Brain Fiber Architecture, Genetics, and Intelligence: A High Angular Resolution Diffusion Imaging (HARDI) Study

  • Authors:

  • Ming-Chang Chiang;Marina Barysheva;Agatha D. Lee;Sarah Madsen;Andrea D. Klunder;Arthur W. Toga;Katie L. Mcmahon;Greig I. Zubicaray;Matthew Meredith;Margaret J. Wright;Anuj Srivastava;Nikolay Balov;Paul M. Thompson

  • Affiliations:

  • Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,;Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,;Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,;Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,;Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,;Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,;Functional MRI Lab., Centre for Magnetic Resonance, Univ. Queensland, Brisbane, Australia;Functional MRI Lab., Centre for Magnetic Resonance, Univ. Queensland, Brisbane, Australia;Functional MRI Lab., Centre for Magnetic Resonance, Univ. Queensland, Brisbane, Australia;Queensland Institute of Medical Research, , Brisbane, Australia;Dept. of Statistics, Florida State University, Tallahassee,;Dept. of Statistics, Florida State University, Tallahassee,;Laboratory of Neuro Imaging, Dept. of Neurology, UCLA School of Medicine, Los Angeles,

  • Venue:
  • MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
  • Year:
  • 2008

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Abstract

We developed an analysis pipeline enabling population studies of HARDI data, and applied it to map genetic influences on fiber architecture in 90 twin subjects. We applied tensor-driven 3D fluid registration to HARDI, resampling the spherical fiber orientation distribution functions (ODFs) in appropriate Riemannian manifolds, after ODF regularization and sharpening. Fitting structural equation models (SEM) from quantitative genetics, we evaluated genetic influences on the Jensen-Shannon divergence (JSD), a novel measure of fiber spatial coherence, and on the generalized fiber anisotropy (GFA; [1]) a measure of fiber integrity. With random-effects regression, we mapped regions where diffusion profiles were highly correlated with subjects' intelligence quotient (IQ). Fiber complexity was predominantly under genetic control, and higher in more highly anisotropic regions; the proportion of genetic versus environmental control varied spatially. Our methods show promise for discovering genes affecting fiber connectivity in the brain.