ArticleHuman brain mapping2021
Topologically convergent and divergent morphological gray matter networks in early-stage Parkinson's disease with and without mild cognitive impairment.
Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine learning for the detection and diagnosis of cognitive impairment in Parkinson's Disease: A systematic review.PloS one · 2024Pooled it
- Global Alterations of Whole Brain Structural Connectome in Parkinson's Disease: A Meta-analysis.Neuropsychology review · 2023Pooled it
- Topological disruptions of metabolic brain networks in early-stage chronic kidney disease.BMC medical imaging · 2026Article
- Structural covariance network alterations across the spectrum of cognitive status in Parkinson's disease.Clinical parkinsonism & related disorders · 2026Review
- MRI Epicenters Differentiate Spatiotemporal Patterns of Neurodegeneration in Parkinson's Disease.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Brainstem and cerebellar radiological findings in progressive supranuclear palsy.Brain communications · 2025Review
- Integrated cerebellar radiomic-network model for predicting mild cognitive impairment in Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- A multimodal MRI framework employing machine learning for detecting beginning cognitive impairment in Parkinson's disease.Frontiers in neuroscience · 2025Article
- Diagnostic Accuracy of Machine Learning-Assisted MRI for Mild Cognitive Impairment in Parkinson's Disease: A Systematic Review and Meta-Analysis.Parkinson's disease · 2025Review
- Facial emotion recognition in individuals with mild cognitive impairment: An exploratory study.Cognitive, affective & behavioral neuroscience · 2024Article
- Mild cognitive impairment in Parkinson's disease: current view.Frontiers in cognition · 2024Review
- Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks.International journal of molecular sciences · 2023Review
- Individual-level brain morphological similarity networks: Current methodologies and applications.CNS neuroscience & therapeutics · 2023Review
- Altered large-scale individual-based morphological brain network in spinocerebellar ataxia type 3.CNS neuroscience & therapeutics · 2023Article
- Linking the cerebellum to Parkinson disease: an update.Nature reviews. Neurology · 2023Review
- Abnormal functional connectivity density involvement in freezing of gait and its application for subtyping Parkinson's disease.Brain imaging and behavior · 2023Article
- Topological disruption of high-order functional networks in cognitively preserved Parkinson's disease.CNS neuroscience & therapeutics · 2023Article
- Brain functional network abnormalities in parkinson's disease with mild cognitive impairment.Cerebral cortex (New York, N.Y. : 1991) · 2022Article
- Dopamine depletion and subcortical dysfunction disrupt cortical synchronization and metastability affecting cognitive function in Parkinson's disease.Human brain mapping · 2022Article
- Topologically Disrupted Gray Matter Networks in Drug-Naïve Essential Tremor Patients With Poor Sleep Quality.Frontiers in neurology · 2022Article
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Patients with Parkinson's disease with mild cognitive impairment (PD-M) progress to dementia more frequently than those with normal cognition (PD-N), but the underlying neurobiology remains unclear. This study aimed to define the specific morphological brain network alterations in PD-M, and explore their potential diagnostic value. Twenty-four PD-M patients, 17 PD-N patients, and 29 healthy controls (HC) underwent a structural MRI scan. Similarity between interregional gray matter volume distributions was used to construct individual morphological brain networks. These were analyzed using graph theory and network-based statistics (NBS), and their relationship to neuropsychological tests was assessed. Support vector machine (SVM) was used to perform individual classification. Globally, compared with HC, PD-M showed increased local efficiency (p = .001) in their morphological networks, while PD-N showed decreased normalized path length (p = .008). Locally, similar nodal deficits were found in the rectus and lingual gyrus, and cerebellum of both PD groups relative to HC; additionally in PD-M nodal deficits involved several frontal and parietal regions, correlated with cognitive scores. NBS found that similar connections were involved in the default mode and cerebellar networks of both PD groups (to a greater extent in PD-M), while PD-M, but not PD-N, showed altered connections involving the frontoparietal network. Using connections identified by NBS, SVM allowed discrimination with high accuracy between PD-N and HC (90%), PD-M and HC (85%), and between the two PD groups (65%). These results suggest that default mode and cerebellar disruption characterizes PD, more so in PD-M, whereas frontoparietal disruption has diagnostic potential.
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