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Brain connectome from neuronal morphology

Suhui Jin,Junle Li,Jinhui Wang

Published 2025 in Network Neuroscience

ABSTRACT

Abstract Single-subject morphological brain networks derived from cross-feature correlation of macroscopic MRI-derived morphological measures provide an important means for studying the brain connectome. However, the validity of this approach remains to be confirmed at the microscopic level. Here, we constructed morphological brain networks at the single-cell level by extending features from macroscopic morphological measures to microscopic descriptions of neuronal morphology. We demonstrated the feasibility and generalizability of the method using neurons in the somatosensory cortex of a rat, neurons over the whole brain of a mouse, and neurons in the middle temporal gyrus (MTG) of a human. We found that interneuron morphological similarity was higher for intra- than interclass connections, depended on cytoarchitectonic, chemoarchitectonic, and laminar classification of neurons (rat), differed between regions with different evolutionary timelines (mouse), and correlated with neuronal axonal projections (mouse). Furthermore, highly connected hub neurons were disproportionately from superficial layers (rat), inhibitory neurons (rat), and subcortical regions (mouse), and exhibited unique morphology. Finally, we demonstrated a more segregated, less integrated, and economic network architecture with worse resistance to targeted attacks for neurons in human MTG than neurons in a mouse’s primary visual cortex. Overall, our method provides an alternative avenue to study neuronal wiring diagrams in brains.

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