Computational modeling approaches to emotional development.

Computational models of development have the potential to address a key challenge in emotional development research: investigating not only what changes across development but also how these changes come about. Drawing on connectionist and Bayesian methods, this review considers how computational modeling could augment the processes of theorizing and behavioral research to investigate causal processes underlying emotional development. As an illustrative example, we consider how different modeling approaches could help researchers evaluate different ideas about how children come to reason about others' emotions in increasingly sophisticated ways across development. This example is just a starting point; we propose that computational modeling could be an invaluable tool for exploring a variety of yet unresolved "how" questions in emotional development. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The neural underpinnings of intergroup social cognition: an fMRI meta-analysis.

Roughly 20 years of functional magnetic resonance imaging (fMRI) studies have investigated the neural correlates underlying engagement in social cognition (e.g. empathy and emotion perception) about targets spanning various social categories (e.g. race and gender). Yet, findings from individual studies remain mixed. In the present quantitative functional neuroimaging meta-analysis, we summarized across 50 fMRI studies of social cognition to identify consistent differences in neural activation as a function of whether the target of social cognition was an in-group or out-group member. We investigated if such differences varied according to a specific social category (i.e. race) and specific social cognitive processes (i.e. empathy and emotion perception). We found that social cognition about in-group members was more reliably related to activity in brain regions associated with mentalizing (e.g. dorsomedial prefrontal cortex), whereas social cognition about out-group members was more reliably related to activity in regions associated with exogenous attention and salience (e.g. anterior insula). These findings replicated for studies specifically focused on the social category of race, and we further found intergroup differences in neural activation during empathy and emotion perception tasks. These results help shed light on the neural mechanisms underlying social cognition across group lines.

Affect in the Aging Brain: A Neuroimaging Meta-Analysis of Older Vs. Younger Adult Affective Experience and Perception.

We report the first functional neuroimaging meta-analysis on age-related differences in adult neural activity during affect. We identified and coded experimental contrasts from 27 studies (published 1997-2018) with 490 older adults (55-87 years, M age = 69 years) and 470 younger adults (18-39 years, M age = 24 years). Using multilevel kernel density analysis, we assessed functional brain activation contrasts for older vs. younger adult affect across in-scanner tasks (i.e., affect induction and perception). Relative to older adults, younger adults showed more reliable activation in subcortical structures (e.g., amygdala, thalamus, caudate) and in relatively more posterior aspects of specific brain structures (e.g., posterior insula, mid- and posterior cingulate). In contrast, older adults exhibited more reliable activation in the prefrontal cortex and more anterior aspects of specific brain structures (e.g., anterior insula, anterior cingulate). Meta-analytic coactivation network analyses further revealed that in younger adults, the amygdala and mid-cingulate were more central, locally efficient network nodes, whereas in older adults, regions in the superior and medial prefrontal cortex were more central, locally efficient network nodes. Collectively, these findings help characterize age differences in the brain basis of affect and provide insights for future investigations into the neural mechanisms underlying affective aging.