Resting-state "physiological networks"
Resting-state "physiological networks"
复制标题
DOI：
10.1016/j.neuroimage.2020.116707
复制
发表时间：
2020-06-01
期刊：
影响因子：
5.7
通讯作者：
Polimeni, Jonathan R.
中科院分区：
文献类型：
--
作者：
Chen, Jingyuan E.;Lewis, Laura D.;Polimeni, Jonathan R.
系统性脑生理的缓慢变化可以引起fMRI时间序列的大幅波动，表现为遥远脑区之间时间相关性的结构化空间模式。在这里，我们调查是否这样的“生理网络”-组隔离的大脑区域，表现出类似的反应后，缓慢的变化，在全身生理-类似的模式与大规模的网络通常归因于远程同步神经元活动。通过分析来自3 T人类连接组计划（HCP）数据库的一大组受试者，我们证明了与呼吸变化或心率变化紧密相关的全脑和明显的异质动力学。我们表明，使用合成的数据产生的生理记录跨学科，这些生理耦合的波动单独可以产生的网络，强烈类似于以前报道的静息态网络，这表明，在某些情况下，“生理网络”似乎模仿神经网络。此外，我们表明，这种生理相关的连接估计似乎占主导地位的整体连接观察在多个HCP科目，这种明显的“生理连接”不能被删除的使用一个单一的滋扰回归为整个大脑（如全球信号回归），由于明确的区域异质性的生理耦合响应。我们的研究结果挑战了以前的概念，即生理混淆要么局限于大静脉，要么在整个皮层中具有全局连贯性，因此强调了在基于fMRI的功能连接研究中考虑潜在生理贡献的必要性。这种“生理”动力学所携带的丰富的时空模式也表明了与大规模神经网络互补的临床生物标志物的巨大潜力。
Slow changes in systemic brain physiology can elicit large fluctuations in fMRI time series, which manifest as structured spatial patterns of temporal correlations between distant brain regions. Here, we investigated whether such "physiological networks"-sets of segregated brain regions that exhibit similar responses following slow changes in systemic physiology-resemble patterns associated with large-scale networks typically attributed to remotely synchronized neuronal activity. By analyzing a large group of subjects from the 3T Human Connectome Project (HCP) database, we demonstrate brain-wide and noticeably heterogenous dynamics tightly coupled to either respiratory variation or heart rate changes. We show, using synthesized data generated from physiological recordings across subjects, that these physiologically-coupled fluctuations alone can produce networks that strongly resemble previously reported resting-state networks, suggesting that, in some cases, the "physiological networks" seem to mimic the neuronal networks. Further, we show that such physiologically-relevant connectivity estimates appear to dominate the overall connectivity observations in multiple HCP subjects, and that this apparent "physiological connectivity" cannot be removed by the use of a single nuisance regressor for the entire brain (such as global signal regression) due to the clear regional heterogeneity of the physiologically-coupled responses. Our results challenge previous notions that physiological confounds are either localized to large veins or globally coherent across the cortex, therefore emphasizing the necessity to consider potential physiological contributions in fMRI-based functional connectivity studies. The rich spatiotemporal patterns carried by such "physiological" dynamics also suggest great potential for clinical biomarkers that are complementary to large-scale neuronal networks.