ArticleFrontiers in aging neuroscience2018
Gray Matter Network Disruptions and Regional Amyloid Beta in Cognitively Normal Adults.
Article in Frontiers in aging neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Comparison of Brain Age With Standard MRI Assessment for Dementia Risk Stratification in Subjective and Mild Cognitive Impairment.Neurology · 2026Article
- Generative AI for amyloid PET from MRI: research promise and clinical considerations.European radiology · 2026Article
- Prediction of disease progression in individuals with subjective cognitive decline using brain network analysis.CNS neuroscience & therapeutics · 2024Article
- Disrupted single-subject gray matter networks are associated with cognitive decline and cortical atrophy in Alzheimer's disease.Frontiers in neuroscience · 2024Article
- Changes in Multiparametric Magnetic Resonance Imaging and Plasma Amyloid-Beta Protein in Subjective Cognitive Decline.Brain sciences · 2023Article
- Spatial navigation is associated with subcortical alterations and progression risk in subjective cognitive decline.Alzheimer's research & therapy · 2023Article
- Review
- Brain Network Organization and Aging.Advances in experimental medicine and biology · 2023Article
- Complex spiking neural networks with synaptic time-delay based on anti-interference function.Cognitive neurodynamics · 2022Article
- Nigral neuropathology of Parkinson's motor subtypes coincide with circuitopathies: a scoping review.Brain structure & function · 2022Article
- Subjective cognitive decline-related worries modulate the relationship between global amyloid load and gray matter volume in preclinical Alzheimer's disease.Brain imaging and behavior · 2022Article
- Rich-Club Connectivity of the Structural Covariance Network Relates to Memory Processes in Mild Cognitive Impairment and Alzheimer's Disease.Journal of Alzheimer's disease : JAD · 2022Article
- Grey matter network markers identify individuals with prodromal Alzheimer's disease who will show rapid clinical decline.Brain communications · 2022Article
- The association between global cognitive function and walking capacity in individuals with broad ranges of cognitive and physical function: Are there sex differences?Frontiers in rehabilitation sciences · 2022Article
- Gray matter network properties show distinct associations with CSF p-tau 181 levels and amyloid status in individuals without dementia.Aging brain · 2022Article
- The human connectome in Alzheimer disease - relationship to biomarkers and genetics.Nature reviews. Neurology · 2021Review
- Tau-related grey matter network breakdown across the Alzheimer's disease continuum.Alzheimer's research & therapy · 2021Article
- Comparing CSF amyloid-beta biomarker ratios for two automated immunoassays, Elecsys and Lumipulse, with amyloid PET status.Alzheimer's & dementia (Amsterdam, Netherlands) · 2021Article
- Neuroimaging advances regarding subjective cognitive decline in preclinical Alzheimer's disease.Molecular neurodegeneration · 2020Review
- Improving brain age prediction models: incorporation of amyloid status in Alzheimer's disease.Neurobiology of aging · 2020Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The accumulation of amyloid plaques is one of the earliest pathological changes in Alzheimer's disease (AD) and may occur 20 years before the onset of symptoms. Examining associations between amyloid pathology and other early brain changes is critical for understanding the pathophysiological underpinnings of AD. Alterations in gray matter networks might already start at early preclinical stages of AD. In this study, we examined the regional relationship between amyloid aggregation measured with positron emission tomography (PET) and gray matter network measures in elderly subjects with subjective memory complaints. Single-subject gray matter networks were extracted from T1-weigthed structural MRI in cognitively normal subjects (
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