ArticleFrontiers in neuroscience2019
Brain Connectivity and Information-Flow Breakdown Revealed by a Minimum Spanning Tree-Based Analysis of MRI Data in Behavioral Variant Frontotemporal Dementia.
Article in Frontiers in neuroscience, 2019. 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.
- A multi-modal approach for the treatment of non-fluent/agrammatic variant of Primary Progressive Aphasia.Brain communications · 2025Trial
- Brain Topology Disruption in Early-Onset Dementia: Review of Current Findings and the Need for Network Resilience Focused Models.Brain and behavior · 2025Review
- Persistent homology-based functional connectivity and its association with cognitive ability: Life-span study.Human brain mapping · 2023Article
- Non-invasive mapping of epileptogenic networks predicts surgical outcome.Brain : a journal of neurology · 2023Article
- Clinical relevance of disrupted topological organization of anatomical connectivity in behavioral variant frontotemporal dementia.Neurobiology of aging · 2023Article
- Multiclass characterization of frontotemporal dementia variants via multimodal brain network computational inference.Network neuroscience (Cambridge, Mass.) · 2023Article
- Article
- Functional connectivity in behavioral variant frontotemporal dementia.Brain and behavior · 2022Review
- Neuromodulation of brain power topography and network topology by prefrontal transcranial photobiomodulation.Journal of neural engineering · 2022Article
- Minimum spanning tree analysis of brain networks: A systematic review of network size effects, sensitivity for neuropsychiatric pathology, and disorder specificity.Network neuroscience (Cambridge, Mass.) · 2022Article
- The Role of Graph Theory in Evaluating Brain Network Alterations in Frontotemporal Dementia.Frontiers in neurology · 2022Review
- Disentangling age- and disease-related alterations in schizophrenia brain network using structural equation modeling: A graph theoretical study based on minimum spanning tree.Human brain mapping · 2021Article
- Changes in local brain function in mild cognitive impairment due to semantic dementia.CNS neuroscience & therapeutics · 2021Article
- Brain Structural Covariance Networks in Behavioral Variant of Frontotemporal Dementia.Brain sciences · 2021Article
- Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility.Advances in experimental medicine and biology · 2021Review
- Special Patterns of Dynamic Brain Networks Discriminate Between Face and Non-face Processing: A Single-Trial EEG Study.Frontiers in neuroscience · 2021Article
- Quantitative Identification of Functional Connectivity Disturbances in Neuropsychiatric Lupus Based on Resting-State fMRI: A Robust Machine Learning Approach.Brain sciences · 2020Article
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10 authors.
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Abstract
Brain functional disruption and cognitive shortfalls as consequences of neurodegeneration are among the most investigated aspects in current clinical research. Traditionally, specific anatomical and behavioral traits have been associated with neurodegeneration, thus directly translatable in clinical terms. However, these qualitative traits, do not account for the extensive information flow breakdown within the functional brain network that deeply affect cognitive skills. Behavioural variant Frontotemporal Dementia (bvFTD) is a neurodegenerative disorder characterized by behavioral and executive functions disturbances. Deviations from the physiological cognitive functioning can be accurately inferred and modeled from functional connectivity alterations. Although the need for unbiased metrics is still an open issue in imaging studies, the graph-theory approach applied to neuroimaging techniques is becoming popular in the study of brain dysfunction. In this work, we assessed the global connectivity and topological alterations among brain regions in bvFTD patients using a minimum spanning tree (MST) based analysis of resting state functional MRI (rs-fMRI) data. Whilst several graph theoretical methods require arbitrary criteria (including the choice of network construction thresholds and weight normalization methods), MST is an unambiguous modeling solution, ensuring accuracy, robustness, and reproducibility. MST networks of 116 regions of interest (ROIs) were built on wavelet correlation matrices, extracted from 41 bvFTD patients and 39 healthy controls (HC). We observed a global fragmentation of the functional network backbone with severe disruption of information-flow highways. Frontotemporal areas were less compact, more isolated, and concentrated in less integrated structures, respect to healthy subjects. Our results reflected such complex breakdown of the frontal and temporal areas at both intra-regional and long-range connections. Our findings highlighted that MST, in conjunction with rs-fMRI data, was an effective method for quantifying and detecting functional brain network impairments, leading to characteristic bvFTD cognitive, social, and executive functions disorders.
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