Network-specific selectivity of functional connections in the neonatal brain

Chad M. Sylvester, Sydney Kaplan, Michael J. Myers, Evan M. Gordon, Rebecca F. Schwarzlose, Dimitrios Alexopoulos, Ashley N. Nielsen, Jeanette K. Kenley, Dominique Meyer, Qiongru Yu, Alice M. Graham, Damien A. Fair, Barbara B. Warner, Deanna M. Barch, Cynthia E. Rogers, Joan L. Luby, Steven E. Petersen, Christopher D. Smyser

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

The adult human brain is organized into functional brain networks, groups of functionally connected segregated brain regions. A key feature of adult functional networks is long-range selectivity, the property that spatially distant regions from the same network have higher functional connectivity than spatially distant regions from different networks. Although it is critical to establish the status of functional networks and long-range selectivity during the neonatal period as a foundation for typical and atypical brain development, prior work in this area has been mixed. Although some studies report distributed adult-like networks, other studies suggest that neonatal networks are immature and consist primarily of spatially isolated regions. Using a large sample of neonates (n = 262), we demonstrate that neonates have long-range selective functional connections for the default mode, fronto-parietal, and dorsal attention networks. An adult-like pattern of functional brain networks is evident in neonates when network-detection algorithms are tuned to these long-range connections, when using surface-based registration (versus volume-based registration), and as per-subject data quantity increases. These results help clarify factors that have led to prior mixed results, establish that key adult-like functional network features are evident in neonates, and provide a foundation for studies of typical and atypical brain development.

Original languageEnglish (US)
Pages (from-to)2200-2214
Number of pages15
JournalCerebral Cortex
Volume33
Issue number5
DOIs
StatePublished - Mar 1 2023

Bibliographical note

Publisher Copyright:
© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: [email protected].

Keywords

  • fMRI
  • functional connectivity
  • infant
  • neonate
  • networks

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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