Skip to main content

Complex Mouse Brain Anatomical Network Attributes Estimated via Diffusion- MRI Data and Graph Theory

  • Conference paper
V Latin American Congress on Biomedical Engineering CLAIB 2011 May 16-21, 2011, Habana, Cuba

Abstract

Evidence about high global and local parallel information processing between brain gray matter regions has being previously reported for different mammalian species (e.g. cat, monkey and humans). Here our goal is to study these characteristics but this time in mouse looking for other different mammalian species that shares this trait, which should be indicating similar brain structural growing organizational strategies shaped conveniently trough the evolutionary processes. Specifically, anatomical connections between 150 anatomic regions covering all the gray matter of healthy (C3HeB.FeJ, n = 5) mice were estimated by means of fiber tractography techniques based on high resolution Diffusion Weighted MRI data, and from the resultant information individual brain structural networks were created considering each brain region as a node that can be connected to any other node (region) depending of the obtained evidence supporting white matter fiber connections amount them. Then the created individual structural brain networks were analyzed attending to five different topological measures: clustering, mean path length, local efficiency, global efficiency and small-worldness index. The results reveals the small-word attributes of the structural network of the mouse brain, at the same time that confirms a smaller global efficiency and bigger local efficiency in comparison with the equivalent random networks, which in conjunction is in agreement with the previous studies on mammalian species.

Considering that mouse animal models are of especial interest for biomedical research, in conjunction with the fact that current trends in human brain networks analyses are focused to detect topological network alterations associated to specific states of pathology, our methodology/findings could be of significant utility for the scientific community that employ the mouse animal model in the study of specific brain pathologies as well as their responds to different therapies.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Y. Iturria-Medina .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Berlin Heidelberg

About this paper

Cite this paper

Iturria-Medina, Y., Ontivero-Ortega, M., Canales-Rodríguez, E.J., Melie-García, L., Valdés-Hernández, P., Pérez-Fernández, A. (2013). Complex Mouse Brain Anatomical Network Attributes Estimated via Diffusion- MRI Data and Graph Theory. In: Folgueras Méndez, J., et al. V Latin American Congress on Biomedical Engineering CLAIB 2011 May 16-21, 2011, Habana, Cuba. IFMBE Proceedings, vol 33. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21198-0_17

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-21198-0_17

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21197-3

  • Online ISBN: 978-3-642-21198-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics