Neurofeedback for Depression
(CNF-RNT Trial)
Recruiting in Palo Alto (17 mi)
Age: 18 - 65
Sex: Any
Travel: May Be Covered
Time Reimbursement: Varies
Trial Phase: Academic
Recruiting
Sponsor: Laureate Institute for Brain Research, Inc.
Must not be taking: Cardiovascular, Psychotropic, others
Disqualifiers: Traumatic brain injury, Cardiovascular, Psychosis, Schizophrenia, Substance use, others
No Placebo Group
Trial Summary
What is the purpose of this trial?
In this project, the investigators use real-time fMRI neurofeedback (rtfMRI-nf) to causally relate dysfunction of right anterior insula (rAI) and right superior temporal sulcus (rSTS) connectivity with the intensity of repetitive negative thinking (RNT). The investigators hypothesize that rtfMRI-nf reducing rAI-rSTS connectivity would reduce RNT. The investigators propose a randomized double-blind, sham-controlled trial of rtfMRI-nf with 110 young adults (n=55/arm) with major depressive disorder (MDD) and high trait-RNT levels.
Will I have to stop taking my current medications?
The trial does not specify if you need to stop taking your current medications, but you cannot start new psychotropic medications or therapy for depression or anxiety less than a month before joining. Also, you cannot use more than three psychotropic medications or certain cardiovascular medications.
What data supports the effectiveness of the treatment Neurofeedback for Depression?
Research shows that real-time fMRI neurofeedback can help people with depression improve their symptoms by teaching them to control brain areas linked to positive emotions. Studies found that patients using this method showed significant improvement in depression scores, although more research is needed to confirm these findings and rule out placebo effects.12345
Is neurofeedback safe for humans?
How does real-time fMRI neurofeedback treatment for depression differ from other treatments?
Eligibility Criteria
This trial is for young adults with major depressive disorder (MDD) who often have repetitive negative thoughts. Participants must be within a certain age range, typically considered 'young adult', and should meet specific criteria for MDD and high levels of such thoughts.Inclusion Criteria
I am between 18 and 35 years old.
I have been diagnosed with major depression according to DSM-5.
I am able to understand and willing to sign a consent form.
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Exclusion Criteria
Current psychosis
Severe claustrophobia
Pregnancy
See 15 more
Trial Timeline
Screening
Participants are screened for eligibility to participate in the trial
2-4 weeks
Treatment
Participants undergo real-time fMRI neurofeedback sessions to modulate brain connectivity related to repetitive negative thinking
1 week
2 visits (in-person)
Follow-up
Participants are monitored for changes in functional connectivity and depression severity
1 week
Treatment Details
Interventions
- Active neurofeedback (Behavioral Intervention)
- Sham neurofeedback (Behavioral Intervention)
Trial OverviewThe study tests if real-time fMRI neurofeedback can influence brain networks to reduce repetitive negative thinking in depression. It's a randomized trial comparing active neurofeedback targeting specific brain areas versus sham (fake) feedback.
Participant Groups
2Treatment groups
Experimental Treatment
Placebo Group
Group I: Active neurofeedbackExperimental Treatment1 Intervention
Receiving feedback signals from the repetitive negative thinking (RNT)-related brain functional connectivity
Group II: Sham neurofeedbackPlacebo Group1 Intervention
Receiving artificially generated feedback signals.
Find a Clinic Near You
Research Locations NearbySelect from list below to view details:
Laureate Institute for Brain ResearchTulsa, OK
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Who Is Running the Clinical Trial?
Laureate Institute for Brain Research, Inc.Lead Sponsor
National Institute of General Medical Sciences (NIGMS)Collaborator
References
Real-time self-regulation of emotion networks in patients with depression. [2022]Many patients show no or incomplete responses to current pharmacological or psychological therapies for depression. Here we explored the feasibility of a new brain self-regulation technique that integrates psychological and neurobiological approaches through neurofeedback with functional magnetic resonance imaging (fMRI). In a proof-of-concept study, eight patients with depression learned to upregulate brain areas involved in the generation of positive emotions (such as the ventrolateral prefrontal cortex (VLPFC) and insula) during four neurofeedback sessions. Their clinical symptoms, as assessed with the 17-item Hamilton Rating Scale for Depression (HDRS), improved significantly. A control group that underwent a training procedure with the same cognitive strategies but without neurofeedback did not improve clinically. Randomised blinded clinical trials are now needed to exclude possible placebo effects and to determine whether fMRI-based neurofeedback might become a useful adjunct to current therapies for depression.
A real-time fMRI neurofeedback system for the clinical alleviation of depression with a subject-independent classification of brain states: A proof of principle study. [2022]Most clinical neurofeedback studies based on functional magnetic resonance imaging use the patient's own neural activity as feedback. The objective of this study was to create a subject-independent brain state classifier as part of a real-time fMRI neurofeedback (rt-fMRI NF) system that can guide patients with depression in achieving a healthy brain state, and then to examine subsequent clinical changes. In a first step, a brain classifier based on a support vector machine (SVM) was trained from the neural information of happy autobiographical imagery and motor imagery blocks received from a healthy female participant during an MRI session. In the second step, 7 right-handed female patients with mild or moderate depressive symptoms were trained to match their own neural activity with the neural activity corresponding to the "happiness emotional brain state" of the healthy participant. The training (4 training sessions over 2 weeks) was carried out using the rt-fMRI NF system guided by the brain-state classifier we had created. Thus, the informative voxels previously obtained in the first step, using SVM classification and Effect Mapping, were used to classify the Blood-Oxygen-Level Dependent (BOLD) activity of the patients and converted into real-time visual feedback during the neurofeedback training runs. Improvements in the classifier accuracy toward the end of the training were observed in all the patients [Session 4-1 Median = 6.563%; Range = 4.10-27.34; Wilcoxon Test (0), 2-tailed p = 0.031]. Clinical improvement also was observed in a blind standardized clinical evaluation [HDRS CE2-1 Median = 7; Range 2 to 15; Wilcoxon Test (0), 2-tailed p = 0.016], and in self-report assessments [BDI-II CE2-1 Median = 8; Range 1-15; Wilcoxon Test (0), 2-tailed p = 0.031]. In addition, the clinical improvement was still present 10 days after the intervention [BDI-II CE3-2_Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.50/ HDRS CE3-2 Median = 0; Range -1 to 2; Wilcoxon Test (0), 2-tailed p = 0.625]. Although the number of participants needs to be increased and a control group included to confirm these findings, the results suggest a novel option for neural modulation and clinical alleviation in depression using noninvasive stimulation technologies.
Real-time fMRI neurofeedback compared to cognitive behavioral therapy in a pilot study for the treatment of mild and moderate depression. [2023]Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback was found to reduce depressive symptoms. However, no direct comparison of drug-free patients with an active psychotherapy control group is available. The present study compared rt-fMRI neurofeedback with cognitive behavioral therapy, as the standard treatment in patients declining anti-depressants. Twenty adult, drug-free patients with mild or moderate depression were non-randomly assigned either to a course of eight half-hour sessions of neurofeedback targeting the left medial prefrontal cortex (N = 12) or to a 16-session course of cognitive behavioral therapy (N = 8). Montgomery-Asberg Depression Rating Scale was introduced at baseline, mid-treatment, and end-treatment points. In each group, 8 patients each remained in the study to a mid-treatment evaluation and 6 patients each to the study end-point. ANOVA revealed a depression reduction with a significant effect of Time (F(3,6) = 19.0, p < 0.001, η2 = 0.76). A trend to greater improvement in the cognitive behavioral therapy group compared to neurofeedback emerged (Group × Time; p = 0.078). Percent signal change in the region of interest between up- and down-regulation conditions was significantly correlated with session number (Pearson's r = 0.85, p < 0.001) indicating a learning effect. As limitations, small sample size could lead to insufficient power and non-random allocation to selection bias. Both neurofeedback and cognitive behavioral therapy improved mild and moderate depression. Neurofeedback was not superior to cognitive behavioral therapy. Noteworthy, the neurofeedback training course was associated with continuous improvement in the self-regulation skill, without plateau. This study delivers data to plan clinical trials comparing neurofeedback with cognitive behavioral interventions.
Real-Time fMRI Neurofeedback Training as a Neurorehabilitation Approach on Depressive Disorders: A Systematic Review of Randomized Control Trials. [2022]Real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-nf) training is an emerging intervention for neurorehabilitation. However, its translation into clinical use on participants with clinical depression is unclear, the effect estimates from randomized control trials and the certainty of the supporting evidence on the effect estimates are unknown. As the number of studies on neurofeedback increases every year, and better quality evidence becomes available, we evaluate the evidence of all randomized control trials available on the clinical application of rt-fMRI-nf training on participants with clinical depression. We performed electronic searches in Pubmed, Embase, CENTRAL, rtFIN database, Epistemonikos, trial registers, reference lists, other systematic reviews, conference abstracts, and cross-citation in Google Scholar. Reviewers independently selected studies, extracted data and evaluated the risk of bias. The certainty of the evidence was judged using the GRADE framework. This review complies with PRISMA guidelines and was submitted to PROSPERO registration. We found 435 results. After the selection process, we included 11 reports corresponding to four RCTs. The effect of rt-fMRI-nf on improving the severity of clinical depression scores demonstrated a tendency to favor the intervention; however, the general effect was not significant. At end of treatment, SMD (standardized mean difference): -0.32 (95% CI -0.73 to 0.10). At follow-up, SMD: -0.33 (95% CI -0.91, 1.25). All the studies showed changes in BOLD fMRI activation after training; however, only one study confirmed regulation success during a transfer run. Whole-brain analyses suggests that rt-fMRI nf may alter activity patterns in brain networks. More studies are needed to evaluate quality of life, acceptability, adverse effects, cognitive tasks, and physiology measures. We conclude that the current evidence on the effect of rt-fMRI-nf training for decision-making outcomes in patients with clinical depression is still based on low certainty of the evidence.
Connectivity based Real-Time fMRI Neurofeedback Training in Youth with a History of Major Depressive Disorder. [2023]Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-nf) has proven to be a powerful technique to help subjects to gauge and enhance emotional control. Traditionally, rtfMRI-nf has focused on emotional regulation through self-regulation of amygdala. Recently, rtfMRI studies have observed that regulation of a target brain region is accompanied by connectivity changes beyond the target region. Therefore, the aim of present study is to investigate the use of connectivity between amygdala and prefrontal regions as the target of neurofeedback training in healthy individuals and subjects with a life-time history of major depressive disorder (MDD) performing an emotion regulation task.
The efficacy of real-time functional magnetic resonance imaging neurofeedback for psychiatric illness: A meta-analysis of brain and behavioral outcomes. [2022]Real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) has gained popularity as an experimental treatment for a variety of psychiatric illnesses. However, there has yet to be a quantitative review regarding its efficacy. Here, we present the first meta-analysis of rtfMRI-NF for psychiatric disorders, evaluating its impact on brain and behavioral outcomes. Our literature review identified 17 studies and 105 effect sizes across brain and behavioral outcomes. We find that rtfMRI-NF produces a medium-sized effect on neural activity during training (g = .59, 95 % CI [.44, .75], p
Real-time fMRI neurofeedback as a new treatment for psychiatric disorders: A meta-analysis. [2022]Neurofeedback using real-time functional MRI (RT-fMRI-NF) is an innovative technique that allows to voluntarily modulate a targeted brain response and its associated behavior. Despite promising results in the current literature, its effectiveness on symptoms management in psychiatric disorders is not yet clearly demonstrated. Here, we provide 1) a state-of-art qualitative review of RT-fMRI-NF studies aiming at alleviating clinical symptoms in a psychiatric population; 2) a quantitative evaluation (meta-analysis) of RT-fMRI-NF effectiveness on various psychiatric disorders and 3) methodological suggestions for future studies. Thirty-one clinical trials focusing on psychiatric disorders were included and categorized according to standard diagnostic categories. Among the 31 identified studies, 22 consisted of controlled trials, of which only eight showed significant clinical improvement in the experimental vs. control group after the training. Nine studies found an effect at follow-up on ADHD symptoms, emotion dysregulation, facial emotion processing, depressive symptoms, hallucinations, psychotic symptoms, and specific phobia. Within-group meta-analysis revealed large effects of the NF training on depressive symptoms right after the training (g = 0.81, p
Neurofeedback and networks of depression. [2021]Recent advances in imaging technology and in the understanding of neural circuits relevant to emotion, motivation, and depression have boosted interest and experimental work in neuromodulation for affective disorders. Real-time functional magnetic resonance imaging (fMRI) can be used to train patients in the self regulation of these circuits, and thus complement existing neurofeedback technologies based on electroencephalography (EEG). EEG neurofeedback for depression has mainly been based on models of altered hemispheric asymmetry. fMRI-based neurofeedback (fMRI-NF) can utilize functional localizer scans that allow the dynamic adjustment of the target areas or networks for self-regulation training to individual patterns of emotion processing. An initial application of fMRI-NF in depression has produced promising clinical results, and further clinical trials are under way. Challenges lie in the design of appropriate control conditions for rigorous clinical trials, and in the transfer of neurofeedback protocols from the laboratory to mobile devices to enhance the sustainability of any clinical benefits.
Clinical Application of Real-Time fMRI-Based Neurofeedback for Depression. [2021]Real-time functional magnetic resonance imaging-based neurofeedback (rt-fMRI NF) is a recent technique used to train self-regulation of circumscribed brain areas or networks. For clinical applications in depression, NF training targets brain areas with disturbed activation patterns, such as heightened reactivity of amygdala in response to negative stimuli, in order to normalize the neurophysiology and their behavioral correlates. Recent studies have targeted emotion processing areas such as the amygdala, the salience network, and top-down control areas such as the lateral prefrontal cortex. Different methods of rt-fMRI-based NF in depression, their potential for clinical improvement, and most recent advancements of this technology are discussed considering their role for future clinical applications. Initial findings of randomized controlled trials show promising results. However, for lasting treatment effects, clinical efficiency and optimal target regions, tasks, control conditions, and duration of training need to be established.
Individual- and Connectivity-Based Real-Time fMRI Neurofeedback to Modulate Emotion-Related Brain Responses in Patients with Depression: A Pilot Study. [2022]Individual real-time functional magnetic resonance imaging neurofeedback (rtfMRI NF) might be a promising adjuvant in treating depressive symptoms. Further studies showed functional variations and connectivity-related changes in the dorsolateral prefrontal cortex (dlPFC) and the insular cortex.