Chelsea Helion

Moral disagreements are common in interpersonal relationships, yet people vary widely in how they respond to them–from avoiding interaction and keeping silent, to finding common ground, persuading others, or updating belief. The present work examines whether emotion regulation (ER) can systematically predict how individuals choose among these responses when facing disagreements. Across three online studies (total N = 892), participants reported their likelihood of using eleven response strategies in hypothetical disagreement scenarios. Response strategies formed meaningful clusters that reflect different regulatory approaches: disengaging from disagreement, attempting to resolve it, or accommodating opposing views. In turn, these response categories were systematically predicted by individual differences in trait ER (e.g., reappraisal, avoidance) as well as situation-specific appraisals of the moral, relational, and social stakes of disagreement. Together, these findings indicate that ER provides a useful lens for understanding interpersonal moral disagreements.

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.

Social connection is important for physical and mental health across the lifespan. Friendships are a critical source of social connection that rely on effective interpersonal support. Emotion categories (e.g., happiness, disgust) serve to efficiently communicate internal states to others, but how does individual variation in these conceptual representations impact social connectivity? In a longitudinal social network sample of first-year university students, we investigated whether representing emotions more similarly to others predicts friendship accuracy, a foundation for forging social connection and effectively recruiting social support. We also explore relationships between friendship accuracy and markers of physical and mental wellbeing. We found that emotional normativity was predictive of friendship accuracy over time, which in turn was associated with social network centrality, reduced anxiety, and higher resting heart rate variability, a marker of reduced stress. Taken together, emotional normativity may play an important role in social connection and wellbeing, particularly during early adulthood.

Fairness decisions often integrate affective responses within a social context, yet emotion regulation in this literature has been largely studied as a self-directed process rather than an interpersonal one. We examined how individual differences in other-directed emotion regulation—measured with the Emotion Regulation of Others and Self (EROS) scale—relate to behavioral and neural responses during fairness decisions in 138 adults completing a variant of the Ultimatum Game with human and computer partners during fMRI. Behaviorally, participants who more strongly endorsed worsening others’ emotions rejected unfair offers more frequently, and this tendency interacted with offer fairness to amplify rejection of unfair offers. At the neural level, the left anterior insula tracked offer unfairness more strongly in social versus nonsocial contexts, consistent with sociality modulating the neural encoding of fairness. Right dlPFC activation during socially unfair offers was greater among individuals who preferred to improve others’ emotions. Connectivity analyses revealed that social fairness sensitivity predicted stronger amygdala–orbitofrontal and amygdala–dmPFC coupling; the latter was further amplified among individuals higher in other-directed emotion worsening. Together, these findings identify interpersonal emotion regulation as an understudied source of variation in the affective and prefrontal systems supporting fairness-based social decisions.

The ability to influence our emotional states, also known as emotion regulation, is an important indicator of psychological health. However, the techniques to do so vary not only in difficulty to learn, but difficulty to implement effectively. Curiosity, on the other hand, is generally associated with positive affect, intrinsic motivation, and intrinsic reward. These qualities make curiosity an excellent candidate as an emotion regulation technique that may be equally as effective as cognitive methods of emotion regulation while being less effortful. To test this, we conducted a series of three studies designed to evaluate whether curiosity serves as an efficacious and minimally effortful method of emotion regulation. Participants were prompted to create idiographic scenarios designed to increase negative affect before being briefly instructed on one of three emotion regulation techniques: upregulation, downregulation, and curiosity. Participants applied each of these techniques to the imagined scenarios before rating the techniques various measures of efficacy. We found that participants endorsed curiosity as effectively reducing negative affect relative to the upregulation control. Notably, curiosity was also endorsed as a lower effort method of emotion regulation relative to downregulation. This is the first study to demonstrate that curiosity can be used as a form of emotion regulation that is equally efficacious to, yet less effortful than, downregulation.

Continuous self-report during ongoing experience provides a high-resolution window into subjective processing, yet concerns that it may disrupt the neural and cognitive processes being measured have limited its use in neuroimaging. We tested this by examining how expressing metacognitive judgment influences neural activity and behavior during complex social inference. Thirty-five participants underwent fMRI while watching an episode of a murder-mystery show and evaluating their certainty of a central character’s guilt. Participants continuously rated their certainty during one half of the episode (expressive metacognition) and viewed the other half without providing ratings (reflective metacognition), followed by surprise free recall and character evaluations. Expressive metacognition increased activation across salience, dorsal attention, and control networks, including medial frontal, parietal, and lateral prefrontal regions, whereas reflective metacognition yielded greater activation within a single anterior vmPFC cluster. The two conditions were also associated with increased intersubject synchrony in control and default mode networks, respectively. Despite these differences, they did not differ in which or how many scenes were recalled, recall order, or socioemotional character judgments, indicating that core aspects of episodic organization and social evaluation remain intact. However, expressive metacognition yielded greater episodic detail in recall. These findings show that expressing judgments reshapes neural processing and shared responses while leaving many downstream outcomes unchanged. supporting continuous self-report as a viable tool for studying dynamic cognition in naturalistic settings, provided its engagement of attention and control networks aligns with the research question.

Effective social support can benefit recipients, but it can be challenging to give. Determining what type of support will be most effective, for whom, and when, is a multi-pronged calculation that providers execute while balancing personal goals, motivations, and current resources. Prior research outlines support providers’ traits and methods that may improve support-giving, but the internal and psychological processes that underlie optimal support provision remain unclear. Here, we argue that self-regulation plays a critical and understudied role in giving effective social support. We leverage research on self-regulatory processes to examine how they influence effective support provision. We propose that support providers must first evaluate their aims and prioritize relational goals with recipients, and next utilize self-regulatory processes (e.g., effort, cognitive control) to understand recipient’s goals and deliver support. More effective self-regulation may enhance support exchanges for all involved. This framework generates testable research questions on how people give optimal support.

Conversations are intricately structured forms of social interaction in which talkers move through interconnected topics with nested levels of semantic specificity. What principles govern how conversational partners jointly navigate an expansive topic space? To characterize these dynamics, we introduce a new dataset of annotated topic shifts from N=1,505 annotators on 200 distinct video call conversations between strangers (Reece et al., 2023). Conversational dyads made stochastic but systematic transitions between topics, and within individual topics, we find that dyads begin concentrated in semantic space before dispersing to more idiosyncratic regions as topics progress. The same dispersion pattern also holds over entire conversations, providing quantitative evidence for nested levels of increasing specificity over conversations. Overall, our findings suggest that strangers get to know one another through systematic exploration of topic space, revealing hierarchical structure in idle talk.

Much of our understanding of language processing has been informed by controlled laboratory experiments abstracted from the real world demands of naturalistic communication. Interactive language use “in the wild” involves synchronizing numerous verbal and non-verbal behaviors between interlocutors. Conversation partners synchronize verbal production through modulations of rate, amplitude, lexical-semantic complexity, affective tone, and many other dimensions. Much remains to be learned about how to measure linguistic alignment in naturalistic interactions. We developed an open-source R package (ConversationAlign) capable of computing novel indices of alignment and main effects of language use between interlocutors across 30 psycholinguistic dimensions (e.g., valence, concreteness, frequency, word length). We describe operations of the ConversationAlign workflow, including its primary functions of cleaning transcripts and transforming raw language data to simultaneous time series objects aggregated by interlocutor, turn, and conversation. We present a use case of ConversationAlign applied to interview transcripts between American radio legend, Terry Gross, and her many guests over the span of 15 years (Fresh Air Archive, 2001). We identify caveats for use and potential sources of bias (e.g., polysemy, missing data, robustness to brief language samples). We close with a discussion of potential applications to better understand lexical alignment. ConversationAlign is freely available for download and use via GitHub at https://github.com/Reilly-ConceptsCognitionLab/ConversationAlign

Our earliest acquired words tend to reference concrete objects that can be seen, heard, touched, and felt. One hallmark of language maturation involves an ‘abstractness shift’ where language is used to convey intangible mental states, emotions, and ideas. Much of our understanding of the trajectory of concreteness in language development ends at early adolescence and is informed by studies of comprehension. We investigated concreteness effects in language production across the span of adulthood with a focus on conversation. We tested two competing hypotheses about abstract word use in conversation as a function of normal aging. The first hypothesis is that a steady accrual of vocabulary knowledge over the lifespan will confer a more expansive abstract lexicon and that older adults will in turn produce more abstract words in conversation. An alternative hypothesis is that aging gradually compromises executive resources that impact abstract word retrieval, leading to a concreteness bias in conversation. We analyzed distributions of abstract and concrete words and cross-speaker alignment within unscripted conversations between adults of different ages (N=1565 conversations, >8 million words, age range 19-66) using a novel computational algorithm (ConversationAlign). Aging was associated with abstract word dropout, a finding that is consistent with the hypothesis that high processing demands of conversation (e.g., alignment, topic maintenance) bias lexical retrieval toward concrete word use. We discuss the significance of these results for understanding intergenerational communication and relationships between aging, executive functioning, and lexical retrieval in high-level discourse.