Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia.
Cognitive Neuroscience Unit, School of Psychology, Deakin University, Melbourne, Australia.
Dev Cogn Neurosci. 2022 Apr;54:101076. doi: 10.1016/j.dcn.2022.101076. Epub 2022 Jan 22.
The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for the emergence and maturation of a range of social and cognitive processes. Here, we utilised both eyes open and eyes closed resting-state electroencephalography (EEG) to examine maturational changes in both oscillatory (i.e., periodic) and non-oscillatory (aperiodic, '1/f-like') activity in a large cohort of participants ranging from 4-to-12 years of age (N = 139, average age=9.41 years, SD=1.95). The EEG signal was parameterised into aperiodic and periodic components, and linear regression models were used to evaluate if chronological age could predict aperiodic exponent and offset, as well as well as peak frequency and power within the alpha and beta ranges. Exponent and offset were found to both decrease with age, while aperiodic-adjusted alpha peak frequency increased with age; however, there was no association between age and peak frequency for the beta band. Age was also unrelated to aperiodic-adjusted spectral power within either the alpha or beta bands, despite both frequency ranges being correlated with the aperiodic signal. Overall, these results highlight the capacity for both periodic and aperiodic features of the EEG to elucidate age-related functional changes within the developing brain.
神经发育时期跨越儿童早期到中期,代表了大脑皮层在整个时期的显著生长和重组。这些变化对于一系列社会和认知过程的出现和成熟至关重要。在这里,我们利用睁眼和闭眼静息状态脑电图(EEG)来研究从 4 岁到 12 岁的大样本参与者中,无论是在振荡(即周期性)还是非振荡(非周期性,“1/f 样”)活动中都存在的成熟变化(N=139,平均年龄=9.41 岁,标准差=1.95)。EEG 信号被参数化为非周期性和周期性成分,线性回归模型用于评估年龄是否可以预测非周期性指数和偏移,以及在 alpha 和 beta 范围内的峰值频率和功率。发现指数和偏移都随年龄而降低,而经过非周期性调整的 alpha 峰值频率随年龄增加而增加;然而,beta 波段的年龄与峰值频率之间没有关联。年龄与 alpha 或 beta 波段中的非周期性调整的光谱功率也没有关系,尽管这两个频率范围都与非周期性信号相关。总的来说,这些结果强调了 EEG 的周期性和非周期性特征都有能力阐明发育中大脑的与年龄相关的功能变化。