Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches

How do "words poorly expressed emotion" affect mental health? The mediating role of affect labelling effect

Previous studies have found that people with high negative emotional granularity(NEG) tend to have better health levels. It is generally believed that this is due to the selection and application of explicit emotion regulation strategies that affect mental health. However, no research has yet examined a more fundamental process, the role of affect labelling, an implicit emotion regulation strategy. This study focuses on the aforementioned issues and uses the experience sampling method to categorise participants into groups with high and low NEG. Using an affect labelling paradigm with ERP(event-related potential) technology, the study measures the effects of affect labelling in participants. Furthermore, it assesses the mental health levels of the participants through questionnaires to explore whether the affect labelling effect serves as a mediator between NEG and mental health. The results show that: (1) The high-NEG group exhibited significantly lower LPP wave amplitudes under affect labelling compared to under non-affect labelling, whereas the low-NEG group did not show significant differences. The results indicate that only the high-NEG group can produce the affect labelling effect. (2) The affect labelling effect mediates the relationship between NEG and mental health, meaning that NEG predicts mental health through the affect labelling effect.

Impaired implicit emotion regulation in patients with panic disorder: An event-related potential study on affect labeling

BACKGROUND

Panic disorder (PD) involves emotion dysregulation, but its underlying mechanisms remain poorly understood. Previous research suggests that implicit emotion regulation may play a central role in PD-related emotion dysregulation and symptom maintenance. However, there is a lack of studies exploring the neural mechanisms of implicit emotion regulation in PD using neurophysiological indicators.

AIM

To study the neural mechanisms of implicit emotion regulation in PD with event-related potentials (ERP).

METHODS

A total of 25 PD patients and 20 healthy controls (HC) underwent clinical eva-luations. The study utilized a case-control design with random sampling, selecting participants for the case group from March to December 2018. Participants performed an affect labeling task, using affect labeling as the experimental condition and gender labeling as the control condition. ERP and behavioral data were recorded to compare the late positive potential (LPP) within and between the groups.

RESULTS

Both PD and HC groups showed longer reaction times and decreased accuracy under the affect labeling. In the HC group, late LPP amplitudes exhibited a dynamic pattern of initial increase followed by decrease. Importantly, a significant group × condition interaction effect was observed. Simple effect analysis revealed a reduction in the differences of late LPP amplitudes between the affect labeling and gender labeling conditions in the PD group compared to the HC group. Furthermore, among PD patients under the affect labeling, the late LPP was negatively correlated with disease severity, symptom frequency, and intensity.

CONCLUSION

PD patients demonstrate abnormalities in implicit emotion regulation, hampering their ability to mobilize cognitive resources for downregulating negative emotions. The late LPP amplitude in response to affect labeling may serve as a potentially valuable clinical indicator of PD severity.

Brain imaging studies of emotional well-being: a scoping review

This scoping review provides an overview of previous empirical studies that used brain imaging techniques to investigate the neural correlates of emotional well-being (EWB). We compiled evidence on this topic into one accessible and usable document as a foundation for future research into the relationship between EWB and the brain. PRISMA 2020 guidelines were followed. We located relevant articles by searching five electronic databases with 95 studies meeting our inclusion criteria. We explored EWB measures, brain imaging modalities, research designs, populations studied, and approaches that are currently in use to characterize and understand EWB across the literature. Of the key concepts related to EWB, the vast majority of studies investigated positive affect and life satisfaction, followed by sense of meaning, goal pursuit, and quality of life. The majority of studies used functional MRI, followed by EEG and event-related potential-based EEG to study the neural basis of EWB (predominantly experienced affect, affective perception, reward, and emotion regulation). It is notable that positive affect and life satisfaction have been studied significantly more often than the other three aspects of EWB (i.e., sense of meaning, goal pursuit, and quality of life). Our findings suggest that future studies should investigate EWB in more diverse samples, especially in children, individuals with clinical disorders, and individuals from various geographic locations. Future directions and theoretical implications are discussed, including the need for more longitudinal studies with ecologically valid measures that incorporate multi-level approaches allowing researchers to better investigate and evaluate the relationships among behavioral, environmental, and neural factors.

Systematic review registration

https://osf.io/t9cf6/.

A 4-session written emotional disclosure intervention lowers 6-month sympathoadrenal urinary output in persons living with HIV

OBJECTIVE

We previously reported that a brief guided written emotional disclosure (WED) intervention resulted in significant reductions in post-traumatic stress disorder (PTSD) symptomology in women, but not men, living with HIV. Levels of 24-hour urinary output of epinephrine (E) and norepinephrine (NE) are shown to be elevated in persons diagnosed with PTSD. The current study tested whether there was an effect for the 4-week WED intervention on 6-month change in urinary E and NE output amongst persons living with HIV.

METHOD

Fourteen women and 11 men living with HIV randomized to four 30-min expressive writing sessions of either trauma writing or daily events writing in the parent trial were included based upon collection of urine specimens at baseline, 1-, and 6-months after the intervention. Total volume (µg) and concentration (µg/ml) of urinary E and NE were derived from the specimens as study outcomes.

RESULTS

Four repeated measures analyses of covariance (ANCOVA) were performed to evaluate study outcomes using trauma- versus daily-writing as the between-subject factors and collection time point as the within-subject factor, controlling for age and sex. A group x time interaction was observed wherein the trauma writing treatment group showed a significantly greater decrease in total urinary output, F(2, 46) = 4.03, p = .03, and concentration, F(2, 46) = 4.74, p = .01 of epinepherine. Post-hoc analyses revealed the interaction effect for the total, F(2, 22) = 4.82, p = .03, and concentration, F(2, 22) = 7.57, p = .005, of urinary E output over 6-months was significant for women. Interactions were not observed in urinary NE output.

CONCLUSIONS

Significant reductions in the total output and concentration of urinary E were found up to 6-months following initiation of a 4-session guided written emotional disclosure intervention. Profiles of sympathoadrenal activity and response to expressive writing differ between men and women living with HIV. Futher research is need to characterize the putative pathways linking sympathoadrenal response to upstream neurobiological function and downstream inflammatory-immune status in women living with HIV and PTSD.

Current and lasting effects of affect labeling on late positive potential (LPP) amplitudes elicited by negative events

INTRODUCTION

Labeling the emotional aspect of self-unrelated stimuli (i.e., affect labeling) is a crucial strategy for implicit emotion regulation. However, it is uncertain whether affect labeling influences event-related potential (ERP) responses (e.g., the late positive potential, LPP) to negative stimuli in comparison with control conditions in which attention is shifted to the emotional content of the stimuli (e.g., affect matching). Additionally, it is unknown whether affect labeling has a lasting effect on the processing of negative stimuli.

METHODS

Participants were required to label the emotion (negative or neutral) of target pictures with two words, to match the emotion with alternative pictures or to merely view the target pictures. Target pictures were presented again immediately after the regulation task. After all the target pictures had been labeled, matched and viewed, the pictures were re-exposed for the third time.

RESULTS

The results showed that negative pictures elicited larger late LPP responses during the affect labeling task than during other tasks. However, the LPP responses were smaller for negative pictures in the affect labeling condition than in the other conditions when target pictures were re-exposed immediately after the task. When target pictures were re-presented again long after the regulation tasks, the LPP responses were smaller for negative stimuli with a history of affect labeling than viewing, whereas this effect did not differ between the affect labeling and matching conditions.

CONCLUSION

The current findings suggest that affect labeling has current effects and, to some extent, has lasting effects on negative stimulus processing.

A Network Investigation of Core Mindfulness Processes

Objective

Mindfulness has been associated with improved psychological well-being and health, although outcomes from mindfulness-based interventions are mixed. One challenge is a limited understanding about which specific processes are core to mindfulness. Network analysis offers a method to characterize the core processes of mindfulness.

Methods

This study used network analysis to identify which processes are central to mindfulness (have the strongest connectivity with other mindfulness processes) as measured by the Five Facets Mindfulness Questionnaire- Short Form, analyzed at the item-level. Data were obtained from baseline of a randomized clinical trial of smartphone app-based mindfulness training for smoking cessation.

Results

The most central processes in the mindfulness network included, "I think some of my emotions are bad or inappropriate and I shouldn't feel them," an aspect of Nonjudgment/acceptance; as well as "I can easily put my beliefs, opinions, and expectations into words," and "It's hard for me to find the words to describe what I'm thinking," aspects of Describing.

Conclusions

Findings help to clarify which processes are to mindfulness, contributing to a better understanding of the definition of mindfulness, and suggest factors that may be promising to target in mindfulness-based interventions. Future research should examine if mindfulness-based interventions may be improved by targeting these core mindfulness processes.

Affect labeling: The role of timing and intensity

A growing number of studies have shown that labeling negative feelings can down-regulate distress. The present study aimed to test the effectiveness of affect labeling while manipulating two factors known to influence the emotion regulation process, namely timing, and emotional intensity. In Experiment 1, sixty-three participants completed a performance-based affect labeling paradigm in which they had to choose between two labels that best describe their feeling. Participants were randomly assigned to one of three experimental conditions: (1) Simultaneous labeling- the labeling occurs while watching the aversive picture. (2) Subsequent labeling- the labeling occurs immediately after watching the aversive picture. (3) Delayed labeling- the labeling occurs 10 seconds after watching the aversive picture. We found that affect labeling efficiently down-regulated distress independent of the labeling timing. In Experiment 2, seventy-nine participants utilized simultaneous labeling for aversive pictures with low and high intensity. We revealed that while affect labeling reduces distress in high-intensity aversive conditions, it increases distress in low-intensity conditions. The results question the standard advice, which calls to count to 10 before you speak in highly aversive states. In addition, it suggests that affect labeling can be beneficial in high-intensity conditions. However, it should be used with caution in low-intensity conditions.

Automatic Decision-Making Style Recognition Method Using Kinect Technology

In recent years, somatosensory interaction technology, represented by Microsoft's Kinect hardware platform, has been widely used in various fields, such as entertainment, education, and medicine. Kinect technology can easily capture and record behavioral data, which provides new opportunities for behavioral and psychological correlation analysis research. In this paper, an automatic decision-style recognition method is proposed. Experiments involving 240 subjects were conducted to obtain face data and individual decision-making style score. The face data was obtained using the Kinect camera, and the decision-style score were obtained via a questionnaire. To realize automatic recognition of an individual decision-making style, machine learning was employed to establish the mapping relationship between the face data and a scaled evaluation of the decision-making style score. This study adopts a variety of classical machine learning algorithms, including Linear regression, Support vector machine regression, Ridge regression, and Bayesian ridge regression. The experimental results show that the linear regression model returns the best results. The correlation coefficient between the linear regression model evaluation results and the scale evaluation results was 0.6, which represents a medium and higher correlation. The results verify the feasibility of automatic decision-making style recognition method based on facial analysis.

Neural reference groups: a synchrony-based classification approach for predicting attitudes using fNIRS

Social neuroscience research has demonstrated that those who are like-minded are also 'like-brained.' Studies have shown that people who share similar viewpoints have greater neural synchrony with one another, and less synchrony with people who 'see things differently.' Although these effects have been demonstrated at the 'group level,' little work has been done to predict the viewpoints of specific 'individuals' using neural synchrony measures. Furthermore, the studies that have made predictions using synchrony-based classification at the individual level used expensive and immobile neuroimaging equipment (e.g. functional magnetic resonance imaging) in highly controlled laboratory settings, which may not generalize to real-world contexts. Thus, this study uses a simple synchrony-based classification method, which we refer to as the 'neural reference groups' approach, to predict individuals' dispositional attitudes from data collected in a mobile 'pop-up neuroscience' lab. Using functional near-infrared spectroscopy data, we predicted individuals' partisan stances on a sociopolitical issue by comparing their neural timecourses to data from two partisan neural reference groups. We found that partisan stance could be identified at above-chance levels using data from dorsomedial prefrontal cortex. These results indicate that the neural reference groups approach can be used to investigate naturally occurring, dispositional differences anywhere in the world.

Stage detection of mild cognitive impairment via fMRI using Hilbert Huang transform based classification framework

PURPOSE

This work aims to establish a classification framework for the diagnosis of mild cognitive impairment (MCI) at different stages (early MCI and late MCI) through direct analysis of resting-state functional magnetic resonance imaging (rs-fMRI) signals and using the accuracy (total correct rate), specificity (correct rate of late MCI) and sensitivity (correct rate of early MCI) to validate its classification performance.

METHODS

All fMR images of subjects were parcellated into 116 regions of interest (ROIs) by applying the Anatomical Automatic Labeling (AAL) template, and the average rs-fMRI signals of each ROI were extracted. The Hilbert-Huang transform (HHT) was introduced into the framework to decompose each rs-fMRI signal into a series of intrinsic mode functions (IMFs) and to analyze these nonstationary and nonlinear time-series from the perspective of multiresolution. After obtaining the instantaneous frequencies and amplitudes of all IMFs of a signal, the Hilbert weighted frequencies (HWFs) were calculated and combined into a vector as the feature of the corresponding ROI. Support Vector Machine (SVM) was implemented to classify MCI at different stages. We used the independent two-sample t-test as the feature selection method and measured the classification performance through the leave-one-out cross-validation (LOOCV) method.

RESULTS

Results on 77 early MCI (eMCI) and 64 late MCI (lMCI) with baseline rs-fMRI data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) yielded 87.94% classification accuracy. Some of the brain regions with significant differences found by previous studies have been confirmed in this work. We found that HWF characteristics exhibited a significant downward trend in all cerebellar regions. The rs-fMRI signals in differential brain regions have not changed completely, but only altered in some narrow frequency bands. The analysis results showed that during the progress of MCI, the main changes of rs-fMRI were concentrated in IMF3, while IMFs with other indexes also contained HWF features with high SVM weights, such as Orbitofrontal superior frontal gyrus in IMF2, Insula in IMF4, and Lobule Ⅲ of vermis in IMF5, indicating that other IMFs provide important information for the diagnosis of MCI as well.

CONCLUSIONS

This work confirmed the classification ability of HHT-based classification framework in classification of at different stages of MCI. Through the analysis, we found that during the progress of MCI the main changes of rs-fMRI were concentrated in IMF3, and HWF characteristics showed a significant downward trend in all cerebellar regions.

Effects of Expressive Writing on Neural Processing During Learning

Expressive writing about past negative events has been shown to lead to a slew of positive outcomes. However, little is known about why writing about something negative would have positive effects. While some have posited that telling a narrative of a past negative event or current anxiety "frees up" cognitive resources, allowing individuals to focus more on the task at hand, there is little neural evidence suggesting that expressive writing has an effect on cognitive load. Moreover, little is known about how individual differences in the content of expressive writing could affect neural processing and the cognitive benefits writing confers. In our experiment, we compared brain activity in a group that had engaged in expressive writing vs. a control group, during performance on a feedback-based paired-associate word-learning task. We found that across groups, differential activation in the dorsal striatum in response to positive vs. negative feedback significantly predicted better later memory. Moreover, writing about a past failure resulted in more activation relative to the control group during the learning task in the mid-cingulate cortex (MCC), an area of the brain crucial to processing negative emotion. While our results do not provide support for the assertion that expressive writing alters attentional processing, our findings suggest that choosing to write about particularly intense past negative experiences like a difficult past failure may have resulted in changes in neural activation during task processing.