Contributions of self-report and performance-based individual differences measures of social cognitive ability to large-scale neural network functioning

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.

The neural signatures of social hierarchy-related learning and interaction: A coordinate- and connectivity-based meta-analysis

Numerous neuroimaging studies have investigated the neural mechanisms of two mutually independent yet closely related cognitive processes aiding humans to navigate complex societies: social hierarchy-related learning (SH-RL) and social hierarchy-related interaction (SH-RI). To integrate these heterogeneous results into a more fine-grained and reliable characterization of the neural basis of social hierarchy, we combined coordinate-based meta-analyses with connectivity and functional decoding analyses to understand the underlying neuropsychological mechanism of SH-RL and SH-RI. We identified the anterior insula and temporoparietal junction (dominance detection), medial prefrontal cortex (information updating and computation), and intraparietal sulcus region, amygdala, and hippocampus (social hierarchy representation) as consistent activated brain regions for SH-RL, but the striatum, amygdala, and hippocampus associated with reward processing for SH-RI. Our results provide an overview of the neural architecture of the neuropsychological processes underlying how we understand, and interact within, social hierarchy.

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.

Changes in Brain Function Networks in Patients With Amnestic Mild Cognitive Impairment: A Resting-State fMRI Study

Patients with amnestic mild cognitive impairment (aMCI) are at high risk of developing dementia. This study used resting-state functional magnetic resonance imaging (rs-fMRI) and an independent component analysis (ICA) approach to explore changes in functional connectivity (FC) in the default mode network (DMN), executive control network (ECN), and salience network (SN). Thirty patients with aMCI and 30 healthy controls (HCs) were enrolled. All the participants underwent an rs-fMRI scan. The brain FC in DMN, ECN, and SN was calculated using the ICA approach. We found that the FC of brain regions in DMN decreased significantly and that of brain regions in ECN increased, which was in accordance with the findings of previous studies on Alzheimer's disease (AD) and aMCI. We also found that the FC of brain regions in SN increased, which was different from the findings of previous studies on AD. The increase in FC in brain regions in SN might result from different pathophysiological states in AD and aMCI, indicating that a decrease in FC in SN does not occur in a person with aMCI. These results are consistent with those of previous studies using the voxel-mirrored homotopic connectivity approach and seed-based correlation analysis. We therefore considered that the decrease in FC in DMN and the increase in FC in ECN and SN might be peculiar patterns observed on the rs-fMRI of a person with aMCI. These findings may contribute to the development of imaging biomarkers for the diagnosis of aMCI.

Intranetwork and Internetwork Effects of Navigated Transcranial Magnetic Stimulation Using Low- and High-Frequency Pulse Application to the Dorsolateral Prefrontal Cortex: A Combined rTMS-fMRI Approach

PURPOSE

Although transcranial magnetic stimulation (TMS) is routinely applied in neuroscience and clinical settings, not much is known about its effects on brain networks. Therefore, this pilot study was set up using repetitive navigated transcranial magnetic stimulation (rTMS) combined with resting-state functional MRI (rs-fMRI) to explore frequency-dependent stimulation effects on an intranetwork and internetwork level.

METHODS

Six healthy subjects (median age: 23.5 years) underwent two rTMS sessions (1 and 10 Hz), 7 days apart, and prestimulation and poststimulation rs-fMRI. Repetitive navigated transcranial magnetic stimulation was delivered to the left dorsolateral prefrontal cortex, with the exact stimulation target being determined by independent component analysis. Alterations of functional connectivity strength were evaluated using seed-based correlation analyses within and between the salience network, central executive network, and posterior and anterior default mode network.

RESULTS

Low-frequency rTMS resulted in significant intranetwork alterations only for the anterior default mode network and primarily within the left hemisphere. In contrast, high-frequency rTMS led to changes within all four networks of interest. Moreover, the posterior and anterior default mode network largely showed opposite effects to rTMS, and the anterior default mode network was rather isolated from the other networks, which was especially true for low-frequency rTMS. Changes in functional connectivity strength because of low-frequency rTMS were even detectable 7 days after stimulation.

CONCLUSIONS

This is one of the first studies using neuronavigated TMS with independent component analysis-based target selection to explore frequency-dependent stimulation effects in a combined rTMS-fMRI approach. Future studies including higher subject numbers may define the underlying mechanisms for the different responses to low- and high-frequency rTMS.

Mean diffusivity associated with trait emotional intelligence

Previous neuroimaging studies have suggested that the neural bases of trait emotional intelligence (TEI) lie in the social cognition network (SCN) and the somatic marker circuitry (SMC). The current study was the first to investigate the associations of total TEI factors and subfactors with mean diffusivity (MD) of these networks as well as regional MD of the dopaminergic system (MDDS). We found that TEI intrapersonal factor score and total TEI score were negatively correlated with regional MDDS in the vicinity of the right putamen and right pallidum and that TEI intrapersonal factor score was negatively correlated with MD values of the fusiform gyrus. Total TEI score and TEI factor scores were positively correlated with MD values of various areas within or adjacent to SCN components, SMC structures and the lateral prefrontal cortex (LPFC). Our MD findings demonstrated the importance of the dopaminergic system to TEI and implicate the SCN, SMC and LPFC in TEI. Future studies are required to investigate the implications of positive and negative associations with MD values.

A meta-analysis of the relationship between emotion recognition ability and intelligence

The ability to recognise others' emotions from nonverbal cues (emotion recognition ability, ERA) is measured with performance-based tests and has many positive correlates. Although researchers have long proposed that ERA is related to general mental ability or intelligence, a comprehensive analysis of this relationship is lacking. For instance, it remains unknown whether the magnitude of the association varies by intelligence type, ERA test features, as well as demographic variables. The present meta-analysis examined the relationship between ERA and intelligence based on 471 effect sizes from 133 samples and found a significant mean effect size (controlled for nesting within samples) of r = .19. Different intelligence types (crystallized, fluid, spatial, memory, information processing speed and efficiency) yielded similar effect sizes, whereas academic achievement measures (e.g. SAT scores) were unrelated to ERA. Effect sizes were higher for ERA tests that simultaneously present facial, vocal, and bodily cues (as compared to tests using static pictures) and for tests with higher reliability and more emotions. Results were unaffected by most study and sample characteristics, but effect size increased with higher mean age of the sample. These findings establish ERA as sensory-cognitive ability that is distinct from, yet related to, intelligence.

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.

Emotional intelligence is associated with connectivity within and between resting state networks

Emotional intelligence (EI) is defined as an individual’s capacity to accurately perceive, understand, reason about, and regulate emotions, and to apply that information to facilitate thought and achieve goals. Although EI plays an important role in mental health and success in academic, professional and social realms, the neurocircuitry underlying this capacity remains poorly characterized, and no study to date has yet examined the relationship between EI and intrinsic neural network function. Here, in a sample of 54 healthy individuals (28 women, 26 men), we apply independent components analysis (ICA) with dual regression to functional magnetic resonance imaging (fMRI) data acquired while subjects were resting in the scanner to investigate brain circuits (intrinsic resting state networks) whose activity is associated with greater self-reported (i.e. Trait) and objectively measured (i.e. Ability) EI. We show that higher Ability EI, but not Trait EI, is associated with stronger negatively correlated spontaneous fMRI signals between the basal ganglia/limbic network (BGN) and posterior default mode network (DMN), and regions involved in emotional processing and regulation. Importantly, these findings suggest that the functional connectivity within and between intrinsic networks associated with mentation, affective regulation, emotion processing, and reward are strongly related to ability EI.

Mindfulness-related differences in neural response to own infant negative versus positive emotion contexts

Mindfulness is thought to promote well-being by shaping the way people respond to challenging social-emotional situations. Current understanding of how this occurs at the neural level is based on studies of response to decontextualized emotion stimuli that may not adequately represent lived experiences. In this study, we tested relations between mothers' dispositional mindfulness and neural responses to their own infant in different emotion-eliciting contexts. Mothers (n = 25) engaged with their 3-month-old infants in videorecorded tasks designed to elicit negative (arm restraint) or positive (peekaboo) emotion. During a functional MRI session, mothers were presented with 15-s clips from these recordings, and dispositional mindfulness scores were used to predict their neural responses to arm restraint > peekaboo videos. Mothers higher in nonreactivity showed relatively lower activation to their infants’ arm restraint compared to peekaboo videos in hypothesized regions—insula and dorsal prefrontal cortex—as well as non-hypothesized regions. Other mindfulness dimensions were associated with more limited areas of lower (nonjudgment) and higher (describing) activation in this contrast. Mothers who were higher in mindfulness generally activated more to the positive emotion context and less to the negative emotion context in perceptual and emotion processing areas, a pattern that may help to explain mindfulness-related differences in well-being.