GCS fMRI, Koelliker Hospital and University of Turin, Turin, Italy; FOCUS Lab, Department of Psychology, University of Turin, Via Verdi, 10, Turin 10124, Italy.
FOCUS Lab, Department of Psychology, University of Turin, Via Verdi, 10, Turin 10124, Italy.
Neuroimage. 2021 Jan 15;225:117481. doi: 10.1016/j.neuroimage.2020.117481. Epub 2020 Oct 24.
Brain disorders tend to impact on many different regions in a typical way: alterations do not spread randomly; rather, they seem to follow specific patterns of propagation that show a strong overlap between different pathologies. The insular cortex is one of the brain areas more involved in this phenomenon, as it seems to be altered by a wide range of brain diseases. On these grounds we thoroughly investigated the impact of brain disorders on the insular cortices analyzing the patterns of their structural co-alteration. We therefore investigated, applying a network analysis approach to meta-analytic data, 1) what pattern of gray matter alteration is associated with each of the insular cortex parcels; 2) whether or not this pattern correlates and overlaps with its functional meta-analytic connectivity; and, 3) the behavioral profile related to each insular co-alteration pattern. All the analyses were repeated considering two solutions: one with two clusters and another with three. Our study confirmed that the insular cortex is one of the most altered cerebral regions among the cortical areas, and exhibits a dense network of co-alteration including a prevalence of cortical rather than sub-cortical brain regions. Regions of the frontal lobe are the most involved, while occipital lobe is the less affected. Furthermore, the co-alteration and co-activation patterns greatly overlap each other. These findings provide significant evidence that alterations caused by brain disorders are likely to be distributed according to the logic of network architecture, in which brain hubs lie at the center of networks composed of co-altered areas. For the first time, we shed light on existing differences between insula sub-regions even in the pathoconnectivity domain.
改变不是随机扩散的；相反，它们似乎遵循特定的传播模式，这些模式在不同的病理中表现出很强的重叠。脑岛是涉及到这种现象的大脑区域之一，因为它似乎受到广泛的脑疾病的影响。基于这些原因，我们通过分析其结构共改变的模式，深入研究了脑区疾病对脑岛的影响。因此，我们应用网络分析方法对荟萃分析数据进行了研究，以调查：1）脑岛各脑区的灰质改变模式；2）该模式是否与功能元连接相关联和重叠；3）与每个脑岛共改变模式相关的行为特征。所有分析均考虑了两种解：一种是两个簇，另一种是三个簇。我们的研究证实，脑岛是皮质区域中最易受影响的大脑区域之一，它具有密集的共改变网络，包括皮质区域而非皮质下区域的改变。额叶区域最易受影响，而枕叶区域则受影响最小。此外，共改变和共激活模式彼此高度重叠。这些发现提供了重要的证据，表明脑区疾病引起的改变很可能根据网络结构的逻辑分布，而大脑枢纽处于由共改变区域组成的网络的中心。我们首次揭示了即使在病理连接域中，脑岛亚区之间也存在的差异。
