The grammar of anger: Mapping the computational architecture of a recalibrational emotion

A behavioral signature for quantifying the social value of interpersonal relationships with specific others

The idea that individuals ascribe value to social phenomena, broadly construed, is well-established. Despite the ubiquity of this concept, defining social value in the context of interpersonal relationships remains elusive. This is notable because while prominent theories of human social behavior acknowledge the role of value-based processes, they mostly emphasize the value of individual actions an agent may choose to take in a given environment. Comparatively little is known about how humans value their interpersonal relationships. To address this, we devised a method for engineering a behavioral signature of social value in several independent samples (total N = 1111). Incorporating the concept of opportunity cost from economics and data-driven quantitative methods, we derived this signature by sourcing and weighting a range of social behaviors based on how likely individuals are to prioritize them in the face of limited resources. We examined how strongly the signature was expressed in self-reported social behaviors with specific relationship partners (a parent, close friend, and acquaintance). Social value scores track with other aspects of these relationships (e.g., relationship quality, aversion to losing relationship partners), are predictive of decision preferences on a range of tasks, and display good psychometric properties. These results provide greater mechanistic specificity in delineating human value-based behavior in social contexts and help parse the motivational relevance of the different facets that comprise interpersonal relationships.

When rules are over-ruled: Virtual bargaining as a contractualist method of moral judgment

Rules help guide our behavior-particularly in complex social contexts. But rules sometimes give us the "wrong" answer. How do we know when it is okay to break the rules? In this paper, we argue that we sometimes use contractualist (agreement-based) mechanisms to determine when a rule can be broken. Our model draws on a theory of social interactions - "virtual bargaining" - that assumes that actors engage in a simulated bargaining process when navigating the social world. We present experimental data which suggests that rule-breaking decisions are sometimes driven by virtual bargaining and show that these data cannot be explained by more traditional rule-based or outcome-based approaches.

Terrorism as Coalitional Predation: Explaining Definitional Ambiguities and Precautionary Responses

Terrorism continues to be an enigmatic and contested concept, lacking a universally accepted definition despite extensive scholarly debate. Lay intuitions, however, demonstrate a notable convergence in identifying acts as "terrorism" when specific situational features are present, such as indiscriminate violence and out-group perpetration. These features elicit predictable and robust precautionary responses, raising the question: Is there a unified and parsimonious explanation for these phenomena? It is hypothesized that a situational template exists in the human mind, the coalitional predation template (CPT), which evolved not to detect modern-day terrorism, per se, but to identify and respond to situations of predatory coalitional conflict. The paper examines the potential cues and mechanisms that constitute the psychological systems activated by such threats, suggesting that matching the input cues of the CPT triggers well-documented precautionary responses to terrorism. However, this cue-based system may not align neatly with contemporary threats, leading to disproportionate responses to some threats while underestimating others. The model also posits that interpretations of violence can vary due to incomplete cues and the social position of the evaluator, leading to public disagreements and inconsistencies in defining terrorism. Consequently, arriving at an unambiguous and widely accepted definition of terrorism may not be possible. The model presented may account for a range of phenomena, including the inclination towards attributing mental illness to particular violent incidents and the uncanny surface similarities between terrorism and war crimes. The findings have significant implications for both the theoretical understanding of terrorism and practical policy responses.

Computational Social Psychology

Social psychologists attempt to explain how we interact by appealing to basic principles of how we think. To make good on this ambition, they are increasingly relying on an interconnected set of formal tools that model inference, attribution, value-guided decision making, and multi-agent interactions. By reviewing progress in each of these areas and highlighting the connections between them, we can better appreciate the structure of social thought and behavior, while also coming to understand when, why, and how formal tools can be useful for social psychologists.

Rational inferences about social valuation

The decisions made by other people can contain information about the value they assign to our welfare-for example how much they are willing to sacrifice to make us better off. An emerging body of research suggests that we extract and use this information, responding more favorably to those who sacrifice more even if they provide us with less. The magnitude of their trade-offs governs our social responses to them-including partner choice, giving, and anger. This implies that people have well-designed cognitive mechanisms for estimating the weight someone else assigns to their welfare, even when the amounts at stake vary and the information is noisy or sparse. We tested this hypothesis in two studies (N=200; US samples) by asking participants to observe a partner make two trade-offs, and then predict the partner's decisions in other trials. Their predictions were compared to those of a model that uses statistically optimal procedures, operationalized as a Bayesian ideal observer. As predicted, (i) the estimates people made from sparse evidence matched those of the ideal observer, and (ii) lower welfare trade-offs elicited more anger from participants, even when their total payoffs were held constant. These results support the view that people efficiently update their representations of how much others value them. They also provide the most direct test to date of a key assumption of the recalibrational theory of anger: that anger is triggered by cues of low valuation, not by the infliction of costs.

Emotion prediction as computation over a generative theory of mind

From sparse descriptions of events, observers can make systematic and nuanced predictions of what emotions the people involved will experience. We propose a formal model of emotion prediction in the context of a public high-stakes social dilemma. This model uses inverse planning to infer a person's beliefs and preferences, including social preferences for equity and for maintaining a good reputation. The model then combines these inferred mental contents with the event to compute 'appraisals': whether the situation conformed to the expectations and fulfilled the preferences. We learn functions mapping computed appraisals to emotion labels, allowing the model to match human observers' quantitative predictions of 20 emotions, including joy, relief, guilt and envy. Model comparison indicates that inferred monetary preferences are not sufficient to explain observers' emotion predictions; inferred social preferences are factored into predictions for nearly every emotion. Human observers and the model both use minimal individualizing information to adjust predictions of how different people will respond to the same event. Thus, our framework integrates inverse planning, event appraisals and emotion concepts in a single computational model to reverse-engineer people's intuitive theory of emotions. This article is part of a discussion meeting issue 'Cognitive artificial intelligence'.

Rational information search in welfare-tradeoff cognition

One of the most important dimensions along which we evaluate others is their propensity to value our welfare: we like people who are disposed to incur costs for our benefit and who refrain from imposing costs on us to benefit themselves. The evolutionary importance of social valuation in our species suggests that humans have cognitive mechanisms that are able to efficiently extract information about how much another person values them. Here I test the hypothesis that people are spontaneously interested in the kinds of events that have the most potential to reveal such information. In two studies, I presented participants (Ns = 216; 300) with pairs of dilemmas that another individual faced in an economic game; for each pair, I asked them to choose the dilemma for which they would most like to see the decision that the individual had made. On average, people spontaneously selected the choices that had the potential to reveal the most information about the individual's valuation of the participant, as quantified by a Bayesian ideal search model. This finding suggests that human cooperation is supported by sophisticated cognitive mechanisms for information-gathering.

A general motivational architecture for human and animal personality

To achieve integration in the study of personality, researchers need to model the motivational processes that give rise to stable individual differences in behavior, cognition, and emotion. The missing link in current approaches is a motivational architecture-a description of the core set of mechanisms that underlie motivation, plus a functional account of their operating logic and inter-relations. This paper presents the initial version of such an architecture, the General Architecture of Motivation (GAM). The GAM offers a common language for individual differences in humans and other animals, and a conceptual toolkit for building species-specific models of personality. The paper describes the main components of the GAM and their interplay, and examines the contribution of these components to the emergence of individual differences. The final section discusses how the GAM can be used to construct explicit functional models of personality, and presents a roadmap for future research.

Seeing Red: A Grounded Theory Study of Women's Anger after Childbirth

Persistent intense anger is indicative of postpartum distress, yet maternal anger has been little explored after childbirth. Using grounded theory, we explained how and why mothers develop intense anger after childbirth and the actions they take to manage their anger. Twenty mothers of healthy singleton infants described their experiences of anger during the first two postpartum years. Mothers indicated they became angry when they had violated expectations, compromised needs, and felt on edge (e.g., exhausted, stressed, and resentful), particularly around infants' sleep. Mothers described suppressing and/or expressing anger with outcomes such as conflict and recruiting support. Receiving support from partners, family, and others helped mothers manage their anger, with more positive outcomes. Women should be screened for intense anger, maternal-infant sleep problems, and adequacy of social supports after childbirth. Maternal anger can be reduced by changing expectations and helping mothers meet their needs through social and structural supports.

Trajectories and Correlates of Anger During the Perinatal Period

OBJECTIVES

To investigate trajectories of anger during pregnancy and the early postpartum period; to identify baseline psychosocial predictors of anger trajectory group membership; and to examine correlates of anger trajectory group membership, including symptoms of depression, anxiety, insomnia, and social support, in the postpartum period.

DESIGN

Longitudinal descriptive design.

SETTING

We recruited participants from a maternity clinic in Calgary, Alberta, Canada.

PARTICIPANTS

The sample included a convenience sample of 143 pregnant women who had basic fluency in English, were older than 17 years of age, and were less than 19 weeks gestation with a single fetus at the time of recruitment.

METHODS

Participants completed online questionnaires at four time points: early, mid-, and late pregnancy and 2 months after birth. We used group-based semiparametric mixture modeling to estimate patterns of anger. We used multinomial logistic regression to explore associations between baseline predictors and trajectory membership.

RESULTS

We identified four distinct trajectories of anger during pregnancy through 2 months after birth: minimal-stable anger (52.4%), mild-stable anger (27.5%), moderate-stable anger (12.7%), and high-decreasing anger (7.4%). Membership in the moderate-stable group was associated with greater baseline symptoms of depression, anxiety, and insomnia severity scores compared to the minimal-stable anger group. Moderate-stable trajectory group membership was also associated with greater symptoms of anxiety, depression, and insomnia at 2 months after birth.

CONCLUSION

Higher levels of anger were associated with worse mental health in pregnancy and after childbirth in our participants. Women should be made aware of anger as a possible mood disturbance by clinicians, and researchers should investigate the consequences of anger during the perinatal period.

Are we there yet? Every computational theory needs a few black boxes, including theories about groups

Pietraszewski exemplifies the need for computational theory using group conflict; I complement this with an example of group cooperation. He criticizes past theories for having black boxes; I suggest his theory also has a black box - the concept of costs. He divides what mentally constitutes a group from mere ancillary attributes; I hazard that some of these attributes are essential.

Sex Differences in Fearful Personality Traits Are Mediated by Physical Strength

Across cultures, women reliably exhibit higher levels of Neuroticism than men. Recent work shows that this sex difference, particularly in Neuroticism’s anxiety facet, is partly mediated by the sex difference in physical strength. We build on this finding by testing pre-registered predictions of mediation by physical strength of the sex differences in HEXACO Emotionality and its Anxiety and Fearfulness facets (HEXACO stands for the factors of honesty–humility, emotionality, extraversion, agreeableness, conscientiousness, and openness to experience). Facultative calibration models predict that levels of these two facets, but not necessarily Emotionality’s other facets, will be adaptively adjusted during ontogeny to a person’s relative physical formidability. Results from five samples of U.S. undergraduates (total N = 1,399) showed that strength mediated the sex difference (women > men) in Emotionality and all its facets, but that the mediation effect was strongest for Fearfulness and weakest for Sentimentality. Overall, findings are consistent with the hypothesis that physical strength explains sex differences found in fearful and anxious personality traits.

Third-Party Perceptions of Male and Female Status: Male Physical Strength and Female Physical Attractiveness Cue High Status

Status is a universal feature of human sociality. A lesser-studied adaptive problem surrounding status is assessing who has which levels of status in a given group (e.g., identifying which people possess high status). Here, we integrate theory and methods from evolutionary social science, animal behavior, and social psychology, and we use an emotion inference paradigm to investigate what cues render people high status in the eyes of social perceivers. This paradigm relies on robust associations between status and emotion display—particularly the anger display. If a target is expected to enact (but not necessarily feel) anger, this would suggest that social perceivers view that target as higher status. By varying target attributes, we test whether those attributes are considered status cues in the eyes of social perceivers. In two well-powered, pre-registered experiments in the United States (N = 451) and India (N = 378), participants read one of eight vignettes about a male or female target—described as high or low in either physical strength or physical attractiveness (possible status cues)—who is thwarted by another person, and then reported expectations of the target’s felt and enacted anger. We find that people expected physically stronger (versus less strong) men and more (versus less) physically attractive women to enact greater anger when thwarted by a same-sex other. Strength had no significant effect on estimations of female status and attractiveness had no significant effect on estimations of male status. There were no differences in expectations of felt anger. Results suggest that people use men’s strength and women’s attractiveness as status cues. Moreover, results underscore the notion that focusing on male-typical cues of status might obscure our understanding of the female status landscape. We discuss how this paradigm might be fruitfully employed to examine and discover other unexplored cues of male and female status.

Neurotransmitters and Electrophysiological Changes Might Work as Biomarkers for Diagnosing Affective Disorders

Affective disorders are the leading causes of human disability worldwide; however, the diagnosis is still hard to define, because emotion is the least study subjects in psychology. Recent emotional studies suggest that human emotions are developed from basic emotions, which are evolved for fundamental human lives. Even though most psychologists agree upon the idea that there are some basic emotions, there is little agreement on how many emotions are basic, which emotions are basic, and why they are basic. In our previous papers, we suggested that there are three basic emotions: joy, fear, and disgust. These basic emotions depend on the peptides and monoamines: dopamine-joy (peptides-reward), norepinephrine-fear (anger), and serotonin-disgust (sadness). Further tests with event-related potentials (ERP) found that joy, fear, and disgust showed the fastest response compared with other emotions, suggesting that they are fast automatic responses, which confirmed that these three emotions are prototypical emotions. Other basic emotions, anger and sadness, are due to object induced behaviors instead of sensation of object, so they developed secondary to prototypical emotions. Thus, we concluded that only joy, fear, and disgust are prototypical emotions, which can mix into other emotions, like the primary colors. In all, the neural substrates for all emotions, including the affections, are possibly monoamine neuromodulators: joy-dopamine (peptides), fear (anger)-norepinephrine, and disgust-serotonin. We hope these basic emotional studies will offer some neural mechanisms for emotional processing and shed lights on the diagnosis of affective disorders.

Cognitive Behavior Therapy for Depression From an Evolutionary Perspective

Evolutionary medicine attempts to solve a problem with which traditional medicine has struggled historically; how do we distinguish between diseased states and "healthy" responses to disease states? Fever and diarrhea represent classic examples of evolved adaptations that increase the likelihood of survival in response to the presence of pathogens in the body. Whereas, the severe mental disorders like psychotic mania or the schizophrenias may involve true "disease" states best treated pharmacologically, most non-psychotic "disorders" that revolve around negative affects like depression or anxiety are likely adaptations that evolved to serve a function that increased inclusive fitness in our ancestral past. What this likely means is that the proximal mechanisms underlying the non-psychotic "disorders" are "species typical" and neither diseases nor disorders. Rather, they are coordinated "whole body" responses that prepare the individual to respond in a maximally functional fashion to the variety of different challenges that our ancestors faced. A case can be made that depression evolved to facilitate a deliberate cognitive style (rumination) in response to complex (often social) problems. What this further suggests is that those interventions that best facilitate the functions that those adaptations evolved to serve (such as rumination) are likely to be preferred over those like medications that simply anesthetize the distress. We consider the mechanisms that evolved to generate depression and the processes utilized in cognitive behavior therapy to facilitate those functions from an adaptationist evolutionary perspective.

A simple definition of 'intentionally'

Cognitive scientists have been debating how the folk concept of intentional action works. We suggest a simple account: people consider that an agent did X intentionally to the extent that X was causally dependent on how much the agent wanted X to happen (or not to happen). Combined with recent models of human causal cognition, this definition provides a good account of the way people use the concept of intentional action, and offers natural explanations for puzzling phenomena such as the side-effect effect. We provide empirical support for our theory, in studies where we show that people's causation and intentionality judgments track each other closely, in everyday situations as well as in scenarios with unusual causal structures. Study 5 additionally shows that the effect of norm violations on intentionality judgments depends on the causal structure of the situation, in a way uniquely predicted by our theory. Taken together, these results suggest that the folk concept of intentional action has been difficult to define because it is made of cognitive building blocks, such as our intuitive concept of causation, whose logic cognitive scientists are just starting to understand.

Forms and Functions of the Social Emotions

In engineering, form follows function. It is therefore difficult to understand an engineered object if one does not examine it in light of its function. Just as understanding the structure of a lock requires understanding the desire to secure valuables, understanding structures engineered by natural selection, including emotion systems, requires hypotheses about adaptive function. Social emotions reliably solved adaptive problems of human sociality. A central function of these emotions appears to be the recalibration of social evaluations in the minds of self and others. For example, the anger system functions to incentivize another individual to value your welfare more highly when you deem the current valuation insufficient; gratitude functions to consolidate a cooperative relationship with another individual when there are indications that the other values your welfare; shame functions to minimize the spread of discrediting information about yourself and the threat of being devalued by others; and pride functions to capitalize on opportunities to become more highly valued by others. Using the lens of social valuation, researchers are now mapping these and other social emotions at a rapid pace, finding striking regularities across industrial and small-scale societies and throughout history.

Towards a computational theory of social groups: A finite set of cognitive primitives for representing any and all social groups in the context of conflict

We don't yet have adequate theories of what the human mind is representing when it represents a social group. Worse still, many people think we do. This mistaken belief is a consequence of the state of play: Until now, researchers have relied on their own intuitions to link up the concept social group on the one hand, and the results of particular studies or models on the other. While necessary, this reliance on intuition has been purchased at considerable cost. When looked at soberly, existing theories of social groups are either (i) literal, but not remotely adequate (such as models built atop economic games), or (ii) simply metaphorical (typically a subsumption or containment metaphor). Intuition is filling in the gaps of an explicit theory. This paper presents a computational theory of what, literally, a group representation is in the context of conflict: it is the assignment of agents to specific roles within a small number of triadic interaction types. This "mental definition" of a group paves the way for a computational theory of social groups-in that it provides a theory of what exactly the information-processing problem of representing and reasoning about a group is. For psychologists, this paper offers a different way to conceptualize and study groups, and suggests that a non-tautological definition of a social group is possible. For cognitive scientists, this paper provides a computational benchmark against which natural and artificial intelligences can be held.

Are Emotions Natural Kinds After All? Rethinking the Issue of Response Coherence

The synchronized co-activation of multiple responses-motivational, behavioral, and physiological-has been taken as a defining feature of emotion. Such response coherence has been observed inconsistently however, and this has led some to view emotion programs as lacking biological reality. Yet, response coherence is not always expected or desirable if an emotion program is to carry out its adaptive function. Rather, the hallmark of emotion is the capacity to orchestrate multiple mechanisms adaptively-responses will co-activate in stereotypical fashion or not depending on how the emotion orchestrator interacts with the situation. Nevertheless, might responses cohere in the general case where input variables are specified minimally? Here we focus on shame as a case study. We measure participants' responses regarding each of 27 socially devalued actions and personal characteristics. We observe internal and external coherence: The intensities of felt shame and of various motivations of shame (hiding, lying, destroying evidence, and threatening witnesses) vary in proportion (i) to one another, and (ii) to the degree to which audiences devalue the disgraced individual-the threat shame defends against. These responses cohere both within and between the United States and India. Further, alternative explanations involving the low-level variable of arousal do not seem to account for these results, suggesting that coherence is imparted by a shame system. These findings indicate that coherence can be observed at multiple levels and raise the possibility that emotion programs orchestrate responses, even in those situations where coherence is low.

An Adaptationist Framework for Personality Science

The field of personality psychology aspires to construct an overarching theory of human nature and individual differences: one that specifies the psychological mechanisms that underpin both universal and variable aspects of thought, emotion, and behaviour. Here, we argue that the adaptationist toolkit of evolutionary psychology provides a powerful meta–theory for characterizing the psychological mechanisms that give rise to within–person, between–person, and cross–cultural variations. We first outline a mechanism–centred adaptationist framework for personality science, which makes a clear ontological distinction between (i) psychological mechanisms designed to generate behavioural decisions and (ii) heuristic trait concepts that function to perceive, describe, and influence others behaviour and reputation in everyday life. We illustrate the utility of the adaptationist framework by reporting three empirical studies. Each study supports the hypothesis that the anger programme—a putative emotional adaptation—is a behaviour–regulating mechanism whose outputs are described in the parlance of the person description factor called ‘Agreeableness’. We conclude that the most productive way forward is to build theory–based models of specific psychological mechanisms, including their culturally evolved design features, until they constitute a comprehensive depiction of human nature and its multifaceted variations. © 2020 European Association of Personality Psychology

The Active Inference Approach to Ecological Perception: General Information Dynamics for Natural and Artificial Embodied Cognition

The emerging neurocomputational vision of humans as embodied, ecologically embedded, social agents—who shape and are shaped by their environment—offers a golden opportunity to revisit and revise ideas about the physical and information-theoretic underpinnings of life, mind, and consciousness itself. In particular, the active inference framework (AIF) makes it possible to bridge connections from computational neuroscience and robotics/AI to ecological psychology and phenomenology, revealing common underpinnings and overcoming key limitations. AIF opposes the mechanistic to the reductive, while staying fully grounded in a naturalistic and information-theoretic foundation, using the principle of free energy minimization. The latter provides a theoretical basis for a unified treatment of particles, organisms, and interactive machines, spanning from the inorganic to organic, non-life to life, and natural to artificial agents. We provide a brief introduction to AIF, then explore its implications for evolutionary theory, ecological psychology, embodied phenomenology, and robotics/AI research. We conclude the paper by considering implications for machine consciousness.