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Macrostructural characteristics, such as cost of living and state-level anti-poverty programs relate to the magnitude of socioeconomic disparities in brain development and mental health. In this study we leveraged data from the Adolescent Brain and Cognitive Development (ABCD) study from 10,633 9-11 year old youth (5115 female) across 17 states. Lower income was associated with smaller hippocampal volume and higher internalizing psychopathology. These associations were stronger in states with higher cost of living. However, in high cost of living states that provide more generous cash benefits for low-income families, socioeconomic disparities in hippocampal volume were reduced by 34%, such that the association of family income with hippocampal volume resembled that in the lowest cost of living states. We observed similar patterns for internalizing psychopathology. State-level anti-poverty programs and cost of living may be confounded with other factors related to neurodevelopment and mental health. However, the patterns were robust to controls for numerous state-level social, economic, and political characteristics. These findings suggest that state-level macrostructural characteristics, including the generosity of anti-poverty policies, are potentially relevant for addressing the relationship of low income with brain development and mental health.

 

How do people go about reading a room or taking the temperature of a crowd? When people catch a brief glimpse of an array of faces, they can focus their attention on only some of the faces. We propose that perceivers preferentially attend to faces exhibiting strong emotions and that this generates a crowd-emotion-amplification effect—estimating a crowd’s average emotional response as more extreme than it actually is. Study 1 ( N = 50) documented the crowd-emotion-amplification effect. Study 2 ( N = 50) replicated the effect even when we increased exposure time. Study 3 ( N = 50) used eye tracking to show that attentional bias to emotional faces drives amplification. These findings have important implications for many domains in which individuals must make snap judgments regarding a crowd’s emotionality, from public speaking to controlling crowds. 

Scholars from across the social and media sciences have issued a clarion call to address a recent resurgence in criminalized characterizations of immigrants. Do these characterizations meaningfully impact individuals’ beliefs about immigrants and immigration? Across two online convenience samples (total N = 1,054 adult U.S. residents), we applied a novel analytic technique to test how different narratives—achievement, criminal, and struggle-oriented—impacted cognitive representations of German, Russian, Syrian, and Mexican immigrants and the concept of immigrants in general. All stories featured male targets. Achievement stories homogenized individual immigrant representations, whereas both criminal and struggle-oriented stories racialized them along a White/non-White axis: Germany clustered with Russia, and Syria clustered with Mexico. However, criminal stories were unique in making our most egalitarian participants’ representations as differentiated as our least egalitarian participants’. Narratives about individual immigrants also generalized to update representations of nationality groups. Most important, narrative-induced representations correlated with immigration-policy preferences: Achievement narratives and corresponding homogenized representations promoted preferences for less restriction, and criminal narratives promoted preferences for more. 

What is a group? How do we know to which groups we belong? How do we assign others to groups? A great deal of theorizing across the social sciences, has conceptualized “groups” as synonymous with “categories.” There are significant limitations to this approach, however, particularly for making predictions about novel intergroup contexts and about how intergroup dynamics will change over time. Here I systematize the conditions under which a generalized coalitional psychology gets activated—the recognition of another’s capacity for and likelihood of coordination not only with oneself but with others. First, I synthesize recent developments in research on the cognitive processes that give rise to the inference of coalitions and group-biased preferences (even in the absence of category labels). Then I review downstream consequences of inferences about capacity and likelihood of coordination for valuation, emotions, attribution, and inter-coalitional harm. Finally, I discuss ways to use these psychological levers to attenuate intergroup hostility. 

Social-structure learning is the process by which social groups are identified on the basis of experience. Building on models of structure learning in other domains, we formalize this problem within a Bayesian framework. According to this framework, the probabilistic assignment of individuals to groups is computed by combining information about individuals with prior beliefs about group structure. Experiments with adults and children provide support for this framework, ruling out alternative accounts based on dyadic similarity. More broadly, we highlight the implications of social-structure learning for intergroup cognition, stereotype updating, and coalition formation. 

Humans form social coalitions in every society, yet we know little about how we learn and represent social group boundaries. Here we derive predictions from a computational model of latent structure learning to move beyond explicit category labels and interpersonal, or dyadic similarity as the sole inputs to social group representations. Using a model-based analysis of functional neuroimaging data, we find that separate areas correlate with dyadic similarity and latent structure learning. Trial-by-trial estimates of 'allyship' based on dyadic similarity between participants and each agent recruited medial prefrontal cortex/pregenual anterior cingulate (pgACC). Latent social group structure-based allyship estimates, in contrast, recruited right anterior insula (rAI). Variability in the brain signal from rAI improved prediction of variability in ally-choice behavior, whereas variability from the pgACC did not. These results provide novel insights into the psychological and neural mechanisms by which people learn to distinguish 'us' from 'them'.