Abstract
The preservation of the spatial relationships among axonal pathways has long been studied and known to be critical for many functions of the brain. Being a fundamental property of the brain connections, there is an intuitive understanding of topographic regularity in neuroscience but yet to be systematically explored in connectome imaging research. In this work, we propose a general mathematical model for topographic regularity of fiber bundles that is consistent with its neuroanatomical understanding. Our model is based on a novel group spectral graph analysis (GSGA) framework motivated by spectral graph theory and tensor decomposition. GSGA provides a common set of eigenvectors for the graphs formed by topographic proximity measures whose preservation along individual tracts in return is modeled as topographic regularity. To demonstrate the application of this novel measure of topographic regularity, we apply it to filter fiber tracts from connectome imaging. Using large-scale data from the Human Connectome Project (HCP), we show that our novel algorithm can achieve better performance than existing methods on the filtering of both individual bundles and whole brain tractograms.
Y. Shi—This work was in part supported by NIH grants R01EB022744, U01EY025864, K01EB013633, P41EB015922, U54EB020406, R01MH094343, and Research to Prevent Blindness.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bullmore, E.T., Bassett, D.S.: Brain graphs: graphical models of the human brain connectome. Annu. Rev. Clin. Psychol. 7(1), 113–140 (2011)
Thomas, C., Ye, F.Q., Irfanoglu, M.O., Modi, P., Saleem, K.S., Leopold, D.A., Pierpaoli, C.: Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited. Proc. Nat. Acad. Sci. 111(46), 16574–16579 (2014)
O’Donnell, L.J., Westin, C.F.: Automatic tractography segmentation using a high-dimensional white matter atlas. IEEE Trans. Med. Imaging 26(11), 1562–1575 (2007)
Aydogan, D.B., Shi, Y.: Track filtering via iterative correction of TDI topology. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9349, pp. 20–27. Springer, Cham (2015). doi:10.1007/978-3-319-24553-9_3
Patel, G.H., Kaplan, D.M., Snyder, L.H.: Topographic organization in the brain: searching for general principles. Trends Cogn. Sci. 18(7), 351–363 (2014)
Engel, S.A., Glover, G.H., Wandell, B.A.: Retinotopic organization in human visual cortex and the spatial precision of functional MRI. Cereb. Cortex 7(2), 181–192 (1997)
Ebeling, U., Reulen, H.J.: Neurosurgical topography of the optic radiation in the temporal lobe. Acta Neurochir. 92(1), 29–36 (1988)
Ruben, J., Schwiemann, J., Deuchert, M., Meyer, R., Krause, T., Curio, G., Villringer, K., Kurth, R., Villringer, A.: Somatotopic organization of human secondary somatosensory cortex. Cereb. Cortex 11(5), 463–473 (2001)
Morosan, P., Rademacher, J., Schleicher, A., Amunts, K., Schormann, T., Zilles, K.: Human primary auditory cortex: cytoarchitectonic subdivisions and mapping into a spatial reference system. NeuroImage 13(4), 684–701 (2001)
Lehman, J.F., Greenberg, B.D., McIntyre, C.C., Rasmussen, S.A., Haber, S.N.: Rules ventral prefrontal cortical axons use to reach their targets: implications for diffusion tensor imaging tractography and deep brain stimulation for psychiatric illness. J. Neurosci. 31(28), 10392–10402 (2011)
Wedeen, V.J., Rosene, D.L., Wang, R., Dai, G., Mortazavi, F., Hagmann, P., Kaas, J.H., Tseng, W.Y.I.: The geometric structure of the brain fiber pathways. Science 335(6076), 1628–1634 (2012)
Aydogan, D.B., Shi, Y.: Probabilistic tractography for topographically organized connectomes. In: Ourselin, S., Joskowicz, L., Sabuncu, M.R., Unal, G., Wells, W. (eds.) MICCAI 2016. LNCS, vol. 9900, pp. 201–209. Springer, Cham (2016). doi:10.1007/978-3-319-46720-7_24
Thivierge, J.P., Marcus, G.F.: The topographic brain: from neural connectivity to cognition. Trends Neurosci. 30(6), 251–259 (2007)
Umeyama, S.: An eigendecomposition approach to weighted graph matching problems. IEEE Trans. Pattern Anal. Mach. Intell. 10(5), 695–703 (1988)
Brouwer, A.E., Haemers, W.H.: Spectra of Graphs. Springer Science & Business Media, Heidelberg (2011)
Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to a nonmetric hypothesis. Psychometrika 29(1), 1–27 (1964)
Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888–905 (2000)
Bunse-Gerstner, A., Byers, R., Mehrmann, V.: Numerical methods for simultaneous diagonalization. SIAM J. Matrix Anal. Appl. 14(4), 927–949 (1993)
Tucker, L.R.: Some mathematical notes on three-mode factor analysis. Psychometrika 31(3), 279–311 (1966)
Essen, D.V., Ugurbil, K., et al.: The Human Connectome Project: a data acquisition perspective. NeuroImage 62(4), 2222–2231 (2012)
Tran, G., Shi, Y.: Fiber orientation and compartment parameter estimation from multi-shell diffusion imaging. IEEE Trans. Med. Imaging 34(11), 2320–2332 (2015)
Tournier, J.D., Calamante, F., Connelly, A.: MRtrix: diffusion tractography in crossing fiber regions. Int. J. Imaging Syst. Technol. 22(1), 53–66 (2012)
Kammen, A., Law, M., Tjan, B.S., Toga, A.W., Shi, Y.: Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis. NeuroImage 125, 767–779 (2016)
Smith, R.E., Tournier, J.D., Calamante, F., Connelly, A.: SIFT: spherical-deconvolution informed filtering of tractograms. NeuroImage 67, 298–312 (2013)
Benson, N.C., Butt, O.H., Datta, R., Radoeva, P.D., Brainard, D.H., Aguirre, G.K.: The retinotopic organization of striate cortex is well predicted by surface topology. Curr. Biol.: CB 22(21), 2081–2085 (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Wang, J., Aydogan, D.B., Varma, R., Toga, A.W., Shi, Y. (2017). Topographic Regularity for Tract Filtering in Brain Connectivity. In: Niethammer, M., et al. Information Processing in Medical Imaging. IPMI 2017. Lecture Notes in Computer Science(), vol 10265. Springer, Cham. https://doi.org/10.1007/978-3-319-59050-9_21
Download citation
DOI: https://doi.org/10.1007/978-3-319-59050-9_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-59049-3
Online ISBN: 978-3-319-59050-9
eBook Packages: Computer ScienceComputer Science (R0)