ArticleBrain and behavior2025
Resting-State Functional Connectivity of Sensorimotor and Default Mode Networks and Lower Limb Performance in Chronic Stroke: A Cross-Sectional Study.
Article in Brain and behavior, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03666533 (Transcranial Direct Current Stimulation for Post-stroke Gait Rehab), which is not on this map. Cited by 1 paper.
What it found
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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.
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.
Transcranial Direct Current Stimulation for Post-stroke Gait Rehab
Who cites it
1 citing paper in PubMed.
- Effect of robot-assisted gait training combined with electroacupuncture on lower limb motor function and brain network characteristics in stroke: an EEG study.Journal of neuroengineering and rehabilitation · 2025Trial
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
introductionStroke disrupts functional brain connectivity, yet how this relates to lower limb motor and sensory abilities is not well understood. Greater knowledge of movement-related brain connectivity can aide in the development of better interventions for recovery after stroke. Our objective was to evaluate the relationship between lower limb performance and resting-state functional connectivity (rsFC) of large-scale brain networks for individuals with chronic motor deficits (> 6 months) after stroke.
methodsResting-state functional magnetic resonance imaging and lower limb clinical measures were collected for 37 individuals. Regions of interest (ROI)-to-ROI connectivity analysis was conducted for cortical sensorimotor network (SMN) (cortical SMN), SMN with both cortical and subcortical ROIs (SMN), and default mode network (DMN). Relationship of ROI-ROI connectivity and clinical measures or lesion load was assessed using general linear models. Graph theory metrics (global efficiency, clustering coefficient, and betweenness centrality) were related to clinical measures using elastic nets analysis.
resultsGreater connectivity between several SMN and DMN ROI pairs was associated with better gait speed, Timed-Up-and-Go score, and monofilament perception. The majority of ROI pairs showing statistically significant relationship with clinical measures were interhemispheric, non-homologous, and cortical-to-subcortical. Elastic net analysis for graph theory metrics revealed complexity and multi-directionality of the relationship of the individual ROIs to clinical outcomes and lesion load. There were unique sets of ROIs associated with each clinical measure for different graph metrics.
conclusionsrsFC between specific ROIs within SMN and DMN are related to lower limb performance. Non-homologous interhemispheric ROI-to-ROI connectivity was featured in the analysis. Graph theory analysis demonstrates the complex role that an individual ROI has in relation to sensorimotor function of lower extremity.
trial registrationClinicialtrials.gov registration number NCT03666533.
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