Evolution of the Linked Architecture of Network Control and Executive Function in Adolescence

 描述（由申请人提供）：执行功能的快速发展是青春期的标志，需要跨越多个大脑区域的大规模神经回路的整合招募。在这里，我们建议开发和应用从网络控制理论到大脑成像数据的方法，以便让我们了解执行功能在青年中的发展。控制和动力系统理论的最新进展提供了网络可控性的定量诊断，它们共同定义了外部输入如何影响网络节点（在这种情况下是大脑区域）移动整个系统（在这种情况下是认知功能）。此外，这些方法允许不同的控制结构的成本的定量估计。虽然这些技术以前没有被应用于脑成像数据，但它们提供了执行功能的直观机制，因此有可能成为执行能力的推定生物标志物。在本提案中，我们利用了现有的扩散成像和工作记忆任务fMRI数据，这些数据是在费城神经发育队列（PNC）的一部分，对8-22岁青少年的大样本进行成像。在目标1中，我们将通过以下方式描述大脑结构连接体的网络控制结构：（i）识别网络控制的驱动节点，并将其与已知执行网络的关系映射;（ii）量化网络控制诊断的重测信度。在目标2中，我们将使用横截面（n=968）和纵向数据（n=350）PNC数据，通过描述网络控制诊断的发展来绘制青少年网络控制的演变。在目标3中，我们将通过检查具有较高网络控制水平的个体是否表现出更好的执行功能，并调查基线可控性是否预测了随后的执行功能纵向改善，来确定网络控制与执行功能之间的关系。在目标4中，我们将提供一个实验室可用的工具箱，用于测量网络可控性，作为神经成像社区的资源。这种多学科研究有可能产生高影响力的发现，因此代表了R21机制的良好契合。我们团队的实力（网络科学、发育神经影像学和神经精神病学方面的专业知识）、待检验的多层次假设、收敛的初步数据以及我们对PNC数据集的熟悉程度，都缓和了与该项目创新相关的风险。

 DESCRIPTION (provided by applicant): The rapid development of executive function is a hallmark of adolescence, and requires the integrated recruitment of large-scale neural circuitry spanning multiple brain regions. Here we propose to develop and apply methods from network control theory to brain imaging data in order to allow us to understand how executive function develops in youth. Recent advances in control and dynamical systems theory have provided quantitative diagnostics of network controllability, which collectively define how external input t network nodes (in this case brain areas) can move the entire system (in this case cognitive function). Further, these methods allow quantitative estimation of the costs of disparate control structures. While these techniques have not previously been applied to brain imaging data, they provide an intuitive mechanism for executive function, and therefore have the potential to be putative biomarkers of executive capability. In this proposal, we capitalize upon existing diffusion imaging and working-memory task fMRI data acquired in a large sample of youth ages 8-22 imaged as part of the Philadelphia Neurodevelopmental Cohort (PNC). In Aim 1, we will describe the network control structure of the brain's structural connectome by (i) identifying driver nodes of network control and mapping their relationship to known executive networks and (ii) quantifying test-retest reliability of network control diagnostics. In Aim 2, we will chart th evolution of network control in adolescence by characterizing the development of network control diagnostics using cross-sectional (n=968) and longitudinal data (n=350) PNC data. In Aim 3, we will determine how network control is associated with executive function by examining whether individuals with higher levels of network control demonstrate better executive functioning, and investigating if baseline controllability predicts subsequent longitudinal improvement of executive function. In Aim 4, we will provide a publically available toolbox for measurement of network controllability as a resource to the neuroimaging community. This multi-disciplinary research has the potential to yield high-impact discoveries, and therefore represents a good fit for the R21 mechanism. Risks associated with the innovation in this project are tempered by the strength of our team (expertise in network science, developmental neuroimaging, and neuropsychiatry), the multiple levels of hypotheses to be tested, convergent preliminary data, and our intimate familiarity with the PNC dataset.