Decoding Cortical Activity through Neuronal Tracing Connectome-Harmonics in Marmosets

Abstract Deciphering the complex relationship between neuroanatomical connections and functional activity in primate brains remains a daunting task, especially regarding the influence of monosynaptic connectivity on cortical activity. In this study, we utilized graph signal processing to study the anatomical-functional relationship and decomposed the neuronal-tracing based connectome of marmoset brains into a series of harmonics. These connectomic harmonics effectively decoded cortical activity observed in resting-state functional magnetic resonance imaging, and exposed a patterned cellular-functional dependency. This pattern revealed a spatial gradient from coupled unimodal to decoupled transmodal cortices, and recapitulated the hierarchical organization of cortical structures across both micro-structural and macro-scale spatial properties. Notably, these marmoset-derived harmonics facilitated the inference of human cortical activity and connectivity, underlining the potential of generalizing the connectomic constraints across species. Our findings illuminate how neuronal-tracing connectome harmonics constrain cortical activity and improve our understanding of the brain’s anatomical-functional relationship.