Cohen Emily, Wong Flora Y, Wallace Euan M, Mockler Joanne C, Odoi Alexsandria, Hollis Samantha, Horne Rosemary S C, Yiallourou Stephanie R
The Ritchie Centre, Hudson Institute of Medical Research and Department of Paediatrics, Monash University, Level 5 Monash Children's Hospital, 246 Clayton Road, Clayton, Victoria 3168, Australia; Department of Neonatology, Wilhelmina Children's Hospital/University Medical Center Utrecht and Utrecht University, PO Box 85090, 3508 AB Utrecht, The Netherlands.
The Ritchie Centre, Hudson Institute of Medical Research and Department of Paediatrics, Monash University, Level 5 Monash Children's Hospital, 246 Clayton Road, Clayton, Victoria 3168, Australia; Monash Newborn, Monash Health, Level 5 Monash Children's Hospital, 246 Clayton Road, Clayton, Victoria 3168, Australia.
Brain Res. 2018 Jan 1;1678:180-186. doi: 10.1016/j.brainres.2017.10.010. Epub 2017 Oct 16.
Power spectral analysis of the electroencephalogram (EEG) is a non-invasive method to examine infant brain maturation. Preterm fetal growth restricted (p-FGR) neonates display an altered EEG power spectrum compared to appropriate-for-gestational-age (AGA) peers, suggesting delayed brain maturation. Longitudinal studies investigating EEG power spectrum maturation in p-FGR infants are lacking, however. We thus aimed to investigate brain maturation using sleep EEG power spectral analysis in p-FGR infants compared to preterm and term AGA controls (p-AGA and t-AGA, respectively). EEG was recorded during spontaneous sleep in 13 p-FGR, 17 p-AGA and 19 t-AGA infants at 1 and 6 months post-term age. Infant sleep states (active and quiet sleep) were scored using standard criteria. Power spectral analysis of a single-channel EEG (C3-M2/C4-M1) was performed using Fast Fourier Transform. The EEG power spectrum was divided into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), sigma (12-14 Hz) and beta (14-30 Hz) frequency bands. Relative (%) powers and the spectral edge frequency were calculated. The spectral edge frequency was significantly higher in p-FGR infants compared to p-AGA controls in quiet sleep at 1 month post-term age (p < .01). This was due to significantly reduced %-delta and significantly increased %-theta, %-alpha and %-beta power (p < .01 for all) compared to p-AGA infants. p-FGR infants also showed significantly increased %-beta power compared to t-AGA infants (p < .05). No group differences were observed in active sleep or at 6 months post-term age. In conclusion, p-FGR infants show altered sleep EEG power spectrum maturation compared to AGA peers. However, changes resolved by 6 months post-term age.
脑电图(EEG)的功率谱分析是一种用于检查婴儿大脑成熟度的非侵入性方法。与孕龄相称(AGA)的同龄人相比,早产胎儿生长受限(p-FGR)新生儿的脑电图功率谱有所改变,这表明大脑成熟延迟。然而,缺乏对p-FGR婴儿脑电图功率谱成熟度的纵向研究。因此,我们旨在通过睡眠脑电图功率谱分析来研究p-FGR婴儿与早产和足月AGA对照组(分别为p-AGA和t-AGA)相比的大脑成熟情况。在足月后1个月和6个月时,对13名p-FGR、17名p-AGA和19名t-AGA婴儿的自发睡眠期间进行脑电图记录。使用标准标准对婴儿睡眠状态(活跃睡眠和安静睡眠)进行评分。使用快速傅里叶变换对单通道脑电图(C3-M2/C4-M1)进行功率谱分析。脑电图功率谱分为δ(0.5-4Hz)、θ(4-8Hz)、α(8-12Hz)、σ(12-14Hz)和β(14-30Hz)频段。计算相对(%)功率和频谱边缘频率。在足月后1个月的安静睡眠中,p-FGR婴儿的频谱边缘频率显著高于p-AGA对照组(p<.01)。这是因为与p-AGA婴儿相比,δ功率百分比显著降低,θ、α和β功率百分比显著增加(所有p<.01)。与t-AGA婴儿相比,p-FGR婴儿的β功率百分比也显著增加(p<.05)。在活跃睡眠或足月后6个月时未观察到组间差异。总之,与AGA同龄人相比,p-FGR婴儿的睡眠脑电图功率谱成熟度发生了改变。然而,这些变化在足月后6个月时消失。