Jarrahi Behnaz, Kollias Spyros
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:1116-1119. doi: 10.1109/EMBC44109.2020.9175465.
Recent neuroimaging studies have employed graph theory as a data-driven approach to describe topological organization of the brain under different neurological disorders or task conditions and across life span. In this exploratory study, we tested whether subtle differences in interoception related to intravesical fullness can alter brain topological architecture in healthy participants. 17 right-handed women underwent a series of resting state fMRI scans that included catheterization and partial bladder filling. Using a whole brain regions of interest (ROIs), we computed several graph theory metrics to assess the efficiency of brain-wide information exchange. Results showed that brain network's topological properties significantly changed in many brain regions when we binary compared different interoceptive resting state conditions. Notably, we observed changes in global efficiency in the salience network, the central executive network, anterior dorsal attention network and the posterior default-mode network (DMN) as bladder became full and interoceptive signals intensified. Moreover, degree (the number of connections for each node), and betweenness centrality (how connected a particular region is to other regions) differed between the empty bladder, the catheterized empty bladder, and the catheterized and partially filled bladder. Comparing resting state data before and after an interoceptive task (repeated intravesical infusion and drainage) further showed increased average path length for the salience networks and decreased clustering coefficient of the DMN. These results suggest visceral interoception influences brain topological properties of resting state networks.
最近的神经影像学研究采用图论作为一种数据驱动的方法，来描述在不同神经系统疾病、任务条件下以及整个生命周期中大脑的拓扑组织。在这项探索性研究中，我们测试了与膀胱内充盈相关的内感受的细微差异是否会改变健康参与者的大脑拓扑结构。17名右利手女性接受了一系列静息态功能磁共振成像扫描，包括导尿和膀胱部分充盈。我们使用全脑感兴趣区域（ROI）计算了几个图论指标，以评估全脑信息交换的效率。结果表明，当我们对不同的内感受静息态条件进行二元比较时，许多脑区的脑网络拓扑属性发生了显著变化。值得注意的是，随着膀胱充盈和内感受信号增强，我们观察到显著网络、中央执行网络、前背侧注意网络和后默认模式网络（DMN）的全局效率发生了变化。此外，在膀胱空虚、导尿后膀胱空虚以及导尿并部分充盈膀胱的状态下，度（每个节点的连接数）和中介中心性（一个特定区域与其他区域的连接程度）有所不同。比较内感受任务（重复膀胱内灌注和引流）前后的静息态数据进一步显示，显著网络的平均路径长度增加，而DMN的聚类系数降低。这些结果表明，内脏内感受会影响静息态网络的大脑拓扑属性。
