Precision fMRI reveals densely interdigitated network patches with conserved motifs in the lateral prefrontal cortex

Dominant models of human lateral prefrontal cortex (LPFC) organization emphasize broad domain-general zones and smooth functional gradients. However, these models rely on group-averaged neuroimaging, which can obscure fine-scale cortical features in highly inter-individually variable regions such as the LPFC. To address this limitation, we collected a new precision fMRI dataset from 10 individuals, each with approximately 2 h of resting-state fMRI and 6 h of task fMRI data. We mapped individual-specific LPFC networks using resting-state data and tested network-level functional preferences using task data. We found that individual LPFC networks showed fragmented and interdigitated organization compared to the group-averaged networks, including novel conserved motifs present across individuals. Task fMRI revealed that distinct yet adjacent networks support domain-specific processes (i.e., language, social cognition, and episodic projection) versus domain-general cognitive control. Sharp functional boundaries were visible at the individual level that could not be observed in group data. These findings uncover previously hidden fine-scale organizational principles present in the LPFC.