Social interaction and diversity in brain health

Understanding social cognition and prosociality requires incorporating the influences of diversity and disparity, as they significantly impact brain health and, at the same time, shape how individuals perceive, interpret, and interact in social contexts.
Social interaction and diversity in brain health
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When diversity and disparity meet brain health and disease

 Diversity and disparity are critical in understanding brain health, aging, and dementia. Diversity not only refers to the inclusion and representation of gender and race but also encompasses other aspects such as ethnicity, age, social determinants of health and socioeconomic status, cultural background, quality of education and life, environmental exposome, and cognitive and affective abilities. Disparity, on the other hand, generally relates to inequalities or differences within or between groups, especially in health, access to resources, or opportunities. It often points to the gaps or imbalances that can impact various aspects of life, including health outcomes, educational attainment, or socioeconomic status. Both diversity and disparity are significant in understanding complex social and health phenomena. 

Diversity and disparity are intertwined and significantly impact brain health, particularly in the context of social cognition. Diverse backgrounds and disparities in resources and opportunities influence (a) overall health and (b) how individuals perceive, interpret, and engage in social interactions. This variation contributes to differences in the development and manifestation of social cognitive abilities, affecting how people understand and respond to social cues.

Social interactions: A context-dependent phenomenon

 Social cognition, the process of understanding and interacting with others, is deeply influenced by our surroundings and experiences. This aspect of cognitive science highlights how our social interactions and interpretations are shaped by our internal mental processes and the context in which we find ourselves.

 Social cognition abilities in older adults vary significantly across different countries and cultures, suggesting that diverse contextual factors play a crucial role. Diverse populations, including those from the majority of the world (i.e., the global south), are critical to understanding the full spectrum of social cognition, especially in the context of brain diseases like dementia. These disparities in resources, healthcare access, and cultural backgrounds contribute to different experiences and manifestations of social cognitive processes, underlining the necessity of inclusive research approaches in social neuroscience. Socioeconomic status (SES) can negatively impact social cognition and prosociality, particularly in environments of scarcity and stress. Lower SES is often associated with reduced access to resources and opportunities, increasing stress, and allostatic overload. This heightened stress can impair social cognitive functions like empathy, perspective-taking, and emotional regulation, intertwined with brain alterations. A survival-oriented focus may also influence the diminished capacity for prosocial behaviors in low SES contexts, where immediate needs take precedence over social considerations.

 A pioneering study involving 1,063 older adults across nine countries demonstrated the profound influence of diversity on social cognition (Fig 1). Using computational methods, we found that factors like cognitive/executive functions, education, and income were more predictive of social cognition abilities than age, diagnosis, or brain reserve (brain volume and network connectivity). Income (measured at the country level) influenced social cognition in some models. These findings challenge traditional views on the decline of social cognition with age, emphasizing the need to consider various factors, including cultural and demographic diversity.

 

Fig. 1: Analysis pipeline and traditional effects of age and diagnosis on social cognition performance. a, (i) Participants were recruited from HICs (Chile, France, Italy and the United Kingdom) and UMICs (Argentina, Brazil, Colombia, Peru and Mexico) through ReDLat, the INSCD and GERO. (ii) Diagnosis, demographics, cognition, gray matter volume (vol) and fMRI resting-state functional connectivity of brain networks, and in-scanner motion artifacts were entered into computational models as predictors of social cognition. (iii) Data were harmonized across countries (including scale transformation) and missing values were imputed. (iv) The analysis involved Bayesian optimization with k = 3 cross-validation for tuning the hyperparameters in 70:30 train and test partitioning and SVR models using a bootstrap approach. (v) Outcome variables were facial emotion recognition, mentalizing and a social cognition total score from the mini-SEA battery. Emotion recognition image was reproduced from ref. 118. b, age significantly predicted worse performance in emotion recognition, mentalizing and the total score across the full sample (n = 998). Data were analyzed with simple linear regression analysis. Red lines and gray shadings represent the best-fit line for each simple linear regression with 95% confidence bands. **P < 0.0001 (for details, see Extended Data Table 1). c, Participants with MCI (n = 96), AD (n = 339) and bvFTD (n = 102) performed significantly worse in social cognition relative to HCs (n = 316) and the SCC group (n = 145), and participants with bvFTD also performed significantly worse than those with AD in emotion recognition. Data were analyzed with linear mixed-effects models controlling for sex, age, education, and country of origin. The red dots and lines display the mean and s.d. 

Towards diversity- and disparity-oriented agendas

 Integrating diversity, disparity, and heterogeneity in research is crucial for the future of social neuroscience, aging research,  and brain health. Researchers should start to create theoretical models that embrace diversity across different biological, cognitive, and social levels to understand the complexities of social cognition truly. Embracing diversity in scientific research is not just about being inclusive; it is about enriching our understanding of human cognition and brain health in a way that more genuinely reflects our real world.

Note: The poster image was designed using a generative artificial intelligence program (GPT4 and DALL-E) supervised by the authors of this post .

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Social Inequality
Humanities and Social Sciences > Society > Sociology > Social Structure > Social Inequality
Neuroscience
Life Sciences > Biological Sciences > Neuroscience
Brain
Life Sciences > Biological Sciences > Anatomy > Nervous System > Brain
Dementia
Life Sciences > Biological Sciences > Neuroscience > Neurological Disorders > Dementia
Social Cognition
Humanities and Social Sciences > Behavioral Sciences and Psychology > Social Psychology > Social Cognition
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