Larger is twistier: Spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism
Larger is twistier: Spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism
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DOI：
10.1016/j.neuroimage.2012.07.053
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发表时间：
2012-11-15
期刊：
影响因子：
5.7
通讯作者：
Mangin, Jean-Francois
中科院分区：
文献类型：
--
作者：
Germanaud, David;Lefevre, Julien;Mangin, Jean-Francois
皮质折叠模式（CFP）的描述是具有挑战性的，因为几何的复杂性和受试者之间的差异。在皮质表面网格上，曲率估计提供了CFP的良好标量代理。该函数的振荡可以使用类傅立叶分析来研究，以产生代表CFP的空间频率组成的功率谱。首先，我们介绍了一个原始的方法GYSTAY（Spangy），它执行的平均曲率的灰/白色界面网格的Laplace-Beltrami算子特征函数的基础上的谱分解的谱分析。Spangy产生了有序的7波段曲率功率谱（B 0-B6），并提供了一个解剖学相关的分割CFP的基础上，当地的频谱组成。空间频率与每个本征函数相关联，带宽设计假设连续谱带之间的频率加倍。接下来，我们观察到最后3个频谱带（84、5和6）占分析的频谱功率的93%，并且与曲率的折叠相关变化相关，而较低的频带与整体脑形状相关。CFP的光谱分段显示了与B4、B5和B6分别相关的一、二和三阶元素。这些元素可能与发育定义的初级，次级和三级褶皱有关。最后，我们使用异速生长的频带功率和分割的频谱组成的CFP和大脑的大小在一个大的成人数据集之间的关系进行了分析。总折叠力遵循正异速生长标度，其在条带之间不成比例地划分：84贡献是恒定的，85像总折叠力一样增加，86快得多。此外，随着图案尺寸的增加，图案新元素的出现只涉及3阶。因此，我们证明，大的大脑是twistier比较小的，因为增加了数量的高空间频率的褶皱，分支和扭结，以适应异速生长的皮质表面。(C)2012 Elsevier Inc. All rights reserved.
The description of cortical folding pattern (CFP) is challenging because of geometric complexity and inter-subject variability. On a cortical surface mesh, curvature estimation provides a good scalar proxy of CFP. The oscillations of this function can be studied using a Fourier-like analysis to produce a power spectrum representative of the spatial frequency composition of CFP. First, we introduce an original method for the SPectral ANalysis of GYrication (Spangy), which performs a spectral decomposition of the mean curvature of the grey/white interface mesh based on the Laplace-Beltrami operator eigenfunctions. Spangy produces an ordered 7 bands power spectrum of curvature (B0-B6) and provides an anatomically relevant segmentation of CFP based on local spectral composition. A spatial frequency being associated with each eigenfunction, the bandwidth design assumes frequency doubling between consecutive spectral bands. Next, we observed that the last 3 spectral bands (84,5 and 6) accounted for 93% of the analyzed spectral power and were associated with fold-related variations of curvature, whereas the lower frequency bands were related to global brain shape. The spectral segmentation of CFP revealed 1st, 2nd and 3rd order elements associated with B4, B5 and B6 respectively. These elements could be related to developmentally-defined primary, secondary and tertiary folds. Finally, we used allometric scaling of frequency bands power and segmentation to analyze the relationship between the spectral composition of CFP and brain size in a large adult dataset. Total folding power followed a positive allometric scaling which did not divide up proportionally between the bands: 84 contribution was constant, 85 increased like total folding power and 86 much faster. Besides, apparition of new elements of pattern with increasing size only concerned the 3rd order. Hence, we demonstrate that large brains are twistier than smaller ones because of an increased number of high spatial frequency folds, ramifications and kinks that accommodate the allometric increase of cortical surface. (C) 2012 Elsevier Inc. All rights reserved.