Abstract
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 language | English |
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Pages (from-to) | 199-208 |
Number of pages | 10 |
Journal | Mathematics and Visualization |
Volume | 0 |
DOIs | |
State | Published - 2014 |
Externally published | Yes |
Event | 16th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013 - Nagoya, Japan Duration: 22 Sep 2013 → 26 Sep 2013 |
Keywords
- Brain connectivity
- DTI
- Graph theory
- K-core
- Threshold
- Tractography