Vergara Victor M, Damaraju Eswar, Turner Jessica A, Pearlson Godfrey, Belger Aysenil, Mathalon Daniel H, Potkin Steven G, Preda Adrian, Vaidya Jatin G, van Erp Theo G M, McEwen Sarah, Calhoun Vince D
Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, United States.
2The Mind Research Network, Albuquerque, NM, United States.
Front Psychiatry. 2019 Jul 23;10:499. doi: 10.3389/fpsyt.2019.00499. eCollection 2019.
Functional connectivity is one of the most widely used tools for investigating brain changes due to schizophrenia. Previous studies have identified abnormal functional connectivity in schizophrenia patients at the resting state brain network level. This study tests the existence of functional connectivity effects at whole brain and domain levels. Domain level refers to the integration of data from several brain networks grouped by their functional relationship. Data integration provides more consistent and accurate information compared to an individual brain network. This work considers two domain level measures: functional connectivity strength and randomness. The first measure is simply an average of connectivities within the domain. The second measure assesses the unpredictability and lack of pattern of functional connectivity within the domain. Domains with less random connectivity have higher chance of exhibiting a biologically meaningful connectivity pattern. Consistent with prior observations, individuals with schizophrenia showed aberrant domain connectivity strength between subcortical, cerebellar, and sensorial brain areas. Compared to healthy volunteers, functional connectivity between cognitive and default mode domains showed less randomness, while connectivity between default mode-sensorial areas showed more randomness in schizophrenia patients. These differences in connectivity patterns suggest deleterious rewiring trade-offs among important brain networks.
功能连接性是研究精神分裂症所致大脑变化时使用最广泛的工具之一。先前的研究已经在静息态脑网络水平上确定了精神分裂症患者存在异常的功能连接性。本研究测试了全脑和领域水平上功能连接性效应的存在。领域水平指的是将几个根据功能关系分组的脑网络的数据进行整合。与单个脑网络相比,数据整合能提供更一致和准确的信息。这项工作考虑了两种领域水平的测量方法:功能连接强度和随机性。第一种测量方法只是该领域内连接性的平均值。第二种测量方法评估该领域内功能连接性的不可预测性和缺乏模式性。连接性随机性较小的领域更有可能呈现出具有生物学意义的连接模式。与先前的观察结果一致,精神分裂症患者在皮质下、小脑和感觉脑区之间表现出异常的领域连接强度。与健康志愿者相比,精神分裂症患者认知和默认模式领域之间的功能连接性随机性较小,而默认模式-感觉区域之间的连接性随机性较大。这些连接模式的差异表明重要脑网络之间存在有害的重新布线权衡。