C. O. Tan: CVLab, SW052, Spaulding Hospital Cambridge, 1575 Cambridge Street, Cambridge, MA 02138, USA.
Exp Physiol. 2014 Jan;99(1):3-15. doi: 10.1113/expphysiol.2013.072355. Epub 2013 Oct 4.
The brain requires steady delivery of oxygen and glucose, without which neurodegeneration occurs within minutes. Thus, the ability of the cerebral vasculature to maintain relatively steady blood flow in the face of changing systemic pressure, i.e. cerebral autoregulation, is critical to neurophysiological health. Although the study of autoregulation dates to the early 20th century, only the recent availability of cerebral blood flow measures with high temporal resolution has allowed rapid, beat-by-beat measurements to explore the characteristics and mechanisms of autoregulation. These explorations have been further enhanced by the ability to apply sophisticated computational approaches that exploit the large amounts of data that can be acquired. These advances have led to unique insights. For example, recent studies have revealed characteristic time scales wherein cerebral autoregulation is most active, as well as specific regions wherein autonomic mechanisms are prepotent. However, given that effective cerebral autoregulation against pressure fluctuations results in relatively unchanging flow despite changing pressure, estimating the pressure-flow relationship can be limited by the error inherent in computational models of autoregulatory function. This review focuses on the autonomic neural control of the cerebral vasculature in health and disease from an integrative physiological perspective. It also provides a critical overview of the current analytical approaches to understand cerebral autoregulation.
大脑需要稳定的氧气和葡萄糖供应，否则神经退行性病变会在数分钟内发生。因此，脑血管在面对全身血压变化时保持相对稳定血流的能力（即脑自动调节）对神经生理健康至关重要。尽管自动调节的研究可以追溯到 20 世纪初，但只有最近能够以高时间分辨率测量脑血流，才能够进行快速的逐拍测量，以探索自动调节的特征和机制。这些探索进一步得益于应用复杂计算方法的能力，这些方法利用了可以获取的大量数据。这些进展带来了独特的见解。例如，最近的研究揭示了脑自动调节最活跃的特征时间尺度，以及自主机制占优势的特定区域。然而，由于有效的针对压力波动的脑自动调节会导致尽管压力变化但流量相对不变，因此，估计压力-流量关系可能会受到自动调节功能计算模型固有的误差限制。这篇综述从综合生理学的角度关注健康和疾病状态下脑血管的自主神经控制。它还批判性地概述了目前用于理解脑自动调节的分析方法。
