From microscopy data to hemodynamic simulations: a vascular graph approach to understand the fMRI signal formation

Motivation: Understanding the impact of cortical vascular architecture on the spatiotemporal features of hemodynamic responses. Goal(s): Automatic extraction of realistic cortical vasculature models from microscopy data, and simulation of hemodynamic changes across the extracted vascular network. Approach: We present a pipeline that utilizes graph theory for extracting the vasculature from microscopy data, representing it as a vascular graph. Simulations were performed using the extracted vascular graphs by converting the connectivity matrix into a dynamic system modeled by RC circuits. Results: We extracted two realistic vascular graphs and used them to mimic hemodynamic changes resulting from simulated arterial dilation. Impact: Vascular graphs extracted by the developed pipeline could serve to simulate hemodynamic changes across the cortical vasculature. This provides a tool to enhance fMRI signal interpretation and provide valuable insights into the role of vascular dysfunction in cerebrovascular diseases.