Considerations When Characterizing Adolescent Neurocognitive Development

Luna, Beatriz; Tervo‐Clemmens, Brenden; Calabro, Finnegan J.

doi:10.1016/j.biopsych.2020.04.026

Cited by 14 publications

(13 citation statements)

References 10 publications

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“…At the neural level, the transition between childhood and young adulthood is marked by decreases in gray matter, increases in white matter volume, and a shift from local short-range connections to the strengthening of distributed long-range connections ( Casey, 2015 ; Dosenbach et al, 2010 ; Hwang et al, 2013 ; Sporns, 2013 ). With the maturation of long-range connections that support integrated and distributed processing comes neural and cognitive specialization (Beatriz Luna et al, 2020 ). A hallmark of this specialization during adolescence is the capacity for flexible control over behaviour, which is perhaps most obvious when the demands on self-regulation co-occur with heightened arousal, emotional saliency, and social pressures.…”

Section: Discussionmentioning

confidence: 99%

“…A hallmark of this specialization during adolescence is the capacity for flexible control over behaviour, which is perhaps most obvious when the demands on self-regulation co-occur with heightened arousal, emotional saliency, and social pressures. The large maturational changes between frontal cortical and subcortical limbic networks are thought to support the development of this “emotional maturity” that allows individuals to appropriately monitor and regulate endogenous states so that they are in line with environmental demands ( Johnson et al, 2009 ; Luna, 2009 ; Luna et al, 2020 ). The asynchrony between the maturation of cortical and subcortical networks is thought to be a key factor ( Casey, 2015 ) leading to poorer self-regulation and maladaptive emotional decision-making that is prevalent during the adolescent transition period.…”

Section: Discussionmentioning

confidence: 99%

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Cortical maturation from childhood to adolescence is reflected in resting state EEG signal complexity

Noordt

Willoughby

2021

Developmental Cognitive Neuroscience

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Endogenous cortical fluctuations captured by electroencephalograms (EEGs) reflect activity in large-scale brain networks that exhibit dynamic patterns over multiple time scales. Developmental changes in the coordination and integration of brain function leads to greater complexity in population level neural dynamics. In this study we examined multiscale entropy, a measure of signal complexity, in resting-state EEGs in a large (N = 405) cross-sectional sample of children and adolescents (9–16 years). Our findings showed consistent age-dependent increases in EEG complexity that are distributed across multiple temporal scales and spatial regions. Developmental changes were most robust as the age gap between groups increased, particularly between late childhood and adolescence, and were most prominent over fronto-central scalp regions. These results suggest that the transition from late childhood to adolescence is characterized by age-dependent changes in the underlying complexity of endogenous brain networks.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Cortical maturation from childhood to adolescence is reflected in resting state EEG signal complexity

Noordt

Willoughby

2021

Developmental Cognitive Neuroscience

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“…Not only did inverse age and quadratic age models find different trajectories (as would be expected), but quadratic trajectories themselves also displayed considerable analytic variability, with some specifications finding “convex” and others finding “concave” fits (see sFigure 17). Although estimating nonlinear age-related change was not a primary goal of the present study, future work should use model comparisons for better differentiating nonlinear patterns (Curran et al, 2010; Luna et al, 2021).…”

Section: Resultsmentioning

confidence: 99%

“…We fit separate models for the d' performance metric, overall accuracy (probability of a correct response on any trial), hit rate (on neutral face trials), and false alarm rate (on fear face trials) as the respective outcomes, and included nested random effects for task sessions within participants (models were not nested for d' as this analysis used only 1 metric per session rather than trial-wise outcomes, but still included random effects for participants). Additionally, to model age-related change in reaction times during correct hit trials, we fit linear, quadratic, cubic, and inverse age (1/age; Luna et al, 2004Luna et al, , 2021 regressions with identical random effects structures. Model equations and results for all behavioral analyses can be found in the supplement (see supplemental methods p.12-14, sFigures 3-4).…”

Section: Behavioral Analysesmentioning

confidence: 99%

Age-related change in task-evoked amygdala—prefrontal circuitry: a multiverse approach with an accelerated longitudinal cohort aged 4-22 years

Bloom

VanTieghem

Gabard-Durnam

et al. 2021

Preprint

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There has been considerable interest in the development of the amygdala and its connections with medial prefrontal cortex (mPFC) given the central role of these brain regions in emotional processes. While several studies have suggested that this circuitry exhibits functional changes across the first two decades of life, they have typically employed cross-sectional designs, and findings have been mixed. Additionally, analytic choices may contribute to discrepancies across studies. Here we used an accelerated longitudinal design to examine task-evoked changes in amygdala-mPFC circuitry from 4-22 years of age (N=98; 183 total scans; 1-3 scans per participant). Participants were recruited from the greater Los Angeles area, and completed an event-related emotional face (fear, neutral) task designed to be appropriate for the wide age range. 'Multiverse' analyses examined the robustness of our findings to fMRI analysis choices. 2808 parallel analyses varying in preprocessing and modeling choices found evidence for average age-related decreases in amygdala reactivity to faces. Greater amygdala reactivity at younger ages was attributable to elevated responses during the first few trials relative to later trials. Within-participant changes in amygdala reactivity with age could not be differentiated from between-participant differences, however. Across analysis decision points, we did not find consistent evidence of age-related change in amygdala-mPFC connectivity through generalized psychophysiological interaction (gPPI) or beta-series correlation (BSC) methods. We also did not find evidence for associations between separation anxiety behaviors and amygdala reactivity or amygdala-mPFC connectivity. Within the context of this faces task and age range, age-related changes in amygdala reactivity were more robust to processing pipeline than were task-evoked functional connectivity measures, particularly those using gPPI. These findings highlight both the challenges in estimating developmental change in longitudinal cohorts and the value of multiverse approaches in developmental neuroimaging for assessing robustness of results.

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“…In the field of developmental psychopathology, null findings serve as an important baseline for future longitudinal research [87]. Given that adolescence is a transitional developmental period, the presently hypothesized effects and associated sex differences are expected to emerge and grow over time [88].…”

Section: Discussionmentioning

confidence: 99%

A Multidimensional Approach to Understanding the Emergence of Sex Differences in Internalizing Symptoms in Adolescence

Serio

Kohler

et al. 2022

Preprint

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Women are more vulnerable to internalizing disorders (e.g., depression and anxiety). This study took an integrative, developmental approach to investigate multidimensional factors associated with the emergence of sex differences in internalizing symptoms, using data from the Adolescent Brain Cognitive Development (ABCD) study. Indices of sex hormone levels (dehydroepiandrosterone, testosterone, and estradiol), physical pubertal development, task-based functional brain activity, family conflict, and internalizing symptoms were drawn from the ABCD study's baseline sample (9- to 10-year-old; N = 11,844). Principal component analysis served as a data-driven dimensionality reduction technique on the internalizing subscales to yield a single robust measure of internalizing symptoms. Moderated mediation analyses assessed whether associations between known risk factors and internalizing symptoms vary by sex. Results revealed direct and indirect effects of physical pubertal development on internalizing symptoms through family conflict across sexes. No effects were found of sex hormone levels or amygdala response to fearful faces on internalizing symptoms. Females did not report overall greater internalizing symptoms relative to males, suggesting that internalizing symptoms have not yet begun to increase in females at this age. Findings provide an essential baseline for future longitudinal research on the endocrine, neurocognitive, and psychosocial factors associated with sex differences in internalizing symptoms.

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Considerations When Characterizing Adolescent Neurocognitive Development

Cited by 14 publications

References 10 publications

Cortical maturation from childhood to adolescence is reflected in resting state EEG signal complexity

Cortical maturation from childhood to adolescence is reflected in resting state EEG signal complexity

Age-related change in task-evoked amygdala—prefrontal circuitry: a multiverse approach with an accelerated longitudinal cohort aged 4-22 years

A Multidimensional Approach to Understanding the Emergence of Sex Differences in Internalizing Symptoms in Adolescence

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