GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
FOCUS Lab, Department of Psychology, University of Turin, Turin, Italy.
Brain. 2018 Nov 1;141(11):3211-3232. doi: 10.1093/brain/awy252.
The pathological brain is characterized by distributed morphological or structural alterations in the grey matter, which tend to follow identifiable network-like patterns. We analysed the patterns formed by these alterations (increased and decreased grey matter values detected with the voxel-based morphometry technique) conducting an extensive transdiagnostic search of voxel-based morphometry studies in a large variety of brain disorders. We devised an innovative method to construct the networks formed by the structurally co-altered brain areas, which can be considered as pathological structural co-alteration patterns, and to compare these patterns with three associated types of connectivity profiles (functional, anatomical, and genetic). Our study provides transdiagnostical evidence that structural co-alterations are influenced by connectivity constraints rather than being randomly distributed. Analyses show that although all the three types of connectivity taken together can account for and predict with good statistical accuracy, the shape and temporal development of the co-alteration patterns, functional connectivity offers the better account of the structural co-alteration, followed by anatomic and genetic connectivity. These results shed new light on the possible mechanisms at the root of neuropathological processes and open exciting prospects in the quest for a better understanding of brain disorders.
病理性大脑的特征是灰质的分布形态或结构改变,这些改变往往遵循可识别的网络样模式。我们通过对各种大脑疾病的基于体素的形态计量学研究进行广泛的跨诊断搜索,分析了这些改变形成的模式(通过体素基于形态计量学技术检测到的增加和减少的灰质值)。我们设计了一种创新的方法来构建由结构上共同改变的脑区形成的网络,可以将其视为病理性结构共同改变模式,并将这些模式与三种相关类型的连接谱(功能、解剖和遗传)进行比较。我们的研究提供了跨诊断证据,表明结构共同改变受连接约束的影响,而不是随机分布。分析表明,尽管所有三种类型的连接组合在一起可以很好地解释和预测,但是共同改变模式的形状和时间发展,功能连接提供了更好的结构共同改变解释,其次是解剖和遗传连接。这些结果为神经病理学过程的可能机制提供了新的线索,并为更好地理解大脑疾病开辟了令人兴奋的前景。