A statistical 3D model of the human cortical vasculature to compute the hemodynamic fingerprint of the BOLD fMRI signal

Abstract

BOLD fMRI is a commonly used technique to map brain activity; nevertheless, BOLD fMRI is an indirect measurement of brain function triggered by neurometabolic and neurovascular coupling. Hence, the origin of the BOLD fMRI signal is quite complex, and the signal formation depends, among others, on the geometry of the cortical vasculature and the associated hemodynamic behavior. To characterize and quantify the hemodynamic contributions to the BOLD signal response in humans, it is necessary to adopt a computational model that resembles the human cortical vascular architecture and mimics realistic hemodynamic changes. To this end, we have developed a statistically defined 3D vascular model that resembles the human cortical vasculature. Using this model, we simulated hemodynamic changes triggered by a neuronal activation and local magnetic field disturbances created by the vascular topology and the blood oxygenation changes. The proposed model considers also the biophysical interactions and the intrinsic magnetic properties of the nearby tissue in order to compute a dynamic BOLD fMRI signal response. This computational pipeline results in an integrated biophysical model that can provide a better insight on the understanding and quantification of the hemodynamic fingerprint of the BOLD fMRI signal evolution.