Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri; Medical Scientist Training Program, Washington University in St. Louis, St. Louis, Missouri.
Department of Psychiatry, Washington University in St. Louis, St. Louis, Missouri.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2019 Oct;4(10):870-880. doi: 10.1016/j.bpsc.2019.05.004. Epub 2019 May 20.
Disorders with psychotic features, including schizophrenia and some bipolar disorders, are associated with impairments in regulation of goal-directed behavior, termed cognitive control. Cognitive control-related neural alterations have been studied in psychosis. However, studies are typically unimodal, and relationships across modalities of brain function and structure remain unclear. Thus, we performed transdiagnostic multimodal analyses to examine cognitive control-related neural variation in psychosis.
Structural, resting, and working memory task imaging for 31 control participants, 27 participants with bipolar disorder, and 23 participants with schizophrenia were collected and processed identically to the Human Connectome Project, enabling identification of relationships with prior multimodal work. Two cognitive control-related independent components (ICs) derived from the Human Connectome Project using multiset canonical correlation analysis with joint IC analysis were used to predict performance in psychosis. De novo multiset canonical correlation analysis with joint IC analysis was performed, and the results were correlated with cognitive control.
A priori working memory and cortical thickness maps significantly predicted cognitive control in psychosis. De novo multiset canonical correlation analysis with joint IC analysis identified an IC correlated with cognitive control that also discriminated groups. Structural contributions included insular and cingulate regions; task contributions included precentral, posterior parietal, cingulate, and visual regions; and resting-state contributions highlighted canonical network organization. Follow-up analyses suggested that correlations with cognitive control were primarily influenced by participants with schizophrenia.
A priori and de novo imaging replicably identified a set of interrelated patterns across modalities and the healthy-to-psychosis spectrum, suggesting robustness of these features. Relationships between imaging and cognitive control performance suggest that shared symptomatology may be key to identifying transdiagnostic relationships in psychosis.
包括精神分裂症和某些双相情感障碍在内的以精神病特征为特征的疾病与目标导向行为的调节障碍有关，称为认知控制。已经在精神病学中研究了与认知控制相关的神经改变。然而，研究通常是单模态的，并且大脑功能和结构的模态之间的关系尚不清楚。因此，我们进行了跨诊断多模态分析，以研究精神病中的与认知控制相关的神经变化。
对 31 名对照参与者，27 名双相情感障碍参与者和 23 名精神分裂症患者进行了结构，静息和工作记忆任务成像，其处理方式与人类连接组计划相同，从而能够识别与先前多模态工作的关系。使用多集典型相关分析和联合 IC 分析从人类连接组计划中得出的两个与认知控制相关的独立成分（IC）用于预测精神病中的表现。进行了从头开始的多集典型相关分析和联合 IC 分析，并将结果与认知控制相关联。
工作记忆和皮质厚度图的先验预测对精神病中的认知控制有重要意义。从头开始的多集典型相关分析和联合 IC 分析确定了与认知控制相关且可区分组别的 IC。结构贡献包括岛叶和扣带回区域；任务贡献包括中央前回，顶后回，扣带回和视觉区域；静息状态贡献突出了规范网络组织。后续分析表明，与认知控制的相关性主要受精神分裂症患者的影响。
预先和从头开始的成像可复制地识别出跨模态和健康与精神病谱之间的一组相互关联的模式，表明这些特征具有稳健性。成像与认知控制表现之间的关系表明，共同的症状学可能是确定精神病中跨诊断关系的关键。
