Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets

Jie Xia, Cirong Liu, Jiao Li, Yao Meng, Siqi Yang, Huafu Chen () and Wei Liao ()
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Jie Xia: University of Electronic Science and Technology of China
Cirong Liu: Chinese Academy of Sciences
Jiao Li: University of Electronic Science and Technology of China
Yao Meng: University of Electronic Science and Technology of China
Siqi Yang: Chengdu University of Information Technology
Huafu Chen: University of Electronic Science and Technology of China
Wei Liao: University of Electronic Science and Technology of China

Nature Communications, 2024, vol. 15, issue 1, 1-13

Abstract: 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. Here, we investigate the anatomical-functional relationship and decompose the neuronal-tracing connectome of marmoset brains into a series of eigenmodes using graph signal processing. These cellular connectome eigenmodes effectively constrain the cortical activity derived from resting-state functional MRI, and uncover a patterned cellular-functional decoupling. This pattern reveals a spatial gradient from coupled dorsal-posterior to decoupled ventral-anterior cortices, and recapitulates micro-structural profiles and macro-scale hierarchical cortical organization. Notably, these marmoset-derived eigenmodes may facilitate the inference of spontaneous cortical activity and functional connectivity of homologous areas in humans, highlighting the potential generalizing of the connectomic constraints across species. Collectively, our findings illuminate how neuronal-tracing connectome eigenmodes constrain cortical activity and improve our understanding of the brain’s anatomical-functional relationship.

Date: 2024
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DOI: 10.1038/s41467-024-46651-8

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