4.6 Article

Functional Brain Connectivity Develops Rapidly Around Term Age and Changes Between Vigilance States in the Human Newborn

期刊

CEREBRAL CORTEX
卷 26, 期 12, 页码 4540-4550

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/cercor/bhv219

关键词

early brain development; neonatal EEG; nestedness; neurodevelopment; resting-state networks

资金

  1. Academy of Finland [276523, 288220]
  2. Sigrid Juselius Foundation
  3. Finnish Cultural Foundation [00140992]
  4. Paivikki ja Sakari Sohlberg Foundation
  5. Helsinki University Hospital
  6. Academy of Finland (AKA) [276523, 276523] Funding Source: Academy of Finland (AKA)

向作者/读者索取更多资源

Large-scale coupling in neuronal activity is essential in all cognitive functions, but its emergence and functional correlates are poorly known in the human newborn. This study aimed to characterize functional connectivity in the healthy human newborn, and to identify the changes in connectivity related to vigilance states and to maturation during the early postnatal weeks. We recorded active and quiet sleep of 38 sleeping newborn babies using multichannel electroencephalography (EEG) at 2 neonatal time points. Functional connectivity between brain areas was quantified with 3 different metrics: phase-phase correlations, amplitude-amplitude correlations (AACs), and phase-amplitude correlations. All functional connectivity measures changed significantly between vigilance states and matured rapidly after normal birth. The observed changes were frequency-specific, most salient in AAC coupling, and their development was compatible with the known development of structural cortico-cortical connectivity. The present findings support the view that emerging functional connectivity exhibits fundamental differences between sleep states months before the onset of genuine EEG signatures of sleep states. Moreover, our findings also support the idea that early cortical events entail different mechanisms of functional coupling needed to provide endogenous guidance for early activity-dependent development of brain networks.

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