Hierarchical Complexity of the Macro-Scale Neonatal Brain

Area of Science:

• Neuroscience
• Developmental Neuroscience
• Network Science

Background:

• The human brain exhibits a complex nodal hierarchy with diverse connectivity patterns linked to functional specialization.
• The developmental trajectory of this hierarchical complexity remains largely unexplored.
• Preterm birth is a significant risk factor for atypical brain development and neurocognitive deficits.

Purpose of the Study:

• To establish the presence of hierarchical tiers and complexity in newborn brain networks.
• To compare neonatal hierarchical complexity with that of adult structural connectomes.
• To investigate the impact of preterm birth on brain network hierarchical complexity.

Main Methods:

• Analysis of structural connectomes in neonates and adults.
• Quantification of hierarchical network properties.
• Comparison of network complexity between term-born and preterm infants.

Main Results:

• Both neonatal and adult structural connectomes demonstrate distinct hierarchical tiers.
• Hierarchical complexity is significantly higher in term-born neonates compared to preterm infants.
• The highest tier (hub regions) shows ordered, homogeneous connectivity in both neonates and adults, while intermediate tiers exhibit greater diversity in term-born neonates.

Conclusions:

• The brain develops a rigid structure in hub regions early on, facilitating specialization in lower-level regions.
• Connectivity supporting functional diversity in intermediate brain network tiers is less mature in preterm infants.
• Findings suggest that preterm birth may disrupt the typical development of brain network complexity, impacting sensorimotor and cognitive integration.