Evidence map›Paper›PMID 41947308›Full record

ArticleCNS neuroscience & therapeutics2026

Shared and Specific Patterns of Brain Functional Network Abnormalities in Patients With Idiopathic Dystonia and Across Subtypes.

Gang Liu, Jiana Zhang, Yiheng Gao, Shiyuan Gong, Yuhan Luo, Linchang Zhong, Zilin Ou, Zhicong Yan, Weixi Zhang, Kangqiang Peng and 3 more

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Gang LiuDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.
Jiana ZhangDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.
Yiheng GaoInstitute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Shiyuan GongDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.ORCID 0009-0003-3622-9034
Yuhan LuoDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.
Linchang ZhongDepartment of Medical Imaging, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Zilin OuDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.
Zhicong YanDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.
Weixi ZhangDepartment of Neurology, the First Affiliated Hospital, Sun Yat-Sen University, Guangdong Provincial Key Laboratory for Diagnosis and Treatment of Major Neurological Diseases, National Key Clinical Department and Key Discipline of Neurology, Guangzhou, China.
Kangqiang PengDepartment of Medical Imaging, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Huiming LiuDepartment of Medical Imaging, Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in Southern China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
Qingmao HuShenzhen University of Advanced Technology, Shenzhen, China.
Jinping XuInstitute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.ORCID 0000-0003-3877-5445

Funding

Guangdong Key Project 2018B030335001Guangdong Province International Cooperation Base for Early Intervention and Functional Rehabilitation of Neurological Diseases 2020A0505020004Guangdong Provincial Clinical Research Center for Neurological Diseases 2020B1111170002Guangdong Provincial Engineering Center for Major Neurological Disease TreatmentGuangdong Provincial Translational Medicine Innovation Platform for Diagnosis and Treatment of Major Neurological DiseaseGuangzhou Key Project 202007030002Guangzhou Major Difficult and Rare Diseases Project 2024MDRD02Guangzhou Science and Technology Plan (Industry-University-Research Cooperation) 2023B03J0466National Natural Science Foundation of China 62476267National Natural Science Foundation of China 81771137National Natural Science Foundation of China 81971103National Natural Science Foundation of China 82101399National Natural Science Foundation of China 82271300National Natural Science Foundation of China 82471258Natural Science Foundation of Guangdong Province 2021A1515010600Natural Science Foundation of Guangdong Province 2023A1515012739Natural Science Foundation of Guangdong Province 2024A1515030183Shenzhen Medical Research Fund A2503031
6 · The paper itself

Abstract

aimsAccumulating neuroimaging evidence showed that idiopathic dystonia is a large-scale network disorder, but whether the various clinical sub-types shared imaging abnormalities remains controversial. We aimed to determine whether various forms of idiopathic dystonia have common topological changes or are distinct entities.

methodsResting-state functional magnetic resonance imaging and clinical data were obtained from 215 patients with various forms of dystonia and 160 healthy controls (HCs). Whole-brain functional networks were constructed, and the topological parameters were calculated via graph theoretical analyses. Networks were compared between patients with idiopathic dystonia and HCs and in subgroup analyses (each dystonia subtype vs. HCs; one-to-one and one-to-many comparisons among blepharospasm [BSP], blepharospasm-oromandibular dystonia [BOD], and cervical dystonia [CD] subgroups). Then, we analyzed the relationship between network topological changes and clinical characteristics in patients with idiopathic dystonia.

resultsCompared to HCs, patients with idiopathic dystonia exhibited alterations in network integration and segregation. Subgroup analyses revealed similar changes in BSP and BOD but not in CD. Regionally, degree centrality and nodal efficiency (Ne) in the somatomotor network of patients with idiopathic dystonia decreased and increased in the subcortical and cerebellar networks. Decreased nodal clustering coefficient (Ncp) and nodal local efficiency were observed in the visual and subcortical networks. Similar regional alterations were observed in patients with BSP. Patients with idiopathic dystonia showed additional hub regions. Correlation analyses showed that higher Ne in visual and cerebellar networks correlated positively, and lower Ncp correlated negatively in the visual network with motor severity in patients with BSP.

conclusionOur findings suggest that patients with BSP and BOD share extensive reorganization in the large-scale functional network.

Indexed as

BrainDystonic DisordersNerve NetAdultBrain MappingFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeural PathwaysYoung Adultfunctional networksidiopathic dystoniasensorimotor integrationsubgroup analysestopological analyses

Identifiers

PMID41947308
PMCPMC13056703

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.