Self-regulation of the dopaminergic reward circuit in cocaine users with mental imagery and neurofeedback

Happy Hour: The association between trait hedonic capacity and motivation to drink alcohol

The (over)consumption of alcohol and other addictive substances is often conceptualized as a problem of low self-control (i.e., people's inability to inhibit unwanted impulses). According to that view, people drink because they cannot resist. In the present studies, we approached this from a different perspective and tested whether alcohol consumption might also be a problem of low hedonic capacity (i.e., people's inability to experience pleasure and relaxation, often due to intrusive thoughts). According to that view, people drink because it helps them enjoy or cope with negative thoughts or emotions. In two studies among individuals at low risk of harmful alcohol use (e.g., AUDIT < 7) we consistently found that trait hedonic capacity was unrelated to alcohol consumption but negatively related to coping motivation (drinking alcohol to cope with negative thoughts and feelings; Study 1: N = 348; Study 2: N = 302, preregistered). Exploratory analyses in study 2 (conducted during the COVID-19 pandemic) also showed that people with low, but not high, trait hedonic capacity drank more alcohol in response to stress. Our findings are in line with the notion that people's drinking motivation and behavior might not only be a problem of poor self-control but also of low trait hedonic capacity. They align with a new direction in addiction prevention and treatment research, which explores ways to help people to seek out and savor hedonic experiences from non-drug related reinforcers (e.g., engaging in leisure activities).

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

Introduction

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

Methods

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

Results

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

Discussion

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

Development and validation of an fMRI-informed EEG model of reward-related ventral striatum activation

Reward processing is essential for our mental-health and well-being. In the current study, we developed and validated a scalable, fMRI-informed EEG model for monitoring reward processing related to activation in the ventral-striatum (VS), a significant node in the brain's reward system. To develop this EEG-based model of VS-related activation, we collected simultaneous EEG/fMRI data from 17 healthy individuals while listening to individually-tailored pleasurable music - a highly rewarding stimulus known to engage the VS. Using these cross-modal data, we constructed a generic regression model for predicting the concurrently acquired Blood-Oxygen-Level-Dependent (BOLD) signal from the VS using spectro-temporal features from the EEG signal (termed hereby VS-related-Electrical Finger Print; VS-EFP). The performance of the extracted model was examined using a series of tests that were applied on the original dataset and, importantly, an external validation dataset collected from a different group of 14 healthy individuals who underwent the same EEG/FMRI procedure. Our results showed that the VS-EFP model, as measured by simultaneous EEG, predicted BOLD activation in the VS and additional functionally relevant regions to a greater extent than an EFP model derived from a different anatomical region. The developed VS-EFP was also modulated by musical pleasure and predictive of the VS-BOLD during a monetary reward task, further indicating its functional relevance. These findings provide compelling evidence for the feasibility of using EEG alone to model neural activation related to the VS, paving the way for future use of this scalable neural probing approach in neural monitoring and self-guided neuromodulation.

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

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

Transdiagnostic brain correlates of self-reported trait impulsivity: A dimensional structure-symptom investigation

Impulsivity transcends psychiatric diagnoses and is often related to anhedonia. This ad hoc cross-sectional investigation explored 1) whether self-reported trait impulsivity mapped onto a common structural brain substrate across healthy controls (HCs) and psychiatric patients, and 2) in a more exploratory fashion, whether impulsivity and anhedonia were related to each other and shared overlapping brain correlates. Structural magnetic resonance imaging (sMRI) datasets from 234 participants including HCs (n = 109) and patients with opioid use disorder (OUD, n = 22), cocaine use disorder (CUD, n = 43), borderline personality disorder (BPD, n = 45) and schizophrenia (SZ, n = 15) were included. Trait impulsivity was measured with the Barratt Impulsiveness Scale (BIS-11) and anhedonia with a subscore of the Beck Depression Inventory (BDI). BIS-11 global score data were available for the entire sample, while data on the BIS-11 2nd order factors attentional, motor and non-planning were additionally in hand for a subsample consisting of HCs, OUD and BPD patients (n = 116). Voxel-based morphometry analyses were conducted for identifying dimensional associations between grey matter volume and impulsivity/anhedonia. Partial correlations were further performed to exploratory test the relationships between impulsivity and anhedonia and their corresponding volumetric brain substrates. Volume of the left opercular part of the inferior frontal gyrus (IFG) was negatively related to global impulsivity across the entire sample and specifically to motor impulsivity in the subsample of HCs, OUD and BPD patients. Across patients anhedonia expression was negatively correlated with left putamen volume. Although there was no relationship between global impulsivity and anhedonia across all patients, only across OUD and BPD patients anhedonia was positively associated with attentional impulsivity. Finally, also across OUD and BPD patients, motor impulsivity associated left IFG volume was positively linked with anhedonia-associated volume in the left putamen. Our findings suggest a critical role of left IFG volume in self-reported global impulsivity across healthy participants and patients with substance use disorder, BPD and SZ. Preliminary findings in OUD and BPD patients further suggests associations between impulsivity and anhedonia that are related to grey matter reductions in the left IFG and putamen.

Computationally Informed Interventions for Targeting Compulsive Behaviors

Compulsive behaviors are central to addiction and obsessive-compulsive disorder and can be understood as a failure of adaptive decision making. Particularly, they can be conceptualized as an imbalance in behavioral control, such that behavior is guided predominantly by learned rather than inferred outcome expectations. Inference is a computational process required for adaptive behavior, and recent work across species has identified the neural circuitry that supports inference-based decision making. This includes the orbitofrontal cortex, which has long been implicated in disorders of compulsive behavior. Inspired by evidence that modulating orbitofrontal cortex activity can alter inference-based behaviors, here we discuss noninvasive approaches to target these circuits in humans. Specifically, we discuss the potential of network-targeted transcranial magnetic stimulation and real-time neurofeedback to modulate the neural underpinnings of inference. Both interventions leverage recent advances in our understanding of the neurocomputational mechanisms of inference-based behavior and may be used to complement current treatment approaches for behavioral disorders.

Testing the efficacy of real-time fMRI neurofeedback for training people who smoke daily to upregulate neural responses to nondrug rewards

Although the use of nondrug rewards (e.g., money) to facilitate smoking cessation is widespread, recent research has found that such rewards may be least effective when people who smoke cigarettes are tempted to do so. Specifically, among people who smoke, the neural response to nondrug rewards appears blunted when access to cigarettes is anticipated, and this blunting is linked to a decrease in willingness to refrain from smoking to earn a monetary incentive. Accordingly, methods to enhance the value of nondrug rewards may be theoretically and clinically important. The current proof-of-concept study tested if real-time fMRI neurofeedback training augments the ability to upregulate responses in reward-related brain areas relative to a no-feedback control condition in people who smoke. Adults (n = 44, age range = 20-44) who reported smoking >5 cigarettes per day completed the study. Those in the intervention group (n = 22, 5 females) were trained to upregulate brain responses using feedback of ongoing striatal activity (i.e., a dynamic "thermometer" that reflected ongoing changes of fMRI signal intensity in the striatum) in a single neurofeedback session with three training runs. The control group (n = 22, 5 females) underwent a nearly identical procedure but received no neurofeedback. Those who received neurofeedback training demonstrated significantly greater increases in striatal BOLD activation while attempting to think about something rewarding compared to controls, but this effect was present only during the first training run. Future neurofeedback research with those who smoke should explore how to make neurofeedback training more effective for the self-regulation of reward-related brain activities.

Analysis of individual differences in neurofeedback training illuminates successful self-regulation of the dopaminergic midbrain

The dopaminergic midbrain is associated with reinforcement learning, motivation and decision-making – functions often disturbed in neuropsychiatric disorders. Previous research has shown that dopaminergic midbrain activity can be endogenously modulated via neurofeedback. However, the robustness of endogenous modulation, a requirement for clinical translation, is unclear. Here, we examine whether the activation of particular brain regions associates with successful regulation transfer when feedback is no longer available. Moreover, to elucidate mechanisms underlying effective self-regulation, we study the relation of successful transfer with learning (temporal difference coding) outside the midbrain during neurofeedback training and with individual reward sensitivity in a monetary incentive delay (MID) task. Fifty-nine participants underwent neurofeedback training either in standard (Study 1 N = 15, Study 2 N = 28) or control feedback group (Study 1, N = 16). We find that successful self-regulation is associated with prefrontal reward sensitivity in the MID task (N = 25), with a decreasing relation between prefrontal activity and midbrain learning signals during neurofeedback training and with increased activity within cognitive control areas during transfer. The association between midbrain self-regulation and prefrontal temporal difference and reward sensitivity suggests that reinforcement learning contributes to successful self-regulation. Our findings provide insights in the control of midbrain activity and may facilitate individually tailoring neurofeedback training.

Analysis of real-time fMRI data from 59 participants undergoing neurofeedback training suggests that reinforcement learning contributes to successful self-regulation in the dopaminergic midbrain.

Cold Suggestion to Cope with the Negative Impact of Tropical Climate

The thermal discomfort experienced in a tropical environment has negative effects on human performance. Cooling techniques before, during, or immediately after exercise have been extensively reported on in the physiological literature, but psychological techniques for subjective cooling have rarely been explored. The purpose of this experiment was to evaluate whether a cold suggestion would have an effect on environmental perceptions and affect in a tropical climate. Fifty participants were assigned in random order to two experimental sessions in similar hot and humid conditions at a 1-week interval (30°C ± 1.2; 87% rH ± 2): one with a suggestion focused on cold and the other a control session. The main results indicated that the suggestion focused on cold significantly decreased thermal discomfort and perceived heat and reduced the degradation on the Feeling Scale. The cold suggestion used as a per-cooling technique to cope with the negative impact of a tropical climate is discussed.

Neural mapping of anhedonia across psychiatric diagnoses: A transdiagnostic neuroimaging analysis

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Anhedonia is present in many different psychiatric disorders.

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Anhedonia has been associated with abnormal reward-related striatal dopamine functioning.

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This study tested whether transdiagnostic anhedonia expression mapped onto striatal volume.

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Our findings suggest volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities.

Anhedonia has been associated with abnormal reward-related striatal dopamine functioning in patients with different psychiatric disorders. Here, we tested whether anhedonia expression mapped onto striatal volume across several psychiatric diagnoses.

T1-weighted images from 313 participants including 89 healthy controls (HC), 22 patients with opioid use disorder (OUD), 50 patients with major depressive disorder (MDD), 45 patients with borderline personality disorder (BPD), 49 patients with first-episode psychosis (FEP), 43 patients with cocaine use disorder (CUD) and 15 patients with schizophrenia (SZ) were included. Anhedonia was assessed with subscores of the Beck Depression Inventory (BDI) and/or the Scale for the Assessment of Negative Symptoms (SANS). Voxel-based morphometry (VBM) was conducted for identifying dimensional symptom-structure associations using region of interest (ROI, dorsal and ventral striatum) and whole-brain analyses, as well as for group comparisons of striatal volume.

ROI analyses revealed significant negative relationships between putamen volume and BDI and SANS anhedonia scores across OUD, MDD, BPD, CUD and SZ patients (n = 175) and MDD, FEP and SZ patients (n = 114), respectively. Whole-brain VBM analyses confirmed these associations and further showed negative relationships between anhedonia severity and volume of the bilateral cerebellum. There were group differences in right accumbens volume, which however were not related to anhedonia expression across the different diagnoses.

Our findings indicate volumetric abnormalities in the putamen and cerebellum as a common neural substrate of anhedonia severity that cut across psychiatric entities.

Psychedelic-Assisted Therapy for Substance Use Disorders and Potential Mechanisms of Action

Substance use disorders (SUD) represent a significant public health issue with a high need for novel and efficacious treatment options. In light of this high unmet need, recent results reporting beneficial outcomes of psychedelic-assisted therapy in SUD are particularly relevant. However, several questions remain with regard to this treatment approach. The clinical mechanisms of action of psychedelic substances in the treatment of SUD are not well understood. Closing this knowledge gap is critical to inform and optimize the psychotherapeutic embedding of the acute substance administration. In this chapter, we discuss potential mechanisms that have implications on psychotherapeutic approaches including induced neuroplasticity, alterations in brain network connectivity, reward and emotion processing, social connectedness, insight, and mystical experiences. Furthermore, we outline considerations and approaches that leverage these mechanisms in order to optimize the therapeutic embedding by maximizing synergy between substance effects and psychotherapy. Understanding the mechanisms of action, developing psychotherapeutic approaches accordingly, and evaluating their synergistic efficacy in scientific studies will be critical to advance the framework of psychedelic-assisted therapy for addiction, create evidence-based approaches, and achieve the best treatment outcome for patients with SUD.

The neurobiology of drug addiction: cross-species insights into the dysfunction and recovery of the prefrontal cortex

A growing preclinical and clinical body of work on the effects of chronic drug use and drug addiction has extended the scope of inquiry from the putative reward-related subcortical mechanisms to higher-order executive functions as regulated by the prefrontal cortex. Here we review the neuroimaging evidence in humans and non-human primates to demonstrate the involvement of the prefrontal cortex in emotional, cognitive, and behavioral alterations in drug addiction, with particular attention to the impaired response inhibition and salience attribution (iRISA) framework. In support of iRISA, functional and structural neuroimaging studies document a role for the prefrontal cortex in assigning excessive salience to drug over non-drug-related processes with concomitant lapses in self-control, and deficits in reward-related decision-making and insight into illness. Importantly, converging insights from human and non-human primate studies suggest a causal relationship between drug addiction and prefrontal insult, indicating that chronic drug use causes the prefrontal cortex damage that underlies iRISA while changes with abstinence and recovery with treatment suggest plasticity of these same brain regions and functions. We further dissect the overlapping and distinct characteristics of drug classes, potential biomarkers that inform vulnerability and resilience, and advancements in cutting-edge psychological and neuromodulatory treatment strategies, providing a comprehensive landscape of the human and non-human primate drug addiction literature as it relates to the prefrontal cortex.

Negative symptoms in alcohol use disorder: A pilot study applying the two-factor model of negative symptoms to patients with alcohol use disorder

BACKGROUND AND AIMS

Alcohol Use Disorder (AUD) is characterized by a reduction in goal-directed behavior, with alcohol use taking precedence over other areas of life. These features in AUD resemble negative symptoms in schizophrenia, especially the reduction in motivation and pleasure (MAP). Given the clinical similarities of negative symptoms across diagnostic categories, it comes as a surprise that there are few investigations on negative symptoms in alcohol and other substance use disorders. To our knowledge, our study is the first to assess negative symptoms in AUD based on a two-factorial approach, and to investigate the interrelation of these dimensions with the severity of AUD, and alcohol craving.

MATERIALS AND METHODS

We examined a sample of 42 patients with AUD at the Psychiatric University Hospital in Zurich. Participants provided self-report and interview-based measures of the severity of AUD, negative symptoms, and alcohol craving. Finally, we used data from the electronic health records of the patients.

RESULTS

Patients with AUD show negative symptoms to a similar extent as patients with schizophrenia or bipolar disorder. We found a positive correlation between the extent of impairment within the MAP factor and overall severity of AUD. Furthermore, MAP negative symptoms were correlated with alcohol craving. In a linear regression, negative symptoms predicted alcohol craving whereas depression did not.

SUMMARY

Negative symptoms as conceptualized for schizophrenia are prevalent in patients with AUD and associated with the severity of AUD. More specifically, severity of AUD correlates with diminished motivation and pleasure, highlighting the importance of disturbances in motivational functions in AUD. This is further supported by the correlation between negative symptoms and craving, a hallmark of AUD. Taken together, our findings suggest that negative symptoms might be a highly relevant but hitherto often neglected therapeutic target in AUD.

Disentangling craving- and valence-related brain responses to smoking cues in individuals with nicotine use disorder

Tobacco smoking is one of the leading causes of preventable death and disease worldwide. Most smokers want to quit, but relapse rates are high. To improve current smoking cessation treatments, a better understanding of the underlying mechanisms of nicotine dependence and related craving behaviour is needed. Studies on cue‐driven cigarette craving have been a particularly useful tool for investigating the neural mechanisms of drug craving. Here, functional neuroimaging studies in humans have identified a core network of craving‐related brain responses to smoking cues that comprises of amygdala, anterior cingulate cortex, orbitofrontal cortex, posterior cingulate cortex and ventral striatum. However, most functional Magnetic Resonance Imaging (fMRI) cue‐reactivity studies do not adjust their stimuli for emotional valence, a factor assumed to confound craving‐related brain responses to smoking cues. Here, we investigated the influence of emotional valence on key addiction brain areas by disentangling craving‐ and valence‐related brain responses with parametric modulators in 32 smokers. For one of the suggested key regions for addiction, the amygdala, we observed significantly stronger brain responses to the valence aspect of the presented images than to the craving aspect. Our results emphasize the need for carefully selecting stimulus material for cue‐reactivity paradigms, in particular with respect to emotional valence. Further, they can help designing future research on teasing apart the diverse psychological dimensions that comprise nicotine dependence and, therefore, can lead to a more precise mapping of craving‐associated brain areas, an important step towards more tailored smoking cessation treatments.

Deep Network Pharmacology: Targeting Glutamate Systems as Integrative Treatments for Jump-Starting Neural Networks and Recovery Trajectories

Significant advances in pharmacological treatments for mental illness and addiction will require abandoning old monoaminergic theories of psychiatric disorders and traditionally narrow approaches to how we conduct treatment research. Reframing our efforts with a view on integrative treatments that target core neural network function and plasticity may provide new approaches for lifting patients out of chronic psychiatric symptom sets and addiction. For example, we discuss new treatments that target brain glutamate systems at key transition points within longitudinal courses of care that integrate several treatment modalities. A reconsideration of what our novel and already available medications are intended to achieve and how and when we deliver them for patients with complex illness trajectories could be the key to unlocking new advances in general and addiction psychiatry.

Impaired glutamate homeostasis in the nucleus accumbens in human cocaine addiction

Cocaine addiction is characterized by overwhelming craving for the substance, which drives its escalating use despite adverse consequences. Animal models suggest a disrupted glutamate homeostasis in the nucleus accumbens to underlie addiction-like behavior. After chronic administration of cocaine, rodents show decreased levels of accumbal glutamate, whereas drug-seeking reinstatement is associated with enhanced glutamatergic transmission. However, due to technical obstacles, the role of disturbed glutamate homeostasis for cocaine addiction in humans remains only partially understood, and accordingly, no approved pharmacotherapy exists. Here, we applied a tailored proton magnetic resonance spectroscopy protocol that allows glutamate quantification within the human nucleus accumbens. We found significantly reduced basal glutamate concentrations in the nucleus accumbens in cocaine-addicted (N = 26) compared with healthy individuals (N = 30), and increased glutamate levels during cue-induced craving in cocaine-addicted individuals compared with baseline. These glutamatergic alterations, however, could not be significantly modulated by a short-term challenge of N-acetylcysteine (2400 mg/day on 2 days). Taken together, our findings reveal a disturbed accumbal glutamate homeostasis as a key neurometabolic feature of cocaine addiction also in humans. Therefore, we suggest the glutamatergic system as a promising target for the development of novel pharmacotherapies, and in addition, as a potential biomarker for a personalized medicine approach in addiction.

A Novel Cognition-Guided Neurofeedback BCI Dataset on Nicotine Addiction

Compared with the traditional neurofeedback paradigm, the cognition-guided neurofeedback brain–computer interface (BCI) is a novel paradigm with significant effect on nicotine addiction. However, the cognition-guided neurofeedback BCI dataset is extremely lacking at present. This paper provides a BCI dataset based on a novel cognition-guided neurofeedback on nicotine addiction. Twenty-eight participants are recruited and involved in two visits of neurofeedback training. This cognition-guided neurofeedback includes two phases: an offline classifier construction and a real-time neurofeedback training. The original electroencephalogram (EEG) raw data of two phases are provided and evaluated in this paper. The event-related potential (ERP) amplitude and channel waveform suggest that our BCI dataset is of good quality and consistency. During neurofeedback training, the participants’ smoking cue reactivity patterns have a significant reduction. The mean accuracy of the multivariate pattern analysis (MVPA) classifier can reach approximately 70%. This novel cognition-guided neurofeedback BCI dataset can be used to develop comparisons with other neurofeedback systems and provide a reference for the development of other BCI algorithms and neurofeedback paradigms on addiction.

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.

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.

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.

Common and separable neural alterations in substance use disorders: A coordinate-based meta-analyses of functional neuroimaging studies in humans

Delineating common and separable neural alterations in substance use disorders (SUD) is imperative to understand the neurobiological basis of the addictive process and to inform substance‐specific treatment strategies. Given numerous functional MRI (fMRI) studies in different SUDs, a meta‐analysis could provide an opportunity to determine robust shared and substance‐specific alterations. The present study employed a coordinate‐based meta‐analysis covering fMRI studies in individuals with addictive cocaine, cannabis, alcohol, and nicotine use. The primary meta‐analysis demonstrated common alterations in primary dorsal striatal, and frontal circuits engaged in reward/salience processing, habit formation, and executive control across different substances and task‐paradigms. Subsequent sub‐analyses revealed substance‐specific alterations in frontal and limbic regions, with marked frontal and insula‐thalamic alterations in alcohol and nicotine use disorders respectively. Examining task‐specific alterations across substances revealed pronounced frontal alterations during cognitive processes yet stronger striatal alterations during reward‐related processes. Finally, an exploratory meta‐analysis revealed that neurofunctional alterations in striatal and frontal reward processing regions can already be determined with a high probability in studies with subjects with comparably short durations of use. Together the findings emphasize the role of dysregulations in frontostriatal circuits and dissociable contributions of these systems in the domains of reward‐related and cognitive processes which may contribute to substance‐specific behavioral alterations.

Neuromodulation of brain activation associated with addiction: A review of real-time fMRI neurofeedback studies

Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) has emerged in recent years as an imaging modality used to examine volitional control over targeted brain activity. rtfMRI-nf has also been applied clinically as a way to train individuals to self-regulate areas of the brain, or circuitry, involved in various disorders. One such application of rtfMRI-nf has been in the domain of addictive behaviors, including substance use. Given the pervasiveness of substance use and the challenges of existing treatments to sustain abstinence, rtfMRI-nf has been identified as a promising treatment tool. rtfMRI-nf has also been used in basic science research in order to test the ability to modulate brain function involved in addiction. This review focuses first on providing an overview of recent rtfMRI-nf studies in substance-using populations, specifically nicotine, alcohol, and cocaine users, aimed at reducing craving-related brain activation. Next, rtfMRI-nf studies targeting reward responsivity and emotion regulation in healthy samples are reviewed in order to examine the extent to which areas of the brain involved in addiction can be self-regulated using neurofeedback. We propose that future rtfMRI-nf studies could be strengthened by improvements to study design, sample selection, and more robust strategies in the development and assessment of rtfMRI-nf as a clinical treatment. Recommendations for ways to accomplish these improvements are provided. rtfMRI-nf holds much promise as an imaging modality that can directly target key brain regions involved in addiction, however additional studies are needed in order to establish rtfMRI-nf as an effective, and practical, treatment for 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.