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Updated: Jan 31, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
Published on: October 13, 2023
Biological substrates of structure-function coupling in brain networks
Panagiotis Fotiadis1, Amy F T Arnsten2, Linden Parkes3
1Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA; Department of Anesthesiology, University of Michigan, Ann Arbor, MI, USA.
None:
In this review, we draw insight from the fields of neurobiology and computational neuroscience to address a fundamental question: Why does the correlation between structural and functional connectivity vary across the human cortex? We begin by summarizing empirical studies that reveal the heterogeneous expression of structure-function coupling across brain regions and among individuals. We then identify potential biological factors that mediate this variability, focusing on the roles of evolution, myeloarchitecture, cytoarchitecture, and neuromodulation in sculpting the dynamic and diverse structure-function landscape of the human cortex. We next turn to computational modeling to deepen our understanding of the relationship between a system's structural architecture and functional expression. We investigate biologically inspired computational models that map structure to function in human brain networks, paying special attention to studies that simulate external perturbations and structural lesions, and discuss the insights these approaches offer into the causal mechanisms governing the heterogeneous interplay between structural and functional connectivity. We close with a discussion of future directions, emphasizing efforts to bridge neurobiology and computational modeling to design biologically accurate, individualized models of the human brain. In particular, we highlight the potential of multi-layered networks informed by individual-specific microstructural and neuromodulatory gradients and governed by non-linear dynamics as a particularly fruitful direction. Such personalized models accounting for the synergistic effects of biological gradients could be experimentally validated to assess their predictive efficacy, ultimately bringing us one step closer to non-invasive, connectome-based clinical treatments tailored to the individual.
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