Amygdala Modulation During Emotion Regulation Training With fMRI-Based Neurofeedback

Intimate partner violence perpetration among veterans: associations with neuropsychiatric symptoms and limbic microstructure

Background

Intimate partner violence (IPV) perpetration is highly prevalent among veterans. Suggested risk factors of IPV perpetration include combat exposure, post-traumatic stress disorder (PTSD), depression, alcohol use, and mild traumatic brain injury (mTBI). While the underlying brain pathophysiological characteristics associated with IPV perpetration remain largely unknown, previous studies have linked aggression and violence to alterations of the limbic system. Here, we investigate whether IPV perpetration is associated with limbic microstructural abnormalities in military veterans. Further, we test the effect of potential risk factors (i.e., PTSD, depression, substance use disorder, mTBI, and war zone-related stress) on the prevalence of IPV perpetration.

Methods

Structural and diffusion-weighted magnetic resonance imaging (dMRI) data were acquired from 49 male veterans of the Iraq and Afghanistan wars (Operation Enduring Freedom/Operation Iraqi Freedom; OEF/OIF) of the Translational Research Center for TBI and Stress Disorders (TRACTS) study. IPV perpetration was assessed using the psychological aggression and physical assault sub-scales of the Revised Conflict Tactics Scales (CTS2). Odds ratios were calculated to assess the likelihood of IPV perpetration in veterans with either of the following diagnoses: PTSD, depression, substance use disorder, or mTBI. Fractional anisotropy tissue (FA) measures were calculated for limbic gray matter structures (amygdala-hippocampus complex, cingulate, parahippocampal gyrus, entorhinal cortex). Partial correlations were calculated between IPV perpetration, neuropsychiatric symptoms, and FA.

Results

Veterans with a diagnosis of PTSD, depression, substance use disorder, or mTBI had higher odds of perpetrating IPV. Greater war zone-related stress, and symptom severity of PTSD, depression, and mTBI were significantly associated with IPV perpetration. CTS2 (psychological aggression), a measure of IPV perpetration, was associated with higher FA in the right amygdala-hippocampus complex (r = 0.400, p = 0.005).

Conclusion

Veterans with psychiatric disorders and/or mTBI exhibit higher odds of engaging in IPV perpetration. Further, the more severe the symptoms of PTSD, depression, or TBI, and the greater the war zone-related stress, the greater the frequency of IPV perpetration. Moreover, we report a significant association between psychological aggression against an intimate partner and microstructural alterations in the right amygdala-hippocampus complex. These findings suggest the possibility of a structural brain correlate underlying IPV perpetration that requires further research.

Clinical Response to Neurofeedback in Major Depression Relates to Subtypes of Whole-Brain Activation Patterns During Training

Major Depressive Disorder (MDD) poses a significant public health challenge due to its high prevalence and the substantial burden it places on individuals and healthcare systems. Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) shows promise as a treatment for this disorder, although its mechanisms of action remain unclear. This study investigated whole-brain response patterns during rtfMRI-NF training to explain interindividual variability in clinical efficacy in MDD. We analyzed data from 95 participants (67 active, 28 control) with MDD from previous rtfMRI-NF studies designed to increase left amygdala activation through positive autobiographical memory recall. Significant symptom reduction was observed in the active group (t=-4.404, d=-0.704, p<0.001) but not in the control group (t=-1.609, d=-0.430, p=0.111). However, left amygdala activation did not account for the variability in clinical efficacy. To elucidate the brain training process underlying the clinical effect, we examined whole-brain activation patterns during two critical phases of the neurofeedback procedure: activation during the self-regulation period, and transient responses to feedback signal presentations. Using a systematic process involving feature selection, manifold extraction, and clustering with cross-validation, we identified two subtypes of regulation activation and three subtypes of brain responses to feedback signals. These subtypes were significantly associated with the clinical effect (regulation subtype: F=8.735, p=0.005; feedback response subtype: F=5.326, p=0.008; subtypes' interaction: F=3.471, p=0.039). Subtypes associated with significant symptom reduction were characterized by selective increases in control regions, including lateral prefrontal areas, and decreases in regions associated with self-referential thinking, such as default mode areas. These findings suggest that large-scale brain activity during training is more critical for clinical efficacy than the level of activation in the neurofeedback target region itself. Tailoring neurofeedback training to incorporate these patterns could significantly enhance its therapeutic efficacy.

Mapping the evolution of neurofeedback research: a bibliometric analysis of trends and future directions

Introduction

This study conducts a bibliometric analysis on neurofeedback research to assess its current state and potential future developments.

Methods

It examined 3,626 journal articles from the Web of Science (WoS) using co-citation and co-word methods.

Results

The co-citation analysis identified three major clusters: "Real-Time fMRI Neurofeedback and Self-Regulation of Brain Activity," "EEG Neurofeedback and Cognitive Performance Enhancement," and "Treatment of ADHD Using Neurofeedback." The co-word analysis highlighted four key clusters: "Neurofeedback in Mental Health Research," "Brain-Computer Interfaces for Stroke Rehabilitation," "Neurofeedback for ADHD in Youth," and "Neural Mechanisms of Emotion and Self-Regulation with Advanced Neuroimaging.

Discussion

This in-depth bibliometric study significantly enhances our understanding of the dynamic field of neurofeedback, indicating its potential in treating ADHD and improving performance. It offers non-invasive, ethical alternatives to conventional psychopharmacology and aligns with the trend toward personalized medicine, suggesting specialized solutions for mental health and rehabilitation as a growing focus in medical practice.

A Narrative Review of the Efficacy of Interventions for Emotional Dysregulation, and Underlying Bio-Psycho-Social Factors

In this narrative, comprehensive, and updated review of the literature, we summarize evidence about the effectiveness of interventions aimed at reducing emotion dysregulation and improving emotion regulation in children, adolescents, and adults. After introducing emotion dysregulation and emotion regulation from a theoretical standpoint, we discuss the factors commonly associated with emotion regulation, including neurobiological and neuropsychological mechanisms, and the role of childhood adverse experiences and psycho-social factors in the onset of emotion dysregulation. We then present evidence about pharmacological and non-pharmacological interventions aiming at improving emotion dysregulation and promoting emotion regulation across the lifespan. Although our review was not intended as a traditional systematic review, and the search was only restricted to systematic reviews and meta-analyses, we highlighted important implications and provided recommendations for clinical practice and future research in this field.

Estimating individual subjective values of emotion regulation strategies

Individuals have a repertoire of emotion regulation (ER) strategies at their disposal, which they can use more or less flexibly. In ER flexibility research, strategies that facilitate goal achievement are considered adaptive and therefore are subjectively valuable. Individuals are motivated to reduce their emotional arousal effectively and to avoid cognitive effort. Perceived costs of ER strategies in the form of effort, however, are highly subjective. Subjective values (SVs) should therefore represent a trade-off between effectiveness and subjectively required cognitive effort. However, SVs of ER strategies have not been determined so far. We present a new paradigm for quantifying individual SVs of ER strategies by offering monetary values for ER strategies in an iterative process. N = 120 participants first conducted an ER paradigm with the strategies distraction, distancing, and suppression. Afterwards, individual SVs were determined using the new CAD paradigm. SVs significantly predicted later choice for an ER strategy (χ2 (4, n = 119) = 115.40, p < 0.001, BF10 = 1.62 × 1021). Further, SVs were associated with Corrugator activity (t (5, 618.96) = 2.09, p = 0.037, f2 = 0.001), subjective effort (t (5, 618.96) = - 13.98, p < 0.001, f2 = 0.035), and self-reported utility (t (5, 618.96) = 29.49, p < 0.001, f2 = 0.155). SVs were further associated with self-control (t (97.97) = 2.04, p = 0.044, f2 = 0.002), but not with flexible ER. With our paradigm, we were able to determine subjective values. The trait character of the values will be discussed. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on July 19, 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.17605/OSF.IO/FN9BT .

Happy Software: An interactive program based on an emotion management model for assertive conflict resolution

Emotions are key to conflict resolution: to resolve conflict situations assertively, we must be able to manage the emotions that cause them. After a detailed analysis of the relevant theoretical framework, this paper presents a theoretical emotion management model aimed at assertive conflict resolution. The model, which is described step by step, has been transformed into an interactive program for students, implemented, and assessed in a population aged 8-16 years. The model is divided into four steps or phases. The first is emotional awareness, which consists of understanding and legitimating emotions; the second focuses on reducing emotional intensity and impulsivity; the third encompasses the use of different emotion regulation strategies; and the fourth and final step is assertive communication. Training in this process results in better emotion management, which eventually leads to greater wellbeing and a more positive assessment of new conflicts and aids in the assertive resolution thereof. The final section of the paper summarizes the most important evidence and outcomes of the use of the Happy software so far.

Depressive symptoms are associated with reduced positivity preferences in episodic memory in aging

Age-related positivity preferences are represented as greater memory benefits for positive and/or reduced benefits for negative material with age. It is unknown if positivity preferences are limited to older adults without depressive symptoms. In this fMRI study, adults across the lifespan with a range of depressive symptoms were scanned as they rated emotional intensity of images and subsequently completed a recognition memory task. Behavioral, univariate, and functional connectivity analyses provided evidence for interactive effects between age and depressive symptoms. With low depressive symptoms, typical age-related emotional preferences emerged: younger age was associated with better memory for negative images, and this benefit was reduced with older age. With increasing depressive symptoms in older age, positivity preferences were reduced, manifesting as improvements in negative memory. The neural data highlighted potential underlying mechanisms, including reductions in prefrontal cortex connectivity reflecting diminished ability to engage regulatory processes to reduce negative affect in older participants with higher depressive symptoms. These findings suggest that depressive symptoms in older adulthood reduce positivity preferences through alterations in neural networks underlying emotion regulation.

Dynamic functional connectivity estimation for neurofeedback emotion regulation paradigm with simultaneous EEG-fMRI analysis

Joint Analysis of EEG and fMRI datasets can bring new insight into brain mechanisms. In this paper, we employed the recently introduced Correlated Coupled Tensor Matrix Factorization (CCMTF) method for analysis of the emotion regulation paradigm based on EEG frontal asymmetry neurofeedback in the alpha frequency band with simultaneous fMRI. CCMTF method assumes that the co-variations of the common dimension (temporal dimension) between EEG and fMRI are correlated and not necessarily identical. The results of the CCMTF method suggested that EEG and fMRI had similar covariations during the transition of brain activities from resting states to task (view and upregulation) states and these covariations followed an increasing trend. The fMRI shared spatial component showed activations in the limbic system, DLPFC, OFC, and VLPC regions, which were consistent with the previous studies and were linked to EEG frequency patterns in the range of 1–15 Hz with a correlation value close to 0.75. The estimated regions from the CCMTF method were then used as the candidate nodes for dynamic functional connectivity (dFC) analysis, in which the changes in connectivity from view to upregulation states were examined. The results of the dFC analysis were compared with a Normalized Mutual information (NMI) based approach in two different frequency ranges (1–15 and 15–40 Hz) as the NMI method was applied to the vectors of dFC nodes of EEG and fMRI data. The results of the two methods illustrated that the relation between EEG and fMRI datasets was mostly in the frequency range of 1–15 Hz. These relations were both in the brain activations and the dFCs between the two modalities. This paper suggests that the CCMTF method is a capable approach for extracting the shared information between EEG and fMRI data and can reveal new information about brain functions and their connectivity without solving the EEG inverse problem or analyzing different frequency bands.

Interactions between emotions and eating behaviors: Main issues, neuroimaging contributions, and innovative preventive or corrective strategies

Emotional eating is commonly defined as the tendency to (over)eat in response to emotion. Insofar as it involves the (over)consumption of high-calorie palatable foods, emotional eating is a maladaptive behavior that can lead to eating disorders, and ultimately to metabolic disorders and obesity. Emotional eating is associated with eating disorder subtypes and with abnormalities in emotion processing at a behavioral level. However, not enough is known about the neural pathways involved in both emotion processing and food intake. In this review, we provide an overview of recent neuroimaging studies, highlighting the brain correlates between emotions and eating behavior that may be involved in emotional eating. Interaction between neural and neuro-endocrine pathways (HPA axis) may be involved. In addition to behavioral interventions, there is a need for a holistic approach encompassing both neural and physiological levels to prevent emotional eating. Based on recent imaging, this review indicates that more attention should be paid to prefrontal areas, the insular and orbitofrontal cortices, and reward pathways, in addition to regions that play a major role in both the cognitive control of emotions and eating behavior. Identifying these brain regions could allow for neuromodulation interventions, including neurofeedback training, which deserves further investigation.

The Effect of Quantitative Electroencephalography-Based Neurofeedback Therapy on Anxiety, Depression, and Emotion Regulation in People with Generalized Anxiety Disorder

Introduction:

Generalized Anxiety Disorder (GAD) is one of the most common anxiety disorders that has significant adverse effects on social functioning, occupational/academic performance, and daily living. This study aimed to evaluate the effect of Quantitative Electroencephalography (QEEG)-based Neurofeedback (NFB) therapy on anxiety, depression, and emotion regulation of people with GAD.

Methods:

This research is a quasi-experimental study with a pre-test/post-test/follow-up design and a control group. The study participants were 29 college students with GAD living in Zanjan City, Iran, who were selected using a convenience sampling method. Then, they were randomly divided into two groups of intervention (n=15) and control (n=14). The protocol of NFB therapy was designed based on the QEEG method. The intervention group received QEEG-based NFB therapy for 8 weeks (20 sessions, 2 sessions per week, each session for 45 min), while the control group received no intervention. The samples were surveyed and measured by using a 7-item GAD scale, Emotion Regulation Questionnaire (ERQ), 21-item Depression, Anxiety, and Stress Scale (DASS), and Structured Clinical Interview for DSM (SCID) before and after the intervention and then at a 3-month follow-up. The collected data were analyzed in SPSS software V. 22 using univariate ANCOVA and repeated measures ANOVA.

Results:

The within-subjects effect of time (pre-test, post-test, and follow-up) was statistically significant (P=0.031). The intervention group showed significant changes in the post-test and follow-up phases in comparison with the control group. The anxiety and depression levels of patients reduced significantly (P=0.001), and their emotion regulation improved (P=0.001) after the intervention, and they remained unchanged in the follow-up period.

Conclusion:

QEEG-based NFB therapy can reduce anxiety and depression and improve emotion regulation in patients with GAD.

Functional connectivity between the ventral anterior cingulate and amygdala during implicit emotional conflict regulation and daily-life emotion dysregulation

Emotional conflict adaptation involving ventral anterior cingulate cortex (ACC) suppression of the amygdala is thought to be important in emotion regulation, with evidence of impaired implicit emotion regulation in emotional distress disorders. However, it is unclear how this impairment is associated with daily-life emotion dysregulation in emotional distress disorders. In the current study, female participants with an emotional distress disorder (N = 27) were scanned with MRI while completing an implicit emotion conflict regulation task that involved identifying the facial expression of an image while ignoring an overlaid congruent or incongruent affect label. Participants then completed two weeks of ambulatory assessment of daily-life emotion dysregulation. Consistent with previous research on comorbid emotional distress disorders (Etkin and Schatzberg, 2011), there was no behavioral effect of emotional conflict adaptation (p = .701) but a significant effect of congruent adaptation (p = .006), suggesting impairment is specific to implicit emotional conflict regulation. Additionally, there was no neural evidence of emotional conflict adaptation in the ventral ACC and amygdala (ps > .766). Further, in our primary psychophysiological interactions analyses, we examined ventral ACC-amygdala functional connectivity. As hypothesized, increased ventral ACC-amygdala functional connectivity for emotional conflict adaptation was associated with increased daily-life affective instability (p = .022), but not mean daily-life negative affect (p = .372). Overall, results provide behavioral and neural evidence of impaired implicit emotional conflict adaptation in individuals with emotional distress disorders and suggests that this impairment is related to daily-life affective instability in these disorders.

Real-Time Decoding of Attentional States Using Closed-Loop EEG Neurofeedback

Sustained attention is a cognitive ability to maintain task focus over extended periods of time (Mackworth, 1948; Chun, Golomb, & Turk-Browne, 2011). In this study, scalp electroencephalography (EEG) signals were processed in real time using a 32 dry-electrode system during a sustained visual attention task. An attention training paradigm was implemented, as designed in DeBettencourt, Cohen, Lee, Norman, and Turk-Browne (2015) in which the composition of a sequence of blended images is updated based on the participant's decoded attentional level to a primed image category. It was hypothesized that a single neurofeedback training session would improve sustained attention abilities. Twenty-two participants were trained on a single neurofeedback session with behavioral pretraining and posttraining sessions within three consecutive days. Half of the participants functioned as controls in a double-blinded design and received sham neurofeedback. During the neurofeedback session, attentional states to primed categories were decoded in real time and used to provide a continuous feedback signal customized to each participant in a closed-loop approach. We report a mean classifier decoding error rate of 34.3% (chance = 50%). Within the neurofeedback group, there was a greater level of task-relevant attentional information decoded in the participant's brain before making a correct behavioral response than before an incorrect response. This effect was not visible in the control group (interaction p=7.23e-4), which strongly indicates that we were able to achieve a meaningful measure of subjective attentional state in real time and control participants' behavior during the neurofeedback session. We do not provide conclusive evidence whether the single neurofeedback session per se provided lasting effects in sustained attention abilities. We developed a portable EEG neurofeedback system capable of decoding attentional states and predicting behavioral choices in the attention task at hand. The neurofeedback code framework is Python based and open source, and it allows users to actively engage in the development of neurofeedback tools for scientific and translational use.

Closed-loop neurostimulation for affective symptoms and disorders: An overview

Affective and anxiety disorders are the most prevalent and incident psychiatric disorders worldwide. Therapeutic approaches to these disorders using non-invasive brain stimulation (NIBS) and analogous techniques have been extensively investigated. In this paper, we discuss the combination of NIBS and neurofeedback in closed-loop setups and its application for affective symptoms and disorders. For this, we first provide a rationale for this combination by presenting some of the main original findings of NIBS, with a primary focus on transcranial magnetic stimulation (TMS), and neurofeedback, including protocols based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Then, we provide a scope review of studies combining real-time neurofeedback with NIBS protocols in the so-called closed-loop brain state-dependent neuromodulation (BSDS). Finally, we discuss the concomitant use of TMS and real-time functional near-infrared spectroscopy (fNIRS) as a possible solution to the current limitations of BSDS-based protocols for affective and anxiety disorders.

The Current Evidence Levels for Biofeedback and Neurofeedback Interventions in Treating Depression: A Narrative Review

This article is aimed at showing the current level of evidence for the usage of biofeedback and neurofeedback to treat depression along with a detailed review of the studies in the field and a discussion of rationale for utilizing each protocol. La Vaque et al. criteria endorsed by the Association for Applied Psychophysiology and Biofeedback and International Society for Neuroregulation & Research were accepted as a means of study evaluation. Heart rate variability (HRV) biofeedback was found to be moderately supportable as a treatment of MDD while outcome measure was a subjective questionnaire like Beck Depression Inventory (level 3/5, “probably efficacious”). Electroencephalographic (EEG) neurofeedback protocols, namely, alpha-theta, alpha, and sensorimotor rhythm upregulation, all qualify for level 2/5, “possibly efficacious.” Frontal alpha asymmetry protocol also received limited evidence of effect in depression (level 2/5, “possibly efficacious”). Finally, the two most influential real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback protocols targeting the amygdala and the frontal cortices both demonstrate some effectiveness, though lack replications (level 2/5, “possibly efficacious”). Thus, neurofeedback specifically targeting depression is moderately supported by existing studies (all fit level 2/5, “possibly efficacious”). The greatest complication preventing certain protocols from reaching higher evidence levels is a relatively high number of uncontrolled studies and an absence of accurate replications arising from the heterogeneity in protocol details, course lengths, measures of improvement, control conditions, and sample characteristics.

Neighborhood Poverty and Amygdala Response to Negative Face

Introduction

Considerable research has established a link between socioeconomic status (SES) and brain function. While studies have shown a link between poverty status and amygdala response to negative stimuli, a paucity of knowledge exists on whether neighborhood poverty is also independently associated with amygdala hyperactive response to negative stimuli.

Purpose

Using functional brain imaging data, this study tested the association between neighborhood SES and the amygdala's response to negative stimuli. Considering race as a sociological rather than a biological construct, we also explored racial heterogeneity in this association between non-Hispanic Black and non-Hispanic White youth.

Methods

We borrowed the functional Magnetic Resonance Imaging (fMRI) data of the Adolescent Brain Cognitive Development (ABCD) study. The sample was 2,490 nine to ten year old non-Hispanic Black and non-Hispanic White adolescents. The independent variable was neighborhood income which was treated as a continuous measure. The primary outcomes were the right and left amygdala response to negative face during an N-Back task. Age, sex, race, marital status, and family SES were the covariates. To analyze the data, we used linear regression models.

Results

Low neighborhood income was independently associated with a higher level of amygdala response to negative face. Similar results were seen for the right and left amygdala. These effects were significant net of race, age, sex, marital status, and family SES. An association between low neighborhood SES and higher left but not right amygdala response to negative face could be observed for non-Hispanic Black youth. No association between neighborhood SES and left or right amygdala response to negative face could be observed for non-Hispanic White youth.

Conclusions

For American youth, particularly non-Hispanic Black youth, living in a poor neighborhood predicts the left amygdala reaction to negative face. This result suggested that Black youth who live in poor neighborhoods are at a high risk of poor emotion regulation. This finding has implications for policy making to reduce inequalities in undesired behavioral and emotional outcomes. Policy solutions to health inequalities should address inequalities in neighborhood SES.