A neuro-cognitive process model of emotional intelligence

Impaired emotional awareness is associated with childhood maltreatment exposure and positive symptoms in schizophrenia

Objectives

Evidence suggests that emotional awareness-the ability to identify and label emotions-may be impaired in schizophrenia and related to positive symptom severity. Exposure to childhood maltreatment is a risk factor for both low emotional awareness and positive symptoms.

Methods

The current investigation examines associations between a performance-based measure of emotional awareness, positive symptom severity, and childhood maltreatment exposure in 44 individuals with a schizophrenia-spectrum disorder and 48 healthy comparison participants using the electronic Levels of Emotional Awareness Scale (eLEAS), Positive and Negative Syndrome Scale (PANSS) and Childhood Trauma Questionnaire (CTQ).

Results

Patients demonstrated significant deficits in emotional awareness overall, which was true for both self and others. In patients, lower emotional awareness was significantly associated with more severe positive symptoms. Emotional awareness was significantly impaired in patients with schizophrenia with self-reported maltreatment exposure, relative to other groups. Severity of maltreatment was not significantly associated with emotional awareness or positive symptoms when looking continuously, and there was no significant indirect effect.

Conclusion

These data suggest that emotional awareness impairments observed in schizophrenia may be exacerbated by exposure to childhood maltreatment, possibly putting individuals at greater risk for experiencing positive symptoms of psychosis.

Emotional intelligence frameworks in leadership education

This article focuses on integrating topics of emotional intelligence in curricular and co-curricular collegiate leadership education. The authors spotlight one institution's use of emotionally intelligent leadership as a framework across a variety of leadership programs, courses, and trainings. Critiques, considerations, and resources to inform leadership education efforts that focus on emotional intelligence are included.

Emotional intelligence mediates the protective role of the orbitofrontal cortex spontaneous activity measured by fALFF against depressive and anxious symptoms in late adolescence

As a stable personality construct, trait emotional intelligence (TEI) refers to a battery of perceived emotion-related skills that make individuals behave effectively to adapt to the environment and maintain well-being. Abundant evidence has consistently shown that TEI is important for the outcomes of many mental health issues, particularly depression and anxiety. However, the neural substrates involved in TEI and the underlying neurobehavioral mechanism of how TEI reduces depression and anxiety symptoms remain largely unknown. Herein, resting-state functional magnetic resonance imaging and a group of behavioral measures were applied to examine these questions among a large sample comprising 231 general adolescent students aged 16-20 years (52% female). Whole-brain correlation analysis and prediction analysis demonstrated that TEI was negatively linked with spontaneous activity (measured with the fractional amplitude of low-frequency fluctuations) in the bilateral medial orbitofrontal cortex (OFC), a critical site implicated in emotion-related processes. Furthermore, structural equation modeling analysis found that TEI mediated the link of OFC spontaneous activity to depressive and anxious symptoms. Collectively, the current findings present new evidence for the neurofunctional bases of TEI and suggest a potential "brain-personality-symptom" pathway for alleviating depressive and anxious symptoms among students in late adolescence.

How past trauma impacts emotional intelligence: Examining the connection

Backed by both research and practice, the organizational psychology field has come to value emotional intelligence (EI) as being vital for leader and employee effectiveness. While this field values EI, it has paid little attention to the antecedents of emotional intelligence, leaving the EI domain without clarity on (1) why EI might vary across individuals, and (2) how to best develop EI. In this article, we rely on neuroscience and psychology research to make the case that past psychological trauma impacts later EI capabilities. Specifically, we present evidence that psychological trauma impairs the brain areas and functions that support EI. Establishing psychological trauma has valuable theoretical and practical implications that include providing an explanation of why EI might vary across individuals and providing a focus for improving EI: healing from past trauma. Further theoretical and practical implications for the field of organizational psychology are provided.

Age-related intrinsic functional connectivity underlying emotion utilization

Previous studies investigated the age-related positivity effect in terms of emotion perception and management, whereas little is known about whether the positivity effect is shown in emotion utilization (EU). If yes, the EU-related intrinsic functional connectivity and its age-associated alterations remain to be elucidated. In this study, we collected resting-state functional magnetic resonance imaging data from 62 healthy older adults and 72 undergraduates as well as their self-ratings of EU. By using the connectome-based predictive modeling (CPM) method, we constructed a predictive model of the positive relationship between EU self-ratings and resting-state functional connectivity. Lesion simulation analyses revealed that the medial-frontal network, default mode network, frontoparietal network, and subcortical regions played key roles in the EU-related CPM. Older subjects showed significantly higher EU self-ratings than undergraduates, which was associated with strengthened connectivity between the left dorsolateral prefrontal cortex and bilateral frontal poles, and between the left frontal pole and thalamus. A mediation analysis indicated that the age-related EU network mediated the age effect on EU self-ratings. Our findings extend previous research on the age-related "positivity effect" to the EU domain, suggesting that the positivity effect on the self-evaluation of EU is probably associated with emotion knowledge which accumulates with age.

Emotional Intelligence Not Only Can Make Us Feel Negative, but Can Provide Cognitive Resources to Regulate It Effectively: An fMRI Study

Neuroscientists have formulated the model of emotional intelligence (EI) based on brain imaging findings of individual differences in EI. The main objective of our study was to operationalize the advantage of high EI individuals in emotional information processing and regulation both at behavioral and neural levels of investigation. We used a self-report measure and a cognitive reappraisal task to demonstrate the role of EI in emotional perception and regulation. Participants saw pictures with negative or neutral captions and shifted (reappraised) from negative context to neutral while we registered brain activation. Behavioral results showed that higher EI participants reported more unpleasant emotions. The Utilization of emotions scores negatively correlated with the valence ratings and the subjective difficulty of reappraisal. In the negative condition, we found activation in hippocampus (HC), parahippocampal gyrus, cingulate cortex, insula and superior temporal lobe. In the neutral context, we found elevated activation in vision-related areas and HC. During reappraisal (negative-neutral) condition, we found activation in the medial frontal gyrus, temporal areas, vision-related regions and in cingulate gyrus. We conclude that higher EI is associated with intensive affective experiences even if emotions are unpleasant. Strong skills in utilizing emotions enable one not to repress negative feelings but to use them as source of information. High EI individuals use effective cognitive processes such as directing attention to relevant details; have advantages in allocation of cognitive resources, in conceptualization of emotional scenes and in building emotional memories; they use visual cues, imagination and executive functions to regulate negative emotions effectively.

Emotional Strengths and Difficulties in Italian Adolescents: Analysis of Adaptation through the SDQ

An adolescent’s knowledge of him/herself (positive aspects and weaknesses) is shaped by interactions with external and internal factors, including the family context and the educational environment. The assessment of this knowledge serves to construct the concept of self-esteem. The main objective of the present study was to examine the prevalence of self-reported emotional and behavioral symptoms in a representative sample of Italian adolescents and their relationship with gender and age, using Goodman’s Strengths and Difficulties Questionnaire (SDQ). A total of 440 adolescents (49.8% female) aged 15–18 years from the southern Italy region participated. The results show the prevalence of emotional and behavioral symptoms in the analyzed sample. Gender differences were also found in the variables under study. In conclusion, the SDQ test is offered as an agile, simplified, and effective tool, to be proposed to all formative agents who are concerned with the interest and care not only of young people, but also of the future of socio-political realities.

A Study on the Cognition and Emotion Identification of Participative Budgeting Based on Artificial Intelligence

Cognition and emotion exert a powerful influence on human behavior. Based on cognitive psychology and organizational behavior theory, this paper examines the role of cognition and emotion in participative budgeting and corporate performance using a questionnaire survey. The questionnaires were sent to 345 listed companies in China. The results support the hypothesis that human cognition and emotion have a positive moderating effect on the relationship between participative budgeting and corporate performance. Cognition and emotion can promote the effect of participative budgeting on corporate performance. Furthermore, according to the theory of artificial intelligence (AI), this paper designs an AI-based cognition and emotion identification system. This system can help managers identify the budget participants' cognitive and emotional states and undertake the interventions necessary to improving corporate performance.

Higher emotional awareness is associated with greater domain-general reflective tendencies

The tendency to reflect on the emotions of self and others is a key aspect of emotional awareness (EA)—a trait widely recognized as relevant to mental health. However, the degree to which EA draws on general reflective cognition vs. specialized socio-emotional mechanisms remains unclear. Based on a synthesis of work in neuroscience and psychology, we recently proposed that EA is best understood as a learned application of domain-general cognitive processes to socio-emotional information. In this paper, we report a study in which we tested this hypothesis in 448 (125 male) individuals who completed measures of EA and both general reflective cognition and socio-emotional performance. As predicted, we observed a significant relationship between EA measures and both general reflectiveness and socio-emotional measures, with the strongest contribution from measures of the general tendency to engage in effortful, reflective cognition. This is consistent with the hypothesis that EA corresponds to the application of general reflective cognitive processes to socio-emotional signals.

Validating a Novel Emotional Intelligence Instrument for Resident Physicians

To construct and validate a scale of emotional intelligence (EI) for the medical field, n = 80 resident physicians responded to a 69-item self-report measure during the pilot phase of development of the Scale of Emotional Functioning: Medicine (SEF:MED). Based on multiple-phase item and structural analyses, a final 36-item version was created based on data from n = 321 respondent residents. Initially exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) supported the expected three-factor solution as did additional CFA from a second sample of n = 113 participants. Internal consistency reliabilities obtained from the original n = 321 residents for the three SEF:MED subscales of Interpersonal Skills (IS), Emotional Awareness (EA), and Emotional Management (EM) were 0.81, 0.82, and 0.84, respectively. Alphas for the second CFA data set were 0.89, 0.87, and 0.88 for IS, EM, and EA, respectively. In addition, the SEF:MED was validated by comparing it to related measures (i.e., the Profile of Emotional Competence (PEC) and the Maslach Burnout Inventory-Human Services Survey for Medical Personnel [MBI-HSS (MP)]); Correlation coefficients between the Total EI composite on the SEF:MED and the PEC global scales ranged from r = 0.64 to 0.68. Finally, correlation coefficients from the Total EI composite on the SEF:MED significantly related to the MBI-HSS (MP) Emotional Exhaustion (EE), Depersonalization (DP), and Personal Accomplishment (PA) scales (r = -0.50, -0.44, and 0.52, respectively). The SEF:MED may provide useful data to physicians and other medical professionals as they consider their own well-being and how it may affect care of their patients.

Sleep quality and duration are associated with greater trait emotional intelligence

OBJECTIVES

Prior work suggests that short sleep and total sleep deprivation are associated with reduced trait Emotional Intelligence (trait EI) but not reduced ability Emotional Intelligence (ability EI). To expand this knowledge base, we investigated the role of habitual sleep quality on trait and ability EI above and beyond the known effects of recent sleep duration.

METHODS

A large sample, comprising 477 healthy adults completed the Pittsburgh Sleep Quality Index (PSQI), Trait Emotional Intelligence Questionnaire (TEIQue; trait EI), and Mayer-Salovey-Caruso Emotional Intelligence Scale (MSCEIT; ability EI).

RESULTS

Bivariate correlation and multiple linear regression showed that recent sleep duration and PSQI sleep quality each independently predicted higher trait EI scores, including Emotionality, Self-Control, Sociability, and Well-being, but were unrelated to ability EI scores.

CONCLUSIONS

In this large community sample, recent sleep duration and habitual sleep quality both independently associated with self-perceived dispositional aspects of EI (ie, trait EI). In contrast, recent sleep duration and PSQI score were unrelated to more crystalized aspects of EI performance, which encompass the general fund of emotional information and the ability to understand and reason about emotional concepts (ie, ability EI). In sum, greater self-perceived sleep duration and quality was associated with subjective perceptions of better emotional functioning, but was unrelated to performance-based metrics of emotional reasoning.

Levels of Emotional Awareness: Theory and Measurement of a Socio-Emotional Skill

Emotional awareness is the ability to conceptualize and describe one's own emotions and those of others. Over thirty years ago, a cognitive-developmental theory of emotional awareness patterned after Piaget's theory of cognitive development was created as well as a performance measure of this ability called the Levels of Emotional Awareness Scale (LEAS). Since then, a large number of studies have been completed in healthy volunteers and clinical populations including those with mental health or systemic medical disorders. Along the way, there have also been further refinements and adaptations of the LEAS such as the creation of a digital version in addition to further advances in the theory itself. This review aims to provide a comprehensive summary of the evolving theoretical background, measurement methods, and empirical findings with the LEAS. The LEAS is a reliable and valid measure of emotional awareness. Evidence suggests that emotional awareness facilitates better emotion self-regulation, better ability to navigate complex social situations and enjoy relationships, and better physical and mental health. This is a relatively new but promising area of research in the domain of socio-emotional skills. The paper concludes with some recommendations for future research.

Theory of minds: managing mental state inferences in working memory is associated with the dorsomedial subsystem of the default network and social integration

We often interact with multiple people at a time and consider their various points of view to facilitate smooth social interaction. Yet, how our brains track multiple mental states at once, and whether skill in this domain links to social integration, remains underspecified. To fill this gap, we developed a novel social working memory paradigm in which participants manage two- or four-people’s mental states in working memory, as well as control trials in which they alphabetize two- or four-people’s names in working memory. In Study 1, we found that the dorsomedial subsystem of the default network shows relative increases in activity with more mental states managed in working memory. In contrast, this subsystem shows relative decreases in activity with more non-mental state information (the number of names alphabetized) managed in working memory. In Study 2, only individual differences in managing mental states in working memory, specifically on trials that posed the greatest mental state load to working memory, correlated with social integration. Collectively, these findings add further support to the hypothesis that social working memory relies on partially distinct brain systems and may be a key ingredient to success in a social world.

Deeply Felt Affect: The Emergence of Valence in Deep Active Inference

The positive-negative axis of emotional valence has long been recognized as fundamental to adaptive behavior, but its origin and underlying function have largely eluded formal theorizing and computational modeling. Using deep active inference, a hierarchical inference scheme that rests on inverting a model of how sensory data are generated, we develop a principled Bayesian model of emotional valence. This formulation asserts that agents infer their valence state based on the expected precision of their action model-an internal estimate of overall model fitness ("subjective fitness"). This index of subjective fitness can be estimated within any environment and exploits the domain generality of second-order beliefs (beliefs about beliefs). We show how maintaining internal valence representations allows the ensuing affective agent to optimize confidence in action selection preemptively. Valence representations can in turn be optimized by leveraging the (Bayes-optimal) updating term for subjective fitness, which we label affective charge (AC). AC tracks changes in fitness estimates and lends a sign to otherwise unsigned divergences between predictions and outcomes. We simulate the resulting affective inference by subjecting an in silico affective agent to a T-maze paradigm requiring context learning, followed by context reversal. This formulation of affective inference offers a principled account of the link between affect, (mental) action, and implicit metacognition. It characterizes how a deep biological system can infer its affective state and reduce uncertainty about such inferences through internal action (i.e., top-down modulation of priors that underwrite confidence). Thus, we demonstrate the potential of active inference to provide a formal and computationally tractable account of affect. Our demonstration of the face validity and potential utility of this formulation represents the first step within a larger research program. Next, this model can be leveraged to test the hypothesized role of valence by fitting the model to behavioral and neuronal responses.

Recent advances in the application of predictive coding and active inference models within clinical neuroscience

Research in clinical neuroscience is founded on the idea that a better understanding of brain (dys)function will improve our ability to diagnose and treat neurological and psychiatric disorders. In recent years, neuroscience has converged on the notion that the brain is a 'prediction machine,' in that it actively predicts the sensory input that it will receive if one or another course of action is chosen. These predictions are used to select actions that will (most often, and in the long run) maintain the body within the narrow range of physiological states consistent with survival. This insight has given rise to an area of clinical computational neuroscience research that focuses on characterizing neural circuit architectures that can accomplish these predictive functions, and on how the associated processes may break down or become aberrant within clinical conditions. Here, we provide a brief review of examples of recent work on the application of predictive processing models of brain function to study clinical (psychiatric) disorders, with the aim of highlighting current directions and their potential clinical utility. We offer examples of recent conceptual models, formal mathematical models, and applications of such models in empirical research in clinical populations, with a focus on making this material accessible to clinicians without expertise in computational neuroscience. In doing so, we aim to highlight the potential insights and opportunities that understanding the brain as a prediction machine may offer to clinical research and practice.

Empathy Enhancement Based on a Semiotics Training Program: A Longitudinal Study in Peruvian Medical Students

Background

Empathy, as a core element of medical professionalism, is part of leadership in medicine. This attribute, predominantly cognitive, involves understanding and communication capacity. Empathy can be enhanced with courses on medical semiotics. It appears adequate to apply this enhancement in the early stages of professional training. Based on this, this study was performed with the purpose of demonstrating the positive effect that an academic course on medical semiotics has on the development of empathy in medical students.

Methods

A quasi-experimental study was conducted in one School of Medicine in Peru, where medical students had to attend a 17-week course on medical semiotics as part of their regular training. The sample, composed by 269 students, included two cohorts of third-year medical students. As main measures, the Jefferson Scales of Empathy (JSE), inter-professional collaboration (JSAPNC), and lifelong learning (JeffSPLL), were used. In addition, students’ scores evaluating theoretical and practical aspects of the course were collected once the course was finished. Pre- and post-tests were administered in week 1 and in week 17. Analyses compared measures in both moments and in time. Inter-professional collaboration and lifelong learning scores and empathy scores were used as discriminant and convergent validity measures of students’ course scores, respectively.

Results

Gender differences on empathy appeared, but only at the beginning. In the entire sample, empathy enhancement was confirmed in time (p < 0.001), with a large effect size (r = 0.45). This effect was also observed in both gender groups, separately. On the contrary, no changes appeared in inter-professional collaboration and in lifelong learning abilities in time. In addition, a positive correlation was observed among empathy, inter-professional collaboration and lifelong learning abilities at the beginning and at the end, confirming that the improvement observed was specific for empathy and explained by the educational intervention assessed.

Conclusion

These findings bring empiric evidence supporting the positive effect that training in medical semiotics has on empathy. In addition, these findings highlight some gender differences in the development of empathy in medical students.

Thinking through others' emotions: Incorporating the role of emotional state inference in thinking through other minds

The active inference framework offers an attractive starting point for understanding cultural cognition. Here, we argue that affective dynamics are essential to include when constructing this type of theory. We highlight ways in which interactions between emotional responses and the perception of those responses, both within and between individuals, can play central roles in both motivating and constraining sociocultural practices.

The Role of Emotional vs. Cognitive Intelligence in Economic Decision-Making Amongst Older Adults

The links between emotions, bio-regulatory processes, and economic decision-making are well-established in the context of age-related changes in fluid, real-time, decision competency. The objective of the research reported here is to assess the relative contributions, interactions, and impacts of affective and cognitive intelligence in economic, value-based decision-making amongst older adults. Additionally, we explored this decision-making competency in the context of the neurobiology of aging by examining the neuroanatomical correlates of intelligence and decision-making in an aging cohort. Thirty-nine, healthy, community dwelling older adults were administered the Iowa Gambling Task (IGT), an ecologically valid laboratory measure of complex, economic decision-making; along with standardized, performance-based measures of cognitive and emotional intelligence (EI). A smaller subset of this group underwent structural brain scans from which thicknesses of the frontal, parietal, temporal, occipital, cingulate cortices and their sub-sections, were computed. Fluid (online processing) aspects of Perceptual Reasoning cognitive intelligence predicted superior choices on the IGT. However, older adults with higher overall emotional intelligence (EI) and higher Experiential EI area/sub-scores learned faster to make better choices on the IGT, even after controlling for cognitive intelligence and its area scores. Thickness of the left rostral anterior cingulate (associated with fluid affective, processing) mediated the relationship between age and Experiential EI. Thickness of the right transverse temporal gyrus moderated the rate of learning on the IGT. In conclusion, our data suggest that fluid processing, which involves "online," bottom-up, cognitive processing, predicts value-based decision-making amongst older adults, while crystallized intelligence, which relies on "offline" previously acquired knowledge, does not. However, only emotional intelligence, especially its fluid "online" aspects of affective processing predicts the rate of learning in situations of complex choice, especially when there is a paucity of cues/information available to guide decision-making. Age-related effects on these cognitive, affective and decision mechanisms may have neuroanatomical correlates, especially in regions that form a subset of the human mirror-neuron and mentalizing systems. While superior decision-making may be stereotypically associated with "smarter people" (i.e., higher cognitive intelligence), our data indicate that emotional intelligence has a significant role to play in the economic decisions of older adults.

Ability-Based Emotional Intelligence Is Associated With Greater Cardiac Vagal Control and Reactivity

Several distinct models of emotional intelligence (EI) have been developed over the past two decades. The ability model conceptualizes EI as a narrow set of interconnected, objectively measured, cognitive-emotional abilities, including the ability to perceive, manage, facilitate, and understand the emotions of the self and others. By contrast, trait or mixed models focus on subjective ratings of emotional/social competencies. Theoretically, EI is associated with neurobiological processes involved in emotional regulation and reactivity. The neurovisceral integration (NVI) model proposes a positive relationship between cardiac vagal control (CVC) and cognitive-emotional abilities similar to those encompassed by EI. The current study examined the association between CVC and EI. Because ability EI is directly tied to actual performance on emotional tasks, we hypothesized that individuals with higher ability-based EI scores would show greater levels of CVC at rest, and in response to a stressful task. Because mixed-models of EI are not linked directly to observable emotional behavior, we predicted no association with CVC. Consistent with expectations, individuals with higher levels of ability EI, but not mixed EI, had higher levels of CVC. We also found that individuals with greater levels of CVC who demonstrated reactivity to a stress induction had significantly higher EI compared to individuals that did not respond to the stress induction. Our findings support the theoretically expected overlap between constructs within the NVI model and ability EI model, however, the observed effect size was small, and the associations between EI and CVC should not be taken to indicate a causal connection. Results suggest that variance in the ability to understand emotional processes in oneself and to reason about one's visceral experience may facilitate better CVC. Future work manipulating either CVC or EI may prove informative in teasing apart the causal role driving their observed relationship.

Parameters as Trait Indicators: Exploring a Complementary Neurocomputational Approach to Conceptualizing and Measuring Trait Differences in Emotional Intelligence

Current assessments of trait emotional intelligence (EI) rely on self-report inventories. While this approach has seen considerable success, a complementary approach allowing objective assessment of EI-relevant traits would provide some potential advantages. Among others, one potential advantage is that it would aid in emerging efforts to assess the brain basis of trait EI, where self-reported competency levels do not always match real-world behavior. In this paper, we review recent experimental paradigms in computational cognitive neuroscience (CCN), which allow behavioral estimates of individual differences in range of parameter values within computational models of neurocognitive processes. Based on this review, we illustrate how several of these parameters appear to correspond well to EI-relevant traits (i.e., differences in mood stability, stress vulnerability, self-control, and flexibility, among others). In contrast, although estimated objectively, these parameters do not correspond well to the optimal performance abilities assessed within competing “ability models” of EI. We suggest that adapting this approach from CCN—by treating parameter value estimates as objective trait EI measures—could (1) provide novel research directions, (2) aid in characterizing the neural basis of trait EI, and (3) offer a promising complementary assessment method.