Contributions of default mode network stability and deactivation to adolescent task engagement
Contributions of default mode network stability and deactivation to adolescent task engagement
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DOI：
10.1038/s41598-018-36269-4
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发表时间：
2018-12
影响因子：
4.6
通讯作者：
E. McCormick;Eva H. Telzer
中科院分区：
文献类型：
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作者：
E. McCormick;Eva H. Telzer
在过去十年通过静息状态功能分析发现的几个内在脑网络中，默认模式网络(DMN)一直是人们强烈兴趣和研究的主题。特别是，DMN在任务参与过程中表现出明显的抑制，并导致了内部定向认知中的假设角色，需要下调这些角色才能执行目标定向行为。以前的工作主要集中在单变量失活作为DMN抑制的机制。然而，鉴于任务过程中DMN下调的暂时性，一个重要的问题出现了：为了促进成功的任务学习，DMN是否需要被强烈地抑制，或者更稳定地被抑制？为了探索这个问题，65名青少年(MAGE= 13.32；21名女性)在功能磁共振扫描期间完成了一项高风险的决策任务。我们测试了我们的主要问题，通过检查在预测任务反馈学习水平时，去激活的绝对水平与激活的稳定性随时间的个体差异。为了测量稳定性，我们使用了一种基于模型的功能连接性方法，该方法估计了跨时间区域激活的稳定性。根据我们的假设，默认模式区域激活的稳定性预测了任务投入超过DMN去激活的绝对水平，揭示了大脑可以抑制大脑网络对行为的影响的新机制。这些结果还突显了采用基于模型的网络方法来理解大脑功能动力学的重要性。
Out of the several intrinsic brain networks discovered through resting-state functional analyses in the past decade, the default mode network (DMN) has been the subject of intense interest and study. In particular, the DMN shows marked suppression during task engagement, and has led to hypothesized roles in internally-directed cognition that need to be down-regulated in order to perform goal-directed behaviors. Previous work has largely focused on univariate deactivation as the mechanism of DMN suppression. However, given the transient nature of DMN down-regulation during task, an important question arises: Does the DMN need to bestrongly, or morestablysuppressed to promote successful task learning? In order to explore this question, 65 adolescents (Mage= 13.32; 21 females) completed a risky decision-making task during an fMRI scan. We tested our primary question by examining individual differences in absolute level of deactivation against the stability of activation across time in predicting levels of feedback learning on the task. To measure stability, we utilized a model-based functional connectivity approach that estimates the stability of activation across timewithina region. In line with our hypothesis, the stability of activation in default mode regions predicted task engagement over and above the absolute level of DMN deactivation, revealing a new mechanism by which the brain can suppress the influence of brain networks on behavior. These results also highlight the importance of adopting model-based network approaches to understand the functional dynamics of the brain.