Brainstem and Deep Gray Nuclei Modulate Brain Network Efficiency in Low-risk Term Newborns.

Area of Science:

• Neuroscience
• Developmental Neuroscience
• Brain Network Analysis

Background:

• Network analysis of source electroencephalography (EEG) in newborns identifies critical hub regions for information transfer.
• The impact of removing these hubs on overall brain network efficiency remains unclear.

Purpose of the Study:

• To investigate how the removal of specific hub regions affects brain network efficiency in low-risk term newborns.
• To identify critical hubs whose removal significantly diminishes network function.

Main Methods:

• Resting-state 124-channel high-density electroencephalography (HD-EEG) data were collected from newborns within 72 hours of birth.
• Functional connectivity matrices were constructed using source EEG data in the delta band.
• Small-World Propensity (SWP) was calculated after individually and simultaneously removing identified hub regions.

Main Results:

• Removing individual hubs, specifically the right caudate, left thalamus, right thalamus, and brainstem, significantly reduced SWP (P < 0.05).
• Simultaneous removal of these four hubs also resulted in a significant decrease in SWP.
• These findings demonstrate reduced network efficiency following the removal of key hubs.

Conclusions:

• Specific hub regions play a critical role in maintaining functional brain network efficiency in low-risk term newborns.
• The removal of these identified hubs leads to diminished network efficiency, underscoring their importance in early brain development.