title: The effects of maturation on early and late phases of phrenic neurogram during eupnea.
abstract: In this paper, we investigate the effects of maturation on the early and late phases of the phrenic neurogram. We have used the matching pursuit (MP) method to examine the effects of maturation on breathing patterns in both time and frequency domains. The MP was chosen since the wavelet transform method may not represent signals whose Fourier transforms have a narrow high-frequency support. The phrenic neurogram was recorded from 25 piglets (3-35 days) during eupnea (normal breathing) at three postnatal age groups: young (3-7 days (n = 9)), (middle) 10-21 days (n = 6), and old (29-35 days (n = 10)). The energy percentage of atoms representing the nonperiodic neural activities (NPNAs) significantly decreased from young age to middle age groups (p<0.01) and from young age to old age groups (p<0.01), and from middle age to old age groups (p<0.055) in the early phase (the first half) of the phrenic neurogram, but these changes were not statistically significant in the late phase (the second half) of the phrenic neurogram as maturation proceeded. However, the energy percentage of atoms representing the periodic neural activities (PNAs) decreased with maturation, but these changes were not statistically significant in the early phase of the phrenic neurogram. The energy percentage of (PNAs) increased in the late phase of the phrenic neurogram as maturation proceeded although these changes were only significant between young and old age groups (p<0.01). These results suggest that the significant decrease of the NPNAs in the early phase and the increase in the late phase of the phrenic neurogram could be a sign of maturation in piglets.
authors.affiliation: Thayer School of Engineering, Dartmouth College, Hanover, NH 03755-8000, USA. metin.akay@dartmouth.edu
authors.forename: Metin
authors.initials: M
authors.lastname: Akay
authors.forename: Masaki
authors.initials: M
authors.lastname: Sekine
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000367:Age Factors; D000375:Aging / Q000502:physiology*; D000465:Algorithms; D000818:Animals; D000831:Animals, Newborn; D001683:Biological Clocks / Q000502:physiology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004576:Electromyography / Q000379:methods*; D005260:Female; D008297:Male; D009046:Motor Neurons / Q000502:physiology; D010363:Pattern Recognition, Automated / Q000379:methods; D010507:Periodicity; D010791:Phrenic Nerve / Q000502:physiology*; D012119:Respiration; D013552:Swine