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Irregularities and power law distributions in the breathing pattern in preterm and term infants

U Frey1, M Silverman, A L Barabási

  • 1Department of Child Health, Leicester University, Leicester LE2 7LX, United Kingdom. urs.frey@insel.ch

Journal of Applied Physiology (Bethesda, Md. : 1985)
|September 8, 1998
PubMed

Insights

Infant breathing irregularities, measured by interbreath intervals (IBI), decrease with maturation. A new exponent, alpha, quantifies breathing stability, linking clinical data to respiratory control neurophysiology.

Area of Science:

  • Neonatal physiology
  • Respiratory control
  • Computational neuroscience

Background:

  • Young infants exhibit unstable respiratory patterns, unlike older children, indicating developmental differences in breathing control.
  • Irregular breathing, including apnea and hypopnea, is common in infants and requires objective measurement for understanding.
  • The neurophysiological basis of infant respiratory control and its maturation remains an area of active research.

Purpose of the Study:

  • To examine irregular breathing patterns in preterm and term infants using interbreath interval (IBI) analysis.
  • To develop a quantitative measure (exponent alpha) of breathing instability and its relationship to maturation.
  • To model infant respiratory control to understand the neurophysiological mechanisms underlying breathing stability.

Main Methods:

  • Measured interbreath intervals (IBI) from abdominal movements during sleep in preterm and term infants.
  • Developed a threshold algorithm to detect breaths, incorporating apneic and hypopneic periods within IBIs.
  • Analyzed the probability density distribution of IBIs using a power law, P(IBI) ~ IBI-alpha, to determine the exponent alpha.

Main Results:

  • The probability density distribution of IBIs followed a power law, P(IBI) ~ IBI-alpha.
  • The exponent alpha increased with postconceptional age, indicating a decrease in prolonged hypopneas (P = 0.002).
  • A computational model based on noisy neural inputs to a respiratory oscillator successfully reproduced the observed IBI properties.

Conclusions:

  • Breathing irregularities in infants can be quantitatively characterized by the exponent alpha.
  • Maturation of infant respiratory control involves tonic inputs moving away from a critical region in the respiratory oscillator model.
  • The exponent alpha provides a link between clinically accessible breathing data and the neurophysiology of infant respiratory control.

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