Gender consistency and difference in healthy adults revealed by cortical thickness

doi:10.1016/j.neuroimage.2010.05.020

NeuroImage

Volume 53, Issue 2, 1 November 2010, Pages 373-382

https://doi.org/10.1016/j.neuroimage.2010.05.020 Get rights and content

Abstract

Many previous studies have shown that there exists the gender effect on the structural and functional organization in the human brain. Although the reported functional differences are generally consistent, the structural differences are controversial among the various studies. In this study, we particularly focused on the gender-related effect in the gray matter (GM). We performed a structural magnetic resonance imaging (MRI) study in 184 healthy adults (90 males and 94 females) with ages ranging from 18 to 70 years. Cortical thickness was measured using an automated surface-based method. Based on this surface morphological feature of GM, we first compared their regional differences between males and females. We then constructed the morphometry-based anatomical networks derived from cortical thickness measurement, while the anatomical connection between two cortical areas depended upon the statistical dependence of their cortical thickness across subjects. Subsequently, we applied graph theoretical approaches to investigate the properties of the resultant anatomical networks. The results showed that the significant gender-related differences of cortical thickness appeared extensively in the frontal, parietal and occipital lobes. And there were also some between-group differences in the interregional correlation. Additional graph theoretical analysis on the morphological networks revealed both networks exhibited the small-world efficiency and their patterns of topological vulnerability had no statistical differences. The findings on the large sample may provide the evidences to study the gender consistency and difference in the human brain structures.

Introduction

With the postmortem and neuroimaging techniques, a number of evidences have demonstrated that there exist structural and functional differences in the human brain between men and women (DeLacoste-Utamsing and Holloway, 1982, Leonard et al., 2008, Shaywitz et al., 1995). For instance, many studies have founded the functional dimorphisms in language (Shaywitz et al., 1995), emotion (Hofer et al., 2006), memory (Speck et al., 2000), object naming (Garn et al., 2009). There are also evidences for the gender-related structural differences in brain volume, brain tissue composition (Nopoulos et al., 2000, Sullivan et al., 2004) and the cortical morphometry (Good et al., 2001, Im et al., 2006, Luders et al., 2004, Raz et al., 2004).

Especially for gray matter (GM), the gender differences in regional distribution were investigated by using the traditional region of interest (ROI)-based method (Nopoulos et al., 2000, Raz et al., 2004) and the voxel-based morphometry method (Ashburner and Friston, 2000, Good et al., 2001). The results revealed that the gender effect provided a significant contribution to their variations. For example, males had larger volumes in lateral prefrontal cortex, orbito-frontal cortex, anterior cingulated gyrus and so on, even after the body size was statistically controlled (Raz et al., 2004). Advances in image processing allowed us to characterize the structural differences on the cortical surface. Investigators examined the cortical complexity, which reflects the frequency of sulcal and gyral convolutions in the defined regions, and found greater gyrification in females than males in the frontal and parietal regions (Luders et al., 2004). Cortical thickness, which is another important morphological property of the cerebral cortex, has also been investigated in the studies of gender-related structural differences (Im et al., 2006, Luders et al., 2006, Sowell et al., 2007). In these reports, females were observed to have a thicker cortex than males mostly in some regions in the frontal and parietal lobes.

Most of the aforementioned studies employed the univariate approach to detect the gender-related structural differences in global or regional levels. However, they may miss the important information of supra-regional structural correlations. Mechelli et al. investigated the relationships of the GM densities from 12 ROIs in 172 healthy individuals, and the positive associations were detected between the symmetrical interhemispheric regions (Mechelli et al., 2005). Another study used a multivariate approach to identify covariance patterns of GM and white matter (WM) tissue density to distinguish the older from the younger adults, and examined whether the pattern expression was related to the age-related cognitive performance (Brickman et al., 2007). Several recent studies suggested that there were interregional statistical associations in GM volume (Bassett et al., 2008) and cortical thickness (Lerch et al., 2006, Worsley et al., 2005). Based on these studies, investigators established the morphological networks in human brains and applied the graph theoretical analysis to explore the organizational patterns of cortical network (He et al., 2007). These studies provided some important connectivity characteristics in the normal subjects (He et al., 2007), schizophrenia (Bassett et al., 2008) and Alzheimer's disease (He et al., 2008). Graph theoretical approaches provided a more quantitative analysis to the complex networks, and have been widely applied to investigate the brain structural and functional networks recently (for reviews, see Bullmore and Sporns, 2009). To the best of our knowledge, so far no study has been reported on whether the structural correlations based on cortical thickness were affected by the gender.

The motivation of this paper is to investigate the gender effect not only on the regional structures but also on the cortical anatomical connections based on the MRI-derived cortical thickness in healthy adults. To address these issues, first, the cortical thickness values were examined to determine whether regional structural differences existed between males and females. Second, the cortical anatomical networks were statistically inferred by correlating the mean thickness values between any two different cortical areas across the subjects. Finally, the properties of the morphometry-based anatomical network between the two groups were characterized and compared using the graph theoretical approaches.

Section snippets

Subjects

In this study, 184 right-handed normal subjects (90 males, 94 females) were recruited at TongRen Hospital (Beijing, China), with males' ages ranging from 18 to 67 years (mean: 38.43 ± 12.57 years) and females' ages ranging from 18 to 70 years (mean: 44.51 ± 11.20 years). Subjects with a history of brain injury or conditions incompatible with an MRI scan were excluded. This study was approved by the local ethics committee of TongRen Hospital, Capital Medical University. And the written informed consent

Vertex-wise cortical thickness analysis

The distribution of average cortical thickness was shown on Fig.1. And the calculated t values were shown on the average cortical surface model of the whole sample (Fig. 2A). The maps were thresholded with the corrected T value (t > 2.28, and t < −2.28) using the FDR procedure at the specific p < 0.05 (Fig. 2B). In Fig. 2, we can observe the significant differences in cortical thickness between males and females. The most significant cortical thickening in females appeared extensively in the frontal,

Discussion

The cerebral cortex is organized with two general principles, namely functional segregation and functional integration (Sporns et al., 2004, Zeki and Shipp, 1988). The variations in the anatomy may correspond to the function segregation (Zeki and Shipp, 1988), while the coordinated variations can provide in part the underlying structural basis for the function integration. In the present study, we used an automated surface-based method to measure the cortical thickness and demonstrated the

Acknowledgments

We are grateful to Professor Alan C. Evans and Dr. Claude Lepage for providing the CIVET software. And we would also like to thank Dr. Yong He for his insightful suggestions, and Dr. Hai Jiang and Wenjing Li for English language and editing assistance. This study was supported by the Natural Science Foundation of China, Grant Nos. 30670530, 60875079, the National High-Tech Research and Development Plan of China (863), Grant No. 2007AA01Z327, 2006AA02Z391, and the New Star Plan of Science and

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¹: Bin Lv and Jing Li contributed equally to this work.

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