# Discovering dynamic functional networks in the human neonatal brain with electric source imaging

## TL;DR

This study uncovers the existence and organization of dynamic functional networks in the neonatal brain using EEG source imaging, revealing rich topologies, spectral features, and hierarchical temporal dynamics in infants at term age.

## Contribution

It introduces a novel approach to identify and characterize dynamic functional connectivity in the neonatal brain through EEG source estimates, highlighting complex network topologies and temporal organization.

## Key findings

- Identified macro-scale dynamic functional networks in neonatal EEG data.
- Revealed rich topological and spectral properties of infant brain networks.
- Demonstrated hierarchical temporal dynamics and small-world topology in neonatal networks.

## Abstract

When the human brain manifests the birth of organised communication among local and large-scale neuronal populations activity remains undescribed. We report, in resting-state EEG source-estimates of 100 infants at term age, the existence of macro-scale dynamic functional connectivity, which have rich topological organisations, distinct spectral fingerprints and scale-invariance temporal dynamics. These functional networks encompass the default mode, primary sensory-limbic system, thalamo-frontal, thalamo-sensorimotor and visual-limbic system confined in the delta and low-alpha frequency intervals (1-8 Hz). The temporal dynamics of these networks not only are nested within much slower timescale (<0.1 Hz) but also correlated in a hierarchical leading-following organisation. We show that the anatomically constrained richly organised spatial topologies, spectral contents and temporal fluctuations of resting-state networks reflect an established intrinsic dynamic functional connectome in the human brain at term age. The graph theoretical analysis of the spatial architectures of the networks revealed small-world topology and distinct rich-club organisations of interconnected cortical hubs that exhibit rich synchronous dynamics at multiple timescales. The approach opens new avenues to advance our understanding about the early configuration organisation of dynamic networks in the human brain and offers a novel monitoring platform to investigate functional brain network development in sick preterm infants.