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Weighted networks are advantageous as the relation between different structural connections is preserved (instead of assigning equal weights to all tracts), and they are independent of network density thresholds (Gong et al. 2009; Rubinov and Sporns 2010).
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In certain cases the relationship between different structural properties is formed in a systematic way, e.g. larger brain regions tend to have more connections than smaller brain regions.
We define morphisms (mappings) between reaction networks that establish structural connections between them.
High functional connectivity was found between regions with low structural connectivity, possibly due to fibers not contained within the imaging slice or indirect structural connections; but low functional connectivity was not found between regions with high structural connectivity.
Network morphisms that are emulations provide an explanation of network structure, in that they reveal structural connections between networks that entail kinetic connections.
The connection among different structural components may be promoted by several means.
We first assessed the presence of structural connections between the DMN regions identified with GICA.
We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography.
Finite element models of the columns were created with ANSYS by considering the bond-slip effect between reinforcement and concrete, contact behavior of connection surface, and material nonlinearity, depending on different structural details.
Correlations in brain activity between two areas (functional connectivity) have been shown to relate to their underlying structural connections.
> -wrap-foot> We classify all connections into 2 main groups: Recurrent intralayer or "within-layer" connections and connections between different layers or "interlayer" connections.
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