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.
Download Full PDF Version (Non-Commercial Use)