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However, the evidence is less clear about the amplitude of this alpha oscillation, termed alpha power. Indeed, numerous studies have investigated developmental changes in this alpha oscillation and reported evidence of an increase in the individual alpha frequency (IAF) at around 7 to 14 years of age ( Cragg et al., 2011 Díaz de León, Harmony, Marosi, Becker, & Alvarez, 1988 Klimesch, 1999 Lindsley, 1939 Marcuse et al., 2008 Niedermeyer, 1999 Somsen, van’t Klooster, van der Molen, van Leeuwen, & Licht, 1997). This lead to the notion that developmental changes in alpha activity reveals mechanisms of cortical manifestations of cognitive function. Cognitive functions such as attention and memory, which undergo critical changes during maturation, have frequently been associated with EEG alpha activity ( Foxe & Snyder, 2011 Klimesch, 1997 Klimesch, 2012 Niedermeyer, 1999). A substantial body of literature has focused on investigating these neurophysiological changes with electroencephalography (EEG) (for reviews, see Anderson & Perone, 2018 Segalowitz, Santesso, & Jetha, 2010). It is therefore particularly important to understand these maturational changes in brain structure and function, which are accompanied by neurophysiological changes. The typical emergence of mental illnesses during childhood and adolescence ( Kessler et al., 2005) further indicates fundamental maturational reorganization. Functionally, our results suggest that increased thalamic control of cortical alpha power is linked to improved attentional performance during brain maturation.Ĭhildhood and adolescence are critical stages of the human lifespan, in which the brain undergoes various and complex micro- and macroscopic changes ( Giedd et al., 1999 Lebel, Walker, Leemans, Phillips, & Beaulieu, 2008). Instead, additional analyses of diffusion tensor imaging data indicate that the maturational increase in periodic alpha power is related to increased thalamocortical connectivity.
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The interpretation of decreased total alpha power as elimination of active synapses rather links to decreases in the aperiodic intercept. Consequently, earlier interpretations on age related changes of alpha power need to be fundamentally reconsidered, incorporating changes in the aperiodic signal. However, when controlling for the aperiodic signal component, our findings provide strong evidence for a reversed developmental trajectory of the periodic alpha power, whereas the aperiodic signal components, slope and offset, decreased. First, the well documented age-related decrease in total alpha power was replicated. Using multivariate Bayesian generalized linear mixed models, we examined aperiodic and periodic parameters of alpha activity in the largest openly available pediatric dataset (N=2529, age range 5-21 years) and replicated these findings in a preregistered analysis of an independent validation sample (N=369, age range 6–21yrs). It is therefore unclear how each part of the signal relates to changes during brain maturation. Simulations in this study show that conventional measures of alpha power are confounded by various factors and need to be decomposed into periodic and aperiodic components, which represent distinct underlying brain mechanisms. Ambiguous results were reported for the developmental trajectory of the power of the alpha oscillation. A substantial body of literature investigated neurophysiological changes during brain maturation by focusing on the most dominant feature of the human EEG signal: the alpha oscillation. Childhood and adolescence are critical stages of the human lifespan, in which fundamental neural reorganizational processes take place.