Abstract
Visual-motor task processing relies on neurovascular coupling (NVC), a neuro-hemodynamic interaction phenomenon. The brain's short-term effects following visual-motor tasks and the underlying mechanisms remain largely unexplored. We developed a novel NVC-based dynamical model comprising multiple topologically coupled node units with intrinsic heterogeneity. Each node integrates a reverse neural mass model (RNMM) and a metabolic-hemodynamic model (MHM), interconnected via biophysically meaningful network connectivity matrix to enable cross-node interactions. The results show that, first, the model accurately replicated dynamic signatures during pre- and post-visual-motor task conditions, elucidating the NVC-mediated mechanism. Second, sustained elevation of transient metabolic-hemodynamic effects was observed in task-relevant regions (e.g., cuneus) post-task execution. Third, these short-term dynamical effects were jointly driven by NVC mechanisms and excitatory-inhibitory (E-I) balance regulation. In conclusion, our dynamical modeling approach elucidates the short-term effects jointly mediated by multiple mechanisms following visual-motor tasks, providing novel methodological and theoretical insights for understanding the cognitive mechanisms of brain function. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11571-025-10351-w.