Disrupted brain connectivity in Alzheimer’s disease: Effects of network thresholding

Madelaine Daianu, Emily L. Dennis, Neda Jahanshad, Talia M. Nir, Arthurw Toga, Clifford R. Jack, Michael W. Weiner, Paul M. Thompson

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Diffusion imaging is accelerating our understanding of the human brain. As brain connectivity analyses become more popular, it is vital to develop reliable metrics of the brain’s connections, and their network properties, to allow statistical study of factors that influence brain ‘wiring’. Here we chart differences in brain structural networks between normal aging and Alzheimer’s disease (AD) using 3-T whole-brain diffusion-weighted images (DWI) from 66 subjects (22 AD/44 normal elderly). We performed whole-brain tractography based on the orientation distribution functions. Connectivity matrices were compiled, representing the proportion of detected fibers interconnecting 68 cortical regions.We found clear disease effects on anatomical network topology in the structural backbone – the so-called ‘kcore’ – of the anatomical network, defined by varying the nodal degree threshold, k. However, the thresholding of the structural networks – based on their nodal degree – affected the pattern and interpretation of network differences discovered between patients and controls.

Original languageEnglish (US)
Pages (from-to)199-208
Number of pages10
JournalMathematics and Visualization
StatePublished - 2014
Event16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan
Duration: Sep 22 2013Sep 26 2013


  • Brain connectivity
  • DTI
  • Graph theory
  • K-core
  • Threshold
  • Tractography

ASJC Scopus subject areas

  • Modeling and Simulation
  • Geometry and Topology
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics


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