Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n = 90) and replication (n = 74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ.

中文翻译：

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结构协方差揭示了慢性精神分裂症患者控制和显着性网络完整性的改变。

精神分裂症（SCZ）被认为是一种分布性大脑不连通的疾病。尽管在描述SCZ中的大型功能网络方面已经取得了进展，但是对于这些网络的灰质完整性的改变知之甚少。我们使用多元方法来确定显着性，默认，运动，视觉，额顶控制和背侧注意力网络的结构协方差。我们得出了反映给定网络每个结构图像中协方差的个体分数。在SCZ患者和健康对照的发现样本（n = 90）和复制样本（n = 74）中对结构图像进行基于种子的多元分析。我们首先在所有网络上验证了模式，并与完善的功能连接报告保持一致。接下来，在两个SCZ样本中，我们发现额顶控制和显着网络的结构完整性可靠而稳健地降低了，但并非默认情况下降低了背部注意力，运动和感觉网络。功能强大的探索性分析无法确定与症状的关系。这些发现提供了SCZ关联网络选择性结构性下降的证据。这种下降可能与关联网络中最近发现的功能干扰有关，从而在SCZ中提供了更为敏感的多模式网络级探针。缺乏症状影响表明，已识别的障碍可能是SCZ中性状类型标记的基础。这些发现提供了SCZ关联网络选择性结构性下降的证据。这种下降可能与关联网络中最近发现的功能干扰有关，从而在SCZ中提供了更为敏感的多模式网络级探针。缺乏症状影响表明，已识别的疾病可能是SCZ中性状类型标记的基础。这些发现提供了SCZ关联网络选择性结构性下降的证据。这种下降可能与关联网络中最近发现的功能干扰有关，从而在SCZ中提供了更为敏感的多模式网络级探针。缺乏症状影响表明，已识别的疾病可能是SCZ中性状类型标记的基础。