Individuals are motivated to increase their social status. To succeed in this pursuit, people must track information about others in their social sphere, monitor group norms, and adjust their behavior strategically. This study employed functional MRI and ecological momentary assessment methods in a sample of 92 college students belonging to 9 social groups to elucidate the neural mechanisms underlying these processes and their relationship to conformity in the context of alcohol use. When young adults passively looked at faces of their real-life social group peers, brain systems implicated in valuation and social cognition spontaneously tracked information about the popularity and leadership status of the social targets in an interdependent manner. Individual differences in these neural valuations were systematically associated with varying levels of conformity. Students who had stronger responses to faces of peers with relatively higher popularity and leadership status than themselves in one key valuation brain region, the ventromedial prefrontal cortex (vmPFC), were more likely to align their drinking behavior with their groups' norms in everyday life. These results provide evidence for how brain systems involved in valuation and social cognition flexibly track information about peers' popularity and leadership status in real-life social groups and contribute to a growing literature on the neural mechanisms through which social comparison processes shape conformity. Our study highlights the vmPFC as a central hub that spontaneously tracks status differences between the self and peers and uses this information to guide behavior to match group norms.

Digital interventions can change behaviors like alcohol use, but effectiveness varies widely across individuals. Accurately identifying non-responders—i.e., those least (vs. most) likely to change their behavior—before intervention delivery is difficult. Individual intervention effectiveness predictions from prior studies perform only slightly above chance (e.g., AUC ≈0.60; balanced accuracy ≈0.60). We present a novel approach integrating multimodal data across theory-driven domains—including psychological assessments, social network data, and neural responses to alcohol cues—to make ex-ante predictions about the effectiveness of smartphone-delivered alcohol interventions targeting psychological distancing in young adults (Study 1: N = 67; Study 2: N = 114). Demonstrating the feasibility of this approach, random forest models predicted individual differences in intervention effectiveness (Study 1: balanced accuracy = 0.71, 95% CI: 0.69–0.73, p = .020; AUC = 0.87, 95% CI: 0.85–0.88, p = .020) and replicated in a an external test sample (Study 2, balanced accuracy = 0.68; AUC = 0.68, 95% CI: 0.54–0.82), meeting clinical-utility thresholds from prior digital health studies (balanced accuracy = 0.67; correctly classifying (non)responders 67% of the time). Interventions were most effective for participants who perceived their peers as moderate but frequent drinkers. Peer drinking perceptions may serve as a low-burden indicator to support early identification of non-responders in preventive alcohol interventions among young adults. Future work can apply and extend the multimodal approach developed here for adaptive tailoring of digital behavior change interventions in real-world settings.

Developing interventions to change health behaviors—especially those targeting cross-cutting health risk factors like alcohol use—is a public health priority. In this study, we used a translational neuroscience approach to evaluate the underlying mechanisms and individual differences in a mindful distancing intervention designed to reduce alcohol consumption among college students. We combined functional neuroimaging and machine learning to develop a brain-based predictive model (a “neural signature”) of mindful distancing. This model allowed us to track moment-to-moment variation in how participants implemented the strategy, as well as differences between individuals. Students completed a mindful distancing task involving alcohol cues during fMRI scanning. They then completed a 28-day, smartphone-based, experience sampling intervention. In the laboratory, mindfully attending to alcohol decreased craving, particularly among people who more strongly expressed the mindful distancing signature. In daily life, the mindful distancing intervention increased mindful responses to alcohol and decreased subsequent alcohol consumption through two distinct pathways: mindful responses directly influenced alcohol consumption and indirectly influenced it by reducing cravings for alcohol. Individuals with stronger expression of the neural signature experienced the greatest benefits from the intervention. These findings extend theoretical models of how mindfulness-based emotion regulation strategies impact alcohol use in emerging adults without alcohol use disorders. They also demonstrate the potential of using neural signatures to evaluate health behavior change interventions within a translational neuroscience framework.

Cognitive control is a suite of processes that helps individuals pursue goals despite resistance or uncertainty about what to do. Deficits of cognitive control underlie compulsive or risky behavior, as well as other clinical challenges associated with difficulties in regulating impulses, attention, thoughts, and feelings. Although cognitive control has been extensively studied as a dynamic feedback loop of perception, valuation, and action, it remains incompletely understood as a cohesive dynamic and distributed neural process. Here, we critically examine the history of and advances in the study of cognitive control, including how metaphors and cultural norms of power, morality, and rationality are intertwined with definitions of control, to consider holistically how different models explain which brain regions act as controllers. Controllers, the source of top-down signals, are typically localized in regions whose neural activations implement elementary component processes of control, including conflict monitoring and behavioral inhibition. Top-down signals from these regions guide the activation of other task-specific regions, biasing them towards task-specific activity patterns. A relatively new approach, network control theory, has roots in dynamical systems theory and systems engineering. This approach can mathematically show that controllers are regions with strongly nested and recurrent anatomical connectivity that efficiently propagate top-down signals, and precisely estimate the amount, location, and timing of signaling required to bias global activity to task-specific patterns. Importantly, the theory converges with established findings, provides new mathematical tools and intuitions for understanding control loops across levels of analysis, and naturally produces graded predictions of control across brain regions and modules of psychological function that have been unconsidered, marginalized, or indirectly linked. We describe how psychological and network control approaches converge and diverge, noting directions for future integration that could strengthen and sharpen our understanding and predictions of how the brain instantiates cognitive control.

In times of high stress, support from our social networks is essential. This paper tested the influence of close friendships on young adults’ well-being in the early months of the COVID-19 pandemic (May-October 2020). In a longitudinal study of 28 days (N = 205 participants; 10,088 observations), students with more close friends in college, as reported pre-pandemic, adjusted better to COVID-19 stressors, even when away from campus. Follow-up analyses revealed that this effect could be partially explained by differences in the quality of significant online conversations. Students with many close friends in college benefited equally from important in-person and online conversations. In contrast, those with few close friends experienced higher negative affect and lower positive affect on days when their most important interactions were online vs. in-person. Participants’ number of friends was uncorrelated with their number of online interactions or personality traits. Our intensive longitudinal design also permitted investigation, within individuals, of how online vs. in-person interactions led to feelings of closeness. Personal disclosures emerged as the base of closeness in both types of communications; all participants felt closer to their interaction partners when one of them shared something personal, regardless of whether the interaction took place in-person or online. This effect was stronger for those with few close friends, suggesting that individuals can foster connection in everyday interactions by allowing themselves—and inviting others—to be vulnerable. This research leveraged social network and longitudinal methods to highlight how young adults coped with the COVID-19 pandemic through their friendship networks.

Studies on college drinking-a behavior associated with health risks and reduced productivity-often rely on broadly defined peer or friendship networks. Yet, friendship networks can be further divided into more specific relational types, and the associations between such diverse social ties and drinking ties remain poorly understood. This study adopts a multilayer network framework to conduct a fine-grained examination of ten distinct types of social networks (i.e., layers)-including friendship, leadership, emotional support, and perceived drinking-by analyzing their structural similarity across three levels (node, link, and triad) and along a relationship-axis spectrum. We cluster networks based on these multi-level similarities, identifying three primary clusters (Affiliation, Leadership, and Drinking) and assess whether these structurally coherent clusters contribute to improved link prediction performance in perceived drinking networks. Both k-means clustering based on multi-level structural similarity and projection-based analysis along the hierarchical-horizontal spectrum revealed that perceived drinking nominations are structurally closest to leadership layers, followed by emotional support layers within the Affiliation cluster. Assessing whether these functional clusters can improve link prediction in perceived drinking networks, we find that layers within the same cluster yield predictive performance close to that of models using all layers. Notably, emotional support layers, which may reflect their structural proximity and distributed connectivity, offer the highest link prediction accuracy for drinking ties. Taken together, these findings demonstrate that coherent clusters of fine-grained, functionally and structurally aligned social layers facilitate more efficient inference in sparse or partially observed drinking-related networks. This, in turn, highlights their potential utility in predicting and preventing health-risk behaviors-such as alcohol use-that are typically difficult to observe or measure directly, and clarifies the types of relationships most strongly associated with such behaviors.

Social interactions are fundamental to human well-being. Much of what people invest time, energy, and money in revolves around connecting with others. Yet many people still feel lonely, increasing their risk for poor sleep quality, depression, and mortality. Identifying underlying mechanisms of loneliness is key to developing efficient interventions. Here, we used neuroimaging to investigate how multivariate patterns of functional connectivity between and within brain systems relate to loneliness. We developed a neural signature of loneliness from distributed patterns of resting-state functional connectivity in the Human Connectome Project (HCP) dataset. We then demonstrate the generalizability of this neural signature in predicting individual differences in loneliness in an independent sample of young adult students. Our results reveal that functional connectivity between sensory systems and higher-order process networks (frontoparietal control and default networks) is a key feature of how loneliness is instantiated in the brain. Finally, this neural signature appears to be specific for loneliness, as it was not predictive of other closely related measures of social connection or negative affect. Overall, this work offers a neural marker that could be used across new datasets, and suggests key brain systems to target with future interventions.

Conversations shape future behaviors, particularly among young adults. However, young adults vary widely in their susceptibility to peer influence. What neural processes relate to this susceptibility? We examined whether activity in brain regions associated with social rewards and making sense of others’ minds relates to a common health behavior—drinking, following conversations about alcohol. We studied ten social groups of college students (N = 104 students; 4760 total observations) across two university campuses. We collected whole-brain fMRI data while participants viewed photographs of peers with whom they tended to drink at varying frequencies. Next, using ecological momentary assessment, we tracked alcohol conversations and drinking twice daily for 28 days. On average, talking about alcohol was associated with a higher likelihood of next-day drinking. Controlling for baseline drinking, participants who responded more strongly to peers with whom they drank alcohol more frequently—in brain regions associated with social rewards and mentalizing—showed a stronger, positive association between alcohol conversations and next-day drinking. Conversely, stronger neural responses to peers with whom they drank less frequently decoupled associations between alcohol conversations and next-day drinking. We conceptually replicate prior findings linking conversations and drinking in an observational, longitudinal setting and provide new evidence that neural responses to peers moderate links between alcohol conversations and drinking behavior among young adults.

It is critical to support healthy development of alcohol-related habits, particularly in contexts with heightened risk such as college campuses. Mindfulness-based strategies are frequently used in interventions to reduce substance use in clinical populations, but their utility as a preventative strategy among emerging adults is less clear. Combining multivariate neuroimaging, intervention, and experience sampling methodologies, we tested the degree to which mindful attention reduces alcohol cravings in the laboratory and consumption in daily life in a sample of college students. Students completed a mindful attention task towards alcohol in an fMRI scanner followed by a 28-day, smartphone-based, experience sampling intervention. We leveraged functional neuroimaging and machine learning to develop a neural measure (signature) of mindful attention that enabled us to examine moment-to-moment fluctuations and individual differences in effective implementation of mindful attention. In the laboratory, mindfully attending to alcohol decreased craving, particularly among people who more strongly expressed the mindful attention signature. In daily life, the mindful attention intervention increased mindful responses to alcohol and decreased lagged alcohol consumption through two distinct pathways: mindful responses directly influenced alcohol consumption and indirectly influenced it by reducing cravings for alcohol. Moreover, individuals who more strongly expressed the mindful attention signature benefitted the most from the intervention. Broadly, our study highlights how mindful attention can reduce alcohol consumption among emerging adults in college via a scalable smartphone-based intervention.

Mindful attention is characterized by acknowledging the present experience as a transient mental event. Early stages of mindfulness practice may require greater neural effort for later efficiency. Early effort may self-regulate behavior and focalize the present, but this understanding lacks a computational explanation. Here we used network control theory as a model of how external control inputs-operationalizing effort-distribute changes in neural activity evoked during mindful attention across the white matter network. We hypothesized that individuals with greater network controllability, thereby efficiently distributing control inputs, effectively self-regulate behavior. We further hypothesized that brain regions that utilize greater control input exhibit shorter intrinsic timescales of neural activity. Shorter timescales characterize quickly discontinuing past processing to focalize the present. We tested these hypotheses in a randomized controlled study that primed participants to either mindfully respond or naturally react to alcohol cues during fMRI and administered text reminders and measurements of alcohol consumption during 4 wk postscan. We found that participants with greater network controllability moderated alcohol consumption. Mindful regulation of alcohol cues, compared to one's own natural reactions, reduced craving, but craving did not differ from the baseline group. Mindful regulation of alcohol cues, compared to the natural reactions of the baseline group, involved more-effortful control of neural dynamics across cognitive control and attention subnetworks. This effort persisted in the natural reactions of the mindful group compared to the baseline group. More-effortful neural states had shorter timescales than less effortful states, offering an explanation for how mindful attention promotes being present.

Evidence on the harms and benefits of social media use is mixed, in part because the effects of social media on well-being depend on a variety of individual difference moderators. Here, we explored potential neural moderators of the link between time spent on social media and subsequent negative affect. We specifically focused on the strength of correlation among brain regions within the frontoparietal system, previously associated with the top-down cognitive control of attention and emotion. Participants (N = 54) underwent a resting state functional magnetic resonance imaging scan. Participants then completed 28 days of ecological momentary assessment and answered questions about social media use and negative affect, twice a day. Participants who spent more than their typical amount of time on social media since the previous time point reported feeling more negative at the present moment. This within-person temporal association between social media use and negative affect was mainly driven by individuals with lower resting state functional connectivity within the frontoparietal system. By contrast, time spent on social media did not predict subsequent affect for individuals with higher frontoparietal functional connectivity. Our results highlight the moderating role of individual functional neural connectivity in the relationship between social media and affect.

Modifying behaviors, such as alcohol consumption, is difficult. Creating psychological distance between unhealthy triggers and one's present experience can encourage change. Using two multisite, randomized experiments, we examine whether theory-driven strategies to create psychological distance-mindfulness and perspective-taking-can change drinking behaviors among young adults without alcohol dependence via a 28-day smartphone intervention (Study 1, N = 108 participants, 5492 observations; Study 2, N = 218 participants, 9994 observations). Study 2 presents a close replication with a fully remote delivery during the COVID-19 pandemic. During weeks when they received twice-a-day intervention reminders, individuals in the distancing interventions reported drinking less frequently than on control weeks-directionally in Study 1, and significantly in Study 2. Intervention reminders reduced drinking frequency but did not impact amount. We find that smartphone-based mindfulness and perspective-taking interventions, aimed to create psychological distance, can change behavior. This approach requires repeated reminders, which can be delivered via smartphones.

BACKGROUND AND AIM:Alcohol craving is an urge to consume alcohol that commonly precedes drinking; however, craving does not lead to drinking for all people under all circumstances. The current study measured the correlation between neural reactivity and alcohol cues as a risk, and purpose in daily life as a protective factor that may influence the link between alcohol craving and the subsequent amount of consumption.DESIGN:Observational study that correlated functional magnetic resonance imaging (fMRI) data on neural cue reactivity and ecological momentary assessments (EMA) on purpose in life and alcohol use.SETTING:Two college campuses in the United States.PARTICIPANTS:A total of 54 college students (37 women, 16 men, and 1 other) recruited via campus-based groups from January 2019 to October 2020.MEASUREMENTS:Participants underwent fMRI while viewing images of alcohol; we examined activity within the ventral striatum, a key region of interest implicated in reward and craving. Participants then completed 28 days of EMA and answered questions about daily levels of purpose in life and alcohol use, including how much they craved and consumed alcohol.FINDINGS:A significant three-way interaction indicated that greater alcohol cue reactivity within the ventral striatum was associated with heavier alcohol use following craving in daily life only when people were previously feeling a lower than usual sense of purpose. By contrast, individuals with heightened neural alcohol cue reactivity drank less in response to craving if they were feeling a stronger than their usual sense of purpose in the preceding moments (binteraction  = -0.086, P < 0.001, 95% CI = -0.137, -0.035).CONCLUSIONS:Neural sensitivity to alcohol cues within the ventral striatum appears to be a potential risk for increased alcohol use in social drinkers, when people feel less purposeful. Enhancing daily levels of purpose in life may promote alcohol moderation among social drinkers who show relatively higher reactivity to alcohol cues.

Background: The waxing and waning of negative affect in daily life is normative, reflecting an adaptive capacity to respond flexibly to changing circumstances. However, understanding of the brain structure correlates of affective variability in naturalistic settings has been limited. Using network control theory, we examine facets of brain structure that may enable negative affect variability in daily life.Methods: We use diffusion weighted imaging data from 95 young adults (Mage = 20.19 years, SDage = 1.80; 56 women) to construct structural connectivity networks that map white matter fiber connections between 200 cortical and 14 sub-cortical regions. We apply network control theory to these structural networks to estimate the degree to which each brain region’s pattern of structural connectivity facilitates the spread of activity to other brain systems. We examine how the average controllability of functional brain systems relates to negative affect variability, computed by taking the standard deviation of negative affect self-reports collected via smartphone-based experience-sampling twice per day over 28 days as participants went about their daily lives. Results: We find that high average controllability of the cingulo-insular system is associated with increased negative affect variability. We find that greater negative affect variability is related to the presence of more depressive symptoms, yet average controllability of the cingulo-insular system was not associated with depressive symptoms. Conclusions: Our results highlight the role brain structure plays in affective dynamics as observed in the context of daily life, suggesting that average controllability of the cingulo-insular system promotes normative negative affect variability.