Literature DB >> 24711485

Connectome and Maturation Profiles of the Developing Mouse Brain Using Diffusion Tensor Imaging.

Madhura Ingalhalikar1, Drew Parker1, Yasser Ghanbari1, Alex Smith1, Kegang Hua2, Susumu Mori2, Ted Abel3, Christos Davatzikos1, Ragini Verma1.   

Abstract

This paper presents a comprehensive effort to establish a structural mouse connectome using diffusion tensor magnetic resonance imaging coupled with connectivity analysis tools. This work lays the foundation for imaging-based structural connectomics of the mouse brain, potentially facilitating a whole-brain network analysis to quantify brain changes in connectivity during development, as well as deviations from it related to genetic effects. A connectomic trajectory of maturation during postnatal ages 2-80 days is presented in the C57BL/6J mouse strain, using a whole-brain connectivity analysis, followed by investigations based on local and global network features. The global network measures of density, global efficiency, and modularity demonstrated a nonlinear relationship with age. The regional network metrics, namely degree and local efficiency, displayed a differential change in the major subcortical structures such as the thalamus and hippocampus, and cortical regions such as visual and motor cortex. Finally, the connectomes were used to derive an index of "brain connectivity index," which demonstrated a high correlation (r = 0.95) with the chronological age, indicating that brain connectivity is a good marker of normal age progression, hence valuable in detecting subtle deviations from normality caused by genetic, environmental, or pharmacological manipulations.
© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  connectome; diffusion tensor imaging; maturation; mouse

Mesh:

Year:  2014        PMID: 24711485      PMCID: PMC4537430          DOI: 10.1093/cercor/bhu068

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  56 in total

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