ArticleScientific reports2021
The corticolimbic structural covariance network as an early predictive biosignature for cognitive impairment in Parkinson's disease.
Article in Scientific reports, 2021. 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.
- Molecular Pathogenesis of Memory Impairment in Parkinson's Disease: An Exploration of Underlying Mechanisms.Health science reports · 2026Article
- Structural covariance network alterations across the spectrum of cognitive status in Parkinson's disease.Clinical parkinsonism & related disorders · 2026Review
- Abnormal topological organization of structural covariance networks in early-stage Parkinson's disease patients with autonomic dysfunction.Quantitative imaging in medicine and surgery · 2025Article
- Fine-grained features characterize hippocampal and amygdaloid change pattern in Parkinson's disease and discriminate cognitive-deficit subtype.CNS neuroscience & therapeutics · 2024Article
- Imaging the Limbic System in Parkinson's Disease-A Review of Limbic Pathology and Clinical Symptoms.Brain sciences · 2022Review
- Divergence Between Informant and Self-Ratings of Activities of Daily Living Impairments in Parkinson's Disease.Frontiers in aging neuroscience · 2022Article
- Magnetic Resonance Imaging Markers for Cognitive Impairment in Parkinson's Disease: Current View.Frontiers in aging neuroscience · 2022Review
- Study of the Biological Developmental Characteristics of the Eye in Children After Laser Surgery for the Treatment of Retinopathy of Prematurity.Frontiers in medicine · 2021Article
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10 authors.
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Abstract
Structural covariance assesses similarities in gray matter between brain regions and can be applied to study networks of the brain. In this study, we explored correlations between structural covariance networks (SCNs) and cognitive impairment in Parkinson's disease patients. 101 PD patients and 58 age- and sex-matched healthy controls were enrolled in the study. For each participant, comprehensive neuropsychological testing using the Wechsler Adult Intelligence Scale-III and Cognitive Ability Screening Instrument were conducted. Structural brain MR images were acquired using a 3.0T whole body GE Signa MRI system. T1 structural images were preprocessed and analyzed using Statistical Parametric Mapping software (SPM12) running on Matlab R2016a for voxel-based morphometric analysis and SCN analysis. PD patients with normal cognition received follow-up neuropsychological testing at 1-year interval. Cognitive impairment in PD is associated with degeneration of the amygdala/hippocampus SCN. PD patients with dementia exhibited increased covariance over the prefrontal cortex compared to PD patients with normal cognition (PDN). PDN patients who had developed cognitive impairment at follow-up exhibited decreased gray matter volume of the amygdala/hippocampus SCN in the initial MRI. Our results support a neural network-based mechanism for cognitive impairment in PD patients. SCN analysis may reveal vulnerable networks that can be used to early predict cognitive decline in PD patients.
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