Spatial and Temporal Cortical Variability Track with Age and Affective Experience During Emotion Regulation in Youth

Abstract

Variability is a fundamental feature of human brain activity that is particularly pronounced during development. However, developmental neuroimaging research has only recently begun to move beyond characterizing brain function across development exclusively in terms of magnitude of neural activation to incorporating estimates of variability. No prior neuroimaging study has done so in the domain of emotion regulation. We investigated how age and affective experiences influence spatial and temporal variability in neural activity during emotion regulation. In the current study, 70 typically developing youth aged 8-17 years completed a cognitive reappraisal task of emotion regulation while undergoing functional magnetic resonance imaging. Estimates of spatial and temporal variability during emotion regulation were calculated across a network of brain regions, defined a priori, and were then related to age and affective experiences. Results showed that increasing age was associated with reduced spatial and temporal variability in a set of frontoparietal regions (e.g., dorsomedial prefrontal cortex, superior parietal lobule) known to be involved in effortful emotion regulation. In addition, youth who reported less negative affect during emotion regulation had less spatial variability in the ventrolateral prefrontal cortex. We interpret age-related reductions in spatial and temporal variability as evidence of neural specialization. These results imply that the development of emotion regulation is undergirded by a process of neural specialization and open up a host of possibilities for incorporating neural variability into the study of emotion regulation development.Keywords: Emotion; Emotion Regulation; Development; Variability; Neuroimaging . CC-BY-NC-ND 4.0 International license It is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. Heller & Casey, 2016;Nomi, Bolt, Ezie, Uddin, & Heller, 2017). This is because age-related differences in neural variability likely reflect important developmental processes, including the degree of efficiency, specialization, and experience-based plasticity (e.g., pruning) in neural circuits across age (Casey, 2015;Durston et al., 2006). Emotion regulation presents itself as a particularly important skill to be assessed in a developmental neural variability framework because it exhibits protracted maturation and is critical for wellbeing (Cole & Deater-Deckard, 2009;Gross, 2015;McLaughlin, Garrard, & Somerville, 2015). However, virtually all developmental neuroimaging studies of emotion regulation to date have concentrated on age-related differences in the magnitude of brain activity across individuals, and have ignored how variability within individuals during emotion regulation differs across development. The present study sought to address this knowledge gap by investigating how within-subject variability in neural activity during emotion regulation-both spatial and temporal-is ...

Context and dynamics: The new frontier for developmental research on emotion regulation.

“…This represents an important direction for future developmental research on emotion dynamics. Moreira, McLaughlin, and Silvers (2019), in this special issue, tackle the dynamics of emotion regulation variability in youth from ages 8 to 17 years, addressing it from an interdisciplinary affective neuroscience perspective. Specifically, they find that older adolescents show reduced variability in brain activation over the course of an explicit emotion regulation task, in regions of the brain thought to support emotion regulation, such as the dorsomedial and ventrolateral prefrontal cortex.…”

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

“…To test this, we re-extracted multivariate patterns from the NAcc and lPFC and computed Gini coefficients for each region for each trial. Traditionally used in macroeconomics but recently applied in neuroscience (Guest and Love, 2017;Guassi Moreira et al, 2019), Gini coefficients in this context can describe the extent to which brain activity in a given region is homogeneous (uniform) or heterogeneous. Indeed, as shown in Table 6, a lower Gini coefficient in the NAcc (i.e., more uniform activation) was associated with an increased propensity to take risks on the YLG, suggesting a strong, one-dimensional encoding of value signatures during decision-making.…”

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

“…To test this, we re-extracted multivariate patterns from the NAcc and lPFC and computed Gini coefficients for each region for each trial. Traditionally used in macroeconomics but recently applied in neuroscience (59,60), Gini coefficients in this context can describe the extent to which brain activity in a given region is homogenous (uniform) or heterogeneous. Indeed, as shown in Supplementary Table 6, a lower Gini coefficient in the NAcc (i.e., more uniform activation) was associated with an increased propensity to take risks on the YLG, suggesting a strong, one-dimensional encoding of value signatures during decision-making.…”