Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered

Pineda Pardo, José Ángel; Martínez, Kenia; Solana Sánchez, Ana Beatriz; Hernández Tamames, J.A.; Colom, Roberto y Pozo Guerrero, Francisco del (2015). Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered. "Brain Topography", v. 28 (n. 2); pp. 187-196. ISSN 0896-0267. https://doi.org/10.1007/s10548-014-0393-3.

Descripción

Título: Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered
Autor/es:
  • Pineda Pardo, José Ángel
  • Martínez, Kenia
  • Solana Sánchez, Ana Beatriz
  • Hernández Tamames, J.A.
  • Colom, Roberto
  • Pozo Guerrero, Francisco del
Tipo de Documento: Artículo
Título de Revista/Publicación: Brain Topography
Fecha: Marzo 2015
Volumen: 28
Materias:
Escuela: Centro de Tecnología Biomédica (CTB) (UPM)
Departamento: Aeronaves y Vehículos Espaciales
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Macroscopic brain networks have been widely described with the manifold of metrics available using graph theory. However, most analyses do not incorporate information about the physical position of network nodes. Here, we provide a multimodal macroscopic network characterization while considering the physical positions of nodes. To do so, we examined anatomical and functional macroscopic brain networks in a sample of twenty healthy subjects. Anatomical networks are obtained with a graph based tractography algorithm from diffusion-weighted magnetic resonance images (DW-MRI). Anatomical con- nections identified via DW-MRI provided probabilistic constraints for determining the connectedness of 90 dif- ferent brain areas. Functional networks are derived from temporal linear correlations between blood-oxygenation level-dependent signals derived from the same brain areas. Rentian Scaling analysis, a technique adapted from very- large-scale integration circuits analyses, shows that func- tional networks are more random and less optimized than the anatomical networks. We also provide a new metric that allows quantifying the global connectivity arrange- ments for both structural and functional networks. While the functional networks show a higher contribution of inter-hemispheric connections, the anatomical networks highest connections are identified in a dorsal?ventral arrangement. These results indicate that anatomical and functional networks present different connectivity organi- zations that can only be identified when the physical locations of the nodes are included in the analysis.

Más información

ID de Registro: 33513
Identificador DC: http://oa.upm.es/33513/
Identificador OAI: oai:oa.upm.es:33513
Identificador DOI: 10.1007/s10548-014-0393-3
URL Oficial: http://link.springer.com/article/10.1007%2Fs10548-014-0393-3
Depositado por: Memoria Investigacion
Depositado el: 12 Abr 2015 12:59
Ultima Modificación: 01 Abr 2016 22:56
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