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.

中文翻译：

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静息状态的“生理网络”

全身大脑生理学的缓慢变化会引起 fMRI 时间序列的大幅波动，表现为远处大脑区域之间时间相关性的结构化空间模式。在这里，我们调查了这种“生理网络”——一组在系统生理学缓慢变化后表现出类似反应的隔离大脑区域——是否与通常归因于远程同步神经元活动的大规模网络相关联的模式相似。通过分析来自 3T 人类连接组计划 (HCP) 数据库的大量受试者，我们展示了与呼吸变化或心率变化紧密耦合的全脑和明显异质的动态。我们显示，使用从跨受试者的生理记录生成的合成数据，仅这些生理耦合的波动就可以产生与先前报道的静息状态网络非常相似的网络，这表明在某些情况下，“生理网络”似乎模仿了神经元网络。此外，我们表明，这种与生理相关的连接估计似乎在多个 HCP 受试者的整体连接观察中占主导地位，并且无法通过对整个大脑使用单个令人讨厌的回归器（例如全局）来消除这种明显的“生理连接”。信号回归）由于生理耦合反应的明显区域异质性。我们的结果挑战了先前的观点，即生理混淆要么位于大静脉，要么在整个皮层全局一致，因此强调有必要在基于 fMRI 的功能连接研究中考虑潜在的生理贡献。这种“生理”动力学所携带的丰富时空模式也表明临床生物标志物的巨大潜力，这些生物标志物与大规模神经元网络互补。