Mazziotta J, Toga A, Evans A, Fox P, Lancaster J, Zilles K, Woods R, Paus T, Simpson G, Pike B, Holmes C, Collins L, Thompson P, MacDonald D, Iacoboni M, Schormann T, Amunts K, Palomero-Gallagher N, Geyer S, Parsons L, Narr K, Kabani N, Le Goualher G, Boomsma D, Cannon T, Kawashima R, Mazoyer B
Ahmanson-Lovelace Brain Mapping Center, UCLA School of Medicine, 660 Charles E. Young Drive, South Los Angeles, CA 90095, USA.
Philos Trans R Soc Lond B Biol Sci. 2001 Aug 29;356(1412):1293-322. doi: 10.1098/rstb.2001.0915.
Motivated by the vast amount of information that is rapidly accumulating about the human brain in digital form, we embarked upon a program in 1992 to develop a four-dimensional probabilistic atlas and reference system for the human brain. Through an International Consortium for Brain Mapping (ICBM) a dataset is being collected that includes 7000 subjects between the ages of eighteen and ninety years and including 342 mono- and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioural and imaging information. DNA has been collected for genotyping from 5800 subjects. A component of the programme uses post-mortem tissue to determine the probabilistic distribution of microscopic cyto- and chemoarchitectural regions in the human brain. This, combined with macroscopic information about structure and function derived from subjects in vivo, provides the first large scale opportunity to gain meaningful insights into the concordance or discordance in micro- and macroscopic structure and function. The philosophy, strategy, algorithm development, data acquisition techniques and validation methods are described in this report along with database structures. Examples of results are described for the normal adult human brain as well as examples in patients with Alzheimer's disease and multiple sclerosis. The ability to quantify the variance of the human brain as a function of age in a large population of subjects for whom data is also available about their genetic composition and behaviour will allow for the first assessment of cerebral genotype-phenotype-behavioural correlations in humans to take place in a population this large. This approach and its application should provide new insights and opportunities for investigators interested in basic neuroscience, clinical diagnostics and the evaluation of neuropsychiatric disorders in patients.
鉴于以数字形式迅速积累的关于人类大脑的海量信息,我们于1992年启动了一个项目,旨在开发一个人类大脑的四维概率图谱和参考系统。通过国际脑图谱联盟(ICBM),正在收集一个数据集,其中包括7000名年龄在18岁至90岁之间的受试者,包括342对单卵和双卵双胞胎。每个受试者的数据包括详细的人口统计学、临床、行为和成像信息。已从5800名受试者中收集了用于基因分型的DNA。该项目的一个组成部分利用死后组织来确定人类大脑微观细胞和化学结构区域的概率分布。这与从活体受试者获得的关于结构和功能的宏观信息相结合,提供了第一个大规模的机会,以深入了解微观和宏观结构与功能的一致性或不一致性。本报告介绍了该项目的理念、策略、算法开发、数据采集技术和验证方法以及数据库结构。报告还描述了正常成人大脑的结果示例以及阿尔茨海默病和多发性硬化症患者的示例。能够在大量受试者中量化人类大脑随年龄变化的方差,且这些受试者同时还拥有关于其基因组成和行为的数据,这将首次使得在如此大规模的人群中对人类大脑基因型-表型-行为相关性进行评估成为可能。这种方法及其应用应该为对基础神经科学、临床诊断以及患者神经精神疾病评估感兴趣的研究人员提供新的见解和机会。