Greater cortical thickness within the limbic visceromotor network predicts higher levels of trait emotional awareness

Higher emotional granularity relates to greater inferior frontal cortex cortical thickness in healthy, older adults

Individuals with high emotional granularity make fine-grained distinctions between their emotional experiences. To have greater emotional granularity, one must acquire rich conceptual knowledge of emotions and use this knowledge in a controlled and nuanced way. In the brain, the neural correlates of emotional granularity are not well understood. While the anterior temporal lobes, angular gyri, and connected systems represent conceptual knowledge of emotions, inhibitory networks with hubs in the inferior frontal cortex (i.e., posterior inferior frontal gyrus, lateral orbitofrontal cortex, and dorsal anterior insula) guide the selection of this knowledge during emotions. We investigated the structural neuroanatomical correlates of emotional granularity in 58 healthy, older adults (ages 62-84 years), who have had a lifetime to accrue and deploy their conceptual knowledge of emotions. Participants reported on their daily experience of 13 emotions for 8 weeks and underwent structural magnetic resonance imaging. We computed intraclass correlation coefficients across daily emotional experience surveys (45 surveys on average per participant) to quantify each participant's overall emotional granularity. Surface-based morphometry analyses revealed higher overall emotional granularity related to greater cortical thickness in inferior frontal cortex (pFWE < 0.05) in bilateral clusters in the lateral orbitofrontal cortex and extending into the left dorsal anterior insula. Overall emotional granularity was not associated with cortical thickness in the anterior temporal lobes or angular gyri. These findings suggest individual differences in emotional granularity relate to variability in the structural neuroanatomy of the inferior frontal cortex, an area that supports the controlled selection of conceptual knowledge during emotional experiences.

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.

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.

Blue-Light Therapy Strengthens Resting-State Effective Connectivity within Default-Mode Network after Mild TBI

Background:

Emerging evidence suggests that post concussive symptoms, including mood changes, may be improved through morning blue-wavelength light therapy (BLT). However, the neurobiological mechanisms underlying these effects remain unknown. We hypothesize that BLT may influence the effective brain connectivity (EC) patterns within the default-mode network (DMN), particularly involving the medial prefrontal cortex (MPFC), which may contribute to improvements in mood.

Methods:

Resting-state functional MRI data were collected from 41 healthy-controls (HCs) and 28 individuals with mild traumatic brain injury (mTBI). Individuals with mTBI also underwent a diffusion-weighted imaging scan and were randomly assigned to complete either 6 weeks of daily morning BLT (N = 14) or amber light therapy (ALT; N = 14). Advanced spectral dynamic causal modeling (sDCM) and diffusion MRI connectometry were used to estimate EC patterns and structural connectivity strength within the DMN, respectively.

Results:

The sDCM analysis showed dominant connectivity pattern following mTBI (pre-treatment) within the hemisphere contralateral to the one observed for HCs. BLT, but not ALT, resulted in improved directional information flow (ie, EC) from the left lateral parietal cortex (LLPC) to MPFC within the DMN. The improvement in EC from LLPC to MPFC was accompanied by stronger structural connectivity between the 2 areas. For the BLT group, the observed improvements in function and structure were correlated (at a trend level) with changes in self-reported happiness.

Conclusions:

The current preliminary findings provide empirical evidence that morning short-wavelength light therapy could be used as a novel alternative rehabilitation technique for mTBI.

Trial registry:

The research protocols were registered in the ClinicalTrials.gov database (CT Identifiers NCT01747811 and NCT01721356).

Large-Scale Morphological Network Efficiency of Human Brain: Cognitive Intelligence and Emotional Intelligence

Network efficiency characterizes how information flows within a network, and it has been used to study the neural basis of cognitive intelligence in adolescence, young adults, and elderly adults, in terms of the white matter in the human brain and functional connectivity networks. However, there were few studies investigating whether the human brain at different ages exhibited different underpins of cognitive and emotional intelligence (EI) from young adults to the middle-aged group, especially in terms of the morphological similarity networks in the human brain. In this study, we used 65 datasets (aging 18–64), including sMRI and behavioral measurements, to study the associations of network efficiency with cognitive intelligence and EI in young adults and the middle-aged group. We proposed a new method of defining the human brain morphological networks using the morphological distribution similarity (including cortical volume, surface area, and thickness). Our results showed inverted age × network efficiency interactions in the relationship of surface-area network efficiency with cognitive intelligence and EI: a negative age × global efficiency (nodal efficiency) interaction in cognitive intelligence, while a positive age × global efficiency (nodal efficiency) interaction in EI. In summary, this study not only proposed a new method of morphological similarity network but also emphasized the developmental effects on the brain mechanisms of intelligence from young adult to middle-aged groups and may promote mental health study on the middle-aged group in the future.

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.

Affective agnosia: a core affective processing deficit in the alexithymia spectrum

Affective agnosia, an impairment in knowing how one feels emotionally, has been described as an extreme deficit in the experience and expression of emotion that may confer heightened risk for adverse medical outcomes. Alexithymia, by contrast, has been proposed as an over-arching construct that includes a spectrum of deficits of varying severity, including affective agnosia at the more severe end. This perspective has been challenged by Taylor and colleagues, who argue that the concept of affective agnosia is unnecessary. We compare these two perspectives by highlighting areas of agreement, reasons for asserting the importance of the affective agnosia concept, errors in Taylor and colleagues’ critique, and measurement issues. The need for performance-based measures of the ability to mentally represent emotional states in addition to metacognitive measures is emphasized. We then draw on a previously proposed three-process model of emotional awareness that distinguishes affective response generation, conceptualization and cognitive control processes which interact to produce a variety of emotional awareness and alexithymia phenotypes - including affective agnosia. The tools for measuring these three processes, their neural substrates, the mechanisms of brain-body interactions that confer heightened risk for adverse medical outcomes, and the differential treatment implications for different kinds of deficits are described. By conceptualizing alexithymia as a spectrum of deficits, the opportunity to match specific deficit mechanisms with personalized treatment for patients will be enhanced.

Transient effects of multi-infusion ketamine augmentation on treatment-resistant depressive symptoms in patients with treatment-resistant bipolar depression - An open-label three-week pilot study

INTRODUCTION

While the psychiatric benefits of ketamine have been verified through clinical trials, there is limited information about ketamine augmentation in patients with treatment-resistant bipolar depression (TRBPD). Hence, in the present study, we investigate the therapeutic efficacy and functional brain alterations associated with multi-infusion ketamine augmentation in patients with TRBPD.

METHODS

The present three-week study included 38 patients with TRBPD, all of whom received a series of nine ketamine injections over the study period. The Hamilton Depression Rating Scale (HAMD) was used to assess the effects of multi-infusion ketamine combined with mood stabilizers. Brain function was evaluated by global functional connectivity density (gFCD).

RESULTS

Adjunctive treatment with multiple infusions of ketamine, when combined with a mood stabilizer, could effectively alleviate depressive symptoms for one week, yet the symptoms began to relapse during the second week. Functional brain alterations were detected via gFCD. Specifically, gFCD reductions were mainly found in the bilateral insula, right caudate nucleus, and bilateral inferior frontal gyrus, while increased gFCD was mainly located in the bilateral postcentral gyrus, subgenual anterior cingulate cortex, bilateral thalamus, and cerebellum. Although gFCD alterations were sustained for up to three weeks after the first ketamine infusion, the antidepressant effects of ketamine augmentation sharply declined from the end of the second week of treatment.

CONCLUSIONS

Multi-infusion ketamine augmentation can rapidly alleviate depressive symptoms in patients with TRBPD. The clinical effects were primarily visible in the first week after treatment and partially sustained for two weeks; however, the therapeutic effects and related functional brain alterations sharply decreased from the end of the second week. Based on these findings, we demonstrated that the clinical efficacy and functional brain alterations induced by ketamine augmentation are transient.

Adjunct ketamine treatment of depression in treatment-resistant schizophrenia patients is unsatisfactory in pilot and secondary follow-up studies

OBJECTIVE

To investigate the effects of adjunct ketamine treatment on chronic treatment-resistant schizophrenia patients with treatment-resistant depressive symptoms (CTRS-TRD patients), including alterations in brain function.

METHODS

Intravenous ketamine (0.5 mg/kg body weight) was administered to CTRS-TRD patients over a 1-hr period on days 1, 4, 7, 10, 13, 16, 19, 22, and 25 of our initial pilot study. This treatment method was subsequently repeated 58 days after the start of the pilot study for a secondary follow-up study. Calgary Depression Scale for Schizophrenia (CDSS), Positive and Negative Syndrome Scale (PANSS), and regional homogeneity (ReHo) results were used to assess treatment effects and alterations in brain function throughout the entire duration of our studies.

RESULTS

Between day 7 and day 14 of the first treatment, CDSS scores were reduced by 63.8% and PANSS scores were reduced by 30.04%. In addition, ReHo values increased in the frontal, temporal, and parietal lobes. However, by day 21, depressive symptoms relapsed. During the second treatment period, CDSS and PANSS scores exhibited no significant differences compared to baseline between day 58 and day 86. On day 65, ReHo values were higher in the temporal, frontal, and parietal lobes. However, on day 79, the increase in ReHo values completely disappeared.

CONCLUSIONS

Depressive symptoms in CTRS-TRD patients were alleviated with adjunct ketamine treatment for only 1 week during the first treatment period. Moreover, after 1 month, the antidepressant effects of ketamine on CTRS-TRD patients completely disappeared. Correspondingly, ReHo alterations induced by ketamine in the CTRS-TRD patients were not maintained for more than 3 weeks. These pilot findings indicate that adjunct ketamine treatment is not satisfactory for CTRS-TRD patients.

Simulating Emotions: An Active Inference Model of Emotional State Inference and Emotion Concept Learning

The ability to conceptualize and understand one's own affective states and responses - or "Emotional awareness" (EA) - is reduced in multiple psychiatric populations; it is also positively correlated with a range of adaptive cognitive and emotional traits. While a growing body of work has investigated the neurocognitive basis of EA, the neurocomputational processes underlying this ability have received limited attention. Here, we present a formal Active Inference (AI) model of emotion conceptualization that can simulate the neurocomputational (Bayesian) processes associated with learning about emotion concepts and inferring the emotions one is feeling in a given moment. We validate the model and inherent constructs by showing (i) it can successfully acquire a repertoire of emotion concepts in its "childhood", as well as (ii) acquire new emotion concepts in synthetic "adulthood," and (iii) that these learning processes depend on early experiences, environmental stability, and habitual patterns of selective attention. These results offer a proof of principle that cognitive-emotional processes can be modeled formally, and highlight the potential for both theoretical and empirical extensions of this line of research on emotion and emotional disorders.

Higher levels of trait emotional awareness are associated with more efficient global information integration throughout the brain: a graph-theoretic analysis of resting state functional connectivity

Previous studies have suggested that trait differences in emotional awareness (tEA) are clinically relevant, and associated with differences in neural structure/function. While multiple leading theories suggest that conscious awareness requires widespread information integration across the brain, no study has yet tested the hypothesis that higher tEA corresponds to more efficient brain-wide information exchange. Twenty-six healthy volunteers (13 females) underwent a resting state functional magnetic resonance imaging scan, and completed the Levels of Emotional Awareness Scale (LEAS; a measure of tEA) and the Wechsler Abbreviated Scale of Intelligence (WASI-II; a measure of general intelligence quotient [IQ]). Using a whole-brain (functionally defined) region of interest (ROI) atlas, we computed several graph theory metrics to assess the efficiency of brain-wide information exchange. After statistically controlling for differences in age, gender and IQ, we first observed a significant relationship between higher LEAS scores and greater average degree (i.e. overall whole-brain network density). When controlling for average degree, we found that higher LEAS scores were also associated with shorter average path lengths across the collective network of all included ROIs. These results jointly suggest that individuals with higher tEA display more efficient global information exchange throughout the brain. This is consistent with the idea that conscious awareness requires global accessibility of represented information.

Common and Unique Neural Systems Underlying the Working Memory Maintenance of Emotional vs. Bodily Reactions to Affective Stimuli: The Moderating Role of Trait Emotional Awareness

Many leading theories suggest that the neural processes underlying the experience of one's own emotional reactions partially overlap with those underlying bodily perception (i.e., interoception, somatosensation, and proprioception). However, the goal-directed maintenance of one's own emotions in working memory (EWM) has not yet been compared to WM maintenance of one's own bodily reactions (BWM). In this study, we contrasted WM maintenance of emotional vs. bodily reactions to affective stimuli in 26 healthy individuals while they underwent functional magnetic resonance imaging. Specifically, we examined the a priori hypothesis that individual differences in trait emotional awareness (tEA) would lead to greater differences between these two WM conditions within medial prefrontal cortex (MPFC). We observed that MPFC activation during EWM (relative to BWM) was positively associated with tEA. Whole-brain analyses otherwise suggested considerable similarity in the neural activation patterns associated with EWM and BWM. In conjunction with previous literature, our findings not only support a central role of body state representation/maintenance in EWM, but also suggest greater engagement of MPFC-mediated conceptualization processes during EWM in those with higher tEA.

The role of medial prefrontal cortex in the working memory maintenance of one's own emotional responses

The role of medial prefrontal cortex (MPFC) in maintaining emotional information within working memory (WM) remains insufficiently investigated – with some studies suggesting this process activates MPFC and others suggesting its activity is suppressed. To reconcile these different results, we asked 26 healthy participants to complete a WM task involving the maintenance of emotional content (EWM), visual content (VWM), or no content (“rest”) after exposure to emotion-provoking images. We also assessed individual differences in emotional awareness (EA). We observed that dorsal MPFC was more active during EWM than VWM; further, relative to the rest condition, both of these WM conditions involved suppression of ventral MPFC. We also observed that the dorsal anterior cingulate subregion of dorsal MPFC was positively associated with EA. We discuss how these results may be able to reconcile the findings of previous EWM studies, and extend understanding of the relationship between MPFC, EA, and WM.