Abstract
A large body of evidence relates autism with abnormal structural and functional brain connectivity. Structural covariance MRI (scMRI) is a technique that maps brain regions with covarying gray matter density across subjects. It provides a way to probe the anatomical structures underlying intrinsic connectivity networks (ICNs) through the analysis of the gray matter signal covariance. In this paper, we apply topological data analysis in conjunction with scMRI to explore network-specific differences in the gray matter structure in subjects with autism versus age-, gender- and IQ-matched controls. Specifically, we investigate topological differences in gray matter structures captured by structural covariance networks (SCNs) derived from three ICNs strongly implicated in autism, namely, the salience network (SN), the default mode network (DMN) and the executive control network (ECN). By combining topological data analysis with statistical inference, our results provide evidence of statistically significant network-specific structural abnormalities in autism, from SCNs derived from SN and ECN. These differences in brain architecture are consistent with direct structural analysis using scMRI (Zielinski et al. 2012).
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References
Altaye, M., Holland, S.K., Wilke, M., Gaser, C.: Infant brain probability templates for MRI segmentation and normalization. NeuroImage 43(4), 721–730 (2008)
Böhm, W., Hornik, K.: A Kolmogorov-Smirnov test for r samples. Fundam. Inf. 117(1–4), 103–125 (2012)
Bullmore, E., Sporns, O.: Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10(3), 186–198 (2009)
Chung, M.K., Villalta-Gil, V., Lee, H., Rathouz, P.J., Lahey, B.B., Zald, D.H.: Exact topological inference for paired brain networks via persistent homology. bioRxiv:140533 (2017)
Courchesne, E., Pierce, K., Schumann, C.M., Redcay, E., Buckwalter, J.A., Kennedy, D.P., Morgan, J.: Mapping early brain development in autism. Neuron 56(2), 399–413 (2007)
Edelsbrunner, H., Letscher, D., Zomorodian, A.J.: Topological persistence and simplification. Discrete Comput. Geom. 28, 511–533 (2002)
Fair, D.A., Cohen, A.L., Dosenbach, N.U.F., Church, J.A., Miezin, F.M., Barch, D.M., Raichle, M.E., Petersen, S.E., Schlaggar, B.L.: The maturing architecture of the brain’s default network. Proc. Natl. Acad. Sci. 105(10), 4028–4032 (2008)
Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E.: The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U.S.A. 102(27), 9673–9678 (2005)
Minkova, L., Eickhoff, S.B., Abdulkadir, A., Kaller, C.P., Peter, J., Scheller, E., Lahr, J., Roos, R.A., Durr, A., Leavitt, B.R., Tabrizi, S.J., Klöppel, S., Investigators, T.-H.: Large-scale brain network abnormalities in huntington’s disease revealed by structural covariance. Hum. Brain Mapp. 37(1), 67–80 (2016)
Montembeault, M., Rouleau, I., Provost, J.-S., Brambati, S.M.: Altered gray matter structural covariance networks in early stages of Alzheimer’s disease. Cereb. Cortex 26(6), 2650 (2016)
Schumann, C.M., Bloss, C.S., Barnes, C.C., Wideman, G.M., Carper, R.A., Akshoomoff, N., Pierce, K., Hagler, D., Schork, N., Lord, C., Courchesne, E.: Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism. J. Neurosci. 30(12), 4419–4427 (2010)
Seeley, W.W., Crawford, R.K., Zhou, J., Miller, B.L., Greicius, M.D.: Neurodegenerative diseases target large-scale human brain networks. Neuron 62, 42–52 (2009)
Seeley, W.W., Menon, V., Schatzberg, A.F., Keller, J., Glover, G.H., Kenna, H., Reiss, A.L., Greicius, M.D.: Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 27(9), 2349–2356 (2007)
Stigler, K.A., McDonald, B.C., Anand, A., Saykin, A.J., McDougle, C.J.: Structural and functional magnetic resonance imaging of autism spectrum disorders. Brain Res. 1380, 146–161 (2011)
Wilke, M., Holland, S.K., Altaye, M., Gaser, C.: Template-O-Matic: a toolbox for creating customized pediatric templates. NeuroImage 41(3), 903–913 (2008)
Zielinski, B.A., Anderson, J.S., Froehlich, A.L., Prigge, M.B.D., Nielsen, J.A., Cooperrider, J.R., Cariello, A.N., Fletcher, P.T., Alexander, A.L., Lange, N., Bigler, E.D., Lainhart, J.E.: scMRI reveals large-scale brain network abnormalities in Autism. PLOS ONE 7(11), 1–14 (2012)
Zielinski, B.A., Gennatas, E.D., Zhou, J., Seeley, W.W.: Network-level structural covariance in the developing brain. Proc. Natl. Acad. Sci. 107(42), 18191–18196 (2010)
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This work was supported by NIH grant R01EB022876 and NSF grant IIS-1513616.
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Palande, S., Jose, V., Zielinski, B., Anderson, J., Fletcher, P.T., Wang, B. (2017). Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference. In: Wu, G., Laurienti, P., Bonilha, L., Munsell, B. (eds) Connectomics in NeuroImaging. CNI 2017. Lecture Notes in Computer Science(), vol 10511. Springer, Cham. https://doi.org/10.1007/978-3-319-67159-8_12
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