Evidence map›Paper›PMID 39523453›Full record

ArticleCNS neuroscience & therapeutics2024

Static and Dynamic Functional Network Connectivity in Parkinson's Disease Patients With Postural Instability and Gait Disorder.

Bo Shen, Qun Yao, Yixuan Zhang, Yinyin Jiang, Yaxi Wang, Xu Jiang, Yang Zhao, Haiying Zhang, Shuangshuang Dong, Dongfeng Li and 9 more

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Bo ShenDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Qun YaoDepartment of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0002-2336-2018
Yixuan ZhangMedical Basic Research Innovation Center for Cardiovascular and Cerebrovascular Diseases, Ministry of Education, China.ORCID 0000-0001-9781-6281
Yinyin JiangDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Yaxi WangDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Xu JiangDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Yang ZhaoDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Haiying ZhangDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Shuangshuang DongDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Dongfeng LiDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Yaning ChenDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Yang PanDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Jun YanDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.
Feng HanKey Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China.ORCID 0000-0002-4868-3491
Shengrong LiKey Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Qi ZhuKey Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Daoqiang ZhangKey Laboratory of Brain-Machine Intelligence Technology, Ministry of Education, Nanjing University of Aeronautics and Astronautics, Nanjing, China.
Li ZhangDepartment of Geriatrics, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.ORCID 0000-0003-1092-7531
Yun-Cheng WuDepartment of Neurology, Shanghai General Hospital of Nanjing Medical University, Shanghai, China.ORCID 0000-0003-4581-6524

Funding

Fundamental Research Funds for the Central Universities NJ2024029Jiangsu Province Elderly Health Project NO.LD2021013Jiangsu Provincial Cadre Health Projects NO.BJ20005Medical Science and Technology Development Foundation, Nanjing Municipality Health Bureau NO.QRX17026Nanjing Brain Hospital Youth Talent Project 23-25-2R11Nanjing Brain Hospital Youth Talent Project 23-25-2R6Nanjing Rehabilitation Medicine Center ProjectNational Natural Science Foundation of China NO.81971185National Natural Science Foundation of China NO.82171243National Natural Science Foundation of China NO.82171249National Natural Science Foundation of China NO.82204352Special Funds of the Jiangsu Provincial Key Research and Development Program NO.BE2022842
6 · The paper itself

Abstract

aimsThe exact cause of the parkinsonism gait remains uncertain. We first focus on understanding the underlying neurological reasons for these symptoms through the examination of both static functional network connectivity (SFNC) and dynamic functional network connectivity (DFNC).

methodsWe recruited 64 postural instability and gait disorder-dominated Parkinson's disease (PIGD-PD) patients, 31 non-PIGD-PD (nPIGD-PD) patients, and 54 healthy controls (HC) from Nanjing Brain Hospital. The GIFT software identified five distinct independent components: the basal ganglia (BG), cerebellum (CB), sensory networks (SMN), default mode network (DMN), and central executive network (CEN). We conducted a comparison between the SFNC and DFNC of the five networks and analyzed their correlations with postural instability and gait disorder (PIGD) symptoms.

resultsCompared with nPIGD-PD patients, the PIGD-PD patients demonstrated reduced connectivity between CEN and DMN while spending less mean dwell time (MDT) in state 4. This is characterized by strong connections. Compared with HC, PIGD-PD patients exhibited enhanced connectivity in the SFNC between CB and CEN, as well as the network between CB and DMN. Patients with PIGD-PD spent more MDT in state 1, which is characterized by few connections, and less MDT in state 4. In state 3, there was an increase in the functional connectivity between the CB and DMN in patients with PIGD-PD. The nPIGD patients showed increased SFNC connectivity between CB and DMN compared to HC. These patients spent more MDT in state 1 and less in state 4. The MDT and fractional windows of state 2 showed a positive link with PIGD scores.

conclusionPatients with PIGD-PD exhibit a higher likelihood of experiencing reduced brain connectivity and impaired information processing. The enhanced connection between the cerebellum and DMN networks is considered a type of dynamic compensation.

Indexed as

Gait Disorders, NeurologicMagnetic Resonance ImagingParkinson DiseasePostural BalanceAgedBrainConnectomeFemaleHumansMaleMiddle AgedNerve NetNeural Pathways

Identifiers

PMID39523453
PMCPMC11551039

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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.