Abstract
We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains’ continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer’s patients and controls. Our measures show significant differences between the two groups.
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Duarte-Carvajalino, J.M., Jahanshad, N., Lenglet, C., McMahon, K.L., de Zubicaray, G.I., Martin, N.G., Wright, M.J., Thompson, P.M., Sapiro, G.: Hierarchical topological network analysis of anatomical human brain connectivity and differences related to sex and kinship. Neuroimage 59, 3784–3804 (2012)
Rubinov, M., Sporns, O.: Complex network measures of brain connectivity: Uses and interpretations. Neuroimage 52, 1059–1069 (2010)
Zhu, D., Li, K., Guo, L., Jiang, X., Zhang, T., Zhang, D., Chen, H., Deng, F., Faraco, C., Jin, C., Wee, C.Y., Yuan, Y., Lv, P., Yin, Y., Hu, X., Duan, L., Han, J., Wang, L., Shen, D., Miller, L.S., Li, L., Liu, T.: DICCCOL: dense individualized and common connectivity-based cortical landmarks. Cereb Cortex 23, 786–800 (2013)
Lecoeur, J., Ingalhalikar, M., Verma, R.: Reproducibility of connectivity based parcellation: primary visual cortex. Proc. Int. Soc. Magn. Reson. Med. Sci. Meet. Exhib. Int. 2089 (2013)
Siless, V., Glaunès, J., Guevara, P., Mangin, J.-F., Poupon, C., Le Bihan, D., Thirion, B., Fillard, P.: Joint T1 and brain fiber log-demons registration using currents to model geometry. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds.) MICCAI 2012, Part II. LNCS, vol. 7511, pp. 57–65. Springer, Heidelberg (2012)
Petrović, A., Smith, S., Menke, R., Jenkinson, M.: Methods for Tractography-Driven Surface Registration of Brain Structures. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part I. LNCS, vol. 5761, pp. 705–712. Springer, Heidelberg (2009)
Gutman, B.A., Madsen, S.K., Toga, A.W., Thompson, P.M.: A Family of Fast Spherical Registration Algorithms for Cortical Shapes. Multimodal Brain Image Analysis (MBIA 2013) (2013)
Chung, M.K., Hartley, R., Dalton, K.M., Davidson, R.J.: Encoding Cortical Surface by Spherical Harmonics. Stat. Sinica 18, 1269–1291 (2008)
Rubenstein, J.L., Merzenich, M.M.: Model of autism: increased ratio of excitation/inhibition in key neural systems. Genes. Brain Behav. 2, 255–267 (2003)
Kreyszig, E.: Introductory functional analysis with applications. Krieger Pub. Co., Malabar (1989)
Aganj, I., Lenglet, C., Jahanshad, N., Yacoub, E., Harel, N., Thompson, P.M., Sapiro, G.: A Hough transform global probabilistic approach to multiple-subject diffusion MRI tractography. Medical Image Analysis 15, 414–425 (2011)
Beattie, C.: Galerkin Eigenvector Approximations. Math. Comput. 69, 1409–1434 (2000)
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Gutman, B. et al. (2014). Registering Cortical Surfaces Based on Whole-Brain Structural Connectivity and Continuous Connectivity Analysis. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2014. MICCAI 2014. Lecture Notes in Computer Science, vol 8675. Springer, Cham. https://doi.org/10.1007/978-3-319-10443-0_21
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DOI: https://doi.org/10.1007/978-3-319-10443-0_21
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