Orbitofrontal cortex neurofeedback produces lasting changes in contamination anxiety and resting-state connectivity

Effects of School-Based Neurofeedback Training on Attention in Students with Autism and Intellectual Disabilities

In this study we aimed to assess the influence of school-based neurofeedback training on the attention of students with autism and intellectual disabilities. We assessed 24 students of a special education center who attended neurofeedback training sessions during the schoolyear; we also assessed 25 controls from the same center. We used two computer tasks to assess sustained attention in simple and cognitively demanding test situations, and we used a pen-and-paper task to assess selective attention. Each student who took part in the study was tested at the beginning and at the end of the schoolyear. Students from the experimental group significantly improved their performance in the task related to sustained attention to simple stimuli. No performance improvement related to neurofeedback treatment was observed in either sustained attention in cognitively demanding situations or selective attention. School-based neurofeedback training may improve sustained attention to simple stimuli in students with developmental disabilities.

A systems identification approach using Bayes factors to deconstruct the brain bases of emotion regulation

Cognitive reappraisal is fundamental to cognitive therapies and everyday emotion regulation. Analyses using Bayes factors and an axiomatic systems identification approach identified four reappraisal-related components encompassing distributed neural activity patterns across two independent functional magnetic resonance imaging (fMRI) studies (n = 182 and n = 176): (1) an anterior prefrontal system selectively involved in cognitive reappraisal; (2) a fronto-parietal-insular system engaged by both reappraisal and emotion generation, demonstrating a general role in appraisal; (3) a largely subcortical system activated during negative emotion generation but unaffected by reappraisal, including amygdala, hypothalamus and periaqueductal gray; and (4) a posterior cortical system of negative emotion-related regions downregulated by reappraisal. These systems covaried with individual differences in reappraisal success and were differentially related to neurotransmitter binding maps, implicating cannabinoid and serotonin systems in reappraisal. These findings challenge 'limbic'-centric models of reappraisal and provide new systems-level targets for assessing and enhancing emotion regulation.

Neurofeedback for alcohol addiction: Changes in resting state network activity✰

Alcohol dependence continues to be a major global burden despite significant research progress and treatment development. The aim of this study was to investigate whether neurofeedback training can alter resting state fMRI activity in brain regions that play a crucial role in addiction disorders in patients with alcohol dependence. For this purpose, a total of 52 patients were recruited for the present study, randomized, and divided into an active and a sham group. Patients in the active group received three sessions of neurofeedback training. We compared the resting state data in the active group as part of the NF training on six measurement days. When comparing the results of the active group from neurofeedback day 3 with baseline 1, a significant reduction in activated voxels in the ventral attention network area was seen. This suggests that reduced activity over the course of therapy in subjects may lead to greater independence from external stimuli. Overall, a global decrease in activated voxels within all three analysed networks compared to baseline was observed in the study. The use of resting-state data as potential biomarkers, as activity changes within these networks, may be to help restore cognitive processes and alcohol abuse-related craving and emotions.

Amygdala-related electroencephalogram neurofeedback as add-on therapy for treatment-resistant childhood sexual abuse posttraumatic stress disorder: feasibility study

AIM

Childhood sexual abuse (CSA) among women is an alarmingly prevalent traumatic experience that often leads to debilitating and treatment-refractory posttraumatic stress disorder (PTSD), raising the need for novel adjunctive therapies. Neuroimaging investigations systematically report that amygdala hyperactivity is the most consistent and reliable neural abnormality in PTSD and following childhood abuse, raising the potential of implementing volitional neural modulation using neurofeedback (NF) aimed at down-regulating amygdala activity. This study aimed to reliably probe limbic activity but overcome the limited applicability of functional magnetic resonance imaging (fMRI) NF by using a scalable electroencephalogram NF probe of amygdala-related activity, termed amygdala electrical-finger-print (amyg-EFP) in a randomized controlled trial.

METHOD

Fifty-five women with CSA-PTSD who were in ongoing intensive trauma-focused psychotherapy for a minimum of 1 year but still met Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) PTSD criteria were randomized to either 10 add-on sessions of amyg-EFP-NF training (test group) or continuing psychotherapy (control group). Participants were blindly assessed for PTSD symptoms before and after the NF training period, followed by self-reported clinical follow-up at 1, 3, and 6 months, as well as one session of amygdala real-time fMRI-NF before and after NF training period.

RESULTS

Participants in the test group compared with the control group demonstrated a marginally significant immediate reduction in PTSD symptoms, which progressively improved during the follow-up period. In addition, successful neuromodulation during NF training was demonstrated.

CONCLUSION

This feasibility study for patients with treatment-resistant CSA-PTSD indicates that amyg-EFP-NF is a viable and efficient intervention.

Protocol description for a randomized controlled trial of fMRI neurofeedback for tics in adolescents with Tourette Syndrome

This article describes the protocol for a randomized, controlled clinical trial of a neurofeedback (NF) intervention for Tourette Syndrome (TS) and chronic tic disorder. The intervention involves using functional magnetic resonance imaging (fMRI) to provide feedback regarding activity in the supplementary motor area: participants practice controlling this brain area while using the feedback as a training signal. The previous version of this NF protocol was tested in a small study (n = 21) training adolescents with TS that yielded clinically promising results. Therefore, we plan a larger trial. Here we describe the background literature that motivated this work, the design of our original neurofeedback study protocol, and adaptations of the research study protocol for the new trial. We focus on those ideas incorporated into our protocol that may be of interest to others designing and running NF studies. For example, we highlight our approach for defining an unrelated brain region to be trained in the control group that is based on identifying a region with low functional connectivity to the target area. Consistent with a desire for transparency and open science, the new protocol is described in detail here prior to conducting the trial.

Multi-voxel neuro-reinforcement changes resting-state functional connectivity: A pilot study

Background

Multi-voxel neuro-reinforcement has been shown to selectively reduce amygdala reactivity in response to feared stimuli, but the precise mechanisms supporting these effects are still unknown. The current pilot study seeks to identify potential intermediaries of change using functional brain connectivity at rest.

Methods

Individuals (N = 11) diagnosed with at least two animal subtype specific phobias took part in a double-blind multi-voxel neuro-reinforcement clinical trial targeting one of two phobic animals, with the untargeted animal as placebo control. Changes in whole-brain resting state functional connectivity from pre-treatment to post-treatment were measured using group ICA. These changes were tested to see if they predicted the previously observed decreases in amygdala reactivity in response to images of target phobic animals.

Results

A common functional connectivity network overlapping with the visual network was identified in resting state data pre-treatment and post-treatment. Significant increases in functional connectivity in this network from pre-treatment to post-treatment were found in higher level visual and cognitive processing regions of the brain. Increases in functional connectivity in these regions also significantly predicted decreases in task-based amygdala reactivity to targeted phobic animals following multi-voxel neuro-reinforcement. Specifically, greater increases of functional connectivity pre-treatment to post-treatment were associated with greater decreases of amygdala reactivity to target phobic stimuli pre-treatment to post-treatment.

Conclusions

These findings provide preliminary evidence that multi-voxel neuro-reinforcement can induce persisting functional connectivity changes in the brain. Moreover, these changes in functional connectivity were not limited to the direct area of neuro-reinforcement, suggesting neuro-reinforcement may change how the targeted region interacts with other brain regions. Identification of these brain regions represent a first step towards explaining the underlying mechanisms of change in previous multi-voxel neuro-reinforcement studies. Future research should seek to replicate these effects in a larger sample size to further assess their role in the effects observed from multi-voxel neuro-reinforcement.

Emotional intelligence mediates the protective role of the orbitofrontal cortex spontaneous activity measured by fALFF against depressive and anxious symptoms in late adolescence

As a stable personality construct, trait emotional intelligence (TEI) refers to a battery of perceived emotion-related skills that make individuals behave effectively to adapt to the environment and maintain well-being. Abundant evidence has consistently shown that TEI is important for the outcomes of many mental health issues, particularly depression and anxiety. However, the neural substrates involved in TEI and the underlying neurobehavioral mechanism of how TEI reduces depression and anxiety symptoms remain largely unknown. Herein, resting-state functional magnetic resonance imaging and a group of behavioral measures were applied to examine these questions among a large sample comprising 231 general adolescent students aged 16-20 years (52% female). Whole-brain correlation analysis and prediction analysis demonstrated that TEI was negatively linked with spontaneous activity (measured with the fractional amplitude of low-frequency fluctuations) in the bilateral medial orbitofrontal cortex (OFC), a critical site implicated in emotion-related processes. Furthermore, structural equation modeling analysis found that TEI mediated the link of OFC spontaneous activity to depressive and anxious symptoms. Collectively, the current findings present new evidence for the neurofunctional bases of TEI and suggest a potential "brain-personality-symptom" pathway for alleviating depressive and anxious symptoms among students in late adolescence.

Preliminary findings on long-term effects of fMRI neurofeedback training on functional networks involved in sustained attention

INTRODUCTION

Neurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up-regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long-term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long-term learning effects of neurofeedback training remain under-explored.

METHODS

Here, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self-regulation runs without feedback (i.e., transfer runs) and during resting-state runs from 15 healthy individuals.

RESULTS

Neurally, we found that participants maintained their ability to control the differential activity during follow-up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow-up transfer runs but not during follow-up resting-state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow-up.

CONCLUSION

The discrepancy between lasting regulation-related brain changes but transient behavioral and resting-state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain-behavior associations during and after neurofeedback training is needed to develop its full potential as a promising scientific and clinical tool.

Neurofeedback for obsessive compulsive disorder: A randomized, double-blind trial

We aim to develop fMRI neurofeedback as a treatment for obsessive compulsive disorder (OCD). In prior work, we found that providing neurofeedback of activity in the anterior prefrontal cortex (aPFC) improved control over contamination anxiety in a subclinical population. Here, we present the results of a randomized, double-blind clinical trial (NCT02206945) testing this intervention in patients with OCD. We recruited patients with primary symptoms in the fear-of-harm/checking or contamination/washing domains. During neurofeedback, they viewed symptom provocative images and attempted to up- and down-regulate the aPFC during different blocks of time. The active group received two sessions of neurofeedback and the control group received yoked sham feedback. The primary outcome measure was the Yale-Brown Obsessive-Compulsive Symptom scale. The secondary outcome was control over aPFC. Thirty-six participants completed feedback training (18 active, 18 control). The active group had a slightly but significantly greater reduction of obsessive-compulsive symptoms after neurofeedback compared to the control group (p<.05) but no significant differences in control over the aPFC. These data demonstrate that neurofeedback targeting the aPFC can reduce symptoms in OCD. Future investigations should seek to optimize the training protocol to yield larger effects and to clarify the mechanism of action.

HALO: A software tool for real-time head alignment in the MR scanner

PURPOSE

MRI studies in human subjects often require multiple scanning sessions/visits. Changes in a subject's head position across sessions result in different alignment between brain tissues and the magnetic field which leads to changes in magnetic susceptibility. These changes can have considerable impacts on acquired signals. Head ALignment Optimization (HALO), a software tool was developed by the authors for active head alignment between sessions.

METHODS

HALO provides real-time visual feedback of a subject's current head position relative to the position in a previous session. The tool was evaluated in a pilot sample of seven healthy human subjects.

RESULTS

HALO was shown to enable subjects to actively align their head positions to the desired position of their initial sessions. The subjects were able to improve their head alignment significantly using HALO and achieved good alignment with their first session meeting stringent criteria similar to that used for within-run head motion (less than 2 mm translation or 2 degrees rotation in any direction from the desired position). Moreover, we found a negative correlation between the post-alignment rotation and similarity in inter-session BOLD patterns around the air-tissue interface near sinus which further highlighted the impact of tissue-field alignment on BOLD data quality.

CONCLUSION

Utilization of HALO in longitudinal studies may help to improve data quality by ensuring the consistency of susceptibility gradients in brain tissues across sessions. HALO has been made publicly available.

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.

Difference analysis of multidimensional electroencephalogram characteristics between young and old patients with generalized anxiety disorder

Growing evidences indicate that age plays an important role in the development of mental disorders, but few studies focus on the neuro mechanisms of generalized anxiety disorder (GAD) in different age groups. Therefore, this study attempts to reveal the neurodynamics of Young_GAD (patients with GAD under the age of 50) and Old_GAD (patients with GAD over 50 years old) through statistical analysis of multidimensional electroencephalogram (EEG) features and machine learning models. In this study, 10-min resting-state EEG data were collected from 45 Old_GAD and 33 Young_GAD. And multidimensional EEG features were extracted, including absolute power (AP), fuzzy entropy (FE), and phase-lag-index (PLI), on which comparison and analyses were performed later. The results showed that Old_GAD exhibited higher power spectral density (PSD) value and FE value in beta rhythm compared to theta, alpha1, and alpha2 rhythms, and functional connectivity (FC) also demonstrated significant reorganization of brain function in beta rhythm. In addition, the accuracy of machine learning classification between Old_GAD and Young_GAD was 99.67%, further proving the feasibility of classifying GAD patients by age. The above findings provide an objective basis in the field of EEG for the age-specific diagnosis and treatment of GAD.

Subjective Improvement of Sleep in Insomnia Patients Treated at a Day Rehabilitation Centre After the Use of EEG Neurofeedback Therapy – a Pilot Study

Introduction: Insomnia affects nearly 1/3 of the worldwide population. Electroencephalography neurofeedback (EEG-NFB) is one of the methods used in applied psychophysiology, which can improve nightly sleep scheme. Research objective: The aim of this pilot study was to assess the relative effect of a 20-day neurorehabilitation intervention based on EEG-NFB therapy in insomnia patients treated at a day rehabilitation centre. Materials and methods: Seventy-four patients with insomnia: 28 women (mean age ± SD: 67.9 ± 8.84 years, range: 42–83 years) and 46 men (mean age ± SD: 63.0 ± 9.24 years, range: 42-80 years) were subjected to the EEG-NFB training-neurorehabilitation using the C4 protocol: sensorimotor rhythm (SMR) (12-15 Hz)/theta (4-7 Hz). The individual everyday EEG-NFB training consisted of 20, 30-minute sessions. Before and after the training, the data was collected from 12-electrode quantitative EEG (QEEG) tests. In addition, several standardised psychological questionnaires were performed: Pittsburgh Sleep Quality Index (PSQI), State-Trait Anxiety Inventory (STAI) and Beck Depression Inventory (BDI). Results: The EEG-NFB therapy reduced anxiety (7.39 ± 1.0 vs. 6.12 ± 0.88 in STAI, p< 0.001) and improved patients' mood (17.6 ± 3.9 vs. 14.65 ± 3.39 in BDI, p< 0.001). During the PSQI test, the time of falling asleep and number of night awakenings were statistically reduced (both p<0.001). However, there was no significant difference in the -SMR amplitude between pre- to post-treatment (9.15 ± 3.11 and 8.62 ± 2.82, respectively, p=0.095). Conclusions: Due to the subjective improvement of sleep quality, without statistically significant changes in the electrophysiological record (expressed by SMR amplitude), it is advisable to continue research with the use of EEG-NFB therapy.

Frontostriatal circuitry as a target for fMRI-based neurofeedback interventions: A systematic review

Dysregulated frontostriatal circuitries are viewed as a common target for the treatment of aberrant behaviors in various psychiatric and neurological disorders. Accordingly, experimental neurofeedback paradigms have been applied to modify the frontostriatal circuitry. The human frontostriatal circuitry is topographically and functionally organized into the “limbic,” the “associative,” and the “motor” subsystems underlying a variety of affective, cognitive, and motor functions. We conducted a systematic review of the literature regarding functional magnetic resonance imaging-based neurofeedback studies that targeted brain activations within the frontostriatal circuitry. Seventy-nine published studies were included in our survey. We assessed the efficacy of these studies in terms of imaging findings of neurofeedback intervention as well as behavioral and clinical outcomes. Furthermore, we evaluated whether the neurofeedback targets of the studies could be assigned to the identifiable frontostriatal subsystems. The majority of studies that targeted frontostriatal circuitry functions focused on the anterior cingulate cortex, the dorsolateral prefrontal cortex, and the supplementary motor area. Only a few studies (n = 14) targeted the connectivity of the frontostriatal regions. However, post-hoc analyses of connectivity changes were reported in more cases (n = 32). Neurofeedback has been frequently used to modify brain activations within the frontostriatal circuitry. Given the regulatory mechanisms within the closed loop of the frontostriatal circuitry, the connectivity-based neurofeedback paradigms should be primarily considered for modifications of this system. The anatomical and functional organization of the frontostriatal system needs to be considered in decisions pertaining to the neurofeedback targets.

Doubting the double-blind: Introducing a questionnaire for awareness of experimental purposes in neurofeedback studies

Double-blinding subjects to the experiment's purpose is an important standard in neurofeedback studies. However, it is difficult to provide evidence that humans are entirely unaware of certain information. This study used insights from consciousness studies and neurophenomenology to develop a contingency awareness questionnaire for neurofeedback. We assessed whether participants had an awareness of experimental purposes to manipulate their attention and multisensory perception. A subset of subjects (5 out of 20) gained a degree of awareness of experimental purposes as evidenced by their correct guess about the purposes of the experiment to affect their attention and multisensory perceptions specific to their double-blinded group assignment. The results warrant replication before they are applied to clinical neurofeedback studies, given the considerable time taken to perform the questionnaire (∼25 min). We discuss the strengths and limitations of our contingency awareness questionnaire and the growing appeal of the double-blinded standard in clinical neurofeedback studies.

Abnormal Insular Dynamic Functional Connectivity and Its Relation to Social Dysfunctioning in Children With Attention Deficit/Hyperactivity Disorder

Anomalies in large-scale cognitive control networks impacting social attention abilities are hypothesized to be the cause of attention deficit hyperactivity disorder (ADHD). The precise nature of abnormal brain functional connectivity (FC) dynamics including other regions, on the other hand, is unknown. The concept that insular dynamic FC (dFC) among distinct brain regions is dysregulated in children with ADHD was evaluated using Insular subregions, and we studied how these dysregulations lead to social dysfunctioning. Data from 30 children with ADHD and 28 healthy controls (HCs) were evaluated using dynamic resting state functional magnetic resonance imaging (rs-fMRI). We evaluated the dFC within six subdivisions, namely both left and right dorsal anterior insula (dAI), ventral anterior insula (vAI), and posterior insula (PI). Using the insular sub-regions as seeds, we performed group comparison between the two groups. To do so, two sample t-tests were used, followed by post-hoc t-tests. Compared to the HCs, patients with ADHD exhibited decreased dFC values between right dAI and the left middle frontal gyrus, left postcentral gyrus and right of cerebellum crus, respectively. Results also showed a decreased dFC between left dAI and thalamus, left vAI and left precuneus and left PI with temporal pole. From the standpoint of the dynamic functional connectivity of insular subregions, our findings add to the growing body of evidence on brain dysfunction in ADHD. This research adds to our understanding of the neurocognitive mechanisms behind social functioning deficits in ADHD. Future ADHD research could benefit from merging the dFC approach with task-related fMRI and non-invasive brain stimulation, which could aid in the diagnosis and treatment of the disorder.

Neurofeedback training: Decreases in Mu rhythm lead to improved motor performance in complex visuomotor skills

The physiological function of the Mu rhythm (8-13 Hz in the central region) is still unclear, particularly its role in visuomotor performance in sports (shooting vs. golf putting), as both the complexity of the motor skills (i.e., simple vs. complex visuomotor skills) and the skill level (e.g., novices vs. experts or low-skilled vs. highly skilled) may modulate Mu rhythm. To gain a broader understanding of the association between Mu rhythm and visuomotor skill performance, a study design that considers both a control moderator (the difference in skill level) and the ability to manipulate Mu rhythm (i.e., either increase or decrease Mu rhythm) is required. To achieve this, we recruited 30 novice golfers who were randomly assigned to either the increased Mu rhythm group (IMG), decreased Mu rhythm group (DMG), or sham group (SG) and used electroencephalographic-neurofeedback training (EEG-NFT) to manipulate Mu rhythm during a golf putting task (complex visuomotor skill). The aim was to determine whether the complexity of the motor skill was a potential moderator of Mu rhythm. We mainly found that Mu power was significantly decreased in the DMG following EEG-NFT, which lead to increased motor control and improved performance. We suggest that (1) the complexity of the motor skill, rather than the difference in skill level, may be a potential moderator of Mu rhythm and visuomotor performance, as our results were not consistent with a previous study that reported that increased Mu rhythm improved shooting performance (a simple visuomotor task) in novices.

Depressive symptoms reduce when dorsolateral prefrontal cortex-precuneus connectivity normalizes after functional connectivity neurofeedback

Depressive disorders contribute heavily to global disease burden; This is possibly because patients are often treated homogeneously, despite having heterogeneous symptoms with differing underlying neural mechanisms. A novel treatment that can directly influence the neural circuit relevant to an individual patient's subset of symptoms might more precisely and thus effectively aid in the alleviation of their specific symptoms. We tested this hypothesis in a proof-of-concept study using fMRI functional connectivity neurofeedback. We targeted connectivity between the left dorsolateral prefrontal cortex/middle frontal gyrus and the left precuneus/posterior cingulate cortex, because this connection has been well-established as relating to a specific subset of depressive symptoms. Specifically, this connectivity has been shown in a data-driven manner to be less anticorrelated in patients with melancholic depression than in healthy controls. Furthermore, a posterior cingulate dominant state-which results in a loss of this anticorrelation-is expected to specifically relate to an increase in rumination symptoms such as brooding. In line with predictions, we found that, with neurofeedback training, the more a participant normalized this connectivity (restored the anticorrelation), the more related (depressive and brooding symptoms), but not unrelated (trait anxiety), symptoms were reduced. Because these results look promising, this paradigm next needs to be examined with a greater sample size and with better controls. Nonetheless, here we provide preliminary evidence for a correlation between the normalization of a neural network and a reduction in related symptoms. Showing their reproducibility, these results were found in two experiments that took place several years apart by different experimenters. Indicative of its potential clinical utility, effects of this treatment remained one-two months later.Clinical trial registration: Both experiments reported here were registered clinical trials (UMIN000015249, jRCTs052180169).

Feasibility of training the dorsolateral prefrontal-striatal network by real-time fMRI neurofeedback

Real-time fMRI neurofeedback (rt-fMRI NF) is a promising non-invasive technique that enables volitional control of usually covert brain processes. While most rt-fMRI NF studies so far have demonstrated the ability of the method to evoke changes in brain activity and improve symptoms of mental disorders, a recently evolving field is network-based functional connectivity (FC) rt-fMRI NF. However, FC rt-fMRI NF has methodological challenges such as respirational artefacts that could potentially bias the training if not controlled. In this randomized, double-blind, yoke-controlled, pre-registered FC rt-fMRI NF study with healthy participants (N = 40) studied over three training days, we tested the feasibility of an FC rt-fMRI NF approach with online global signal regression (GSR) to control for physiological artefacts for up-regulation of connectivity in the dorsolateral prefrontal-striatal network. While our pre-registered null hypothesis significance tests failed to reach criterion, we estimated the FC training effect at a medium effect size at the end of the third training day after rigorous control of physiological artefacts in the offline data. This hints at the potential of FC rt-fMRI NF for the development of innovative transdiagnostic circuit-specific interventional approaches for mental disorders and the effect should now be confirmed in a well-powered 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.

Progressive modulation of resting-state brain activity during neurofeedback of positive-social emotion regulation networks

Neurofeedback allows for the self-regulation of brain circuits implicated in specific maladaptive behaviors, leading to persistent changes in brain activity and connectivity. Positive-social emotion regulation neurofeedback enhances emotion regulation capabilities, which is critical for reducing the severity of various psychiatric disorders. Training dorsomedial prefrontal cortex (dmPFC) to exert a top-down influence on bilateral amygdala during positive-social emotion regulation progressively (linearly) modulates connectivity within the trained network and induces positive mood. However, the processes during rest that interleave the neurofeedback training remain poorly understood. We hypothesized that short resting periods at the end of training sessions of positive-social emotion regulation neurofeedback would show alterations within emotion regulation and neurofeedback learning networks. We used complementary model-based and data-driven approaches to assess how resting-state connectivity relates to neurofeedback changes at the end of training sessions. In the experimental group, we found lower progressive dmPFC self-inhibition and an increase of connectivity in networks engaged in emotion regulation, neurofeedback learning, visuospatial processing, and memory. Our findings highlight a large-scale synergy between neurofeedback and resting-state brain activity and connectivity changes within the target network and beyond. This work contributes to our understanding of concomitant learning mechanisms post training and facilitates development of efficient neurofeedback training.

Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder

An important challenge in mental health research is to translate findings from cognitive neuroscience and neuroimaging research into effective treatments that target the neurobiological alterations involved in psychiatric symptoms. To address this challenge, in this review we propose a heuristic neurocircuit-based taxonomy to guide the treatment of obsessive-compulsive disorder (OCD). We do this by integrating information from several sources. First, we provide case vignettes in which patients with OCD describe their symptoms and discuss different clinical profiles in the phenotypic expression of the condition. Second, we link variations in these clinical profiles to underlying neurocircuit dysfunctions, drawing on findings from neuropsychological and neuroimaging studies in OCD. Third, we consider behavioral, pharmacological, and neuromodulatory treatments that could target those specific neurocircuit dysfunctions. Finally, we suggest methods of testing this neurocircuit-based taxonomy as well as important limitations to this approach that should be considered in future research.

Matched neurofeedback during fMRI differentially activates reward-related circuits in active and sham groups

BACKGROUND AND PURPOSE

Functional MRI neurofeedback (fMRI-nf) leverages the brain's ability to self-regulate its own activity. However, self-regulation processes engaged during fMRI-nf are incompletely understood. Here, we used matched feedback in an fMRI-nf experimental protocol to investigate whether brain processes recognize true neurofeedback signals.

METHODS

We implemented an existing fMRI-nf protocol to train lateralized motor activity using a finger-tap task in conjunction with real-time feedback. Twelve healthy, right-handed, adult participants were assigned into age- and sex-matched active and sham study groups. Matched participant pairs received the same visual feedback, based on brain activity of the participant from the active group. We compared group-averaged activation maps before, during, and after neurofeedback, and analyzed changes in lateralized motor activity due to neurofeedback.

RESULTS

Active and sham groups demonstrated different brain activation to the same feedback during neurofeedback. In particular, there was higher activation in visual cortex, secondary somatosensory cortex, and right inferior frontal gyrus in the active group compared to the sham group. Conversely, sham participants demonstrated higher activation in anterior cingulate cortex, left frontal pole, and posterior superior temporal gyrus. Despite differing brain activations during neurofeedback, neither group demonstrated significant improvement in lateralized motor activity from pre to postfeedback scan in the same session. We also observed no significant difference between pre and postfeedback activation maps, suggesting that no significant finger-tap related functional reorganization had occurred.

CONCLUSIONS

These findings suggest that fMRI neurofeedback paradigms that monitor or incorporate activity from regions reported here would provide enhanced efficacy for research investigation and clinical intervention.

Affective Neurofeedback Under Naturalistic Conditions: A Mini-Review of Current Achievements and Open Challenges

Affective neurofeedback training allows for the self-regulation of the putative circuits of emotion regulation. This approach has recently been studied as a possible additional treatment for psychiatric disorders, presenting positive effects in symptoms and behaviors. After neurofeedback training, a critical aspect is the transference of the learned self-regulation strategies to outside the laboratory and how to continue reinforcing these strategies in non-controlled environments. In this mini-review, we discuss the current achievements of affective neurofeedback under naturalistic setups. For this, we first provide a brief overview of the state-of-the-art for affective neurofeedback protocols. We then discuss virtual reality as a transitional step toward the final goal of "in-the-wild" protocols and current advances using mobile neurotechnology. Finally, we provide a discussion of open challenges for affective neurofeedback protocols in-the-wild, including topics such as convenience and reliability, environmental effects in attention and workload, among others.

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

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

[The contribution of orbitofrontal cortex to stress-related psychiatric disorders: stress induced synaptic change in the orbitofrontal-basolateral amygdala pathway]

Exposure to stress induces alterations in synaptic functions, and increases the risk of stress-related psychiatric disorders, such as major depression and PTSD. To develop new treatments for stress-related psychiatric disorders, it is important to understand the effect of stress on the emotional circuits, such as prefrontal cortex (PFC), amygdala and other limbic regions. The orbitofrontal cortex (OFC, ventral subregion of the PFC) has important roles for processing of negative emotion and has recently been highlighted as a critical region in stress-related psychiatric disorders. However, mechanisms how stress affect OFC circuit and induce psychiatric symptoms were less understood. OFC sends dense projection to the amygdala, which is one of the key nodes for processing of negative emotion. Taken together, there is a possibility that stress affects the information processing in the OFC-amygdala pathway, and it underlies stress-induced emotional alteration. In this article, we introduce our research that examined effects of stress on the excitatory synaptic transmission from OFC to the basolateral nucleus of the amygdala (BLA) using optogenetic and whole-cell patch-clamp methods in mice.

Neurofeedback training improves anxiety trait and depressive symptom in GAD

OBJECTIVE

To investigate the effectiveness of alpha activity neurofeedback training over the parietal lobe in GAD patients.

METHODS

Twenty-six female patients who had been diagnosed as GAD according to the Diagnostic and Statistical Manual of Mental Disorders (5th edition, DSM-V) criteria were included in this study. Patients were randomized into two groups: the left parietal lobe training group (LPL group, n = 13) and the right parietal lobe training group (RPL group, n = 13), and then received ten 40-minute alpha training sessions in the relevant area. Evaluations included severity of anxiety (by State-Trait Anxiety Inventory, STAI) and depression (by Beck Depression Inventory, BDI-II) after the fifth training session and the last training session.

RESULTS

The scores of STAI-S decreased significantly two weeks after the fifth training session in both groups (LPL group: from 47.15 ± 10.65 to 38.69 ± 8.78, p<.05; RPL group: from 44.92 ± 12.37 to 37.31 ± 6.41, p < .05) and decreased further at the four weeks' time point after the last training session (LPL group: 35.15 ± 9.24; RPL group: 29.85 ± 6.18). Compared with baseline, the scores of STAI-T, BDI-II and ISI decrease at two weeks, no significant difference found between LPL group and RPL group. The scores of STAI-T, BDI-II and ISI decreased at four weeks when compared with two weeks, and no significant difference found between LPL group and RPL group.

CONCLUSION

Neurofeedback training of alpha activity over the parietal lobe is effective in GAD patients, especially the anxiety trait and depressive symptoms.

Neurofeedback training in major depressive disorder: A systematic review of clinical efficacy, study quality and reporting practices

Major depressive disorder (MDD) is the leading cause of disability worldwide. Neurofeedback training has been suggested as a potential additional treatment option for MDD patients not reaching remission from standard care (i.e., psychopharmacology and psychotherapy). Here we systematically reviewed neurofeedback studies employing electroencephalography, or functional magnetic resonance-based protocols in depressive patients. Of 585 initially screened studies, 24 were included in our final sample (N = 480 patients in experimental and N = 194 in the control groups completing the primary endpoint). We evaluated the clinical efficacy across studies and attempted to group studies according to the control condition categories currently used in the field that affect clinical outcomes in group comparisons. In most studies, MDD patients showed symptom improvement superior to the control group(s). However, most articles did not comply with the most stringent study quality and reporting practices. We conclude with recommendations on best practices for experimental designs and reporting standards for neurofeedback training.

Targeting hippocampal hyperactivity with real-time fMRI neurofeedback: protocol of a single-blind randomized controlled trial in mild cognitive impairment

BACKGROUND

Several fMRI studies found hyperactivity in the hippocampus during pattern separation tasks in patients with Mild Cognitive Impairment (MCI; a prodromal stage of Alzheimer's disease). This was associated with memory deficits, subsequent cognitive decline, and faster clinical progression. A reduction of hippocampal hyperactivity with an antiepileptic drug improved memory performance. Pharmacological interventions, however, entail the risk of side effects. An alternative approach may be real-time fMRI neurofeedback, during which individuals learn to control region-specific brain activity. In the current project we aim to test the potential of neurofeedback to reduce hippocampal hyperactivity and thereby improve memory performance.

METHODS

In a single-blind parallel-group study, we will randomize n = 84 individuals (n = 42 patients with MCI, n = 42 healthy elderly volunteers) to one of two groups receiving feedback from either the hippocampus or a functionally independent region. Percent signal change of the hemodynamic response within the respective target region will be displayed to the participant with a thermometer icon. We hypothesize that only feedback from the hippocampus will decrease hippocampal hyperactivity during pattern separation and thereby improve memory performance.

DISCUSSION

Results of this study will reveal whether real-time fMRI neurofeedback is able to reduce hippocampal hyperactivity and thereby improve memory performance. In addition, the results of this study may identify predictors of successful neurofeedback as well as the most successful regulation strategies.

TRIAL REGISTRATION

The study has been registered with clinicaltrials.gov on the 16th of July 2019 (trial identifier: NCT04020744 ).

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.

A systematic review of fMRI neurofeedback reporting and effects in clinical populations

Real-time fMRI-based neurofeedback is a relatively young field with a potential to impact the currently available treatments of various disorders. In order to evaluate the evidence of clinical benefits and investigate how consistently studies report their methods and results, an exhaustive search of fMRI neurofeedback studies in clinical populations was performed. Reporting was evaluated using a limited number of Consensus on the reporting and experimental design of clinical and cognitive-behavioral neurofeedback studies (CRED-NF checklist) items, which was, together with a statistical power and sensitivity calculation, used to also evaluate the existing evidence of the neurofeedback benefits on clinical measures. The 62 found studies investigated regulation abilities and/or clinical benefits in a wide range of disorders, but with small sample sizes and were therefore unable to detect small effects. Most points from the CRED-NF checklist were adequately reported by the majority of the studies, but some improvements are suggested for the reporting of group comparisons and relations between regulation success and clinical benefits. To establish fMRI neurofeedback as a clinical tool, more emphasis should be placed in the future on using larger sample sizes determined through a priori power calculations and standardization of procedures and reporting.

Training the anxious brain: using fMRI-based neurofeedback to change brain activity in adolescence

Anxiety disorders are a leading cause of morbidity and entail a lot of costs. Adolescence is characterized by social fears and poor emotion regulation abilities which together increase the likelihood of the emergence of anxiety disorders. This emotion dysregulation is potentially caused by the emotion regulating brain areas, such as the prefrontal cortex and temporal cortex, that are still undergoing developmental changes throughout late adolescence. Recently, new approaches have used functional magnetic resonance imaging-based neurofeedback to help participants gain control over emotion regulation brain networks by receiving real-time feedback on their brain activity and to use effective emotion regulation abilities. In this review, we provide an overview of the developmental changes in the brain and the corresponding behavioural changes, and explore how these can be influenced during adolescence using neurofeedback. We conclude that recent studies show promising results that children and adolescents can self-regulate emotion regulation brain networks thereby supporting the development of effective emotion regulation abilities. WHAT THIS PAPER ADDS: Functional magnetic resonance imaging-based neurofeedback can be used for brain self-regulation in development. The emotion regulation networks play a key role in treating social anxiety with neurofeedback.

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.

Advances in biofeedback and neurofeedback studies on smoking

Smoking is a leading cause of morbidity and premature death constituting a global health challenge. Although, pharmacological and behavioral approaches comprise the mainstay of smoking cessation interventions, the efficacy and safety of pharmacotherapy is not demonstrated for some populations. Non-pharmacological approaches, such as biofeedback (BF) and neurofeedback (NF) could facilitate self-regulation of predisposing factors of relapse such as craving and stress. The current review aims to aggregate the existing evidence regarding the effects of BF and NF training on smokers. Relevant studies were identified through searching in Scopus, PubMed and Cochrane Library, and through hand-searching the references of screened articles. Peer-reviewed controlled and uncontrolled studies, where BF and/or NF training was administered, were included and evaluated according to PICOS framework. Narrative qualitative synthesis of ten eligible studies was performed, aggregated into three categories according to training provided. BF outcomes seem to be affected by smoking behavior prior to training; individualized EEG NF training holds promise for modulating craving-related response while minimizing the required number of sessions. Real-time fMRI NF studies concluded that nicotine-dependent individuals could modulate craving-related brain responses, while mixed results were revealed regarding smokers' ability to modulate brain responses related to resistance towards the urge to smoke. BF and NF training seem to facilitate modulation of autonomous and/or central nervous system activity while also transferring this learned self-regulation to behavioral outcomes. BF and NF training should a) address remaining issues on specificity and scientific validity, b) target diverse demographics, and c) produce robust reproducible methodologies and clinical guidelines for relevant health care providers, in order to be considered as viable complementary tools to standard smoking cessation care.

Identification of a brain fingerprint for overweight and obesity

The brain plays a central role in the pathophysiology of overweight and obesity. Connectome-based Predictive Modeling (CPM) is a newly developed, data-driven approach that exploits whole-brain functional connectivity to predict a behavior or trait that varies across individuals. We used CPM to determine whether brain "fingerprints" evoked during milkshake consumption could be isolated for common measures of adiposity in 67 adults with overweight and obesity. We found that CPM captures more variance in waist circumference than either percent body fat or BMI, the most frequently used measures to assess brain correlates of obesity. In a post-hoc analysis, we were also able to derive a largely separable functional connectivity network predicting fasting blood insulin. These findings suggest that, in individuals with overweight and obesity, brain network patterns may be more tightly coupled to waist circumference than BMI or percent body fat and that adiposity and glucose tolerance are associated with distinct maps, pointing to dissociable central pathophysiological phenotypes for obesity and diabetes.

Modulation of Intrinsic Brain Connectivity by Implicit Electroencephalographic Neurofeedback

Despite the increasing popularity of neurofeedback, its mechanisms of action are still poorly understood. This study aims to describe the processes underlying implicit electroencephalographic neurofeedback. Fifty-two healthy volunteers were randomly assigned to a single session of infra-low frequency neurofeedback or sham neurofeedback, with electrodes over the right middle temporal gyrus and the right inferior parietal lobule. They observed a moving rocket, the speed of which was modulated by the waveform derived from a band-limited infra-low frequency filter. Immediately before and after the session, the participants underwent a resting-state fMRI. Network-based statistical analysis was applied, comparing post- vs. pre-session and real vs. sham neurofeedback conditions. As a result, two phenomena were observed. First, we described a brain circuit related to the implicit neurofeedback process itself, consisting of the lateral occipital cortex, right dorsolateral prefrontal cortex, left orbitofrontal cortex, right ventral striatum, and bilateral dorsal striatum. Second, we found increased connectivity between key regions of the salience, language, and visual networks, which is indicative of integration in sensory processing. Thus, it appears that a single session of implicit infra-low frequency electroencephalographic neurofeedback leads to significant changes in intrinsic brain connectivity.

Modulatory effects of dynamic fMRI-based neurofeedback on emotion regulation networks in adolescent females

Research has shown that difficulties with emotion regulation abilities in childhood and adolescence increase the risk for developing symptoms of mental disorders, e.g anxiety. We investigated whether functional magnetic resonance imaging (fMRI)-based neurofeedback (NF) can modulate brain networks supporting emotion regulation abilities in adolescent females.

We performed three experiments (Experiment 1: N ​= ​18; Experiment 2: N ​= ​30; Experiment 3: N ​= ​20). We first compared different NF implementations regarding their effectiveness of modulating prefrontal cortex (PFC)-amygdala functional connectivity (fc). Further we assessed the effects of fc-NF on neural measures, emotional/metacognitive measures and their associations. Finally, we probed the mechanism underlying fc-NF by examining concentrations of inhibitory and excitatory neurotransmitters.

Results showed that NF implementations differentially modulate PFC-amygdala fc. Using the most effective NF implementation we observed important relationships between neural and emotional/metacognitive measures, such as practice-related change in fc was related with change in thought control ability. Further, we found that the relationship between state anxiety prior to the MRI session and the effect of fc-NF was moderated by GABA concentrations in the PFC and anterior cingulate cortex.

To conclude, we were able to show that fc-NF can be used in adolescent females to shape neural and emotional/metacognitive measures underlying emotion regulation. We further show that neurotransmitter concentrations moderate fc–NF–effects.

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Neurofeedback implementations differentially modulate PFC-amygdala connectivity.

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Functional connectivity neurofeedback affect measures of emotion regulation.

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Neurotransmitter concentrations moderate neurofeedback effects.

Cognitive and Social Rehabilitation in Schizophrenia-From Neurophysiology to Neuromodulation. Pilot Study

The aim of this pilot study was to analyse the influence of Galvanic Skin Response (GSR) Biofeedback training in a group of 18 men with schizophrenia at the remission stage. The results were verified according to: Positive and Negative Syndrome Scale (PANSS), Acceptance of Illness Scale (AIS), Self-efficacy Scale (GSES), Beck Cognitive Insight Scale (BCIS) scales, Colour Trial Test (CTT-1, CTT-2), d2 psychological tests, Quantitative Electroencephalogram (QEEG) Biofeedback, auditory event-related potentials (ERPs), and serum levels of brain-derived neurotrophic factor (BDNF). The results were compared in the same patients after 3 months. Statistically significant changes were noted in results for the variables on the PANSS scale. For the BDNF variable, a statistically significant increase occurred, indicating that GSR Biofeedback training may influence serum levels of the neurotrophic factor. Statistically significant changes were noted in results for the variables on the BCIS, AIS, and GSES indicating an improvement in the cognitive and social functioning. Changes were noted for results for theta/beta and theta/Sensory Motor Rhythm (SMR) ratios, which indicate an improvement in concentration and attention. Changes were noted for the N1 wave amplitude in the frontal brain region (F-z), and for the P2 wave latency in the central brain region (C-z), which indicates an improvement in the initial perceptual analysis. The use of GSR Biofeedback in a group of patients with schizophrenia gives interesting results, but requires further in-depth research.

Global Data-Driven Analysis of Brain Connectivity During Emotion Regulation by Electroencephalography Neurofeedback

Background: Emotion regulation by neurofeedback involves interactions among multiple brain regions, including prefrontal cortex and subcortical regions. Previous studies focused on connections of specific brain regions such as amygdala with other brain regions. New method: Electroencephalography (EEG) neurofeedback is used to upregulate positive emotion by retrieving positive autobiographical memories and functional magnetic resonance imaging (fMRI) data acquired simultaneously. A global data-driven approach, group independent component analysis, is applied to the fMRI data and functional network connectivity (FNC) estimated. Results: The proposed approach identified all functional networks engaged in positive autobiographical memories and evaluated effects of neurofeedback. The results revealed two pairs of networks with significantly different functional connectivity among emotion regulation blocks (relative to other blocks of the experiment) and between experimental and control groups (false discovery rate corrected for multiple comparisons, q = 0.05). FNC distribution showed significant connectivity differences between neurofeedback blocks and other blocks, revealing more synchronized brain networks during neurofeedback. Comparison with Existing Methods: Although the results are consistent with those of previous model-based studies, some of the connections found in this study were not found previously. These connections are between (a) occipital and other regions including limbic system/sublobar, prefrontal/frontal cortex, inferior parietal, and middle temporal gyrus and (b) posterior cingulate cortex and hippocampus. Conclusions: This study provided a global insight into brain connectivity for emotion regulation. The brain network interactions may be used to develop connectivity-based neurofeedback methods and alternative therapeutic approaches, which may be more effective than the traditional activity-based neurofeedback methods.

Effect of deactivation of activity patterns related to smoking cue reactivity on nicotine addiction

With approximately 75% of smokers resuming cigarette smoking after using the Gold Standard Programme for smoking cessation, investigation into novel therapeutic approaches is warranted. Typically, smoking cue reactivity is crucial for smoking behaviour. Here we developed a novel closed-loop, smoking cue reactivity patterns EEG-based neurofeedback protocol and evaluated its therapeutic efficacy on nicotine addiction. During an evoked smoking cue reactivity task participants' brain activity patterns corresponding to smoking cues were obtained with multivariate pattern analysis of all EEG channels data, then during neurofeedback the EEG activity patterns of smoking cue reactivity were continuously deactivated with adaptive closed-loop training. In a double-blind, placebo-controlled, randomized clinical trial, 60 nicotine-dependent participants were assigned to receive two neurofeedback training sessions (∼1 h/session) either from their own brain (n = 30, real-feedback group) or from the brain activity pattern of a matched participant (n = 30, yoked-feedback group). Cigarette craving and craving-related P300 were assessed at pre-neurofeedback and post-neurofeedback. The number of cigarettes smoked per day was assessed at baseline, 1 week, 1 month, and 4 months following the final neurofeedback visit. In the real-feedback group, participants successfully deactivated EEG activity patterns of smoking cue reactivity. The real-feedback group showed significant decrease in cigarette craving and craving-related P300 amplitudes compared with the yoked-feedback group. The rates of cigarettes smoked per day at 1 week, 1 month and 4 months follow-up decreased 30.6%, 38.2%, and 27.4% relative to baseline in the real-feedback group, compared to decreases of 14.0%, 13.7%, and 5.9% in the yoked-feedback group. The neurofeedback effects on craving change and smoking amount at the 4-month follow-up were further predicted by neural markers at pre-neurofeedback. This novel neurofeedback training approach produced significant short-term and long-term effects on cigarette craving and smoking behaviour, suggesting the neurofeedback protocol described herein is a promising brain-based tool for treating addiction.

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.

Resilience and the brain: a key role for regulatory circuits linked to social stress and support

Given the high prevalence and burden of mental disorders, fostering the understanding of protective factors is an urgent issue for translational medicine in psychiatry. The concept of resilience describes individual and environmental protective factors against the backdrop of established adversities linked to mental illness. There is convergent evidence for a crucial role of direct as well as indirect adversity impacting the developing brain, with persisting effects until adulthood. Direct adversity may include childhood maltreatment and family adversity, while indirect social adversity can include factors such as urban living or ethnic minority status. Recently, research has begun to examine protective factors which may be able to buffer against or even reverse these influences. First evidence indicates that supportive social environments as well as trait-like individual protective characteristics might impact on similar neural substrates, thus strengthening the capacity to actively cope with stress exposure in order to counteract the detrimental effects evoked by social adversity. Here, we provide an overview of the current literature investigating the neural mechanisms of resilience with a putative social background, including studies on individual traits and genetic variation linked to resilience. We argue that the regulatory perigenual anterior cingulate cortex and limbic regions, including the amygdala and the ventral striatum, play a key role as crucial convergence sites of protective factors. Further, we discuss possible prevention and early intervention approaches targeting both the individual and the social environment to reduce the risk of psychiatric disorders and foster resilience.

Self-regulation of ventromedial prefrontal cortex activation using real-time fMRI neurofeedback-Influence of default mode network

The ventromedial prefrontal cortex (vmPFC) is involved in regulation of negative emotion and decision-making, emotional and behavioral control, and active resilient coping. This pilot study examined the feasibility of training healthy subjects (n = 27) to self-regulate the vmPFC activity using a real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf). Participants in the experimental group (EG, n = 18) were provided with an ongoing vmPFC hemodynamic activity (rtfMRI-nf signal represented as variable-height bar). Individuals were instructed to raise the bar by self-relevant value-based thinking. Participants in the control group (CG, n = 9) performed the same task; however, they were provided with computer-generated sham neurofeedback signal. Results demonstrate that (a) both the CG and the EG show a higher vmPFC fMRI signal at the baseline than during neurofeedback training; (b) no significant positive training effect was seen in the vmPFC across neurofeedback runs; however, the medial prefrontal cortex, middle temporal gyri, inferior frontal gyri, and precuneus showed significant decreasing trends across the training runs only for the EG; (c) the vmPFC rtfMRI-nf signal associated with the fMRI signal across the default mode network (DMN). These findings suggest that it may be difficult to modulate a single DMN region without affecting other DMN regions. Observed decreased vmPFC activity during the neurofeedback task could be due to interference from the fMRI signal within other DMN network regions, as well as interaction with task-positive networks. Even though participants in the EG did not show significant positive increase in the vmPFC activity among neurofeedback runs, they were able to learn to accommodate the demand of self-regulation task to maintain the vmPFC activity with the help of a neurofeedback signal.

Using connectivity-based real-time fMRI neurofeedback to modulate attentional and resting state networks in people with high trait anxiety

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Controlled experiment on functional connectivity-based real-time fMRI neurofeedback.

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Reduced anxiety levels in the experimental group after neurofeedback training.

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Altered activity and connectivity in neurofeedback ROIs in the experimental group.

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Increased resting state functional connectivity in the PCC in the experimental group.

High levels of trait anxiety are associated with impaired attentional control, changes in brain activity during attentional control tasks and altered network resting state functional connectivity (RSFC). Specifically, dorsolateral prefrontal cortex to anterior cingulate cortex (DLPFC – ACC) functional connectivity, thought to be crucial for effective and efficient attentional control, is reduced in high trait anxious individuals. The current study examined the potential of connectivity-based real-time functional magnetic imaging neurofeedback (rt-fMRI-nf) for enhancing DLPFC – ACC functional connectivity in trait anxious individuals. We specifically tested if changes in DLPFC - ACC connectivity were associated with reduced anxiety levels and improved attentional control. Thirty-two high trait anxious participants were assigned to either an experimental group (EG), undergoing veridical rt-fMRI-nf, or a control group (CG) that received sham (yoked) feedback. RSFC (using resting state fMRI), anxiety levels and Stroop task performance were assessed pre- and post-rt-fMRI-nf training. Post-rt-fMRI-nf training, relative to the CG, the EG showed reduced anxiety levels and increased DLPFC-ACC functional connectivity as well as increased RSFC in the posterior default mode network. Moreover, in the EG, changes in DLPFC – ACC functional connectivity during rt-fMRI-nf training were associated with reduced anxiety levels. However, there were no group differences in Stroop task performance. We conclude that rt-fMRI-nf targeting DLPFC – ACC functional connectivity can alter network connectivity and interactions and is a feasible method for reducing trait anxiety.

Mental Imagery and Brain Regulation-New Links Between Psychotherapy and Neuroscience

Mental imagery is a promising tool and mechanism of psychological interventions, particularly for mood and anxiety disorders. In parallel developments, neuromodulation techniques have shown promise as add-on therapies in psychiatry, particularly non-invasive brain stimulation for depression. However, these techniques have not yet been combined in a systematic manner. One novel technology that may be able to achieve this is neurofeedback, which entails the self-regulation of activation in specific brain areas or networks (or the self-modulation of distributed activation patterns) by the patients themselves, through real-time feedback of brain activation (for example, from functional magnetic resonance imaging). One of the key mechanisms by which patients learn such self-regulation is mental imagery. Here, we will first review the main mental imagery approaches in psychotherapy and the implicated brain networks. We will then discuss how these networks can be targeted with neuromodulation (neurofeedback or non-invasive or invasive brain stimulation). We will review the clinical evidence for neurofeedback and discuss possible ways of enhancing it through systematic combination with psychological interventions, with a focus on depression, anxiety disorders, and addiction. The overarching aim of this perspective paper will be to open a debate on new ways of developing neuropsychotherapies.

Brain activity mediators of PTSD symptom reduction during real-time fMRI amygdala neurofeedback emotional training

Self-regulation of brain activation with real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) is emerging as a promising treatment for psychiatric disorders. The association between the regulation and symptom reduction, however, has not been consistent, and the mechanisms underlying the symptom reduction remain poorly understood. The present study investigated brain activity mediators of the amygdala rtfMRI-nf training effect on combat veterans' PTSD symptom reduction. The training was designed to increase a neurofeedback signal either from the left amygdala (experimental group; EG) or from a control region not implicated in emotion regulation (control group; CG) during positive autobiographical memory recall. We employed a structural equation model mapping analysis to identify brain regions that mediated the effects of the rtfMRI-nf training on PTSD symptoms. Symptom reduction was mediated by low activation in the dorsomedial prefrontal cortex (DMPFC) and the middle cingulate cortex. There was a trend toward less activation in these regions for the EG compared to the CG. Low activation in the precuneus, the right superior parietal, the right insula, and the right cerebellum also mediated symptom reduction while their effects were moderated by the neurofeedback signal; a higher signal was linked to less effect on symptom reduction. This moderation was not specific to the EG. MDD comorbidity was associated with high DMPFC activation, which resulted in less effective regulation of the feedback signal. These results indicated that symptom reduction due to the neurofeedback training was not specifically mediated by the neurofeedback target activity, but broad regions were involved in the process.