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首页> 外文期刊>Cerebral cortex >Topologically Reorganized Connectivity Architecture of Default-Mode, Executive-Control, and Salience Networks across Working Memory Task Loads
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Topologically Reorganized Connectivity Architecture of Default-Mode, Executive-Control, and Salience Networks across Working Memory Task Loads

机译:跨工作内存任务负载的默认模式,执行控制和显着网络的拓扑重组连接结构

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The human brain is topologically organized into a set of spatially distributed, functionally specific networks. Of these networks, the default-mode network (DMN), executive-control network (ECN), and salience network (SN) have received the most attention recently for their vital roles in cognitive functions. However, very little is known about whether and how the interactions within and between these 3 networks would be modulated by cognitive demands. Here, we employed graph-based modularity analysis to identify the DMN, ECN, and SN during an N-back working memory (WM) task and further investigated the modulation of intra- and inter-network interactions at different cognitive loads. As the task load elevated, functional connectivity decreased within the DMN while increased within the ECN, and the SN connected more with both the DMN and ECN. Within-network connectivity of the ventral and dorsal posterior cingulate cortex was differentially modulated by cognitive load. Further, the superior parietal regions in the ECN showed increased internetwork connections at higher WM loads, and these increases correlated positively with WM task performance. Together, these findings advance our understanding of dynamic integrations of specialized brain systems in response to cognitive demands and may serve as a baseline for assessing potential disruptions of these interactions in pathological conditions.
机译:人脑在拓扑上被组织为一组空间分布的,功能特定的网络。在这些网络中,默认模式网络(DMN),执行控制网络(ECN)和显着网络(SN)最近因其在认知功能中的重要作用而受到了最广泛的关注。然而,关于这三个网络之间以及之间的相互作用是否以及如何被认知需求所调节的了解甚少。在这里,我们采用了基于图的模块化分析来识别N背工作记忆(WM)任务期间的DMN,ECN和SN,并进一步研究了在不同认知负载下网络内和网络间交互的调制方式。随着任务负载的增加,DMN中的功能连接性下降,而ECN中的功能连接性增加,并且SN与DMN和ECN的连接更多。腹侧和背后扣带回皮层的网络内连接受到认知负荷的差异调节。此外,ECN的上壁区域在更高的WM负载下显示出增加的互联网络连接,并且这些增加与WM任务性能呈正相关。在一起,这些发现使我们对响应认知需求的专用大脑系统动态整合的理解成为可能,并且可以作为评估病理条件下这些相互作用的潜在破坏的基线。

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