TY - GEN
T1 - Brain network efficiency and topology depend on the fiber tracking method
T2 - 2013 IEEE 10th International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2013
AU - Zhan, Liang
AU - Jahanshad, Neda
AU - Jin, Yan
AU - Toga, Arthur W.
AU - McMahon, Katie L.
AU - De Zubicaray, Greig I.
AU - Martin, Nicholas G.
AU - Wright, Margaret J.
AU - Thompson, Paul M.
PY - 2013
Y1 - 2013
N2 - As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.
AB - As connectivity analyses become more popular, claims are often made about how the brain's anatomical networks depend on age, sex, or disease. It is unclear how results depend on tractography methods used to compute fiber networks. We applied 11 tractography methods to high angular resolution diffusion images of the brain (4-Tesla 105-gradient HARDI) from 536 healthy young adults. We parcellated 70 cortical regions, yielding 70×70 connectivity matrices, encoding fiber density. We computed popular graph theory metrics, including network efficiency, and characteristic path lengths. Both metrics were robust to the number of spherical harmonics used to model diffusion (4th-8th order). Age effects were detected only for networks computed with the probabilistic Hough transform method, which excludes smaller fibers. Sex and total brain volume affected networks measured with deterministic, tensor-based fiber tracking but not with the Hough method. Each tractography method includes different fibers, which affects inferences made about the reconstructed networks.
KW - Anatomical connectivity
KW - brain
KW - diffusion imaging
KW - efficiency
KW - networks
KW - random effects analysis
KW - tractography
UR - http://www.scopus.com/inward/record.url?scp=84881646893&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84881646893&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2013.6556679
DO - 10.1109/ISBI.2013.6556679
M3 - Conference contribution
AN - SCOPUS:84881646893
SN - 9781467364546
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 1134
EP - 1137
BT - ISBI 2013 - 2013 IEEE 10th International Symposium on Biomedical Imaging
Y2 - 7 April 2013 through 11 April 2013
ER -