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Author Notes:

Corresponding author: Xiaoping Hu, Address: Hospital Education Annex, Biomedical Imaging Technology Center, 531 Asbury Circle, Suite 305, Atlanta, GA 30322, Fax: (404) 712-2707, Phone: (404) 712-2615, xhu3@emory.edu.

Subjects:

Research Funding:

This work was kindly supported by NIH 5P01 AG026423–03.

We also thank Dr. Helen Mayberg (NIH MH073719) and Dr. Paul Holtzheimer (NARSAD YIA) for kindly supplying part of the data used for these analyses.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Neurosciences
  • Neuroimaging
  • Radiology, Nuclear Medicine & Medical Imaging
  • Neurosciences & Neurology
  • connectivity
  • network
  • diffusion
  • tractography
  • small world
  • modularity
  • probabilistic
  • macaque
  • SMALL-WORLD NETWORKS
  • ECHO-PLANAR IMAGES
  • ANATOMICAL NETWORK
  • CEREBRAL-CORTEX
  • BEHAVIOR
  • MATTER

The effects of connection reconstruction method on the interregional connectivity of brain networks via diffusion tractography

Tools:

Journal Title:

Human Brain Mapping

Volume:

Volume 33, Number 8

Publisher:

, Pages 1894-1913

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Estimating the interregional structural connections of the brain via diffusion tractography is a complex procedure and the parameters chosen can affect the outcome of the connectivity matrix. Here, we investigated the influence of different connection reconstruction methods on brain connectivity networks. Specifically, we applied three connection reconstruction methods to the same set of diffusion MRI data, initiating tracking from deep white matter (method #1, M1), from the gray matter/white matter interface (M2), and from the gray/white matter interface with thresholded tract volume rather than the connection probability as the connectivity index (M3). Small-world properties, hub identification, and hemispheric asymmetry in connectivity patterns were then calculated and compared across methods. Despite moderate to high correlations in the graph-theoretic measures across different methods, significant differences were observed in small-world indices, identified hubs, and hemispheric asymmetries, highlighting the importance of reconstruction method on network parameters. Consistent with the prior reports, the left precuneus was identified as a hub region in all three methods, suggesting it has a prominent role in brain networks.

Copyright information:

© 2011 Wiley Periodicals, Inc.

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