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Ge S, Liu J, Jia Y, Li Z, Wang J, Wang M. Topological alteration of the brain structural network in Parkinson's disease with apathy. Brain Res Bull 2024; 208:110899. [PMID: 38340778 DOI: 10.1016/j.brainresbull.2024.110899] [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: 09/22/2023] [Revised: 11/05/2023] [Accepted: 02/07/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND Apathy is a common neuropsychiatric manifestations in Parkinson's disease (PD), but neural network mechanisms still remain elusive. We aim to investigate the topological alteration of the brain structural network in PD with apathy. METHOD In the present study, a total of 47 apathetic PD (aPD) patients, 37 non-apathetic PD (naPD) patients, and 40 healthy controls (HCs) were enrolled. Diffusion tensor imaging (DTI) in conjunction with graph-theoretic approaches were used to explore the alterations of topological properties of the WM structural network arising from apathy in PD. One-way analysis of covariance and post hoc analyses were performed to explore differences among the three groups. Correlations were ascertained to examine relationships between the Starkstein Apathy Scale (AS) scores and significantly different network metrics among the three groups. RESULTS Both aPD and naPD patients remained small-world topology. However, compared with the naPD patients, aPD patients showed increased clustering coefficient (Cp) at the global level. At the regional level, aPD exhibited decreased nodal properties, mainly in the right dorsolateral prefrontal cortex (DLPFC), the right caudate nucleus (CAU), the right hippocampus, and the right superior parietal gyrus. Further, AS scores were negatively correlated with degree centrality of the right DLPFC (r = -0.254, p = 0.020) and the right CAU ( r = -0.357, p = 0.001) in the pooled patients with PD. CONCLUSIONS The findings suggested that apathy in PD presented relatively optimized global topological properties of the brain structural network and disrupted topological organization of the regional network, particularly involving the fronto-striatal-limbic circuits. The altered topological properties of abnormal brain regions might be used to understand the physiopathologic mechanism of the neural network in aPD patients.
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Affiliation(s)
- Shaoyun Ge
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Jun Liu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Yongfeng Jia
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Zihan Li
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China
| | - Jianwei Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
| | - Min Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
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Yin N, Wang H, Wang Z, Feng K, Xu G, Yin S. A study of brain networks associated with Freezing of gait in Parkinson's disease using transfer entropy analysis. Brain Res 2023; 1821:148610. [PMID: 37783260 DOI: 10.1016/j.brainres.2023.148610] [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: 06/30/2023] [Revised: 09/22/2023] [Accepted: 09/27/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND Parkinson's disease (PD) is a common neurodegenerative disease in the elderly. Freezing of Gait (FOG) is one of the common motor symptoms of PD, but the potential mechanism remains unclear. This study aimed to investigate the changes of brain functional network topology in PD patients with FOG. METHODS The resting electroencephalogram (EEG) were acquired from15 PD patients with FOG (PD-FOG), 13 PD patients without FOG (PD-nFOG), and 16 healthy control (HC). Cognitive and motor functions were assessed using subjective scales. The whole-brain functional networks were constructed based on transfer entropy. Transfer entropy was used to analyse the information flow and causality in the network and the network connectivity was analyzed by graph theory. The characteristics of PD-FOG and PD-nFOG were compared by receiver operator characteristic (ROC) curve analysis. RESULTS The θ bands brain network of PD-FOG, PD-nFOG and HC group was significantly different (P < 0.05). The average characteristic path length of the θ bands brain network was positively correlated with FOG Questionnaire (FOGQ). PD-FOG and PD-nFOG get high classification accuracy according to this feature. The information inflow in the frontal and occipital lobes and information outflow in the temporal lobe of PD-FOG patients in the θ bands increased significantly. CONCLUSIONS The whole-brain functional network characteristics of PD-FOG in the θ bands can serve as potential biomarkers for early diagnosis of PD-FOG. Abnormal information flow of the frontal, occipital, and temporal lobes in the θ bands may be an important factor leading to FOG.
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Affiliation(s)
- Ning Yin
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Haili Wang
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Zhaoya Wang
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China
| | - Keke Feng
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300350, China
| | - Guizhi Xu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China; Tianjin Key Laboratory of Bioelectromagnetic Technology and Intelligent Health, Hebei University of Technology, Tianjin 300130, China; School of Health Sciences and Biomedical Engineering, Hebei University of Technology, Tianjin 300130, China.
| | - Shaoya Yin
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300350, China.
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Nerrise F, Zhao Q, Poston KL, Pohl KM, Adeli E. An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2023; 14221:723-733. [PMID: 37982132 PMCID: PMC10657737 DOI: 10.1007/978-3-031-43895-0_68] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
One of the hallmark symptoms of Parkinson's Disease (PD) is the progressive loss of postural reflexes, which eventually leads to gait difficulties and balance problems. Identifying disruptions in brain function associated with gait impairment could be crucial in better understanding PD motor progression, thus advancing the development of more effective and personalized therapeutics. In this work, we present an explainable, geometric, weighted-graph attention neural network (xGW-GAT) to identify functional networks predictive of the progression of gait difficulties in individuals with PD. xGW-GAT predicts the multi-class gait impairment on the MDS-Unified PD Rating Scale (MDS-UPDRS). Our computational- and data-efficient model represents functional connectomes as symmetric positive definite (SPD) matrices on a Riemannian manifold to explicitly encode pairwise interactions of entire connectomes, based on which we learn an attention mask yielding individual- and group-level explainability. Applied to our resting-state functional MRI (rs-fMRI) dataset of individuals with PD, xGW-GAT identifies functional connectivity patterns associated with gait impairment in PD and offers interpretable explanations of functional subnetworks associated with motor impairment. Our model successfully outperforms several existing methods while simultaneously revealing clinically-relevant connectivity patterns. The source code is available at https://github.com/favour-nerrise/xGW-GAT.
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Affiliation(s)
- Favour Nerrise
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Qingyu Zhao
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Kathleen L Poston
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Kilian M Pohl
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Ehsan Adeli
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
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Nerrise F, Zhao Q, Poston KL, Pohl KM, Adeli E. An Explainable Geometric-Weighted Graph Attention Network for Identifying Functional Networks Associated with Gait Impairment. ARXIV 2023:arXiv:2307.13108v1. [PMID: 37547656 PMCID: PMC10402187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
One of the hallmark symptoms of Parkinson's Disease (PD) is the progressive loss of postural reflexes, which eventually leads to gait difficulties and balance problems. Identifying disruptions in brain function associated with gait impairment could be crucial in better understanding PD motor progression, thus advancing the development of more effective and personalized therapeutics. In this work, we present an explainable, geometric, weighted-graph attention neural network (xGW-GAT) to identify functional networks predictive of the progression of gait difficulties in individuals with PD. xGW-GAT predicts the multi-class gait impairment on the MDS-Unified PD Rating Scale (MDS-UPDRS). Our computational- and data-efficient model represents functional connectomes as symmetric positive definite (SPD) matrices on a Riemannian manifold to explicitly encode pairwise interactions of entire connectomes, based on which we learn an attention mask yielding individual- and group-level explain-ability. Applied to our resting-state functional MRI (rs-fMRI) dataset of individuals with PD, xGW-GAT identifies functional connectivity patterns associated with gait impairment in PD and offers interpretable explanations of functional subnetworks associated with motor impairment. Our model successfully outperforms several existing methods while simultaneously revealing clinically-relevant connectivity patterns. The source code is available at https://github.com/favour-nerrise/xGW-GAT.
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Affiliation(s)
- Favour Nerrise
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Qingyu Zhao
- Dept. of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Kathleen L. Poston
- Dept. of Neurology & Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Kilian M. Pohl
- Dept. of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Ehsan Adeli
- Dept. of Psychiatry & Behavioral Sciences, Stanford University, Stanford, CA, USA
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Sreenivasan K, Bayram E, Zhuang X, Longhurst J, Yang Z, Cordes D, Ritter A, Caldwell J, Cummings JL, Mari Z, Litvan I, Bluett B, Mishra VR. Topological reorganization of functional hubs in patients with Parkinson's disease with freezing of gait. J Neuroimaging 2023; 33:547-557. [PMID: 37080778 PMCID: PMC10523899 DOI: 10.1111/jon.13107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 04/10/2023] [Accepted: 04/10/2023] [Indexed: 04/22/2023] Open
Abstract
BACKGROUND AND PURPOSE Resting-state functional MRI (rs-fMRI) studies in Parkinson's disease (PD) patients with freezing of gait (FOG) have implicated dysfunctional connectivity over multiple resting-state networks (RSNs). While these findings provided network-specific insights and information related to the aberrant or altered regional functional connectivity (FC), whether these alterations have any effect on topological reorganization in PD-FOG patients is incompletely understood. Understanding the higher order functional organization, which could be derived from the "hub" and the "rich-club" organization of the functional networks, could be crucial to identifying the distinct and unique pattern of the network connectivity associated with PD-FOG. METHODS In this study, we use rs-fMRI data and graph theoretical approaches to explore the reorganization of RSN topology in PD-FOG when compared to those without FOG. We also compared the higher order functional organization derived using the hub and rich-club measures in the FC networks of these PD-FOG patients to understand whether there is a topological reorganization of these hubs in PD-FOG. RESULTS We found that the PD-FOG patients showed a noticeable reorganization of hub regions. Regions that are part of the prefrontal cortex, primary somatosensory, motor, and visuomotor coordination areas were some of the regions exhibiting altered hub measures in PD-FOG patients. We also found a significantly altered feeder and local connectivity in PD-FOG. CONCLUSIONS Overall, our findings demonstrate a widespread topological reorganization and disrupted higher order functional network topology in PD-FOG that may further assist in improving our understanding of functional network disturbances associated with PD-FOG.
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Affiliation(s)
| | - Ece Bayram
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Xiaowei Zhuang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
| | - Jason Longhurst
- Department of Physical Therapy and Athletic Training, Saint Louis University, St. Louis, Missouri, USA
| | - Zhengshi Yang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
- Department of Radiology, University of Colorado Boulder, Boulder, Colorado, USA
| | - Aaron Ritter
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
| | - Jessica Caldwell
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
| | - Jeffrey L. Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada, Las Vegas, Nevada, USA
| | - Zoltan Mari
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
| | - Irene Litvan
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Brent Bluett
- Central California Movement Disorders, Pismo Beach, California, USA
| | - Virendra R. Mishra
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, Nevada, USA
- Department of Radiology, Heersink School of Medicine, The University of Alabama at Birmingham, Birmingham, Alabama, USA
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Ruan X, Huang X, Li Y, Kuang Z, Li M, Wei X. Dysfunction of human brain network hierarchy in Parkinson's disease patients with freezing of gait. Parkinsonism Relat Disord 2023; 112:105446. [PMID: 37245278 DOI: 10.1016/j.parkreldis.2023.105446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/10/2023] [Accepted: 05/18/2023] [Indexed: 05/30/2023]
Abstract
INTRODUCTION Hierarchy has been identified as a principle underlying the organization of human brain networks. In Parkinson's disease with freezing of gait (PD-FOG), it remains unclear whether and how the network hierarchy is disrupted. Additionally, the associations between changes in the brain network hierarchy of PD patients with FOG and clinical scales remain unclear. The aim of this study was to explore alterations in the network hierarchy of PD-FOG and their clinical relevance. METHODS In this study, the brain network hierarchy of each group was described through a connectome gradient analysis among 31 PD-FOG, 50 PD patients without FOG (PD-NFOG), and 38 healthy controls (HC). Changes in the network hierarchy were assessed by comparing different gradient values of each network between the PD-FOG, PD-NFOG and HC groups. We further examined the relationship between dynamically changing network gradient values and clinical scales. RESULTS For the second gradient, Salience/ventral attention network-A (SalVentAttnA) network gradient of PD-FOG group was significantly lower than that of PD-NFOG, while both PD subgroups had a Default mode network-C gradient that was significantly lower than that of the HC group. In the third gradient, somatomotor network-A gradient of PD-FOG patients was significantly lower than the PD-NFOG group. Moreover, reduced SalVentAttnA network gradient values were associated with more severe gaits, fall risk, and frozen gait in PD-FOG patients. CONCLUSIONS The brain network hierarchy in PD-FOG is disturbed, this dysfunction is related to the severity of frozen gait. This study provides novel evidence for the neural mechanisms of FOG.
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Affiliation(s)
- Xiuhang Ruan
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Xiaofei Huang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Yuting Li
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Zhanyu Kuang
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Mengyan Li
- Department of Neurology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, China.
| | - Xinhua Wei
- Department of Radiology, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, 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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Zhu PA, Lu QQ, Li ZL, Hu RL, Xu S, Brodersen L, Liu YX, Liu H, Bao X. Efficacy of Tai Chi on lower limb function of Parkinson's disease patients: A systematic review and meta-analysis. Front Aging Neurosci 2023; 15:1096417. [PMID: 36819715 PMCID: PMC9929552 DOI: 10.3389/fnagi.2023.1096417] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 01/09/2023] [Indexed: 02/04/2023] Open
Abstract
Background At present, the effect of Tai Chi (TC) on lower limb function in patients with Parkinson's disease (PD) is controversial. Therefore, we conducted a meta-analysis on the influence of TC on lower limb function in PD patients. Methods According to the PRISMA guidelines, seven databases were searched. Randomized controlled trials (RCTS) were selected and screened according to inclusion and exclusion criteria. We assessed the quality of the studies using the Cochrane Risk of Bias tool and then extracted the characteristics of the included studies. The random effect model was adopted, and heterogeneity was measured by I 2 statistic. Results A total of 441 articles were screened, and 10 high-quality RCTs were with a total of 532 patients with PD met Our inclusion criteria. Meta-analysis showed that compared To control groups TC improved several outcomes. TC significantly improved motor function (SMD = -0.70; 95% CI = -0.95, -0.45; p < 0.001; I 2 = 35%), although The results were not statistically significant for The subgroup analysis of TC duration (SMD = -0.70; 95% CI = -0.95, -0.45; p = 0.88; I 2 = 0%;). TC significantly improved balance function (SMD = 0.89; 95% CI = 0.51, 1.27; p < 0.001; I 2 = 54%), functional walking capacity (SMD = -1.24; 95% CI = -2.40, -0.09; p = 0.04; I 2 = 95%), and gait velocity (SMD = 0.48; 95% CI = -0.02, 0.94; p = 0.04; I 2 = 78%), But Did Not improve endurance (SMD = 0.31; 95% CI = -0.12, 0.75; p = 0.16; I 2 = 0%), step length (SMD = 0.01; 95% CI = -0.34, 0.37; p = 0.94; I 2 = 29%), and cadence (SMD = 0.06; 95% CI = -0.25, 0.36; p = 0.70; I 2 = 0%). Conclusion TC has beneficial effects on motor function, balance function, functional walking ability, and gait velocity, but does not improve walking endurance, stride length, and cadence.
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Affiliation(s)
- Ping-an Zhu
- Department of Rehabilitation Medicine, Yuebei People’s Hospital, Shaoguan, China
| | - Qi-qi Lu
- Department of Rehabilitation Medicine, Yuebei People’s Hospital, Shaoguan, China
| | - Zhi-liang Li
- Department of Rehabilitation Medicine, Yuebei People’s Hospital, Shaoguan, China
| | - Rong-liang Hu
- Department of Rehabilitation Medicine, Jiangmen Central Hospital, Guangdong, Jiangmen, China
| | - Shu Xu
- Department of Rehabilitation Medicine, Shaoguan Railway Hospital, Shaoguan, China
| | - Lisa Brodersen
- Physical Therapy Program, Allen College, Waterloo, IA, United States
| | - Yuan-xin Liu
- College of Sports and Health Science, Xi’an Physical Education University, Xi’an, China,*Correspondence: Yuan-xin Liu,
| | - Howe Liu
- Physical Therapy Program, Allen College, Waterloo, IA, United States,Howe Liu,
| | - Xiao Bao
- Department of Rehabilitation Medicine, Yuebei People’s Hospital, Shaoguan, China,Xiao Bao,
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Wang L, Gan C, Sun H, Ji M, Zhang H, Cao X, Wang M, Yuan Y, Zhang K. Impaired structural and reserved functional topological organizations of brain networks in Parkinson's disease with freezing of gait. Quant Imaging Med Surg 2023; 13:66-79. [PMID: 36620158 PMCID: PMC9816763 DOI: 10.21037/qims-22-351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2022] [Accepted: 09/16/2022] [Indexed: 01/11/2023]
Abstract
Background Freezing of gait (FOG) is a common disabling motor disturbance in Parkinson's disease (PD). Our study aimed to probe the topological organizations of structural and functional brain networks and their coupling in FOG. Methods In this cross-sectional retrospective study, a total of 30 PD patients with FOG (PD-FOG), 40 patients without FOG, and 25 healthy controls (HCs) underwent clinical assessments and magnetic resonance imaging (MRI) scanning. Large-scale structural and functional brain networks were constructed. Subsequently, global and nodal graph theoretical properties and functional-structural coupling were investigated. Finally, correlations between the altered brain topological properties and freezing severity were analyzed in PD-FOG. Results For structural networks, at the global level, PD-FOG exhibited increased normalized characteristic path length (P=0.040, Bonferroni-corrected) and decreased global efficiency (P=0.005, Bonferroni-corrected) compared with controls, and showed reduced global (P=0.001, Bonferroni-corrected) and local (P=0.032, Bonferroni-corrected) efficiency relative to patients without FOG. At the nodal level, nodal efficiency of structural networks was reduced in PD-FOG compared with PD patients without FOG, located in the left supplementary motor area (SMA), gyrus rectus, and middle cingulate cortex (MCC) (all P<0.05, Bonferroni-corrected). Notably, altered global and nodal properties of structural networks were significantly correlated with Freezing of Gait Questionnaire scores [all P<0.05, false discovery rate (FDR)-corrected]. However, only an increase in local efficiency (P=0.003, Bonferroni-corrected) of functional networks was identified in PD-FOG compared with those without FOG. No significant structural-functional coupling was detected among the 3 groups. Conclusions This study demonstrates the extensively impaired structural and relatively reserved functional network topological organizations in PD-FOG. Our results also provide evidence that the pathogenesis of PD-FOG is primarily attributable to network vulnerability established by crucial structural damage, especially in the left SMA, gyrus rectus, and MCC.
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Affiliation(s)
- Lina Wang
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Caiting Gan
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huimin Sun
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Min Ji
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Heng Zhang
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xingyue Cao
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Min Wang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Yongsheng Yuan
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Kezhong Zhang
- Department of Neurology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Kou W, Wang X, Zheng Y, Zhao J, Cai H, Chen H, Sui B, Feng T. Freezing of gait in Parkinson’s disease is associated with the microstructural and functional changes of globus pallidus internus. Front Aging Neurosci 2022; 14:975068. [PMID: 36062153 PMCID: PMC9434315 DOI: 10.3389/fnagi.2022.975068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 08/01/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundFreezing of gait (FOG) is a common motor symptom in advanced Parkinson’s disease (PD). However, the pathophysiology mechanism of FOG is not fully understood. The purpose of this study was to investigate microstructural abnormalities in subcortical gray matter and alterations in functional connectivity of the nuclei with microstructural changes. In addition, the correlations between these microstructural and functional changes and the severity of FOG were measured.Materials and methodsTwenty-four patients with FOG (PD-FOG), 22 PD patients without FOG (PD-nFOG), and 27 healthy controls (HC) were recruited. FOG Questionnaire (FOGQ) and Gait and Falling Questionnaire (GFQ) were assessed, and Timed Up and Go (TUG) tests were performed in PD-FOG patients. All subjects underwent diffusion tensor imaging (DTI) and resting-state functional MRI scanning. The DTI measures, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD), were extracted and measured from basal ganglia, thalamus, and substantia nigra. The nuclei with microstructural alterations were selected as seed regions to perform the seed-based resting-state functional connectivity.ResultsThe MD and RD values of the right globus pallidus internus (GPi) were significantly higher in patients with PD-FOG compared with PD-nFOG patients and HC. In PD-FOG patients, the MD and RD values of the right GPi were significantly correlated with the time of the TUG test in both ON and OFF states. The MD values were also correlated with the GFQ scores in PD-FOG patients. Resting-state functional connectivity between the right GPi and left middle occipital gyri decreased significantly in PD-FOG patients compared to PD-nFOG patients, and was negatively correlated with GFQ scores as well as the time of ON state TUG in PD-FOG patients.ConclusionMicrostructural alterations in the right GPi and functional connectivity between the right GPi and visual cortex may be associated with the pathophysiological mechanisms of FOG in PD patients.
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Affiliation(s)
- Wenyi Kou
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xuemei Wang
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuanchu Zheng
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jiajia Zhao
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huihui Cai
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Huimin Chen
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Binbin Sui
- Tiantan Neuroimaging Center for Excellence, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Binbin Sui,
| | - Tao Feng
- Center for Movement Disorders, Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- Tao Feng,
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Zheng JH, Sun WH, Ma JJ, Wang ZD, Chang QQ, Dong LR, Shi XX, Li MJ, Gu Q, Chen SY. Structural and functional abnormalities in Parkinson's disease based on voxel-based morphometry and resting-state functional magnetic resonance imaging. Neurosci Lett 2022; 788:136835. [PMID: 35963477 DOI: 10.1016/j.neulet.2022.136835] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 07/25/2022] [Accepted: 08/07/2022] [Indexed: 11/30/2022]
Abstract
OBJECTIVE To explore differences in gray matter volume (GMV) and white matter volume (WMV) between patients with Parkinson's disease (PD) and healthy controls, and to examine whether the structural abnormalities correlate with functional abnormalities. METHODS T1-weighted magnetic resonance imaging and resting-state functional magnetic resonance imaging (fMRI) were performed on 180 patients with PD and 58 age- and sex-matched healthy controls. We used voxel-based morphometry (VBM) to compare GMV and WMV between groups, and resting-state fMRI to compare amplitudes of low-frequency fluctuations (ALFF) in the structurally abnormal brain regions. RESULTS Structural neuroimaging showed smaller whole-brain GMV, but not WMV, in patients. Furthermore, VBM revealed smaller GMV in the right superior temporal gyrus (STG) and left frontotemporal space in patients, after correction for multiple comparisons. Patients also showed significantly higher ALFF in the right STG. GMV in the right STG and left frontotemporal space in patients correlated negatively with age and scores on Part III of the Movement Disorder Society Unified Parkinson's Disease Rating Scale, but not with PD duration. CONCLUSIONS Structural atrophy in the frontotemporal lobe may be a useful imaging biomarker in PD, such as for detecting disease progression. Furthermore, this structural atrophy appears to correlate with enhanced spontaneous brain activity. This study associates particular structural and functional abnormalities with PD neuropathology.
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Affiliation(s)
- Jin Hua Zheng
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Henan University, Zhengzhou, Henan Province, China
| | - Wen Hua Sun
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Jian Jun Ma
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Henan University, Zhengzhou, Henan Province, China.
| | - Zhi Dong Wang
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Qing Qing Chang
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Lin Rui Dong
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Xiao Xue Shi
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China
| | - Ming Jian Li
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Henan University, Zhengzhou, Henan Province, China
| | - Qi Gu
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Henan University, Zhengzhou, Henan Province, China
| | - Si Yuan Chen
- Department of Neurology, Henan Provincial People's Hospital, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Zhengzhou University, Zhengzhou, Henan Province, China; Department of Neurology, People's Hospital of Henan University, Zhengzhou, Henan Province, China
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12
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Jin C, Yang L, Qi S, Teng Y, Li C, Yao Y, Ruan X, Wei X. Structural Brain Network Abnormalities in Parkinson’s Disease With Freezing of Gait. Front Aging Neurosci 2022; 14:944925. [PMID: 35875794 PMCID: PMC9304752 DOI: 10.3389/fnagi.2022.944925] [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: 05/16/2022] [Accepted: 06/20/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveDiffusion tensor imaging (DTI) studies have investigated white matter (WM) integrity abnormalities in Parkinson’s disease (PD). However, little is known about the topological changes in the brain network. This study aims to reveal these changes by comparing PD without freezing of gait (FOG) (PD FOG–), PD with FOG (PD FOG+), and healthy control (HC).Methods21 PD FOG+, 34 PD FOG-, and 23 HC were recruited, and DTI images were acquired. The graph theoretical analysis and network-based statistical method were used to calculate the topological parameters and assess connections.ResultsPD FOG+ showed a decreased normalized clustering coefficient, small-worldness, clustering coefficient, and increased local network efficiency compared with HCs. PD FOG+ showed decreased centrality, degree centrality, and nodal efficiency in the striatum, frontal gyrus, and supplementary motor area (SMA). PD FOG+ showed decreased connections in the frontal gyrus, cingulate gyrus, and caudate nucleus (CAU). The between centrality of the left SMA and left CAU was negatively correlated with FOG questionnaire scores.ConclusionThis study demonstrates that PD FOG+ exhibits disruption of global and local topological organization in structural brain networks, and the disrupted topological organization can be potential biomarkers in PD FOG+. These new findings may provide increasing insight into the pathophysiological mechanism of PD FOG+.
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Affiliation(s)
- Chaoyang Jin
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Lei Yang
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Shouliang Qi
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
- Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
- *Correspondence: Shouliang Qi,
| | - Yueyang Teng
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Chen Li
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
| | - Yudong Yao
- Department of Electrical and Computer Engineering, Stevens Institute of Technology, Hoboken, NJ, United States
| | - Xiuhang Ruan
- Department of Radiology, School of Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, China
| | - Xinhua Wei
- Department of Radiology, School of Medicine, Guangzhou First People’s Hospital, South China University of Technology, Guangzhou, China
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13
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Xu H, Wang L, Zuo C, Jiang J. Brain network analysis between Parkinson's Disease and Health Control based on edge functional connectivity. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:4805-4808. [PMID: 36085832 DOI: 10.1109/embc48229.2022.9871613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Parkinson's Disease (PD) is the second largest neurodegenerative disease. Brain functional connectivity (FC) studies for PD were useful. In this study, we employed a novel brain network construction method, edge functional connectivity (eFC), to explore FC differences between healthy control (HC) subjects and PD patients. The data used in this study included 34 HCs and 47 PDs from Huashan Hospital, Fudan University, China. Resting state functional magnetic resonance imaging (rsfMRI) and clinical information were selected. Firstly, we constructed eFC brain network and calculated network matrix for the HC and PD groups. Then, we compared brain network matrix between eFC and the traditional nodal functional connectivity (nFC) method. Receiver operating characteristic curve (ROC) analysis was applied to validate the efficiency of the eFC brain network. The results showed that both nFC and eFC brain networks could identify significantly different characteristics between the HC and PD groups. Important hubs were mainly concentrated in visual network, sensorimotor network, subcortex and cerebellum. In addition, new hubs in basal ganglia and cerebellum regions were found in eFC. Furthermore, eFC achieved better classification results (AUC=0.985) than nFC (AUC=0.861) in discriminating PD from CN subjects.
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14
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Zhang J, Villringer A, Nikulin VV. Dopaminergic Modulation of Local Non-oscillatory Activity and Global-Network Properties in Parkinson's Disease: An EEG Study. Front Aging Neurosci 2022; 14:846017. [PMID: 35572144 PMCID: PMC9106139 DOI: 10.3389/fnagi.2022.846017] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Dopaminergic medication for Parkinson's disease (PD) modulates neuronal oscillations and functional connectivity (FC) across the basal ganglia-thalamic-cortical circuit. However, the non-oscillatory component of the neuronal activity, potentially indicating a state of excitation/inhibition balance, has not yet been investigated and previous studies have shown inconsistent changes of cortico-cortical connectivity as a response to dopaminergic medication. To further elucidate changes of regional non-oscillatory component of the neuronal power spectra, FC, and to determine which aspects of network organization obtained with graph theory respond to dopaminergic medication, we analyzed a resting-state electroencephalography (EEG) dataset including 15 PD patients during OFF and ON medication conditions. We found that the spectral slope, typically used to quantify the broadband non-oscillatory component of power spectra, steepened particularly in the left central region in the ON compared to OFF condition. In addition, using lagged coherence as a FC measure, we found that the FC in the beta frequency range between centro-parietal and frontal regions was enhanced in the ON compared to the OFF condition. After applying graph theory analysis, we observed that at the lower level of topology the node degree was increased, particularly in the centro-parietal area. Yet, results showed no significant difference in global topological organization between the two conditions: either in global efficiency or clustering coefficient for measuring global and local integration, respectively. Interestingly, we found a close association between local/global spectral slope and functional network global efficiency in the OFF condition, suggesting a crucial role of local non-oscillatory dynamics in forming the functional global integration which characterizes PD. These results provide further evidence and a more complete picture for the engagement of multiple cortical regions at various levels in response to dopaminergic medication in PD.
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Affiliation(s)
- Juanli Zhang
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Arno Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
| | - Vadim V. Nikulin
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Neurophysics Group, Department of Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
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15
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Ni R, Yuan Y, Yang L, Meng Q, Zhu Y, Zhong Y, Cao Z, Zhang S, Yao W, Lv D, Chen X, Chen X, Bu J. Novel Non-invasive Transcranial Electrical Stimulation for Parkinson's Disease. Front Aging Neurosci 2022; 14:880897. [PMID: 35493922 PMCID: PMC9039727 DOI: 10.3389/fnagi.2022.880897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Accepted: 03/15/2022] [Indexed: 11/25/2022] Open
Abstract
Conventional transcranial electrical stimulation (tES) is a non-invasive method to modulate brain activity and has been extensively used in the treatment of Parkinson's disease (PD). Despite promising prospects, the efficacy of conventional tES in PD treatment is highly variable across different studies. Therefore, many have tried to optimize tES for an improved therapeutic efficacy by developing novel tES intervention strategies. Until now, these novel clinical interventions have not been discussed or reviewed in the context of PD therapy. In this review, we focused on the efficacy of these novel strategies in PD mitigation, classified them into three categories based on their distinct technical approach to circumvent conventional tES problems. The first category has novel stimulation modes to target different modulating mechanisms, expanding the rang of stimulation choices hence enabling the ability to modulate complex brain circuit or functional networks. The second category applies tES as a supplementary intervention for PD hence amplifies neurological or behavioral improvements. Lastly, the closed loop tES stimulation can provide self-adaptive individualized stimulation, which enables a more specialized intervention. In summary, these novel tES have validated potential in both alleviating PD symptoms and improving understanding of the pathophysiological mechanisms of PD. However, to assure wide clinical used of tES therapy for PD patients, further large-scale trials are required.
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Affiliation(s)
- Rui Ni
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
- Department of Life Sciences, Imperial College London, London, United Kingdom
| | - Ye Yuan
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Li Yang
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Qiujian Meng
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Ying Zhu
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Yiya Zhong
- Department of Life Sciences, Imperial College London, London, United Kingdom
| | - Zhenqian Cao
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Shengzhao Zhang
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Wenjun Yao
- Department of Radiology, The Second Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Daping Lv
- Department of Neurology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xin Chen
- Department of Neurology, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Xianwen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Junjie Bu
- Department of Intelligent Medical Engineering, School of Biomedical Engineering, Anhui Medical University, Hefei, China
- Department of Neurosurgery, The Fourth Affiliated Hospital of Anhui Medical University, Hefei, China
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Peng J, Yang J, Li J, Lei D, Li N, Suo X, Duan L, Chen C, Zeng Y, Xi J, Jiang Y, Gong Q, Peng R. Disrupted Brain Functional Network Topology in Essential Tremor Patients With Poor Sleep Quality. Front Neurosci 2022; 16:814745. [PMID: 35360181 PMCID: PMC8960629 DOI: 10.3389/fnins.2022.814745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2021] [Accepted: 01/14/2022] [Indexed: 11/30/2022] Open
Abstract
Sleep disturbances, especially poor quality of sleep (QoS), are common among essential tremor (ET) patients and may have adverse effects on their quality of life, but the etiology driving the poor QoS in these individuals remains inadequately understood. Few data are available on the neuroimaging alterations of ET with poor QoS. Thirty-eight ET patients with poor QoS (SleET), 48 ET patients with normal QoS (NorET), and 80 healthy controls (HCs) participated in this study. All subjects underwent a 3.0-T magnetic resonance imaging (MRI) scan for resting-state functional MRI data collection. Then, the whole-brain functional connectome was constructed by thresholding the partial correlation matrices of 116 brain regions. Graph theory and network-based statistical analyses were performed. We used a non-parametric permutation test for group comparisons of topological metrics. Partial correlation analyses between the topographical features and clinical characteristics were conducted. The SleET and NorET groups exhibited decreased clustering coefficients, global efficiency, and local efficiency and increased the characteristic path length. Both of these groups also showed reduced nodal degree and nodal efficiency in the left superior dorsolateral frontal gyrus, superior frontal medial gyrus (SFGmed), posterior cingulate gyrus (PCG), lingual gyrus, superior occipital gyrus, right middle occipital gyrus, and right fusiform gyrus. The SleET group additionally presented reduced nodal degrees and nodal efficiency in the right SFGmed relative to the NorET and HC groups, and nodal efficiency in the right SFGmed was negatively correlated with the Pittsburgh Sleep Quality Index score. The observed impaired topographical organizations of functional brain networks within the central executive network (CEN), default mode network (DMN), and visual network serve to further our knowledge of the complex interactions between tremor and sleep, adding to our understanding of the underlying neural mechanisms of ET with poor QoS.
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Affiliation(s)
- Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Yang
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Xueling Suo
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yan Zeng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Jing Xi
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yi Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Qiyong Gong,
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
- Rong Peng,
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17
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Li G, Huang P, Cui SS, Tan YY, He YC, Shen X, Jiang QY, Huang P, He GY, Li BY, Li YX, Xu J, Wang Z, Chen SD. Mechanisms of motor symptom improvement by long-term Tai Chi training in Parkinson’s disease patients. Transl Neurodegener 2022; 11:6. [PMID: 35125106 PMCID: PMC8819852 DOI: 10.1186/s40035-022-00280-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Accepted: 01/05/2022] [Indexed: 11/10/2022] Open
Abstract
Background Tai Chi has been shown to improve motor symptoms in Parkinson’s disease (PD), but its long-term effects and the related mechanisms remain to be elucidated. In this study, we investigated the effects of long-term Tai Chi training on motor symptoms in PD and the underlying mechanisms. Methods Ninety-five early-stage PD patients were enrolled and randomly divided into Tai Chi (n = 32), brisk walking (n = 31) and no-exercise (n = 32) groups. At baseline, 6 months and 12 months during one-year intervention, all participants underwent motor symptom evaluation by Berg balance scale (BBS), Unified PD rating-scale (UPDRS), Timed Up and Go test (TUG) and 3D gait analysis, functional magnetic resonance imaging (fMRI), plasma cytokine and metabolomics analysis, and blood Huntingtin interaction protein 2 (HIP2) mRNA level analysis. Longitudinal self-changes were calculated using repeated measures ANOVA. GEE (generalized estimating equations) was used to assess factors associated with the longitudinal data of rating scales. Switch rates were used for fMRI analysis. False discovery rate correction was used for multiple correction. Results Participants in the Tai Chi group had better performance in BBS, UPDRS, TUG and step width. Besides, Tai Chi was advantageous over brisk walking in improving BBS and step width. The improved BBS was correlated with enhanced visual network function and downregulation of interleukin-1β. The improvements in UPDRS were associated with enhanced default mode network function, decreased L-malic acid and 3-phosphoglyceric acid, and increased adenosine and HIP2 mRNA levels. In addition, arginine biosynthesis, urea cycle, tricarboxylic acid cycle and beta oxidation of very-long-chain fatty acids were also improved by Tai Chi training. Conclusions Long-term Tai Chi training improves motor function, especially gait and balance, in PD. The underlying mechanisms may include enhanced brain network function, reduced inflammation, improved amino acid metabolism, energy metabolism and neurotransmitter metabolism, and decreased vulnerability to dopaminergic degeneration. Trial registration This study has been registered at Chinese Clinical Trial Registry (Registration number: ChiCTR2000036036; Registration date: August 22, 2020). Supplementary Information The online version contains supplementary material available at 10.1186/s40035-022-00280-7.
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18
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Zheng JH, Sun WH, Ma JJ, Wang ZD, Chang QQ, Dong LR, Shi XX, Li MJ. Resting-state functional magnetic resonance imaging in patients with Parkinson’s disease with and without constipation: a prospective study. Clin Auton Res 2022; 32:51-58. [DOI: 10.1007/s10286-022-00851-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 01/12/2022] [Indexed: 02/07/2023]
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19
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Portnova GV. Resting-state network activity revealed by EEG in unresponsive hospice patients at the end of life. Clin Neurophysiol 2021; 135:162-163. [PMID: 34952804 DOI: 10.1016/j.clinph.2021.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Accepted: 12/06/2021] [Indexed: 11/17/2022]
Affiliation(s)
- Galina V Portnova
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, 5A Butlerova St., Moscow, 117485, Russia.
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Li N, Lei D, Peng J, Suo X, Li J, Duan L, Chen C, Gong Q, Peng R. Brain network topology and future development of freezing of gait in Parkinson's disease: a longitudinal study. J Neurol 2021; 269:2503-2512. [PMID: 34618223 DOI: 10.1007/s00415-021-10817-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 09/08/2021] [Accepted: 09/21/2021] [Indexed: 02/06/2023]
Abstract
BACKGROUND Freezing of gait (FOG) is a common disabling gait disturbance in Parkinson's disease (PD). The objectives of this study were to explore alterations in the topological organization of whole-brain functional networks in patients with PD who will develop FOG. METHODS We recruited 20 patients with PD who developed FOG (PD-FOGt) during a 5-year follow-up period, 20 patients with PD who did not developed FOG (PD-FOGn) within the follow-up period, and 20 healthy control subjects. Using graph theory approaches, we performed a comparative analysis of the topological organization of whole-brain functional networks among the groups, and further explored their potential relationships with latency to develop FOG. RESULTS At baseline, the global topological properties of functional brain networks in PD-FOGt and PD-FOGn showed no abnormalities. Additionally, regarding regional topological properties, compared with PD-FOGn patients, PD-FOGt patients exhibited decreased nodal centrality in the left middle frontal gyrus (MFG). Although there were no significant differences compared with PD-FOGn patients, the PD-FOGt group exhibited the lowest nodal centrality values in the frontal cortex (left gyrus rectus), and visual cortex (bilateral inferior occipital gyrus and left fusiform gyrus), and the highest nodal centrality values in the cerebellum (vermis_6) among the three groups. However, no relationship was found between the nodal centrality in above brain regions and latency to develop FOG. CONCLUSION This study demonstrates the disrupted regional topological organization might contribute to the future development of FOG in PD patients, especially associated with damage to the left MFG.
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Affiliation(s)
- Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Du Lei
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH, USA
| | - Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Xueling Suo
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Chaolan Chen
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China
| | - Qiyong Gong
- Department of Radiology, Huaxi MR Research Center (HMRRC), West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, No. 37 Guoxue Xiang, Chengdu, 610041, Sichuan, China.
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Li N, Suo X, Zhang J, Lei D, Wang L, Li J, Peng J, Duan L, Gong Q, Peng R. Disrupted functional brain network topology in Parkinson's disease patients with freezing of gait. Neurosci Lett 2021; 759:135970. [PMID: 34023405 DOI: 10.1016/j.neulet.2021.135970] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 05/16/2021] [Accepted: 05/17/2021] [Indexed: 02/05/2023]
Abstract
BACKGROUND Freezing of gait (FOG) is a common and debilitating gait disturbance in patients with Parkinson's disease (PD), but the potential mechanisms are still unclear. This study aimed to explore alterations in the topological organization of whole-brain functional networks in PD patients with FOG. METHODS We recruited 75 patients with PD, 37 patients with FOG and 38 patients without FOG, to undergo resting-state functional magnetic resonance imaging (fMRI). The whole-brain functional networks were constructed, and the topological properties at three (global, nodal, and connectional) levels were analyzed using graph theory approaches. RESULTS Compared with patients without FOG, patients with FOG exhibited altered global topological properties (a significant decrease in the normalized clustering coefficient and small-worldness), implying a shift toward randomization in their functional brain networks. At the node and connectional levels, patients with FOG showed increased nodal centralities and functional connectivity in the sensorimotor network, frontoparietal network, visual network, subcortical and limbic regions, and decreased nodal centralities in the frontoparietal network and the cerebellum. Furthermore, the altered nodal centralities in the right hippocampus (HIP) were positively correlated with FOG severity. CONCLUSIONS This study suggests that FOG in PD is associated with disrupted topological organization of whole-brain functional networks, involving dysfunction of the multiple networks.
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Affiliation(s)
- Nannan Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xueling Suo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jinhong Zhang
- Department of Internal Medicine, Wangjiang Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Du Lei
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Wang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Junying Li
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Jiaxin Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Liren Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Rong Peng
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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