Complex visual cognitive function based on a large-scale neurovascular and metabolic coupling mechanisms model in whole brain

The neurovascular and metabolic coupling (NVMC) mechanism constitutes a critical physiological foundation for visual information processing. However, multimodal studies remain confined to phenomenological descriptions and fail to provide deeper theoretical investigations, preventing precise assessment of individuals. To address these limitations, we developed a heterogeneous whole-brain computational model of NVMC that integrates task-based EEG-MRI-fMRI multimodal data to simulate the cascading processes from neural mass firing to metabolic-hemodynamic responses. The model was validated against 33 resting-state simultaneous EEG-fMRI datasets. It was found that at the regional level, the fusiform exhibited stronger functional connectivity associated with face recognition, and its NVMC (CBF/FCS) demonstrated statistically significant differences between face stimuli (famous and unfamiliar faces) and scrambled faces (P < 0.001). Whole brain level analyses revealed reduced NVMC (CBF-FCS) with increasing face regularity and familiarity, despite nonsignificant differences in network indices. Subnetwork-level investigations further identified pronounced heterogeneity in functional interactions across distinct neural circuits. In this study, we developed a whole-brain-scale computational model to investigate the heterogeneity of NVMC during face-specific stimulus processing. The model provides an interpretable computational framework for enabling personalized assessments of visual cognitive tasks.