Abstract：
Delusion is an important feature of schizophrenia, which may stem from cognitive biases. Working memory (WM) is the core foundation of cognition, closely related to delusion. However, the knowledge of neural mechanisms underlying the relationship between WM and delusion in schizophrenia is poorly investigated. Two hundred and thirty patients with schizophrenia (dataset 1: n = 130; dataset 2: n = 100) were enrolled and scanned for an N-back WM task. We constructed the WM-related whole-brain functional connectome and conducted Connectome-based Predictive Modelling (CPM) to detect the delusion-related networks and built the correlation model in dataset 1. The correlation between identified networks and delusion severity was tested in a separate, heterogeneous sample of dataset 2 that mainly includes early-onset schizophrenia. The identified delusion-related network has a strong correlation with delusion severity measured by the NO.20 item of SAPS in dataset 1 (r = 0.433, p = 2.7 × 10-7, permutation-p = 0.035), and can be validated in the same dataset by using another delusion measurement, that is, the P1 item of PANSS (r = 0.362, p = 0.0005). It can be validated in another independent dataset 2 (NO.20 item of SAPS for r = 0.31, p = 0.0024, P1 item of PANSS for r = 0.27, p = 0.0074). The delusion-related network comprises the connections between the default mode network (DMN), cingulo-opercular network (CON), salience network (SN), subcortical, sensory-somatomotor network (SMN), and visual networks. We successfully established correlation models of individualized delusion based on the WM-related functional connectome and showed a strong correlation between delusion severity and connections within the DMN, CON, SMN, and subcortical network.
摘要：
妄想是精神分裂症的一个重要特征,这可能源于认知偏见。工作记忆是认知的核心基础,与妄想密切相关。然而,关于精神分裂症中WM与妄想之间关系的神经机制的知识研究甚少。招募了230名精神分裂症患者（数据集1：n=130；数据集2：n=100），并扫描了N-backWM任务。我们构建了WM相关的全脑功能连接体，并进行了基于连接体的预测模型（CPM）来检测妄想相关网络，并在数据集1中建立了相关模型。已识别的网络和妄想严重程度之间的相关性进行了单独的测试，数据集2的异质性样本，主要包括早发性精神分裂症。已识别的与妄想相关的网络与数据集1中SAPS的NO.20项测量的妄想严重程度具有很强的相关性（r=0.433，p=2.7×10-7，排列-p=0.035），并且可以通过使用另一个妄想测量在同一数据集中进行验证，也就是说,PANSS的P1项（r=0.362，p=0.0005）。它可以在另一个独立的数据集2（SAPS的NO.20项，r=0.31，p=0.0024，PANSS的P1项，r=0.27，p=0.0074）中进行验证。与错觉相关的网络包括默认模式网络(DMN)之间的连接，环带-可操作网络(CON)，显著性网络(SN)，皮质下,感觉-躯体运动网络(SMN)，和视觉网络。我们成功建立了基于WM相关功能连接组的个体化妄想的相关模型，并显示了妄想严重程度与DMN内的连接之间的强相关性，CON,SMN,和皮层下网络。
