In search of convergent regional brain abnormality in cognitive emotion regulation: a transdiagnostic neuroimaging meta-analysis

Cognitive emotion regulation (i.e., reappraisal) impairment is a key feature in a wide variety of mental disorders, suggesting common nature of disruption across psychiatric diagnoses. However, the extent of potential shared neurobiological disturbances related to reappraisalimpairment is incompletely understood. This study, therefore, aimed to identify neurobiological substrates of disturbed reappraisal using a transdiagnostic approach by performing a quantitative coordinate-based meta-analysis (CBMA) on reappraisal tasks across various mental disorders. Following the best-practice guidelines for neuroimaging meta-analysis, we systematicallysearched PubMed, ScienceDirect and Web of Science databases for whole-brain neuroimaging studies published through February 2020 that compared brain activation in patients with mental disorders and matched healthy controls during a reappraisal task. Out of 1608 publications, we retrieved 32 publications with 1240 unique individuals, providing sufficient power for conducting CBMA using activation likelihood estimation (ALE) method. The reported peak coordinates for the patient/control difference in selected articles were extracted and several ALE analyses were performed to identify spatial convergence. Surprisingly, neither the pooled ALE analysis noradditional analyses restricting to in-/decreased contrasts and more homogeneous grouping of coordinates (i.e., regulation direction, stimulus valence and disorder category) provided significant convergent findings. This CBMA indicates a lack of convergent regional abnormality related to reappraisal across various mental disorders. This might be due to the complex nature of reappraisal, heterogeneous clinical populations or methodological flexibility including preprocessing and analytical methods.

Download Full-text

In search of convergent regional brain abnormality in cognitive emotion regulation: A transdiagnostic neuroimaging meta‐analysis

Human Brain Mapping ◽

10.1002/hbm.25722 ◽

2021 ◽

Author(s):

Tina Khodadadifar ◽

Zahra Soltaninejad ◽

Amir Ebneabbasi ◽

Claudia R. Eickhoff ◽

Christian Sorg ◽

...

Keyword(s):

Emotion Regulation ◽

Meta Analysis ◽

Cognitive Emotion Regulation ◽

Brain Abnormality ◽

Regional Brain

Download Full-text

The relationship between emotion regulation and well-being in patients with mental disorders: A meta-analysis

Comprehensive Psychiatry ◽

10.1016/j.comppsych.2020.152189 ◽

2020 ◽

Vol 102 ◽

pp. 152189

Author(s):

Jannis T. Kraiss ◽

Peter M. ten Klooster ◽

Judith T. Moskowitz ◽

Ernst T. Bohlmeijer

Keyword(s):

Emotion Regulation ◽

Mental Disorders ◽

Meta Analysis ◽

Well Being ◽

The Relationship

Download Full-text

Meta-analytic evidence for downregulation of the amygdala during working memory maintenance

10.1101/2020.12.18.423445 ◽

2020 ◽

Author(s):

Lycia D. de Voogd ◽

Erno J. Hermans

Keyword(s):

Working Memory ◽

Emotion Regulation ◽

Meta Analysis ◽

Cognitive Reappraisal ◽

Memory Task ◽

Likelihood Estimation ◽

Underlying Mechanism ◽

Reciprocal Relationship ◽

Amygdala Activity ◽

Regulation Of Emotion

The amygdala is a region critically implicated in affective processes. Downregulation of the amygdala is therefore one of the hallmarks of successful emotion regulation. Downregulation is thought to be established through top-down control of the executive control network over the amygdala. Such a reciprocal relationship, however, is not exclusive to cognitive regulation of emotion. It has recently been noted that any cognitively demanding task may downregulate the amygdala, including a standard working memory task. Here, using a coordinate-based meta-analysis based on an activation likelihood estimation (ALE), we examined whether a standard working memory task (i.e., a 2-back task) downregulates the amygdala similarly to a cognitive reappraisal task. Following the PRISMA guidelines, we included a total of 66 studies using a 2-back working memory task and 65 studies using a cognitive reappraisal task. We found that a standard 2-back working memory task indeed systematically downregulates the amygdala, and that deactivated clusters strongly overlap with those observed during a cognitive reappraisal task. This finding has important consequences for the interpretation of the underlying mechanism of the effects of cognitive reappraisal on amygdala activity: downregulation of amygdala during cognitive reappraisal might be due to the cognitively demanding nature of the task and not per se by the act of the reappraisal itself. Moreover, it raises the possibility of applying working memory tasks in a clinical setting as an alternative emotion regulation strategy.

Download Full-text

Epidemiology of Mental Disorder Symptoms in Students of University of Bojnord: The Role of Demographic Characteristics and Cognitive Emotion Regulation Strategies

International journal of epidemiologic research ◽

10.34172/ijer.2021.30 ◽

2021 ◽

Vol 8 (4) ◽

pp. 167-174

Author(s):

Khadije Alavi

Keyword(s):

Emotion Regulation ◽

Regression Analysis ◽

Mental Disorders ◽

Mental Disorder ◽

Demographic Characteristics ◽

Emotion Regulation Strategies ◽

Cognitive Emotion Regulation ◽

Place Of Origin ◽

Regulation Strategies

Background and aims: Mental health problems are considered as important public health issues. This study aimed, firstly, to investigate the epidemiology of mental disorders’ symptoms among the students of Bojnord University and examine the role of demographic characteristics in the prevalence of the given symptoms; and, secondly, to explore and compare the predictive role of adaptive and maladaptive emotion regulation strategies in identifying symptoms of different mental disorders. Methods: A total of 351 students from Bojnord University completing their 2018-2019 academic year were recruited using cluster sampling method and responded to Symptom Checklist-SCL90 and Cognitive Emotion Regulation Questionnaire. Data were analyzed using descriptive statistics including mean, standard deviation, frequency and percentage, as well as multiple regression analysis. Results: According to the findings from this epidemiological study, 33% of the students suffered from moderate symptoms of mental disorders, while 14% of them suffered from severe symptoms. Demographic characteristics of gender, marital status, and place of origin (i.e., being indigenous/non-indigenous) were not found to exert a significant effect on the prevalence of symptoms of mental disorders. The results of multiple regression analysis also indicated that cognitive emotion regulation strategies were capable of predicting all nine dimensions of mental disorder symptoms. In this regard, the maladaptive strategies were discovered to play a stronger role in predicting mental disorders compared to adaptive strategies. Conclusions: Mental disorders were very common among university students. No significant relationship was detected between the prevalence of mental disorders’ symptoms and gender, marital status, and place of origin. The study findings were also found to support the trans-diagnostic role of the emotion regulation in mental disorders.

Download Full-text

BUGSnet: an R package to facilitate the conduct and reporting of Bayesian network Meta-analyses

BMC Medical Research Methodology ◽

10.1186/s12874-019-0829-2 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 9

Author(s):

Audrey Béliveau ◽

Devon J. Boyne ◽

Justin Slater ◽

Darren Brenner ◽

Paul Arora

Keyword(s):

Best Practice ◽

Meta Analysis ◽

R Package ◽

Model Fit ◽

Support Unit ◽

Best Practice Guidelines ◽

League Tables ◽

Regulatory Standards ◽

Meta Analyses ◽

Current Guidelines

Abstract Background Several reviews have noted shortcomings regarding the quality and reporting of network meta-analyses (NMAs). We suspect that this issue may be partially attributable to limitations in current NMA software which do not readily produce all of the output needed to satisfy current guidelines. Results To better facilitate the conduct and reporting of NMAs, we have created an R package called “BUGSnet” (Bayesian inference Using Gibbs Sampling to conduct a Network meta-analysis). This R package relies upon Just Another Gibbs Sampler (JAGS) to conduct Bayesian NMA using a generalized linear model. BUGSnet contains a suite of functions that can be used to describe the evidence network, estimate a model and assess the model fit and convergence, assess the presence of heterogeneity and inconsistency, and output the results in a variety of formats including league tables and surface under the cumulative rank curve (SUCRA) plots. We provide a demonstration of the functions contained within BUGSnet by recreating a Bayesian NMA found in the second technical support document composed by the National Institute for Health and Care Excellence Decision Support Unit (NICE-DSU). We have also mapped these functions to checklist items within current reporting and best practice guidelines. Conclusion BUGSnet is a new R package that can be used to conduct a Bayesian NMA and produce all of the necessary output needed to satisfy current scientific and regulatory standards. We hope that this software will help to improve the conduct and reporting of NMAs.

Download Full-text

Corrigendum to “Neural network of cognitive emotion regulation — An ALE meta-analysis and MACM analysis”

NeuroImage ◽

10.1016/j.neuroimage.2015.03.003 ◽

2015 ◽

Vol 111 ◽

pp. 631

Author(s):

N. Kohn ◽

S.B. Eickhoff ◽

M. Scheller ◽

A.R. Laird ◽

P.T. Fox ◽

...

Keyword(s):

Neural Network ◽

Emotion Regulation ◽

Meta Analysis ◽

Cognitive Emotion Regulation

Download Full-text

The relationship between Cognitive Emotion Regulation Questionnaire (CERQ) and depression, anxiety: Meta-analysis

The Japanese journal of psychology ◽

10.4992/jjpsy.87.15302 ◽

2016 ◽

Vol 87 (2) ◽

pp. 179-185 ◽

Cited By ~ 10

Author(s):

Ryota Sakakibara ◽

Mizuho Kitahara

Keyword(s):

Emotion Regulation ◽

Meta Analysis ◽

Cognitive Emotion Regulation ◽

The Relationship

Download Full-text

Predicting Depression Based on Cognitive Emotion Regulation Strategies

The Journal of Tolooebehdasht ◽

10.18502/tbj.v19i1.2815 ◽

2020 ◽

Author(s):

Shekoofeh Dadfarnia ◽

Habib Hadianfard ◽

Changiz Rahimi ◽

Abdulaziz Aflakseir

Keyword(s):

Emotion Regulation ◽

Mental Disorders ◽

Stepwise Regression ◽

Emotional Reactivity ◽

Pearson Correlation ◽

Emotion Regulation Strategies ◽

Cognitive Emotion Regulation ◽

Self Blame ◽

Regulation Strategies ◽

Other Blame

Introduction: In recent years, many studies focused on emotion regulation in conceptualization, explanation, and treatment of mental disorders. Problematic patterns of emotional reactivity and regulation are prominent factors in various mental disorders, specially internalizing disorders. The present study aimed to identify the role of emotion regulation strategies in predicting depression. Method: This descriptive –correlational research was conducted on 650 students of Yazd University selected by cluster sampling. They completed the Beck depression inventory (BDI-II) and Cognitive Emotion Regulation Strategies Questionnaire (CERQ.) Research data were analyzed in SPSS-22 by Pearson correlation coefficient and stepwise regression. Results: A significant positive correlation was found between maladaptive emotion regulation strategies (self-blame, rumination, catastrophizing, other-blame) and depression. Adaptive emotion regulation strategies (acceptance, reorientation, plan-focus, perspective taking) were negatively correlated with depression. Results of Stepwise regression showed that self-blame, reorientation, catastrophizing, plan-focus, and other blame could explain 34% of depression variance significantly. Conclusion: According to the results, emotion regulation strategies can be a significant factor in predicting depression; so, strengthening the adaptive cognitive emotion regulation strategies should be considered in the development and modification of treatments for depression.

Download Full-text

Neurobiological models of emotion regulation: a meta-analysis of neuroimaging studies of acceptance as an emotion regulation strategy

Social Cognitive and Affective Neuroscience ◽

10.1093/scan/nsab007 ◽

2021 ◽

Author(s):

Irene Messina ◽

Alessandro Grecucci ◽

Roberto Viviani

Keyword(s):

Emotion Regulation ◽

Brain Activity ◽

Meta Analysis ◽

Likelihood Estimation ◽

Posterior Cingulate Cortex ◽

Emotional States ◽

Emotional Acceptance ◽

Complementary Role ◽

Emotion Regulation Strategy ◽

High Level

Abstract Emotional acceptance is an important emotion regulation strategy promoted by most psychotherapy approaches. We adopted the Activation Likelihood Estimation technique to obtain a quantitative summary of previous fMRI (functional Magnetic Resonance Imaging) studies of acceptance and test different hypotheses on its mechanisms of action. The main meta-analysis included 13 experiments contrasting acceptance to control conditions, yielding a total of 422 subjects and 170 foci of brain activity. Additionally, subgroups of studies with different control conditions (react naturally or focus on emotions) were identified and analysed separately. Our results showed executive areas to be affected by acceptance only in the subgroup of studies in which acceptance was compared to natural reactions. In contrast, a cluster of decreased brain activity located in the posterior cingulate cortex (PCC)/precuneus was associated with acceptance regardless of the control condition. These findings suggest that high-level executive cortical processes are not a distinctive feature of acceptance, whereas functional deactivations in the PCC/precuneus constitute its specific neural substrate. The neuroimaging of emotional acceptance calls into question a key tenet of current neurobiological models of emotion regulation consisting in the necessary involvement of high-level executive processes to actively modify emotional states, suggesting a complementary role for limbic portions of the default system.

Download Full-text