ArticlePloS one2015
Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- The ultrametric backbone is the union of all minimum spanning forests.Journal of physics. Complexity · 2024Article
- Genetic risk for schizophrenia is associated with increased proportion of indirect connections in brain networks revealed by a semi-metric analysis: evidence from population sample stratified for polygenic risk.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- The distance backbone of complex networks.Journal of complex networks · 2021Article
- Single-participant structural similarity matrices lead to greater accuracy in classification of participants than function in autism in MRI.Molecular autism · 2021Article
- fNIRS-based functional connectivity estimation using semi-metric analysis to study decision making by nursing students and registered nurses.Scientific reports · 2020Article
- Enhancement of indirect functional connections with shortest path length in the adult autistic brain.Human brain mapping · 2019Article
- Communication dynamics in complex brain networks.Nature reviews. Neuroscience · 2017Review
- Commentary: Semi-Metric Topology of the Human Connectome: Sensitivity and Specificity to Autism and Major Depressive Disorder.Frontiers in neuroscience · 2016Article
- A Winding Road: Alzheimer's Disease Increases Circuitous Functional Connectivity Pathways.Frontiers in computational neuroscience · 2015Article
- Semi-metric analysis of the functional brain network: Relationship with familial risk for psychotic disorder.NeuroImage. Clinical · 2015Article
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16 authors.
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Abstract
introductionThe human functional connectome is a graphical representation, consisting of nodes connected by edges, of the inter-relationships of blood oxygenation-level dependent (BOLD) time-series measured by MRI from regions encompassing the cerebral cortices and, often, the cerebellum. Semi-metric analysis of the weighted, undirected connectome distinguishes an edge as either direct (metric), such that there is no alternative path that is accumulatively stronger, or indirect (semi-metric), where one or more alternative paths exist that have greater strength than the direct edge. The sensitivity and specificity of this method of analysis is illustrated by two case-control analyses with independent, matched groups of adolescents with autism spectrum conditions (ASC) and major depressive disorder (MDD).
resultsSignificance differences in the global percentage of semi-metric edges was observed in both groups, with increases in ASC and decreases in MDD relative to controls. Furthermore, MDD was associated with regional differences in left frontal and temporal lobes, the right limbic system and cerebellum. In contrast, ASC had a broadly increased percentage of semi-metric edges with a more generalised distribution of effects and some areas of reduction. In summary, MDD was characterised by localised, large reductions in the percentage of semi-metric edges, whilst ASC is characterised by more generalised, subtle increases. These differences were corroborated in greater detail by inspection of the semi-metric backbone for each group; that is, the sub-graph of semi-metric edges present in >90% of participants, and by nodal degree differences in the semi-metric connectome.
conclusionThese encouraging results, in what we believe is the first application of semi-metric analysis to neuroimaging data, raise confidence in the methodology as potentially capable of detection and characterisation of a range of neurodevelopmental and psychiatric disorders.
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