Title
The multivariate A/C/E model and the genetics of fiber architecture
Abstract
We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 monozygotic (MZ) twins and 25 dizygotic (DZ) twin pairs (100 subjects total). First, the structural and DT scans were linearly co-registered. Structural MR scans were nonlinearly mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. After tensor re-orientation to realign them to the anatomy, we computed several scalar and multivariate DT-derived measures including the geodesic anisotropy (GA), the tensor eigenvalues and the full diffusion tensors. A covariance-weighted distance was measured between twins in the Log-Euclidean framework [2], and used as input to a maximum-likelihood based algorithm to compute the contributions from genetics (A), common environmental factors (C) and unique environmental ones (E) to fiber architecture. Quanititative genetic studies can take advantage of the full information in the diffusion tensor, using covariance weighted distances and statistics on the tensor manifold.
Year
DOI
Venue
2009
10.1109/ISBI.2009.5192999
ISBI
Keywords
Field
DocType
genetics,twin studies,multivariate statistics
Computer vision,Diffusion MRI,Tensor,Scalar (physics),Stress (mechanics),Artificial intelligence,Deformation (mechanics),Genetics,Eigenvalues and eigenvectors,Geodesic,Mathematics,Covariance
Conference
Volume
Citations 
PageRank 
2009
3
0.44
References 
Authors
12
12
Name
Order
Citations
PageRank
Agatha D Lee129623.02
Natasha Leporé212211.23
Yi-Yu Chou329022.25
caroline brun422223.32
Marina Barysheva526922.02
Ming-chang Chiang699754.25
Sarah Madsen713113.50
Katie L. Mcmahon837433.49
Greig I. De Zubicaray949143.04
Margaret J. Wright1043639.31
Arthur W. Toga113128261.46
Paul Thompson123860321.32