论文标题
评估静息脑熵的神经认知相关性
Assessing the neurocognitive correlates of resting brain entropy
论文作者
论文摘要
人脑表现出大规模的自发波动，这些波动是其总能量代谢的大部分。独立于任何明显的功能，这种巨大的持续活动可能会产生或维持潜在的功能性脑部储备，以促进正常的大脑功能。自发性大脑活动的重要特性是远程时间连贯性，可以以静止状态fMRI为基于fMRI的脑熵映射（BEN）来表征，这是一种相对较新的方法，它已增强了研究兴趣。这项研究的目的是利用人类Connectome项目公开获得的大型休息状态和行为数据，以解决三个重要但未知问题的问题：RSFMRI-derive的Ben的时间稳定性；休息本与潜在功能储备的关系；静止的BEN与神经认知的关联。我们的结果表明，RSFMRI衍生的Ben在整个时间内都非常稳定。在默认模式网络（DMN）和执行控制网络（ECN）中休息BEN与大脑储备有关，与教育年份的负相关；较低的DMN/ECN BEN对应于更高的流体智能和更好的任务性能。这些结果表明，静止的Ben是一个暂时稳定的脑特征。 DMN/ECN中的BEN可以提供一种方法来衡量潜在功能储备，从而赋予更好的大脑功能，并可以通过教育增强。
The human brain exhibits large-scale spontaneous fluctuations that account for most of its total energy metabolism. Independent of any overt function, this immense ongoing activity likely creates or maintains a potential functional brain reserve to facilitate normal brain function. An important property of spontaneous brain activity is the long-range temporal coherence, which can be characterized by resting state fMRI-based brain entropy mapping (BEN), a relatively new method that has gained increasing research interest. The purpose of this study was to leverage the large resting state fMRI and behavioral data publicly available from the human connectome project to address three important but still unknown questions: temporal stability of rsfMRI-derived BEN; the relationship of resting BEN to latent functional reserve; associations of resting BEN to neurocognition. Our results showed that rsfMRI-derived BEN was highly stable across time; resting BEN in the default mode network (DMN) and executive control network (ECN) was related to brain reserve in a negative correlation to education years; and lower DMN/ECN BEN corresponds to higher fluid intelligence and better task performance. These results suggest that resting BEN is a temporally stable brain trait; BEN in DMN/ECN may provide a means to measure the latent functional reserve that bestows better brain functionality and may be enhanced by education.
