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

Pineda Pardo, José Ángel and Martínez, Kenia and Solana Sánchez, Ana Beatriz and Hernández Tamames, J.A. and Colom, Roberto and 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.

Description

Title: Disparate connectivity for structural and functional networks is revealed when physical location of the connected nodes is considered
Author/s:
  • Pineda Pardo, José Ángel
  • Martínez, Kenia
  • Solana Sánchez, Ana Beatriz
  • Hernández Tamames, J.A.
  • Colom, Roberto
  • Pozo Guerrero, Francisco del
Item Type: Article
Título de Revista/Publicación: Brain Topography
Date: March 2015
ISSN: 0896-0267
Volume: 28
Subjects:
Faculty: Centro de Tecnología Biomédica (CTB) (UPM)
Department: Aeronaves y Vehículos Espaciales
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

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.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainAP2010-1317UnspecifiedUnspecifiedAyudas para la formación de profesorado universitario (FPU)

More information

Item ID: 33513
DC Identifier: http://oa.upm.es/33513/
OAI Identifier: oai:oa.upm.es:33513
DOI: 10.1007/s10548-014-0393-3
Official URL: http://link.springer.com/article/10.1007%2Fs10548-014-0393-3
Deposited by: Memoria Investigacion
Deposited on: 12 Apr 2015 12:59
Last Modified: 30 May 2019 14:33
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