Age-related Change and the Predictive Value of the 'Resting State': A Commentary on Campbell and Schacter (2016).
Age-related Change and the Predictive Value of the 'Resting State': A Commentary on Campbell and Schacter (2016).
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与年龄相关的变化和“静息状态”的预测价值：坎贝尔和沙克特的评论（2016）。
DOI：
10.1080/23273798.2016.1242759
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Reuter-Lorenz,PatriciaA
中科院分区：
文献类型：
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作者：
Iordan,AlexandruD;Reuter-Lorenz,PatriciaA
“静息状态功能连接”（RSFC）作为研究人脑功能组织的主要工具正在日益占据主导地位。大脑大规模功能网络的整体拓扑已被证明具有高度可重复性，据称超越了多种任务环境，并随着发育、衰老和疾病而以系统的方式发生变化（参见 Matthews & Hampshire, 2016；Stevens & Spreng, 2014 了解最新评论）。 RSFC 研究的出现恰逢方法论创新，例如将图论网络模型和大数据分析融入大脑研究。 Campbell & Schacter (C&S) 在当前的文章中承认使用 RSFC 认知测量方法的研究激增，并对其作为认知功能和动态的卓越预测因子的地位提出了挑战。他们主张基于任务的设计在测试有关认知和衰老的具体假设方面发挥重要作用。简而言之，C&S 认为 RSFC 并没有提供了解人脑功能结构的特权窗口，而且它很容易出现变异，并受到非认知因素（例如运动和血管健康）年龄差异的影响。至关重要的是，RSFC 在检验认知假设方面的用途有限，因为它的测量总是远离研究人员试图将其与之联系起来的认知现象。虽然我们同意 C&S 的立场，即精心设计的实验操作对于测试有关认知及其神经相关性的特定机制假设至关重要，但我们认为，在特定情况下，RSFC 测量可能比任务诱发活动提供某些优势，并且 RSFC 和任务相关方法真正且日益彻底的整合对于增进我们对大脑功能和衰老的理解至关重要。在我们对 C&S 文章的评论中，我们首先强调了 RSFC 方法的一些具体优势，特别是在研究神经认知衰老方面，然后我们回顾了支持大脑“静息状态”预测价值的关键证据，最后我们讨论了强调大脑“内在”活动的观点的含义。正如 C&S 所说，衰老神经科学研究的主要目标是了解与年龄相关的大脑变化如何影响认知功能。尽管如此，迄今为止，大多数研究都采用了横断面设计，因此仅反映了年龄差异。虽然这项工作激发了重要的新假设，但对相对较小、精英和非代表性样本的横断面研究的依赖限制了我们可以得出的结论以及我们对神经认知衰老的理解（例如 Falk 等人，2013）。相比之下，纵向设计对于评估随时间的变化以及将大脑维护和补偿过程的贡献与神经认知特征中预先存在的个体差异分开是必要的（Nyberg et al., 2010; Raz & Lindenberger, 2013; Reuter-Lorenz & Park, 2014）。随着时间的推移，在同一组测量上评估表现和神经活动的变化是神经认知衰老纵向研究的决定性特征，但即使每个测量点使用新的任务版本，也会引入实践的混杂效应（另见 Lövdén、Bäckman、Lindenberger、Schaefer 和 Schmiedek，2010；Morcom 和 Johnson，2015）。由于 RSFC 方法不会直接受到实践效果的影响，因此它可能提供一种有价值的工具来评估衰退，以及缓解过程，例如功能补偿和/或随时间的可塑性……
“Resting state functional connectivity”(RSFC) is gaining ascendency as a primary tool for investigating the functional organisation of the human brain. The overall topography of the brain’s large-scale functional networks has been shown to be highly reproducible, purportedly transcending a multiplicity of task contexts and changing in systematic ways with development, aging, and disease (see Matthews & Hampshire, 2016; Stevens & Spreng, 2014 for recent reviews). The advent of RSFC research has coincided with methodological innovations, such as the integration into brain research of graph theoretical network models and big data analytics. In their current article, Campbell & Schacter (C&S) acknowledge the proliferation of studies using RSFC measures of cognition and challenge its status as the pre-eminent predictor of cognitive function and dynamics. They advocate for the essential role of task-based designs in testing specific hypotheses about cognition and aging. In brief, C&S argue that RSFC does not provide a privileged window into the functional architecture of the human brain, and that it is prone to variability and influences by age differences in non-cognitive factors, such as motion and vascular health. Critically, RSFC is of limited use for testing hypotheses about cognition because its measures are always remote from the cognitive phenomena that the researchers are trying to relate them to. While we agree with C&S’s position that carefully designed experimental manipulations are essential for testing specific mechanistic hypotheses about cognition and its neural correlates, we will argue that, under specific circumstances, RSFC measures may provide certain advantages over task-evoked activity, and that a genuine and increasingly thorough integration of RSFC and task-related approaches is essential for advancing our understanding of brain function and aging. In our commentary to the C&S article, we first highlight some specific advantages of the RSFC approach, especially to study neurocognitive aging, then we review key evidence supporting the predictive value of the brain’s “resting state”, and finally we discuss the implications of a perspective emphasising the brain’s “intrinsic” activity. As C&S state, the major goal of neuroscientific research on aging is to understand how age-related brain changes impact cognitive function. Still, the majority of studies to date have employed crosssectional designs and thus have informed only about age differences. While this work has stimulated important new hypotheses, reliance on cross-sectional studies with relatively small, elite, and non-representative samples has limited the conclusions we can draw, and our understanding of neurocognitive aging (eg Falk et al., 2013). By contrast, longitudinal designs are necessary for evaluating change over time and for isolating contributions of brain maintenance and compensatory processes from pre-existing individual differences in neurocognitive characteristics (Nyberg et al., 2010; Raz & Lindenberger, 2013; Reuter-Lorenz & Park, 2014). Assessing performance and neural activity changes on the same set of measures over time is the defining feature of longitudinal studies of neurocognitive aging, but also one that introduces confounding effects of practice even when new task versions are used for each measurement point (see also Lövdén, Bäckman, Lindenberger, Schaefer, & Schmiedek, 2010; Morcom & Johnson, 2015). Because the RSFC approach is not directly influenced by practice effects, it may provide a valuable tool for assessing decline, along with mitigating processes such as functional compensation and/or plasticity over time …