ArticleNPJ Parkinson's disease2023
Temporal and spatial variability of dynamic microstate brain network in early Parkinson's disease.
Article in NPJ Parkinson's disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Resting-state EEG changes associated with cognitive decline in Parkinson's disease: a systematic review.Journal of neural transmission (Vienna, Austria : 1996) · 2026Pooled it
- EEG biomarkers can predict early-stage Alzheimer's disease and correlate with intracerebral pathology: a multimodal machine learning study.Alzheimer's research & therapy · 2026Article
- Neuromodulation-induced normalization of cortical metastable dynamics signatures in Parkinson's disease.NPJ Parkinson's disease · 2026Article
- Dynamic brain synergy uncovers functional neural coordination in Parkinson's disease under dopaminergic modulation.Journal of neuroengineering and rehabilitation · 2026Article
- EEG microstate features under visual feedback gain conditions exhibit high sensitivity in identifying early Parkinson's disease patients.Journal of neuroengineering and rehabilitation · 2026Article
- Observational
- Disruption of low-frequency narrowband EEG microstate networks in Parkinson's disease with mild cognitive impairment.Journal of neuroengineering and rehabilitation · 2025Article
- PRISMA Systematic Review of Electroencephalographic (EEG) Microstates as Biomarkers: Secondary Findings in Memory Functions.Neurology international · 2025Review
- Temporal and spatial variability of large-scale dynamic brain networks in ASD.European child & adolescent psychiatry · 2025Article
- A novel ST-GCN model based on homologous microstate for subject-independent seizure prediction.Scientific reports · 2025Article
- Effects of two types of repetitive transcranial magnetic stimulation on brain network in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Interconnections and global transitions among functional states encode activity-related dynamics as brain topology changes after yoga training.Scientific reports · 2025Article
- Article
- Enhancing Attention Network Spatiotemporal Dynamics for Motor Rehabilitation in Parkinson's Disease.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Modulation of Brain Activities in Healthy Individuals by Acupuncture at Quchi (LI11).Brain topography · 2024Article
- Multi-perspective characterization of seizure prediction based on microstate analysis.Frontiers in neuroscience · 2024Article
- FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer's disease.Network neuroscience (Cambridge, Mass.) · 2024Article
- Deciphering network dysregulations and temporo-spatial dynamics in disorders of consciousness: insights from minimum spanning tree analysis.Frontiers in psychology · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Changes of brain network dynamics reveal variations in macroscopic neural activity patterns in behavioral and cognitive aspects. Quantification and application of changed dynamics in brain functional connectivity networks may contribute to a better understanding of brain diseases, and ultimately provide better prognostic indicators or auxiliary diagnostic tools. At present, most studies are focused on the properties of brain functional connectivity network constructed by sliding window method. However, few studies have explored evidence-based brain network construction algorithms that reflect disease specificity. In this work, we first proposed a novel approach to characterize the spatiotemporal variability of dynamic functional connectivity networks based on electroencephalography (EEG) microstate, and then developed a classification framework for integrating spatiotemporal variability of brain networks to improve early Parkinson's disease (PD) diagnostic performance. The experimental results indicated that compared with the brain network construction method based on conventional sliding window, the proposed method significantly improved the performance of early PD recognition, demonstrating that the dynamic spatiotemporal variability of microstate-based brain networks can reflect the pathological changes in the early PD brain. Furthermore, we observed that the spatiotemporal variability of early PD brain network has a specific distribution pattern in brain regions, which can be quantified as the degree of motor and cognitive impairment, respectively. Our work offers innovative methodological support for future research on brain network, and provides deeper insights into the spatiotemporal interaction patterns of brain activity and their variabilities in early PD.
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Registered trials
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.