Department of Human Development and Quantitative Methodology, University of Maryland, 3304 Benjamin Building, College Park, MD 20742, USA.
Department of Psychology, University of Southern California, USA.
Neuroimage. 2023 Apr 1;269:119925. doi: 10.1016/j.neuroimage.2023.119925. Epub 2023 Feb 3.
Age-related structural and functional changes that occur during brain development are critical for cortical development and functioning. Previous electroencephalography (EEG) and magnetoencephalography (MEG) studies have highlighted the utility of power spectra analyses and have uncovered age-related trends that reflect perceptual, cognitive, and behavioural states as well as their underlying neurophysiology. The aim of the current study was to investigate age-related change in aperiodic and periodic alpha activity across a large sample of pre- and school-aged children (N = 502, age range 4 -11-years-of-age). Power spectra were extracted from baseline EEG recordings (eyes closed, eyes open) for each participant and parameterized into aperiodic activity to derive the offset and exponent parameters and periodic alpha oscillatory activity to derive the alpha peak frequency and the associated power estimates. Multilevel models were run to investigate age-related trends and condition-dependent changes for each of these measures. We found quadratic age-related effects for both the aperiodic offset and exponent. In addition, we observed increases in periodic alpha peak frequency as a function of age. Aperiodic measures and periodic alpha power were larger in magnitude during eyes closed compared to the eyes open baseline condition. Taken together, these results advance our understanding of the maturational patterns/trajectories of brain development during early- to middle-childhood.
年龄相关的结构和功能变化在大脑发育过程中对皮质发育和功能至关重要。先前的脑电图 (EEG) 和脑磁图 (MEG) 研究强调了功率谱分析的实用性,并揭示了与感知、认知和行为状态以及它们的潜在神经生理学相关的年龄相关趋势。本研究的目的是在大量的学前和学龄儿童样本中(N=502,年龄在 4 至 11 岁之间),研究非周期性和周期性α活动的年龄相关性变化。从每个参与者的基础脑电图记录(闭眼、睁眼)中提取功率谱,并将其参数化为非周期性活动,以推导出偏移和指数参数,以及周期性α振荡活动,以推导出α峰值频率和相关的功率估计。运行多层次模型以研究这些措施中的每一个的年龄相关趋势和条件依赖性变化。我们发现非周期性的偏移和指数都存在二次年龄相关效应。此外,我们观察到周期性α峰值频率随着年龄的增加而增加。与闭眼基线相比,在睁眼基线条件下,非周期性测量和周期性α功率的幅度更大。总的来说,这些结果提高了我们对儿童早期到中期大脑发育的成熟模式/轨迹的理解。