Linking Structure and Function in Macroscale Brain Networks
Structure–function relationships are a fundamental principle of many naturally occurring systems. However, network neuroscience research suggests that there is an imperfect link between structural connectivity and functional connectivity in the brain. Here, we synthesize the current state of knowled...
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Published in | Trends in cognitive sciences Vol. 24; no. 4; pp. 302 - 315 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
Elsevier Ltd
01.04.2020
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Subjects | |
Online Access | Get full text |
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Summary: | Structure–function relationships are a fundamental principle of many naturally occurring systems. However, network neuroscience research suggests that there is an imperfect link between structural connectivity and functional connectivity in the brain. Here, we synthesize the current state of knowledge linking structure and function in macroscale brain networks and discuss the different types of models used to assess this relationship. We argue that current models do not include the requisite biological detail to completely predict function. Structural network reconstructions enriched with local molecular and cellular metadata, in concert with more nuanced representations of functions and properties, hold great potential for a truly multiscale understanding of the structure–function relationship.
The emergence of network neuroscience allows researchers to quantify the link between the organizational features of neuronal networks and the spectrum of cortical functions.Current models indicate that structure and function are significantly correlated, but the correspondence is not perfect because function reflects complex multisynaptic interactions in structural networks.Function cannot be directly estimated from structure, but must be inferred by models of higher-order interactions. Statistical, communication, and biophysical models have been used to translate brain structure to brain function.Structure–function coupling is regionally heterogeneous and follows molecular, cytoarchitectonic, and functional hierarchies. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 ObjectType-Review-3 content type line 23 |
ISSN: | 1364-6613 1879-307X 1879-307X |
DOI: | 10.1016/j.tics.2020.01.008 |