Characterizations of resting-state modulatory interactions in the human brain
Characterizations of resting-state modulatory interactions in the human brain
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DOI：
10.1152/jn.00893.2014
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发表时间：
2015-11-01
影响因子：
2.5
通讯作者：
Biswal, Bharat B.
中科院分区：
文献类型：
--
作者：
Di, Xin;Biswal, Bharat B.
使用功能性磁共振成像（fMRI）测量的两个大脑区域之间的功能连接已经被证明即使在休息状态下也会受到其他区域的调节，即，而不执行特定任务。我们的目的是通过对静息状态fMRI数据进行基于感兴趣区域（ROI）的生理生理相互作用分析来表征大规模的调节相互作用。在对全脑取样的160个ROI中，计算三个ROI的每种可能组合的调制相互作用。首先，在所有重要的调节相互作用中，负面影响远多于正面影响;即，在更多的情况下，一个区域活动的增加与另外两个区域之间功能连接的减少有关。接下来，将调节性相互作用分类为三个ROI是否来自一个单一的网络模块，两个模块，或三个不同的模块（通过对其功能连接性的模块化分析来定义）。积极的调制相互作用比预期的情况下，其中三个ROI是从一个单一的模块，这表明通过积极的调制相互作用模块内的处理效率的增加。相反，负调制的相互作用比预期的情况下，其中三个ROI是从两个模块，这表明通过负调制的相互作用模块之间的隔离的趋势。然后确定更可能具有调节相互作用的区域。不同区域的显著调节相互作用的数量与区域的连接强度和连接程度相关。这些结果表明，全脑的调制相互作用的特点，并可能提供指导，为未来的研究在静息状态和任务状态下的连接动力学。
Functional connectivity between two brain regions, measured using functional MRI (fMRI), has been shown to be modulated by other regions even in a resting state, i.e., without performing specific tasks. We aimed to characterize large-scale modulatory interactions by performing region-of-interest (ROI)-based physiophysiological interaction analysis on resting-state fMRI data. Modulatory interactions were calculated for every possible combination of three ROIs among 160 ROIs sampling the whole brain. Firstly, among all of the significant modulatory interactions, there were considerably more negative than positive effects; i.e., in more cases, an increase of activity in one region was associated with decreased functional connectivity between two other regions. Next, modulatory interactions were categorized as to whether the three ROIs were from one single network module, two modules, or three different modules (defined by a modularity analysis on their functional connectivity). Positive modulatory interactions were more represented than expected in cases in which the three ROIs were from a single module, suggesting an increase within module processing efficiency through positive modulatory interactions. In contrast, negative modulatory interactions were more represented than expected in cases in which the three ROIs were from two modules, suggesting a tendency of between-module segregation through negative modulatory interactions. Regions that were more likely to have modulatory interactions were then identified. The numbers of significant modulatory interactions for different regions were correlated with the regions' connectivity strengths and connection degrees. These results demonstrate whole-brain characteristics of modulatory interactions and may provide guidance for future studies of connectivity dynamics in both resting state and task state.