The development of theta and alpha neural oscillations from ages 3 to 24 years

Abstract

Intrinsic, unconstrained neural activity exhibits rich spatial, temporal, and spectral organization that undergoes continuous refinement from childhood through adolescence. The goal of this study was to investigate the development of theta (4-8 Hertz) and alpha (8-12 Hertz) oscillations from early childhood to adulthood (years 3-24), as these oscillations play a fundamental role in cognitive function. We analyzed eyes-open, resting-state EEG data from 96 participants to estimate genuine oscillations separately from the aperiodic (1/f) signal. We examined age-related differences in the aperiodic signal (slope and offset), as well as the peak frequency and power of the dominant posterior oscillation. For the aperiodic signal, we found that both the aperiodic slope and offset decreased with age. For the dominant oscillation, we found that peak frequency, but not power, increased with age. Critically, early childhood (ages 3-7) was characterized by a dominance of theta oscillations in posterior electrodes, whereas peak frequency of the dominant oscillation in the alpha range increased between ages 7 and 24. Furthermore, theta oscillations displayed a topographical transition from dominance in posterior electrodes in early childhood to anterior electrodes in adulthood. Our results provide a quantitative description of the development of theta and alpha oscillations.

Keywords: Alpha oscillations; Aperiodic signal; Development; EEG; Peak frequency; Theta oscillations.

Graphical abstract

Fig. 1

Power spectrum as an aperiodic signal with superimposed periodic signal(s) (A) An illustration of the power spectrum as two separable signal sources: the aperiodic background signal (dashed line), and one or more periodic components (dark purple “bump”). Analysis of the aperiodic and periodic signals separately allows for a more accurate estimate of changes in oscillatory activity with age. The canonical alpha-band (α) is highlighted in light purple. (B, C) Two example participants, one age 4.5 years (light purple line) and the other age 15 (dark purple line), have different aperiodic slopes (B) and offsets (C). The solid grey lines show the raw power spectra. The aperiodic signal slope was estimated as the exponent of the equation in (B) and the offset as the intercept in (C). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

Fig. 2

Aperiodic signal flattens with age in early childhood (A) The aperiodic signal from the parietal-midline is depicted for all participants with the intercept anchored to a single point at 20 Hz to visualize individual differences in slope varying with age. Younger participants (light colors) have a steeper aperiodic signal than older participants (dark colors). Insert depicts the parietal-midline electrode cluster for all data in this figure. (B) The aperiodic signal is depicted for all participants to illustrate the difference in the aperiodic offset. Younger participants have greater intercepts (offsets) than older participants. (C) Aperiodic slope displayed a significant inverse relationship with age. (D) Aperiodic offset also displayed a significant inverse relationship with age. As participants increased in age, the slope and offset of the aperiodic signal decreased. ** p < 0.005, *** p < 0.0005. Grey area is 95 % confidence interval.

Fig. 3

The frequency and power of the dominant oscillation increases with age (A) The peak frequency of the dominant oscillation between 4-12 Hz is displayed in all participants who exhibited an oscillation. The peak frequency of the dominant oscillation from the parietal-midline electrode cluster (insert) increased in frequency with increasing age. (B) Power of the posterior dominant oscillation trended positively with age. Altogether, these results suggest a shifting of the dominant posterior oscillation from slower theta (4-8 Hz) to faster alpha-range (8-12 Hz) peaks. *** p < 0.0001 ∼ p < 0.1 Grey area is 95 % confidence interval.

Fig. 4

Theta to alpha oscillation transition with age (A) Two hypothetical participants with periodic signals modeled as Gaussian curves above the aperiodic signal. (B) Logistic regression of the age of the participant from which a genuine theta or alpha oscillation (categorical variable) was found. The 50 % probability mark (dashed line) occurs at approximately 7.19 years of age. Dots represent a genuine alpha or theta oscillation and the age of the participant. Dots are jittered along the y-axis for illustration.

Fig. 5

Analysis of peak theta and alpha frequency in younger and older participants (A) Two example participants with peak frequency of the dominant oscillation highlighted by a colored circle. (B) The power spectra correcting for the slope of the aperiodic signal for all participants is depicted with peak frequency in the theta-band (4-8 Hz) and alpha-band (8-12 Hz) plotted as dots. Younger (light purple) participants tend to have an overall lower alpha peak frequency than older (dark purple) participants. (C) Dominant frequency plotted with age. Logistic regression determined the age and frequency inflection points separating old and young participants and theta and alpha oscillations (dashed lines). Light purple square depicts theta frequency dominant oscillations in the young participants and dark purple square depicts alpha frequency dominant oscillation in the old participants. (D) Linear regression of age to individual alpha frequency in old participants and (E) to individual theta frequency in young participants. * p < 0.05. Grey area is 95 % confidence interval. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).

Fig. 6

Analysis of peak theta and alpha power in younger and older participants (A) Two hypothetical participants with oscillations that have a similar power prior to aperiodic signal correction. Note that without aperiodic signal correction, the power of the two oscillations in the hypothetical participants appears to be similar. After aperiodic signal correction, the peaks differ in power. (B) Aperiodic signal corrected power spectra for all participants. Dots indicate the peak frequency of each oscillations. (C) Linear regression of age to individual alpha power in younger participants and (D) to individual theta power in older participants. * p < 0.05. Grey area is 95 % confidence interval.

Fig. 7

Emergence of the frontal-midline theta oscillation in development (A) Example participant (age 10) who demonstrated alpha and theta oscillations in frontal-midline and parietal-midline clusters. Theta power was greater in the frontal-midline (red trace), whereas alpha power was greater in the parietal-midline (blue trace). (B) Frontal-midline power spectra for all participants with the slope of the aperiodic signal removed. Dots indicate the peak frequency for each participant. We observed a number of anterior theta peaks in younger participants and anterior alpha peaks in older participants, possibly due to the confounding influence of volume conduction. We therefore conducted our analyses on peak theta power, since this is likely to reflect greater proximity to the true origin of resting theta power in children versus adults. (C) Logistic regression of the site of aperiodic signal corrected peak theta power with age. Spatially-normalized (z-scored) theta topography averaged over participants with greater power in anterior (D) and posterior (E) electrodes. (Insert in C) Difference in z-scored theta power between participants with greater anterior versus posterior power. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article).