Reineberg Andrew E, Gustavson Daniel E, Benca Chelsie, Banich Marie T, Friedman Naomi P
Department of Psychology and Neuroscience, University of Colorado Boulder, Boulder, CO, United States.
Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, United States.
Front Psychol. 2018 Sep 5;9:1600. doi: 10.3389/fpsyg.2018.01600. eCollection 2018.
The brain is organized into a number of large networks based on shared function, for example, high-level cognitive functions (frontoparietal network), attentional capabilities (dorsal and ventral attention networks), and internal mentation (default network). The correlations of these networks during resting-state fMRI scans varies across individuals and is an indicator of individual differences in ability. Prior work shows higher cognitive functioning (as measured by working memory and attention tasks) is associated with stronger negative correlations between frontoparietal/attention and default networks, suggesting that increased ability may depend upon the diverging activation of networks with contrasting function. However, these prior studies lack specificity with regard to the higher-level cognitive functions involved, particularly with regards to separable components of executive function (EF). Here we decompose EF into three factors from the unity/diversity model of EFs: Common EF, Shifting-specific EF, and Updating-specific EF, measuring each via factor scores derived from a battery of behavioral tasks completed by 250 adult participants (age 28) at the time of a resting-state scan. We found the hypothesized segregated pattern only for Shifting-specific EF. Specifically, after accounting for one's general EF ability (Common EF), individuals better able to fluidly switch between task sets have a stronger negative correlation between the ventral attention network and the default network. We also report non-predicted novel findings in that individuals with higher Shifting-specific abilities exhibited more positive connectivity between frontoparietal and visual networks, while those individuals with higher Common EF exhibited increased connectivity between sensory and default networks. Overall, these results reveal a new degree of specificity with regard to connectivity/EF relationships.
大脑基于共享功能被组织成多个大型网络，例如，高级认知功能（额顶叶网络）、注意力能力（背侧和腹侧注意力网络）以及内部心理活动（默认网络）。在静息态功能磁共振成像扫描期间，这些网络之间的相关性因人而异，并且是能力个体差异的一个指标。先前的研究表明，较高的认知功能（通过工作记忆和注意力任务衡量）与额顶叶/注意力网络和默认网络之间更强的负相关性相关，这表明能力的提高可能取决于具有相反功能的网络的不同激活。然而，这些先前的研究在涉及的高级认知功能方面缺乏特异性，特别是在执行功能（EF）的可分离成分方面。在这里，我们根据执行功能的统一/多样性模型将执行功能分解为三个因素：共同执行功能、特定转换执行功能和特定更新执行功能，通过对250名成年参与者（28岁）在静息态扫描时完成的一系列行为任务得出的因素得分来衡量每个因素。我们仅在特定转换执行功能中发现了假设的分离模式。具体而言，在考虑了一个人的一般执行功能能力（共同执行功能）之后，能够在任务集之间更流畅切换的个体，其腹侧注意力网络和默认网络之间的负相关性更强。我们还报告了未预测到的新发现，即具有较高特定转换能力的个体在额顶叶和视觉网络之间表现出更多的正连接，而具有较高共同执行功能的个体在感觉和默认网络之间表现出连接增加。总体而言，这些结果揭示了连接性/执行功能关系方面新的特异性程度。
