Gender Differences in Cerebral Cortical Folding: Multivariate Complexity-Shape Analysis with Insights into Handling Brain-Volume Differences

This paper presents a study of gender differences in adult human cerebral cortical folding patterns. The study employs a new multivariate statistical descriptor for analyzing folding patterns in a region of interest (ROI) and a rigorous nonparametric permutation-based scheme for hypothesis testing. Unlike typical ROI-based methods that summarize folding complexity or shape by single/few numbers, the proposed descriptor systematically constructs a unified description of complexity and shape in a high-dimensional space (thousands of numbers/dimensions). Furthermore, this paper presents new mathematical insights into the relationship of intra-cranial volume (ICV) with cortical complexity and shows that conventional complexity descriptors implicitly handle ICV differences in different ways, thereby lending different meanings to "complexity". This paper describes two systematic methods for handling ICV changes in folding studies using the proposed descriptor. The clinical study in this paper exploits these theoretical insights to demonstrate that (i) the answer to which gender has higher/lower "complexity" depends on how a folding measure handles ICV differences and (ii) cortical folds in males and females differ significantly in shape as well.

[1]  D. V. Essen,et al.  Surface-Based and Probabilistic Atlases of Primate Cerebral Cortex , 2007, Neuron.

[2]  William M. Wells,et al.  Medical Image Computing and Computer-Assisted Intervention — MICCAI’98 , 1998, Lecture Notes in Computer Science.

[3]  Suyash P. Awate,et al.  Multivariate High-Dimensional Cortical Folding Analysis, Combining Complexity and Shape, in Neonates with Congenital Heart Disease , 2009, IPMI.

[4]  T. Paus,et al.  Brain size and folding of the human cerebral cortex. , 2008, Cerebral cortex.

[5]  R. Woods,et al.  Sex differences in cortical thickness mapped in 176 healthy individuals between 7 and 87 years of age. , 2007, Cerebral cortex.

[6]  Alan C. Evans,et al.  Brain size and cortical structure in the adult human brain. , 2008, Cerebral cortex.

[7]  A. Schleicher,et al.  The human pattern of gyrification in the cerebral cortex , 2004, Anatomy and Embryology.

[8]  N. Makris,et al.  A methodology for analyzing curvature in the developing brain from preterm to adult , 2008, Int. J. Imaging Syst. Technol..

[9]  D. V. van Essen,et al.  Structural and Functional Analyses of Human Cerebral Cortex Using a Surface-Based Atlas , 1997, The Journal of Neuroscience.

[10]  Eileen Luders,et al.  Gender differences in cortical complexity , 2004, Nature Neuroscience.

[11]  Andrea J. van Doorn,et al.  Surface shape and curvature scales , 1992, Image Vis. Comput..

[12]  D. V. van Essen,et al.  Cortical Folding Abnormalities in Autism Revealed by Surface-Based Morphometry , 2007, The Journal of Neuroscience.

[13]  Zudi Lu,et al.  Spatial kernel regression estimation: weak consistency. , 2004 .

[14]  S. Geman,et al.  Consistent Cross-Validated Density Estimation , 1983 .

[15]  David J. Hawkes,et al.  Measures of folding applied to the development of the human fetal brain , 2002, IEEE Transactions on Medical Imaging.

[16]  Robert T. Schultz,et al.  3D Cerebral Cortical Morphometry in Autism: Increased Folding in Children and Adolescents in Frontal, Parietal, and Temporal Lobes , 2008, MICCAI.

[17]  Guido Gerig,et al.  Effects of Healthy Aging Measured By Intracranial Compartment Volumes Using a Designed MR Brain Database , 2005, MICCAI.

[18]  Thomas E. Nichols,et al.  Nonparametric permutation tests for functional neuroimaging: A primer with examples , 2002, Human brain mapping.

[19]  Yuan Qi,et al.  Cortical Surface Shape Analysis Based on Spherical Wavelets , 2007, IEEE Transactions on Medical Imaging.

[20]  E. Duchesnay,et al.  A framework to study the cortical folding patterns , 2004, NeuroImage.

[21]  Suyash P. Awate,et al.  Adaptive Markov modeling for mutual-information-based, unsupervised MRI brain-tissue classification , 2006, Medical Image Anal..