Abstract
Cortical folding patterns are believed to be good predictors of brain cytoarchitecture and function. For instance, neuroscientists frequently apply their domain knowledge to identify brain Regions of Interests (ROIs) based on cortical folding patterns. However, quantitative mapping of cortical folding pattern and brain function has not been established yet in the literature. This paper presents our initial effort in quantification of the regularity and variability of cortical folding pattern features for working memory ROIs identified by taskbased fMRI, which is widely accepted as a standard approach to localize functionally-specialized brain regions. Specifically, we used a set of shape attributes for each ROI base on multiple resolution decomposition of cortical surfaces, and described the meso-scale folding pattern via a polynomial-based approach. We also applied brain atlas label distribution as a global-scale description of ROI folding pattern. Our studies suggest that there is deep-rooted regularity of cortical folding patterns for certain working memory ROIs across subjects, and folding pattern attributes could be useful for the characterization, recognition and prediction of ROIs, if extracted and applied in a proper way.
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Van Essen, D.C.: A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature 385(6614), 313–318 (1997)
Sporns, O., Chialvo, D.R., Kaiser, M., Hilgetag, C.C.: Organization, development and function of complex brain networks. Trends Cogn. Sci. 8(9), 418–425 (2004)
Passingham, R.E., Stephan, K.E., Kötter, R.: The anatomical basis of functional localization in the cortex. Nat Rev. Neurosci. 3(8), 606–616 (2002)
Zhang, T., Guo, L., Li, G., Nie, J., Liu, T.: Parametric representation of cortical surface folding based on polynomials. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009. LNCS, vol. 5762, pp. 184–191. Springer, Heidelberg (2009)
Zilles, K., Armstrong, E., Schleicher, A., Kretschmann, H.J.: The human pattern of gyrification in the cerebral cortex. Anat. Embryol (Berl.) 179, 173–179 (1988)
Yu, P., Yeo, B.T., Grant, P.E., Fischl, B., Golland, P.: Cortical Folding Development Study based on Over-Complete Spherical Wavelets. In: IEEE Workshop on MMBIA, pp. 1–8 (2007)
Yeo, B.T., Yu, P., Grant, P.E., Fischl, B., Golland, P.: Shape analysis with overcomplete spherical wavelets. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 468–476. Springer, Heidelberg (2008)
Besl, P.J., Jain, R.C.: Segmentation Through Variable-Order Surface Fitting. IEEE Transactions on Pattern Analysis and Machine Intelligence 10, 167–192 (1988)
Li, K., Guo, L., Li, G., Nie, J., Faraco, C., Cui, G., Zhao, Q., Miller, L.S., Liu, T.: Gyral folding pattern analysis via surface profiling. NeuroImage 52(4), 1202–1214 (2010)
Liu, T., Li, H., Wong, K., Tarokh, A., Guo, L., Wong, S.T.: Brain tissue segmentation based on DTI data. NeuroImage 38, 114–123 (2007)
Chang, C.-C., Lin, C.-J.: LIBSVM: a library for support vector machines. Software (2001), http://www.csie.ntu.edu.tw/cjlin/libsvm
Shen, D., Davatzikos, C.: HAMMER: hierarchical attribute matching mechanism for elastic registration. IEEE Trans. Med. Imaging 21(11), 1421–1439 (2002)
FMRIB Software Library, http://www.fmrib.ox.ac.uk/fsl/index.html
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Chen, H., Zhang, T., Li, K., Hu, X., Guo, L., Liu, T. (2011). Assessing Regularity and Variability of Cortical Folding Patterns of Working Memory ROIs. In: Fichtinger, G., Martel, A., Peters, T. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2011. MICCAI 2011. Lecture Notes in Computer Science, vol 6892. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23629-7_39
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DOI: https://doi.org/10.1007/978-3-642-23629-7_39
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