ArticleNetwork neuroscience (Cambridge, Mass.)2022
Connectomic analysis of Alzheimer's disease using percolation theory.
Article in Network neuroscience (Cambridge, Mass.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
8 citing papers in PubMed.
- Foundations of Gerophysics.Aging · 2026Article
- Multilayer network analysis across cortical depths in 7-T resting-state fMRI.Network neuroscience (Cambridge, Mass.) · 2025Article
- Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI.bioRxiv : the preprint server for biology · 2024Article
- The brain network hub degeneration in Alzheimer's disease.Biophysics reports · 2024Article
- Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer's disease.Network neuroscience (Cambridge, Mass.) · 2024Article
- Age-related differences in affective behaviors in mice: possible role of prefrontal cortical-hippocampal functional connectivity and metabolomic profiles.Frontiers in aging neuroscience · 2024Article
- Increasing hub disruption parallels dementia severity in autosomal dominant Alzheimer disease.bioRxiv : the preprint server for biology · 2023Article
- Early path dominance as a principle for neurodevelopment.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Alzheimer's disease (AD) is a severe neurodegenerative disorder that affects a growing worldwide elderly population. Identification of brain functional biomarkers is expected to help determine preclinical stages for targeted mechanistic studies and development of therapeutic interventions to deter disease progression. Connectomic analysis, a graph theory-based methodology used in the analysis of brain-derived connectivity matrices was used in conjunction with percolation theory targeted attack model to investigate the network effects of AD-related amyloid deposition. We used matrices derived from resting-state functional magnetic resonance imaging collected on mice with extracellular amyloidosis (TgCRND8 mice,
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Registered trials
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