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Fang H, Berman SA, Wang Y, Yang Y. Robust adaptive deep brain stimulation control of in-silico non-stationary Parkinsonian neural oscillatory dynamics. J Neural Eng 2024; 21:036043. [PMID: 38834058 DOI: 10.1088/1741-2552/ad5406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 06/04/2024] [Indexed: 06/06/2024]
Abstract
Objective. Closed-loop deep brain stimulation (DBS) is a promising therapy for Parkinson's disease (PD) that works by adjusting DBS patterns in real time from the guidance of feedback neural activity. Current closed-loop DBS mainly uses threshold-crossing on-off controllers or linear time-invariant (LTI) controllers to regulate the basal ganglia (BG) Parkinsonian beta band oscillation power. However, the critical cortex-BG-thalamus network dynamics underlying PD are nonlinear, non-stationary, and noisy, hindering accurate and robust control of Parkinsonian neural oscillatory dynamics.Approach. Here, we develop a new robust adaptive closed-loop DBS method for regulating the Parkinsonian beta oscillatory dynamics of the cortex-BG-thalamus network. We first build an adaptive state-space model to quantify the dynamic, nonlinear, and non-stationary neural activity. We then construct an adaptive estimator to track the nonlinearity and non-stationarity in real time. We next design a robust controller to automatically determine the DBS frequency based on the estimated Parkinsonian neural state while reducing the system's sensitivity to high-frequency noise. We adopt and tune a biophysical cortex-BG-thalamus network model as an in-silico simulation testbed to generate nonlinear and non-stationary Parkinsonian neural dynamics for evaluating DBS methods.Main results. We find that under different nonlinear and non-stationary neural dynamics, our robust adaptive DBS method achieved accurate regulation of the BG Parkinsonian beta band oscillation power with small control error, bias, and deviation. Moreover, the accurate regulation generalizes across different therapeutic targets and consistently outperforms current on-off and LTI DBS methods.Significance. These results have implications for future designs of closed-loop DBS systems to treat PD.
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Affiliation(s)
- Hao Fang
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou 310058, People's Republic of China
- Nanhu Brain-computer Interface Institute, Hangzhou 311100, People's Republic of China
| | - Stephen A Berman
- College of Medicine, University of Central Florida, Orlando, FL 32816, United States of America
| | - Yueming Wang
- Nanhu Brain-computer Interface Institute, Hangzhou 311100, People's Republic of China
- Qiushi Academy for Advanced Studies, Hangzhou 310058, People's Republic of China
- College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, People's Republic of China
- State Key Laboratory of Brain-machine Intelligence, Hangzhou 310058, People's Republic of China
| | - Yuxiao Yang
- MOE Frontier Science Center for Brain Science and Brain-machine Integration, Zhejiang University, Hangzhou 310058, People's Republic of China
- Nanhu Brain-computer Interface Institute, Hangzhou 311100, People's Republic of China
- College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, People's Republic of China
- State Key Laboratory of Brain-machine Intelligence, Hangzhou 310058, People's Republic of China
- Department of Neurosurgery, Second Affiliated Hospital, School of Medicine, Hangzhou 310058, People's Republic of China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, People's Republic of China
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Bonanno L, Cannuli A, Pignolo L, Marino S, Quartarone A, Calabrò RS, Cerasa A. Neural Plasticity Changes Induced by Motor Robotic Rehabilitation in Stroke Patients: The Contribution of Functional Neuroimaging. Bioengineering (Basel) 2023; 10:990. [PMID: 37627875 PMCID: PMC10451271 DOI: 10.3390/bioengineering10080990] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 08/07/2023] [Accepted: 08/18/2023] [Indexed: 08/27/2023] Open
Abstract
Robotic rehabilitation is one of the most advanced treatments helping people with stroke to faster recovery from motor deficits. The clinical impact of this type of treatment has been widely defined and established using clinical scales. The neurofunctional indicators of motor recovery following conventional rehabilitation treatments have already been identified by previous meta-analytic investigations. However, a clear definition of the neural correlates associated with robotic neurorehabilitation treatment has never been performed. This systematic review assesses the neurofunctional correlates (fMRI, fNIRS) of cutting-edge robotic therapies in enhancing motor recovery of stroke populations in accordance with PRISMA standards. A total of 7, of the initial yield of 150 articles, have been included in this review. Lessons from these studies suggest that neural plasticity within the ipsilateral primary motor cortex, the contralateral sensorimotor cortex, and the premotor cortices are more sensitive to compensation strategies reflecting upper and lower limbs' motor recovery despite the high heterogeneity in robotic devices, clinical status, and neuroimaging procedures. Unfortunately, the paucity of RCT studies prevents us from understanding the neurobiological differences induced by robotic devices with respect to traditional rehabilitation approaches. Despite this technology dating to the early 1990s, there is a need to translate more functional neuroimaging markers in clinical settings since they provide a unique opportunity to examine, in-depth, the brain plasticity changes induced by robotic rehabilitation.
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Affiliation(s)
- Lilla Bonanno
- IRCCS Centro Neurolesi Bonino Pulejo, 98123 Messina, Italy; (L.B.); (A.C.); (S.M.); (A.Q.)
| | - Antonio Cannuli
- IRCCS Centro Neurolesi Bonino Pulejo, 98123 Messina, Italy; (L.B.); (A.C.); (S.M.); (A.Q.)
| | | | - Silvia Marino
- IRCCS Centro Neurolesi Bonino Pulejo, 98123 Messina, Italy; (L.B.); (A.C.); (S.M.); (A.Q.)
| | - Angelo Quartarone
- IRCCS Centro Neurolesi Bonino Pulejo, 98123 Messina, Italy; (L.B.); (A.C.); (S.M.); (A.Q.)
| | | | - Antonio Cerasa
- S’Anna Institute, 88900 Crotone, Italy;
- Institute for Biomedical Research and Innovation (IRIB), National Research Council of Italy (CNR), 98164 Messina, Italy
- Translational Pharmacology, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, 87036 Rende, Italy
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Chaib S, Vidal B, Bouillot C, Depoortere R, Newman-Tancredi A, Zimmer L, Levigoureux E. Multimodal imaging study of the 5-HT 1A receptor biased agonist, NLX-112, in a model of L-DOPA-induced dyskinesia. Neuroimage Clin 2023; 39:103497. [PMID: 37632990 PMCID: PMC10474496 DOI: 10.1016/j.nicl.2023.103497] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 07/20/2023] [Accepted: 08/14/2023] [Indexed: 08/28/2023]
Abstract
INTRODUCTION The leading treatment for motor signs of Parkinson's disease is L-DOPA, but, upon extended use, it can lead to levodopa-induced dyskinesia (LID). Serotonergic neurons are involved in LID etiology and previous pre-clinical studies have shown that NLX-112, a 5-HT1A biased agonist, has robust antidyskinetic effects. Here, we investigated its effects in hemiparkinsonian (HPK) rats with a unilateral nigrostriatal 6-OHDA lesion. METHODS We compared HPK rats with LID (i.e., sensitized to the dyskinetic effects of chronic L-DOPA) and without LID (HPK-non-LID), using [18F]FDG PET imaging and fMRI functional connectivity following systemic treatment with saline, L-DOPA, NLX-112 or L-DOPA + NLX-112. RESULTS In HPK-non-LID rats, [18F]FDG PET experiments showed that L-DOPA led to hypermetabolism in motor areas (cerebellum, brainstem, and mesencephalic locomotor region) and to hypometabolism in cortical regions. L-DOPA effects were also observed in HPK-LID rats, with the additional emergence of hypermetabolism in raphe nuclei and hypometabolism in hippocampus and striatum. NLX-112 attenuated L-DOPA-induced raphe hypermetabolism and cingulate cortex hypometabolism in HPK-LID rats. Moreover, in fMRI experiments NLX-112 partially corrected the altered neural circuit connectivity profile in HPK-LID rats, through activity in regions rich in 5-HT1A receptors. CONCLUSION This neuroimaging study sheds light for the first time on the brain activation patterns of HPK-LID rats. The 5-HT1A receptor agonist, NLX-112, prevents occurrence of LID, likely by activating pre-synaptic autoreceptors in the raphe nuclei, resulting in a partial restoration of brain metabolic and connectivity profiles. In addition, NLX-112 also rescues L-DOPA-induced deficits in cortical activation, suggesting potential benefit against non-motor symptoms of Parkinson's disease.
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Affiliation(s)
- Sarah Chaib
- Université Claude Bernard Lyon 1, Lyon Neuroscience Research Center, CNRS, INSERM, Lyon, France; Hospices Civils de Lyon, Lyon, France
| | - Benjamin Vidal
- Université Claude Bernard Lyon 1, Lyon Neuroscience Research Center, CNRS, INSERM, Lyon, France
| | | | | | | | - Luc Zimmer
- Université Claude Bernard Lyon 1, Lyon Neuroscience Research Center, CNRS, INSERM, Lyon, France; Hospices Civils de Lyon, Lyon, France; CERMEP-Imaging Platform, Bron, France.
| | - Elise Levigoureux
- Université Claude Bernard Lyon 1, Lyon Neuroscience Research Center, CNRS, INSERM, Lyon, France; Hospices Civils de Lyon, Lyon, France
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Mertiens S, Sure M, Schnitzler A, Florin E. Alterations of PAC-based resting state networks in Parkinson's disease are partially alleviated by levodopa medication. Front Syst Neurosci 2023; 17:1219334. [PMID: 37588811 PMCID: PMC10427244 DOI: 10.3389/fnsys.2023.1219334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 07/10/2023] [Indexed: 08/18/2023] Open
Abstract
Introduction Parkinson's disease (PD) is a neurodegenerative disorder affecting the whole brain, leading to several motor and non-motor symptoms. In the past, it has been shown that PD alters resting state networks (RSN) in the brain. These networks are usually derived from fMRI BOLD signals. This study investigated RSN changes in PD patients based on maximum phase-amplitude coupling (PAC) throughout the cortex. We also tested the hypothesis that levodopa medication shifts network activity back toward a healthy state. Methods We recorded 23 PD patients and 24 healthy age-matched participants for 30 min at rest with magnetoencephalography (MEG). PD patients were measured once in the dopaminergic medication ON and once in the medication OFF state. A T1-MRI brain scan was acquired from each participant for source reconstruction. After correcting the data for artifacts and performing source reconstruction using a linearly constrained minimum variance beamformer, we extracted visual, sensorimotor (SMN), and frontal RSNs based on PAC. Results We found significant changes in all networks between healthy participants and PD patients in the medication OFF state. Levodopa had a significant effect on the SMN but not on the other networks. There was no significant change in the optimal PAC coupling frequencies between healthy participants and PD patients. Discussion Our results suggest that RSNs, based on PAC in different parts of the cortex, are altered in PD patients. Furthermore, levodopa significantly affects the SMN, reflecting the clinical alleviation of motor symptoms and leading to a network normalization compared to healthy controls.
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Affiliation(s)
- Sean Mertiens
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Matthias Sure
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University 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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Albano L, Basaia S, Emedoli D, Balestrino R, Pompeo E, Barzaghi LR, Castellano A, Falini A, Iannaccone S, Mortini P, Filippi M, Agosta F. Longitudinal brain functional connectivity changes induced by neurosurgical thalamotomy for tremor in Parkinson's disease: a preliminary study. J Neurol 2023; 270:3623-3629. [PMID: 37060360 DOI: 10.1007/s00415-023-11705-2] [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: 02/13/2023] [Revised: 03/29/2023] [Accepted: 03/31/2023] [Indexed: 04/16/2023]
Abstract
The hypothesis that the effectiveness of neurosurgical procedures in Parkinson's disease (PD) would be related to connectivity dysfunctions between the site of the stimulation and other brain regions is growing. This study aimed to assess resting-state functional connectivity between thalamic ventral intermediate nucleus (Vim) and the rest of the brain before and after thalamotomy in PD. A 76-year-old right-handed woman with refractory tremor-dominant PD was selected as a candidate for left Vim radiosurgery thalamotomy. Clinical and motion sensor evaluation and brain resting-state functional MRI (rs-fMRI) were carried out before treatment and 3, 6, and 12 months later. Targeted Vim was selected as region of interest and a seed-based rs-fMRI analysis was performed in the patient and ten age- and sex-matched controls at baseline and over time. Furthermore, a correlation analysis between functional connectivity and tremor data was carried out. Both clinical and motion sensor measurements showed a progressive tremor improvement over time on right side after radiosurgery. In the patient, seed-based analysis showed a significantly increased functional connectivity between targeted Vim and ipsilateral visual areas relative to controls before treatment. Over 1 year, a normalization of aberrant pre-therapeutic functional connectivity between Vim and visual areas was obtained. At correlation analysis, the reduction of tremor metrics over time, assessed by clinical evaluation and wearable motion sensors, was related to the reduction of the left Vim-left visual cortex functional connectivity. Our findings support the evidence that fMRI was able to detect targeted Vim connectivity and its changes over time after thalamotomy.
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Affiliation(s)
- Luigi Albano
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Daniele Emedoli
- Department of Rehabilitation and Functional Recovery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Roberta Balestrino
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Edoardo Pompeo
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
| | | | - Antonella Castellano
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
- Neuroradiology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
- Neuroradiology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Sandro Iannaccone
- Department of Rehabilitation and Functional Recovery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Pietro Mortini
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurorehabilitation Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurophysiology Service, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy.
- Vita-Salute San Raffaele University, Via Olgettina, 60, 20132, Milan, Italy.
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy.
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Jiang L, Zhuo J, Furman A, Fishman PS, Gullapalli R. Cerebellar functional connectivity change is associated with motor and neuropsychological function in early stage drug-naïve patients with Parkinson's disease. Front Neurosci 2023; 17:1113889. [PMID: 37425003 PMCID: PMC10324581 DOI: 10.3389/fnins.2023.1113889] [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: 12/01/2022] [Accepted: 06/05/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction Parkinson's Disease (PD) is a progressive neurodegenerative disorder affecting both motor and cognitive function. Previous neuroimaging studies have reported altered functional connectivity (FC) in distributed functional networks. However, most neuroimaging studies focused on patients at an advanced stage and with antiparkinsonian medication. This study aims to conduct a cross-sectional study on cerebellar FC changes in early-stage drug-naïve PD patients and its association with motor and cognitive function. Methods Twenty-nine early-stage drug-naïve PD patients and 20 healthy controls (HCs) with resting-state fMRI data and motor UPDRS and neuropsychological cognitive data were extracted from the Parkinson's Progression Markers Initiative (PPMI) archives. We used seed-based resting-state fMRI (rs-fMRI) FC analysis and the cerebellar seeds were defined based on the hierarchical parcellation of the cerebellum (AAL atlas) and its topological function mapping (motor cerebellum and non-motor cerebellum). Results The early stage drug-naïve PD patients had significant differences in cerebellar FC when compared with HCs. Our findings include: (1) Increased intra-cerebellar FC within motor cerebellum, (2) increase motor cerebellar FC in inferior temporal gyrus and lateral occipital gyrus within ventral visual pathway and decreased motor-cerebellar FC in cuneus and dorsal posterior precuneus within dorsal visual pathway, (3) increased non-motor cerebellar FC in attention, language, and visual cortical networks, (4) increased vermal FC in somatomotor cortical network, and (5) decreased non-motor and vermal FC within brainstem, thalamus and hippocampus. Enhanced FC within motor cerebellum is positively associated with the MDS-UPDRS motor score and enhanced non-motor FC and vermal FC is negatively associated with cognitive function test scores of SDM and SFT. Conclusion These findings provide support for the involvement of cerebellum at an early stage and prior to clinical presentation of non-motor features of the disease in PD patients.
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Affiliation(s)
- Li Jiang
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
| | - Jiachen Zhuo
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
| | - Andrew Furman
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
| | - Paul S. Fishman
- Department of Neurology, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Rao Gullapalli
- Department of Diagnostic Radiology & Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
- Center for Advanced Imaging Research (CAIR), University of Maryland School of Medicine, Baltimore, MD, United States
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Chu C, Zhang Z, Wang J, Li Z, Shen X, Han X, Bai L, Liu C, Zhu X. Temporal and spatial variability of dynamic microstate brain network in early Parkinson's disease. NPJ Parkinsons Dis 2023; 9:57. [PMID: 37037843 PMCID: PMC10086042 DOI: 10.1038/s41531-023-00498-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 03/23/2023] [Indexed: 04/12/2023] Open
Abstract
Changes of brain network dynamics reveal variations in macroscopic neural activity patterns in behavioral and cognitive aspects. Quantification and application of changed dynamics in brain functional connectivity networks may contribute to a better understanding of brain diseases, and ultimately provide better prognostic indicators or auxiliary diagnostic tools. At present, most studies are focused on the properties of brain functional connectivity network constructed by sliding window method. However, few studies have explored evidence-based brain network construction algorithms that reflect disease specificity. In this work, we first proposed a novel approach to characterize the spatiotemporal variability of dynamic functional connectivity networks based on electroencephalography (EEG) microstate, and then developed a classification framework for integrating spatiotemporal variability of brain networks to improve early Parkinson's disease (PD) diagnostic performance. The experimental results indicated that compared with the brain network construction method based on conventional sliding window, the proposed method significantly improved the performance of early PD recognition, demonstrating that the dynamic spatiotemporal variability of microstate-based brain networks can reflect the pathological changes in the early PD brain. Furthermore, we observed that the spatiotemporal variability of early PD brain network has a specific distribution pattern in brain regions, which can be quantified as the degree of motor and cognitive impairment, respectively. Our work offers innovative methodological support for future research on brain network, and provides deeper insights into the spatiotemporal interaction patterns of brain activity and their variabilities in early PD.
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Affiliation(s)
- Chunguang Chu
- School of Electrical and Information Engineering, Tianjin University, 300072, Tianjin, China
| | - Zhen Zhang
- School of Electrical and Information Engineering, Tianjin University, 300072, Tianjin, China
| | - Jiang Wang
- School of Electrical and Information Engineering, Tianjin University, 300072, Tianjin, China
| | - Zhen Li
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Xiao Shen
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Xiaoxuan Han
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Lipeng Bai
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, 300052, Tianjin, China
| | - Chen Liu
- School of Electrical and Information Engineering, Tianjin University, 300072, Tianjin, China.
| | - Xiaodong Zhu
- Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, 300052, Tianjin, China.
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Wang Q, Yu M, Yan L, Xu J, Wang Y, Zhou G, Liu W. Aberrant inter-network functional connectivity in drug-naive Parkinson's disease patients with tremor dominant and postural instability and gait difficulty. Front Hum Neurosci 2023; 17:1100431. [PMID: 36816505 PMCID: PMC9934857 DOI: 10.3389/fnhum.2023.1100431] [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: 11/16/2022] [Accepted: 01/10/2023] [Indexed: 02/05/2023] Open
Abstract
Background: Insight into neural mechanisms of tremor dominant (TD) and postural instability and gait disorder (PIGD) subtypes in Parkinson's disease (PD) is vital for understanding pathophysiological hypotheses underlying this phenotype. However, network disturbances and their correlation with motor subtypes of PD remain unclear. We aimed to investigate the alterations of intra- and inter-network functional connectivity (FC) in drug-naive PD patients with different motor subtypes. Methods: Resting-state functional magnetic resonance imaging was performed on 25 drug-naive PD patients with TD (PD-TD) and 40 drug-naive PD patients with PIGD (PD-PIGD), and 37 healthy controls (HCs) underwent. The following networks were extracted using independent component analysis: sensorimotor network (SMN), left executive control network (LECN), right executive control network, anterior salience network (aSN), posterior salience network (pSN), ventral attention network (VAN), dorsal attention network (DAN), default mode network (DMN), visual network, and auditory network (AN). We measured FC values within and between these networks. Results: There were no detectable variations in intra-network FC. PD-PIGD group demonstrated lower FC between aSN and pSN, as well as between VAN and DMN, in contrast to PD-TD group. Particularly, the FC strength between VAN and DMN was positively correlated with TD and tremor scores, and the best fitting classification models of TD and PIGD subtypes were based on the FC between aSN and pSN. Compared with HCs, both PD-TD and PD-PIGD patients displayed decreased FC between two SMN subnetworks, while PD-TD patients exhibited increased FC between the SMN subnetwork and pSN, and between LECN and VAN. Furthermore, PD-PIGD patients demonstrated decreased FC between the SMN subnetwork and AN. Conclusions: The altered FC between aSN and pSN can be an imaging marker to distinguish PD-TD from PD-PIGD. We for the first time disclosed that the PD-TD patients compensated by increasing attention resources and the PD-PIGD patients displayed reduced FC between SMN and AN. Our findings provide a basis for identification and precision treatment of PD motor subtypes.
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Affiliation(s)
- Qi Wang
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China,Department of Neurology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Miao Yu
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Lei Yan
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Jianxia Xu
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Yajie Wang
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Gaiyan Zhou
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Weiguo Liu
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China,*Correspondence: Weiguo Liu
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Madadi Asl M, Valizadeh A, Tass PA. Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity. PLoS Comput Biol 2023; 19:e1010853. [PMID: 36724144 PMCID: PMC9891531 DOI: 10.1371/journal.pcbi.1010853] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 01/05/2023] [Indexed: 02/02/2023] Open
Abstract
The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.
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Affiliation(s)
- Mojtaba Madadi Asl
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
| | - Alireza Valizadeh
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States of America
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Shi Z, Jiang B, Liu T, Wang L, Pei G, Suo D, Zhang J, Funahashi S, Wu J, Yan T. Individual-level functional connectomes predict the motor symptoms of Parkinson's disease. Cereb Cortex 2023; 33:6282-6290. [PMID: 36627247 DOI: 10.1093/cercor/bhac503] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 11/28/2022] [Accepted: 11/30/2022] [Indexed: 01/12/2023] Open
Abstract
Abnormalities in functional connectivity networks are associated with sensorimotor networks in Parkinson's disease (PD) based on group-level mapping studies, but these results are controversial. Using individual-level cortical segmentation to construct individual brain atlases can supplement the individual information covered by group-level cortical segmentation. Functional connectivity analyses at the individual level are helpful for obtaining clinically useful markers and predicting treatment response. Based on the functional connectivity of individualized regions of interest, a support vector regression model was trained to estimate the severity of motor symptoms for each subject, and a correlation analysis between the estimated scores and clinical symptom scores was performed. Forty-six PD patients aged 50-75 years were included from the Parkinson's Progression Markers Initiative database, and 63 PD patients were included from the Beijing Rehabilitation Hospital database. Only patients below Hoehn and Yahr stage III were included. The analysis showed that the severity of motor symptoms could be estimated by the individualized functional connectivity between the visual network and sensorimotor network in early-stage disease. The results reveal individual-level connectivity biomarkers related to motor symptoms and emphasize the importance of individual differences in the prediction of the treatment response of PD.
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Affiliation(s)
- Zhongyan Shi
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Bo Jiang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Tiantian Liu
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Li Wang
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Guangying Pei
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Dingjie Suo
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
| | - Jian Zhang
- Intelligent Robotics Institute, School of Mechatronical Engineering, Beijing Institute of Technology, Beijing 100081, China
| | - Shintaro Funahashi
- Advanced Research Institute of Multidisciplinary Sciences, Beijing Institute of Technology, Beijing 100081, China
| | - Jinglong Wu
- School of Medical Technology, Beijing Institute of Technology, Beijing 100081, China
| | - Tianyi Yan
- School of Life Science, Beijing Institute of Technology, Beijing 100081, China
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11
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Saccà V, Novellino F, Salsone M, Abou Jaoude M, Quattrone A, Chiriaco C, Madrigal JLM, Quattrone A. Challenging functional connectivity data: machine learning application on essential tremor recognition. Neurol Sci 2023; 44:199-207. [PMID: 36123559 DOI: 10.1007/s10072-022-06400-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 08/16/2022] [Indexed: 01/10/2023]
Abstract
BACKGROUND AND AIMS This paper aimed to investigate the usefulness of applying machine learning on resting-state fMRI connectivity data to recognize the pattern of functional changes in essential tremor (ET), a disease characterized by slight brain abnormalities, often difficult to detect using univariate analysis. METHODS We trained a support vector machine with a radial kernel on the mean signals extracted by 14 brain networks obtained from resting-state fMRI scans of 18 ET and 19 healthy control (CTRL) subjects. Classification performance between pathological and control subjects was evaluated using a tenfold cross-validation. Recursive feature elimination was performed to rank the importance of the extracted features. Moreover, univariate analysis using Mann-Whitney U test was also performed. RESULTS The machine learning algorithm achieved an AUC of 0.75, with four networks (language, primary visual, cerebellum, and attention), which have an essential role in ET pathophysiology, being selected as the most important features for classification. By contrast, the univariate analysis was not able to find significant results among these two conditions. CONCLUSION The machine learning approach identifies the changes in functional connectivity of ET patients, representing a promising instrument to discriminate specific pathological conditions and find novel functional biomarkers in resting-state fMRI studies.
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Affiliation(s)
- Valeria Saccà
- Department of Medical and Surgical Sciences, University Magna Graecia, Catanzaro, Italy.,Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Fabiana Novellino
- Department of Pharmacology and Toxicology, School of Medicine, Universidad Complutense de Madrid (UCM), Av. Complutense s/n, 28040, Madrid, Spain. .,Instituto de Investigación Neuroquímica (IUINQ-UCM), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Investigación Sanitaria Hospital, 12 de Octubre (Imas12), Madrid, Spain. .,Institute of Bioimaging and Molecular Physiology (IBFM), National Research Council, Catanzaro, Italy.
| | - Maria Salsone
- Institute of Molecular Bioimaging and Physiology, National Research Council, Milan, Italy.,Sleep Disorders Center, Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | | | - Andrea Quattrone
- Institute of Neurology, University Magna Graecia, Catanzaro, Italy.,Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, University College London, London, UK
| | | | - José L M Madrigal
- Department of Pharmacology and Toxicology, School of Medicine, Universidad Complutense de Madrid (UCM), Av. Complutense s/n, 28040, Madrid, Spain.,Instituto de Investigación Neuroquímica (IUINQ-UCM), Centro de Investigación Biomédica en Red de Salud Mental (CIBERSAM), Instituto de Investigación Sanitaria Hospital, 12 de Octubre (Imas12), Madrid, Spain
| | - Aldo Quattrone
- Institute of Bioimaging and Molecular Physiology (IBFM), National Research Council, Catanzaro, Italy. .,Neuroscience Research Center, Magna Graecia University, Catanzaro, Italy.
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12
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Albano L, Agosta F, Basaia S, Cividini C, Stojkovic T, Sarasso E, Stankovic I, Tomic A, Markovic V, Canu E, Stefanova E, Mortini P, Kostic VS, Filippi M. Altered Functional Connectivity of the Subthalamic Nucleus in Parkinson's Disease: Focus on Candidates for Deep Brain Stimulation. JOURNAL OF PARKINSON'S DISEASE 2023; 13:797-809. [PMID: 37270810 PMCID: PMC10473091 DOI: 10.3233/jpd-230005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 05/13/2023] [Indexed: 06/06/2023]
Abstract
BACKGROUND The hypothesis that the effectiveness of deep brain stimulation (DBS) in Parkinson's disease (PD) would be related to connectivity dysfunctions between the site of stimulation and other brain regions is growing. OBJECTIVE To investigate how the subthalamic nucleus (STN), the most frequently used DBS target for PD, is functionally linked to other brain regions in PD patients according to DBS eligibility. METHODS Clinical data and resting-state functional MRI were acquired from 60 PD patients and 60 age- and sex-matched healthy subjects within an ongoing longitudinal project. PD patients were divided into 19 patients eligible for DBS and 41 non-candidates. Bilateral STN were selected as regions of interest and a seed-based functional MRI connectivity analysis was performed. RESULTS A decreased functional connectivity between STN and sensorimotor cortex in both PD patient groups compared to controls was found. Whereas an increased functional connectivity between STN and thalamus was found in PD patient groups relative to controls. Candidates for DBS showed a decreased functional connectivity between bilateral STN and bilateral sensorimotor areas relative to non-candidates. In patients eligible for DBS, a weaker STN functional connectivity with left supramarginal and angular gyri was related with a more severe rigidity and bradykinesia whereas a higher connectivity between STN and cerebellum/pons was related to poorer tremor score. CONCLUSION Our results suggest that functional connectivity of STN varies among PD patients eligible or not for DBS. Future studies would confirm whether DBS modulates and restores functional connectivity between STN and sensorimotor areas in treated patients.
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Affiliation(s)
- Luigi Albano
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Tanja Stojkovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Elisabetta Sarasso
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Iva Stankovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Aleksandra Tomic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladana Markovic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Elisa Canu
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Elka Stefanova
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Pietro Mortini
- Neurosurgery and Gamma Knife Radiosurgery Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Vladimir S. Kostic
- Clinic of Neurology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS Ospedale San Raffaele, Milan, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- Neurology Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurorehabilitation Unit, IRCCS Ospedale San Raffaele, Milan, Italy
- Neurophysiology Service, IRCCS Ospedale San Raffaele, Milan, Italy
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13
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Stylianou O, Kaposzta Z, Czoch A, Stefanovski L, Yabluchanskiy A, Racz FS, Ritter P, Eke A, Mukli P. Scale-Free Functional Brain Networks Exhibit Increased Connectivity, Are More Integrated and Less Segregated in Patients with Parkinson's Disease following Dopaminergic Treatment. FRACTAL AND FRACTIONAL 2022; 6:737. [PMID: 38106971 PMCID: PMC10723163 DOI: 10.3390/fractalfract6120737] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Dopaminergic treatment (DT), the standard therapy for Parkinson's disease (PD), alters the dynamics of functional brain networks at specific time scales. Here, we explore the scale-free functional connectivity (FC) in the PD population and how it is affected by DT. We analyzed the electroencephalogram of: (i) 15 PD patients during DT (ON) and after DT washout (OFF) and (ii) 16 healthy control individuals (HC). We estimated FC using bivariate focus-based multifractal analysis, which evaluated the long-term memory ( H ( 2 ) ) and multifractal strength ( Δ H 15 ) of the connections. Subsequent analysis yielded network metrics (node degree, clustering coefficient and path length) based on FC estimated by H ( 2 ) or Δ H 15 . Cognitive performance was assessed by the Mini Mental State Examination (MMSE) and the North American Adult Reading Test (NAART). The node degrees of the Δ H 15 networks were significantly higher in ON, compared to OFF and HC, while clustering coefficient and path length significantly decreased. No alterations were observed in the H ( 2 ) networks. Significant positive correlations were also found between the metrics of H ( 2 ) networks and NAART scores in the HC group. These results demonstrate that DT alters the multifractal coupled dynamics in the brain, warranting the investigation of scale-free FC in clinical and pharmacological studies.
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Affiliation(s)
- Orestis Stylianou
- Department of Physiology, Semmelweis University, 1094 Budapest, Hungary
- Institute of Translational Medicine, Semmelweis University, 1094 Budapest, Hungary
- Berlin Institute of Health at Charité, University Hospital Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité-University Hospital Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Zalan Kaposzta
- Department of Physiology, Semmelweis University, 1094 Budapest, Hungary
| | - Akos Czoch
- Department of Physiology, Semmelweis University, 1094 Budapest, Hungary
| | - Leon Stefanovski
- Berlin Institute of Health at Charité, University Hospital Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité-University Hospital Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
| | - Andriy Yabluchanskiy
- Vascular Cognitive Impairment and Neurodegeneration Program, Oklahoma Center for Geroscience and Healthy Brain Aging, Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, 975 NE 10th Street, BRC, Oklahoma City, OK 73104, USA
| | - Frigyes Samuel Racz
- Department of Physiology, Semmelweis University, 1094 Budapest, Hungary
- Department of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA
| | - Petra Ritter
- Berlin Institute of Health at Charité, University Hospital Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité-University Hospital Berlin, Corporate Member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience Berlin, 10115 Berlin, Germany
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117 Berlin, Germany
- Einstein Center Digital Future, Wilhelmstraße 67, 10117 Berlin, Germany
| | - Andras Eke
- Department of Physiology, Semmelweis University, 1094 Budapest, Hungary
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 300 Cedar Street, New Haven, CT 06520, USA
| | - Peter Mukli
- Department of Physiology, Semmelweis University, 1094 Budapest, Hungary
- Vascular Cognitive Impairment and Neurodegeneration Program, Oklahoma Center for Geroscience and Healthy Brain Aging, Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, 975 NE 10th Street, BRC, Oklahoma City, OK 73104, USA
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14
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Padmakumar S, Kulkarni P, Ferris CF, Bleier BS, Amiji MM. Traumatic brain injury and the development of parkinsonism: Understanding pathophysiology, animal models, and therapeutic targets. Biomed Pharmacother 2022; 149:112812. [PMID: 35290887 PMCID: PMC9050934 DOI: 10.1016/j.biopha.2022.112812] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Revised: 03/06/2022] [Accepted: 03/08/2022] [Indexed: 02/06/2023] Open
Abstract
The clinical translation of therapeutic approaches to combat debilitating neurodegenerative conditions, such as Parkinson's disease (PD), remains as an urgent unmet challenge. The strong molecular association between the pathogenesis of traumatic brain injury (TBI) and the development of parkinsonism in humans has been well established. Therefore, a lot of ongoing research aims to investigate this pathology overlap in-depth, to exploit the common targets of TBI and PD for development of more effective and long-term treatment strategies. This review article intends to provide a detailed background on TBI pathophysiology and its established overlap with PD with an additional emphasis on the recent findings about their effect on perivascular clearance. Although, the traditional animal models of TBI and PD are still being considered, there is a huge focus on the development of combinatory hybrid animal models coupling concussion with the pre-established PD models for a better recapitulation of the human context of PD pathogenesis. Lastly, the therapeutic targets for TBI and PD, and the contemporary research involving exosomes, DNA vaccines, miRNA, gene therapy and gene editing for the development of potential candidates are discussed, along with the recent development of lesser invasive and promising central nervous system (CNS) drug delivery strategies.
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Affiliation(s)
- Smrithi Padmakumar
- Department of Pharmaceutical Sciences, School of Pharmacy and Department of Chemical Engineering, College of Engineering, Northeastern University, Boston, MA, United States of America
| | - Praveen Kulkarni
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, United States of America
| | - Craig F Ferris
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, United States of America
| | - Benjamin S Bleier
- Massachusetts Eye and Ear Infirmary, Harvard Medical School, Boston, MA, United States of America
| | - Mansoor M Amiji
- Department of Pharmaceutical Sciences, School of Pharmacy and Department of Chemical Engineering, College of Engineering, Northeastern University, Boston, MA, United States of America.
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15
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Associations between resting-state functional connectivity changes and prolonged benefits of writing training in Parkinson's disease. J Neurol 2022; 269:4696-4707. [PMID: 35420350 DOI: 10.1007/s00415-022-11098-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/21/2022] [Accepted: 03/23/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Our earlier work showed that automaticity and retention of writing skills improved with intensive writing training in Parkinson's disease (PD). However, whether this training changed the resting-state networks in the brain and how these changes underlie retention of motor learning is currently unknown. OBJECTIVE To examine changes in resting-state functional connectivity (rs-FC) and their relation to behavioral changes immediately after writing training and at 6 week follow-up. METHODS Twenty-five PD patients underwent resting-state fMRI (ON medication) before and after 6 weeks writing training. Motor learning was evaluated with a dual task paradigm pre- and post-training and at follow-up. Next, pre-post within-network changes in rs-FC were identified by an independent component analysis. Significant clusters were used as seeds in ROI-to-ROI analyses and rs-FC changes were correlated with changes in behavioral performance over time. RESULTS Similar to our larger cohort findings, writing accuracy in single and dual task conditions improved post-training and this was maintained at follow-up. Connectivity within the dorsal attentional network (DAN) increased pre-post training, particularly with the right superior and middle temporal gyrus (rS/MTG). This cluster also proved more strongly connected to parietal and frontal areas and to cerebellar regions. Behavioral improvements from pre- to post-training and follow-up correlated with increased rs-FC between rS/MTG and the cerebellum. CONCLUSIONS Training-driven improvements in dual task writing led to functional reorganization within the DAN and increased connectivity with cerebellar areas. These changes were associated with the retention of writing gains and could signify task-specific neural changes or an inability to segregate neural networks.
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16
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Functional connectivity in Parkinson's disease candidates for deep brain stimulation. NPJ Parkinsons Dis 2022; 8:4. [PMID: 35013326 PMCID: PMC8748462 DOI: 10.1038/s41531-021-00268-6] [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: 05/27/2021] [Accepted: 12/10/2021] [Indexed: 11/29/2022] Open
Abstract
This study aimed to identify functional neuroimaging patterns anticipating the clinical indication for deep brain stimulation (DBS) in patients with Parkinson’s disease (PD). A cohort of prospectively recruited patients with PD underwent neurological evaluations and resting-state functional MRI (RS-fMRI) at baseline and annually for 4 years. Patients were divided into two groups: 19 patients eligible for DBS over the follow-up and 41 patients who did not meet the criteria to undergo DBS. Patients selected as candidates for DBS did not undergo surgery at this stage. Sixty age- and sex-matched healthy controls performed baseline evaluations. Graph analysis and connectomics assessed global and local topological network properties and regional functional connectivity at baseline and at each time point. At baseline, network analysis showed a higher mean nodal strength, local efficiency, and clustering coefficient of the occipital areas in candidates for DBS over time relative to controls and patients not eligible for DBS. The occipital hyperconnectivity pattern was confirmed by regional analysis. At baseline, a decreased functional connectivity between basal ganglia and sensorimotor/frontal networks was found in candidates for DBS compared to patients not eligible for surgery. In the longitudinal analysis, patient candidate for DBS showed a progressively decreased topological brain organization and functional connectivity, mainly in the posterior brain networks, and a progressively increased connectivity of basal ganglia network compared to non-candidates for DBS. RS-fMRI may support the clinical indication to DBS and could be useful in predicting which patients would be eligible for DBS in the earlier stages of PD.
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17
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Iarkov A, Mendoza C, Echeverria V. Cholinergic Receptor Modulation as a Target for Preventing Dementia in Parkinson's Disease. Front Neurosci 2021; 15:665820. [PMID: 34616271 PMCID: PMC8488354 DOI: 10.3389/fnins.2021.665820] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 08/26/2021] [Indexed: 12/20/2022] Open
Abstract
Parkinson’s disease (PD) is a neurodegenerative condition characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) in the midbrain resulting in progressive impairment in cognitive and motor abilities. The physiological and molecular mechanisms triggering dopaminergic neuronal loss are not entirely defined. PD occurrence is associated with various genetic and environmental factors causing inflammation and mitochondrial dysfunction in the brain, leading to oxidative stress, proteinopathy, and reduced viability of dopaminergic neurons. Oxidative stress affects the conformation and function of ions, proteins, and lipids, provoking mitochondrial DNA (mtDNA) mutation and dysfunction. The disruption of protein homeostasis induces the aggregation of alpha-synuclein (α-SYN) and parkin and a deficit in proteasome degradation. Also, oxidative stress affects dopamine release by activating ATP-sensitive potassium channels. The cholinergic system is essential in modulating the striatal cells regulating cognitive and motor functions. Several muscarinic acetylcholine receptors (mAChR) and nicotinic acetylcholine receptors (nAChRs) are expressed in the striatum. The nAChRs signaling reduces neuroinflammation and facilitates neuronal survival, neurotransmitter release, and synaptic plasticity. Since there is a deficit in the nAChRs in PD, inhibiting nAChRs loss in the striatum may help prevent dopaminergic neurons loss in the striatum and its pathological consequences. The nAChRs can also stimulate other brain cells supporting cognitive and motor functions. This review discusses the cholinergic system as a therapeutic target of cotinine to prevent cognitive symptoms and transition to dementia in PD.
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Affiliation(s)
- Alexandre Iarkov
- Laboratorio de Neurobiología, Facultad de Ciencias de la Salud, Universidad San Sebastián, Concepción, Chile
| | - Cristhian Mendoza
- Laboratorio de Neurobiología, Facultad de Ciencias de la Salud, Universidad San Sebastián, Concepción, Chile
| | - Valentina Echeverria
- Laboratorio de Neurobiología, Facultad de Ciencias de la Salud, Universidad San Sebastián, Concepción, Chile.,Research & Development Service, Bay Pines VA Healthcare System, Bay Pines, FL, United States
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18
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Simon OB, Buard I, Rojas DC, Holden SK, Kluger BM, Ghosh D. A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography. Sci Rep 2021; 11:19704. [PMID: 34611218 PMCID: PMC8492620 DOI: 10.1038/s41598-021-99167-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 09/21/2021] [Indexed: 11/11/2022] Open
Abstract
Graph theory-based approaches are efficient tools for detecting clustering and group-wise differences in high-dimensional data across a wide range of fields, such as gene expression analysis and neural connectivity. Here, we examine data from a cross-sectional, resting-state magnetoencephalography study of 89 Parkinson’s disease patients, and use minimum-spanning tree (MST) methods to relate severity of Parkinsonian cognitive impairment to neural connectivity changes. In particular, we implement the two-sample multivariate-runs test of Friedman and Rafsky (Ann Stat 7(4):697–717, 1979) and find it to be a powerful paradigm for distinguishing highly significant deviations from the null distribution in high-dimensional data. We also generalize this test for use with greater than two classes, and show its ability to localize significance to particular sub-classes. We observe multiple indications of altered connectivity in Parkinsonian dementia that may be of future use in diagnosis and prediction.
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Affiliation(s)
- Olivier B Simon
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Isabelle Buard
- Department of Neurology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Donald C Rojas
- Department of Psychology, Colorado State University, Fort Collins, CO, USA
| | - Samantha K Holden
- Department of Neurology, University of Colorado School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Benzi M Kluger
- Department of Neurology, University of Rochester Medical Center, Rochester, NY, USA
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
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19
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Tremblay C, Iravani B, Aubry Lafontaine É, Steffener J, Fischmeister FPS, Lundström JN, Frasnelli J. Parkinson's Disease Affects Functional Connectivity within the Olfactory-Trigeminal Network. JOURNAL OF PARKINSONS DISEASE 2021; 10:1587-1600. [PMID: 32597818 DOI: 10.3233/jpd-202062] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Olfactory dysfunction (OD) is a frequent symptom of Parkinson's disease (PD) that appears years prior to diagnosis. Previous studies suggest that PD-related OD is different from non-parkinsonian forms of olfactory dysfunction (NPOD) as PD patients maintain trigeminal sensitivity as opposed to patients with NPOD who typically exhibit reduced trigeminal sensitivity. We hypothesize the presence of a specific alteration of functional connectivity between trigeminal and olfactory processing areas in PD. OBJECTIVE We aimed to assess potential differences in functional connectivity within the chemosensory network in 15 PD patients and compared them to 15 NPOD patients, and to 15 controls. METHODS Functional MRI scanning session included resting-state and task-related scans where participants carried out an olfactory and a trigeminal task. We compared functional connectivity, using a seed-based correlation approach, and brain network modularity of the chemosensory network. RESULTS PD patients had impaired functional connectivity within the chemosensory network while no such changes were observed for NPOD patients. No group differences we found in modularity of the identified networks. Both patient groups exhibited impaired connectivity when executing an olfactory task, while network modularity was significantly weaker for PD patients than both other groups. When performing a trigeminal task, no changes were found for PD patients, but NPOD patients exhibited impaired connectivity. Conversely, PD patients exhibited a significantly higher network modularity than both other groups. CONCLUSION In summary, the specific pattern of functional connectivity and chemosensory network recruitment in PD-related OD may explain distinct behavioral chemosensory features in PD when compared to NPOD patients and healthy controls.
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Affiliation(s)
- Cécilia Tremblay
- Department of Anatomy, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
| | - Behzad Iravani
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Émilie Aubry Lafontaine
- Department of Anatomy, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada
| | - Jason Steffener
- Faculty of Health Sciences, University of Ottawa, Ottawa, Ontario, Canada
| | | | - Johan N Lundström
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Johannes Frasnelli
- Department of Anatomy, Université du Québec à Trois-Rivières, Trois-Rivières, Québec, Canada.,Research Center, Sacré-Coeur Hospital of Montrealéal, Québec, Canada
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20
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Filippi M, Basaia S, Sarasso E, Stojkovic T, Stankovic I, Fontana A, Tomic A, Piramide N, Stefanova E, Markovic V, Kostic VS, Agosta F. Longitudinal brain connectivity changes and clinical evolution in Parkinson's disease. Mol Psychiatry 2021; 26:5429-5440. [PMID: 32409731 DOI: 10.1038/s41380-020-0770-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 04/23/2020] [Accepted: 04/29/2020] [Indexed: 11/09/2022]
Abstract
Longitudinal connectivity studies might guide our understanding of the underlying neurodegenerative processes. We report the results of a longitudinal study in patients at different stages of Parkinson's disease (PD), who performed motor and non-motor evaluations and serial resting state (RS) functional MRI (fMRI). Cluster analysis was applied to demographic and clinical data of 146 PD patients to define disease subtypes. Brain network functional alterations were assessed at baseline in PD relative to 60 healthy controls and every year for a maximum of 4 years in PD groups. Progression of brain network changes were compared between patient clusters using RS fMRI. The contribution of network changes in predicting clinical deterioration was explored. Two main PD clusters were identified: mild PD (86 patients) and moderate-to-severe PD (60 patients), with the latter group being older and having earlier onset, longer PD duration, more severe motor, non-motor and cognitive deficits. Within the mild patient cluster, two clinical subtypes were further identified: mild motor-predominant (43) and mild-diffuse (43), with the latter being older and having more frequent non-motor symptoms. Longitudinal functional connectivity changes vary across patients in different disease stages with the coexistence of hypo- and hyper-connectivity in all subtypes. RS fMRI changes were associated with motor, cognitive and non-motor evolution in PD patients. Baseline RS fMRI presaged clinical and cognitive evolution. Our network perspective was able to define trajectories of functional architecture changes according to PD stages and prognosis. RS fMRI may be an early biomarker of PD motor and non-motor progression.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy. .,Neurology Unit and Neurophysiology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy. .,Vita-Salute San Raffaele University, Milan, Italy.
| | - Silvia Basaia
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta Sarasso
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Tanja Stojkovic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Iva Stankovic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Andrea Fontana
- Unit of Biostatistics, Fondazione IRCCS Casa Sollievo della Sofferenza, San Giovanni Rotondo, Foggia, Italy
| | - Aleksandra Tomic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Noemi Piramide
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
| | - Elka Stefanova
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladana Markovic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vladimir S Kostic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy
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21
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Within- and across-network alterations of the sensorimotor network in Parkinson's disease. Neuroradiology 2021; 63:2073-2085. [PMID: 34019112 PMCID: PMC8589810 DOI: 10.1007/s00234-021-02731-w] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 05/02/2021] [Indexed: 12/03/2022]
Abstract
Purpose Parkinson’s disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. Methods Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. Results There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. Conclusion PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy. Supplementary Information The online version contains supplementary material available at 10.1007/s00234-021-02731-w.
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22
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Tremblay C, Frasnelli J. Olfactory-Trigeminal Interactions in Patients with Parkinson's Disease. Chem Senses 2021; 46:6218692. [PMID: 33835144 DOI: 10.1093/chemse/bjab018] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Olfactory dysfunction (OD) is a highly frequent early non-motor symptom of Parkinson's disease (PD). An important step to potentially use OD for the development of early diagnostic tools of PD is to differentiate PD-related OD from other forms of non-parkinsonian OD (NPOD: postviral, sinunasal, post-traumatic, and idiopathic OD). Measuring non-olfactory chemosensory modalities, especially the trigeminal system, may allow to characterize a PD-specific olfactory profile. We here review the literature on PD-specific chemosensory alteration patterns compared with NPOD. Specifically, we focused on the impact of PD on the trigeminal system and particularly on the interaction between olfactory and trigeminal systems. As this interaction is seemingly affected in a disease-specific manner, we propose a model of interaction between both chemosensory systems that is distinct for PD-related OD and NPOD. These patterns of chemosensory impairment still need to be confirmed in prodromal PD; nevertheless, appropriate chemosensory tests may eventually help to develop diagnostic tools to identify individuals at risks for PD.
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Affiliation(s)
- Cécilia Tremblay
- Department of Anatomy, Université du Québec à Trois-Rivières, 3351 Boulevard des Forges, Trois-Rivières, QC, G9A 5H7, Canada
| | - Johannes Frasnelli
- Department of Anatomy, Université du Québec à Trois-Rivières, 3351 Boulevard des Forges, Trois-Rivières, QC, G9A 5H7, Canada.,Research Center, Sacré-Coeur Hospital of Montreal, 5400 Boulevard Gouin Ouest, Montréal, QC, H4J 1C5, Canada
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23
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Petiet A. Current and Emerging MR Methods and Outcome in Rodent Models of Parkinson's Disease: A Review. Front Neurosci 2021; 15:583678. [PMID: 33897339 PMCID: PMC8058186 DOI: 10.3389/fnins.2021.583678] [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: 07/15/2020] [Accepted: 03/05/2021] [Indexed: 12/03/2022] Open
Abstract
Parkinson’s disease (PD) is a major neurodegenerative disease characterized by massive degeneration of the dopaminergic neurons in the substantia nigra pars compacta, α-synuclein-containing Lewy bodies, and neuroinflammation. Magnetic resonance (MR) imaging plays a crucial role in the diagnosis and monitoring of disease progression and treatment. A variety of MR methods are available to characterize neurodegeneration and other disease features such as iron accumulation and metabolic changes in animal models of PD. This review aims at giving an overview of how those physiopathological features of PD have been investigated using various MR methods in rodent models. Toxin-based and genetic-based models of PD are first described. MR methods for neurodegeneration evaluation, iron load, and metabolism alterations are then detailed, and the main findings are provided in those models. Ultimately, future directions are suggested for neuroinflammation and neuromelanin evaluations in new animal models.
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Affiliation(s)
- Alexandra Petiet
- Centre de Neuroimagerie de Recherche, Institut du Cerveau, Paris, France.,Inserm U1127, CNRS UMR 7225, Sorbonne Universités, Paris, France
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24
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Iyer KK, Au TR, Angwin AJ, Copland DA, Dissanayaka NN. Theta and gamma connectivity is linked with affective and cognitive symptoms in Parkinson's disease. J Affect Disord 2020; 277:875-884. [PMID: 33065829 DOI: 10.1016/j.jad.2020.08.086] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Revised: 07/16/2020] [Accepted: 08/24/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND The progression of Parkinson's disease (PD) can often exacerbate symptoms of depression, anxiety, and/or cognitive impairment. In this study, we explore the possibility that multiple brain network responses are associated with symptoms of depression, anxiety and cognitive impairment in PD. This association is likely to provide insights into a single multivariate relationship, where common affective symptoms occurring in PD cohorts are related with alterations to electrophysiological response. METHODS 70 PD patients and 21 healthy age-matched controls (HC) participated in a high-density electroencephalography (EEG) study. Functional connectivity differences between PD and HC groups of oscillatory activity at rest and during completion of an emotion-cognition task were examined to identify key brain oscillatory activities. A canonical correlation analysis (CCA) was applied to identify a putative multivariate relationship between connectivity patterns and affective symptoms in PD groups. RESULTS A CCA analysis identified a single mode of co-variation linking theta and gamma connectivity with affective symptoms in PD groups. Increases in frontotemporal gamma, frontal and parietal theta connectivity were related with increased anxiety and cognitive impairment. Decreases in temporal region theta and frontoparietal gamma connectivity were associated with higher depression ratings and PD patient age. LIMITATIONS This study only reports on optimal dosage of dopaminergic treatment ('on' state) in PD and did not investigate at "off" medication". CONCLUSIONS Theta and gamma connectivity during rest and task-states are linked to affective and cognitive symptoms within fronto-temporo-parietal networks, suggesting a potential assessment avenue for understanding brain-behaviour associations in PD with electrophysiological task paradigms.
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Affiliation(s)
- Kartik K Iyer
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Royal Brisbane & Women's Hospital, Herston, QLD 4029, Brisbane, Australia; Clinical Brain Networks group, QIMR Berghofer Medical Research Institute, Australia; School of Health & Rehabilitation Sciences, The University of Queensland, St Lucia, QLD 4067, Brisbane, Australia
| | - Tiffany R Au
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Royal Brisbane & Women's Hospital, Herston, QLD 4029, Brisbane, Australia
| | - Anthony J Angwin
- School of Health & Rehabilitation Sciences, The University of Queensland, St Lucia, QLD 4067, Brisbane, Australia
| | - David A Copland
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Royal Brisbane & Women's Hospital, Herston, QLD 4029, Brisbane, Australia; School of Health & Rehabilitation Sciences, The University of Queensland, St Lucia, QLD 4067, Brisbane, Australia
| | - Nadeeka N Dissanayaka
- UQ Centre for Clinical Research, Faculty of Medicine, The University of Queensland, Royal Brisbane & Women's Hospital, Herston, QLD 4029, Brisbane, Australia; Department of Neurology, Royal Brisbane & Women's Hospital, Herston, QLD 4029, Brisbane, Australia; School of Psychology, The University of Queensland, St Lucia, QLD 4067, Brisbane, Australia.
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25
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Watts J, Khojandi A, Shylo O, Ramdhani RA. Machine Learning's Application in Deep Brain Stimulation for Parkinson's Disease: A Review. Brain Sci 2020; 10:E809. [PMID: 33139614 PMCID: PMC7694006 DOI: 10.3390/brainsci10110809] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 10/16/2020] [Accepted: 10/29/2020] [Indexed: 01/07/2023] Open
Abstract
Deep brain stimulation (DBS) is a surgical treatment for advanced Parkinson's disease (PD) that has undergone technological evolution that parallels an expansion in clinical phenotyping, neurophysiology, and neuroimaging of the disease state. Machine learning (ML) has been successfully used in a wide range of healthcare problems, including DBS. As computational power increases and more data become available, the application of ML in DBS is expected to grow. We review the literature of ML in DBS and discuss future opportunities for such applications. Specifically, we perform a comprehensive review of the literature from PubMed, the Institute for Scientific Information's Web of Science, Cochrane Database of Systematic Reviews, and Institute of Electrical and Electronics Engineers' (IEEE) Xplore Digital Library for ML applications in DBS. These studies are broadly placed in the following categories: (1) DBS candidate selection; (2) programming optimization; (3) surgical targeting; and (4) insights into DBS mechanisms. For each category, we provide and contextualize the current body of research and discuss potential future directions for the application of ML in DBS.
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Affiliation(s)
- Jeremy Watts
- Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USA; (J.W.); (A.K.); (O.S.)
| | - Anahita Khojandi
- Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USA; (J.W.); (A.K.); (O.S.)
| | - Oleg Shylo
- Department of Industrial and Systems Engineering, University of Tennessee, Knoxville, TN 37996, USA; (J.W.); (A.K.); (O.S.)
| | - Ritesh A. Ramdhani
- Department of Neurology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
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26
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Wang X, Cao Z, Liu G, Liu Z, Jiang Y, Ma H, Wang Z, Yang Y, Chen H, Feng T. Clinical Characteristics and Electrophysiological Biomarkers of Parkinson's Disease Developed From Essential Tremor. Front Neurol 2020; 11:582471. [PMID: 33193041 PMCID: PMC7658334 DOI: 10.3389/fneur.2020.582471] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 09/22/2020] [Indexed: 01/16/2023] Open
Abstract
Background and Objective: Parkinson's disease developed from essential tremor (ET-PD) is a distinct clinical syndrome that is different from essential tremor (ET) and Parkinson's disease (PD). There is currently a lack of research on ET-PD. Tremor characteristics (amplitude and frequency) are primary quantitative indexes for diagnosing and monitoring of tremors. In this study, we aimed to explore specific clinical and electrophysiological biomarkers for the identification of ET-PD. Methods: The study included patients with ET-PD (n = 22), ET (n = 42), and tremor-dominant PD (t-PD, n = 47). We collected demographic data, clinical characteristics (including motor and non-motor symptoms), and tremor analysis. The frequency, amplitude, contracting patterns of resting tremor and postural tremor were collected. The analysis of ET-PD and ET/t-PD was compared. The receiver operating characteristic (ROC) curve was used to analyze the electrophysiological features in distinguishing ET-PD from ET or t-PD. Results: Compared with ET, hyposmia, bradykinesia, rigidity, postural abnormality, and resting tremor were more common in the ET-PD group (P = 0.01, 0.003, 0.001, 0.001, 0.019, respectively). The postural tremor frequencies of the head, upper limbs, and lower limbs were significantly lower in the ET-PD than in the ET (P = 0.007, 0.003, 0.035, respectively), which were the most appropriate variables for distinguishing ET-PD from ET (AUC: 0.775, 0.727, and 0.701, respectively). Compared with t-PD, bradykinesia, rigidity, postural abnormality (both P < 0.001), and resting tremor (P = 0.024) were less common in the ET-PD. The postural tremor amplitudes of the head and upper limbs were significantly higher in the ET-PD than in the t-PD (P = 0.022, 0.001, respectively), which were the most appropriate variables for distinguishing ET-PD from t-PD (AUC: 0.793 and 0.716). Conclusions: Hyposmia and electrophysiological biomarkers (postural tremor frequencies and amplitudes) help early recognition of ET-PD.
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Affiliation(s)
- Xuemei Wang
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhentang Cao
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Genliang Liu
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhu Liu
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Ying Jiang
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Huizi Ma
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Zhan Wang
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yaqin Yang
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Huimin Chen
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Tao Feng
- Center for Movement Disorders Disease, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Beijing, China
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27
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Li W, Lao-Kaim NP, Roussakis AA, Martín-Bastida A, Valle-Guzman N, Paul G, Soreq E, Daws RE, Foltynie T, Barker RA, Hampshire A, Piccini P. Longitudinal functional connectivity changes related to dopaminergic decline in Parkinson's disease. Neuroimage Clin 2020; 28:102409. [PMID: 32916466 PMCID: PMC7490914 DOI: 10.1016/j.nicl.2020.102409] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 08/24/2020] [Accepted: 08/30/2020] [Indexed: 01/02/2023]
Abstract
BACKGROUND Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated that basal ganglia functional connectivity is altered in Parkinson's disease (PD) as compared to healthy controls. However, such functional connectivity alterations have not been related to the dopaminergic deficits that occurs in PD over time. OBJECTIVES To examine whether functional connectivity impairments are correlated with dopaminergic deficits across basal ganglia subdivisions in patients with PD both cross-sectionally and longitudinally. METHODS We assessed resting-state functional connectivity of basal ganglia subdivisions and dopamine transporter density using 11C-PE2I PET in thirty-four PD patients at baseline. Of these, twenty PD patients were rescanned after 19.9 ± 3.8 months. A seed-based approach was used to analyze resting-state fMRI data. 11C-PE2I binding potential (BPND) was calculated for each participant. PD patients were assessed for disease severity. RESULTS At baseline, PD patients with greater dopaminergic deficits, as measured with 11C-PE2I PET, showed larger decreases in posterior putamen functional connectivity with the midbrain and pallidum. Reduced functional connectivity of the posterior putamen with the thalamus, midbrain, supplementary motor area and sensorimotor cortex over time were significantly associated with changes in DAT density over the same period. Furthermore, increased motor disability was associated with lower intraregional functional connectivity of the posterior putamen. CONCLUSIONS Our findings suggest that basal ganglia functional connectivity is related to integrity of dopaminergic system in patients with PD. Application of resting-state fMRI in a large cohort and longitudinal scanning may be a powerful tool for assessing underlying PD pathology and its progression.
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Affiliation(s)
- Weihua Li
- Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences, Imperial College London, London W12 0NN, United Kingdom; Department of Radiology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
| | - Nick P Lao-Kaim
- Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences, Imperial College London, London W12 0NN, United Kingdom
| | - Andreas-Antonios Roussakis
- Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences, Imperial College London, London W12 0NN, United Kingdom
| | - Antonio Martín-Bastida
- Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences, Imperial College London, London W12 0NN, United Kingdom; Department of Neurology and Neurosciences, Clínica universidad de Navarra, Pamplona-Madrid, Spain
| | - Natalie Valle-Guzman
- John Van Geest Centre for Brain Repair, University of Cambridge, Cambridge CB2 0PY, United Kingdom
| | - Gesine Paul
- Translational Neurology Group, Department of Clinical Sciences, Wallenberg Neuroscience Centre, Lund University, Lund 221 84, Sweden; Division of Neurology, Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund 22185, Sweden
| | - Eyal Soreq
- Imperial College London, Division of Brain Sciences, Computational Cognitive & Clinical Neuroimaging Lab (C(3)NL), London W12 0NN, United Kingdom
| | - Richard E Daws
- Imperial College London, Division of Brain Sciences, Computational Cognitive & Clinical Neuroimaging Lab (C(3)NL), London W12 0NN, United Kingdom
| | - Tom Foltynie
- Sobell Department of Motor Neuroscience, UCL Institute of Neurology, National Hospital for Neurology and Neurosurgery, London WC1N 3BG, United Kingdom
| | - Roger A Barker
- John Van Geest Centre for Brain Repair, University of Cambridge, Cambridge CB2 0PY, United Kingdom
| | - Adam Hampshire
- Imperial College London, Division of Brain Sciences, Computational Cognitive & Clinical Neuroimaging Lab (C(3)NL), London W12 0NN, United Kingdom
| | - Paola Piccini
- Centre for Neurodegeneration and Neuroinflammation, Division of Brain Sciences, Imperial College London, London W12 0NN, United Kingdom
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28
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Chase BA, Markopoulou K. Olfactory Dysfunction in Familial and Sporadic Parkinson's Disease. Front Neurol 2020; 11:447. [PMID: 32547477 PMCID: PMC7273509 DOI: 10.3389/fneur.2020.00447] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 04/27/2020] [Indexed: 12/26/2022] Open
Abstract
This minireview discusses our current understanding of the olfactory dysfunction that is frequently observed in sporadic and familial forms of Parkinson's disease and parkinsonian syndromes. We review the salient characteristics of olfactory dysfunction in these conditions, discussing its prevalence and characteristics, how neuronal processes and circuits are altered in Parkinson's disease, and what is assessed by clinically used measures of olfactory function. We highlight how studies of monogenic Parkinson's disease and investigations in ethnically diverse populations have contributed to understanding the mechanisms underlying olfactory dysfunction. Furthermore, we discuss how imaging and system-level approaches have been used to understand the pathogenesis of olfactory dysfunction. We discuss the challenging, remaining gaps in understanding the basis of olfactory dysfunction in neurodegeneration. We propose that insights could be obtained by following longitudinal cohorts with familial forms of Parkinson's disease using a combination of approaches: a multifaceted longitudinal assessment of olfactory function during disease progression is essential to identify not only how dysfunction arises, but also to address its relationship to motor and non-motor Parkinson's disease symptoms. An assessment of cohorts having monogenic forms of Parkinson's disease, available within the Genetic Epidemiology of Parkinson's Disease (GEoPD), as well as other international consortia, will have heuristic value in addressing the complexity of olfactory dysfunction in the context of the neurodegenerative process. This will inform our understanding of Parkinson's disease as a multisystem disorder and facilitate the more effective use of olfactory dysfunction assessment in identifying prodromal Parkinson's disease and understanding disease progression.
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Affiliation(s)
- Bruce A. Chase
- Department of Biology, University of Nebraska at Omaha, Omaha, NE, United States
| | - Katerina Markopoulou
- Department of Neurology, NorthShore University HealthSystem, Evanston, IL, United States
- Department of Neurology, University of Chicago, Chicago, IL, United States
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29
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Ruppert MC, Greuel A, Tahmasian M, Schwartz F, Stürmer S, Maier F, Hammes J, Tittgemeyer M, Timmermann L, van Eimeren T, Drzezga A, Eggers C. Network degeneration in Parkinson’s disease: multimodal imaging of nigro-striato-cortical dysfunction. Brain 2020; 143:944-959. [DOI: 10.1093/brain/awaa019] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Revised: 11/21/2019] [Accepted: 12/11/2019] [Indexed: 11/14/2022] Open
Abstract
Abstract
The spreading hypothesis of neurodegeneration assumes an expansion of neural pathologies along existing neural pathways. Multimodal neuroimaging studies have demonstrated distinct topographic patterns of cerebral pathologies in neurodegeneration. For Parkinson’s disease the hypothesis so far rests largely on histopathological evidence of α-synuclein spreading in a characteristic pattern and progressive nigrostriatal dopamine depletion. Functional consequences of nigrostriatal dysfunction on cortical activity remain to be elucidated. Our goal was to investigate multimodal imaging correlates of degenerative processes in Parkinson’s disease by assessing dopamine depletion and its potential effect on striatocortical connectivity networks and cortical metabolism in relation to parkinsonian symptoms. We combined 18F-DOPA-PET, 18F-fluorodeoxyglucose (FDG)-PET and resting state functional MRI to multimodally characterize network alterations in Parkinson’s disease. Forty-two patients with mild-to-moderate stage Parkinson’s disease and 14 age-matched healthy control subjects underwent a multimodal imaging protocol and comprehensive clinical examination. A voxel-wise group comparison of 18F-DOPA uptake identified the exact location and extent of putaminal dopamine depletion in patients. Resulting clusters were defined as seeds for a seed-to-voxel functional connectivity analysis. 18F-FDG metabolism was compared between groups at a whole-brain level and uptake values were extracted from regions with reduced putaminal connectivity. To unravel associations between dopaminergic activity, striatocortical connectivity, glucose metabolism and symptom severity, correlations between normalized uptake values, seed-to-cluster β-values and clinical parameters were tested while controlling for age and dopaminergic medication. Aside from cortical hypometabolism, 18F-FDG-PET data for the first time revealed a hypometabolic midbrain cluster in patients with Parkinson’s disease that comprised caudal parts of the bilateral substantia nigra pars compacta. Putaminal dopamine synthesis capacity was significantly reduced in the bilateral posterior putamen and correlated with ipsilateral nigral 18F-FDG uptake. Resting state functional MRI data indicated significantly reduced functional connectivity between the dopamine depleted putaminal seed and cortical areas primarily belonging to the sensorimotor network in patients with Parkinson’s disease. In the inferior parietal cortex, hypoconnectivity in patients was significantly correlated with lower metabolism (left P = 0.021, right P = 0.018). Of note, unilateral network alterations quantified with different modalities corresponded with contralateral motor impairments. In conclusion, our results support the hypothesis that degeneration of nigrostriatal fibres functionally impairs distinct striatocortical connections, disturbing the efficient interplay between motor processing areas and impairing motor control in patients with Parkinson’s disease. The present study is the first to reveal trimodal evidence for network-dependent degeneration in Parkinson’s disease by outlining the impact of functional nigrostriatal pathway impairment on striatocortical functional connectivity networks and cortical metabolism.
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Affiliation(s)
- Marina C Ruppert
- Department of Neurology, University Hospital of Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Andrea Greuel
- Department of Neurology, University Hospital of Marburg, Germany
| | - Masoud Tahmasian
- Institue of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Frank Schwartz
- Department of Neurology, Hospital of the Brothers of Mercy, Trier, Germany
| | - Sophie Stürmer
- Max Planck Institute for Metabolism Research, Cologne, Germany
- Department of Neurology, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
| | - Franziska Maier
- Department of Psychiatry, University Hospital Cologne, Medical Faculty, Cologne, Germany
| | - Jochen Hammes
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Cologne, Germany
- Cluster of Excellence in Cellular Stress and Aging Associated Disease (CECAD), Cologne, Germany
| | - Lars Timmermann
- Department of Neurology, University Hospital of Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
| | - Thilo van Eimeren
- Department of Neurology, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-3), Research Center Jülich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Germany
| | - Alexander Drzezga
- Multimodal Neuroimaging Group, Department of Nuclear Medicine, Medical Faculty and University Hospital Cologne, University Hospital Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Germany
- Cognitive Neuroscience, Institute of Neuroscience and Medicine (INM-2), Research Center Jülich, Germany
| | - Carsten Eggers
- Department of Neurology, University Hospital of Marburg, Germany
- Center for Mind, Brain and Behavior - CMBB, Universities Marburg and Gießen, Germany
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Innate Immunity: A Common Denominator between Neurodegenerative and Neuropsychiatric Diseases. Int J Mol Sci 2020; 21:ijms21031115. [PMID: 32046139 PMCID: PMC7036760 DOI: 10.3390/ijms21031115] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 02/05/2020] [Accepted: 02/05/2020] [Indexed: 02/06/2023] Open
Abstract
The intricate relationships between innate immunity and brain diseases raise increased interest across the wide spectrum of neurodegenerative and neuropsychiatric disorders. Barriers, such as the blood–brain barrier, and innate immunity cells such as microglia, astrocytes, macrophages, and mast cells are involved in triggering disease events in these groups, through the action of many different cytokines. Chronic inflammation can lead to dysfunctions in large-scale brain networks. Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, and frontotemporal dementia, are associated with a substrate of dysregulated immune responses that impair the central nervous system balance. Recent evidence suggests that similar phenomena are involved in psychiatric diseases, such as depression, schizophrenia, autism spectrum disorders, and post-traumatic stress disorder. The present review summarizes and discusses the main evidence linking the innate immunological response in neurodegenerative and psychiatric diseases, thus providing insights into how the responses of innate immunity represent a common denominator between diseases belonging to the neurological and psychiatric sphere. Improved knowledge of such immunological aspects could provide the framework for the future development of new diagnostic and therapeutic approaches.
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Kaut O, Mielacher C, Hurlemann R, Wüllner U. Resting-state fMRI reveals increased functional connectivity in the cerebellum but decreased functional connectivity of the caudate nucleus in Parkinson’s disease. Neurol Res 2020; 42:62-67. [DOI: 10.1080/01616412.2019.1709141] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- Oliver Kaut
- Department of Neurology, University Clinic Bonn, Bonn, Germany
| | - Clemens Mielacher
- Division of Medical Psychology, University Clinic Bonn, Bonn, Germany
| | - René Hurlemann
- Division of Medical Psychology, University Clinic Bonn, Bonn, Germany
| | - Ullrich Wüllner
- Department of Neurology, University Clinic Bonn, Bonn, Germany
- Department of Clinical Studies, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
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Guan X, Guo T, Zeng Q, Wang J, Zhou C, Liu C, Wei H, Zhang Y, Xuan M, Gu Q, Xu X, Huang P, Pu J, Zhang B, Zhang MM. Oscillation-specific nodal alterations in early to middle stages Parkinson's disease. Transl Neurodegener 2019; 8:36. [PMID: 31807287 PMCID: PMC6857322 DOI: 10.1186/s40035-019-0177-5] [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: 07/05/2018] [Accepted: 11/07/2019] [Indexed: 02/26/2023] Open
Abstract
BACKGROUND Different oscillations of brain networks could carry different dimensions of brain integration. We aimed to investigate oscillation-specific nodal alterations in patients with Parkinson's disease (PD) across early stage to middle stage by using graph theory-based analysis. METHODS Eighty-eight PD patients including 39 PD patients in the early stage (EPD) and 49 patients in the middle stage (MPD) and 36 controls were recruited in the present study. Graph theory-based network analyses from three oscillation frequencies (slow-5: 0.01-0.027 Hz; slow-4: 0.027-0.073 Hz; slow-3: 0.073-0.198 Hz) were analyzed. Nodal metrics (e.g. nodal degree centrality, betweenness centrality and nodal efficiency) were calculated. RESULTS Our results showed that (1) a divergent effect of oscillation frequencies on nodal metrics, especially on nodal degree centrality and nodal efficiency, that the anteroventral neocortex and subcortex had high nodal metrics within low oscillation frequencies while the posterolateral neocortex had high values within the relative high oscillation frequency was observed, which visually showed that network was perturbed in PD; (2) PD patients in early stage relatively preserved nodal properties while MPD patients showed widespread abnormalities, which was consistently detected within all three oscillation frequencies; (3) the involvement of basal ganglia could be specifically observed within slow-5 oscillation frequency in MPD patients; (4) logistic regression and receiver operating characteristic curve analyses demonstrated that some of those oscillation-specific nodal alterations had the ability to well discriminate PD patients from controls or MPD from EPD patients at the individual level; (5) occipital disruption within high frequency (slow-3) made a significant influence on motor impairment which was dominated by akinesia and rigidity. CONCLUSIONS Coupling various oscillations could provide potentially useful information for large-scale network and progressive oscillation-specific nodal alterations were observed in PD patients across early to middle stages.
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Affiliation(s)
- Xiaojun Guan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Tao Guo
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Qiaoling Zeng
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Jiaqiu Wang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Cheng Zhou
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Chunlei Liu
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA USA
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA USA
| | - Hongjiang Wei
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA USA
| | - Yuyao Zhang
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA USA
| | - Min Xuan
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Quanquan Gu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Peiyu Huang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
| | - Jiali Pu
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Min-Ming Zhang
- Department of Radiology, The Second Affiliated Hospital, Zhejiang University School of Medicine, No.88 Jiefang Road, Shangcheng District, Hangzhou, 310009 China
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Ferris CF, Morrison TR, Iriah S, Malmberg S, Kulkarni P, Hartner JC, Trivedi M. Evidence of Neurobiological Changes in the Presymptomatic PINK1 Knockout Rat. JOURNAL OF PARKINSONS DISEASE 2019; 8:281-301. [PMID: 29710734 DOI: 10.3233/jpd-171273] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Genetic models of Parkinson's disease (PD) coupled with advanced imaging techniques can elucidate neurobiological disease progression, and can help identify early biomarkers before clinical signs emerge. PTEN-induced putative kinase 1 (PINK1) helps protect neurons from mitochondrial dysfunction, and a mutation in the associated gene is a risk factor for recessive familial PD. The PINK1 knockout (KO) rat is a novel model for familial PD that has not been neuroradiologically characterized for alterations in brain structure/function, alongside behavior, prior to 4 months of age. OBJECTIVE To identify biomarkers of presymptomatic PD in the PINK1 -/- rat at 3 months using magnetic resonance imaging techniques. METHODS At postnatal weeks 12-13; one month earlier than previously reported signs of motor and cognitive dysfunction, this study combined imaging modalities, including assessment of quantitative anisotropy across 171 individual brain areas using an annotated MRI rat brain atlas to identify sites of gray matter alteration between wild-type and PINK1 -/- rats. RESULTS The olfactory system, hypothalamus, thalamus, nucleus accumbens, and cerebellum showed differences in anisotropy between experimental groups. Molecular analyses revealed reduced levels of glutathione, ATP, and elevated oxidative stress in the substantia nigra, striatum and deep cerebellar nuclei. Mitochondrial genes encoding proteins in Complex IV, along with mRNA levels associated with mitochondrial function and genes involved in glutathione synthesis were reduced. Differences in brain structure did not align with any cognitive or motor impairment. CONCLUSIONS These data reveal early markers, and highlight novel brain regions involved in the pathology of PD in the PINK1 -/- rat before behavioral dysfunction occurs.
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Affiliation(s)
- Craig F Ferris
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, USA.,Department of Psychology and Pharmaceutical Sciences, Northeastern University, Boston, MA, USA
| | - Thomas R Morrison
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, USA
| | - Sade Iriah
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, USA
| | - Samantha Malmberg
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, USA
| | - Praveen Kulkarni
- Center for Translational NeuroImaging, Northeastern University, Boston, MA, USA
| | | | - Malav Trivedi
- NOVA Southeastern University, Ft. Lauderdale, FL, USA
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Chung WY, Liu SY, Gao JC, Jiang YJ, Zhang J, Qu SS, Zhang JP, Tan XL, Chen JQ, Wang SX. Modulatory effect of International Standard Scalp Acupuncture on brain activation in the elderly as revealed by resting-state fMRI. Neural Regen Res 2019; 14:2126-2131. [PMID: 31397351 PMCID: PMC6788231 DOI: 10.4103/1673-5374.262590] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
The specific mechanisms by which acupuncture affects the central nervous system are unclear. In the International Standard Scalp Acupuncture system, acupuncture needles are applied at the middle line of the vertex, anterior parietal-temporal oblique line, and the posterior parietal-temporal oblique line. We conducted a single-arm prospective clinical trial in which seven healthy elderly volunteers (three men and four women; 50–70 years old) received International Standard Scalp Acupuncture at MS5 (the mid-sagittal line between Baihui (DU20) and Qianding (DU21)), the left MS6 (line joining Sishencong (EX-HN1) and Xuanli (GB6)), and the left MS7 (line joining DU20 and Qubin (GB7)). After acupuncture, resting-state functional magnetic resonance imaging demonstrated changes in the fractional amplitude of low frequency fluctuations and regional homogeneity in various areas, showing remarkable enhancement of regional homogeneity in the bilateral anterior cingulate, left medial frontal gyrus, supramarginal gyrus, right middle frontal gyrus, and inferior frontal gyrus. Functional connectivity based on a seed region at the right middle frontal gyrus (42, 51, 9) decreased at the bilateral medial superior frontal gyrus. Our data preliminarily indicates that the international standard scalp acupuncture in healthy elderly participants specifcally enhances the correlation between the brain regions involved in cognition and implementation of the brain network regulation system and the surrounding adjacent brain regions. The study was approved by the Ethics Committee of the China-Japan Union Hospital at Jilin University, China, on July 18, 2016 (approval No. 2016ks043).
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Affiliation(s)
- Wai-Yeung Chung
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong Province; School of Chinese Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Song-Yan Liu
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Jing-Chun Gao
- Department of Rehabilitation Medicine, Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong Province, China
| | - Yi-Jing Jiang
- Department of Rehabilitation Medicine, Rehabilitation Hospital, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian Province, China
| | - Jing Zhang
- Department of Neurology, China-Japan Union Hospital of Jilin University, Changchun, Jilin Province, China
| | - Shan-Shan Qu
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Ji-Ping Zhang
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Xiao-Long Tan
- Department of Medical Image, Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jun-Qi Chen
- Department of Rehabilitation Medicine, Third Affiliated Hospital of Southern Medical University, Guangzhou, Guangdong Province, China
| | - Sheng-Xu Wang
- School of Traditional Chinese Medicine, Southern Medical University, Guangzhou, Guangdong Province, China
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Nackaerts E, D'Cruz N, Dijkstra BW, Gilat M, Kramer T, Nieuwboer A. Towards understanding neural network signatures of motor skill learning in Parkinson's disease and healthy aging. Br J Radiol 2019; 92:20190071. [PMID: 30982328 DOI: 10.1259/bjr.20190071] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
In the past decade, neurorehabilitation has been shown to be an effective therapeutic supplement for patients with Parkinson's disease (PD). However, patients still experience severe problems with the consolidation of learned motor skills. Knowledge on the neural correlates underlying this process is thus essential to optimize rehabilitation for PD. This review investigates the existing studies on neural network connectivity changes in relation to motor learning in healthy aging and PD and critically evaluates the imaging methods used from a methodological point of view. The results indicate that despite neurodegeneration there is still potential to modify connectivity within and between motor and cognitive networks in response to motor training, although these alterations largely bypass the most affected regions in PD. However, so far training-related changes are inferred and possible relationships are not substantiated by brain-behavior correlations. Furthermore, the studies included suffer from many methodological drawbacks. This review also highlights the potential for using neural network measures as predictors for the response to rehabilitation, mainly based on work in young healthy adults. We speculate that future approaches, including graph theory and multimodal neuroimaging, may be more sensitive than brain activation patterns and model-based connectivity maps to capture the effects of motor learning. Overall, this review suggests that methodological developments in neuroimaging will eventually provide more detailed knowledge on how neural networks are modified by training, thereby paving the way for optimized neurorehabilitation for patients.
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Affiliation(s)
| | - Nicholas D'Cruz
- 1Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Bauke W Dijkstra
- 1Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Moran Gilat
- 1Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Thomas Kramer
- 1Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
| | - Alice Nieuwboer
- 1Department of Rehabilitation Sciences, KU Leuven, Leuven, Belgium
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Carmona Arroyave JA, Tobón Quintero CA, Suárez Revelo JJ, Ochoa Gómez JF, García YB, Gómez LM, Pineda Salazar DA. Resting functional connectivity and mild cognitive impairment in Parkinson’s disease. An electroencephalogram study. FUTURE NEUROLOGY 2019. [DOI: 10.2217/fnl-2018-0048] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Objective: Parkinson’s disease (PD) is characterized by cognitive deficits. There is not clarity about electroencephalogram (EEG) connectivity related to the cognitive profile of patients. Our objective was to evaluate connectivity over resting EEG in nondemented PD. Methods: PD subjects with and without mild cognitive impairment (MCI) were assessed using coherence from resting EEG for local, intra and interhemispheric connectivity. Results: PD subjects without MCI (PD-nMCI) had lower intra and interhemispheric coherence in alpha2 compared with controls. PD with MCI (PD-MCI) showed higher intra and posterior interhemispheric coherence in alpha2 and beta1, respectively, in comparison to PD-nMCI. PD-MCI presented lower frontal coherence in beta frequencies compared with PD-nMCI. Conclusion: EEG coherence measures indicate distinct cortical activity in PD with and without MCI.
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Affiliation(s)
- Jairo Alexander Carmona Arroyave
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Carlos Andrés Tobón Quintero
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Jasmín Jimena Suárez Revelo
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Bioinstrumentation & Clinical Engineering Research Group (GIBIC), Bioengineering Program, University of Antioquia, Calle 70 No. 52–21, Medellín, Colombia
| | - John Fredy Ochoa Gómez
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Bioinstrumentation & Clinical Engineering Research Group (GIBIC), Bioengineering Program, University of Antioquia, Calle 70 No. 52–21, Medellín, Colombia
| | - Yamile Bocanegra García
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
| | - Leonardo Moreno Gómez
- Neurology Unit, Pablo Tobón Uribe Hospital, Calle 78B No. 69–240, Medellín, Colombia
| | - David Antonio Pineda Salazar
- Neuroscience Group, Medical School, University of Antioquia, SIU, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Medical School, University of Antioquia, SIU – Área Asistencial, Calle 62 No. 52–59, Medellín, Colombia
- Neuropsychology & Behavior Group (GRUNECO), Psychology Department, University of San Buenaventura, Carrera 56 C No. 51–110, Medellín, Colombia
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Sossi V, Cheng JC, Klyuzhin IS. Imaging in Neurodegeneration: Movement Disorders. IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES 2019. [DOI: 10.1109/trpms.2018.2871760] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
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Mueller K, Jech R, Ballarini T, Holiga Š, Růžička F, Piecha FA, Möller HE, Vymazal J, Růžička E, Schroeter ML. Modulatory Effects of Levodopa on Cerebellar Connectivity in Parkinson's Disease. CEREBELLUM (LONDON, ENGLAND) 2019; 18:212-224. [PMID: 30298443 PMCID: PMC6443641 DOI: 10.1007/s12311-018-0981-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Levodopa has been the mainstay of symptomatic therapy for Parkinson's disease (PD) for the last five decades. However, it is associated with the development of motor fluctuations and dyskinesia, in particular after several years of treatment. The aim of this study was to shed light on the acute brain functional reorganization in response to a single levodopa dose. Functional magnetic resonance imaging (fMRI) was performed after an overnight withdrawal of dopaminergic treatment and 1 h after a single dose of 250 mg levodopa in a group of 24 PD patients. Eigenvector centrality was calculated in both treatment states using resting-state fMRI. This offers a new data-driven and parameter-free approach, similar to Google's PageRank algorithm, revealing brain connectivity alterations due to the effect of levodopa treatment. In all PD patients, levodopa treatment led to an improvement of clinical symptoms as measured with the Unified Parkinson's Disease Rating Scale motor score (UPDRS-III). This therapeutic effect was accompanied with a major connectivity increase between cerebellar brain regions and subcortical areas of the motor system such as the thalamus, putamen, globus pallidus, and brainstem. The degree of interconnectedness of cerebellar regions correlated with the improvement of clinical symptoms due to the administration of levodopa. We observed significant functional cerebellar connectivity reorganization immediately after a single levodopa dose in PD patients. Enhanced general connectivity (eigenvector centrality) was associated with better motor performance as assessed by UPDRS-III score. This underlines the importance of considering cerebellar networks as therapeutic targets in PD.
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Affiliation(s)
- Karsten Mueller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Robert Jech
- Department of Neurology - Center for interventional therapy of movement disorders, 1st Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
- Department of Radiology, Na Homolce Hospital, Prague, Czech Republic.
| | - Tommaso Ballarini
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Štefan Holiga
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Filip Růžička
- Department of Neurology - Center for interventional therapy of movement disorders, 1st Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Fabian A Piecha
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Harald E Möller
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Josef Vymazal
- Department of Radiology, Na Homolce Hospital, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology - Center for interventional therapy of movement disorders, 1st Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Matthias L Schroeter
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
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Rössler J, Unterassner L, Wyss T, Haker H, Brugger P, Rössler W, Wotruba D. Schizotypal Traits are Linked to Dopamine-Induced Striato-Cortical Decoupling: A Randomized Double-Blind Placebo-Controlled Study. Schizophr Bull 2019; 45:680-688. [PMID: 29878280 PMCID: PMC6483584 DOI: 10.1093/schbul/sby079] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The dopamine hypothesis of schizophrenia implies that alterations in the dopamine system cause functional abnormalities in the brain that may converge to aberrant salience attribution and eventually lead to psychosis. Indeed, widespread brain disconnectivity across the psychotic spectrum has been revealed by resting-state functional magnetic resonance imaging (rs-fMRI). However, the dopaminergic involvement in intrinsic functional connectivity (iFC) and its putative relationship to the development of psychotic spectrum disorders remains partly unclear-in particular at the low-end of the psychosis continuum. Therefore, we investigated dopamine-induced changes in striatal iFC and their modulation by psychometrically assessed schizotypy. Our randomized, double-blind placebo-controlled study design included 54 healthy, right-handed male participants. Each participant was assessed with the Schizotypal Personality Questionnaire (SPQ) and underwent 10 minutes of rs-fMRI scanning. Participants then received either a placebo or 200 mg of L-DOPA, a dopamine precursor. We analyzed iFC of 6 striatal seeds that are known to evoke modulation of dopamine-related networks. The main effect of L-DOPA was a significant functional decoupling from the right ventral caudate to both occipital fusiform gyri. This dopamine-induced decoupling emerged primarily in participants with low SPQ scores, while participants with high positive SPQ scores showed decoupling indifferently of the L-DOPA challenge. Taken together, these findings demonstrate that schizotypal traits may be the result of dopamine-induced striato-occipital decoupling.
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Affiliation(s)
- Julian Rössler
- Collegium Helveticum, University of Zurich; and ETH Zurich, Zurich, Switzerland,To whom correspondence should be addressed; Julian Rössler, Institute of Anaesthesiology, University Hospital Zurich, Raemistrasse 100, Zurich 8091, Switzerland; tel: +41 442551111; fax: +41 442554409; e-mail:
| | - Lui Unterassner
- Collegium Helveticum, University of Zurich; and ETH Zurich, Zurich, Switzerland
| | - Thomas Wyss
- Collegium Helveticum, University of Zurich; and ETH Zurich, Zurich, Switzerland
| | - Helene Haker
- Translational Neuromodeling Unit (TNU), Institute for Biomedical Engineering, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Peter Brugger
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Wulf Rössler
- Collegium Helveticum, University of Zurich; and ETH Zurich, Zurich, Switzerland,Psychiatric University Hospital, Zürich University, Zürich, Switzerland,Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, University of Sao Paulo, Sao Paulo, Brazil,Department of Psychiatry and Psychotherapy, Charité – Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Diana Wotruba
- Collegium Helveticum, University of Zurich; and ETH Zurich, Zurich, Switzerland
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Cai X, Qiao J, Knox T, Iriah S, Kulkarni P, Madularu D, Morrison T, Waszczak B, Hartner JC, Ferris CF. In search of early neuroradiological biomarkers for Parkinson’s Disease: Alterations in resting state functional connectivity and gray matter microarchitecture in PINK1 −/− rats. Brain Res 2019; 1706:58-67. [DOI: 10.1016/j.brainres.2018.10.033] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Revised: 10/29/2018] [Accepted: 10/30/2018] [Indexed: 12/12/2022]
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Abstract
Even before the success of combined positron emission tomography and computed tomography (PET/CT), the neuroimaging community was conceiving the idea to integrate the positron emission tomography (PET), with very high molecular quantitative data but low spatial resolution, and magnetic resonance imaging (MRI), with high spatial resolution. Several technical limitations have delayed the use of a hybrid scanner in neuroimaging studies, including the full integration of the PET detector ring within the MRI system, the optimization of data acquisition, and the implementation of reliable methods for PET attenuation, motion correction, and joint image reconstruction. To be valid and useful in clinical and research settings, this instrument should be able to simultaneously acquire PET and MRI, and generate quantitative parametric PET images comparable to PET-CT. While post hoc co-registration of combined PET and MRI data acquired separately became the most reliable technique for the generation of "fused" PET-MRI images, only hybrid PET-MRI approach allows merging these measurements naturally and correlating them in a temporal manner. Furthermore, hybrid PET-MRI represents the most accurate tool to investigate in vivo the interplay between molecular and functional aspects of brain pathophysiology. Hybrid PET-MRI technology is still in the early stages in the movement disorders field, due to the limited availability of scanners with integrated optimized methodological models. This technology is ideally suited to investigate interactions between resting-state functional/arterial spin labeling MRI and [18F]FDG PET glucose metabolism in the evaluation of the brain "hubs" particularly vulnerable to neurodegeneration, areas with a high degree of connectivity and associated with an efficient synaptic neurotransmission. In Parkinson's disease, hybrid PET-MRI is also the ideal instrument to deeper explore the relationship between resting-state functional MRI and dopamine release at [11C]raclopride PET challenge, in the identification of early drug-naïve Parkinson's disease patients at higher risk of motor complications and in the evaluation of the efficacy of novel neuroprotective treatment able to restore at the same time the altered resting state and the release of dopamine. In this chapter, we discuss the key methodological aspects of hybrid PET-MRI; the evidence in movement disorders of the key resting-state functional and perfusion MRI; [18F]FDG PET and [11C]raclopride PET challenge studies; the potential advantages of using hybrid PET-MRI to investigate the pathophysiology of movement disorders and neurodegenerative diseases. Future directions of hybrid PET-MRI will be discussed alongside with up-to-date technological innovations on hybrid systems.
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Filippi M, Elisabetta S, Piramide N, Agosta F. Functional MRI in Idiopathic Parkinson's Disease. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2018; 141:439-467. [PMID: 30314606 DOI: 10.1016/bs.irn.2018.08.005] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Functional MRI (fMRI) has been widely used to study abnormal patterns of brain connectivity at rest and activation during a variety of tasks in patients with idiopathic Parkinson's disease (PD). fMRI studies in PD have led to a better understanding of many aspects of the disease including both motor and non-motor symptoms. Although its translation into clinical practice is still at an early stage, fMRI measures hold promise for multiple clinical applications in PD, including the early detection, predicting future change in clinical status, and as a marker of alterations in brain physiology related to neurotherapeutic agents and neurorehabilitative strategies.
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Affiliation(s)
- Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
| | - Sarasso Elisabetta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy; Laboratory of Movement Analysis, San Raffaele Scientific Institute, Milan, Italy
| | - Noemi Piramide
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Vita-Salute San Raffaele University, Milan, Italy
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Abstract
Recent advances in disease understanding, instrumentation technology, and computationally demanding image analysis approaches are opening new frontiers in the investigation of movement disorders and brain disease in general. A key aspect is the recognition of the need to determine molecular correlates to early functional and metabolic connectivity alterations, which are increasingly recognized as useful signatures of specific clinical disease phenotypes. Such multi-modal approaches are highly likely to provide new information on pathogenic mechanisms and to help the identification of novel therapeutic targets. This chapter describes recent methodological developments in PET starting with a very brief overview of radiotracers relevant to movement disorders while emphasizing the development of instrumentation, algorithms and imaging analysis methods relevant to multi-modal investigation of movement disorders.
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Affiliation(s)
- Vesna Sossi
- Department of Physics and Astronomy, University of British Columbia, Vancouver, BC, Canada.
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Xu X, Guan X, Guo T, Zeng Q, Ye R, Wang J, Zhong J, Xuan M, Gu Q, Huang P, Pu J, Zhang B, Zhang M. Brain Atrophy and Reorganization of Structural Network in Parkinson's Disease With Hemiparkinsonism. Front Hum Neurosci 2018; 12:117. [PMID: 29636671 PMCID: PMC5881349 DOI: 10.3389/fnhum.2018.00117] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 03/12/2018] [Indexed: 11/13/2022] Open
Abstract
Hemiparkinsonism duration in patients with Parkinson's disease (PD) is a key time window to study early pathology of PD. We aimed to comprehensively explore the alterations of deformation and structural network in PD patients with hemiparkinsonism, which could potentially disclose the early biomarker for PD. Thirty-one PD patients with hemiparkinsonism and 37 age- and gender- matched normal controls were included in the present study. First of all, we normalized the left hemisphere of structural images as the contralateral side to the affected limbs. Deformation-based morphometry (DBM) was conducted to evaluate the brain atrophy and/or enlargement. structural networks were constructed by thresholding gray matter volume correlation matrices of 116 regions and analyzed using graph theoretical approaches (e.g., small-worldness, global, and nodal measures). Significantly decreased deformation values were observed in the temporoparietal regions like bilateral middle temporal gyri, ipsilateral precuneus and contralateral Rolandic operculum extending to supramarginal and postcentral gyri. Lower deformation values in contralateral middle temporal gyrus were negatively correlated with higher motor impairment which was dominated by akinesia/rigidity. Moreover, nodal reorganization of structural network mainly located in frontal, temporal, subcortex and cerebellum was bilaterally explored in PD patients with hemiparkinsonism. Increased nodal properties could be commonly observed in frontal lobes. Disruption of subcortex including basal ganglia and amygdala was detected by nodal local efficiency and nodal clustering coefficient. Twelve hubs, mainly from paralimbic-limbic and heteromodal networks, were disrupted and, alternatively, 14 hubs, most of which were located in frontal lobes, were additionally detected in PD patients with hemiparkinsonism. In conclusion, during hemiparkinsonism period, mild brain atrophy in the temporoparietal regions and widespread reorganization of structural network, e.g., enhanced frontal function and disruption of basal ganglia nodes, occurred in both hemispheres. With our data, we can also argue that MTG contralateral to the affected limbs (expressing clinically verified brain atrophy) might be a potential living biomarker to monitor disease progression. Therefore, the combination of DBM and structural network analyses can provide a comprehensive and sensitive evaluation for potential pathogenesis of early PD patients with hemiparkinsonism.
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Affiliation(s)
- Xiaojun Xu
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaojun Guan
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Tao Guo
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Qiaoling Zeng
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Rong Ye
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jiaqiu Wang
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jianguo Zhong
- Department of Radiology, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Min Xuan
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Quanquan Gu
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Peiyu Huang
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Jiali Pu
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Baorong Zhang
- Department of Neurology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Minming Zhang
- Department of Radiology, Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China
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Altered brain metabolic connectivity at multiscale level in early Parkinson's disease. Sci Rep 2017; 7:4256. [PMID: 28652595 PMCID: PMC5484707 DOI: 10.1038/s41598-017-04102-z] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2017] [Accepted: 05/11/2017] [Indexed: 01/29/2023] Open
Abstract
To explore the effects of PD pathology on brain connectivity, we characterized with an emergent computational approach the brain metabolic connectome using [18F]FDG-PET in early idiopathic PD patients. We applied whole-brain and pathology-based connectivity analyses, using sparse-inverse covariance estimation in thirty-four cognitively normal PD cases and thirty-four age-matched healthy subjects for comparisons. Further, we assessed high-order resting state networks by interregional correlation analysis. Whole-brain analysis revealed altered metabolic connectivity in PD, with local decreases in frontolateral cortex and cerebellum and increases in the basal ganglia. Widespread long-distance decreases were present within the frontolateral cortex as opposed to connectivity increases in posterior cortical regions, all suggestive of a global-scale connectivity reconfiguration. The pathology-based analyses revealed significant connectivity impairment in the nigrostriatal dopaminergic pathway and in the regions early affected by α-synuclein pathology. Notably, significant connectivity changes were present in several resting state networks especially in frontal regions. These findings expand previous imaging evidence of altered connectivity in cognitively stable PD patients by showing pathology-based connectivity changes and disease-specific metabolic architecture reconfiguration at multiple scale levels, from the earliest PD phases. These alterations go well beyond the known striato-cortical connectivity derangement supporting in vivo an extended neural vulnerability in the PD synucleinopathy.
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Non-human primate models of PD to test novel therapies. J Neural Transm (Vienna) 2017; 125:291-324. [PMID: 28391443 DOI: 10.1007/s00702-017-1722-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Accepted: 04/04/2017] [Indexed: 12/13/2022]
Abstract
Non-human primate (NHP) models of Parkinson disease show many similarities with the human disease. They are very useful to test novel pharmacotherapies as reviewed here. The various NHP models of this disease are described with their characteristics including the macaque, the marmoset, and the squirrel monkey models. Lesion-induced and genetic models are described. There is no drug to slow, delay, stop, or cure Parkinson disease; available treatments are symptomatic. The dopamine precursor, L-3,4-dihydroxyphenylalanine (L-Dopa) still remains the gold standard symptomatic treatment of Parkinson. However, involuntary movements termed L-Dopa-induced dyskinesias appear in most patients after chronic treatment and may become disabling. Dyskinesias are very difficult to manage and there is only amantadine approved providing only a modest benefit. In this respect, NHP models have been useful to seek new drug targets, since they reproduce motor complications observed in parkinsonian patients. Therapies to treat motor symptoms in NHP models are reviewed with a discussion of their translational value to humans. Disease-modifying treatments tested in NHP are reviewed as well as surgical treatments. Many biochemical changes in the brain of post-mortem Parkinson disease patients with dyskinesias are reviewed and compare well with those observed in NHP models. Non-motor symptoms can be categorized into psychiatric, autonomic, and sensory symptoms. These symptoms are present in most parkinsonian patients and are already installed many years before the pre-motor phase of the disease. The translational usefulness of NHP models of Parkinson is discussed for non-motor symptoms.
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Affiliation(s)
- José Bargas
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, México City, México
| | - Jesús Pérez-Ortega
- División de Neurociencias, Instituto de Fisiología Celular, Universidad Nacional Autónoma de México, México City, México
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