Elsevier

NeuroImage

Volume 29, Issue 4, 15 February 2006, Pages 1224-1230
NeuroImage

A curvature-based approach to estimate local gyrification on the cortical surface

https://doi.org/10.1016/j.neuroimage.2005.08.049Get rights and content

Abstract

Using magnetic resonance imaging and a new method to analyze local surface shape, we examined the effects of gender on gyrification in a large and well-matched sample of healthy subjects. Unlike traditional 2D methods that produce whole-brain measurements of cortical complexity or more sophisticated 3D parametric mesh-based techniques that allow only different sections (lobes) of the cortex to be investigated, we employed a novel approach with increased spatial resolution. Although our method is sensitive to similar cortical features like the classic whole-brain gyrification index (depths of sulci and heights of gyri), we are now able to provide detailed and regionally specific estimates of cortical convolution at thousands of points across the cortical surface without introducing any bias through the rater or the selected orientation of the slices. We revealed pronounced gender differences, showing increased gyrification in frontal and parietal regions in females compared to males that agree with recent regions-of-interest findings. In addition, we detected higher female gyrification in temporal and occipital cortices that was not previously identified in studies using more global measures. No cortical area was significantly more convoluted in males compared to females. Our results demonstrate the sensitivity of this automated approach for identifying very local changes in gyrification. This technique may serve to isolate regionally specific changes in fissuration/gyrification in neurodevelopmental or neuropsychiatric disorders.

Introduction

Brain expansion is partly constrained by the size of the intracranial cavity during neurodevelopment (Hofman, 1989, Van Essen, 1997, Courchesne et al., 2000), so gender-specific patterns of cortical folding are likely influenced by smaller female skull sizes. Traditional postmortem and in vivo morphometric studies have used several unique approaches to examine cortical complexity and to establish the presence and direction of gender differences in sulcal/gyral convolutions. Measuring cortical folding in postmortem data with a 2D gyrification index (i.e. the ratio between deep and superficial cortex in coronal sections) revealed no differences between men and women (Zilles et al., 1988). Similarly, no gender differences were identified in an in vivo study defining whole-brain surface complexity as the ratio of total cortical surface area to overall brain volume, raised to the 2/3 power (Nopoulos et al., 2000). However, another MRI investigation used surface-to-volume ratios to calculate a fissurization index for the hemispheres and cingulate cortices. This study detected a hemisphere by gender interaction, reflecting increased asymmetries of fissurization in male brains (Yucel et al., 2001). Moreover, using a sophisticated 3D parametric mesh-based approach (Thompson et al., 1996a, Thompson et al., 1996b) applied to five functionally relevant cortical regions, our group demonstrated that females exhibit greater cortical complexity than males in frontal and parietal regions (Luders et al., 2004).

Overall, empirical data concerning sex-related differences in cortical complexity or gyrification are sparse, and findings lack consistency, where discrepancies may stem from differences in measurement methods (e.g. postmortem vs. in vivo, 2D vs. 3D). Available data, however, suggest that the ability to detect gender-specific differences in gyrification increases by shifting focus from global (e.g. whole brain) to more regional examinations (e.g. frontal lobe). Region-of-interest (ROI) analysis appears to be the most spatially detailed method used to date. However, using ROIs defined a priori limits the identification of changes elsewhere in the cortex, may introduce user bias and makes it impractical to study large populations given that manual delineations are labor-intensive.

In order to circumvent these potential limitations, we applied a refined and automated whole-brain approach for estimating regional differences in cortical surface convolution. Specifically, we computed the degree of convolution across the entire cortex at thousands of surface points in order to provide color-coded maps indexing the local gyrification. We hypothesized that gender-specific differences in gyrification would exist in numerous cortical regions that would complement and extend existing knowledge from studies using less spatially detailed methods. In order to confirm correspondences with results achieved through a lower resolution parametric mesh-based approach (Thompson et al., 1996a, Thompson et al., 1996b), we examined local gyrification in the same sample as analyzed in a previously published study (Luders et al., 2004).

Section snippets

Subjects

We analyzed the brain scans of 60 young and right-handed subjects that were selected from a database of high-resolution anatomical MR images acquired at the Center for Neuroscientific Innovation and Technology (ZENIT), Magdeburg. Subjects were matched for biological sex (30 women, 30 men) and age (women: 24.32 ± 4.35 years; men: 25.45 ± 4.72 years). Handedness was determined by referring to self-reports of hand preference. Subjects were healthy volunteers and included university students from

Results

Fig. 2 shows the average distributions of local gyrification in ICBM-305 stereotaxic space for females (first row) and males (second row). The highest local gyrification in both men and women appears to be located in the left and right parietal lobes between midline and intraparietal sulcus, as well as in the left superior frontal cortex and bilaterally along the precentral sulcus in women, and to a lesser degree also in men. Another small region exhibiting extremely high gyrification was

Discussion

In this study, we present a new method for estimating a local gyrification index. Our approach is related to formerly described calculations of curvature indices (CI) (Magnotta et al., 1999, Nopoulos et al., 2000). However, in contrast to measuring whole-brain sulcal and gyral CIs as implemented previously, we computed the degree of convolution across the entire cortex at thousands of surface points. Our approach further complements traditional methods that produce global measures of

Acknowledgments

This work was supported by research grants R01 LM005639 (funded by the NLM and NIA) and P01 EB001955 (funded by the NIBIB, NINDS, and NIMG), an NIMH NRSA Training Grant (MH14584) and a Daniel X. Freedman NARSAD Young Investigator Award (to KLN) and R21 grants RR19771 and EB01561 (to PMT). Additional support was provided by U54 RR021813 (funded by the NCRR, NCBC and NIGMS), P41 RR013642 and M01 RR000865 (funded by the NCRR). We thank Karen Schrock for proof reading the manuscript.

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