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, 16 (11), e2004188
eCollection

Adolescent Development of Cortical Oscillations: Power, Phase, and Support of Cognitive Maturation

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Adolescent Development of Cortical Oscillations: Power, Phase, and Support of Cognitive Maturation

Scott Marek et al. PLoS Biol.

Abstract

During adolescence, the integration of specialized functional brain networks related to cognitive control continues to increase. Slow frequency oscillations (4-10 Hz) have been shown to support cognitive control processes, especially within prefrontal regions. However, it is unclear how neural oscillations contribute to functional brain network development and improvements in cognitive control during adolescence. To bridge this gap, we employed magnetoencephalography (MEG) to explore changes in oscillatory power and phase coupling across cortical networks in a sample of 68 adolescents and young adults. We found a redistribution of power from lower to higher frequencies throughout adolescence, such that delta band (1-3 Hz) power decreased, whereas beta band power (14-16 and 22-26 Hz) increased. Delta band power decreased with age most strongly in association networks within the frontal lobe and operculum. Conversely, beta band power increased throughout development, most strongly in processing networks and the posterior cingulate cortex, a hub of the default mode (DM) network. In terms of phase, theta band (5-9 Hz) phase-locking robustly decreased with development, following an anterior-to-posterior gradient, with the greatest decoupling occurring between association networks. Additionally, decreased slow frequency phase-locking between frontolimbic regions was related to decreased impulsivity with age. Thus, greater decoupling of slow frequency oscillations may afford functional networks greater flexibility during the resting state to instantiate control when required.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Workflow diagram.
Preprocessing: Raw MEG and structural MRI data were preprocessed and coregistered. After surface ROI time series were extracted, a PLV was calculated for each frequency in the interval from 1–49 Hz, resulting in an ROI × ROI PLV matrix at each frequency interval for each subject. Global PLV: For each frequency, the mean PLV between all ROI pairs was calculated for each subject. Subject age was then regressed onto this global mean at each frequency to test for significant age effects, controlling for power. Regional PLV: Slow frequency (5–9 Hz) PLV matrices were averaged for each subject. Age was then regressed onto PLV for each edge of the matrix. The beta weight associated with age for every edge was extracted from each regression model. To summarize regional changes, we summed down the columns of the matrix, resulting in a composite linear age effect for each ROI. Global/regional power: Similar to the PLV pipeline, we calculated relative power for each ROI at each frequency interval. To obtain a global measure of power, we averaged power across all ROIs within a frequency band. For each region, we regressed power at a given frequency interval onto age and extracted the beta weight from the age regressor for additional analyses. Regional power estimates were examined for age effects and also included as nuisance regressors in all PLV × Age models. ICA, independent components analysis; MEG, magnetoencephalography; MNE, minimum-norm estimate; PLV, phase-locking value; ROI, region of interest; tSSS, temporal signal space separation.
Fig 2
Fig 2. Developmental differences in global cortical phase-locking and power.
(A) Across most frequency bands, adolescents displayed similar resting-state phase-locking to adults. However, in the 5–9 Hz frequency band, there was a significant linear decrease in phase-locking throughout development (gray shaded region; p < 0.05, FDR corrected). Top color bar represents the magnitude of the t statistic from the PLV × Age regression model. Data displayed categorically after segregation into 2 groups via a median split. (B) Power as a function of frequency. Delta band power significantly decreased with age, whereas beta band power significantly increased with age. Top color bar represents the magnitude of the t statistic from the Power × Age regression model. Data displayed categorically after segregation into 2 groups via a median split. In both (A) and (B), shaded gray patches represent frequency intervals demonstrating a significant linear relationship with age. Red and blue lines and shaded bars in the line plots represent the mean (solid line) and standard error of the mean (shaded patch around mean), respectively, in adolescents (red) and adults (blue). See S1 Data for individual data points. FDR, false discovery rate; PLV, phase-locking value.
Fig 3
Fig 3. Regional age-related differences in phase-locking.
(A) Regional age-related decreases in theta band phase-locking. (B) Scatter plot containing summed regional age effect (beta weight from theta PLV × Age model) as a function of the region’s anatomical y-coordinate center of mass. (C) PLV × Age anatomical gradient as a function of frequency. We found that the greatest anterior-to-posterior gradient developmental effect was in the 6–15 Hz regime. Gray error bars represent standard error of the model fit. Red shaded bar denotes theta/alpha regime. y-Axis represents the beta weight (slope) of the relationship between PLV and age with the anatomical y-coordinate of the region’s center of mass. See S1 Data for individual data points. PLV, phase-locking value.
Fig 4
Fig 4. Regional age-related differences in power.
(A) Regional age-related decreases in delta band power. (B) Regional age-related increases in beta band power. Scatter plots contain summed regional age effect (beta weight from Power × Age model) as a function of the region’s anatomical y-coordinate center of mass. (C) Power × Age anatomical gradient as a function of frequency. Error bars represent standard error of the model fit. Red shaded bar denotes delta and beta band regimes from panels A and B. y-Axis represents the beta weight (slope) of the relationship between power and age with the anatomical y-coordinate of the region’s center of mass. See S1 Data for individual data points.
Fig 5
Fig 5. Network changes in phase-locking.
(A) Age-related decreases in phase-locking tended to be within and between association networks (e.g., DM, FP, and SAL), while within- and between-network oscillations involving processing networks remained relatively stable. (B) Age-related increases in slow frequency decoupling were greater in association networks than in processing networks (p = 10−9). Oscillations in the SAL network became significantly more decoupled compared to any other association or processing network, with the exception of the CP network (all p < 0.05, corrected). See S1 Data for individual data points. AUD, Auditory; CO, Cinguloopercular; CP, Cinguloparietal; DA, Dorsal Attention; DM, Default Mode; FP, Frontoparietal; NONE, Unknown; RT, Retrospenial Temporal; SAL, Salience; SMH, Somatomotor Hand; SMM, Somatomotor Mouth; VA, Ventral Attention; VIS, Visual.
Fig 6
Fig 6. Pairwise age-related decreases in resting-state phase-locking.
Pairwise increases in decoupling between the top 5% of brain regions that showed age-related increases in decoupling (developmental hubs) and their respective top 5% pairwise interactions. Regions (little circles) are colored by the network to which they are affiliated. Link color represents the network affiliation to which the developmental hub belonged. The most significant pairwise increases occurred between regions of the DM, and FP networks to other association networks. DM, Default Mode; FP, Frontoparietal.
Fig 7
Fig 7. Frontolimbic 5–9 Hz phase-locking is related to decreased impulsivity during adolescence.
(A) Anatomical location PLV × Age and PLV × Impulsivity relationships. Red links denote the significant PLV × Age NBS cluster. Orange links denote the significant PLV × Impulsivity NBS cluster. Yellow links denote overlap between the 2 clusters. These overlapping links were tested for mediation. (B) Mediation model including statistics for specific paths. Note PLV of these 3 interactions fully mediated the relationship between age and impulsivity (difference in p-values between path C and paths in C’), confirming overlap of clusters. NBS, network-based statistic; PLV, phase-locking value.

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