of pathologically patterned basal ganglia output, mediated to the cerebral cortex by way of the ventral motor thalamus. However, recent studies in humans with Parkinson's disease and in animal models of the disease have provided strong evidence suggesting that the involvement of the cerebral cortex is much broader than merely serving as a passive conduit for subcortical disturbances. In the present review, we discuss Parkinson's disease-related changes in frontal cortical motor regions, focusing on neuropathology, plasticity, changes in neurotransmission, and altered network interactions. We will also examine recent studies exploring the cortical circuits as potential targets for neuromodulation to treat Parkinson's disease.
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Affiliation(s)
- Hong-Yuan Chu
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Department of Pharmacology and Physiology, Georgetown University Medical Center, 3900 Reservoir Rd N.W., Washington D.C. 20007, United States
| | - Yoland Smith
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Department of Neurology, School of Medicine, Emory University, 12 Executive Drive N.E., Atlanta, GA 30329, United States
- Emory National Primate Research Center, 954 Gatewood Road N.E., Emory University, Atlanta, GA 30329, United States
| | - William W Lytton
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Department of Physiology & Pharmacology, SUNY Downstate Medical Center, 450 Clarkson Avenue, Brooklyn, NY 11203, United States
- Department of Neurology, Kings County Hospital, 451 Clarkson Avenue,Brooklyn, NY 11203, United States
| | - Scott Grafton
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Department of Psychological and Brain Sciences, University of California, 551 UCEN Road, Santa Barbara, CA 93106, United States
| | - Rosa Villalba
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Emory National Primate Research Center, 954 Gatewood Road N.E., Emory University, Atlanta, GA 30329, United States
| | - Gunasingh Masilamoni
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Emory National Primate Research Center, 954 Gatewood Road N.E., Emory University, Atlanta, GA 30329, United States
| | - Thomas Wichmann
- Aligning Science Across Parkinson’s (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, United States
- Department of Neurology, School of Medicine, Emory University, 12 Executive Drive N.E., Atlanta, GA 30329, United States
- Emory National Primate Research Center, 954 Gatewood Road N.E., Emory University, Atlanta, GA 30329, United States
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da Silva Castanheira J, Wiesman AI, Hansen JY, Misic B, Baillet S. The neurophysiological brain-fingerprint of Parkinson's disease. EBioMedicine 2024; 105:105201. [PMID: 38908100 PMCID: PMC11253223 DOI: 10.1016/j.ebiom.2024.105201] [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: 12/04/2023] [Revised: 05/30/2024] [Accepted: 05/30/2024] [Indexed: 06/24/2024] Open
Abstract
BACKGROUND Research in healthy young adults shows that characteristic patterns of brain activity define individual "brain-fingerprints" that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson's disease (PD). METHODS We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. FINDINGS The arrhythmic spectral components of cortical activity in patients with Parkinson's disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson's brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson's symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson's brain-fingerprint aligns with that of neurotransmitter systems affected by the disease's pathophysiology. INTERPRETATION The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson's disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson's disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. FUNDING Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer's Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311).
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Affiliation(s)
| | - Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Justine Y Hansen
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Bratislav Misic
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Sylvain Baillet
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.
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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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Vinding MC, Waldthaler J, Eriksson A, Manting CL, Ferreira D, Ingvar M, Svenningsson P, Lundqvist D. Oscillatory and non-oscillatory features of the magnetoencephalic sensorimotor rhythm in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:51. [PMID: 38443402 PMCID: PMC10915140 DOI: 10.1038/s41531-024-00669-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Accepted: 02/26/2024] [Indexed: 03/07/2024] Open
Abstract
Parkinson's disease (PD) is associated with changes in neural activity in the sensorimotor alpha and beta bands. Using magnetoencephalography (MEG), we investigated the role of spontaneous neuronal activity within the somatosensory cortex in a large cohort of early- to mid-stage PD patients (N = 78) on Parkinsonian medication and age- and sex-matched healthy controls (N = 60) using source reconstructed resting-state MEG. We quantified features of the time series data in terms of oscillatory alpha power and central alpha frequency, beta power and central beta frequency, and 1/f broadband characteristics using power spectral density. Furthermore, we characterised transient oscillatory burst events in the mu-beta band time-domain signals. We examined the relationship between these signal features and the patients' disease state, symptom severity, age, sex, and cortical thickness. PD patients and healthy controls differed on PSD broadband characteristics, with PD patients showing a steeper 1/f exponential slope and higher 1/f offset. PD patients further showed a steeper age-related decrease in the burst rate. Out of all the signal features of the sensorimotor activity, the burst rate was associated with increased severity of bradykinesia, whereas the burst duration was associated with axial symptoms. Our study shows that general non-oscillatory features (broadband 1/f exponent and offset) of the sensorimotor signals are related to disease state and oscillatory burst rate scales with symptom severity in PD.
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Affiliation(s)
- Mikkel C Vinding
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
| | - Josefine Waldthaler
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Section of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, University Hospital Marburg, Marburg, Germany
| | - Allison Eriksson
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Cassia Low Manting
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Cognitive Neuroimaging Centre, Lee Kong Chien School of Medicine, Nanyang Technological University, Singapore, Singapore
- McGovern Institute of Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Daniel Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer's Research, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Facultad de Ciencias de la Salud, Universidad Fernando Pessoa Canarias, Las Palmas de Gran, Canaria, España
| | - Martin Ingvar
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Per Svenningsson
- Section of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Daniel Lundqvist
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
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5
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Vinding MC, Eriksson A, Comarovschii I, Waldthaler J, Manting CL, Oostenveld R, Ingvar M, Svenningsson P, Lundqvist D. The Swedish National Facility for Magnetoencephalography Parkinson's disease dataset. Sci Data 2024; 11:150. [PMID: 38296972 PMCID: PMC10830455 DOI: 10.1038/s41597-024-02987-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 01/18/2024] [Indexed: 02/02/2024] Open
Abstract
Parkinson's disease (PD) is characterised by a loss of dopamine and dopaminergic cells. The consequences hereof are widespread network disturbances in brain function. It is an ongoing topic of investigation how the disease-related changes in brain function manifest in PD relate to clinical symptoms. We present The Swedish National Facility for Magnetoencephalography Parkinson's Disease Dataset (NatMEG-PD) as an Open Science contribution to identify the functional neural signatures of Parkinson's disease and contribute to diagnosis and treatment. The dataset contains whole-head magnetoencephalographic (MEG) recordings from 66 well-characterised PD patients on their regular dose of dopamine replacement therapy and 68 age- and sex-matched healthy controls. NatMEG-PD contains three-minute eyes-closed resting-state MEG, MEG during an active movement task, and MEG during passive movements. The data includes anonymised MRI for source analysis and clinical scores. MEG data is rich in nature and can be used to explore numerous functional features. By sharing these data, we hope other researchers will contribute to advancing our understanding of the relationship between brain activity and disease state or symptoms.
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Affiliation(s)
- Mikkel C Vinding
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital - Amager and Hvidovre, Copenhagen, Denmark.
| | - Allison Eriksson
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden
| | - Igori Comarovschii
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Josefine Waldthaler
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Neurology, University Hospital Marburg, Marburg, Germany
| | - Cassia Low Manting
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- McGovern Institute of Brain Research, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Robert Oostenveld
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands
| | - Martin Ingvar
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Per Svenningsson
- Section of Neurology, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Daniel Lundqvist
- NatMEG, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
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6
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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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Gimenez-Aparisi G, Guijarro-Estelles E, Chornet-Lurbe A, Ballesta-Martinez S, Pardo-Hernandez M, Ye-Lin Y. Early detection of Parkinson's disease: Systematic analysis of the influence of the eyes on quantitative biomarkers in resting state electroencephalography. Heliyon 2023; 9:e20625. [PMID: 37829809 PMCID: PMC10565694 DOI: 10.1016/j.heliyon.2023.e20625] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 07/24/2023] [Accepted: 10/02/2023] [Indexed: 10/14/2023] Open
Abstract
While resting state electroencephalography (EEG) provides relevant information on pathological changes in Parkinson's disease, most studies focus on the eyes-closed EEG biomarkers. Recent evidence has shown that both eyes-open EEG and reactivity to eyes-opening can also differentiate Parkinson's disease from healthy aging, but no consensus has been reached on a discriminatory capability benchmark. The aim of this study was to determine the resting-state EEG biomarkers suitable for real-time application that can differentiate Parkinson's patients from healthy subjects under both eyes closed and open. For this, we analysed and compared the quantitative EEG analyses of 13 early-stage cognitively normal Parkinson's patients with an age and sex-matched healthy group. We found that Parkinson's disease exhibited abnormal excessive theta activity in eyes-closed, which was reflected by a significantly higher relative theta power, a higher time percentage with a frequency peak in the theta band and a reduced alpha/theta ratio, while Parkinson's patients showed a significantly steeper non-oscillatory spectral slope activity than that of healthy subjects. We also found considerably less alpha and beta reactivity to eyes-opening in Parkinson's disease plus a significant moderate correlation between these EEG-biomarkers and the MDS-UPDRS score, used to assesses the clinical symptoms of Parkinson's Disease. Both EEG recordings with the eyes open and reactivity to eyes-opening provided additional information to the eyes-closed condition. We thus strongly recommend that both eyes open and closed be used in clinical practice recording protocols to promote EEG as a complementary non-invasive screening method for the early detection of Parkinson's disease, which would allow clinicians to design patient-oriented treatment and improve the patient's quality of life.
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Affiliation(s)
- G. Gimenez-Aparisi
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
| | - E. Guijarro-Estelles
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
| | - A. Chornet-Lurbe
- Servicio de Neurofisiología Clínica, Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, 46800, Xàtiva, València, Spain
| | - S. Ballesta-Martinez
- Servicio de Neurofisiología Clínica, Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, 46800, Xàtiva, València, Spain
| | - M. Pardo-Hernandez
- Servicio de Neurofisiología Clínica, Hospital Lluís Alcanyís, departamento de salud Xàtiva-Ontinyent, 46800, Xàtiva, València, Spain
| | - Y. Ye-Lin
- Centro de Investigación e Innovación en Bioingeniería, Universitat Politècnica de València, 46022, València, Spain
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8
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Shabanpour M, Kaboodvand N, Iravani B. Parkinson's disease is characterized by sub-second resting-state spatio-oscillatory patterns: A contribution from deep convolutional neural network. Neuroimage Clin 2022; 36:103266. [PMID: 36451369 PMCID: PMC9723309 DOI: 10.1016/j.nicl.2022.103266] [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: 09/13/2022] [Revised: 11/08/2022] [Accepted: 11/09/2022] [Indexed: 11/15/2022]
Abstract
Deep convolutional neural network (DCNN) provides a multivariate framework to detect relevant spatio-oscillatory patterns in the data beyond common mass-univariate statistics. Yet, its practical application is limited due to the low interpretability of the results beyond accuracy. We opted to use DCNN with a minimalistic architecture design and large penalized terms to yield a generalizable and clinically relevant network model. Our network was trained based on the scalp topology of the electroencephalography (EEG) from an open access dataset, constituting our primary sample of healthy controls (n = 25) and Parkinson's disease (PD) patients (n = 25), with and without medication. Next, we validated the model on another independent, yet comparable open access EEG dataset (healthy controls (n = 20) and PD patients (n = 20)), which was unseen to the network. We applied Gradient-weighted Class Activation Mapping (Grad-CAM) interpretability technique to create a localization map exhibiting the key network predictors, based on the gradients of the classification score flowing into the last convolutional layer. Accordingly, our results indicated that a sub-second of intrinsic oscillatory power pattern in the beta band over the occipitoparietal, gamma band over the left motor cortex as well as theta band over the frontoparietal cluster, had the largest impact on the network score for dissociating the PD patients from age- and gender-matched healthy controls, across the two datasets. We further found that the off-medication motor symptoms were related to the occipitoparietal off-medication beta power whereas the disease duration was associated with the off-medication beta power of the motor cortex. The on-medication theta power of the frontoparietal was related to the improvement of the motor symptoms. In conclusion, our method enabled us to characterize PD patho-electrophysiology according to the multivariate topographic analysis approach, where both spatial and frequency aspects of the oscillations were simultaneously considered. Moreover, our approach was free from common reference problem of the EEG data analyses.
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Affiliation(s)
| | - Neda Kaboodvand
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden,Department of Neurology and Neurological Science, Stanford University, Stanford, United States
| | - Behzad Iravani
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden,Department of Neurology and Neurological Science, Stanford University, Stanford, United States,Corresponding author at: Full postal address: K8 Klinisk neurovetenskap, K8 Neuro Fransson, 171 77 Stockholm, Sweden.
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9
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Lee LHN, Huang CS, Wang RW, Lai HJ, Chung CC, Yang YC, Kuo CC. Deep brain stimulation rectifies the noisy cortex and irresponsive subthalamus to improve parkinsonian locomotor activities. NPJ Parkinsons Dis 2022; 8:77. [PMID: 35725730 PMCID: PMC9209473 DOI: 10.1038/s41531-022-00343-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 05/31/2022] [Indexed: 11/10/2022] Open
Abstract
The success of deep brain stimulation (DBS) therapy indicates that Parkinson's disease is a brain rhythm disorder. However, the manifestations of the erroneous rhythms corrected by DBS remain to be established. We found that augmentation of α rhythms and α coherence between the motor cortex (MC) and the subthalamic nucleus (STN) is characteristically prokinetic and is decreased in parkinsonian rats. In multi-unit recordings, movement is normally associated with increased changes in spatiotemporal activities rather than overall spike rates in MC. In parkinsonian rats, MC shows higher spike rates at rest but less spatiotemporal activity changes upon movement, and STN burst discharges are more prevalent, longer lasting, and less responsive to MC inputs. DBS at STN rectifies the foregoing pathological MC-STN oscillations and consequently locomotor deficits, yet overstimulation may cause behavioral restlessness. These results indicate that delicate electrophysiological considerations at both cortical and subcortical levels should be exercised for optimal DBS therapy.
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Affiliation(s)
- Lan-Hsin Nancy Lee
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan.,Department of Neurology, Fu Jen Catholic University Hospital, New Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Chen-Syuan Huang
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Ren-Wei Wang
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan
| | - Hsing-Jung Lai
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan.,Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.,National Taiwan University Hospital, Jin-Shan Branch, New Taipei, Taiwan
| | - Chih-Ching Chung
- Department of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Ya-Chin Yang
- Graduate Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan. .,Department of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan. .,Neuroscience Research Center, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan. .,Department of Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan.
| | - Chung-Chin Kuo
- Department of Physiology, National Taiwan University College of Medicine, Taipei, Taiwan. .,Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
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10
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Tanaka M, Yanagisawa T, Fukuma R, Tani N, Oshino S, Mihara M, Hattori N, Kajiyama Y, Hashimoto R, Ikeda M, Mochizuki H, Kishima H. Magnetoencephalography detects phase-amplitude coupling in Parkinson's disease. Sci Rep 2022; 12:1835. [PMID: 35115607 PMCID: PMC8813926 DOI: 10.1038/s41598-022-05901-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 01/20/2022] [Indexed: 11/25/2022] Open
Abstract
To characterize Parkinson's disease, abnormal phase-amplitude coupling is assessed in the cortico-basal circuit using invasive recordings. It is unknown whether the same phenomenon might be found in regions other than the cortico-basal ganglia circuit. We hypothesized that using magnetoencephalography to assess phase-amplitude coupling in the whole brain can characterize Parkinson's disease. We recorded resting-state magnetoencephalographic signals in patients with Parkinson's disease and in healthy age- and sex-matched participants. We compared whole-brain signals from the two groups, evaluating the power spectra of 3 frequency bands (alpha, 8-12 Hz; beta, 13-25 Hz; gamma, 50-100 Hz) and the coupling between gamma amplitude and alpha or beta phases. Patients with Parkinson's disease showed significant beta-gamma phase-amplitude coupling that was widely distributed in the sensorimotor, occipital, and temporal cortices; healthy participants showed such coupling only in parts of the somatosensory and temporal cortices. Moreover, beta- and gamma-band power differed significantly between participants in the two groups (P < 0.05). Finally, beta-gamma phase-amplitude coupling in the sensorimotor cortices correlated significantly with motor symptoms of Parkinson's disease (P < 0.05); beta- and gamma-band power did not. We thus demonstrated that beta-gamma phase-amplitude coupling in the resting state characterizes Parkinson's disease.
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Affiliation(s)
- Masataka Tanaka
- Department of Neurosurgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Takufumi Yanagisawa
- Department of Neurosurgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
- Institute for Advanced Co-Creation Studies, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
- Department of Neuroinformatics, ATR Computational Neuroscience Laboratories, 2-2-2 Hikaridai, Seika-cho, Kyoto, 619 0288, Japan.
| | - Ryohei Fukuma
- Department of Neurosurgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
- Institute for Advanced Co-Creation Studies, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
- Department of Neuroinformatics, ATR Computational Neuroscience Laboratories, 2-2-2 Hikaridai, Seika-cho, Kyoto, 619 0288, Japan
| | - Naoki Tani
- Department of Neurosurgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Satoru Oshino
- Department of Neurosurgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Masahito Mihara
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Noriaki Hattori
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
- Department of Rehabilitation, Faculty of Medicine, Academic Assembly, University of Toyama, Toyama, Japan
| | - Yuta Kajiyama
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, 4-1 Ogawahigashi, Kodaira, Tokyo, 187-8553, Japan
- Department of Psychiatry, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
- Molecular Research Center for Children's Mental Development, United Graduate School of Child Development, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Manabu Ikeda
- Department of Psychiatry, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Hideki Mochizuki
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
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11
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Wiesman AI, Murman DL, Losh RA, Schantell M, Christopher-Hayes NJ, Johnson HJ, Willett MP, Wolfson SL, Losh KL, Johnson CM, May PE, Wilson TW. Spatially resolved neural slowing predicts impairment and amyloid burden in Alzheimer's disease. Brain 2022; 145:2177-2189. [PMID: 35088842 PMCID: PMC9246709 DOI: 10.1093/brain/awab430] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 10/05/2021] [Accepted: 10/24/2021] [Indexed: 11/28/2022] Open
Abstract
An extensive electrophysiological literature has proposed a pathological ‘slowing’ of neuronal activity in patients on the Alzheimer’s disease spectrum. Supported by numerous studies reporting increases in low-frequency and decreases in high-frequency neural oscillations, this pattern has been suggested as a stable biomarker with potential clinical utility. However, no spatially resolved metric of such slowing exists, stymieing efforts to understand its relation to proteinopathy and clinical outcomes. Further, the assumption that this slowing is occurring in spatially overlapping populations of neurons has not been empirically validated. In the current study, we collected cross-sectional resting state measures of neuronal activity using magnetoencephalography from 38 biomarker-confirmed patients on the Alzheimer’s disease spectrum and 20 cognitively normal biomarker-negative older adults. From these data, we compute and validate a new metric of spatially resolved oscillatory deviations from healthy ageing for each patient on the Alzheimer’s disease spectrum. Using this Pathological Oscillatory Slowing Index, we show that patients on the Alzheimer’s disease spectrum exhibit robust neuronal slowing across a network of temporal, parietal, cerebellar and prefrontal cortices. This slowing effect is shown to be directly relevant to clinical outcomes, as oscillatory slowing in temporal and parietal cortices significantly predicted both general (i.e. Montreal Cognitive Assessment scores) and domain-specific (i.e. attention, language and processing speed) cognitive function. Further, regional amyloid-β accumulation, as measured by quantitative 18F florbetapir PET, robustly predicted the magnitude of this pathological neural slowing effect, and the strength of this relationship between amyloid-β burden and neural slowing also predicted attentional impairments across patients. These findings provide empirical support for a spatially overlapping effect of oscillatory neural slowing in biomarker-confirmed patients on the Alzheimer’s disease spectrum, and link this effect to both regional proteinopathy and cognitive outcomes in a spatially resolved manner. The Pathological Oscillatory Slowing Index also represents a novel metric that is of potentially high utility across a number of clinical neuroimaging applications, as oscillatory slowing has also been extensively documented in other patient populations, most notably Parkinson’s disease, with divergent spectral and spatial features.
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Affiliation(s)
- Alex I Wiesman
- Montreal Neurological Institute, McGill University, Montreal, QC, Canada.,Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Daniel L Murman
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA.,Memory Disorders & Behavioral Neurology Program, UNMC, Omaha, NE, USA
| | - Rebecca A Losh
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | - Mikki Schantell
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Hallie J Johnson
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | - Madelyn P Willett
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Kathryn L Losh
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Pamela E May
- Department of Neurological Sciences, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience,Boys Town National Research Hospital, Omaha, NE, USA
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12
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Zokaei N, Quinn AJ, Hu MT, Husain M, van Ede F, Nobre AC. Reduced cortico-muscular beta coupling in Parkinson's disease predicts motor impairment. Brain Commun 2021; 3:fcab179. [PMID: 34514395 PMCID: PMC8421699 DOI: 10.1093/braincomms/fcab179] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2021] [Revised: 05/15/2021] [Accepted: 05/28/2021] [Indexed: 11/16/2022] Open
Abstract
Long-range communication through the motor system is thought to be facilitated by phase coupling between neural activity in the 15–30 Hz beta range. During periods of sustained muscle contraction (grip), such coupling is manifest between motor cortex and the contralateral forearm muscles—measured as the cortico-muscular coherence. We examined alterations in cortico-muscular coherence in individuals with Parkinson’s disease, while equating grip strength between individuals with Parkinson’s disease (off their medication) and healthy control participants. We show a marked reduction in beta cortico-muscular coherence in the Parkinson’s disease group, even though the grip strength was comparable between the two groups. Moreover, the reduced cortico-muscular coherence was related to motor symptoms, so that individuals with lower cortico-muscular coherence also displayed worse motor symptoms. These findings highlight the cortico-muscular coherence as a simple, effective and clinically relevant neural marker of Parkinson’s disease pathology, with the potential to aid monitoring of disease progression and the efficacy of novel treatments for Parkinson’s disease.
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Affiliation(s)
- Nahid Zokaei
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Michele T Hu
- Department of Neurology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, UK
| | - Masud Husain
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK
| | - Freek van Ede
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
| | - Anna Christina Nobre
- Oxford Centre for Human Brain Activity (OHBA), Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
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13
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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: 18] [Impact Index Per Article: 4.5] [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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14
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McColgan P, Joubert J, Tabrizi SJ, Rees G. The human motor cortex microcircuit: insights for neurodegenerative disease. Nat Rev Neurosci 2020; 21:401-415. [PMID: 32555340 DOI: 10.1038/s41583-020-0315-1] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/04/2020] [Indexed: 12/22/2022]
Abstract
The human motor cortex comprises a microcircuit of five interconnected layers with different cell types. In this Review, we use a layer-specific and cell-specific approach to integrate physiological accounts of this motor cortex microcircuit with the pathophysiology of neurodegenerative diseases affecting motor functions. In doing so we can begin to link motor microcircuit pathology to specific disease stages and clinical phenotypes. Based on microcircuit physiology, we can make future predictions of axonal loss and microcircuit dysfunction. With recent advances in high-resolution neuroimaging we can then test these predictions in humans in vivo, providing mechanistic insights into neurodegenerative disease.
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Affiliation(s)
- Peter McColgan
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.
| | - Julie Joubert
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK
| | - Sarah J Tabrizi
- Huntington's Disease Research Centre, UCL Institute of Neurology, University College London, London, UK.,Dementia Research Institute at UCL, London, UK
| | - Geraint Rees
- Wellcome Centre for Human Neuroimaging, UCL Institute of Neurology, University College London, London, UK.,UCL Institute of Cognitive Neuroscience, University College London, London, UK
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15
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Heideman SG, Quinn AJ, Woolrich MW, van Ede F, Nobre AC. Dissecting beta-state changes during timed movement preparation in Parkinson's disease. Prog Neurobiol 2019; 184:101731. [PMID: 31778771 PMCID: PMC6977086 DOI: 10.1016/j.pneurobio.2019.101731] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 10/18/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022]
Abstract
An emerging perspective describes beta-band (15-28 Hz) activity as consisting of short-lived high-amplitude events that only appear sustained in conventional measures of trial-average power. This has important implications for characterising abnormalities observed in beta-band activity in disorders like Parkinson's disease. Measuring parameters associated with beta-event dynamics may yield more sensitive measures, provide more selective diagnostic neural markers, and provide greater mechanistic insight into the breakdown of brain dynamics in this disease. Here, we used magnetoencephalography in eighteen Parkinson's disease participants off dopaminergic medication and eighteen healthy control participants to investigate beta-event dynamics during timed movement preparation. We used the Hidden Markov Model to classify event dynamics in a data-driven manner and derived three parameters of beta events: (1) beta-state amplitude, (2) beta-state lifetime, and (3) beta-state interval time. Of these, changes in beta-state interval time explained the overall decreases in beta power during timed movement preparation and uniquely captured the impairment in such preparation in patients with Parkinson's disease. Thus, the increased granularity of the Hidden Markov Model analysis (compared with conventional analysis of power) provides increased sensitivity and suggests a possible reason for impairments of timed movement preparation in Parkinson's disease.
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Affiliation(s)
- Simone G Heideman
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Andrew J Quinn
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Mark W Woolrich
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Freek van Ede
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Anna C Nobre
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, United Kingdom; Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom.
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16
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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: 39] [Impact Index Per Article: 7.8] [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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17
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Cao C, Li D, Zeng K, Zhan S, Huang P, Li X, Sun B. Levodopa Reduces the Phase lag Index of Parkinson's Disease Patients: A Magnetoencephalographic Study. Clin EEG Neurosci 2019; 50:134-140. [PMID: 29914268 DOI: 10.1177/1550059418781693] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Objectives. As a method of measuring the phase difference between 2 signals, the phase lag index (PLI) of the alpha and beta bands in patients with Parkinson's disease (PD) was investigated by using magnetoencephalography (MEG). Methods. Eighteen PD patients were measured by MEG in the state of overnight withdrawal of levodopa and after levodopa treatment; meanwhile, Unified Parkinson's Disease Rating Scale (UPDRS) III scale was evaluated. Results. Compared with healthy controls, alpha (8-13 Hz) PLI in the frontal and parietal areas elevated in PD patients, while the elevation was reversed by the levodopa treatment. The alterations of the UPDRS III total scale (rs = 0.552, P = .013, n = 16) and the changes of akinesia scale (rs = 0.622, P = .005, n = 16) were correlated to the change of beta (13-30 Hz) PLI in the left parietal area. The change of the UPDRS total scale was negatively correlated to duration of disease (rs = 0.432, P = .047, n = 16). There was a negative correlation between the age of PD patients and the change of alpha PLI in the left frontal area (rs = 0.519, P = .020, n = 16). Conclusions. PD patients showed a higher mu PLI in the sensorimotor area relative to the healthy controls. The improvement of motor symptoms of PD patients by levodopa was correlated to the inhibition of beta PLI in the sensorimotor area.
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Affiliation(s)
- Chunyan Cao
- Department of Functional Neurosurgery, Ruijin Hospital, Affiliated to Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Dianyou Li
- Department of Functional Neurosurgery, Ruijin Hospital, Affiliated to Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Ke Zeng
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Shikun Zhan
- Department of Functional Neurosurgery, Ruijin Hospital, Affiliated to Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Peng Huang
- Department of Functional Neurosurgery, Ruijin Hospital, Affiliated to Shanghai JiaoTong University School of Medicine, Shanghai, China
| | - Xiaoli Li
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Bomin Sun
- Department of Functional Neurosurgery, Ruijin Hospital, Affiliated to Shanghai JiaoTong University School of Medicine, Shanghai, China
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18
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Modulations on cortical oscillations by subthalamic deep brain stimulation in patients with Parkinson disease: A MEG study. Neurosci Lett 2017; 636:95-100. [DOI: 10.1016/j.neulet.2016.11.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2016] [Revised: 10/31/2016] [Accepted: 11/02/2016] [Indexed: 11/20/2022]
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19
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Jávor-Duray BN, Vinck M, van der Roest M, Mulder AB, Stam CJ, Berendse HW, Voorn P. Early-onset cortico-cortical synchronization in the hemiparkinsonian rat model. J Neurophysiol 2015; 113:925-36. [DOI: 10.1152/jn.00690.2014] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Changes in synchronized neuronal oscillatory activity are reported in both cortex and basal ganglia of Parkinson's disease patients. The origin of these changes, in particular their relationship with the progressive nigrostriatal dopaminergic denervation, is unknown. Therefore, in the present study we studied interregional neuronal synchronization in motor cortex and basal ganglia during the development of dopaminergic degeneration induced by a unilateral infusion of 6-hydroxydopamine (6-OHDA) into the rat medial forebrain bundle. We performed serial local field potential recordings bilaterally in the motor cortex and the subthalamic nucleus of the lesioned hemisphere prior to, during, and after development of the nigrostriatal dopaminergic cell loss. We obtained signal from freely moving rats in both resting and walking conditions, and we computed local spectral power, interregional synchronization (using phase lag index), and directionality (using Granger causality). After neurotoxin injection the first change in phase lag index was an increment in cortico-cortical synchronization. We observed increased bidirectional Granger causality in the beta frequency band between cortex and subthalamic nucleus within the lesioned hemisphere. In the walking condition, the 6-OHDA lesion-induced changes in synchronization resembled that of the resting state, whereas the changes in Granger causality were less pronounced after the lesion. Considering the relatively preserved connectivity pattern of the cortex contralateral to the lesioned side and the early emergence of increased cortico-cortical synchronization during development of the 6-OHDA lesion, we suggest a putative compensatory role of cortico-cortical coupling.
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Affiliation(s)
- B. N. Jávor-Duray
- Department of Anatomy and Neurosciences, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - M. Vinck
- Cognitive and Systems Neuroscience, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - M. van der Roest
- Department of Anatomy and Neurosciences, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - A. B. Mulder
- Department of Anatomy and Neurosciences, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - C. J. Stam
- Department of Clinical Neurophysiology, VU University Medical Center, Amsterdam, The Netherlands; and
| | - H. W. Berendse
- Department of Neurology, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
| | - P. Voorn
- Department of Anatomy and Neurosciences, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, The Netherlands
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20
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Airaksinen K, Mäkelä JP, Nurminen J, Luoma J, Taulu S, Ahonen A, Pekkonen E. Cortico-muscular coherence in advanced Parkinson's disease with deep brain stimulation. Clin Neurophysiol 2014; 126:748-55. [PMID: 25218364 DOI: 10.1016/j.clinph.2014.07.025] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2013] [Revised: 06/27/2014] [Accepted: 07/16/2014] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Cortico-muscular coherence (CMC) is thought to reflect the interplay between cortex and muscle in motor coordination. In Parkinson's disease (PD) patients, levodopa has been shown to enhance CMC. This study examined whether subthalamic nucleus (STN) deep brain stimulation (DBS) affects the CMC in advanced PD. METHODS Magnetoencephalography (MEG) and electromyography (EMG) measurements were done simultaneously both with DBS on and off to determine the CMC during wrist extension. The spatiotemporal signal space separation (tSSS) was used for artifact suppression. RESULTS CMC peaks between 13 and 25 Hz were found in 15 out of 19 patients. The effect of DBS on CMC was variable. Moreover, the correlation between CMC and motor performance was inconsistent; stronger CMC did not necessarily indicate better function albeit tremor and rigidity may diminish the CMC. Patients having CMC between 13 and 25 Hz had the best motor scores at the group level. CONCLUSIONS DBS modifies the CMC in advanced PD with large interindividual variability. SIGNIFICANCE DBS does not systematically modify CMC amplitude in advanced PD. The results suggest that some components of the CMC may be related to the therapeutic effects of DBS.
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Affiliation(s)
- Katja Airaksinen
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Central Hospital, Finland; Department of Neurology, Helsinki University Central Hospital, Finland.
| | - Jyrki P Mäkelä
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Central Hospital, Finland
| | - Jussi Nurminen
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Central Hospital, Finland
| | - Jarkko Luoma
- BioMag Laboratory, HUS Medical Imaging Center, Helsinki University Central Hospital, Finland
| | | | | | - Eero Pekkonen
- Department of Neurology, Helsinki University Central Hospital, Finland
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21
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Li J, Luo C, Chen Y, Chen Q, Huang R, Sun J, Gong Q, Wu X, Qi Z, Liang Z, Li L, Li H, Li P, Wang W, Shang HF. Parkinson׳s disease-related modulation of functional connectivity associated with the striatum in the resting state in a nonhuman primate model. Brain Res 2014; 1555:10-9. [PMID: 24530271 DOI: 10.1016/j.brainres.2014.01.054] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2013] [Revised: 01/26/2014] [Accepted: 01/28/2014] [Indexed: 02/07/2023]
Abstract
The goal of this study was to describe Parkinson׳s disease (PD)-related modulation of functional connectivity (FC) associated with the striatum in the resting state in a nonhuman primate model of early-stage PD. Weekly intravenous injections of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) (0.5 mg/kg body weight) were performed until parkinsonian motor symptoms developed in four macaques. After 13 weeks of MPTP treatment, all monkeys displayed parkinsonian symptoms. During the course of the experiment, each animal underwent four magnetic resonance imaging scans and four positron emission tomography (PET) scans with the vesicular monoamine transporter 2 (VMAT2)-selective ligand 9-[(18)F] fluoropropyl-(+)-dihydrotetrabenazine, performed prior to the beginning of MPTP administration as well as after 4, 9, and 13 MPTP injections. The FC profile of the striatum was evaluated using a seed voxel correlation approach and post hoc region of interest analysis on resting-state functional magnetic resonance imaging data. The PET images were subjected to region of interest analysis to examine brain regional reductions in VMAT2 density in the PD model. Significant reductions in the connectivity pattern of the striatal regions were observed: limbic striatum and left hippocampus; caudate nucleus/associative and brain regions, including the right pre-supplementary motor area and bilateral dorsolateral prefrontal cortex; putamen/associative region and left inferior temporal gyrus or right orbital and medial prefrontal cortex; and putamen/motor and cortical structures, including the right superior temporal gyrus and bilateral postcentral gyrus. Subsequent PET studies showed the progressive loss of striatal VMAT2 in the striatum with the presentation of parkinsonism. Significant differences between the specific uptake ratio reductions in each striatal subdivision were not found. By using a long-term, low-dose MPTP-lesioned nonhuman primate model, this study demonstrated PD-related decreased corticostriatal FC in a resting state; moreover, altered sensorimotor integration was also found in early-stage PD.
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Affiliation(s)
- Jianpeng Li
- Department of Neurology, West China Hospital, Sichuan University, China
| | - Chunyan Luo
- Department of Neurology, West China Hospital, Sichuan University, China
| | - Yongping Chen
- Department of Neurology, West China Hospital, Sichuan University, China
| | - Qin Chen
- Department of Neurology, West China Hospital, Sichuan University, China
| | - Rui Huang
- Department of Neurology, West China Hospital, Sichuan University, China
| | - Jiayu Sun
- Department of Radiology, West China Hospital, Sichuan University, China
| | - Qiyong Gong
- Department of Radiology, West China Hospital, Sichuan University, China
| | - Xiaoai Wu
- Department of Nuclear Medicine, West China Hospital, Sichuan University, China
| | - Zhongzhi Qi
- Department of Nuclear Medicine, West China Hospital, Sichuan University, China
| | - Zhenglu Liang
- Department of Nuclear Medicine, West China Hospital, Sichuan University, China
| | - Lin Li
- Department of Nuclear Medicine, West China Hospital, Sichuan University, China
| | - Hongxia Li
- National Chengdu Center for Safety Evaluation of Drugs, China
| | - Peng Li
- Department of Neurosurgery, West China Hospital, Sichuan University, China
| | - Wei Wang
- Department of Neurosurgery, West China Hospital, Sichuan University, China
| | - Hui-Fang Shang
- Department of Neurology, West China Hospital, Sichuan University, China.
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van Wijk BCM, Beek PJ, Daffertshofer A. Neural synchrony within the motor system: what have we learned so far? Front Hum Neurosci 2012; 6:252. [PMID: 22969718 PMCID: PMC3432872 DOI: 10.3389/fnhum.2012.00252] [Citation(s) in RCA: 154] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2012] [Accepted: 08/17/2012] [Indexed: 11/26/2022] Open
Abstract
Synchronization of neural activity is considered essential for information processing in the nervous system. Both local and inter-regional synchronization are omnipresent in different frequency regimes and relate to a variety of behavioral and cognitive functions. Over the years, many studies have sought to elucidate the question how alpha/mu, beta, and gamma synchronization contribute to motor control. Here, we review these studies with the purpose to delineate what they have added to our understanding of the neural control of movement. We highlight important findings regarding oscillations in primary motor cortex, synchronization between cortex and spinal cord, synchronization between cortical regions, as well as abnormal synchronization patterns in a selection of motor dysfunctions. The interpretation of synchronization patterns benefits from combining results of invasive and non-invasive recordings, different data analysis tools, and modeling work. Importantly, although synchronization is deemed to play a vital role, it is not the only mechanism for neural communication. Spike timing and rate coding act together during motor control and should therefore both be accounted for when interpreting movement-related activity.
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Affiliation(s)
- Bernadette C. M. van Wijk
- MOVE Research Institute, Faculty of Human Movement Sciences, VU University AmsterdamAmsterdam, Netherlands
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23
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van Wijk BCM, Willemse RB, Peter Vandertop W, Daffertshofer A. Slowing of M1 oscillations in brain tumor patients in resting state and during movement. Clin Neurophysiol 2012; 123:2212-9. [PMID: 22608483 DOI: 10.1016/j.clinph.2012.04.012] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Revised: 03/22/2012] [Accepted: 04/05/2012] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Brain tumors may severely disrupt the structure and function of the brain. While abnormal low-frequency activity can be found around tumor borders, disrupted structural connectivity may also impinge on neural activity in distant brain regions and other frequency bands. We investigated how glioma in patients with normal motor functioning affects activity in primary motor areas (M1). METHODS Using magnetoencephalography in 12 patients with unilateral glioma located around the central sulcus, we studied activity in bilateral M1s in resting state and during movement with focus on motor-related mu (8-12Hz) and beta rhythms (15-30Hz). Principal component analysis served to test for differences in spectral content. RESULTS A shift was found towards lower frequencies for M1 in the tumor hemisphere compared to M1 in the healthy hemisphere, caused by an increase in mu and decrease in beta power. This pattern was observed both in resting state and during movement. CONCLUSIONS This 'slowing' of brain oscillations in M1 resembles findings in patients with monohemispheric stroke and Parkinson's disease. A loss of intra-cortical connectivity may account for these findings, possibly supplemented by tumor-induced changes in neurotransmitter systems. SIGNIFICANCE Motor functioning may be unaffected by a spectral shift of mu and beta oscillations.
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24
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Crowell AL, Ryapolova-Webb ES, Ostrem JL, Galifianakis NB, Shimamoto S, Lim DA, Starr PA. Oscillations in sensorimotor cortex in movement disorders: an electrocorticography study. ACTA ACUST UNITED AC 2012; 135:615-30. [PMID: 22252995 DOI: 10.1093/brain/awr332] [Citation(s) in RCA: 127] [Impact Index Per Article: 10.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Movement disorders of basal ganglia origin may arise from abnormalities in synchronized oscillatory activity in a network that includes the basal ganglia, thalamus and motor cortices. In humans, much has been learned from the study of basal ganglia local field potentials recorded from temporarily externalized deep brain stimulator electrodes. These studies have led to the theory that Parkinson's disease has characteristic alterations in the beta frequency band (13-30 Hz) in the basal ganglia-thalamocortical network. However, different disorders have rarely been compared using recordings in the same structure under the same behavioural conditions, limiting straightforward assessment of current hypotheses. To address this, we utilized subdural electrocorticography to study cortical oscillations in the three most common movement disorders: Parkinson's disease, primary dystonia and essential tremor. We recorded local field potentials from the arm area of primary motor and sensory cortices in 31 subjects using strip electrodes placed temporarily during routine surgery for deep brain stimulator placement. We show that: (i) primary motor cortex broadband gamma power is increased in Parkinson's disease compared with the other conditions, both at rest and during a movement task; (ii) primary motor cortex high beta (20-30 Hz) power is increased in Parkinson's disease during the 'stop' phase of a movement task; (iii) the alpha-beta peaks in the motor and sensory cortical power spectra occur at higher frequencies in Parkinson's disease than in the other two disorders; and (iv) patients with dystonia have impaired movement-related beta band desynchronization in primary motor and sensory cortices. The findings support the emerging hypothesis that disease states reflect abnormalities in synchronized oscillatory activity. This is the first study of sensorimotor cortex local field potentials in the three most common movement disorders.
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Affiliation(s)
- Andrea L Crowell
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
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Kringelbach ML, Green AL, Aziz TZ. Balancing the brain: resting state networks and deep brain stimulation. Front Integr Neurosci 2011; 5:8. [PMID: 21577250 PMCID: PMC3088866 DOI: 10.3389/fnint.2011.00008] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2011] [Accepted: 04/18/2011] [Indexed: 01/28/2023] Open
Abstract
Over the last three decades, large numbers of patients with otherwise treatment-resistant disorders have been helped by deep brain stimulation (DBS), yet a full scientific understanding of the underlying neural mechanisms is still missing. We have previously proposed that efficacious DBS works by restoring the balance of the brain's resting state networks. Here, we extend this proposal by reviewing how detailed investigations of the highly coherent functional and structural brain networks in health and disease (such as Parkinson's) have the potential not only to increase our understanding of fundamental brain function but of how best to modulate the balance. In particular, some of the newly identified hubs and connectors within and between resting state networks could become important new targets for DBS, including potentially in neuropsychiatric disorders. At the same time, it is of essence to consider the ethical implications of this perspective.
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