Affective science最新文献

Affective science is a broad and burgeoning field, and the National Institutes of Health (NIH) support research on a similarly broad range of topics. Across NIH, funding is available for basic, translational, and intervention research, including research in non-human animals, healthy populations, and those with or at risk for disease. Multiple NIH Institutes and Centers have specific programs devoted to topics within the affective science umbrella. Here, we introduce the funding priorities of these six: the National Cancer Institute (NCI), National Center for Complementary and Integrative Health (NCCIH), National Institute of Mental Health (NIMH), National Institute on Aging (NIA), National Institute on Drug Abuse (NIDA), and National Institute on Minority Health and Health Disparities (NIMHD). We then discuss overlapping themes and offer a perspective on promising research directions.

A wealth of literature suggests the existence of sex differences in how emotions are experienced, recognized, expressed, and regulated. However, to what extent these differences result from the put in place of stereotypes and social rules is still a matter of debate. Literature is an essential cultural institution, a transposition of the social life of people but also of their intimate affective experiences, which can serve to address questions of psychological relevance. Here, we created a large corpus of literary fiction enriched by authors’ metadata to measure the extent to which culture influences how men and women write about emotion. Our results show that even though before the twenty-first century and across 116 countries women more than men have written about affect, starting from 2000, this difference has diminished substantially. Also, in the past, women’s narratives were more positively laden and less arousing. While the difference in arousal is ubiquitous and still present nowadays, sex differences in valence vary as a function of culture and have dissolved in recent years. Altogether, these findings suggest that historic evolution is associated with men and women writing similarly about emotions and reveal a sizable impact of culture on the affective characteristics of the lexicon.

Valence is central to the experience of emotion. However, to the detriment of affective science, it is often ill-defined and poorly operationalized. Being more precise about what is meant by valence would make for more readily comparable emotion stimuli, methodologies, and results, and would promote consideration of the diversity, complexity, and function of discrete emotions. This brief review uses prior literature and an informal survey of affective scientists to illustrate disagreements in conceptualizing valence. Next, we describe issues of valence in affective science, particularly as they pertain to the emotion process, the functions of emotion, and precision in empirical research. We conclude by providing recommendations for the future of valence in affective science.

This study examined daily affective dynamic indices among individuals with a major depressive disorder (MDD) diagnosis in the past one year at the time of the interview, focusing on affective variability and change in affect in response to daily events (affective reactivity). Data were from the main survey and daily diary project of the Midlife in the United States (MIDUS) study. Participants (N = 1,970; n_MDD = 202; n_non-MDD = 1,768) completed structured clinical interviews on mental health and telephone interviews about their daily experiences spanning eight consecutive days. Multilevel models revealed that the MDD group experienced greater positive (PA) and negative affect (NA) variability than the non-MDD group. On days that at least one stressful event was reported, the MDD group experienced a greater decrease in PA and a greater increase in NA. On days that at least one positive event was reported, the MDD group experienced a greater increase in PA and a greater decrease in NA. Changes in affect to daily events, particularly the mood brightening effect, may be indicators of depression and potential targets for intervention. Limitations of the study include a community sample, reliance on self-reported measures of daily stressors and positive events, inclusion of remitted and current MDD participants, and the DSM-III-R based criteria for MDD diagnosis.

Affective science is stuck in a version of the nature-versus-nurture debate, with theorists arguing whether emotions are evolved adaptations or psychological constructions. We do not see these as mutually exclusive options. Many adaptive behaviors that humans have evolved to be good at, such as walking, emerge during development – not according to a genetically dictated program, but through interactions between the affordances of the body, brain, and environment. We suggest emotions are the same. As developing humans acquire increasingly complex goals and learn optimal strategies for pursuing those goals, they are inevitably pulled to particular brain-body-behavior states that maximize outcomes and self-reinforce via positive feedback loops. We call these recurring, self-organized states emotions. Emotions display many of the hallmark features of self-organized attractor states, such as hysteresis (prior events influence the current state), degeneracy (many configurations of the underlying variables can produce the same global state), and stability. Because most bodily, neural, and environmental affordances are shared by all humans – we all have cardiovascular systems, cerebral cortices, and caregivers who raised us – similar emotion states emerge in all of us. This perspective helps reconcile ideas that, at first glance, seem contradictory, such as emotion universality and neural degeneracy.

Behavior change can be challenging to facilitate and achieve. Behavior change frameworks largely focus on social cognitive determinants, omitting affective determinants or including them in a superficial way. However, evidence points to the role of affect in decision-making and behavior, particularly when the behavior at focus for change is affectively pleasant or when the behavior to be facilitated is affectively unpleasant. This paper identifies challenges and opportunities to further affective science by using behavior change as a context and, relatedly, to further the science of behavior change by leveraging theoretical and methodological innovations in affective science.

People express their own emotions and perceive others’ emotions via a variety of channels, including facial movements, body gestures, vocal prosody, and language. Studying these channels of affective behavior offers insight into both the experience and perception of emotion. Prior research has predominantly focused on studying individual channels of affective behavior in isolation using tightly controlled, non-naturalistic experiments. This approach limits our understanding of emotion in more naturalistic contexts where different channels of information tend to interact. Traditional methods struggle to address this limitation: manually annotating behavior is time-consuming, making it infeasible to do at large scale; manually selecting and manipulating stimuli based on hypotheses may neglect unanticipated features, potentially generating biased conclusions; and common linear modeling approaches cannot fully capture the complex, nonlinear, and interactive nature of real-life affective processes. In this methodology review, we describe how deep learning can be applied to address these challenges to advance a more naturalistic affective science. First, we describe current practices in affective research and explain why existing methods face challenges in revealing a more naturalistic understanding of emotion. Second, we introduce deep learning approaches and explain how they can be applied to tackle three main challenges: quantifying naturalistic behaviors, selecting and manipulating naturalistic stimuli, and modeling naturalistic affective processes. Finally, we describe the limitations of these deep learning methods, and how these limitations might be avoided or mitigated. By detailing the promise and the peril of deep learning, this review aims to pave the way for a more naturalistic affective science.

This study investigated interpersonal effects of regulating naturalistic facial signals on cooperation during an iterative Prisoner’s Dilemma (IPD) game. Fifty pairs of participants played ten IPD rounds across a video link then reported on their own and their partner’s expressed emotion and facial regulation in a video-cued recall (VCR) procedure. iMotions software allowed us to auto-code actors’ and partners’ facial activity following the outcome of each round. We used two-level mixed effects logistic regression to assess over-time actor and partner effects of auto-coded facial activity, self-reported facial regulation, and perceptions of the partner’s facial regulation on the actor’s subsequent cooperation. Actors were significantly less likely to cooperate when their partners had defected on the previous round. None of the lagged scores based on auto-coded facial activity were significant predictors of cooperation. However, VCR variables representing partner’s positive regulation of expressions and actor’s perception of partner’s positive regulation both significantly increased the probability of subsequent actor cooperation after controlling for prior defection. These results offer preliminary evidence about interpersonal effects of facial regulation in interactive contexts and illustrate how dynamic dyadic emotional processes can be systematically investigated in controlled settings.

For affective science to advance, researchers will need to develop a better understanding of neutral affect. At first glance, neutral affect may seem uninteresting to some affective scientists because the goal is to investigate hedonic experiences, not the presumed absence of them. This failure to fully consider and examine neutral affect, however, limits the field’s potential for new discoveries. In this paper, I discuss how a greater understanding of neutral affect can inform researchers’ views of valence, subjective well-being, and behavior. I define neutral affect and discuss evidence indicating that neutral affect is a commonly felt state that occurs independently of positive and negative affect. These data suggest that to understand the entirety of the affective landscape, researchers should move beyond traditional measures of valence and consider how positive, negative, and neutral affective states might inform their phenomenon of interest. I then illustrate how neutral affect might be a key, albeit complex, influence on subjective well-being. I also discuss how neutrality might be a fundamental and unique predictor of inaction. If affective scientists want to fully understand how feelings operate and function, it is essential that they explore the possibility that neutral affect might hold some of the essential clues needed to solve their affective puzzle.

Empathy is a multidimensional construct that includes changes in cognitive, affective, and physiological processes. However, the physiological processes that contribute to empathic responding have received far less empirical attention. Here, we investigated whether physiological synchrony emerged during an empathy-inducing activity in which individuals disclosed a time of suffering while their romantic partner listened and responded (N = 111 couples). Further, we examined the extent to which trait and state measures of cognitive and affective empathy were associated with each other and with physiological synchrony during this activity. We found evidence for physiological synchrony in skin conductance reactivity and also in interbeat interval reactivity, though only when disclosers were women, but not for respiratory sinus arrhythmia reactivity. Physiological synchrony was not consistently associated with other well-established trait and state measures of empathy. These findings identify the nuanced role of physiological synchrony in empathic responding to others’ suffering.