Real-time neurofeedback using functional MRI could improve down-regulation of amygdala activity during emotional stimulation: a proof-of-concept study

Amygdala fMRI-A Critical Appraisal of the Extant Literature

Even before the advent of fMRI, the amygdala occupied a central space in the affective neurosciences. Yet this amygdala-centred view on emotion processing gained even wider acceptance after the inception of fMRI in the early 1990s, a landmark that triggered a goldrush of fMRI studies targeting the amygdala in vivo. Initially, this amygdala fMRI research was mostly confined to task-activation studies measuring the magnitude of the amygdala's response to emotional stimuli. Later, interest began to shift more towards the study of the amygdala's resting-state functional connectivity and task-based psychophysiological interactions. Later still, the test-retest reliability of amygdala fMRI came under closer scrutiny, while at the same time, amygdala-based real-time fMRI neurofeedback gained widespread popularity. Each of these major subdomains of amygdala fMRI research has left its marks on the field of affective neuroscience at large. The purpose of this review is to provide a critical assessment of this literature. By integrating the insights garnered by these research branches, we aim to answer the question: What part (if any) can amygdala fMRI still play within the current landscape of affective neuroscience? Our findings show that serious questions can be raised with regard to both the reliability and validity of amygdala fMRI. These conclusions force us to cast doubt on the continued viability of amygdala fMRI as a core pilar of the affective neurosciences.

The Clinical Impact of Real-Time fMRI Neurofeedback on Emotion Regulation: A Systematic Review

Emotion dysregulation has long been considered a key symptom in multiple psychiatric disorders. Difficulties in emotion regulation have been associated with neural dysregulation in fronto-limbic circuits. Real-time fMRI-based neurofeedback (rt-fMRI-NFB) has become increasingly popular as a potential treatment for emotional dysregulation in psychiatric disorders, as it is able to directly target the impaired neural circuits. However, the clinical impact of these rt-fMRI-NFB protocols in psychiatric populations is still largely unknown. Here we provide a comprehensive overview of primary studies from 2010 to 2023 that used rt-fMRI-NFB to target emotion regulation. We assessed 41 out of 4001 original studies for methodological quality and risk of bias and synthesised concerning the frequency of significant rt-fMRI-NFB-related effects on the neural and behaviour level. Successful modulation of brain activity was reported in between 25 and 50 percent of study samples, while neural effects in clinical samples were more diverse than in healthy samples. Interestingly, the frequency of rt-fMRI-NFB-related behavioural improvement was over 75 percent in clinical samples, while healthy samples showed behavioural improvements between 0 and 25 percent. Concerning clinical subsamples, rt-fMRI-NFB-related behavioural improvement was observed in up to 100 percent of major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) samples. Substance use samples showed behavioural benefits ranging between 50 and 75 percent. Neural effects appeared to be less frequent than behavioural improvements: most neural outcomes ranged between 25 and 50 percent for MDD and substance use and between 0 and 25 percent for PTSD. Using multiple individualised regions of interest (ROIs) for rt-fMRI-NFB training resulted in more frequent behavioural benefits than rt-fMRI-NFB solely based on the amygdala or the prefrontal cortex. While a significant improvement in behavioural outcomes was reported in most clinical studies, the study protocols were heterogeneous, which limits the current evaluation of rt-fMRI-NFB as a putative treatment for emotional dysregulation.

Systematic review and meta-analysis of neurofeedback and its effect on posttraumatic stress disorder

Background

To date, only one systematic review and meta-analysis of randomized controlled trials (RCTs) has evaluated the effect of neurofeedback in PTSD, which included only four studies and found an uncertainty of the effect of EEG-NF on PTSD symptoms. This meta-analysis is an update considering that numerous studies have since been published. Additionally, more recent studies have included fMRI-NF as well as fMRI-guided or -inspired EEG NF.

Methods

Systematic literature searches for RCTs were conducted in three online databases. Additional hand searches of each study identified and of systematic reviews and meta-analyses published were also undertaken. Outcomes evaluated the effect of neurofeedback vs. a control (active, sham, and waiting list) on their effects in reducing PTSD symptoms using various health instruments. Meta-analytical methods used were inverse variance random-effects models measuring both mean and standardized mean differences. Quality and certainty of the evidence were assessed using GRADE. Adverse events were also evaluated.

Results

A total of 17 studies were identified evaluating a total of 628 patients. There were 10 studies used in the meta-analysis. Results from all studies identified favored neurofeedback's effect on reducing PTSD symptoms including BDI pretest-posttest [mean difference (MD): 8.30 (95% CI: 3.09 to 13.52; P = 0.002; I 2 = 0%)]; BDI pretest-follow-up (MD: 8.75 (95% CI: 3.53 to 13.97; P < 0.00001; I 2 = 0%); CAPS-5 pretest-posttest [MD: 7.01 (95% CI: 1.36 to 12.66; P = 0.02; I 2 = 86%)]; CAPS-5 pretest-follow-up (MD: 10 (95% CI: 1.29 to 21.29; P = 0.006; I 2 = 77%); PCL-5 pretest-posttest (MD: 7.14 (95% CI: 3.08 to 11.2; P = 0.0006; I 2 = 0%); PCL-5 pretest-follow-up (MD: 14.95 (95% CI: 7.95 to 21.96; P < 0.0001; I 2 = 0%). Other studies reported improvements using various other instruments. GRADE assessments of CAPS, PCL, and BDI demonstrated a moderate/high level in the quality of the evidence that NF has a positive clinical effect.

Conclusion

Based on newer published studies and the outcomes measured, NF has demonstrated a clinically meaningful effect size, with an increased effect size at follow-up. This clinically meaningful effect appears to be driven by newer fMRI-guided NF and deeper brain derivates of it.

Facing emotions: real-time fMRI-based neurofeedback using dynamic emotional faces to modulate amygdala activity

Introduction

Maladaptive functioning of the amygdala has been associated with impaired emotion regulation in affective disorders. Recent advances in real-time fMRI neurofeedback have successfully demonstrated the modulation of amygdala activity in healthy and psychiatric populations. In contrast to an abstract feedback representation applied in standard neurofeedback designs, we proposed a novel neurofeedback paradigm using naturalistic stimuli like human emotional faces as the feedback display where change in the facial expression intensity (from neutral to happy or from fearful to neutral) was coupled with the participant's ongoing bilateral amygdala activity.

Methods

The feasibility of this experimental approach was tested on 64 healthy participants who completed a single training session with four neurofeedback runs. Participants were assigned to one of the four experimental groups (n = 16 per group), i.e., happy-up, happy-down, fear-up, fear-down. Depending on the group assignment, they were either instructed to "try to make the face happier" by upregulating (happy-up) or downregulating (happy-down) the amygdala or to "try to make the face less fearful" by upregulating (fear-up) or downregulating (fear-down) the amygdala feedback signal.

Results

Linear mixed effect analyses revealed significant amygdala activity changes in the fear condition, specifically in the fear-down group with significant amygdala downregulation in the last two neurofeedback runs as compared to the first run. The happy-up and happy-down groups did not show significant amygdala activity changes over four runs. We did not observe significant improvement in the questionnaire scores and subsequent behavior. Furthermore, task-dependent effective connectivity changes between the amygdala, fusiform face area (FFA), and the medial orbitofrontal cortex (mOFC) were examined using dynamic causal modeling. The effective connectivity between FFA and the amygdala was significantly increased in the happy-up group (facilitatory effect) and decreased in the fear-down group. Notably, the amygdala was downregulated through an inhibitory mechanism mediated by mOFC during the first training run.

Discussion

In this feasibility study, we intended to address key neurofeedback processes like naturalistic facial stimuli, participant engagement in the task, bidirectional regulation, task congruence, and their influence on learning success. It demonstrated that such a versatile emotional face feedback paradigm can be tailored to target biased emotion processing in affective disorders.

No threat: Emotion regulation neurofeedback for police special forces recruits

Police officers of the Special Forces are confronted with highly demanding situations in terms of stress, high tension and threats to their lives. Their tasks are specifically high-risk operations, such as arrests of armed suspects and anti-terror interventions. Improving the emotion regulation skills of police officers might be a vital investment, supporting them to stay calm and focused. A promising approach is training emotion regulation by using real-time (rt-) fMRI neurofeedback. Specifically, downregulating activity in key areas of the fronto-limbic emotion regulation network in the presence of threatening stimuli. Thirteen recruits of the Dutch police special forces underwent six weekly rt-fMRI sessions, receiving neurofeedback from individualized regions of their emotion regulation network. Their task was to reduce the image size of threatening images, wherein the image size represented their brain activity. A reduction in image size represented successful downregulation. Participants were free to use their preferred regulation strategy. A control group of fifteen recruits received no neurofeedback. Both groups completed behavioural tests (image rating on evoked valence and arousal, questionnaire) before and after the neurofeedback training. We hypothesized that the neurofeedback group would improve in downregulation and would score better than the control group on the behavioural tests after the neurofeedback training. Neurofeedback training resulted in a significant decrease in image size (t(12) = 2.82, p = .015) and a trend towards decreased activation in the target regions (t(10) = 1.82, p = .099) from the first to the last session. Notably, subjects achieved downregulation below the pre-stimulus baseline in the last two sessions. No relevant differences between groups were found in the behavioural tasks. Through the training of rt-fMRI neurofeedback, participants learned to downregulate the activity in individualized areas of the emotion regulation network, by using their own preferred strategies. The lack of behavioural between-group differences may be explained by floor effects. Tasks that are close to real-life situations may be needed to uncover behavioural correlates of this emotion regulation training.

Upregulation of a Small-World Brain Network Improves Inhibitory Control: An fNIRS Neurofeedback Training Study

The aim of this study was to investigate the inner link between the small-world brain network and inhibitory control. Functional near-infrared spectroscopy (fNIRS) was used to construct a neurofeedback (NF) training system and regulate the frontal small-world brain network. The small-world network downregulation group (DOWN, n = 17) and the small-world network upregulation group (UP, n = 17) received five days of fNIRS-NF training and performed the color-word Stroop task before and after training. The behavioral and functional brain network topology results of both groups were analyzed by a repeated-measures analysis of variance (ANOVA), which showed that the upregulation training helped to improve inhibitory control. The upregulated small-world brain network exhibits an increase in the brain network regularization, links widely dispersed brain resources, and reduces the lateralization of brain functional networks between hemispheres. This suggests an inherent correlation between small-world functional brain networks and inhibitory control; moreover, dynamic optimization under cost efficiency trade-offs provides a neural basis for inhibitory control. Inhibitory control is not a simple function of a single brain region or connectivity but rather an emergent property of a broader network.

Limbic self-neuromodulation as a novel treatment option for emotional dysregulation in premenstrual dysphoric disorder (PMDD); a proof-of-concept study

AIM

To assess the efficacy of a novel neurofeedback (NF) method, targeting limbic activity, to treat emotional dysregulation related to premenstrual dysphoric disorder (PMDD).

METHODS

We applied a NF probe targeting limbic activity using a functional magnetic resonance imaging-inspired electroencephalogram model (termed Amyg-EFP-NF) in a double-blind randomized controlled trial. A frontal alpha asymmetry probe (AAS-NF), served as active control. Twenty-seven participants diagnosed with PMDD (mean age = 33.57 years, SD = 5.67) were randomly assigned to Amyg-EFP-NF or AAS-NF interventions with a 2:1 ratio, respectively. The treatment protocol consisted of 11 NF sessions through three menstrual cycles, and a follow-up assessment 3 months thereafter. The primary outcome measure was improvement in the Revised Observer Version of the Premenstrual Tension Syndrome Rating Scale (PMTS-OR).

RESULTS

A significant group by time effect was observed for the core symptom subscale of the PMTS-OR, with significant improvement observed at follow-up for the Amyg-EFP group compared with the AAS group [F(1, 15)=4.968, P = 0.042]. This finding was specifically robust for reduction in anger [F(1, 15) = 22.254, P < 0.001]. A significant correlation was found between learning scores and overall improvement in core symptoms (r = 0.514, P = 0.042) suggesting an association between mechanism of change and clinical improvement.

CONCLUSION

Our preliminary findings suggest that Amyg-EFP-NF may serve as an affordable and accessible non-invasive treatment option for emotional dysregulation in women suffering from PMDD. Our main limitations were the relatively small number of participants and the lack of a sham-NF placebo arm.

Altered amygdala functional connectivity after real-time functional MRI emotion self-regulation training

Real-time functional MRI neurofeedback (rtfMRI-NF) is a noninvasive technique that extracts concurrent brain states and provides feedback to subjects in an online method. Our study aims to investigate the effect of rtfMRI-NF on amygdala-based emotion self-regulation by analyzing resting-state functional connectivity. We conducted a task experiment to train subjects in self-regulating amygdala activity in response to emotional stimuli. Twenty subjects were divided into two groups. The up-regulate group (URG) viewed positive stimulus, while the down-regulate group (DRG) viewed negative stimulus. The rtfMRI-NF experiment paradigm consisted of three conditions. The URG's percent amplitude fluctuation (PerAF) scores are significant, indicating that positive emotions may be a partial side effect, with increased activity in the left hemisphere. Resting-state functional connectivity was analyzed via a paired-sample t-test before and after neurofeedback training. Brain network properties and functional connectivity analysis showed a significant difference between the default mode network (DMN) and the brain region associated with the limbic system. These results reveal to some extent the mechanism of neurofeedback training to improve individuals' emotional regulate regulation ability. Our study has shown that rtfMRI-neurofeedback training can effectively enhance the ability to voluntarily control brain responses. Furthermore, the results of the functional analysis have revealed distinct changes in the amygdala functional connectivity circuits following rtfMRI-neurofeedback training. These findings may suggest the potential clinical applications of rtfMRI-neurofeedback as a new therapy for emotionally related mental disorders.

Self-regulation of visual word form area activation with real-time fMRI neurofeedback

The Visual Word Form Area (VWFA) is a key region of the brain's reading network and its activation has been shown to be strongly associated with reading skills. Here, for the first time, we investigated whether voluntary regulation of VWFA activation is feasible using real-time fMRI neurofeedback. 40 adults with typical reading skills were instructed to either upregulate (UP group, N = 20) or downregulate (DOWN group, N = 20) their own VWFA activation during six neurofeedback training runs. The VWFA target region was individually defined based on a functional localizer task. Before and after training, also regulation runs without feedback ("no-feedback runs") were performed. When comparing the two groups, we found stronger activation across the reading network for the UP than the DOWN group. Further, activation in the VWFA was significantly stronger in the UP group than the DOWN group. Crucially, we observed a significant interaction of group and time (pre, post) for the no-feedback runs: The two groups did not differ significantly in their VWFA activation before neurofeedback training, but the UP group showed significantly stronger activation than the DOWN group after neurofeedback training. Our results indicate that upregulation of VWFA activation is feasible and that, once learned, successful upregulation can even be performed in the absence of feedback. These results are a crucial first step toward the development of a potential therapeutic support to improve reading skills in individuals with reading impairments.

Brain responses in aggression-prone individuals: A systematic review and meta-analysis of functional magnetic resonance imaging (fMRI) studies of anger- and aggression-eliciting tasks

Reactive aggression in response to perceived threat or provocation is part of humans' adaptive behavioral repertoire. However, high levels of aggression can lead to the violation of social and legal norms. Understanding brain function in individuals with high levels of aggression as they process anger- and aggression-eliciting stimuli is critical for refining explanatory models of aggression and thereby improving interventions. Three neurobiological models of reactive aggression - the limbic hyperactivity, prefrontal hypoactivity, and dysregulated limbic-prefrontal connectivity models - have been proposed. However, these models are based on neuroimaging studies involving mainly non-aggressive individuals, leaving it unclear which model best describes brain function in those with a history of aggression. We conducted a systematic literature search (PubMed and Psycinfo) and Multilevel Kernel Density meta-analysis (MKDA) of nine functional magnetic resonance imaging (fMRI) studies (eight included in the between-group analysis [i.e., aggression vs. control groups], five in the within-group analysis). Studies examined brain responses to tasks putatively eliciting anger and aggression in individuals with a history of aggression alone and relative to controls. Individuals with a history of aggression exhibited greater activity in the superior temporal gyrus and in regions comprising the cognitive control and default mode networks (right posterior cingulate cortex, precentral gyrus, precuneus, right inferior frontal gyrus) during reactive aggression relative to baseline conditions. Compared to controls, individuals with a history of aggression exhibited increased activity in limbic regions (left hippocampus, left amygdala, left parahippocampal gyrus) and temporal regions (superior, middle, inferior temporal gyrus), and reduced activity in occipital regions (left occipital cortex, left calcarine cortex). These findings lend support to the limbic hyperactivity model in individuals with a history of aggression, and further indicate altered temporal and occipital activity in anger- and aggression-eliciting conditions involving face and speech processing.

Inducing a mental context for associative memory formation with real-time fMRI neurofeedback

Memory, one of the hallmarks of human cognition, can be modified when humans voluntarily modulate neural population activity using neurofeedback. However, it is currently unknown whether neurofeedback can influence the integration of memories, and whether memory is facilitated or impaired after such neural perturbation. In this study, participants memorized objects while we provided them with abstract neurofeedback based on their brain activity patterns in the ventral visual stream. This neurofeedback created an implicit face or house context in the brain while memorizing the objects. The results revealed that participants created associations between each memorized object and its implicit context solely due to the neurofeedback manipulation. Our findings shed light onto how memory formation can be influenced by synthetic memory tags with neurofeedback and advance our understanding of mnemonic processing.

The power of negative and positive episodic memories

The power of episodic memories is that they bring a past moment into the present, providing opportunities for us to recall details of the experiences, reframe or update the memory, and use the retrieved information to guide our decisions. In these regards, negative and positive memories can be especially powerful: Life’s highs and lows are disproportionately represented in memory, and when they are retrieved, they often impact our current mood and thoughts and influence various forms of behavior. Research rooted in neuroscience and cognitive psychology has historically focused on memory for negative emotional content. Yet the study of autobiographical memories has highlighted the importance of positive emotional memories, and more recently, cognitive neuroscience methods have begun to clarify why positive memories may show powerful relations to mental wellbeing. Here, we review the models that have been proposed to explain why emotional memories are long-lasting (durable) and likely to be retrieved (accessible), describing how in overlapping—but distinctly separable—ways, positive and negative memories can be easier to retrieve, and more likely to influence behavior. We end by identifying potential implications of this literature for broader topics related to mental wellbeing, education, and workplace environments.

A real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study

Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the “happiness emotional brain state” of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4–1 Median = 6.563%; Range = 4.10–27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1–15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range −1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.

Can neurofeedback provide evidence of direct brain-behavior causality?

Neurofeedback is a procedure that measures brain activity in real-time and presents it as feedback to an individual, thus allowing them to self-regulate brain activity with effects on cognitive processes inferred from behavior. One common argument is that neurofeedback studies can reveal how the measured brain activity causes a particular cognitive process. The causal claim is often made regarding the measured brain activity being manipulated as an independent variable, similar to brain stimulation studies. However, this causal inference is vulnerable to the argument that other upstream brain activities change concurrently and cause changes in the brain activity from which feedback is derived. In this paper, we outline the inference that neurofeedback may causally affect cognition by indirect means. We further argue that researchers should remain open to the idea that the trained brain activity could be part of a "causal network" that collectively affects cognition rather than being necessarily causally primary. This particular inference may provide a better translation of evidence from neurofeedback studies to the rest of neuroscience. We argue that the recent advent of multivariate pattern analysis, when combined with implicit neurofeedback, currently comprises the strongest case for causality. Our perspective is that although the burden of inferring direct causality is difficult, it may be triangulated using a collection of various methods in neuroscience. Finally, we argue that the neurofeedback methodology provides unique advantages compared to other methods for revealing changes in the brain and cognitive processes but that researchers should remain mindful of indirect causal effects.

Neural Indices of Emotion Regulatory Implementation Correlate With Behavioral Regulatory Selection: Proof-of-Concept Investigation

“Do what you do best” conveys an intuition about the association between ability and preference. In the field of emotion regulation, ability and preference are manifested in two central stages, namely, implementation and selection of regulatory strategies, which to date have been mainly studied separately. Accordingly, the present proof-of-concept study wished to provide preliminary evidence for an association between neural indices of implementation ability and behavioral selection preferences. In this pilot study, participants performed a classic neuroimaging regulatory implementation task that examined their ability (neurally reflected in the degree of amygdala modulation) to execute two central regulatory strategies, namely, attentional distraction and cognitive reappraisal while viewing negative images. Then participants performed a separate, classic behavioral selection task that examined their choice preferences for using distraction and reappraisal while viewing negative images. Confirming our conceptual framework, we found that exclusively for distraction, which has been associated with robust amygdala modulation, a decrease in amygdala activity during implementation (i.e., enhanced ability) was associated with enhanced preference to behaviorally select distraction [r(15) = −0.69, p = 0.004]. These preliminary findings link between two central emotion regulatory stages, suggesting a clue of the adaptive association between neural ability and behavioral preference for particular regulatory strategies.

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.

Subject-independent decoding of affective states using functional near-infrared spectroscopy

Affective decoding is the inference of human emotional states using brain signal measurements. This approach is crucial to develop new therapeutic approaches for psychiatric rehabilitation, such as affective neurofeedback protocols. To reduce the training duration and optimize the clinical outputs, an ideal clinical neurofeedback could be trained using data from an independent group of volunteers before being used by new patients. Here, we investigated if this subject-independent design of affective decoding can be achieved using functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas. For this purpose, a linear discriminant analysis classifier was first trained in a dataset (49 participants, 24.65±3.23 years) and then tested in a completely independent one (20 participants, 24.00±3.92 years). Significant balanced accuracies between classes were found for positive vs. negative (64.50 ± 12.03%, p<0.01) and negative vs. neutral (68.25 ± 12.97%, p<0.01) affective states discrimination during a reactive block consisting in viewing affective-loaded images. For an active block, in which volunteers were instructed to recollect personal affective experiences, significant accuracy was found for positive vs. neutral affect classification (71.25 ± 18.02%, p<0.01). In this last case, only three fNIRS channels were enough to discriminate between neutral and positive affective states. Although more research is needed, for example focusing on better combinations of features and classifiers, our results highlight fNIRS as a possible technique for subject-independent affective decoding, reaching significant classification accuracies of emotional states using only a few but biologically relevant features.

Clinical Application of Real-Time fMRI-Based Neurofeedback for Depression

Real-time functional magnetic resonance imaging-based neurofeedback (rt-fMRI NF) is a recent technique used to train self-regulation of circumscribed brain areas or networks. For clinical applications in depression, NF training targets brain areas with disturbed activation patterns, such as heightened reactivity of amygdala in response to negative stimuli, in order to normalize the neurophysiology and their behavioral correlates. Recent studies have targeted emotion processing areas such as the amygdala, the salience network, and top-down control areas such as the lateral prefrontal cortex. Different methods of rt-fMRI-based NF in depression, their potential for clinical improvement, and most recent advancements of this technology are discussed considering their role for future clinical applications. Initial findings of randomized controlled trials show promising results. However, for lasting treatment effects, clinical efficiency and optimal target regions, tasks, control conditions, and duration of training need to be established.

Can we predict real-time fMRI neurofeedback learning success from pretraining brain activity?

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

Grant Report on the Effects of Childhood Maltreatment on Neurocircuitry in Adolescent Depression

This report describes the protocol for an ongoing project funded by the National Institutes of Health (R01MH108155) that is focused on effects of childhood maltreatment (MALTX) on neurocircuitry changes associated with adolescent major depressive disorder (MDD). Extant clinical and neuroimaging literature on MDD is reviewed, which has relied on heterogeneous samples that do not parse out the unique contribution of MALTX on neurobiological changes in MDD. Employing a 2 × 2 study design (controls with no MALTX or MDD, MALTX only, MDD only, and MDD + MALTX), and based on a cohesive theoretical model that incorporates behavioral, cognitive and neurobiological domains, we describe the multi-modal neuroimaging techniques used to test whether structural and functional alterations in the fronto-limbic and fronto-striatal circuits associated with adolescent MDD are moderated by MALTX. We hypothesize that MDD + MALTX youth will show alterations in the fronto-limbic circuit, with reduced connectivity between the amygdala (AMG) and the prefrontal cortex (PFC), as the AMG is sensitive to stress/threat during development. Participants with MDD will exhibit increased functional connectivity between the AMG and PFC due to self-referential negative emotions. Lastly, MDD + MALTX will only show changes in motivational/anticipatory aspects of the fronto-striatal circuit, and MDD will exhibit changes in motivational and consummatory/outcome aspects of reward-processing. Our goal is to identify distinct neural substrates associated with MDD due to MALTX compared to other causes, as these markers could be used to more effectively predict treatment outcome, index treatment response, and facilitate alternative treatments for adolescents who do not respond well to traditional approaches.

Evaluating the amygdala network induced by neurofeedback training for emotion regulation using hierarchical clustering

BACKGROUND

Previous studies have shown that regulating the target region by real-time fMRI-based neurofeedback training can influence the activation of other regions and the functional connectivity between them. However, it is not clear whether the training effect of neurofeedback, especially in emotion regulation, is manifested in local network specialization or global network integration. In the current study, we chose the left amygdala (LA) as the target region to regulate positive emotion through real-time fMRI training. Average-linkage hierarchical clustering was employed to cluster the fMRI data recorded during the training to construct whole-brain networks and the LA network to which the LA belongs.

RESULTS

The activation in the LA and those in some other regions were significantly up-regulated during the training. The clustering analysis at group level showed that the feedback training did not affect the number of networks in the whole brain but altered the distribution and functional connectivity in the LA network.

CONCLUSION

These findings suggested that the feedback training effects in emotion regulation pattern reflected by the activity of the target brain network and the connections within the network were robustly embodied in local network specialization instead of in global network integration.

The role of the subgenual anterior cingulate cortex in dorsomedial prefrontal-amygdala neural circuitry during positive-social emotion regulation

Positive-social emotions mediate one's cognitive performance, mood, well-being, and social bonds, and represent a critical variable within therapeutic settings. It has been shown that the upregulation of positive emotions in social situations is associated with increased top-down signals that stem from the prefrontal cortices (PFC) which modulate bottom-up emotional responses in the amygdala. However, it remains unclear if positive-social emotion upregulation of the amygdala occurs directly through the dorsomedial PFC (dmPFC) or indirectly linking the bilateral amygdala with the dmPFC via the subgenual anterior cingulate cortex (sgACC), an area which typically serves as a gatekeeper between cognitive and emotion networks. We performed functional MRI (fMRI) experiments with and without effortful positive-social emotion upregulation to demonstrate the functional architecture of a network involving the amygdala, the dmPFC, and the sgACC. We found that effortful positive-social emotion upregulation was associated with an increase in top-down connectivity from the dmPFC on the amygdala via both direct and indirect connections with the sgACC. Conversely, we found that emotion processes without effortful regulation increased network modulation by the sgACC and amygdala. We also found that more anxious individuals with a greater tendency to suppress emotions and intrusive thoughts, were likely to display decreased amygdala, dmPFC, and sgACC activity and stronger connectivity strength from the sgACC onto the left amygdala during effortful emotion upregulation. Analyzed brain network suggests a more general role of the sgACC in cognitive control and sheds light on neurobiological informed treatment interventions.

Imaging the socially-anxious brain: recent advances and future prospects

Social anxiety disorder (SAD) is serious psychiatric condition with a genetic background. Insight into the neurobiological alterations underlying the disorder is essential to develop effective interventions that could relieve SAD-related suffering. In this expert review, we consider recent neuroimaging work on SAD. First, we focus on new results from magnetic resonance imaging studies dedicated to outlining biomarkers of SAD, including encouraging findings with respect to structural and functional brain alterations associated with the disorder. Furthermore, we highlight innovative studies in the field of neuroprediction and studies that established the effects of treatment on brain characteristics. Next, we describe novel work aimed to delineate endophenotypes of SAD, providing insight into the genetic susceptibility to develop the disorder. Finally, we outline outstanding questions and point out directions for future research.

Changes in functional connectivity with cognitive behavioral therapy for social anxiety disorder predict outcomes at follow-up

Approximately half of individuals with Social Anxiety Disorder (SAD) treated with psychological intervention do not achieve clinically significant improvement or retain long-term gains. Neurobiological models of SAD propose that disruptions in functioning of amygdala-prefrontal circuitry is implicated in short-term treatment response. However, whether treatment-related changes in functional connectivity predict long-term well-being after psychotherapy is unknown. Patients with SAD completed an incidental emotion regulation task during fMRI before and after treatment with cognitive behavioral therapy or acceptance and commitment therapy (n = 23, collapsed across groups). Psychophysiological interaction analyses using amygdala seed regions were conducted to assess changes in functional connectivity from pre-to post-treatment that predicted symptom change from 6 to 12-month follow-up. Negative change (i.e., greater inverse/weaker positive) in amygdala connectivity with the dorsomedial prefrontal cortex (dmPFC) and dorsal anterior cingulate cortex (dACC) predicted greater symptom reduction during follow-up. Positive change in amygdala connectivity with the cerebellum, fusiform gyrus, and pre-central and post-central gyri predicted less symptom reduction (e.g., no change or worsening). Results suggest that strengthened amygdala connectivity with regulatory regions may promote better long-term outcomes, whereas changes with visual and sensorimotor regions may represent sensitization to emotion-related cues, conferring poorer outcomes. Clinical implications for treatment personalization are discussed, should effects replicate in larger samples.

Regulating posttraumatic stress disorder symptoms with neurofeedback: Regaining control of the mind

Neurofeedback is emerging as a psychophysiological treatment where self-regulation is achieved through online feedback of neural states. Novel personalized medicine approaches are particularly important for the treatment of posttraumatic stress disorder (PTSD), as symptom presentation of the disorder, as well as responses to treatment, are highly heterogeneous. Learning to achieve control of specific neural substrates through neurofeedback has been shown to display therapeutic evidence in patients with a wide variety of psychiatric disorders, including PTSD. This article outlines the neural mechanisms underlying neurofeedback and examines converging evidence for the efficacy of neurofeedback as an adjunctive treatment for PTSD via both electroencephalography (EEG) and real-time functional magnetic resonance imaging (fMRI) modalities. Further, implications for the treatment of PTSD via neurofeedback in the military member and Veteran population is examined.

Improved emotion regulation after neurofeedback: A single-arm trial in patients with borderline personality disorder

Real-time functional magnetic resonance imaging (fMRI) neurofeedback training of amygdala hemodynamic activity directly targets a neurobiological mechanism, which contributes to emotion regulation problems in borderline personality disorder (BPD). However, it remains unknown which outcome measures can assess changes in emotion regulation and affective instability, associated with amygdala downregulation in a clinical trial. The current study directly addresses this question. Twenty-four female patients with a DSM-IV BPD diagnosis underwent four runs of amygdala neurofeedback. Before and after the training, as well as at a six-weeks follow-up assessment, participants completed measures of emotion dysregulation and affective instability at diverse levels of analysis (verbal report, clinical interview, ecological momentary assessment, emotion-modulated startle, heart rate variability, and fMRI). Participants were able to downregulate their amygdala blood oxygen-dependent (BOLD) response with neurofeedback. There was a decrease of BPD symptoms as assessed with the Zanarini rating scale for BPD (ZAN-BPD) and a decrease in emotion-modulated startle to negative pictures after training. Further explorative analyses suggest that patients indicated less affective instability, as seen by lower hour-to-hour variability in negative affect and inner tension in daily life. If replicated by an independent study, our results imply changes in emotion regulation and affective instability for several systems levels, including behavior and verbal report. Conclusions are limited due to the lack of a control group. A randomized controlled trial (RCT) will be needed to confirm effectiveness of the training.

Emotion Regulation of Hippocampus Using Real-Time fMRI Neurofeedback in Healthy Human

Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) is a prospective tool to enhance the emotion regulation capability of participants and to alleviate their emotional disorders. The hippocampus is a key brain region in the emotional brain network and plays a significant role in social cognition and emotion processing in the brain. However, few studies have focused on the emotion NF of the hippocampus. This study investigated the feasibility of NF training of healthy participants to self-regulate the activation of the hippocampus and assessed the effect of rtfMRI-NF on the hippocampus before and after training. Twenty-six right-handed healthy volunteers were randomly assigned to the experimental group receiving hippocampal rtfMRI-NF (n = 13) and the control group (CG) receiving rtfMRI-NF from the intraparietal sulcus rtfMRI-NF (n = 13) and completed a total of four NF runs. The hippocampus and the intraparietal sulcus were defined based on the Montreal Neurological Institute (MNI) standard template, and NF signal was measured as a percent signal change relative to the baseline obtained by averaging the fMRI signal for the preceding 20 s long rest block. NF signal (percent signal change) was updated every 2 s and was displayed on the screen. The amplitude of low-frequency fluctuation and regional homogeneity values was calculated to evaluate the effects of NF on spontaneous neural activity in resting-state fMRI. A standard general linear model (GLM) analysis was separately conducted for each fMRI NF run. Results showed that the activation of hippocampus increased after four NF training runs. The hippocampal activity of the experiment group participants was higher than that of the CG. They also showed elevated hippocampal activity and the greater amygdala–hippocampus connectivity. The anterior temporal lobe, parahippocampal gyrus, hippocampus, and amygdala of brain regions associated with emotional processing were activated during training. We presented a proof-of-concept study using rtfMRI-NF for hippocampus up-regulation in the recall of positive autobiographical memories. The current study may provide a new method to regulate our emotions and can potentially be applied to the clinical treatment of emotional disorders.

Amygdala Modulation During Emotion Regulation Training With fMRI-Based Neurofeedback

Available evidence suggests that individuals can enhance their ability to modulate brain activity in target regions, within the Emotion Regulation network, using fMRI-based neurofeedback. However, there is no systematic review that investigates the effectiveness of this method on amygdala modulation, a core region within this network. The major goal of this study was to systematically review and analyze the effects of real-time fMRI-Neurofeedback concerning the neuromodulation of the amygdala during Emotion Regulation training. A search was performed in PubMed, Science Direct, and Web of Science with the following key terms: ≪(“neurofeedback” or “neuro feedback” or “neuro-feedback”) and (“emotion regulation”) and (fMRI OR “functional magnetic resonance”),≫ and afterwards two additional searches were performed, replacing the term “emotion regulation” for “amygdala” and “neurofeedback” for “feedback.” Of the 531 identified articles, only 19 articles reported results of amygdala modulation during Emotional Regulation training through rtfMRI-NF, using healthy participants or patients, in original research articles. The results, systematically reviewed here, provide evidence for amygdala's modulation during rtfMRI-NF training, although studies' heterogeneity precluded a quantitative meta-analysis—the included studies relied on different outcome measures to infer the success of neurofeedback intervention. Thus, a qualitative analysis was done instead. We identified critical features influencing inference on the quality of the intervention as: the inclusion of a Practice Run, a Transfer Run and a Control Group in the protocol, and to choose adequate Emotion Regulation strategies—in particular, the effective recall of autobiographic memories. Surprisingly, the Regulated vs. Control Condition was lacking in most of the studies, precluding valid inference of amygdala neuromodulation within Session. The best controlled studies nevertheless showed positive effects. The type of stimulus/interface did not seem critical for amygdala modulation. We also identified potential effects of lateralization of amygdala responses following Up- or Down-Regulation, and the impact of fMRI parameters for data acquisition and analysis. Despite qualitative evidence for amygdala modulation during rtfMRI-NF, there are still important limitations in the design of a clear conceptual framework of NF-training research. Future studies should focus on more homogeneous guidelines concerning design, protocol structure and, particularly, harmonized outcome measures to provide quantitative estimates of neuromodulatory effects in the amygdala.

Targeting dynamic facial processing mechanisms in superior temporal sulcus using a novel fMRI neurofeedback target

The superior temporal sulcus (STS) encompasses a complex set of regions involved in a wide range of cognitive functions. To understand its functional properties, neuromodulation approaches such brain stimulation or neurofeedback can be used. We investigated whether the posterior STS (pSTS), a core region in the face perception and imagery network, could be specifically identified based on the presence of dynamic facial expressions (and not just on simple motion or static face signals), and probed with neurofeedback. Recognition of facial expressions is critically impaired in autism spectrum disorder, making this region a relevant target for future clinical neurofeedback studies. We used a stringent localizer approach based on the contrast of dynamic facial expressions against static neutral faces plus moving dots. The target region had to be specifically responsive to dynamic facial expressions instead of mere motion and/or the presence of a static face. The localizer was successful in selecting this region across subjects. Neurofeedback was then performed, using this region as a target, with two novel feedback rules (mean or derivative-based, using visual or auditory interfaces). Our results provide evidence that a facial expression-selective cluster in pSTS can be identified and may represent a suitable target for neurofeedback approaches, aiming at social and emotional cognition. These findings highlight the presence of a highly selective region in STS encoding dynamic aspects of facial expressions. Future studies should elucidate its role as a mechanistic target for neurofeedback strategies in clinical disorders of social cognition such as autism.

Neurofeedback: Principles, appraisal, and outstanding issues

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last 20 years, neurofeedback has been used to treat various neurological and psychiatric conditions, and to improve cognitive function in various contexts. However, in spite of a growing popularity, neurofeedback protocols typically make (often covert) assumptions on what aspects of brain activity to target, where in the brain to act and how, which have far-reaching implications for the assessment of its potential and efficacy. Here we critically examine some conceptual and methodological issues associated with the way neurofeedback's general objectives and neural targets are defined. The neural mechanisms through which neurofeedback may act at various spatial and temporal scales, and the way its efficacy is appraised are reviewed, and the extent to which neurofeedback may be used to control functional brain activity discussed. Finally, it is proposed that gauging neurofeedback's potential, as well as assessing and improving its efficacy will require better understanding of various fundamental aspects of brain dynamics and a more precise definition of functional brain activity and brain-behaviour relationships.

Intrinsic connectivity network dynamics in PTSD during amygdala downregulation using real-time fMRI neurofeedback: A preliminary analysis

Posttraumatic stress disorder (PTSD) has been associated with a disturbance in neural intrinsic connectivity networks (ICN), including the central executive network (CEN), default mode network (DMN), and salience network (SN). Here, we conducted a preliminary investigation examining potential changes in ICN recruitment as a function of real-time fMRI neurofeedback (rt-fMRI-NFB) during symptom provocation where we targeted the downregulation of neural response within the amygdala-a key region-of-interest in PTSD neuropathophysiology. Patients with PTSD (n = 14) completed three sessions of rt-fMRI-NFB with the following conditions: (a) regulate: decrease activation in the amygdala while processing personalized trauma words; (b) view: process trauma words while not attempting to regulate the amygdala; and (c) neutral: process neutral words. We found that recruitment of the left CEN increased over neurofeedback runs during the regulate condition, a finding supported by increased dlPFC activation during the regulate as compared to the view condition. In contrast, DMN task-negative recruitment was stable during neurofeedback runs, albeit was the highest during view conditions and increased (normalized) during rest periods. Critically, SN recruitment was high for both the regulate and the view conditions, a finding potentially indicative of CEN modality switching, adaptive learning, and increasing threat/defense processing in PTSD. In conclusion, this study provides provocative, preliminary evidence that downregulation of the amygdala using rt-fMRI-NFB in PTSD is associated with dynamic changes in ICN, an effect similar to those observed using EEG modalities of neurofeedback.

Amygdala real-time functional magnetic resonance imaging neurofeedback for major depressive disorder: A review

Advances in imaging technologies have allowed for the analysis of functional magnetic resonance imaging data in real-time (rtfMRI), leading to the development of neurofeedback (nf) training. This rtfMRI-nf training utilizes functional magnetic resonance imaging (fMRI) tomographic localization capacity to allow a person to see and regulate the localized hemodynamic signal from his or her own brain. In this review, we summarize the results of several studies that have developed and applied neurofeedback training to healthy and depressed individuals with the amygdala as the neurofeedback target and the goal to increase the hemodynamic response during positive autobiographical memory recall. We review these studies and highlight some of the challenges and advances in developing an rtfMRI-nf paradigm for broader use in psychiatric populations. The work described focuses on our line of research aiming to develop the rtfMRI-nf into an intervention, and includes a discussion of the selection of a region of interest for feedback, selecting a control condition, behavioral and cognitive effects of training, and predicting which participants are most likely to respond well to training. While the results of these studies are encouraging and suggest the clinical potential of amygdala rtfMRI-nf in alleviating symptoms of major depressive disorder, larger studies are warranted to confirm its efficacy.

Mapping the Cortical Network Arising From Up-Regulated Amygdaloidal Activation Using -Louvain Algorithm

The amygdala plays an important role in emotion processing. Several studies have proved that its activation can be regulated by real-time functional magnetic resonance imaging (rtfMRI)-based neurofeedback training. However, although studies have found brain regions that are functionally closely connected to the amygdala in the cortex, it is not clear whether these brain regions and the amygdala are structurally closely connected, and if they show the same training effect as the amygdala in the process of emotional regulation. In this paper, we instructed subjects to up-regulate the activation of the left amygdala (LA) through rtfMRI-based neurofeedback training. In order to fuse multimodal imaging data, we introduced a network analysis method called the -Louvain clustering algorithm. This method was used to integrate multimodal data from the training experiment and construct an LA-cortical network. Correlation analysis and main-effect analysis were conducted to determine the signal covariance associated with the activation of the target area; ultimately, we identified the left temporal pole superior as the amygdaloidal-cortical network region. As a deep nucleus in the brain, the treatment and stimulation of the amygdala remains challenging. Our results provide new insights for the regulation of activation in a deep nucleus using more neurofeedback techniques.

Monitoring and control of amygdala neurofeedback involves distributed information processing in the human brain

Brain-computer interfaces provide conscious access to neural activity by means of brain-derived feedback ("neurofeedback"). An individual's abilities to monitor and control feedback are two necessary processes for effective neurofeedback therapy, yet their underlying functional neuroanatomy is still being debated. In this study, healthy subjects received visual feedback from their amygdala response to negative pictures. Activation and functional connectivity were analyzed to disentangle the role of brain regions in different processes. Feedback monitoring was mapped to the thalamus, ventromedial prefrontal cortex (vmPFC), ventral striatum (VS), and rostral PFC. The VS responded to feedback corresponding to instructions while rPFC activity differentiated between conditions and predicted amygdala regulation. Control involved the lateral PFC, anterior cingulate, and insula. Monitoring and control activity overlapped in the VS and thalamus. Extending current neural models of neurofeedback, this study introduces monitoring and control of feedback as anatomically dissociated processes, and suggests their important role in voluntary neuromodulation.

Mitigation of stress: new treatment alternatives

Complaints of stress are common in modern life. Psychological stress is a major cause of lifestyle-related issues, contributing to poor quality of life. Chronic stress impedes brain function, causing impairment of many executive functions, including working memory, decision making and attentional control. The current study sought to describe newly developed stress mitigation techniques, and their influence on autonomic and endocrine functions. The literature search revealed that the most frequently studied technique for stress mitigation was biofeedback (BFB). However, evidence suggests that neurofeedback (NFB) and noninvasive brain stimulation (NIBS) could potentially provide appropriate approaches. We found that recent studies of BFB methods have typically used measures of heart rate variability, respiration and skin conductance. In contrast, studies of NFB methods have typically utilized neurocomputation techniques employing electroencephalography, functional magnetic resonance imaging and near infrared spectroscopy. NIBS studies have typically utilized transcranial direct current stimulation methods. Mitigation of stress is a challenging but important research target for improving quality of life.

Intermittent compared to continuous real-time fMRI neurofeedback boosts control over amygdala activation

Real-time fMRI neurofeedback is a feasible tool to learn the volitional regulation of brain activity. So far, most studies provide continuous feedback information that is presented upon every volume acquisition. Although this maximizes the temporal resolution of feedback information, it may be accompanied by some disadvantages. Participants can be distracted from the regulation task due to (1) the intrinsic delay of the hemodynamic response and associated feedback and (2) limited cognitive resources available to simultaneously evaluate feedback information and stay engaged with the task. Here, we systematically investigate differences between groups presented with different variants of feedback (continuous vs. intermittent) and a control group receiving no feedback on their ability to regulate amygdala activity using positive memories and feelings. In contrast to the feedback groups, no learning effect was observed in the group without any feedback presentation. The group receiving intermittent feedback exhibited better amygdala regulation performance when compared with the group receiving continuous feedback. Behavioural measurements show that these effects were reflected in differences in task engagement. Overall, we not only demonstrate that the presentation of feedback is a prerequisite to learn volitional control of amygdala activity but also that intermittent feedback is superior to continuous feedback presentation.

Resting state brain network function in major depression - Depression symptomatology, antidepressant treatment effects, future research

The alterations of functional connectivity brain networks in major depressive disorder (MDD) have been subject of a large number of studies. Using different methodologies and focusing on diverse aspects of the disease, research shows heterogeneous results lacking integration. Disrupted network connectivity has been found in core MDD networks like the default mode network (DMN), the central executive network (CEN), and the salience network, but also in cerebellar and thalamic circuitries. Here we review literature published on resting state brain network function in MDD focusing on methodology, and clinical characteristics including symptomatology and antidepressant treatment related findings. There are relatively few investigations concerning the qualitative aspects of symptomatology of MDD, whereas most studies associate quantitative aspects with distinct resting state functional connectivity alterations. Such depression severity associated alterations are found in the DMN, frontal, cerebellar and thalamic brain regions as well as the insula and the subgenual anterior cingulate cortex. Similarly, different therapeutical options in MDD and their effects on brain function showed patchy results. Herein, pharmaceutical treatments reveal functional connectivity alterations throughout multiple brain regions notably the DMN, fronto-limbic, and parieto-temporal regions. Psychotherapeutical interventions show significant functional connectivity alterations in fronto-limbic networks, whereas electroconvulsive therapy and repetitive transcranial magnetic stimulation result in alterations of the subgenual anterior cingulate cortex, the DMN, the CEN and the dorsal lateral prefrontal cortex. While it appears clear that functional connectivity alterations are associated with the pathophysiology and treatment of MDD, future research should also generate a common strategy for data acquisition and analysis, as a least common denominator, to set the basis for comparability across studies and implementation of functional connectivity as a scientifically and clinically useful biomarker.

Assessing the Effectiveness of Neurofeedback Training in the Context of Clinical and Social Neuroscience

Social neuroscience benefits from the experimental manipulation of neuronal activity. One possible manipulation, neurofeedback, is an operant conditioning-based technique in which individuals sense, interact with, and manage their own physiological and mental states. Neurofeedback has been applied to a wide variety of psychiatric illnesses, as well as to treat sub-clinical symptoms, and even to enhance performance in healthy populations. Despite growing interest, there persists a level of distrust and/or bias in the medical and research communities in the USA toward neurofeedback and other functional interventions. As a result, neurofeedback has been largely ignored, or disregarded within social neuroscience. We propose a systematic, empirically-based approach for assessing the effectiveness, and utility of neurofeedback. To that end, we use the term perturbative physiologic plasticity to suggest that biological systems function as an integrated whole that can be perturbed and guided, either directly or indirectly, into different physiological states. When the intention is to normalize the system, e.g., via neurofeedback, we describe it as self-directed neuroplasticity, whose outcome is persistent functional, structural, and behavioral changes. We argue that changes in physiological, neuropsychological, behavioral, interpersonal, and societal functioning following neurofeedback can serve as objective indices and as the metrics necessary for assessing levels of efficacy. In this chapter, we examine the effects of neurofeedback on functional connectivity in a few clinical disorders as case studies for this approach. We believe this broader perspective will open new avenues of investigation, especially within social neuroscience, to further elucidate the mechanisms and effectiveness of these types of interventions, and their relevance to basic research.

Computational neuroscience approach to biomarkers and treatments for mental disorders

Psychiatry research has long experienced a stagnation stemming from a lack of understanding of the neurobiological underpinnings of phenomenologically defined mental disorders. Recently, the application of computational neuroscience to psychiatry research has shown great promise in establishing a link between phenomenological and pathophysiological aspects of mental disorders, thereby recasting current nosology in more biologically meaningful dimensions. In this review, we highlight recent investigations into computational neuroscience that have undertaken either theory- or data-driven approaches to quantitatively delineate the mechanisms of mental disorders. The theory-driven approach, including reinforcement learning models, plays an integrative role in this process by enabling correspondence between behavior and disorder-specific alterations at multiple levels of brain organization, ranging from molecules to cells to circuits. Previous studies have explicated a plethora of defining symptoms of mental disorders, including anhedonia, inattention, and poor executive function. The data-driven approach, on the other hand, is an emerging field in computational neuroscience seeking to identify disorder-specific features among high-dimensional big data. Remarkably, various machine-learning techniques have been applied to neuroimaging data, and the extracted disorder-specific features have been used for automatic case-control classification. For many disorders, the reported accuracies have reached 90% or more. However, we note that rigorous tests on independent cohorts are critically required to translate this research into clinical applications. Finally, we discuss the utility of the disorder-specific features found by the data-driven approach to psychiatric therapies, including neurofeedback. Such developments will allow simultaneous diagnosis and treatment of mental disorders using neuroimaging, thereby establishing 'theranostics' for the first time in clinical psychiatry.

The neurobiology of emotion regulation in posttraumatic stress disorder: Amygdala downregulation via real-time fMRI neurofeedback

Amygdala dysregulation has been shown to be central to the pathophysiology of posttraumatic stress disorder (PTSD) representing a critical treatment target. Here, amygdala downregulation was targeted using real-time fMRI neurofeedback (rt-fMRI-nf) in patients with PTSD, allowing us to examine further the regulation of emotional states during symptom provocation. Patients (n = 10) completed three sessions of rt-fMRI-nf with the instruction to downregulate activation in the amygdala, while viewing personalized trauma words. Amygdala downregulation was assessed by contrasting (a) regulate trials, with (b) viewing trauma words and not attempting to regulate. Training was followed by one transfer run not involving neurofeedback. Generalized psychophysiological interaction (gPPI) and dynamic causal modeling (DCM) analyses were also computed to explore task-based functional connectivity and causal structure, respectively. It was found that PTSD patients were able to successfully downregulate both right and left amygdala activation, showing sustained effects within the transfer run. Increased activation in the dorsolateral and ventrolateral prefrontal cortex (PFC), regions related to emotion regulation, was observed during regulate as compared with view conditions. Importantly, activation in the PFC, rostral anterior cingulate cortex, and the insula, were negatively correlated to PTSD dissociative symptoms in the transfer run. Increased functional connectivity between the amygdala- and both the dorsolateral and dorsomedial PFC was found during regulate, as compared with view conditions during neurofeedback training. Finally, our DCM analysis exploring directional structure suggested that amygdala downregulation involves both top-down and bottom-up information flow with regard to observed PFC-amygdala connectivity. This is the first demonstration of successful downregulation of the amygdala using rt-fMRI-nf in PTSD, which was critically sustained in a subsequent transfer run without neurofeedback, and corresponded to increased connectivity with prefrontal regions involved in emotion regulation during the intervention. Hum Brain Mapp 38:541-560, 2017. © 2016 Wiley Periodicals, Inc.

When the Brain Takes 'BOLD' Steps: Real-Time fMRI Neurofeedback Can Further Enhance the Ability to Gradually Self-regulate Regional Brain Activation

•

Humans are able to gradually self-regulate regional brain activation by applying cognitive strategies.

•

Providing rtfMRI neurofeedback can enhance the gradual self-regulation ability.

•

Findings are generalizable to various mental tasks and clinical MR field strengths.

•

Novel parametric activation paradigm enriches spectrum of rtfMRI-neurofeedback and BCI methodology.

Brain-computer interfaces (BCIs) based on real-time functional magnetic resonance imaging (rtfMRI) are currently explored in the context of developing alternative (motor-independent) communication and control means for the severely disabled. In such BCI systems, the user encodes a particular intention (e.g., an answer to a question or an intended action) by evoking specific mental activity resulting in a distinct brain state that can be decoded from fMRI activation. One goal in this context is to increase the degrees of freedom in encoding different intentions, i.e., to allow the BCI user to choose from as many options as possible. Recently, the ability to voluntarily modulate spatial and/or temporal blood oxygenation level-dependent (BOLD)-signal features has been explored implementing different mental tasks and/or different encoding time intervals, respectively. Our two-session fMRI feasibility study systematically investigated for the first time the possibility of using magnitudinal BOLD-signal features for intention encoding. Particularly, in our novel paradigm, participants (n = 10) were asked to alternately self-regulate their regional brain-activation level to 30%, 60% or 90% of their maximal capacity by applying a selected activation strategy (i.e., performing a mental task, e.g., inner speech) and modulation strategies (e.g., using different speech rates) suggested by the experimenters. In a second step, we tested the hypothesis that the additional availability of feedback information on the current BOLD-signal level within a region of interest improves the gradual-self regulation performance. Therefore, participants were provided with neurofeedback in one of the two fMRI sessions. Our results show that the majority of the participants were able to gradually self-regulate regional brain activation to at least two different target levels even in the absence of neurofeedback. When provided with continuous feedback on their current BOLD-signal level, most participants further enhanced their gradual self-regulation ability. Our findings were observed across a wide variety of mental tasks and across clinical MR field strengths (i.e., at 1.5 T and 3 T), indicating that these findings are robust and can be generalized across mental tasks and scanner types. The suggested novel parametric activation paradigm enriches the spectrum of current rtfMRI-neurofeedback and BCI methodology and has considerable potential for fundamental and clinical neuroscience applications.

Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging-Inspired Electroencephalography Improves Implicit Emotion Regulation

The amygdala has a pivotal role in processing traumatic stress; hence, gaining control over its activity could facilitate adaptive mechanism and recovery. To date, amygdala volitional regulation could be obtained only via real-time functional magnetic resonance imaging (fMRI), a highly inaccessible procedure. The current article presents high-impact neurobehavioral implications of a novel imaging approach that enables bedside monitoring of amygdala activity using fMRI-inspired electroencephalography (EEG), hereafter termed amygdala-electrical fingerprint (amyg-EFP). Simultaneous EEG/fMRI indicated that the amyg-EFP reliably predicts amygdala-blood oxygen level-dependent activity. Implementing the amyg-EFP in neurofeedback demonstrated that learned downregulation of the amyg-EFP facilitated volitional downregulation of amygdala-blood oxygen level-dependent activity via real-time fMRI and manifested as reduced amygdala reactivity to visual stimuli. Behavioral evidence further emphasized the therapeutic potential of this approach by showing improved implicit emotion regulation following amyg-EFP neurofeedback. Additional EFP models denoting different brain regions could provide a library of localized activity for low-cost and highly accessible brain-based diagnosis and treatment.

To work or not to work: Neural representation of cost and benefit of instrumental action

By definition, instrumental actions are performed in order to obtain certain goals. Nevertheless, the attainment of goals typically implies obstacles, and response vigor is known to reflect an integration of subjective benefit and cost. Whereas several brain regions have been associated with cost/benefit ratio decision-making, trial-by-trial fluctuations in motivation are not well understood. We review recent evidence supporting the motivational implications of signal fluctuations in the mesocorticolimbic system. As an extension of "set-point" theories of instrumental action, we propose that response vigor is determined by a rapid integration of brain signals that reflect value and cost on a trial-by-trial basis giving rise to an online estimate of utility. Critically, we posit that fluctuations in key nodes of the network can predict deviations in response vigor and that variability in instrumental behavior can be accounted for by models devised from optimal control theory, which incorporate the effortful control of noise. Notwithstanding, the post hoc analysis of signaling dynamics has caveats that can effectively be addressed in future research with the help of two novel fMRI imaging techniques. First, adaptive fMRI paradigms can be used to establish a time-order relationship, which is a prerequisite for causality, by using observed signal fluctuations as triggers for stimulus presentation. Second, real-time fMRI neurofeedback can be employed to induce predefined brain states that may facilitate benefit or cost aspects of instrumental actions. Ultimately, understanding temporal dynamics in brain networks subserving response vigor holds the promise for targeted interventions that could help to readjust the motivational balance of behavior.

Task-based neurofeedback training: A novel approach toward training executive functions

Cognitive training is an emergent approach to improve cognitive functions in various neurodevelopmental and neurodegenerative diseases. However, current training programs can be relatively lengthy, making adherence potentially difficult for patients with cognitive difficulties. Previous studies suggest that providing individuals with real-time feedback about the level of brain activity (neurofeedback) can potentially help them learn to control the activation of specific brain regions. In the present study, we developed a novel task-based neurofeedback training paradigm that benefits from the effects of neurofeedback in parallel with computerized training. We focused on executive function training given its core involvement in various developmental and neurodegenerative diseases. Near-infrared spectroscopy (NIRS) was employed for providing neurofeedback by measuring changes in oxygenated hemoglobin in the prefrontal cortex. Of the twenty healthy adult participants, ten received real neurofeedback (NFB) on prefrontal activity during cognitive training, and ten were presented with sham feedback (SHAM). Compared with SHAM, the NFB group showed significantly improved executive function performance including measures of working memory after four sessions of training (100min total). The NFB group also showed significantly reduced training-related brain activity in the executive function network including right middle frontal and inferior frontal regions compared with SHAM. Our data suggest that providing neurofeedback along with cognitive training can enhance executive function after a relatively short period of training. Similar designs could potentially be used for patient populations with known neuropathology, potentially helping them to boost/recover the activity in the affected brain regions.