Increased segregation of functional networks in developing brains.

Area of Science:

• Neuroscience
• Developmental Neuroscience
• Network Science

Background:

• Typical brain development is increasingly understood through a network perspective.
• Significant gaps exist in understanding functional brain network development in preschool-aged children due to neuroimaging challenges.

Purpose of the Study:

• To investigate the typical development of functional brain networks in preschool children (ages 4-6) and compare them to older children and adults.
• To elucidate the neurophysiological mechanisms underlying functional brain maturation during early childhood.

Main Methods:

• Magnetoencephalography (MEG) recorded resting-state brain oscillatory activity in 24 children (14 preschool, 10 school-aged) and 24 adults.
• Minimum Spanning Tree (MST) topology, derived from phase synchrony of beamformer-reconstructed time-series, analyzed functional brain network organization.
• Compared network topology across age groups (preschool, school-aged, adult).

Main Results:

• Functional brain networks transition from a star-like (centralized) to a line-like (decentralized) topology with age, indicating increased segregation.
• Network segregation is frequency-independent and associated with decreased centrality in cortical regions, particularly the default mode network.
• A heuristic MST model illustrates a developmental trajectory for complex brain network emergence.

Conclusions:

• Childhood functional brain networks undergo significant topological reorganization, becoming more segregated with age.
• This study reveals key neurophysiological changes in brain maturation during the critical preschool period.
• Findings provide insights into the developmental trajectory of complex brain network organization.