The capacity to identify aspects of meaning that overlap across multiple concepts may relate to individual differences in the strength of intrinsic connectivity within and between distinct brain networks supporting semantic cognition. This study examined a semantic summation task, which tested the capacity to detect weak overlapping aspects of meaning, in 76 participants who were also scanned with resting-state fMRI. We examined associations between summation and the intrinsic connectivity of semantically-relevant default mode and control network regions. These networks are implicated in information integration and controlled retrieval respectively. We found higher intrinsic connectivity between default and control networks was associated with better performance in the summation task. The same pattern of coupling between semantic default mode and control networks was not associated with more efficient retrieval of individual weak as opposed to strong associations in an additional cohort of around 200 participants, suggesting this pattern is specific to the summation of multiple concepts, rather than semantic task difficulty. Finally, higher connectivity within the default mode network was associated with better performance when selecting a word that was strongly-related to a single probe item, supporting the role of this network in more automatic aspects of semantic retrieval.

识别在多个概念上重叠的含义方面的能力可能与支持语义认知的不同大脑网络内部和之间的固有连接强度的个体差异有关。这项研究检查了一项语义求和任务，该任务测试了76位参加者（还接受了静息状态fMRI扫描）来检测意义的弱重叠部分。我们研究了语义相关默认模式和控制网络区域的求和与内部连接之间的关联。这些网络分别涉及信息集成和受控检索。我们发现默认和控制网络之间更高的固有连接性与求和任务中的更好性能相关。语义默认模式与控制网络之间的相同耦合模式与更弱的个体弱势检索（而不是强关联）相联系，而在另外的约200名参与者中，强势关联则表明这种模式特定于多个概念的总和，而不是语义任务难度。最后，选择一个词是强相关的一个探头的项目，支持在语义检索的多种自动方面该网络的作用时的默认模式网络中更高的连接与更好的性能有关。而不是语义任务难度。最后，选择一个词是强相关的一个探头的项目，支持在语义检索的多种自动方面该网络的作用时的默认模式网络中更高的连接与更好的性能有关。而不是语义任务难度。最后，选择一个词是强相关的一个探头的项目，支持在语义检索的多种自动方面该网络的作用时的默认模式网络中更高的连接与更好的性能有关。