Summary
Social relationships have important effects on health and disease. Our interactions with others, feelings of social isolation versus connection, and perceived social norms influence behavior, physiology, and even mortality. Yet, an ongoing challenge is to understand the brain mechanisms underlying social context effects on human health, which could ultimately enable us to use neuroimaging to predict psychosocial risk factors and individual vulnerability to unhealthy lifestyle. I propose to address this challenge, by testing how social norms and social relationships influence food and alcohol craving and health-related decision-making. Paralleling my recently developed brain signature of food and drug craving, I predict that I can develop a brain signature of social craving—our unfulfilled need for social contact—using fMRI and machine learning, and that responses of this signature are associated with increased susceptibility to social context effects on decision-making and health. Work package (WP)1 will test the effects of social influence on food craving, drink craving, and delay discounting, and whether social influence effects generalize across tasks. WP2 will test whether and how social rejection versus connection increases food and drink craving, delay discounting, and social craving. WP3 will use machine-learning to develop a new neurophysiological signature of social craving and use data from all WPs to investigate whether responses of this social craving signature are associated with 1) susceptibility to social influence, 2) social rejection effects on decision-making, and 3) aggregate measures of lifestyle, mental, and physical health. By uncovering the brain bases of social context effects, the SOCIALCRAVING project will transform our understanding of the neurophysiology underlying craving and health-related decision-making and allow for a new level of brain-based prediction of individual vulnerability to psychosocial risks and negative health outcomes.
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| Web resources: | https://cordis.europa.eu/project/id/101041087 |
| Start date: | 01-01-2023 |
| End date: | 31-12-2027 |
| Total budget - Public funding: | 1 491 166,00 Euro - 1 491 166,00 Euro |
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Original description
Social relationships have important effects on health and disease. Our interactions with others, feelings of social isolation versus connection, and perceived social norms influence behavior, physiology, and even mortality. Yet, an ongoing challenge is to understand the brain mechanisms underlying social context effects on human health, which could ultimately enable us to use neuroimaging to predict psychosocial risk factors and individual vulnerability to unhealthy lifestyle. I propose to address this challenge, by testing how social norms and social relationships influence food and alcohol craving and health-related decision-making. Paralleling my recently developed brain signature of food and drug craving, I predict that I can develop a brain signature of social craving—our unfulfilled need for social contact—using fMRI and machine learning, and that responses of this signature are associated with increased susceptibility to social context effects on decision-making and health. Work package (WP)1 will test the effects of social influence on food craving, drink craving, and delay discounting, and whether social influence effects generalize across tasks. WP2 will test whether and how social rejection versus connection increases food and drink craving, delay discounting, and social craving. WP3 will use machine-learning to develop a new neurophysiological signature of social craving and use data from all WPs to investigate whether responses of this social craving signature are associated with 1) susceptibility to social influence, 2) social rejection effects on decision-making, and 3) aggregate measures of lifestyle, mental, and physical health. By uncovering the brain bases of social context effects, the SOCIALCRAVING project will transform our understanding of the neurophysiology underlying craving and health-related decision-making and allow for a new level of brain-based prediction of individual vulnerability to psychosocial risks and negative health outcomes.Status
SIGNEDCall topic
ERC-2021-STGUpdate Date
09-02-2023
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