The psychological, computational, and neural foundations of indebtedness.

Receiving a favor from another person may induce a negative feeling of indebtedness for the beneficiary. In this study, we explore these hidden costs by developing and validating a conceptual model of indebtedness across three studies that combine a large-scale online questionnaire, an interpersonal game, computational modeling, and neuroimaging. Our model captures how individuals perceive the altruistic and strategic intentions of the benefactor. These inferences produce distinct feelings of guilt and obligation that together comprise indebtedness and motivate reciprocity. Perceived altruistic intentions convey care and communal concern and are associated with activity in insula, ventromedial prefrontal cortex and dorsolateral prefrontal cortex, while inferred strategic intentions convey expectations of future reciprocity and are associated with activation in temporal parietal junction and dorsomedial prefrontal cortex. We further develop a neural utility model of indebtedness using multivariate patterns of brain activity that captures the tradeoff between these feelings and reliably predicts reciprocity behavior.

Py-Feat: Python Facial Expression Analysis Toolbox.

Studying facial expressions is a notoriously difficult endeavor. Recent advances in the field of affective computing have yielded impressive progress in automatically detecting facial expressions from pictures and videos. However, much of this work has yet to be widely disseminated in social science domains such as psychology. Current state-of-the-art models require considerable domain expertise that is not traditionally incorporated into social science training programs. Furthermore, there is a notable absence of user-friendly and open-source software that provides a comprehensive set of tools and functions that support facial expression research. In this paper, we introduce Py-Feat, an open-source Python toolbox that provides support for detecting, preprocessing, analyzing, and visualizing facial expression data. Py-Feat makes it easy for domain experts to disseminate and benchmark computer vision models and also for end users to quickly process, analyze, and visualize face expression data. We hope this platform will facilitate increased use of facial expression data in human behavior research. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-023-00191-4.

Recovering Individual Emotional States from Sparse Ratings Using Collaborative Filtering.

A fundamental challenge in emotion research is measuring feeling states with high granularity and temporal precision without disrupting the emotion generation process. Here we introduce and validate a new approach in which responses are sparsely sampled and the missing data are recovered using a computational technique known as collaborative filtering (CF). This approach leverages structured covariation across individual experiences and is available in Neighbors, an open-source Python toolbox. We validate our approach across three different experimental contexts by recovering dense individual ratings using only a small subset of the original data. In dataset 1, participants (n=316) separately rated 112 emotional images on 6 different discrete emotions. In dataset 2, participants (n=203) watched 8 short emotionally engaging autobiographical stories while simultaneously providing moment-by-moment ratings of the intensity of their affective experience. In dataset 3, participants (n=60) with distinct social preferences made 76 decisions about how much money to return in a hidden multiplier trust game. Across all experimental contexts, CF was able to accurately recover missing data and importantly outperformed mean and multivariate imputation, particularly in contexts with greater individual variability. This approach will enable new avenues for affective science research by allowing researchers to acquire high dimensional ratings from emotional experiences with minimal disruption to the emotion-generation process. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-022-00161-2.

Gossip drives vicarious learning and facilitates social connection.

Complex language and communication is one of the unique hallmarks that distinguishes humans from most other animals. Interestingly, the overwhelming majority of our communication consists of social topics involving self-disclosure and discussions about others, broadly construed as gossip. Yet the precise social function of gossip remains poorly understood as research has been heavily influenced by folk intuitions narrowly casting gossip as baseless trash talk. Using a novel empirical paradigm that involves real interactions between a large sample of participants, we provide evidence that gossip is a rich, multifaceted construct, that plays a critical role in vicarious learning and social bonding. We demonstrate how the visibility or lack thereof of others' behavior shifts conversational content between self-disclosure and discussions about others. Social information acquired through gossip aids in vicarious learning, directly influencing future behavior and impression formation. At the same time, conversation partners come to influence each other, form more similar impressions, and build robust social bonds. Consistent with prior work, gossip also helps promote cooperation in groups without a need for formal sanctioning mechanisms. Altogether these findings demonstrate the rich and diverse social functions and effects of this ubiquitous human behavior and lay the groundwork for future investigations.

Endogenous variation in ventromedial prefrontal cortex state dynamics during naturalistic viewing reflects affective experience.

How we process ongoing experiences is shaped by our personal history, current needs, and future goals. Consequently, ventromedial prefrontal cortex (vmPFC) activity involved in processing these subjective appraisals appears to be highly idiosyncratic across individuals. To elucidate the role of the vmPFC in processing our ongoing experiences, we developed a computational framework and analysis pipeline to characterize the spatiotemporal dynamics of individual vmPFC responses as participants viewed a 45-minute television drama. Through a combination of functional magnetic resonance imaging, facial expression tracking, and self-reported emotional experiences across four studies, our data suggest that the vmPFC slowly transitions through a series of discretized states that broadly map onto affective experiences. Although these transitions typically occur at idiosyncratic times across people, participants exhibited a marked increase in state alignment during high affectively valenced events in the show. Our work suggests that the vmPFC ascribes affective meaning to our ongoing experiences.

Intersubject representational similarity analysis reveals individual variations in affective experience when watching erotic movies.

We spend much of our lives pursuing or avoiding affective experiences. However, surprisingly little is known about how these experiences are represented in the brain and if they are shared across individuals. Here, we explored variations in the construction of an affective experience during a naturalistic viewing paradigm based on subjective preferences in sociosexual desire and self-control using intersubject representational similarity analysis (IS-RSA). We found that when watching erotic movies, intersubject variations in sociosexual desire preferences of 26 heterosexual males were associated with similarly structured fluctuations in the cortico-striatal reward, default mode, and mentalizing networks. In contrast, variations in the self-control preferences were associated with shared dynamics in the fronto-parietal executive control and cingulo-insular salience networks. Importantly, these results were specific to the affective experience, as we did not observe any relationship with variation in preferences when individuals watched neutral movies. Moreover, these results appear to require multivariate representations of preferences as we did not observe any significant associations using single scalar summary scores. Our findings indicate that multidimensional variations in individual preferences can be used to uncover unique dimensions of an affective experience, and that IS-RSA can provide new insights into the neural processes underlying psychological experiences elicited through naturalistic experimental designs.

Socially transmitted placebo effects.

Medical treatments typically occur in the context of a social interaction between healthcare providers and patients. Although decades of research have demonstrated that patients' expectations can dramatically affect treatment outcomes, less is known about the influence of providers' expectations. Here we systematically manipulated providers' expectations in a simulated clinical interaction involving administration of thermal pain and found that patients' subjective experiences of pain were directly modulated by providers' expectations of treatment success, as reflected in the patients' subjective ratings, skin conductance responses and facial expression behaviours. The belief manipulation also affected patients' perceptions of providers' empathy during the pain procedure and manifested as subtle changes in providers' facial expression behaviours during the clinical interaction. Importantly, these findings were replicated in two more independent samples. Together, our results provide evidence of a socially transmitted placebo effect, highlighting how healthcare providers' behaviour and cognitive mindsets can affect clinical interactions.

Wanting without enjoying: The social value of sharing experiences.

Social connection can be a rich source of happiness. Humans routinely go out of their way to seek out social connection and avoid social isolation. What are the proximal forces that motivate people to share experiences with others? Here we used a novel experience-sharing and decision-making paradigm to understand the value of shared experiences. In seven experiments across Studies 1 and 2, participants demonstrated a strong motivation to engage in shared experiences. At the same time, participants did not report a commensurate increase in hedonic value or emotional amplification, suggesting that the motivation to share experiences need not derive from their immediate hedonic value. In Study 3, participants reported their explicit beliefs about the reasons people engage in shared experiences: Participants reported being motivated by the desire to forge a social connection. Together, these findings suggest that the desire to share an experience may be distinct from the subjective experience of achieving that state. People may be so driven to connect with each other that social experiences remain valuable even in the most minimalistic contexts.

The Flatland Fallacy: Moving Beyond Low-Dimensional Thinking.

Psychology is a complicated science. It has no general axioms or mathematical proofs, is rarely directly observable, and is the only discipline in which the subject matter (i.e., human psychological phenomena) is also the tool of investigation. Like the Flatlanders in Edwin Abbot's famous short story (), we may be led to believe that the parsimony offered by our low-dimensional theories reflects the reality of a much higher-dimensional problem. Here we contend that this "Flatland fallacy" leads us to seek out simplified explanations of complex phenomena, limiting our capacity as scientists to build and communicate useful models of human psychology. We suggest that this fallacy can be overcome through (a) the use of quantitative models, which force researchers to formalize their theories to overcome this fallacy, and (b) improved quantitative training, which can build new norms for conducting psychological research.

Spontaneous mentalizing predicts the fundamental attribution error.

When explaining the reasons for others' behavior, perceivers often overemphasize underlying dispositions and personality traits over the power of the situation, a tendency known as the fundamental attribution error. One possibility is that this bias results from the spontaneous processing of others' mental states, such as their momentary feelings or more enduring personality characteristics. Here, we use fMRI to test this hypothesis. Participants read a series of stories that described a target's ambiguous behavior in response to a specific social situation and later judged whether that act was attributable to the target's internal dispositions or to external situational factors. Neural regions consistently associated with mental state inference-especially, the medial pFC-strongly predicted whether participants later made dispositional attributions. These results suggest that the spontaneous engagement of mentalizing may underlie the biased tendency to attribute behavior to dispositional over situational forces.

Social-cognitive deficits in normal aging.

A sizeable number of studies have implicated the default network (e.g., medial prefrontal and parietal cortices) in tasks that require participants to infer the mental states of others (i.e., to mentalize). Parallel research has demonstrated that default network function declines over the lifespan, suggesting that older adults may show impairments in social-cognitive tasks that require mentalizing. Older and younger human adults were scanned using functional magnetic resonance imaging while performing three different social-cognitive tasks. Across three mentalizing paradigms, younger and older adults viewed animated shapes in brief social vignettes, stories about a person's moral actions, and false belief stories. Consistent with predictions, older adults responded less accurately to stories about others' false beliefs and made less use of actors' intentions to judge the moral permissibility of behavior. These impairments in performance during social-cognitive tasks were accompanied by age-related decreases across all three paradigms in the BOLD response of a single brain region, the dorsomedial prefrontal cortex. These findings suggest specific task-independent age-related deficits in mentalizing that are localizable to changes in circumscribed subregions of the default network.