Computational Modeling of Neurovascular Coupling Dysfunction in Early Silent Cerebral Small Vessel Disease: A Proof-of-Concept Study

Background: Silent cerebral small vessel disease (sCSVD) is a major contributor to cognitive decline and stroke, often progressing undetected due to the lack of early functional biomarkers.Structural imaging lags behind the underlying pathophysiology.Neurovascular coupling (NVC) dysfunction may precede visible lesions, but noninvasive detection remains elusive. Methods:We conducted a computational proof-of-concept study using simulated blood-oxygen-level-dependent (BOLD) fMRI and arterial spin labeling (ASL) perfusion data based on literature-derived physiological parameters.Two synthetic cohorts (sCSVD and healthy controls, n=100 each) were modeled to assess hemodynamic response characteristics and cortical perfusion.These metrics were further correlated with simulated cognitive scores (MoCA), and a computational NVC index was mapped across gradients of white matter lesion burden and vascular delay. Results:The sCSVD group demonstrated significantly delayed BOLD responses (mean delay 6.1 s vs. 4.9 s, p < 0.001), reduced amplitude (0.42% vs. 0.61%, p < 0.01), and lower frontal cortical perfusion (27.4 vs. 39.2 mL/100g/min).Perfusion correlated with MoCA scores (r = 0.41).The simulated NVC index declined with increased lesion volume and vascular delay, co-localizing with hypoperfused regions. Conclusion:Our findings suggest that early neurovascular uncoupling may serve as a functional biomarker in preclinical sCSVD.This simulation framework offers a translational platform for hypothesis generation, noninvasive biomarker exploration, and virtual testing of early interventions.