电子科技大学学报Issue(2)：296-300,5.DOI:10.3969/j.issn.1001-0548.2014.02.027
多变量模式分析在反社会人格障碍中的应用
Application of Multivariate Pattern Analysis in Antisocial Personality Disorder
摘要
Abstract
Due to a very close link between antisocial personality disorder (ASPD) and criminal behavior, understanding the pathophysiology of ASPD is an international imperative. The objective of the present study is to develop a method of multivariate pattern analysis and investigate the altered functional connectivity patterns of ASPD by using rest-state functional magnetic resonance (MRI). Our results show that multivariate pattern analysis can provides accurate classification between ASPD and control subjects, and the ASPD is motivated from the uncoupling among the default mode network, the attention network, the visual recognition network, and the cerebellar network. Moreover, the method can succeed to extract altered information of ASPD and provide the first evidence for the altered brain’s functional connections in ASPD.关键词
反社会人格障碍/脑功能网络/功能连接/多变量模式分析/静息态功能磁共振/支持向量机Key words
antisocial personality disorder/brain functional network/functional connectivity/multivariate pattern analysis/resting-state functional MRI/support vector machine分类
信息技术与安全科学引用本文复制引用
蒋伟雄,刘华生,廖坚,廖云杰,唐艳,王维..多变量模式分析在反社会人格障碍中的应用[J].电子科技大学学报,2014,(2):296-300,5.基金项目
教育部人文社科基金青年项目(13YJCZH068)；湖南省科技计划(2013GK1024)；湖南省教育厅科学研究项目(13B013) （13YJCZH068）
