ArticleScientific reports2018
Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Multiscale characterization and classification of Alzheimer's disease via integration of brain fingerprint radiomics and graph‑theoretical network metrics.Neuroradiology · 2026Article
- Cortical similarity networks in the rat brain: Postnatal development and sensitivity to early life stress.Network neuroscience (Cambridge, Mass.) · 2026Article
- The brain cortical similarity network: Development and sensitivity to early life stress in a rat model.bioRxiv : the preprint server for biology · 2025Article
- Cortical morphological networks for profiling autism spectrum disorder using tensor component analysis.Frontiers in neurology · 2024Article
- A comprehensive survey of complex brain network representation.Meta-radiology · 2023Article
- Multiple sclerosis clinical forms classification with graph convolutional networks based on brain morphological connectivity.Frontiers in neuroscience · 2023Article
- Imputing Brain Measurements Across Data Sets via Graph Neural Networks.Predictive Intelligence in Medicine. PRIME (Workshop) · 2023Article
- Emerging Materials, Wearables, and Diagnostic Advancements in Therapeutic Treatment of Brain Diseases.Biosensors · 2022Review
- Estimating High-Order Brain Functional Networks in Bayesian View for Autism Spectrum Disorder Identification.Frontiers in neuroscience · 2022Article
- Estimation of gender-specific connectional brain templates using joint multi-view cortical morphological network integration.Brain imaging and behavior · 2021Article
- Gender differences in cortical morphological networks.Brain imaging and behavior · 2020Article
- Predicting full-scale and verbal intelligence scores from functional Connectomic data in individuals with autism Spectrum disorder.Brain imaging and behavior · 2020Article
- Morphological Brain Age Prediction using Multi-View Brain Networks Derived from Cortical Morphology in Healthy and Disordered Participants.Scientific reports · 2019Article
- Joint Pairing and Structured Mapping of Convolutional Brain Morphological Multiplexes for Early Dementia Diagnosis.Brain connectivity · 2019Article
- Article
- Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis.Frontiers in neuroinformatics · 2018Article
- Analysis of Progression Toward Alzheimer's Disease Based on Evolutionary Weighted Random Support Vector Machine Cluster.Frontiers in neuroscience · 2018Article
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Authors and funding
4 authors.
Funding
Abstract
Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer's disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, 'shape connections' between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus.
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