As for the conceptualization of mental disorders,the traditional DSM–ICD classification diagnostic system and the Research Domain Criteria(RDoC)are both based on the latent variable perspective,assuming that the symptoms of mental disorders have an underlying common cause.Both views ignore the interaction between symptoms.In 2008,Borsboom put forward the psychopathological network theory,a new perspective different from the categorical and dimensional views of the conceptualization of mental disorders.The core idea of the psychopathological network theory is that the dynamic causal relationship between symptoms constitutes the mental disorder.Based on this theory,the network methods mainly estimate the partial correlation network of symptoms using the glasso algorithm with EBIC,and examine the different characteristics of mental disorder symptoms using indicators such as node centrality and network connectivity.In recent years,researchers have found that there remained some challenges for the psychopathological network methods with respect to the causal relationship inference of symptoms,the identification of central symptoms,and also the reliability and replicability of the network structures.These challenges proposed possible agendas for future research on the psychopathological network theory and methods.

对于精神障碍这一概念的理解,传统DSM–ICD分类诊断系统和研究领域标准RDoC均基于潜变量视角,认为精神障碍的症状由其潜在共同原因所致。这2种观点都忽略了症状间的相互作用。不同于分类和维度视角, Borsboom在2008年对精神障碍的概念化提出了的全新视角——心理病理学网络理论。此理论的核心观点是症状之间的动态因果关系构成了精神障碍。基于心理病理学网络理论的网络分析方法,主要以结合EBIC的glasso算法估计症状间的偏相关网络,并通过网络中节点中心性与网络连接性等指标,来考查精神障碍症状的不同特性。近几年来,研究者发现心理病理学网络分析方法在对症状间因果关系的推断、核心症状的识别和网络结构的可靠性与可重复性方面仍面临一些挑战。这些挑战为心理病理学网络理论与方法指明了未来可能的发展方向。

国家自然科学基金项目(31471004和31971020);; 国家社会科学基金重大项目(20ZDA079);; 中国科学院对外合作重点项目(153111KYSB20160036);中国科学院重点部署项目(ZDRW-XH-2019-4);; 教育部人文社会科学重点研究基地重大项目(16JJD190006)支持