Depth-Dependent Contributions of Various Vascular Zones to Cerebral Autoregulation and Functional; Hyperemia: An In-Silico Analysis

Autoregulation and neurogliavascular coupling are key mechanisms that modulate myogenic tone (MT) in vessels to regulate cerebral blood flow (CBF) during resting state and periods of increased neural activity, respectively. To determine relative contributions of distinct vascular zones across different cortical depths in CBF regulation, we developed a simplified yet detailed and computationally efficient model of the mouse cerebrovasculature. The model integrates multiple simplifications and generalizations regarding vascular morphology, the hierarchical organization of mural cells, and potentiation/inhibition of MT in vessels. Our analysis showed that autoregulation is the result of the synergy between these factors, but achieving an optimal balance across all cortical depths and throughout the autoregulation range is a complex task. This complexity explains the non-uniformity observed experimentally in capillary blood flow at different cortical depths. In silico simulations of cerebral autoregulation support the idea that the cerebral vasculature does not maintain a plateau of blood flow throughout the autoregulatory range and consists of both flat and sloped phases. We learned that small-diameter vessels with large contractility, such as penetrating arterioles and precapillary arterioles, have major control over intravascular pressure at the entry points of capillaries and play a significant role in CBF regulation. However, temporal alterations in capillary diameter contribute moderately to cerebral autoregulation and minimally to functional hyperemia. In addition, hemodynamic analysis shows that while hemodynamics within capillaries remain relatively stable across all cortical depths throughout the entire autoregulation range, significant variability in hemodynamics can be observed within the first few branch orders of precapillary arterioles or transitional zone vessels. The computationally efficient cerebrovasculature model, proposed in this study, provides a novel framework for analyzing dynamics of the CBF regulation where hemodynamic and vasodynamic interactions are the foundation on which more sophisticated models can be developed. Author summaryBlood vessels dynamically adapt to the mechanical forces exerted by circulating blood. Appropriate adaptive responses to changes in mechanical force are central to the optimal functioning of the cerebral blood flow (CBF) regulatory system, and include processes such as cerebral autoregulation, vasomotion, and neurogliovascular coupling. This adaptation is driven by intercellular interactions, primarily modulated by factors such as vessel wall tension, shear stress, and strain. As our understanding of the biophysicochemical principles of CBF regulatory system has advanced, computational studies have become more detailed and sophisticated, providing practical in-silico environments to investigate its dynamics and gain insight into the underlying biology. In this study, I propose a method to create a computationally efficient platform where the interactions of hemodynamics with vessel segments can be modeled and studied in an in-silico setting. This method can lay the groundwork for more sophisticated computational studies of the CBF regulatory system, where hemodynamics are core elements of the system operation and the model can represent a more realistic version of this system.