Jiang Tianzi, Zhou Yuan
LIAMA Center for Computational Medicine, National Laboratory of Pattern Recognition, Institute of Automation, The Chinese Academy of Sciences, Beijing, China.
Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China.
Shanghai Arch Psychiatry. 2012 Feb;24(1):3-10. doi: 10.3969/j.issn.1002-0829.2012.01.001.
Impaired cognitive function, along with positive and negative symptoms, is a core clinical feature of schizophrenia. Earlier studies suggest that impaired cognitive functioning should be assessed from the perspective of brain networks. The recently developed brainnetome approach to evaluating brain networks-an approach that was initially developed by Chinese scientists-provides a new methodology for studying this issue. In this paper we first introduce the concept of brainnetome. We then review recent progress in developing a brainnetome of impaired cognitive function in people with schizophrenia. The models of the relevant brain networks considered were created using data obtained from functional and anatomical brain imaging technologies at different levels of analysis: networks centered on regions of interest, networks related to specific cognitive functions, whole brain networks, and the attributes of brain networks. Finally, we discuss the current challenges and potential new directions for research about brainnetome.
认知功能受损与阳性和阴性症状一样,是精神分裂症的核心临床特征。早期研究表明,应从脑网络的角度评估认知功能受损情况。最近由中国科学家最初开发的用于评估脑网络的脑网络组学方法,为研究这一问题提供了一种新的方法。在本文中,我们首先介绍脑网络组学的概念。然后,我们回顾了在构建精神分裂症患者认知功能受损脑网络组学方面的最新进展。所考虑的相关脑网络模型是使用从不同分析层面的功能和解剖脑成像技术获得的数据创建的:以感兴趣区域为中心的网络、与特定认知功能相关的网络、全脑网络以及脑网络的属性。最后,我们讨论了脑网络组学研究当前面临的挑战和潜在的新研究方向。