Voluntary control of anterior insula and its functional connections is feedback-independent and increases pain empathy

Self-navigating the "Island of Reil": a systematic review of real-time fMRI neurofeedback training of insula activity

Real-time fMRI (rtfMRI) neurofeedback (NF) is a novel noninvasive technique that permits individuals to voluntarily control brain activity. The crucial role of the insula in emotional and salience processing makes it one of the most commonly targeted regions in previous rtfMRI studies. To provide an overview of progress in the field, the present review identified 25 rtfMRI insula studies and systematically reviewed key characteristics and findings in these studies. We found that rtfMRI-based NF training is efficient for modulating insula activity and its associated behavioral/symptom-related and neural changes. Furthermore, we also observed a maintenance effect of self-regulation ability and sustained symptom improvement, which is of importance for clinical application. However, training success of insula regulation was not consistently paralleled by behavioral/symptom-related changes, suggesting a need for optimizing the NF training protocol enabling more robust training effects. Principles including inclusion of a well-designed control group/condition, statistical analyses and reporting results following common criteria and a priori determination of sample and effect sizes as well as pre-registration are also highly recommended. In summary, we believe our review will inspire and inform both basic research and therapeutic translation of rtfMRI NF training as an intervention in mental disorders particularly those with insula dysfunction.

Neural mechanisms, influencing factors and interventions in empathic pain

Empathic pain, defined as the emotional resonance with the suffering of others, is akin to the observer's own experience of pain and is vital for building and sustaining positive interpersonal relationships. Despite its importance, the neural mechanism of empathic pain remains poorly understood. In this review, we integrated and summarized the currently knowledge on the neural networks associated with empathic pain, focusing on key brain regions such as the insula, anterior cingulate cortex (ACC), ventral tegmental area (VTA), nucleus accumbens (NAc), and locus coeruleus (LC)/norepinephrine (NE)-sympatho-adrenomedullar (LC/NE-SAM) system. We also reviewed the factors that affect empathic pain, including gender, personal beliefs, the intimacy of relationships, and the nature of interpersonal relationships, and highlighted the central role of the insula and ACC in the neural circuitry of empathy, the importance of the IC-BLA and ACC-NAc/VTA connections in modulating empathic pain, and the involvement of the LC/NE-SAM system in mediating pain empathy. We further discussed how gender significantly influences empathic pain, with women showing more intense emotional reactions to social distress than men. It also summarized the roles of personal pain history and empathy levels in modulating empathic responses. Furthermore, the review emphasized the impact of social factors such as the nature of interpersonal relationships and experiences of social exclusion on empathic pain. By providing a detailed exploration of the neural mechanisms and influencing factors of empathic pain, this review aims to establish a robust foundation for developing targeted therapeutic strategies and improving pain management in clinical settings.

Neural Basis of Pain Empathy Dysregulations in Mental Disorders: A Preregistered Neuroimaging Meta-Analysis

BACKGROUND

Pain empathy represents a fundamental building block of several social functions, which have been demonstrated to be impaired across various mental disorders by accumulating evidence from case-control functional magnetic resonance imaging studies. However, it remains unclear whether the dysregulations are underpinned by robust neural alterations across mental disorders.

METHODS

This study utilized coordinate-based meta-analyses to quantitatively determine robust markers of altered pain empathy across mental disorders. To support the interpretation of the findings, exploratory network-level and behavioral meta-analyses were conducted.

RESULTS

Quantitative analysis of 11 case-control functional magnetic resonance imaging studies with data from 296 patients and 229 control participants revealed that patients with mental disorders exhibited increased pain empathic reactivity in the left anterior cingulate gyrus, adjacent medial prefrontal cortex, and right middle temporal gyrus but decreased activity in the left cerebellum IV/V and left middle occipital gyrus compared with control participants. The hyperactive regions showed network-level interactions with the core default mode network and were associated with affective and social cognitive domains.

CONCLUSIONS

The findings suggest that pain empathic alterations across mental disorders are underpinned by excessive empathic reactivity in brain systems involved in empathic distress and social processes, highlighting a shared therapeutic target to normalize basal social dysfunctions in mental disorders.

Real-Time fMRI Neurofeedback Modulation of Dopaminergic Midbrain Activity in Young Adults With Elevated Internet Gaming Disorder Risk: Randomized Controlled Trial

This study provides preliminary evidence for real-time functional magnetic resonance imaging neurofeedback (rt-fMRI NF) as a potential intervention approach for internet gaming disorder (IGD). In a preregistered, randomized, single-blind trial, young individuals with elevated IGD risk were trained to downregulate gaming addiction-related brain activity. We show that, after 2 sessions of neurofeedback training, participants successfully downregulated their brain responses to gaming cues, suggesting the therapeutic potential of rt-fMRI NF for IGD (Trial Registration: ClinicalTrials.gov NCT06063642; https://clinicaltrials.gov/study/NCT06063642).

Connectivity-Based Real-Time Functional Magnetic Resonance Imaging Neurofeedback in Nicotine Users: Mechanistic and Clinical Effects of Regulating a Meta-Analytically Defined Target Network in a Double-Blind Controlled Trial

One of the fundamental questions in real-time functional magnetic resonance imaging neurofeedback (rt-fMRI NF) investigations is the definition of a suitable neural target for training. Previously, we applied a meta-analytical approach to define a network-level target for connectivity-based rt-fMRI NF in substance use disorders. The analysis yielded consistent connectivity alterations between the insula and anterior cingulate cortex (ACC) as well as the dorsal striatum and the ACC. In the current investigation, we addressed the feasibility of regulating this network and its functional relevance using connectivity-based neurofeedback. In a double-blind, sham-controlled design, 60 nicotine users were randomly assigned to the experimental or sham control group for one NF training session. The preregistered primary outcome was defined as improved inhibitory control performance after regulation of the target network compared to sham control. Secondary outcomes were (1) neurofeedback-specific changes in functional connectivity of the target network; (2) changes in smoking behavior and impulsivity measures; and (3) changes in resting-state connectivity profiles. Our results indicated no differences in behavioral measures after receiving feedback from the target network compared to the sham feedback. Target network connectivity was increased during regulation blocks compared to rest blocks, however, the experimental and sham groups could regulate to a similar degree. Accordingly, the observed activation patterns may be related to the mental strategies used during regulation attempts irrespective of the group assignment. We discuss several crucial factors regarding the efficacy of a single-session connectivity-based neurofeedback for the target network. This includes high fluctuation in the connectivity values of the target network that may impact controllability of the signal. To our knowledge, this investigation is the first randomized, double-blind controlled real-time fMRI study in nicotine users. This raises the question of whether previously observed effects in nicotine users are specific to the neurofeedback signal or reflect more general self-regulation attempts.

Identifying brain targets for real-time fMRI neurofeedback in chronic pain: insights from functional neurosurgery

Background

The lack of clearly defined neuromodulation targets has contributed to the inconsistent results of real-time fMRI-based neurofeedback (rt-fMRI-NF) for the treatment of chronic pain. Functional neurosurgery (funcSurg) approaches have shown more consistent effects in reducing pain in patients with severe chronic pain.

Objective

This study aims to redefine rt-fMRI-NF targets for chronic pain management informed by funcSurg studies.

Methods

Based on independent systematic reviews, we identified the neuromodulation targets of the rt-fMRI-NF (in acute and chronic pain) and funcSurg (in chronic pain) studies. We then characterized the underlying functional networks using a subsample of the 7 T resting-state fMRI dataset from the Human Connectome Project. Principal component analyses (PCA) were used to identify dominant patterns (accounting for a cumulative explained variance >80%) within the obtained functional maps, and the overlap between these PCA maps and canonical intrinsic brain networks (default, salience, and sensorimotor) was calculated using a null map approach.

Results

The anatomical targets used in rt-fMRI-NF and funcSurg approaches are largely distinct, with the middle cingulate cortex as a common target. Within the investigated canonical rs-fMRI networks, these approaches exhibit both divergent and overlapping functional connectivity patterns. Specifically, rt-fMRI-NF approaches primarily target the default mode network (P value range 0.001-0.002) and the salience network (P = 0.002), whereas funcSurg approaches predominantly target the salience network (P = 0.001) and the sensorimotor network (P value range 0.001-0.023).

Conclusion

Key hubs of the salience and sensorimotor networks may represent promising targets for the therapeutic application of rt-fMRI-NF in chronic pain.

Real-time fMRI neurofeedback of the anterior insula using arterial spin labelling

Arterial spin labelling (ASL) is the only non-invasive technique that allows absolute quantification of perfusion and is increasingly used in brain activation studies. Contrary to the blood oxygen level-dependent (BOLD) effect ASL measures the cerebral blood flow (CBF) directly. However, the ASL signal has a lower signal-to-noise ratio (SNR), than the BOLD signal, which constrains its utilization in neurofeedback studies. If successful, ASL neurofeedback can be used to aid in the rehabilitation of health conditions with impaired blood flow, for example, stroke. We provide the first ASL-based neurofeedback study incorporating a double-blind, sham-controlled design. A pseudo-continuous ASL (pCASL) approach with background suppression and 3D GRASE readout was combined with a real-time post-processing pipeline. The real-time pipeline allows to monitor the ASL signal and provides real-time feedback on the neural activity to the subject. In total 41 healthy adults (19-56 years) divided into three groups underwent a neurofeedback-based emotion imagery training of the left anterior insula. Two groups differing only in the explicitness level of instruction received real training and a third group received sham feedback. Only those participants receiving real feedback with explicit instruction showed significantly higher absolute CBF values in the trained region during neurofeedback than participants receiving sham feedback. However, responder analyses of percent signal change values show no differences in activation between the three groups. Persisting limitations, such as the lower SNR, confounding effects of arterial transit time and partial volume effects still impact negatively the implementation of ASL neurofeedback.

A brief real-time fNIRS-informed neurofeedback training of the prefrontal cortex changes brain activity and connectivity during subsequent working memory challenge

Working memory (WM) represents a building-block of higher cognitive functions and a wide range of mental disorders are associated with WM impairments. Initial studies have shown that several sessions of functional near-infrared spectroscopy (fNIRS) informed real-time neurofeedback (NF) allow healthy individuals to volitionally increase activity in the dorsolateral prefrontal cortex (DLPFC), a region critically involved in WM. For the translation to therapeutic or neuroenhancement applications, however, it is critical to assess whether fNIRS-NF success transfers into neural and behavioral WM enhancement in the absence of feedback. We therefore combined single-session fNIRS-NF of the left DLPFC with a randomized sham-controlled design (N = 62 participants) and a subsequent WM challenge with concomitant functional MRI. Over four runs of fNIRS-NF, the left DLPFC NF training group demonstrated enhanced neural activity in this region, reflecting successful acquisition of neural self-regulation. During the subsequent WM challenge, we observed no evidence for performance differences between the training and the sham group. Importantly, however, examination of the fMRI data revealed that - compared to the sham group - the training group exhibited significantly increased regional activity in the bilateral DLPFC and decreased left DLPFC - left anterior insula functional connectivity during the WM challenge. Exploratory analyses revealed a negative association between DLPFC activity and WM reaction times in the NF group. Together, these findings indicate that healthy individuals can learn to volitionally increase left DLPFC activity in a single training session and that the training success translates into WM-related neural activation and connectivity changes in the absence of feedback. This renders fNIRS-NF as a promising and scalable WM intervention approach that could be applied to various mental disorders.

Could neurofeedback improve therapist-patient communication? Considering the potential for neuroscience informed examinations of the psychotherapeutic relationship

Empathic communication between a patient and therapist is an essential component of psychotherapy. However, finding objective neural markers of the quality of the psychotherapeutic relationship have been elusive. Here we conceptualize how a neuroscience-informed approach involving real-time neurofeedback, facilitated via existing functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) technologies, could provide objective information for facilitating therapeutic rapport. We propose several neurofeedback-assisted psychotherapy (NF-AP) approaches that could be studied as a way to optimize the experience of the individual patient and therapist across the spectrum of psychotherapeutic treatment. Finally, we consider how the possible strengths of these approaches are balanced by their current limitations and discuss the future prospects of NF-AP.

Empathy in schizophrenia: neural alterations during emotion recognition and affective sharing

Introduction

Deficits in emotion recognition and processing are characteristic for patients with schizophrenia [SCZ].

Methods

We targeted both emotion recognition and affective sharing, one in static and one in dynamic facial stimuli, during functional magnetic resonance imaging [fMRI] in 22 SCZ patients and 22 matched healthy controls [HC]. Current symptomatology and cognitive deficits were assessed as potential influencing factors.

Results

Behaviorally, patients only showed a prolonged response time in age-discrimination trials. For emotion-processing trials, patients showed a difference in neural response, without an observable behavioral correlate. During emotion and age recognition in static stimuli, a reduced activation of the bilateral anterior cingulate cortex [ACC] and the right anterior insula [AI] emerged. In the affective sharing task, patients showed a reduced activation in the left and right caudate nucleus, right AI and inferior frontal gyrus [IFG], right cerebellum, and left thalamus, key areas of empathy.

Discussion

We conclude that patients have deficits in complex visual information processing regardless of emotional content on a behavioral level and that these deficits coincide with aberrant neural activation patterns in emotion processing networks. The right AI as an integrator of these networks plays a key role in these aberrant neural activation patterns and, thus, is a promising candidate area for neurofeedback approaches.

Enhanced attention-related alertness following right anterior insular cortex neurofeedback training

The anterior insular cortex, a central node of the salience network, plays a critical role in cognitive control and attention. Here, we investigated the feasibility of enhancing attention using real-time fMRI neurofeedback training that targets the right anterior insular cortex (rAIC). 56 healthy adults underwent two neurofeedback training sessions. The experimental group received feedback from neural responses in the rAIC, while control groups received sham feedback from the primary visual cortex or no feedback. Cognitive functioning was evaluated before, immediately after, and three months post-training. Our results showed that only the rAIC neurofeedback group successfully increased activity in the rAIC. Furthermore, this group showed enhanced attention-related alertness up to three months after the training. Our findings provide evidence for the potential of rAIC neurofeedback as a viable approach for enhancing attention-related alertness, which could pave the way for non-invasive therapeutic strategies to address conditions characterized by attention deficits.

"Listen to your heart": A novel interoceptive strategy for real-time fMRI neurofeedback training of anterior insula activity

Real-time fMRI (rt-fMRI) neurofeedback (NF) training is a novel non-invasive technique for volitional brain modulation. Given the important role of the anterior insula (AI) in human cognitive and affective processes, it has become one of the most investigated regions in rt-fMRI studies. Most rt-fMRI insula studies employed emotional recall/imagery as the regulation strategy, which may be less effective for psychiatric disorders characterized by altered emotional processing. The present study thus aimed to examine the feasibility of a novel interoceptive strategy based on heartbeat detection in rt-fMRI guided AI regulation and its associated behavioral changes using a randomized double-blind, sham feedback-controlled between-subject design. 66 participants were recruited and randomly assigned to receive either NF from the left AI (LAI) or sham feedback from a control region while using the interoceptive strategy. N = 57 participants were included in the final data analyses. Empathic and interoceptive pre-post training changes were collected as behavioral measures of NF training effects. Results showed that participants in the NF group exhibited stronger LAI activity than the control group with LAI activity being positively correlated with interoceptive accuracy following NF training, although there were no significant increases of LAI activity over training sessions. Importantly, ability of LAI regulation could be maintained in a transfer session without feedback. Successful LAI regulation was associated with strengthened functional connectivity of the LAI with cognitive control, memory and learning, and salience/interoceptive networks. The present study demonstrated for the first time the efficacy of a novel regulation strategy based on interoceptive processing in up-regulating LAI activity. Our findings also provide proof of concept for the translational potential of this strategy in rt-fMRI AI regulation of psychiatric disorders characterized by altered emotional processing.

Training volitional control of the theory of mind network with real-time fMRI neurofeedback

Is there a way improve our ability to understand the minds of others? Towards addressing this question, here, we conducted a single-arm, proof-of-concept study to evaluate whether real-time fMRI neurofeedback (rtfMRI-NF) from the temporo-parietal junction (TPJ) leads to volitional control of the neural network subserving theory of mind (ToM; the process by which we attribute and reason about the mental states of others). As additional aims, we evaluated the strategies used to self-regulate the network and whether volitional control of the ToM network was moderated by participant characteristics and associated with improved performance on behavioral measures. Sixteen participants underwent fMRI while completing a task designed to individually-localize the TPJ, and then three separate rtfMRI-NF scans during which they completed multiple runs of a training task while receiving intermittent, activation-based feedback from the TPJ, and one run of a transfer task in which no neurofeedback was provided. Region-of-interest analyses demonstrated volitional control in most regions during the training tasks and during the transfer task, although the effects were smaller in magnitude and not observed in one of the neurofeedback targets for the transfer task. Text analysis demonstrated that volitional control was most strongly associated with thinking about prior social experiences when up-regulating the neural signal. Analysis of behavioral performance and brain-behavior associations largely did not reveal behavior changes except for a positive association between volitional control in RTPJ and changes in performance on one ToM task. Exploratory analysis suggested neurofeedback-related learning occurred, although some degree of volitional control appeared to be conferred with the initial self-regulation strategy provided to participants (i.e., without the neurofeedback signal). Critical study limitations include the lack of a control group and pre-rtfMRI transfer scan, which prevents a more direct assessment of neurofeedback-induced volitional control, and a small sample size, which may have led to an overestimate and/or unreliable estimate of study effects. Nonetheless, together, this study demonstrates the feasibility of training volitional control of a social cognitive brain network, which may have important clinical applications. Given the study's limitations, findings from this study should be replicated with more robust experimental designs.

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.

The Neural Correlates of the Social Perception Dysfunction in Schizophrenia: An fMRI Study

Purpose

Patients with schizophrenia show deficits in facial emotion recognition and emotional intensity assessment, and also exhibit structural and functional irregularities in specific brain regions. In this study, we aimed to examine differences in active brain regions involved in processing the Emotion Intensity Recognition Task (EIRT), which can serve as an indicator of emotion recognition and ability to perceive intensity, between patients with schizophrenia and healthy controls (HCs). The purpose of this study was to investigate dysfunctional brain regions and investigate the role of the amygdala in social cognition deficits in patients with schizophrenia by focusing on alterations in amygdala activity linked to facial emotion recognition.

Participants and Methods

Twenty-two patients who met a diagnostic criteria for schizophrenia according to DSM-IV and 27 HCs participated in an MRI scan while completing the EIRT. Behavioral and MRI data were collected and analyzed.

Results

Behavioral results showed that patients with schizophrenia made significantly more errors in recognizing surprise, happiness, sadness, fear, and neutral expressions, and patients with schizophrenia exhibited significantly slower response times in recognizing happy facial expressions. Imaging results showed that schizophrenia patients found hypoactivation in several inferior parietal and temporal regions, in the cerebrum and anterior cingulate; and decreased amygdala activation in individuals with schizophrenia was associated with impaired recognition of fear in facial expressions.

Conclusion

Facial emotion processing deficits are emotion-specific (surprise, happiness, sadness, fear, and neutral expressions) in schizophrenia. Hypoactivation in several inferior parietal and temporal regions, in the cerebrum and anterior cingulate, was thought to contribute to symptom formation in schizophrenia. Reduction in amygdala activation in schizophrenia patients was associated with impairment of the fear-emotional process.

Neuroanatomical predictors of real‐time fMRI ‐based anterior insula regulation. A supervised machine learning study

Increasing evidence showed that learned control of metabolic activity in selected brain regions can support emotion regulation. Notably, a number of studies demonstrated that neurofeedback-based regulation of fMRI activity in several emotion-related areas leads to modifications of emotional behavior along with changes of neural activity in local and distributed networks, in both healthy individuals and individuals with emotional disorders. However, the current understanding of the neural mechanisms underlying self-regulation of the emotional brain, as well as their relationship with other emotion regulation strategies, is still limited. In this study, we attempted to delineate neuroanatomical regions mediating real-time fMRI-based emotion regulation by exploring whole brain GM and WM features predictive of self-regulation of anterior insula (AI) activity, a neuromodulation procedure that can successfully support emotional brain regulation in healthy individuals and patients. To this aim, we employed a multivariate kernel ridge regression model to assess brain volumetric features, at regional and network level, predictive of real-time fMRI-based AI regulation. Our results showed that several GM regions including fronto-occipital and medial temporal areas and the basal ganglia as well as WM regions including the fronto-occipital fasciculus, tapetum and fornix significantly predicted learned AI regulation. Remarkably, we observed a substantial contribution of the cerebellum in relation to both the most effective regulation run and average neurofeedback performance. Overall, our findings highlighted specific neurostructural features contributing to individual differences of AI-guided emotion regulation. Notably, such neuroanatomical topography partially overlaps with the neurofunctional network associated with cognitive emotion regulation strategies, suggesting common neural mechanisms.

One session of fMRI-Neurofeedback training on motor imagery modulates whole-brain effective connectivity and dynamical complexity

In the past decade, several studies have shown that Neurofeedback (NFB) by functional magnetic resonance imaging can alter the functional coupling of targeted and non-targeted areas. However, the causal mechanisms underlying these changes remain uncertain. Here, we applied a whole-brain dynamical model to estimate Effective Connectivity (EC) profiles of resting-state data acquired before and immediately after a single-session NFB training for 17 participants who underwent motor imagery NFB training and 16 healthy controls who received sham feedback. Within-group and between-group classification analyses revealed that only for the NFB group it was possible to accurately discriminate between the 2 resting-state sessions. NFB training-related signatures were reflected in a support network of direct connections between areas involved in reward processing and implicit learning, together with regions belonging to the somatomotor, control, attention, and default mode networks, identified through a recursive-feature elimination procedure. By applying a data-driven approach to explore NFB-induced changes in spatiotemporal dynamics, we demonstrated that these regions also showed decreased switching between different brain states (i.e. metastability) only following real NFB training. Overall, our findings contribute to the understanding of NFB impact on the whole brain’s structure and function by shedding light on the direct connections between brain areas affected by NFB training.

Real-Time Functional Magnetic Resonance Imaging Dyadic Neurofeedback for Emotion Regulation: A Proof-of-Concept Study

Real-time fMRI (rt-fMRI) neurofeedback can be used to non-invasively modulate brain activity and has shown initial effectiveness in symptom reduction for psychiatric disorders. Neurofeedback paradigms often target the neurocircuitry underlying emotion regulation, as difficulties with emotion regulation are common across many psychiatric conditions. Adolescence is a key period for the development of emotion regulation, with the parent-adolescent relationship providing an important context for learning how to modulate one's emotions. Here, we present evidence for a novel extension of rt-fMRI neurofeedback wherein a second person (the parent) views neurofeedback from the focal participant (adolescent) and attempts to regulate the other person's brain activity. In this proof-of-concept study, mother-adolescent dyads (n = 6; all female) participated in a dyadic neurofeedback protocol, during which they communicated via active noise-canceling microphones and headphones. During the scan, adolescents described current emotionally upsetting situations in their lives, and their mothers responded while viewing neurofeedback from the adolescent's right anterior insular cortex (aIC)-a key hub for emotion-related processing. The mother was instructed to supportively respond to her daughter's negative emotions and attempt to downregulate the aIC activity. Mean right aIC activation during each run was calculated for each adolescent participant, and results revealed a downward trend across the session (β = -0.17, SE β = 0.19, Cohen's f 2 = 0.03). Results of this proof-of-concept study support further research using dyadic neurofeedback to target emotion-related processing. Future applications may include therapist-client dyads and continued research with parents and children.

Clinical Trial Registration

[www.ClinicalTrials.gov], identifier [NCT03929263].

Intrinsic Shapes of Empathy: Functional Brain Network Topology Encodes Intersubjective Experience and Awareness Traits

Trait empathy is an essential personality feature in the intricacy of typical social inclinations of individuals. Empathy is likely supported by multilevel neuronal network functioning, whereas local topological properties determine network integrity. In the present functional MRI study (N = 116), we aimed to trace empathic traits to the intrinsic brain network architecture. Empathy was conceived as composed of two dimensions within the concept of pre-reflective, intersubjective understanding. Vicarious experience consists of the tendency to resonate with the feelings of other individuals, whereas intuitive understanding refers to a natural awareness of others’ emotional states. Analyses of graph theoretical measures of centrality showed a relationship between the fronto-parietal network and psychometric measures of vicarious experience, whereas intuitive understanding was associated with sensorimotor and subcortical networks. Salience network regions could constitute hubs for information processing underlying both dimensions. The network properties related to empathy dimensions mainly concern inter-network information flow. Moreover, interaction effects implied several sex differences in the relationship between functional network organization and trait empathy. These results reveal that distinct intrinsic topological network features explain individual differences in separate dimensions of intersubjective understanding. The findings could help understand the impact of brain damage or stimulation through alterations of empathy-related network integrity.

Aberrant functional connectivity in insular subregions in somatic depression: a resting-state fMRI study

BACKGROUND

Somatic depression (SD) is different from non-somatic depression (NSD), and insular subregions have been associated with somatic symptoms. However, the pattern of damage in the insular subregions in SD remains unclear. The aim of this study was to use functional connectivity (FC) analyses to explore the bilateral ventral anterior insula (vAI), bilateral dorsal anterior insula (dAI), and bilateral posterior insula (PI) brain circuits in SD patients.

METHODS

The study included 28 SD patients, 30 NSD patients, and 30 matched healthy control (HC) subjects. All participants underwent 3.0 T resting state functional magnetic resonance imaging. FC analyses were used to explore synchronization between insular subregions and the whole brain in the context of depression with somatic symptoms. Pearson correlation analyses were performed to assess relationships between FC values in brain regions showing significant differences and the total and factor scores on the 17-item Hamilton Rating Scale for Depression (HAMD17).

RESULTS

Compared with the NSD group, the SD group showed significantly decreased FC between the left vAI and the right rectus gyrus, right fusiform gyrus, and right angular gyrus; between the right vAI and the right middle cingulate cortex, right precuneus, and right superior frontal gyrus; between the left dAI and the left fusiform gyrus; and between the right dAI and the left postcentral gyrus. Relative to the NSD group, the SD group exhibited increased FC between the left dAI and the left fusiform gyrus. There were no differences in FC between bilateral PI and any brain regions among the SD, NSD, and HC groups. Within the SD group, FC values between the left vAI and right rectus gyrus were positively correlated with cognitive impairment scores on the HAMD17; FC values between the right vAI and right superior frontal gyrus were positively related to the total scores and cognitive impairment scores on the HAMD17 (p < 0.05, uncorrected).

CONCLUSIONS

Aberrant FC between the anterior insula and the frontal and limbic cortices may be one possible mechanism underlying SD.

Real-Time fMRI Neurofeedback Training Changes Brain Degree Centrality and Improves Sleep in Chronic Insomnia Disorder: A Resting-State fMRI Study

Background

Chronic insomnia disorder (CID) is considered a major public health problem worldwide. Therefore, innovative and effective technical methods for studying the pathogenesis and clinical comprehensive treatment of CID are urgently needed.

Methods

Real-time fMRI neurofeedback (rtfMRI-NF), a new intervention, was used to train 28 patients with CID to regulate their amygdala activity for three sessions in 6 weeks. Resting-state fMRI data were collected before and after training. Then, voxel-based degree centrality (DC) method was used to explore the effect of rtfMRI-NF training. For regions with altered DC, we determined the specific connections to other regions that most strongly contributed to altered functional networks based on DC. Furthermore, the relationships between the DC value of the altered regions and changes in clinical variables were determined.

Results

Patients with CID showed increased DC in the right postcentral gyrus, Rolandic operculum, insula, and superior parietal gyrus and decreased DC in the right supramarginal gyrus, inferior parietal gyrus, angular gyrus, middle occipital gyrus, and middle temporal gyrus. Seed-based functional connectivity analyses based on the altered DC regions showed more details about the altered functional networks. Clinical scores in Pittsburgh sleep quality index, insomnia severity index (ISI), Beck depression inventory, and Hamilton anxiety scale decreased. Furthermore, a remarkable positive correlation was found between the changed ISI score and DC values of the right insula.

Conclusions

This study confirmed that amygdala-based rtfMRI-NF training altered the intrinsic functional hubs, which reshaped the abnormal functional connections caused by insomnia and improved the sleep of patients with CID. These findings contribute to our understanding of the neurobiological mechanism of rtfMRI-NF in insomnia treatment. However, additional double-blinded controlled clinical trials with larger sample sizes need to be conducted to confirm the effect of rtfMRI-NF from this initial study.

Real-Time Functional MRI in the Treatment of Mental Health Disorders

Multiple mental disorders have been associated with dysregulation of precise brain processes. However, few therapeutic approaches can correct such specific patterns of brain activity. Since the late 1960s and early 1970s, many researchers have hoped that this feat could be achieved by closed-loop brain imaging approaches, such as neurofeedback, that aim to modulate brain activity directly. However, neurofeedback never gained mainstream acceptance in mental health, in part due to methodological considerations. In this review, we argue that, when contemporary methodological guidelines are followed, neurofeedback is one of the few intervention methods in psychology that can be assessed in double-blind placebo-controlled trials. Furthermore, using new advances in machine learning and statistics, it is now possible to target very precise patterns of brain activity for therapeutic purposes. We review the recent literature in functional magnetic resonance imaging neurofeedback and discuss current and future applications to mental health.

Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Functional Brain Connectivity During Narrative Processing Relates to Transportation and Story Influence

Engaging with narratives involves a complex array of cognitive and affective processes. These processes make stories persuasive in ways that standard arguments are not, though the underlying reasons for this remain unclear. Transportation theory proposes a potential explanation for this: narratives are processed in a way which makes individuals feel immersed in the world of a story, which in turn leads people to resonate emotionally with the events of the story. Recent fMRI studies have shown that the posterior medial cortex (PMC) and anterior insula (AI) play important roles in understanding the meaning of stories and experiencing the feelings they produce. In this study, we aimed to explore the AI’s and PMC’s role in narrative processing by measuring their functional connectivity with the rest of the brain during story listening, and how connectivity changes as a function of narrative transportation and the persuasiveness of the story. We analyzed data from 36 right-handed subjects who listened to two stories, obtained from podcasts, inside the fMRI scanner. After the scan, subjects were asked a series of questions, including a measure of how transported into the story they felt, how likely they would be to donate to causes related to the messages of the stories. We used searchlight multivariate pattern analysis (MVPA) to classify functional connectivity maps using seeds in both the AI and PMC and to compare these maps between participants who differed in transportation and prosocial intention. We found that connectivity to various regions successfully distinguished between high and low ratings on each of these behavioral measures with accuracies over 75%. However, only one pattern of connectivity was consistent across both stories: PMC-inferior frontal gyrus connectivity successfully distinguished high and low ratings of narrative transportation in both stories. All other findings were not consistent across stories. Instead, we found that patterns of connectivity may relate more to the specific content of the story rather than to a universal way in which narratives are processed.

Predictors of real-time fMRI neurofeedback performance and improvement - A machine learning mega-analysis

Real-time fMRI neurofeedback is an increasingly popular neuroimaging technique that allows an individual to gain control over his/her own brain signals, which can lead to improvements in behavior in healthy participants as well as to improvements of clinical symptoms in patient populations. However, a considerably large ratio of participants undergoing neurofeedback training do not learn to control their own brain signals and, consequently, do not benefit from neurofeedback interventions, which limits clinical efficacy of neurofeedback interventions. As neurofeedback success varies between studies and participants, it is important to identify factors that might influence neurofeedback success. Here, for the first time, we employed a big data machine learning approach to investigate the influence of 20 different design-specific (e.g. activity vs. connectivity feedback), region of interest-specific (e.g. cortical vs. subcortical) and subject-specific factors (e.g. age) on neurofeedback performance and improvement in 608 participants from 28 independent experiments. With a classification accuracy of 60% (considerably different from chance level), we identified two factors that significantly influenced neurofeedback performance: Both the inclusion of a pre-training no-feedback run before neurofeedback training and neurofeedback training of patients as compared to healthy participants were associated with better neurofeedback performance. The positive effect of pre-training no-feedback runs on neurofeedback performance might be due to the familiarization of participants with the neurofeedback setup and the mental imagery task before neurofeedback training runs. Better performance of patients as compared to healthy participants might be driven by higher motivation of patients, higher ranges for the regulation of dysfunctional brain signals, or a more extensive piloting of clinical experimental paradigms. Due to the large heterogeneity of our dataset, these findings likely generalize across neurofeedback studies, thus providing guidance for designing more efficient neurofeedback studies specifically for improving clinical neurofeedback-based interventions. To facilitate the development of data-driven recommendations for specific design details and subpopulations the field would benefit from stronger engagement in open science research practices and data sharing.

Intrinsic connectivity of the prefrontal cortex and striato-limbic system respectively differentiate major depressive from generalized anxiety disorder

Major depressive disorder (MDD) and generalized anxiety disorder (GAD) are highly prevalent and debilitating disorders. The high overlap on the symptomatic and neurobiological level led to ongoing debates about their diagnostic and neurobiological uniqueness. The present study aims to identify common and disorder-specific neuropathological mechanisms and treatment targets in MDD and GAD. To this end we combined categorical and dimensional disorder models with a fully data-driven intrinsic network-level analysis (intrinsic connectivity contrast, ICC) to resting-state fMRI data acquired in 108 individuals (n = 35 and n = 38 unmedicated patients with first-episode GAD, MDD, respectively, and n = 35 healthy controls). Convergent evidence from categorical and dimensional analyses revealed MDD-specific decreased whole-brain connectivity profiles of the medial prefrontal and dorsolateral prefrontal cortex while GAD was specifically characterized by decreased whole-brain connectivity profiles of the putamen and decreased communication of this region with the amygdala. Together, findings from the present data-driven analysis suggest that intrinsic communication of frontal regions engaged in executive functions and emotion regulation represent depression-specific neurofunctional markers and treatment targets whereas dysregulated intrinsic communication of the striato-amygdala system engaged in reinforcement-based and emotional learning processes represent GAD-specific markers.

Putamen volume predicts real-time fMRI neurofeedback learning success across paradigms and neurofeedback target regions

Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning this finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback-guided self-regulation.

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.

Rt-fMRI neurofeedback-guided cognitive reappraisal training modulates amygdala responsivity in posttraumatic stress disorder

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We found neurofeedback-specific attenuation of amygdala responses.

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Trauma symptoms and the affective state improved in patients at one-month follow-up.

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Reduced amygdala responses were associated with improved well-being at follow-up.

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75% of individuals with PTSD used the learned strategies in daily life.

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Left lateral prefrontal cortex responses were reduced during neurofeedback training.

Background

Traumatic experiences are associated with neurofunctional dysregulations in key regions of the emotion regulation circuits. In particular, amygdala responsivity to negative stimuli is exaggerated while engagement of prefrontal regulatory control regions is attenuated. Successful application of emotion regulation (ER) strategies may counteract this disbalance, however, application of learned strategies in daily life is hampered in individuals afflicted by posttraumatic stress disorder (PTSD). We hypothesized that a single session of real-time fMRI (rtfMRI) guided upregulation of prefrontal regions during an emotion regulation task enhances self-control during exposure to negative stimuli and facilitates transfer of the learned ER skills to daily life.

Methods

In a cross-over design, individuals with a PTSD diagnosis after a single traumatic event (n = 20) according to DSM-IV-TR criteria and individuals without a formal psychiatric diagnosis (n = 21) underwent a cognitive reappraisal training. In randomized order, all participants completed two rtfMRI neurofeedback (NF) runs targeting the left lateral prefrontal cortex (lPFC) and two control runs without NF (NoNF) while using cognitive reappraisal to reduce their emotional response to negative scenes. During the NoNF runs, two %%-signs were displayed instead of the two-digit feedback (FB) to achieve a comparable visual stimulation. The project aimed at defining the clinical potential of the training according to three success markers: (1) NF induced changes in left lateral prefrontal cortex and bilateral amygdala activity during the regulation of aversive scenes compared to cognitive reappraisal alone (primary registered outcome), (2) associated changes on the symptomatic and behavioral level such as indicated by PTSD symptom severity and affect ratings, (3) clinical utility such as indicated by perceived efficacy, acceptance, and transfer to daily life measured four weeks after the training.

Results

In comparison to the reappraisal without feedback, a neurofeedback-specific decrease in the left lateral PFC (d = 0.54) alongside an attenuation of amygdala responses (d = 0.33) emerged. Reduced amygdala responses during NF were associated with symptom improvement (r = −0.42) and less negative affect (r = −0.63) at follow-up. The difference in symptom scores exceeds requirements for a minimal clinically important difference and corresponds to a medium effect size (d = 0.64). Importantly, 75% of individuals with PTSD used the strategies in daily life during a one-month follow-up period and perceived the training as efficient.

Conclusion

Our findings suggest beneficial effects of the NF training indicated by reduced amygdala responses that were associated with improved symptom severity and affective state four weeks after the NF training as well as patient-centered perceived control during the training, helpfulness and application of strategies in daily life. However, reduced prefrontal involvement was unexpected. The study suggests good tolerability of the training protocol and potential for clinical use in the treatment of PTSD.

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.

Real-Time Functional Magnetic Resonance Imaging Neurofeedback for the Relief of Distressing Auditory-Verbal Hallucinations: Methodological and Empirical Advances

Auditory-verbal hallucinations (AVH) are often associated with high levels of distress and disability in individuals with schizophrenia-spectrum disorders. In around 30% of individuals with distressing AVH and diagnosed with schizophrenia, traditional antipsychotic drugs have little or no effect. Thus, it is important to develop mechanistic models of AVH to inform new treatments. Recently a small number of studies have begun to explore the use of real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) for the treatment of AVH in individuals with schizophrenia. rtfMRI-NF protocols have been developed to provide feedback about brain activation in real time to enable participants to progressively achieve voluntary control over their brain activity. We offer a conceptual review of the background and general features of neurofeedback procedures before summarizing and evaluating existing mechanistic models of AVH to identify feasible neural targets for the application of rtfMRI-NF as a potential treatment. We consider methodological issues, including the choice of localizers and practicalities in logistics when setting up neurofeedback procedures in a clinical setting. We discuss clinical considerations relating to the use of rtfMRI-NF for AVH in individuals distressed by their experiences and put forward a number of questions and recommendations about best practice. Lastly, we conclude by offering suggestions for new avenues for neurofeedback methodology and mechanistic targets in relation to the research and treatment of AVH.

Volitional Modulation of the Left DLPFC Neural Activity Based on a Pain Empathy Paradigm-A Potential Novel Therapeutic Target for Pain

The ability to perceive and feel another person' pain as if it were one's own pain, e.g., pain empathy, is related to brain activity in the "pain-matrix" network. A non-core region of this network in Dorsolateral Prefrontal Cortex (DLPFC) has been suggested as a modulator of the attentional-cognitive dimensions of pain processing in the context of pain empathy. We conducted a neurofeedback experiment using real-time functional magnetic resonance imaging (rt-fMRI-NF) to investigate the association between activity in the left DLPFC (our neurofeedback target area) and the perspective assumed by the participant ("first-person"/"Self" or "third-person"/"Other" perspective of a pain-inducing stimulus), based on a customized pain empathy task. Our main goals were to assess the participants' ability to volitionally modulate activity in their own DLPFC through an imagery task of pain empathy and to investigate into which extent this ability depends on feedback. Our results demonstrate participants' ability to significantly modulate brain activity of the neurofeedback target area for the "first-person"/"Self" and "third-person"/"Other" perspectives. Results of both perspectives show that the participants were able to modulate (with statistical significance) the activity already in the first run of the session, in spite of being naïve to the task and even in the absence of feedback information. Moreover, they improved modulation throughout the session, particularly in the "Self" perspective. These results provide new insights on the role of DLPFC in pain and pain empathy mechanisms and validate the proposed protocol, paving the way for future interventional studies in clinical populations with empathic deficits.

Mesocorticolimbic Interactions Mediate fMRI-Guided Regulation of Self-Generated Affective States

Increasing evidence shows that the generation and regulation of affective responses is associated with activity of large brain networks that also include phylogenetically older regions in the brainstem. Mesencephalic regions not only control autonomic responses but also participate in the modulation of autonomic, emotional, and motivational responses. The specific contribution of the midbrain to emotion regulation in humans remains elusive. Neuroimaging studies grounding on appraisal models of emotion emphasize a major role of prefrontal cortex in modulating emotion-related cortical and subcortical regions but usually neglect the contribution of the midbrain and other brainstem regions. Here, the role of mesolimbic and mesocortical networks in core affect generation and regulation was explored during emotion regulation guided by real-time fMRI feedback of the anterior insula activity. The fMRI and functional connectivity analysis revealed that the upper midbrain significantly contributes to emotion regulation in humans. Moreover, differential functional interactions between the dopaminergic mesocorticolimbic system and frontoparietal networks mediate up and down emotion regulatory processes. Finally, these findings further indicate the potential of real-time fMRI feedback approach in guiding core affect regulation.

A Guide to Literature Informed Decisions in the Design of Real Time fMRI Neurofeedback Studies: A Systematic Review

Background: Although biofeedback using electrophysiology has been explored extensively, the approach of using neurofeedback corresponding to hemodynamic response is a relatively young field. Real time functional magnetic resonance imaging-based neurofeedback (rt-fMRI-NF) uses sensory feedback to operantly reinforce patterns of neural response. It can be used, for example, to alter visual perception, increase brain connectivity, and reduce depression symptoms. Within recent years, interest in rt-fMRI-NF in both research and clinical contexts has expanded considerably. As such, building a consensus regarding best practices is of great value. Objective: This systematic review is designed to describe and evaluate the variations in methodology used in previous rt-fMRI-NF studies to provide recommendations for rt-fMRI-NF study designs that are mostly likely to elicit reproducible and consistent effects of neurofeedback. Methods: We conducted a database search for fMRI neurofeedback papers published prior to September 26th, 2019. Of 558 studies identified, 146 met criteria for inclusion. The following information was collected from each study: sample size and type, task used, neurofeedback calculation, regulation procedure, feedback, whether feedback was explicitly related to changing brain activity, feedback timing, control group for active neurofeedback, how many runs and sessions of neurofeedback, if a follow-up was conducted, and the results of neurofeedback training. Results: rt-fMRI-NF is typically upregulation practice based on hemodynamic response from a specific region of the brain presented using a continually updating thermometer display. Most rt-fMRI-NF studies are conducted in healthy samples and half evaluate its effect on immediate changes in behavior or affect. The most popular control group method is to provide sham signal from another region; however, many studies do not compare use a comparison group. Conclusions: We make several suggestions for designs of future rt-fMRI-NF studies. Researchers should use feedback calculation methods that consider neural response across regions (i.e., SVM or connectivity), which should be conveyed as intermittent, auditory feedback. Participants should be given explicit instructions and should be assessed on individual differences. Future rt-fMRI-NF studies should use clinical samples; effectiveness of rt-fMRI-NF should be evaluated on clinical/behavioral outcomes at follow-up time points in comparison to both a sham and no feedback control group.

Linking brain structure and activation in anterior insula cortex to explain the trait empathy for pain

The ability to perceive, understand, and react to the feelings of others' pain is referred to as empathy for pain which is composed of two components, affective‐perceptual empathy and cognitive‐evaluative empathy. Recent reviews on the neural mechanisms of empathetic pain showed the anterior insula (AI) cortex as a core circuit for empathy. However, little is known about the modulation of brain anatomy and empathic responses by trait measures of empathy (trait empathy). Thus, we investigated whether individual variation in the personality trait of empathy is associated with individual variation in the structure of specific brain regions using voxel‐based morphometry (VBM). We further investigated the relationship between the trait empathy and the activity of the same regions using state measures of empathy for pain in a trial‐by‐trial fashion in the given situation. VBM analysis indicated a small but significant negative relationship between trait empathy and gray matter volume in the bilateral AI. Functional MRI study further demonstrated that experimentally induced activity of the bilateral AI during state empathy for pain was also correlated with trait empathy. An asymmetry exists between the right and left AI between the affective and cognitive empathy. The right AI was found to be involved in the affective‐perceptual form of empathy and the left AI was active in cognitive‐evaluative forms of empathy. The interindividual differences in trait empathy may be reflected both in the state empathy and more stable brain structure difference.

Transcranial Direct Current Stimulation Modulates the Effect of Unreasonable Request in the Context of Peer Punishment

Making a request is a common occurrence during social interactions. In most social contexts, requesters may impose punishments and many behavioral studies have focused on the differential effects of reasonable and unreasonable requests during such interactions. However, few studies have explored whether reasonable or unreasonable requests involve differential neurocognitive mechanisms. In this study, we used transcranial direct current stimulation (tDCS) to investigate the mechanistic effects of request within the context of peer punishment. We used a modified ultimatum game (UG) task as well as a modified dictator game (DG) task. Both unreasonable and reasonable requests induced the proposer to increase their monetary offer for both tasks. Moreover, in the modified UG task, cathodal tDCS over the right dorsolateral prefrontal cortex (rDLPFC) significantly decreased the effect of an unreasonable request when compared to sham stimulation. Cathodal stimulation did not impact the effect of a reasonable request on the modified UG task. For the modified DG task, no tDCS effect for either an unreasonable or reasonable request was observed. These findings suggest that rDLPFC was only involved in decision-making processes during unreasonable requests when there was an opportunity for peer punishment. Moreover, our results indicate that reasonable and unreasonable requests involve differential neurocognitive mechanisms in the context of possible peer punishment.

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.

Real-Time Functional Connectivity-Informed Neurofeedback of Amygdala-Frontal Pathways Reduces Anxiety

BACKGROUND

Deficient emotion regulation and exaggerated anxiety represent a major transdiagnostic psychopathological marker. On the neural level these deficits have been closely linked to impaired, yet treatment-sensitive, prefrontal regulatory control over the amygdala. Gaining direct control over these pathways could therefore provide an innovative and promising intervention to regulate exaggerated anxiety. To this end the current proof-of-concept study evaluated the feasibility, functional relevance and maintenance of a novel connectivity-informed real-time fMRI neurofeedback training.

METHODS

In a randomized crossover sham-controlled design, 26 healthy subjects with high anxiety underwent real-time fMRI-guided neurofeedback training to enhance connectivity between the ventrolateral prefrontal cortex (vlPFC) and the amygdala (target pathway) during threat exposure. Maintenance of regulatory control was assessed after 3 days and in the absence of feedback. Training-induced changes in functional connectivity of the target pathway and anxiety ratings served as primary outcomes.

RESULTS

Training of the target, yet not the sham control, pathway significantly increased amygdala-vlPFC connectivity and decreased levels of anxiety. Stronger connectivity increases were significantly associated with higher anxiety reduction on the group level. At the follow-up, volitional control over the target pathway was maintained in the absence of feedback.

CONCLUSIONS

The present results demonstrate for the first time that successful self-regulation of amygdala-prefrontal top-down regulatory circuits may represent a novel intervention to control anxiety. As such, the present findings underscore both the critical contribution of amygdala-prefrontal circuits to emotion regulation and the therapeutic potential of connectivity-informed real-time neurofeedback.

Functional near-infrared spectroscopy-informed neurofeedback: regional-specific modulation of lateral orbitofrontal activation and cognitive flexibility

Cognitive flexibility and reward processing critically rely on the orbitofrontal cortex (OFC). Dysregulations in these domains and orbitofrontal activation have been reported in major psychiatric disorders. Hemodynamic brain imaging-informed neurofeedback allows regional-specific control over brain activation and thus may represent an innovative intervention to regulate orbitofrontal dysfunctions. Against this background the present proof-of-concept study evaluates the feasibility and behavioral relevance of functional near-infrared spectroscopy (fNIRS)-assisted neurofeedback training of the lateral orbitofrontal cortex (lOFC). In a randomized sham-controlled between-subject design, 60 healthy participants have undergone four subsequent runs of training to enhance the lOFC activation. Training-induced changes in the lOFC, attentional set-shifting performance, and reward experience have served as primary outcomes. Feedback from the target channel significantly increases the regional-specific lOFC activation over the four training runs in comparison with sham neurofeedback. The real-time OFC neurofeedback group demonstrates a trend for faster responses during the set-shifting relative to the sham neurofeedback group. Within the real-time OFC neurofeedback group, stronger training-induced lOFC increases are associated with higher reward experience. The present results demonstrate that fNIRS-informed neurofeedback allows regional-specific regulation of lOFC activation and may have the potential to modulate the associated behavioral domains. As such fNIRS-informed neurofeedback may represent a promising strategy to regulate OFC dysfunctions in psychiatric disorders.

Suppression of Sensorimotor Alpha Power Associated With Pain Expressed by an Avatar: A Preliminary EEG Study

Several studies using functional magnetic resonance imaging (fMRI) showed that empathic capabilities are associated with the activation (and deactivation) of relatively specific neural circuits. A growing number of electroencephalography studies also suggest that it might be useful to assess empathy. The main goal of this study was to use quantitative electroencephalography (qEEG) to test whether observation of pain expressed by an avatar (virtual reality) induces a suppression of alpha waves over sensorimotor cortical areas, as it is observed with human stimuli. Not only was it the case, but also the magnitude of alpha suppression was correlated with perspective-taking capacity of participants. Both empathy levels and magnitude of sensorimotor alpha suppression (SAS) were significantly higher in women than men. Interestingly, a significant interaction emerged between levels of individual empathy and specificity of experimental instructions, where SAS in participants with good perspective-taking was higher during passive observation of the distressed avatar, while the opposite was true during an active (trying to understand) condition. These results suggest that: (1) synthetic characters are able to elicit SAS; (2) SAS is indeed associated with perspective-taking capacities; (3) Persons with poorer perspective-taking capacities can show significant SAS when proper instructions are provided. Therefore, qEEG represents a low-cost objective approach to measure perspective-taking abilities.

Empathic Care and Distress: Predictive Brain Markers and Dissociable Brain Systems

Encountering another's suffering can elicit both empathic distress and empathic care-the warm desire to affiliate. It remains unclear whether these two feelings can be accurately and differentially predicted from neural activity and to what extent their neural substrates can be distinguished. We developed fMRI markers predicting moment-by-moment intensity levels of care and distress intensity while participants (n = 66) listened to true biographies describing human suffering. Both markers' predictions correlated strongly with self-report in out-of-sample participants (r = 0.59 and r = 0.63, p < 0.00001), and both markers predicted later trial-by-trial charitable donation amounts (p < 0.05). Empathic care was preferentially associated with nucleus accumbens and medial orbitofrontal cortex activity, whereas distress was preferentially associated with premotor and somatosensory cortical activity. In tests of marker specificity with an independent behavioral sample (n = 200), the empathic care marker was associated with a mixed-valence feeling state, whereas the empathic distress marker was specific to negative emotion.