Journal
WILEY INTERDISCIPLINARY REVIEWS-COGNITIVE SCIENCE
Volume 12, Issue 6, Pages -Publisher
WILEY
DOI: 10.1002/wcs.1571
Keywords
decision neuroscience; drift diffusion models; prosociality; social affect and cognition (theory of mind); social choice tasks
Categories
Funding
- National Institute of Mental Health Conte Center [2P50 MH094258]
- Natural Sciences and Engineering Research Council of Canada [RGPIN-2019-04329]
- Canada Foundation for Innovation [38812]
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This article discusses how computational models and social neuroscience can be used to study altruistic decision-making and other-regard motivations. It introduces theoretical and methodological tools, outlines relevant mental and neural processes, and emphasizes the importance of integrating different social processes for model and intervention development.
This article discusses insights from computational models and social neuroscience into motivations, precursors, and mechanisms of altruistic decision-making and other-regard. We introduce theoretical and methodological tools for researchers who wish to adopt a multilevel, computational approach to study behaviors that promote others' welfare. Using examples from recent studies, we outline multiple mental and neural processes relevant to altruism. To this end, we integrate evidence from neuroimaging, psychology, economics, and formalized mathematical models. We introduce basic mechanisms-pertinent to a broad range of value-based decisions-and social emotions and cognitions commonly recruited when our decisions involve other people. Regarding the latter, we discuss how decomposing distinct facets of social processes can advance altruistic models and the development of novel, targeted interventions. We propose that an accelerated synthesis of computational approaches and social neuroscience represents a critical step towards a more comprehensive understanding of altruistic decision-making. We discuss the utility of this approach to study lifespan differences in social preference in late adulthood, a crucial future direction in aging global populations. Finally, we review potential pitfalls and recommendations for researchers interested in applying a computational approach to their research. This article is categorized under: Economics > Interactive Decision-Making Psychology > Emotion and Motivation Neuroscience > Cognition Economics > Individual Decision-Making
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