Kim Sun Hyung, Lyu Ilwoo, Fonov Vladimir S, Vachet Clement, Hazlett Heather C, Smith Rachel G, Piven Joseph, Dager Stephen R, Mckinstry Robert C, Pruett John R, Evans Alan C, Collins D Louis, Botteron Kelly N, Schultz Robert T, Gerig Guido, Styner Martin A
Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, NC, USA.
Department of Computer Science, University of North Carolina at Chapel Hill, NC, USA.
Neuroimage. 2016 Jul 15;135:163-76. doi: 10.1016/j.neuroimage.2016.04.053. Epub 2016 May 3.
The quantification of local surface morphology in the human cortex is important for examining population differences as well as developmental changes in neurodegenerative or neurodevelopmental disorders. We propose a novel cortical shape measure, referred to as the 'shape complexity index' (SCI), that represents localized shape complexity as the difference between the observed distributions of local surface topology, as quantified by the shape index (SI) measure, to its best fitting simple topological model within a given neighborhood. We apply a relatively small, adaptive geodesic kernel to calculate the SCI. Due to the small size of the kernel, the proposed SCI measure captures fine differences of cortical shape. With this novel cortical feature, we aim to capture comparatively small local surface changes that capture a) the widening versus deepening of sulcal and gyral regions, as well as b) the emergence and development of secondary and tertiary sulci. Current cortical shape measures, such as the gyrification index (GI) or intrinsic curvature measures, investigate the cortical surface at a different scale and are less well suited to capture these particular cortical surface changes. In our experiments, the proposed SCI demonstrates higher complexity in the gyral/sulcal wall regions, lower complexity in wider gyral ridges and lowest complexity in wider sulcal fundus regions. In early postnatal brain development, our experiments show that SCI reveals a pattern of increased cortical shape complexity with age, as well as sexual dimorphisms in the insula, middle cingulate, parieto-occipital sulcal and Broca's regions. Overall, sex differences were greatest at 6months of age and were reduced at 24months, with the difference pattern switching from higher complexity in males at 6months to higher complexity in females at 24months. This is the first study of longitudinal, cortical complexity maturation and sex differences, in the early postnatal period from 6 to 24months of age with fine scale, cortical shape measures. These results provide information that complement previous studies of gyrification index in early brain development.
量化人类皮质的局部表面形态对于研究群体差异以及神经退行性疾病或神经发育障碍中的发育变化非常重要。我们提出了一种新的皮质形状测量方法，称为“形状复杂性指数”（SCI），它将局部形状复杂性表示为通过形状指数（SI）测量量化的局部表面拓扑结构的观察分布与其在给定邻域内最佳拟合的简单拓扑模型之间的差异。我们应用一个相对较小的自适应测地线内核来计算SCI。由于内核尺寸较小，所提出的SCI测量方法能够捕捉皮质形状的细微差异。借助这一新的皮质特征，我们旨在捕捉相对较小的局部表面变化，这些变化包括：a）脑沟和脑回区域的变宽与加深，以及b）二级和三级脑沟的出现和发育。当前的皮质形状测量方法，如脑回化指数（GI）或固有曲率测量方法，在不同尺度上研究皮质表面，不太适合捕捉这些特定的皮质表面变化。在我们的实验中，所提出的SCI在脑回/脑沟壁区域显示出更高的复杂性，在较宽的脑回脊中复杂性较低，在较宽的脑沟底部区域复杂性最低。在出生后早期的大脑发育中，我们的实验表明，SCI揭示了随着年龄增长皮质形状复杂性增加的模式，以及在脑岛、中央扣带回、顶枕沟和布洛卡区的性别二态性。总体而言，性别差异在6个月大时最大，在24个月时减小，差异模式从6个月时男性的较高复杂性转变为24个月时女性的较高复杂性。这是第一项使用精细尺度的皮质形状测量方法，对出生后6至24个月早期进行纵向皮质复杂性成熟和性别差异研究。这些结果提供了补充先前早期大脑发育中脑回化指数研究的信息。
