ArticleFrontiers in neuroscience2023
Abnormal dynamic functional connectivity changes correlated with non-motor symptoms of Parkinson's disease.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Altered Inter-Network Functional Integration Underlies Speech Impairment in Parkinson's Disease: A Resting-State fMRI Analysis.Brain and behavior · 2026Article
- Dynamic thalamocortical functional connectivity disruptions in Parkinson's disease with probable REM sleep behavior disorder.Scientific reports · 2026Article
- Decoding dynamic brain networks in Parkinson's disease with temporal attention.Scientific reports · 2025Article
- Motor Functional Hierarchical Organization of Cerebrum and Its Underlying Genetic Architecture in Parkinson's Disease.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Hot Topics and Frontiers of Resting-State fMRI in Parkinson's Disease: Research Trends and Paradigm Shifts From a Bibliometric Perspective.Parkinson's disease · 2025Review
- Sequential patterning of dynamic brain states distinguish Parkinson's disease patients with mild cognitive impairments.NeuroImage. Clinical · 2025Article
- Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease.Human brain mapping · 2024Article
- Improving Functional Capacity and Quality of Life in Parkinson's Disease Patients through REAC Neuromodulation Treatments for Mood and Behavioral Disorders.Journal of personalized medicine · 2023Article
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6 authors.
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Abstract
Background: Non-motor symptoms are common in Parkinson's disease (PD) patients, decreasing quality of life and having no specific treatments. This research investigates dynamic functional connectivity (FC) changes during PD duration and its correlations with non-motor symptoms. Methods: Twenty PD patients and 19 healthy controls (HC) from PPMI dataset were collected and used in this study. Independent component analysis (ICA) was performed to select significant components from the entire brain. Components were grouped into seven resting-state intrinsic networks. Static and dynamic FC changes during resting-state functional magnetic resonance imaging (fMRI) were calculated based on selected components and resting state networks (RSN). Results: Static FC analysis results showed that there was no difference between PD-baseline (PD-BL) and HC group. Network averaged connection between frontoparietal network and sensorimotor network (SMN) of PD-follow up (PD-FU) was lower than PD-BL. Dynamic FC analysis results suggested four distinct states, and each state's temporal characteristics, such as fractional windows and mean dwell time, were calculated. The state 2 of our study showed positive coupling within and between SMN and visual network, while the state 3 showed hypo-coupling through all RSN. The fractional windows and mean dwell time of PD-FU state 2 (positive coupling state) were statistically lower than PD-BL. Fractional windows and mean dwell time of PD-FU state 3 (hypo-coupling state) were statistically higher than PD-BL. Outcome scales in Parkinson's disease-autonomic dysfunction scores of PD-FU positively correlated with mean dwell time of state 3 of PD-FU. Conclusion: Overall, our finding indicated that PD-FU patients spent more time in hypo-coupling state than PD-BL. The increase of hypo-coupling state and decrease of positive coupling state might correlate with the worsening of non-motor symptoms in PD patients. Dynamic FC analysis of resting-state fMRI can be used as monitoring tool for PD progression.
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