Systems biology analysis of vasodynamics in mouse cerebral arterioles during resting state and functional hyperemia

Abstract

Cerebral hemodynamics is tightly regulated by arteriolar vasodynamics. In this study, a systems biology approach was employed to investigate how the interplay between passive, myogenic, neurogenic, and astrocytic responses shapes arteriolar vasodynamics in small rodents. A model of neurovascular coupling is proposed in which neurons inhibit and dampen the myogenic response to promote vasodilation during activation, and facilitate the myogenic response to promote rapid vasoconstriction immediately post-activation. In this model, inhibition of the myogenic response is mediated by the hyperpolarization of smooth muscle and endothelial cells. Dampening and facilitation of the response are mediated by neuronal production of nitric oxide and release of neuropeptide Y, respectively. We also introduce a model for gliovascular coupling, in which astrocytes periodically inhibit the myogenic response upon detecting an increase in myogenic activity through interactions between their endfeet and arterioles. Our study revealed that in the resting state, the interplay between the delayed myogenic response and passive distension, acting as negative and positive feedbacks respectively, generates undamped oscillations in vessel diameter, known as vasomotion. In the active state, these oscillations are disrupted by the neurogenic and astrocytic responses. The biophysical model of arteriolar vasodynamics presented in this study lays the foundation for quantitative analysis of cerebral hemodynamics for cerebrovascular health diagnostics and hemodynamic neuroimaging. Author summaryCerebral hemodynamic imaging is widely used to investigate brain function in-vivo. These signals are primarily shaped by arteriolar vasodynamics, which result from a combination of physiological processes mediated by multiple interacting cell types. A biophysical model of this dynamics offers a valuable computational framework for achieving more accurate and quantitative interpretation of hemodynamic signals. In this study, I applied a computational biology approach to incorporate several well-established cellular signaling pathways into a unified model, which was used to investigate system-level arteriolar behavior and identify missing or less understood mechanisms involved in cerebral blood flow regulation. Our results show that arteriolar vasodynamics is not solely driven by neurogenic responses; astrocytic response and hemo-vascular interactions also play important roles in shaping the observed dynamics. The model also provided a means to explore how in-silico analysis of hemodynamic signals can reveal potential cellular-level impairments that manifest as system-level changes in cerebral hemodynamics. Incorporating our proposed biophysical model into cerebral hemodynamic analysis can improve the fidelity of hemodynamic imaging--enabling more accurate inference of regional neuronal and astrocytic activity from hemodynamic signals, and enhancing our ability to diagnose cerebrovascular pathologies.