ArticleHuman brain mapping2020
Sensory-motor network topology in multiple sclerosis: Structural connectivity analysis accounting for intrinsic density discrepancy.
Article in Human brain mapping, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 36 citations in OpenAlex.
- Multimodal MRI biomarkers and machine learning in neuromyelitis optica spectrum disorder: a review.Frontiers in neurology · 2026Review
- A multi-compartment model for pathological connectomes.Network neuroscience (Cambridge, Mass.) · 2025Article
- Resting-State Sensory-Motor Connectivity between Hand and Mouth as a Neural Marker of Socioeconomic Disadvantage, Psychosocial Stress, Cognitive Difficulties, Impulsivity, Depression, and Substance Use in Children.Journal of cellular neuroscience · 2025Article
- Functional gradients reveal cortical hierarchy changes in multiple sclerosis.Human brain mapping · 2024Article
- Genetic architecture of the structural connectome.Nature communications · 2024Article
- Pervasive alterations of intra-axonal volume and network organization in young children with a 16p11.2 deletion.Translational psychiatry · 2024Article
- Progressive remodeling of structural networks following surgery for operculo-insular epilepsy.Frontiers in neurology · 2024Article
- Developmental differences in canonical cortical networks: Insights from microstructure-informed tractography.Network neuroscience (Cambridge, Mass.) · 2024Article
- Evaluation of tractography-based myelin-weighted connectivity across the lifespan.Frontiers in neuroscience · 2023Article
- An investigation of the association between focal damage and global network properties in cognitively impaired and cognitively preserved patients with multiple sclerosis.Frontiers in neuroscience · 2023Article
- The human brain connectome weighted by the myelin content and total intra-axonal cross-sectional area of white matter tracts.Network neuroscience (Cambridge, Mass.) · 2023Article
- Classification of multiple sclerosis patients based on structural disconnection: A robust feature selection approach.Journal of neuroimaging : official journal of the American Society of Neuroimaging · 2022Article
- Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review.NeuroImage · 2022Review
- Bundle myelin fraction (BMF) mapping of different white matter connections using microstructure informed tractography.NeuroImage · 2022Article
- Microstructure-Weighted Connectomics in Multiple Sclerosis.Brain connectivity · 2022Review
- Structural disconnection and functional reorganization in Fabry disease: a multimodal MRI study.Brain communications · 2022Article
- Analysis of Brain Structural Connectivity Networks and White Matter Integrity in Patients With Mild Cognitive Impairment.Frontiers in aging neuroscience · 2022Article
- Neuroimaging Correlates of Cognitive Dysfunction in Adults with Multiple Sclerosis.Brain sciences · 2021Review
- Structural and Functional Connectivity Substrates of Cognitive Impairment in Multiple Sclerosis.Frontiers in neurology · 2021Review
- Sensory-motor network topology in multiple sclerosis: Structural connectivity analysis accounting for intrinsic density discrepancy.Human brain mapping · 2020Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Graph theory and network modelling have been previously applied to characterize motor network structural topology in multiple sclerosis (MS). However, between-group differences disclosed by graph analysis might be primarily driven by discrepancy in density, which is likely to be reduced in pathologic conditions as a consequence of macroscopic damage and fibre loss that may result in less streamlines properly traced. In this work, we employed the convex optimization modelling for microstructure informed tractography (COMMIT) framework, which, given a tractogram, estimates the actual contribution (or weight) of each streamline in order to optimally explain the diffusion magnetic resonance imaging signal, filtering out those that are implausible or not necessary. Then, we analysed the topology of this 'COMMIT-weighted sensory-motor network' in MS accounting for network density. By comparing with standard connectivity analysis, we also tested if abnormalities in network topology are still identifiable when focusing on more 'quantitative' network properties. We found that topology differences identified with standard tractography in MS seem to be mainly driven by density, which, in turn, is strongly influenced by the presence of lesions. We were able to identify a significant difference in density but also in network global and local properties when accounting for density discrepancy. Therefore, we believe that COMMIT may help characterize the structural organization in pathological conditions, allowing a fair comparison of connectomes which considers discrepancies in network density. Moreover, discrepancy-corrected network properties are clinically meaningful and may help guide prognosis assessment and treatment choice.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.