Network-level structure-function relationships in human neocortex

Bratislav Miŝic, Richard F. Betzel, Marcel A. De Reus, Martijn P. Van Den Heuvel, Marc G. Berman, Anthony R. McIntosh, Olaf Sporns

Research output: Contribution to journalArticlepeer-review

208 Scopus citations

Abstract

The dynamics of spontaneous fluctuations in neural activity are shaped by underlying patterns of anatomical connectivity. While numerous studies have demonstrated edge-wise correspondence between structural and functional connections, much less is known about how large-scale coherent functional network patterns emerge from the topology of structural networks. In the present study, we deploy a multivariate statistical technique, partial least squares, to investigate the association between spatially extended structural networks and functional networks. We find multiple statistically robust patterns, reflecting reliable combinations of structural and functional subnetworks that are optimally associated with one another. Importantly, these patterns generally do not show a one-to-one correspondence between structural and functional edges, but are instead distributed and heterogeneous, with many functional relationships arising from nonoverlapping sets of anatomical connections.We also find that structural connections between high-degree hubs are disproportionately represented, suggesting that these connections are particularly important in establishing coherent functional networks. Altogether, these results demonstrate that the network organization of the cerebral cortex supports the emergence of diverse functional network configurations that often diverge from the underlying anatomical substrate.

Original languageEnglish (US)
Pages (from-to)3285-3296
Number of pages12
JournalCerebral Cortex
Volume26
Issue number7
DOIs
StatePublished - Jul 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The Author 2016.

Keywords

  • Connectome
  • Multivariate
  • Network
  • Partial least squares

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