Panerai Ronney B
Medical Physics Group, Department of Cardiovascular Sciences, University of Leicester, Leicester LE1 5WW, UK.
Philos Trans A Math Phys Eng Sci. 2009 Apr 13;367(1892):1319-36. doi: 10.1098/rsta.2008.0264.
The cerebral circulation shows both structural and functional complexity. For time scales of a few minutes or more, cerebral blood flow (CBF) and other cerebrovascular parameters can be shown to follow a random fractal point process. Some studies, but not all, have also concluded that CBF is non-stationary. System identification techniques have been able to explain a substantial fraction of the CBF variability by applying linear and nonlinear multivariate models with classical determinants of flow (arterial blood pressure, arterial CO(2) and cerebrovascular resistance, CVR) as inputs. These findings raise the hypothesis that fractal behaviour is not inherent to CBF but might be simply transmitted from its determinants. If this is the case, future investigations could focus on the complexity of the residuals or the unexplained variance of CBF. In the low-frequency range (below 0.15 Hz), changes in CVR due to pressure and metabolic autoregulation represent an important contribution to CBF variability. A small body of work suggests that parameters describing cerebral autoregulation can also display complexity, presenting significant variability that might also be non-stationary. Fractal analysis, entropy and other nonlinear techniques have a role to play to shed light on the complexity of cerebral autoregulation.
脑循环表现出结构和功能的复杂性。在几分钟或更长的时间尺度上,脑血流量(CBF)和其他脑血管参数可显示为遵循随机分形点过程。一些研究(但并非全部)还得出结论,CBF是非平稳的。系统识别技术通过应用以血流的经典决定因素(动脉血压、动脉二氧化碳和脑血管阻力,CVR)作为输入的线性和非线性多变量模型,能够解释很大一部分CBF变异性。这些发现提出了一个假设,即分形行为并非CBF所固有,而可能只是从其决定因素传递而来。如果是这样,未来的研究可以集中在残差的复杂性或CBF的 unexplained variance上。在低频范围(低于0.15Hz),由于压力和代谢性自动调节导致的CVR变化是CBF变异性的一个重要贡献。一小部分研究表明,描述脑自动调节的参数也可能表现出复杂性,呈现出显著的变异性,这也可能是非平稳的。分形分析、熵和其他非线性技术在揭示脑自动调节的复杂性方面可以发挥作用。