Toga A W, Thompson P M
Division of Brain Mapping, UCLA School of Medicine, Los Angeles, CA, USA.
Anat Rec. 2001 Apr;265(2):37-53. doi: 10.1002/ar.1057.
We review recent developments in brain mapping and computational anatomy that have greatly expanded our ability to analyze brain structure and function. The enormous diversity of brain maps and imaging methods has spurred the development of population-based digital brain atlases. These atlases store information on how the brain varies across age and gender, across time, in health and disease, and in large human populations. We describe how brain atlases, and the computational tools that align new datasets with them, facilitate comparison of brain data across experiments, laboratories, and from different imaging devices. The major methods are presented for the construction of probabilistic atlases, which store information on anatomic and functional variability in a population. Algorithms are reviewed that create composite brain maps and atlases based on multiple subjects. We show that group patterns of cortical organization, asymmetry, and disease-specific trends can be resolved that may not be apparent in individual brain maps. Finally, we describe the creation of four-dimensional (4D) maps that store information on the dynamics of brain change in development and disease. Digital atlases that correlate these maps show considerable promise in identifying general patterns of structural and functional variation in human populations, and how these features depend on demographic, genetic, cognitive, and clinical parameters.
我们回顾了脑图谱和计算解剖学的最新进展,这些进展极大地扩展了我们分析脑结构和功能的能力。脑图谱和成像方法的巨大多样性推动了基于人群的数字脑图谱集的发展。这些图谱集存储了关于大脑如何随年龄、性别、时间、健康与疾病状态以及在大量人群中的变化情况的信息。我们描述了脑图谱集以及将新数据集与其对齐的计算工具如何促进跨实验、跨实验室以及来自不同成像设备的脑数据的比较。介绍了构建概率图谱集的主要方法,概率图谱集存储了人群中解剖学和功能变异性的信息。回顾了基于多个受试者创建复合脑图谱和图谱集的算法。我们表明,皮质组织、不对称性和疾病特异性趋势的群体模式是可以分辨出来的,而这些模式在个体脑图谱中可能并不明显。最后,我们描述了四维(4D)图谱的创建,这些图谱存储了发育和疾病过程中脑变化动态的信息。关联这些图谱的数字图谱集在识别人类群体中结构和功能变异的一般模式以及这些特征如何依赖于人口统计学、遗传学、认知和临床参数方面显示出了巨大的前景。