Evidence map›Paper›PMID 36708666›Full record

ArticleNeuroImage. Clinical2023

Aberrant dynamic Functional-Structural connectivity coupling of Large-scale brain networks in poststroke motor dysfunction.

Xiaoying Liu, Shuting Qiu, Xiaoyang Wang, Hui Chen, Yuting Tang, Yin Qin

Abstract read
In one paragraph

Article in NeuroImage. Clinical, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

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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

15 citing papers in PubMed.

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4 · The record

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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

6 authors.

Xiaoying LiuDepartment of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China.
Shuting QiuDepartment of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China.
Xiaoyang WangDepartment of the Fujian Key Laboratory of Functional Imaging, Department of Radiology, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou 350025, China.
Hui ChenDepartment of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China.
Yuting TangDepartment of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China.
Yin QinDepartment of Rehabilitation Medicine, The 900th Hospital of People's Liberation Army (Fuzhou General Hospital of Nanjing Military Region), Fuzhou, 350025, China; Department of Rehabilitation Medicine, Fuzhou General Hospital (Dongfang Hospital), Xiamen University, Fuzhou 350025, China. Electronic address: baby792305220@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background and purposeStroke may lead to widespread functional and structural reorganization in the brain. Several studies have reported a potential correlation between functional network changes and structural network changes after stroke. However, it is unclear how functional-structural relationships change dynamically over the course of one resting-state fMRI scan in patients following a stroke; furthermore, we know little about their relationships with the severity of motor dysfunction. Therefore, this study aimed to investigate dynamic functional and structural connectivity (FC-SC) coupling and its relationship with motor function in subcortical stroke from the perspective of network dynamics.

methodsResting-state functional magnetic resonance imaging and diffusion tensor imaging were obtained from 39 S patients (19 severe and 20 moderate) and 22 healthy controls (HCs). Brain structural networks were constructed by tracking fiber tracts in diffusion tensor imaging, and structural network topology metrics were calculated using a graph-theoretic approach. Independent component analysis, the sliding window method, and k-means clustering were used to calculate dynamic functional connectivity and to estimate different dynamic connectivity states. The temporal patterns and intergroup differences of FC-SC coupling were analyzed within each state. We also calculated dynamic FC-SC coupling and its relationship with functional network efficiency. In addition, the correlation between FC-SC coupling and the Fugl-Meyer assessment scale was analyzed.

resultsFor SC, stroke patients showed lower global efficiency than HCs (all P < 0.05), and severely affected patients had a higher characteristic path length (P = 0.003). For FC and FC-SC coupling, stroke patients predominantly showed lower local efficiency and reduced FC-SC coupling than HCs in state 2 (all P < 0.05). Furthermore, severely affected patients also showed lower local efficiency (P = 0.031) and reduced FC-SC coupling (P = 0.043) in state 3, which was markedly linked to the severity of motor dysfunction after stroke. In addition, FC-SC coupling was correlated with functional network efficiency in state 2 in moderately affected patients (r = 0.631, P = 0.004) but not significantly in severely affected patients.

conclusionsStroke patients show abnormal dynamic FC-SC coupling characteristics, especially in individuals with severe injuries. These findings may contribute to a better understanding of the anatomical functional interactions underlying motor deficits in stroke patients and provide useful information for personalized rehabilitation strategies.

Indexed as

Diffusion Tensor ImagingStrokeBrainBrain MappingHumansMagnetic Resonance ImagingBrain networksDiffusion tensor imagingDynamic FC-SC couplingResting-state fMRIStrokeTopological analysis

Identifiers

PMID36708666
PMCPMC10037213

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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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 Socratic graph.