Spatial and temporal cortical variability track with age and affective experience during emotion regulation in youth

Experience-dependent neurodevelopment of self-regulation in adolescence

Adolescence is a period of rapid biobehavioral change, characterized in part by increased neural maturation and sensitivity to one's environment. In this review, we aim to demonstrate that self-regulation skills are tuned by adolescents' social, cultural, and socioeconomic contexts. We discuss adjacent literatures that demonstrate the importance of experience-dependent learning for adolescent development: environmental contextual influences and training paradigms that aim to improve regulation skills. We first highlight changes in prominent limbic and cortical regions-like the amygdala and medial prefrontal cortex-as well as structural and functional connectivity between these areas that are associated with adolescents' regulation skills. Next, we consider how puberty, the hallmark developmental milestone in adolescence, helps instantiate these biobehavioral adaptations. We then survey the existing literature demonstrating the ways in which cultural, socioeconomic, and interpersonal contexts drive behavioral and neural adaptation for self-regulation. Finally, we highlight promising results from regulation training paradigms that suggest training may be especially efficacious for adolescent samples. In our conclusion, we highlight some exciting frontiers in human self-regulation research as well as recommendations for improving the methodological implementation of developmental neuroimaging studies and training paradigms.

Classification of Major Depressive Disorder Based on Integrated Temporal and Spatial Functional MRI Variability Features of Dynamic Brain Network

BACKGROUND

Characterization of the dynamics of functional brain network has gained increased attention in the study of depression. However, most studies have focused on single temporal dimension, while ignoring spatial dimensional information, hampering the discovery of validated biomarkers for depression.

PURPOSE

To integrate temporal and spatial functional MRI variability features of dynamic brain network in machine-learning techniques to distinguish patients with major depressive disorder (MDD) from healthy controls (HCs).

STUDY TYPE

Prospective.

POPULATION

A discovery cohort including 119 patients and 106 HCs and an external validation cohort including 126 patients and 124 HCs from Rest-meta-MDD consortium.

FIELD STRENGTH/SEQUENCE

A 3.0 T/resting-state functional MRI using the gradient echo sequence.

ASSESSMENT

A random forest (RF) model integrating temporal and spatial variability features of dynamic brain networks with separate feature selection method (MSFS ) was implemented for MDD classification. Its performance was compared with three RF models that used: temporal variability features (MTVF ), spatial variability features (MSVF ), and integrated temporal and spatial variability features with hybrid feature selection method (MHFS ). A linear regression model based on MSFS was further established to assess MDD symptom severity, with prediction performance evaluated by the correlations between true and predicted scores.

STATISTICAL TESTS

Receiver operating characteristic analyses with the area under the curve (AUC) were used to evaluate models' performance. Pearson's correlation was used to assess relationship of predicted scores and true scores. P < 0.05 was considered statistically significant.

RESULTS

The model with MSFS achieved the best performance, with AUCs of 0.946 and 0.834 in the discovery and validation cohort, respectively. Additionally, altered temporal and spatial variability could significantly predict the severity of depression (r = 0.640) and anxiety (r = 0.616) in MDD.

DATA CONCLUSION

Integration of temporal and spatial variability features provides potential assistance for clinical diagnosis and symptom prediction of MDD.

EVIDENCE LEVEL

2.

TECHNICAL EFFICACY

Stage 2.

Resting-state BOLD temporal variability in sensorimotor and salience networks underlies trait emotional intelligence and explains differences in emotion regulation strategies

A converging body of behavioural findings supports the hypothesis that the dispositional use of emotion regulation (ER) strategies depends on trait emotional intelligence (trait EI) levels. Unfortunately, neuroscientific investigations of such relationship are missing. To fill this gap, we analysed trait measures and resting state data from 79 healthy participants to investigate whether trait EI and ER processes are associated to similar neural circuits. An unsupervised machine learning approach (independent component analysis) was used to decompose resting-sate functional networks and to assess whether they predict trait EI and specific ER strategies. Individual differences results showed that high trait EI significantly predicts and negatively correlates with the frequency of use of typical dysfunctional ER strategies. Crucially, we observed that an increased BOLD temporal variability within sensorimotor and salience networks was associated with both high trait EI and the frequency of use of cognitive reappraisal. By contrast, a decreased variability in salience network was associated with the use of suppression. These findings support the tight connection between trait EI and individual tendency to use functional ER strategies, and provide the first evidence that modulations of BOLD temporal variability in specific brain networks may be pivotal in explaining this relationship.

Impulsivity and Emotional Dysregulation Predict Choice Behavior During a Mixed-Strategy Game in Adolescents With Borderline Personality Disorder

Impulsivity and emotional dysregulation are two core features of borderline personality disorder (BPD), and the neural mechanisms recruited during mixed-strategy interactions overlap with frontolimbic networks that have been implicated in BPD. We investigated strategic choice patterns during the classic two-player game, Matching Pennies, where the most efficient strategy is to choose each option randomly from trial-to-trial to avoid exploitation by one’s opponent. Twenty-seven female adolescents with BPD (mean age: 16 years) and twenty-seven age-matched female controls (mean age: 16 years) participated in an experiment that explored the relationship between strategic choice behavior and impulsivity in both groups and emotional dysregulation in BPD. Relative to controls, BPD participants showed marginally fewer reinforcement learning biases, particularly decreased lose-shift biases, increased variability in reaction times (coefficient of variation; CV), and a greater percentage of anticipatory decisions. A subset of BPD participants with high levels of impulsivity showed higher overall reward rates, and greater modulation of reaction times by outcome, particularly following loss trials, relative to control and BPD participants with lower levels of impulsivity. Additionally, BPD participants with higher levels of emotional dysregulation showed marginally increased reward rate and increased entropy in choice patterns. Together, our preliminary results suggest that impulsivity and emotional dysregulation may contribute to variability in mixed-strategy decision-making in female adolescents with BPD.

Adolescence as a pivotal period for emotion regulation development for consideration at current opinion in psychology

Adolescence is a dynamic period for the development of emotion regulation. For many individuals, emotion regulation skills improve dramatically during adolescence; however, for some youth, adolescence marks the beginning or worsening of psychopathology characterized by difficulties with emotion regulation. In the present review, I describe evidence that caregiving experiences play an outsized role in shaping interindividual variability in emotion regulation during adolescence. After describing work demonstrating links between caregiving - with an emphasis on parental socialization practices - and emotion regulation outcomes, I characterize our current understanding of how behavioral and neurobiological indices of emotion regulation develop normatively across adolescence. Using cognitive reappraisal as an exemplar emotion regulation strategy, I outline ways that caregiving might impact interindividual variability in emotion regulation neurodevelopment. I conclude by identifying two key future directions for adolescent emotion regulation research.

Characterizing the Network Architecture of Emotion Regulation Neurodevelopment

The ability to regulate emotions is key to goal attainment and well-being. Although much has been discovered about neurodevelopment and the acquisition of emotion regulation, very little of this work has leveraged information encoded in whole-brain networks. Here we employed a network neuroscience framework to parse the neural underpinnings of emotion regulation skill acquisition, while accounting for age, in a sample of children and adolescents (N = 70, 34 female, aged 8-17 years). Focusing on three key network metrics-network differentiation, modularity, and community number differences between active regulation and a passive emotional baseline-we found that the control network, the default mode network, and limbic network were each related to emotion regulation ability while controlling for age. Greater network differentiation in the control and limbic networks was related to better emotion regulation ability. With regards to network community structure (modularity and community number), more communities and more crosstalk between modules (i.e., less modularity) in the control network were associated with better regulatory ability. By contrast, less crosstalk (i.e., greater modularity) between modules in the default mode network was associated with better regulatory ability. Together, these findings highlight whole-brain connectome features that support the acquisition of emotion regulation in youth.

Revisiting the Neural Architecture of Adolescent Decision-Making: Univariate and Multivariate Evidence for System-Based Models

Understanding adolescent decision-making is significant for informing basic models of neurodevelopment as well as for the domains of public health and criminal justice. System-based theories posit that adolescent decision-making is guided by activity related to reward and control processes. While successful at explaining behavior, system-based theories have received inconsistent support at the neural level, perhaps because of methodological limitations. Here, we used two complementary approaches to overcome said limitations and rigorously evaluate system-based models. Using decision-level modeling of fMRI data from a risk-taking task in a sample of 2000+ decisions across 51 human adolescents (25 females, mean age = 15.00 years), we find support for system-based theories of decision-making. Neural activity in lateral PFC and a multivariate pattern of cognitive control both predicted a reduced likelihood of risk-taking, whereas increased activity in the NAcc predicted a greater likelihood of risk-taking. Interactions between decision-level brain activity and age were not observed. These results garner support for system-based accounts of adolescent decision-making behavior.SIGNIFICANCE STATEMENT Adolescent decision-making behavior is of great import for basic science, and carries equally consequential implications for public health and criminal justice. While dominant psychological theories seeking to explain adolescent decision-making have found empirical support, their neuroscientific implementations have received inconsistent support. This may be partly because of statistical approaches used by prior neuroimaging studies of system-based theories. We used brain modeling, an approach that predicts behavior from brain activity, of univariate and multivariate neural activity metrics to better understand how neural components of psychological systems guide decision behavior in adolescents. We found broad support for system-based theories such that neural systems involved in cognitive control predicted a reduced likelihood to make risky decisions, whereas value-based systems predicted greater risk-taking propensity.

Emotion dynamics across adulthood in everyday life: Older adults are more emotionally stable and better at regulating desires

Older adults report experiencing improved emotional health, such as more intense positive affect and less intense negative affect. However, there are mixed findings on whether older adults are better at regulating emotion-a hallmark feature of emotional health-and most research is based on laboratory studies that may not capture how people regulate their emotions in everyday life. We used experience sampling to examine how multiple measures of emotional health, including mean affect, dynamic fluctuations between affective states and the ability to resist desires-a common form of emotion regulation-differ in daily life across adulthood. Participants (N = 122, ages 20-80) reported how they were feeling and responding to desire temptations for 10 days. Older adults experienced more intense positive affect, less intense negative affect, and were more emotionally stable, even after controlling for individual differences in global life satisfaction. Older adults were more successful at regulating desires, even though they experienced more intense desires than younger adults. In addition, adults in general experiencing more intense affect were less successful at resisting desires. These results demonstrate how emotional experience is related to more successful desire regulation in everyday life and provide unique evidence that emotional health and regulation improve with age. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Changes in BOLD variability are linked to the development of variable response inhibition

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This is the first study to investigate the development of response inhibition focussing on variability.

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We examined intraindividual variability both in stopping latencies and the underlying neural circuitry.

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There were no developmental differences in mean response inhibition, yet clear differences in performance variability.

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This, in turn, was associated with developmental differences in brain signal variability.

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Behavioral and neural variability indices might be a more sensitive measure of developmental differences in inhibition.

Research on the development of response inhibition in humans has focused almost exclusively on average stopping performance. The development of intra-individual variability in stopping performance and its underlying neural circuitry has remained largely unstudied, even though understanding variability is of core importance for understanding development. In a total sample of 45 participants (19 children aged 10–12 years and 26 adults aged 18–26 years) of either sex we aimed to identify age-related changes in intra-individual response inhibition performance and its underlying brain signal variability. While there was no difference in average stopping performance between children and adults, stop signal latencies for the children were more variable. Further, brain signal variability during successful stopping was significantly higher in adults compared to children, especially in bilateral thalamus, but also across regions of the inhibition network. Finally, brain signal variability was significantly associated with stopping performance behavioral variability in adults. Together these results indicate that variability in stopping performance decreases, whereas neural variability in the inhibition network increases, from childhood to adulthood. Future work will need to assess whether developmental changes in neural variability drive those in behavioral variability. In sum, both, neural and behavioral variability indices might be a more sensitive measure of developmental differences in response inhibition compared to the standard average-based measurements.

Progress in understanding the emergence of human emotion

In the past several decades, research on emotional development has flourished. Scientists have made progress in understanding infants', children's, and adults' abilities to recognize, communicate, and regulate their emotions. However, many questions remain unanswered or only partly answered. We are poised to move from descriptions of aspects of emotional functioning to conceptualizing and studying the developmental mechanisms that underlie those aspects. The gaps in our knowledge provide numerous opportunities for further investigation. With this special issue of Developmental Psychology, we aim to stimulate such progress, especially among colleagues at the beginning of their careers. The articles in this issue are intended to challenge our concepts and take research on emotional development in new directions. Toward this end, this special issue includes empirical studies, theoretical articles, novel conceptualizations, methodological innovations, and invited commentaries from scholars across a range of disciplines. In this introductory essay, we briefly review the history of research on emotional development and provide an overview of the contributions of this special issue with thoughts about the current state of the developmental science and areas in which further advancement on emotional development must be made. These include understanding the nature of emotion itself, identifying the mechanisms that produce developmental changes, examining emotion regulation within differing social contexts, and creating measures of culture that acknowledge globalization, historical change, and within-culture differences. (PsycINFO Database Record (c) 2019 APA, all rights reserved).