Schizophrenia has been understood as a network disease with altered functional and structural connectivity in multiple brain networks compatible to the extremely broad spectrum of psychopathological, cognitive, and behavioral symptoms in this disorder. When building brain networks, functional and structural networks are typically modeled independently: Functional network models are based on temporal correlations among brain regions, whereas structural network models are based on anatomical characteristics. Combining both features may give rise to more realistic and reliable models of brain networks. In this study, we applied a new flexible graph-theoretical-multimodal model called FD (F, the functional connectivity matrix, and D, the structural matrix) to construct brain networks combining functional, structural, and topological information of magnetic resonance imaging (MRI) measurements (structural and resting-state imaging) to patients with schizophrenia (n = 35) and matched healthy individuals (n = 41). As a reference condition, the traditional pure functional connectivity (pFC) analysis was carried out. By using the FD model, we found disrupted connectivity in the thalamo-cortical network in schizophrenic patients, whereas the pFC model failed to extract group differences after multiple comparison correction. We interpret this observation as evidence that the FD model is superior to conventional connectivity analysis, by stressing relevant features of the whole-brain connectivity, including functional, structural, and topological signatures. The FD model can be used in future research to model subtle alterations of functional and structural connectivity, resulting in pronounced clinical syndromes and major psychiatric disorders. Lastly, FD is not limited to the analysis of resting-state functional MRI, and it can be applied to electro-encephalography, magneto-encephalography, etc.

中文翻译：

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使用时间和结构相关性的新的图理论多峰方法揭示了精神分裂症患者丘脑-皮质网络的破坏。

精神分裂症被理解为一种网络疾病，其在多个脑网络中的功能和结构连接性发生了改变，与该疾病的极为广泛的心理病理，认知和行为症状相兼容。在构建大脑网络时，功能和结构网络通常是独立建模的：功能网络模型基于大脑区域之间的时间相关性，而结构网络模型则基于解剖特征。结合这两种功能可能会产生更现实，更可靠的大脑网络模型。在这项研究中，我们应用了一种称为FD（F，功能连接矩阵，D，结构矩阵）的灵活的图论多模式新模型，以构建将功能，结构，精神分裂症患者（n = 35）和健康人（n = 41）的磁共振成像（MRI）测量（结构和静止状态成像）的拓扑信息。作为参考条件，进行了传统的纯功能连接（pFC）分析。通过使用FD模型，我们发现精神分裂症患者的丘脑-皮质网络连接受到破坏，而pFC模型在多次比较校正后未能提取组差异。通过强调全脑连接的相关特征（包括功能，结构和拓扑特征），我们将此观察解释为FD模型优于常规连接分析的证据。FD模型可用于将来的研究中，以对功能和结构连接性的细微变化建模，从而导致明显的临床综合征和主要的精神疾病。最后，FD不仅限于静态功能性MRI的分析，而且可以应用于脑电图，磁脑图等。