Abstract
The perception of emotional facial expressions engages widespread cortical networks, extending beyond occipito-temporal visual areas to multiple frontal and perisylvian regions. While the connectivity of the occipito-temporal territories involved in visual processing of faces has been extensively mapped, the frontal and perisylvian pathways, comprising motor, emotional, and cognitive-attentional components, remain less understood. Building on intracranial recordings, electrical stimulation, and cortico-cortical evoked potentials, our previous work identified two frontal-perisylvian clusters: a premotor cluster (constituted by Rolandic operculum and a region between the frontal eye fields and the ventral premotor cortex) supporting motor resonance, and a limbic/prefrontal cluster (composed by prefrontal and cingulate territories) supporting emotional resonance. Here, combining diffusion tractography (DTI) and resting-state fMRI (rsfMRI), we provide a detailed anatomical and functional connectivity framework for these regions. DTI revealed seven principal fiber tracts organizing the clusters into three coherent networks, while rsfMRI demonstrated shared and dissociable connectivity patterns among them partially consistent with Default Mode, Ventral Attention, Dorsal Attention, Frontoparietal, and Sensorimotor networks. The first two networks here identified largely correspond to the limbic/prefrontal and premotor clusters described in our previous study, while the third appears to serve as a nexus between the first two and as a source of visual information for them. These findings outline a tripartite architecture—emotional, premotor, and cognitive networks—through which facial emotion recognition may operates via parallel, functionally specialized streams, enabling both motor and emotional resonance and supporting adaptive social behavior.