Periodic Reporting for period 1 - SOCIALCRAVING (Towards a social neuroscience of health-related decision-making)
Reporting period: 2023-01-01 to 2025-06-30
Social context has important effects on behavior, experience, and health outcomes. Our interactions with others, feelings of social isolation versus connection, and perceived social norms influence behavior, physiology, and even mortality. Yet, the brain mechanisms that mediate the effects of social relationships and social influence on health-related decision-making are still not well understood. The SOCIALCRAVING project uses a combination of brain imaging, machine learning, and an interdisciplinary approach to better understand how social influence and social relationships alter food and alcohol craving and modulate health-related decision-making more broadly. The first work package (WP1) will characterize the effects of social ratings on a recently developed machine-learning-based brain signature of food and drug craving (the Neurobiological Craving Signature or NCS, Koban, et al., 2023), and test for generalization of social influence effects across modalities and food items. The second WP will characterize the effects of social relationships (e.g. rejection versus acceptance) on food and alcohol craving, NCS responses, and health-related decision-making. Finally, the third WP will develop a novel brain signature of social craving, to assess its relationship with the NCS and to test whether it moderates social context effects on health. By uncovering the brain bases of social context effects, the SOCIALCRAVING project aims at transforming 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.
Since its start, the SOCIALCRAVING project has already led to several promising and novel results as well as preprints and manuscripts in preparation for publication. Across multiple studies, we could show that abstract social information—in the form of “other people’s” ratings—influence self-reported wanting and willingness-to-pay for snack food items. These behavioral effects are paralleled by an effect on an a priori defined neurobiological marker of food and drug craving—the Neurobiological Craving Signature (or NCS, Koban, et al., 2023). In addition, high compared to low social ratings increased activity in the left temporoparietal junction, a brain area often associated with social cognition and mentalizing. This led us to hypothesize that social influence effects on the NCS are driven by activation of social cognitive brain processes. We therefore developed and tested a novel brain signature of self- and other-referential thought (or self- and other-related ‘mentalizing’) and found that responses of this mentalizing-related brain signature were significantly increased for high social ratings and in turn predicted increased NCS (i.e. craving-related) brain responses. This suggests an interplay between brain areas involved in social cognition and those in craving and valuation.
We also found evidence for the idea that social influence effects can generalize beyond specific observations. In three different behavioral studies, our results show that people implicitly learn about the underlying norms that drive others’ food choices, such as the norm to prefer healthier (versus less healthy) food items: When exposed to social ratings that are driven by healthiness of food items, people become also more ‘health-driven’ over time even when choosing new food items (Chene et al., 2024 preprint). In our upcoming experiments, we will use fMRI to investigate the brain mechanisms underlying conceptual generalization of social influence effects on food and health-related decision-making.
Further, we have re-analyzed an existing dataset as an initial validation of our hypothesis of partially shared and potentially interacting brain patterns underlying food and drug craving on the one hand and social craving—our motivation for social connection and meaningful interactions with other people—on the other hand. Our results show that the NCS, which was trained to predict food and drug craving, also significantly predicts the degree to which participants crave social contact. In line with this finding, we further observed that NCS responses to social cues were increased after a brief social isolation manipulation. As the next step, we will use machine-learning to train and validate a novel brain signature of social craving, and to test how it relates to self-reported and physiological markers of health.
Foundational for this project, we have also built and validated a new stimuli database of foods, beverages, social scenes, and other activities to evoke different degrees of food, alcohol and ‘social’ craving. These stimuli are used in ongoing and planned behavioral and brain imaging studies. We are also currently exploring this database regarding potential associations between visual features, cue-evoked craving, and individual health-related lifestyle.
In addition to this research at the core of the SOCIALCRAVING project, we have also been involved in related work, including on the interaction between dietary factors and social decision-making (Falkenstein et al., 2024), in developing a structural brain signature of impulsivity (Godefroy et al., 2024 preprint) that we use as an person-level covariate in our ongoing studies, and in testing the effects of different regulation strategies on craving-related brain responses (e.g. Rodrigues et al., 2023 preprint).
We also found evidence for the idea that social influence effects can generalize beyond specific observations. In three different behavioral studies, our results show that people implicitly learn about the underlying norms that drive others’ food choices, such as the norm to prefer healthier (versus less healthy) food items: When exposed to social ratings that are driven by healthiness of food items, people become also more ‘health-driven’ over time even when choosing new food items (Chene et al., 2024 preprint). In our upcoming experiments, we will use fMRI to investigate the brain mechanisms underlying conceptual generalization of social influence effects on food and health-related decision-making.
Further, we have re-analyzed an existing dataset as an initial validation of our hypothesis of partially shared and potentially interacting brain patterns underlying food and drug craving on the one hand and social craving—our motivation for social connection and meaningful interactions with other people—on the other hand. Our results show that the NCS, which was trained to predict food and drug craving, also significantly predicts the degree to which participants crave social contact. In line with this finding, we further observed that NCS responses to social cues were increased after a brief social isolation manipulation. As the next step, we will use machine-learning to train and validate a novel brain signature of social craving, and to test how it relates to self-reported and physiological markers of health.
Foundational for this project, we have also built and validated a new stimuli database of foods, beverages, social scenes, and other activities to evoke different degrees of food, alcohol and ‘social’ craving. These stimuli are used in ongoing and planned behavioral and brain imaging studies. We are also currently exploring this database regarding potential associations between visual features, cue-evoked craving, and individual health-related lifestyle.
In addition to this research at the core of the SOCIALCRAVING project, we have also been involved in related work, including on the interaction between dietary factors and social decision-making (Falkenstein et al., 2024), in developing a structural brain signature of impulsivity (Godefroy et al., 2024 preprint) that we use as an person-level covariate in our ongoing studies, and in testing the effects of different regulation strategies on craving-related brain responses (e.g. Rodrigues et al., 2023 preprint).
The SOCIALCRAVING project aims to go beyond the state of the art in several aspects. First, by using an interdisciplinary approach and by integrating social, psychological, and neurobiological levels of analyses, the project will identify the brain interface between social context factors and health-related decision-making. Second, a key methodological innovation is to use an independently established, machine-learning-based neuromarker—the Neurobiological Craving Signature—as a main neurobiological target of social context effects on craving and health-related decision-making, and to develop new, replicable brain signatures of social craving and other important social and affective processes (such as the mentalizing signature mentioned above), which can then be targeted in future studies. We expect that this project will lead to a new level of understanding of social and contextual effects on physiology and health outcomes, thereby inspiring better prevention and intervention strategies to improve health outcomes in Europe and worldwide.