Layer-specific functional gradients uncover intrinsic-network organization and feedback processing

Spontaneous activity in the human cortex is organized along large-scale functional gradients, yet how these macroscale patterns relate to laminar functional architecture remains unclear. Here, we use sub-millimeter, layer-resolved 7T resting-state fMRI to map whole-brain functional connectivity gradients across cortical depth. We represent the cortex as a multilayer network with distinct connectivity profiles for deep, middle, and superficial layers, and derive laminar dissimilarity indices that quantify differences between layer-wise gradient embeddings within and across regions. These indices systematically distinguish canonical resting-state networks and vary along a histology-informed microstructural axis that captures a canonical sensory-to-limbic gradient of cytoarchitectural differentiation. Layer-specific analyses further show that the balance between deep- and superficial-layer dissimilarity tracks a functional hierarchy estimated from independent effective-connectivity modelling, consistent with feedback-like intrinsic connectivity at rest. Together, the results establish laminar gradient-derived indices as a bridge between cortical microstructure, large-scale network organization, and hierarchical information flow in the human cortex.