Quantitative electroencephalogram in term neonates under different sleep states.

Area of Science:

• Neuroscience
• Neonatal Medicine
• Signal Processing

Background:

• Electroencephalogram (EEG) assesses consciousness, but interpretation is complex in neonates due to rapid developmental changes.
• Quantitative EEG (QEEG) offers a processed EEG analysis, yet normative data for healthy neonates across different states are limited.
• Establishing baseline QEEG ranges is crucial for monitoring sedation or anesthesia effects in neonates.

Purpose of the Study:

• To determine the range of QEEG parameters in healthy neonates during awake, active sleep, and quiet sleep states.
• To identify which QEEG metrics best discriminate between these three states of consciousness.
• To provide normative QEEG data for neonatal brain activity assessment.

Main Methods:

• Analyzed EEG data from 37-46 week gestational age healthy neonates, classifying states as awake, active sleep, or quiet sleep.
• Calculated QEEG parameters including total power, power ratio, coherence, entropy, and spectral edge frequency (SEF) 50 and 90.
• Utilized descriptive statistics and Receiver Operating Characteristic (ROC) curves to analyze QEEG data and assess discriminatory power.

Main Results:

• Significant QEEG differences were observed between awake and asleep states, but not between active and quiet sleep.
• Entropy beta, delta2 power %, coherence delta2, and SEF50 were most effective in distinguishing awake from active sleep (AUC-ROC ≥ 0.84 for Entropy beta).
• Entropy beta, entropy delta1, theta power %, and SEF50 best differentiated awake from quiet sleep (AUC-ROC ≥ 0.78).

Conclusions:

• Established normative QEEG ranges for healthy neonates across different states of consciousness.
• Entropy beta and SEF50 demonstrated the highest efficacy in differentiating between awake and sleep states.
• QEEG parameters showed limited ability to distinguish between active and quiet sleep states in neonates.