Neurofeedback in Psychiatry: A Decade of Clinical and Neuroimaging Insights

Neurofeedback in Psychiatry: A Decade of Clinical and Neuroimaging Insights | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Neurofeedback in Psychiatry: A Decade of Clinical and Neuroimaging Insights Justin Raj, Nishant Goyal, Reethu Raphy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6556201/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Neurofeedback (NF) has emerged as a promising neuromodulation therapy in psychiatry, offering real-time feedback to help patients self-regulate brain activity. Over the past decade, NF applications across psychiatric disorders have been extensively studied. Objective We systematically reviewed NF research in psychiatry (2015–2025), including all study types, to evaluate clinical outcomes, mechanisms, training protocols, and neuroimaging findings in ADHD, depression, anxiety disorders, PTSD, and schizophrenia. Methods A comprehensive literature search identified clinical studies using EEG, fMRI, or other modalities. We included randomized trials, open-label studies, case series, and meta-analyses. Data on NF protocols, symptom outcomes, and neurophysiological measures were synthesized. Results Across disorders, NF was generally associated with symptom improvements. In ADHD, randomized trials and meta-analyses report moderate improvements in attention and impulsivity that often persist at follow-up. Depression studies using EEG and real-time fMRI show symptom reductions, though sample sizes remain modest. Anxiety-spectrum disorders, including PTSD, demonstrate significant symptom reductions, with meta-analytic effect sizes nearing one standard deviation. PTSD shows robust evidence, with a meta-analysis of 17 studies supporting sustained improvements. Schizophrenia studies suggest NF can reduce positive and negative symptoms, particularly using SMR and beta protocols. Neuroimaging confirms NF-induced brain activity and connectivity changes paralleling symptom improvements. Conclusions NF shows durable clinical benefits with minimal adverse effects, supporting its potential as an adjunctive treatment. However, methodological variability warrants further rigorous studies optimizing protocols, controls, and mechanistic investigations. Neurofeedback Psychiatric Disorders Self-Regulation Neuroimaging Clinical Outcomes Introduction Neurofeedback (NF) is a form of biofeedback enabling individuals to gain voluntary control over brain activity through real-time feedback and reinforcement (Doren et al., 2019 ). Neural signals, typically electroencephalogram (EEG) rhythms or functional MRI signals, are monitored and fed back visually or auditorily to facilitate brain self-regulation. During training sessions, desired changes in brain activity are reinforced using positive feedback, often presented through games or displays (Doren et al., 2019 ). Repeated sessions are hypothesized to induce neuroplastic changes, promoting sustained improvements in self-regulation and symptom reduction (Opera et al., 2024). Interest in neurofeedback (NF) as a psychiatric therapeutic tool has grown substantially over the past decade, driven by its non-invasive, medication-free nature and its ability to target specific neural dysregulations (Duan et al., 2025 ). Unlike pharmacotherapy, which broadly affects neuromodulatory systems, NF offers more precise modulation of relevant brain regions with fewer side effects (Duan et al., 2025 ). Early EEG-based NF studies in the late 20th century demonstrated that patients with attention-deficit/hyperactivity disorder (ADHD) and epilepsy could learn to alter brainwave patterns and improve clinical outcomes. Since then, NF has been applied to ADHD, mood disorders (major depression, dysthymia), anxiety disorders (generalized anxiety, phobias, obsessive-compulsive disorder), post-traumatic stress disorder (PTSD), and schizophrenia. Protocols are tailored to neural abnormalities, such as training sensorimotor rhythm in ADHD or normalizing frontal alpha asymmetry in depression (Doren et al., 2019 ). Despite promising reports, the clinical efficacy and mechanisms of neurofeedback (NF) remain debated. Early reviews noted mixed results and suggested that improvements might stem from placebo or non-specific effects, such as patient engagement or therapist interaction, rather than brain self-regulation (Doren et al., 2019 ). Studies have varied in training protocols, feedback algorithms, session duration, and outcome measures, with small sample sizes and inadequate blinding complicating interpretation (Doren et al., 2019 ). Over the past decade, research has emphasized larger randomized controlled trials (RCTs), sham-controlled designs, meta-analyses, and neuroimaging to verify NF-induced brain changes. New modalities such as real-time fMRI neurofeedback (rt-fMRI NF) and functional near-infrared spectroscopy (fNIRS) NF have emerged, allowing feedback targeting deep brain regions involved in emotion and connectivity (Opera et al., 2024). Given the rapid expansion of neurofeedback (NF) research in psychiatry, a comprehensive review of recent literature is warranted. Here, we present a systematic review of studies published from 2015 to 2025 on NF for psychiatric disorders, encompassing all study designs (case reports to randomized controlled trials) to capture clinical breadth. We synthesize findings on: (1) clinical outcomes of NF interventions in major psychiatric conditions (ADHD, depression, anxiety disorders, PTSD, schizophrenia); (2) training protocols and paradigms (EEG vs. fMRI, targeted frequency bands or regions, session parameters); (3) underlying mechanisms and learning processes, including neural plasticity; and (4) neuroimaging and neurophysiological findings informing NF’s effects. We also discuss strengths, limitations, and future directions, aiming to clarify current evidence and guide future research and clinical application in mental health care. Methods Literature Search and Selection We conducted a systematic search of the literature from January 2015 through March 2025 to identify studies evaluating neurofeedback interventions in psychiatric conditions. The search strategy utilized multiple databases, including PubMed, PsycINFO, Web of Science, and Scopus. Key search terms included combinations of “neurofeedback” or “EEG biofeedback” or “real-time fMRI” with specific disorders (e.g., “ADHD”, “depression”, “anxiety”, “PTSD”, “schizophrenia”, “OCD”, “bipolar”, etc.) and outcome-related terms (e.g., “symptoms”, “RCT”, “clinical trial”, “EEG”, “fMRI”, “connectivity”). We also searched reference lists of relevant review articles and meta-analyses for additional studies. All study types were considered, reflecting our goal of inclusivity: randomized controlled trials, non-randomized and open-label trials, single-case studies, case series, and meta-analyses/systematic reviews were included if they reported clinical or neurophysiological outcomes of a neurofeedback intervention in patients with a diagnosed psychiatric disorder. We included both pediatric and adult populations. Exclusion criteria were: studies not involving a clinical sample (e.g. basic research on healthy participants unless directly tied to mechanisms relevant for clinical translation), studies of biofeedback targeting exclusively peripheral signals (e.g. heart rate variability) without any direct neurofeedback component, and articles not available in English. Two reviewers independently screened titles and abstracts for relevance. Potentially eligible full-text articles were then retrieved and evaluated against inclusion criteria. Disagreements on inclusion were resolved through discussion or consultation with a third reviewer. Given the heterogeneity of study designs, we did not impose a strict quality cutoff; even exploratory studies were included to ensure comprehensive coverage. However, when summarizing results, we considered study quality (e.g. presence of control group, sample size) in interpreting the level of evidence. Data Extraction and Synthesis From each included study, we extracted key data regarding: the psychiatric condition and sample characteristics, the type of NF modality (e.g., EEG, fMRI, etc.) and training protocol used (targeted brain activity, reinforcement paradigm, number and length of sessions), presence of control groups (sham feedback, treatment-as-usual, waitlist, etc.), clinical outcome measures (symptom rating scales, behavioral or cognitive tests), and main results on outcomes. We also noted any reported neurobiological measures (EEG changes, fMRI activation/connectivity changes, or other biomarkers) and adverse events. For meta-analyses, we recorded the aggregate effect size estimates for NF vs control on relevant outcomes. Given the narrative nature of this review, we qualitatively synthesized findings across studies for each condition. We first organize results by psychiatric disorder, summarizing the evidence of NF efficacy and key aspects of protocols. Within each disorder, we highlight notable studies (e.g. large RCTs or meta-analyses) and then discuss patterns or discrepancies among the broader literature. We next integrate neuroimaging findings and mechanistic insights, comparing evidence across disorders to identify common principles or unique mechanisms. Throughout, we report effect size metrics or statistical significance when available, and we cite representative studies to ground each conclusion in the literature. The review is reported in accordance with PRISMA guidelines for transparency, although a formal PRISMA flow diagram is not included due to the broad scope and inclusion of diverse study designs. Results Attention-Deficit/Hyperactivity Disorder (ADHD) Overview of Studies : ADHD is one of the most extensively studied indications for neurofeedback (NF). Over the past decade, numerous randomized controlled trials (RCTs) and meta-analyses have evaluated EEG-based NF for pediatric ADHD (Doren et al., 2019 ). Most protocols target electrophysiological markers of ADHD, with three standard approaches: (a) Theta/Beta training—reducing the elevated theta/beta ratio by inhibiting slow theta (4–8 Hz) and rewarding beta (15–20 Hz) activity; (b) Sensorimotor Rhythm (SMR) training—enhancing 12–15 Hz oscillations over the sensorimotor cortex to improve behavioral inhibition; and (c) Slow Cortical Potential (SCP) training—modulating DC shifts to enhance attention and preparatory responses (Doren et al., 2019 ). These protocols, grounded in ADHD neurophysiology, are applied with some consistency, though feedback and reward mechanisms vary. More recently, fMRI-based NF has been explored, targeting regulation of default mode network or striatal activity, though EEG-NF remains predominant due to greater accessibility and broader clinical application. Clinical Outcomes Meta-analytic evidence supports neurofeedback (NF) as yielding moderate improvements in core ADHD symptoms, particularly inattention. A 2019 meta-analysis by Van Doren et al. examined 10 RCTs with follow-up data, showing parent-rated inattention improved with a medium effect size (~ 0.6) post-treatment, growing to a large effect (~ 0.8) at 6–12 months (Doren et al., 2019 ). Hyperactivity/impulsivity improved with medium effect sizes (~ 0.5) post-treatment, maintained or slightly increasing at follow-up (~ 0.6). NF’s benefits appeared more durable than non-active controls, with NF groups sustaining or enhancing gains, while placebo groups often regressed (Doren et al., 2019 ), suggesting NF fosters lasting neural changes via procedural learning. Comparisons with stimulant medications indicate that while medications produce larger immediate symptom reductions (e.g., methylphenidate SMD ~ 1.1), NF's effects persist longer, narrowing the gap over time (Doren et al., 2019 ). Some NF-treated children have reduced or discontinued medication, though more systematic evidence is needed. However, not all trials have shown uniformly positive results. A double-blind sham-controlled RCT (Arnold et al., 2021 ) found no significant NF advantage at 13-month follow-up, raising concerns about specificity. Placebo-controlled NF trials face challenges like imperfect blinding (Doren et al., 2019 ). A meta-analysis by the European ADHD Guidelines Group found a small but significant effect (~ 0.3) for NF versus controls on blinded outcomes, with larger effects in unblinded parent ratings (Doren et al., 2019 ). Enduring parent-rated improvements after NF suggest genuine neurobiological change rather than transient placebo effects. Neurophysiological and Mechanistic Findings Many ADHD neurofeedback (NF) studies have measured EEG changes to confirm that targeted brain activity was modified. Successful training is reflected in increased power in rewarded bands (e.g., SMR or beta) and/or decreased power in inhibited bands (e.g., theta) during tasks. Learning curves showing progressive EEG pattern control have been documented (Janssen et al., 2017 ). Several studies link greater EEG changes—such as reductions in theta/beta ratio or improved SCP amplitude control—to larger ADHD symptom improvements (Doren et al., 2019 ), supporting a specific NF effect. Beyond EEG, some studies using fMRI or fNIRS before and after EEG-NF have observed enhanced functional connectivity in attention networks and normalization of atypical activation patterns (e.g., reduced hyperactivity in default-mode regions). Although data remain limited, findings suggest NF may induce broader network-level changes consistent with improved attention regulation. Training Protocol Considerations The lack of standardization in neurofeedback (NF) protocols for ADHD complicates interpretation of results (Doren et al., 2019 ). While most studies use standard protocols (theta/beta, SMR, or SCP), some employ alternative or individualized approaches. Session numbers vary (~ 20–40 + sessions), as does the use of concurrent therapies like medication. Meta-analyses suggest standard protocols yield more consistent outcomes and that an adequate “dose” (~ 30 sessions) is important (Doren et al., 2019 ). NF is generally well-tolerated, with no severe adverse events reported; minor frustration or boredom may occur, but most children enjoy the games. Overall, evidence from the past decade supports NF as a viable ADHD treatment, especially for families seeking non-pharmacological options or adjunctive therapies. Clinical guidelines in some countries now list NF as an evidence-based ADHD treatment, although they emphasize that treatment fidelity and patient engagement are critical for success. Major Depressive Disorder (Depression) Overview of Studies Neurofeedback (NF) applications in depression have expanded, though the evidence base remains smaller than for ADHD. Depression NF studies include EEG- and fMRI-based approaches targeting different neural mechanisms. A common EEG-NF protocol is frontal alpha asymmetry training, aimed at increasing left-frontal activity to promote a positive emotional state. Several open-label studies and at least one placebo-controlled trial (e.g., Choi et al., 2011; Patil et al., 2023 ) reported symptom reductions with active NF versus sham. Other EEG-NF approaches target beta activity (alertness), enhance SMR, or train high-frequency heart-rate variability to address autonomic dysregulation. Real-time fMRI neurofeedback (rt-fMRI NF) enables direct training of emotion-related brain regions like the amygdala, often blunted in depression (Young et al., 2017 ). In a double-blind RCT, Young et al. ( 2017 ) found that patients using rt-fMRI feedback to upregulate left amygdala activity showed significantly greater mood improvements than a sham group. At one-week follow-up, 63% of the NF group met response criteria compared to 12% of controls, with a remission rate of 32% versus 6%. Other rt-fMRI NF studies targeting limbic hyperactivity or enhancing frontal-limbic connectivity have also reported symptom improvements, supporting the feasibility and promise of rt-fMRI NF in depression. Clinical Outcomes Overall, neurofeedback (NF) shows potential for alleviating depressive symptoms, though results are mixed and often pilot-scale. A 2023 systematic review identified about 20 EEG-NF studies over the past decade, with most reporting significant pre- to post-training improvements on depression scales, particularly in open-label designs (Patil et al., 2023 ). In controlled studies, NF groups often outperformed waitlist or treatment-as-usual groups. For instance, in treatment-resistant depression (TRD), Cheon et al. ( 2016 ) found greater reductions in depression severity with EEG-NF plus standard care compared to standard care alone (Patil et al., 2023 ). Although some studies assessed peripheral markers like BDNF, findings were unclear. Nonetheless, improvements in TRD highlight NF’s potential as an adjunctive intervention. Randomized controlled trials (RCTs) specifically isolating NF’s effects remain limited. Sham conditions for EEG-NF are difficult to design; some used replayed or random feedback. In these, active NF generally outperformed sham on mood ratings and cognitive measures (Patil et al., 2023 ). However, at least one sham-controlled study (Mennella et al., 2017 ) found mood improvements in both NF and sham groups, suggesting placebo effects. Thus, while evidence tilts positive, further RCTs with better blinding are needed to draw firm conclusions. Neuroimaging and Mechanisms Both EEG and fMRI studies provide insight into how NF may be working in depression. EEG-NF targeting alpha asymmetry has been shown to shift the asymmetry in the desired direction (i.e. relatively greater left frontal activation) in responders​ (Patil et al., 2023 ). Depressed patients who achieved a more balanced alpha power between hemispheres reported reductions in negative automatic thoughts and improved mood​ (Patil et al., 2023 ). This aligns with the hypothesized mechanism that increasing left frontal activity fosters a more approach-oriented emotional style. fMRI neurofeedback (NF) studies have directly demonstrated changes in brain activation and connectivity. Beyond amygdala upregulation, Young et al. ( 2017 ) found NF training increased the percentage of specific positive memories patients could recall, addressing overgeneral memory retrieval common in depression. Zotev et al. ( 2020 ) showed that training happy emotion circuits not only boosted activity during NF but also enhanced resting-state connectivity between the amygdala and prefrontal cortex, suggesting improved emotion regulation. Other mechanistic findings include EEG spectral changes, with some studies reporting increases in beta and gamma power (linked to cognitive processing), and reductions in peripheral stress markers such as cortisol after NF for stress or depression (Zotev et al., 2020 ). These results highlight the potential of NF to produce both neural and behavioral changes relevant to depressive symptom improvement. Training Protocols : There is considerable diversity in neurofeedback (NF) protocols for depression. Key approaches include: alpha asymmetry training; alpha/theta training (rewarding increased theta and alpha during eyes-closed relaxation to promote calm and insight, originally developed for PTSD/substance use); beta uptraining (to counter slow-wave activity and low arousal); and hemodynamic NF (rt-fMRI targeting emotion regions or hemoencephalography). Typical dosing is 10–20 sessions, though some fMRI-NF studies have reported effects with as few as 2–5 sessions (Zotev et al., 2020 ). An emerging concept is personalized NF: selecting protocols based on individual neurophysiological profiles (e.g., frontal asymmetry or attentional impairments). As of 2025, no consensus "best" protocol for depression has been established, reflecting the disorder’s heterogeneity. Safety and Tolerability NF in depression appears safe. Unlike some medications, NF does not generally induce side effects like sexual dysfunction, weight gain, or sedation. Mild fatigue or frustration can occur, and in rare instances transient headache after EEG-NF has been reported (possibly from muscle tension or staring at a screen). There have been no reports of NF worsening depression; at worst, some patients might feel it was not beneficial. On the positive side, patients often find NF engaging as it gives a sense of agency in their treatment, potentially empowering their self-efficacy in managing their mood​ (Opera et al., 2024). In summary, NF for depression has shown encouraging results, especially in modulating neural circuits of emotion. Clinical improvements have been documented, but evidence is still emerging. The next steps include larger controlled trials and examining how NF might complement established treatments like cognitive-behavioral therapy (for example, using NF to prime the brain for better CBT engagement). Combining NF with psychotherapy or medication is a logical avenue, as NF could alter brain function in a way that makes patients more receptive to other interventions (or vice versa, therapy might enhance NF learning). Anxiety Disorders (including PTSD) Generalized Anxiety and Other Anxiety Disorders Anxiety disorders have also been targets for neurofeedback (NF), with fewer studies than ADHD or depression but growing interest. Many anxiety disorders involve hyperarousal and excessive activity in fear circuits, so NF strategies often aim to enhance relaxation indicators or reduce fast activity. A prominent EEG-NF approach is alpha enhancement training. Increasing alpha power (8–12 Hz), particularly over parietal/occipital regions, induces calm attentiveness to counter anxiety. A controlled trial in Generalized Anxiety Disorder (GAD) patients found that 10 sessions of parietal alpha-NF significantly reduced state and trait anxiety (Hou et al., 2021 ). Improvements appeared after five sessions and strengthened after ten, persisting for a month post-training. Alpha training at either left or right sites produced similar benefits (Hou et al., 2021 ). Other EEG protocols for anxiety include sensorimotor rhythm (SMR) training to enhance relaxation and beta down-training for patients with excessive fast beta, though the latter is less common due to risks of drowsiness. Beyond EEG, some studies have explored fMRI-based neurofeedback (NF) for anxiety and OCD. Pilot trials have targeted the insula, amygdala, or orbitofrontal-striatal circuits, aiming to modulate stress responses or compulsive behaviors. Initial results suggest feasibility and symptom improvement, though larger studies are needed to confirm efficacy. Post-Traumatic Stress Disorder (PTSD) PTSD neurofeedback (NF) research has expanded over the past decade. Early EEG alpha-theta protocols aimed to aid trauma processing by inducing a twilight state, showing symptom relief in veterans. Modern studies have built on this foundation, introducing fMRI-based NF targeting dysregulated fear and memory networks. A 2024 meta-analysis synthesized evidence from 17 RCTs (628 patients), with 10 suitable for quantitative analysis (Voigt et al., 2024 ). NF was associated with significant reductions in PTSD symptoms compared to controls, with moderate to large pooled effect sizes. Follow-up assessments often showed maintained or even enhanced gains, suggesting lasting self-regulation skills, mirroring patterns seen in ADHD research. The quality of evidence, assessed by GRADE criteria, was rated moderate to high (Voigt et al., 2024 ). Newer NF techniques, particularly rt-fMRI targeting deep brain regions, yielded stronger effects. For example, a double-blind trial showed that NF patients significantly reduced amygdala activation compared to a sham group, with better PTSD outcomes (Zhao et al., 2023 ). Similarly, van der Kolk et al. ( 2016 ) found that EEG-NF (alpha-theta training) led to greater symptom reduction and affect regulation improvements compared to waitlist controls, with some patients no longer meeting PTSD diagnostic criteria. Neuroimaging and Mechanisms in PTSD/Anxiety : Neurofeedback (NF) directly targeting brain regions in PTSD allows clear mechanistic observations: patients can learn to alter activity in threat-processing centers. After amygdala-downregulation NF, patients showed reduced amygdala responses to trauma cues and strengthened prefrontal control. EEG-NF studies reported increased resting alpha power (calmer brain) and decreased high-beta power (reduced hyperarousal). Alpha-theta NF has been associated with higher theta/alpha ratios during sessions, promoting deep relaxation and vivid imagery. This state may facilitate memory reconsolidation, potentially aiding trauma reprocessing, although this remains theoretical. Functional imaging pre- and post-neurofeedback (NF) is rare for generalized anxiety or panic, but it is likely that NF reduces overactivity in limbic and default mode regions implicated in anxiety. A 2022 meta-analysis by Russo et al. found that NF interventions across anxiety-spectrum disorders (including PTSD) led to nearly a one standard deviation reduction in symptoms (SMD ~ -0.9) compared to baseline or controls (Russo et al., 2022 ). This robust effect suggests significant central nervous system changes. Despite this efficacy, the authors noted that NF remains classified as “experimental” by many payers, calling for broader recognition. Protocols and Training for Anxiety/PTSD Alongside alpha/theta and alpha-increase protocols, some practitioners combine heart rate variability (HRV) biofeedback with neurofeedback (NF) for anxiety, though neural NF remains more common in research. PTSD studies typically provide 20–30 NF sessions, while fMRI-NF studies use fewer (3–5 sessions) but still report significant, rapid brain changes Safety Neurofeedback (NF) for anxiety and PTSD has not shown significant adverse effects. Unlike some exposure therapies, NF is generally tolerable as patients focus on brain signals rather than directly reliving trauma. Even in designs incorporating memory recall, the process remains under patient control. Many PTSD participants describe NF sessions, particularly alpha-theta training, as relaxing or even spiritual, likely due to the deep meditative states induced. If a patient becomes overly emotional, sessions can be paused, though such instances are rare. Overall, NF offers a gentle method to modulate fear networks from the "inside out". Schizophrenia Overview of Studies Schizophrenia involves positive, negative, and cognitive symptoms, with traditional medications mainly addressing psychosis (Duan et al., 2025 ). Neurofeedback (NF) has been explored as an adjunct therapy to improve symptoms medications may not fully resolve. Most research uses EEG-NF alongside antipsychotics, with few studies employing fMRI or other modalities. Early evidence for neurofeedback (NF) in schizophrenia came from case reports and small trials, with larger RCTs emerging recently, particularly in China. A 2025 meta-analysis (Duan et al.) identified 14 RCTs (N = 1371) comparing NF plus medication to medication alone, offering a clearer view of NF’s potential. Clinical Outcomes : The meta-analysis found that adding EEG-neurofeedback (NF) to pharmacological treatment significantly improved both positive and negative symptoms of schizophrenia compared to medication alone (Duan et al., 2025 ). Pooled effect sizes were SMD = -0.87 for positive symptoms and SMD = -1.28 for negative symptoms, favoring NF augmentation (Duan et al., 2025 ). Subgroup analyses revealed that older patients (≥ 45 years) benefited more, showing larger improvements. Higher NF dose—at least 8 weeks and four sessions per week (≥ 32 sessions total)—was associated with greater symptom reductions (Duan et al., 2025 ). Chronicity also mattered: longer illness duration (≥ 5 years) predicted better positive symptom improvement, while shorter duration (< 5 years) was linked to greater negative symptom gains. This suggests early NF may prevent consolidation of negative symptoms, while chronic patients can still benefit regarding persistent psychotic symptoms. Several studies in the meta-analysis reported improvements on standardized scales like the Positive and Negative Syndrome Scale (PANSS), with greater reductions in positive and negative symptoms in NF groups. Some studies also noted cognitive gains (e.g., attention, working memory), although cognitive outcomes were not consistently assessed across trials. Training Protocols Most neurofeedback (NF) trials in schizophrenia used SMR or beta uptraining protocols, aiming to enhance sensorimotor rhythm (12–15 Hz) or low beta (15–20 Hz) activity (Duan et al., 2025 ). Increasing these rhythms may stabilize thalamocortical circuits and improve information processing. The meta-analysis found that SMR and beta-targeted protocols were associated with significant improvements in both positive and negative symptoms (Duan et al., 2025 ). Some studies also targeted frontal theta/beta ratios or increased frontal alpha power to reduce cognitive noise and enhance executive function. Additionally, one group used slow cortical potential (SCP) training, teaching patients to generate positive SCP shifts to potentially downregulate hyperexcitability linked to hallucinations. SCP learning correlated with some symptom improvement, though sample sizes were small (Opera et al., 2024). A unique aspect in schizophrenia NF is that often it’s paired with cognitive or psychosocial rehabilitation. For instance, a protocol might involve NF feedback that is contingent on not only brain activity but also performance in a cognitive task (like a working memory game). This hybrid approach tries to directly link brain self-regulation to functional outcomes. Neurophysiological Findings : Schizophrenia neurofeedback (NF) studies have documented various brain changes. EEG outcomes include increased SMR or beta power post-training, as intended. Some studies also reported normalization of EEG microstate properties, often disrupted in schizophrenia. Neuroimaging findings, though fewer, showed similar effects: PET scans revealed increased frontal metabolic activity, and fMRI demonstrated enhanced activation of task-positive networks during cognitive tasks. These objective changes align with patient-reported improvements in concentration and motivation, suggesting broader neural and functional recovery. The MDPI 2024 review emphasized that NF induces lasting brain changes, with neuroimaging and EEG showing persistent effects beyond training (Opera et al., 2024). This indicates true neural plasticity, supporting NF’s potential for durable therapeutic impact in schizophrenia. Mechanistically, NF may improve positive symptoms by reinforcing neural rhythms that enhance sensory gating and reduce aberrant activity. For example, increasing low-beta (~ 18 Hz) in the left temporal lobe has been linked to reduced auditory hallucinations. For negative symptoms, NF may enhance frontal engagement and reward system function by targeting frontal beta or parietal alpha rhythms. Evidence suggesting greater gains in younger patients for negative symptoms hints that early neuroplasticity could be leveraged to improve functional outcomes. Safety and Feasibility Working with schizophrenia patients on neurofeedback (NF) can be challenging due to cognitive deficits and occasional paranoia, but studies report that most patients tolerate NF well and find it engaging. No serious adverse events are known apart from occasional frustration. Care is taken to ensure patients understand the process. Although theoretically NF could reinforce pathological patterns if protocols are poorly chosen, protocols typically target beneficial frequencies, and early monitoring ensures safety. No studies have reported increases in psychotic symptoms; instead, symptom reductions are consistently observed, supporting NF’s safety and feasibility in this population. Overall efficacy While neurofeedback (NF) in schizophrenia is emerging, evidence shows patients can learn to control brain activity, leading to symptom improvement. Combining NF with medication appears more effective than medication alone (Duan et al., 2025 ), supporting an integrative approach focused on functional recovery and patient empowerment in modern psychiatry. Other Psychiatric Conditions Although our primary focus is on the above major disorders, it is worth noting that neurofeedback has also been explored in other conditions over the past decade: Substance Use Disorders : Building on early studies in alcoholism (the Peniston protocol of alpha-theta training), recent trials have applied NF in stimulant use disorder and opioid use disorder. Some have found that alpha-theta NF can reduce craving and improve abstinence duration, presumably by improving stress tolerance and emotional regulation. However, sample sizes are small and there is risk of bias. Autism Spectrum Disorder (ASD) : NF has been investigated as a tool to improve attention and reduce stereotyped behaviors in ASD. Multiple uncontrolled studies show improvements in ADHD-like symptoms in autistic children after NF. One RCT in 2019 found NF improved social responsiveness modestly. Still, more research is needed to validate NF specifically for core ASD symptoms. Bipolar Disorder : Very limited research exists, but a few case studies attempted NF training (e.g., alpha asymmetry) for bipolar depression or for stabilization. Some mood improvement was reported, but it’s too preliminary to draw conclusions. Insomnia : Though not a psychiatric illness per se, insomnia often co-occurs with anxiety/depression. NF protocols like SMR uptraining can improve sleep quality. Some controlled trials in primary insomnia showed NF yielded longer sleep duration and better sleep efficiency compared to sham. Each of these areas merits mention as part of the broad landscape of NF in mental health, but the level of evidence ranges from preliminary to moderate. Discussion Over the last ten years, neurofeedback has transitioned from a niche, somewhat experimental therapy to a more mainstream consideration in the realm of psychiatric treatment. Our systematic review of the literature from 2015–2025 reveals that NF has been applied to a wide spectrum of mental health conditions with generally positive outcomes. Below, we discuss the implications of these findings, the proposed mechanisms of NF’s action, challenges in the field, and future directions for research and clinical practice. Efficacy Across Disorders In synthesizing results, neurofeedback (NF) appears to offer at least modest efficacy across multiple disorders, with the strongest evidence in ADHD and PTSD. In ADHD, NF consistently produces medium effect size symptom reductions that often persist for months, suggesting durable self-regulation rather than transient symptom masking (Doren et al., 2019 ). This durability hints that NF could alter developmental trajectories if applied early. In PTSD, NF yields substantial symptom reductions (Voigt et al., 2024 ), which is notable given the chronic, refractory nature of many participants. Incorporating fMRI-guided NF seems to enhance outcomes by training specific neural circuits of fear and memory (Voigt et al., 2024 ). For depression and anxiety disorders, the evidence is promising but mixed. While many studies report improvements, rigorous controls highlight that NF’s effects may vary across patients, likely reflecting neurobiological heterogeneity. Meta-analytic data for anxiety-spectrum disorders are encouraging (Russo et al., 2022 ), though condition-specific analyses (e.g., NF for GAD vs. OCD) are still needed. Schizophrenia NF research remains early but promising, especially regarding negative symptom improvement—a domain few interventions effectively address. If replicated, NF could become a valuable component of comprehensive schizophrenia care, promoting functional recovery through neural self-modulation. Mechanisms of Action : A key question is how neurofeedback (NF) leads to clinical changes. The likely mechanism is reinforcement learning-induced neuroplasticity (Doren et al., 2019 ; Opera et al., 2024). NF engages the brain’s reward system: when patients produce desired brain patterns, rewards (points, auditory/visual cues) dopaminergically reinforce the involved networks (Lubianiker et al., 2022 ). Repeated reinforcement strengthens synaptic connections, akin to practicing a mental skill. Lasting EEG/fMRI changes, such as normalized theta/beta ratios in ADHD or sustained frontal alpha increases in depression, suggest trait-level neuroplasticity (Opera et al., 2024). NF may also leverage cognitive-behavioral mechanisms, fostering concentration, relaxation, and an internal locus of control over mental processes. NF likely alters large-scale brain networks. Increasing beta/SMR rhythms may suppress inappropriate default mode network (DMN) activity, improving focus in ADHD and schizophrenia, while alpha training may downregulate hyperactive circuits, reducing anxiety or PTSD hypervigilance. fMRI-NF provides mechanistic specificity by showing that patients can modulate subcortical structures like the amygdala and ventral striatum, offering causal evidence for symptom links (Young et al., 2017 ). Although some improvements may stem from non-specific factors, NF imparts active learning. Unlike placebo effects, which usually wane, NF-related gains often increase at follow-up, supporting genuine neuroplastic change (Doren et al., 2019 ). Neuroimaging Correlates Our review highlights that many neurofeedback (NF) studies include direct measures of brain changes, a major strength compared to therapies where mechanisms are inferred indirectly. EEG studies confirm that NF trainees can willfully alter brain oscillations as trained. fMRI studies show changes in connectivity, such as stronger frontal-limbic coupling after emotion-regulation NF in depression, while PET scans reveal increased cerebral blood flow in engaged regions. These findings reinforce NF’s neurobiological impact. Particularly compelling are brain-behavior correlations, such as reductions in theta/beta ratio correlating with improved inattention in ADHD (Doren et al., 2019 ) or increases in left frontal activation correlating with mood improvement in depression, validating that NF targets are symptom-relevant. Advantages and Limitations Neurofeedback (NF) offers a personalized, patient-centered treatment approach, tailoring training to individual brain profiles. It is engaging, often experienced as a game, and empowering, fostering a sense of agency. NF has a strong safety profile, with no significant psychiatric side effects documented (Duan et al., 2025 ), contrasting with medication risks. It can also be combined synergistically with medications, therapy, or neurostimulation, potentially enhancing overall treatment outcomes. Neurofeedback (NF) faces challenges, including the time commitment of 20–40 sessions and issues with adherence. Variability in response is another concern; while some patients show strong learning and symptom improvement, others show minimal change. Research is exploring factors like motivation, attention, and genetics influencing NF trainability. Methodological challenges persist in neurofeedback (NF) research, as true double-blinding is difficult; participants often detect sham feedback. Although engaging sham protocols have been attempted, expectancy effects remain a concern. Experts recommend emphasizing objective outcomes, such as cognitive tests or blinded observer ratings, to strengthen NF trial validity. Lack of standardization in neurofeedback (NF) protocols complicates comparisons across studies. Consensus on protocol selection and standardized manuals are needed. The CRED-nf checklist (Duan et al., 2025 ) offers guidelines to improve study design and reporting, and wider adoption will help aggregate evidence more reliably across sites. Future Directions The next decade of NF research is poised to refine and expand this therapy. Key future directions include Large-Scale Controlled Trials : Especially for conditions like depression and anxiety, more multicenter RCTs with adequate power are needed to conclusively establish efficacy. These trials should incorporate sham controls or comparative treatments (e.g., compare NF to cognitive training or meditation) to parse specific effects. Mechanistic Studies : Further work using neuroimaging (fMRI, EEG source localization, MEG) during and after NF can elucidate how brain networks reconfigure with training. Questions such as “Does NF increase neurochemical markers of plasticity (like BDNF)?”, “What changes in functional connectivity underlie the clinical improvements?” and “How does the brain’s reward system encode NF learning?” remain ripe for exploration. Personalization and Adaptive Protocols : Rather than a one-size-fits-all, NF could become more adaptive. For example, machine learning algorithms might adjust the difficulty or targets in real-time based on patient progress (“closed-loop” adaptations). If a patient plateaus, the system could switch to a different frequency band or add a secondary target (like coherence between two regions) to encourage further learning. Combining NF with Other Therapies : Some studies already hint at benefits of combining NF with standard treatments (e.g., medication in schizophrenia​ (Duan et al., 2025 ), therapy in PTSD). Future research could formally test NF as an augmentation strategy: does adding NF to exposure therapy improve outcomes in PTSD by calming the brain between sessions? Could NF before a therapy session prime the brain for neuroplasticity, akin to how exercise has pro-cognitive effects? There is also interest in pairing NF with brain stimulation (like transcranial magnetic stimulation) – for instance, using NF to maintain the effects of TMS for depression by teaching the patient to keep brain activity in the desired state after stimulation. New Modalities and Targets : Technological advances might broaden NF’s capabilities. Functional near-infrared spectroscopy (fNIRS) NF is being explored for its portability – one could imagine home-based NF training using a simple fNIRS headband for conditions like anxiety or ADHD. Magnetoencephalography (MEG) NF could target very specific oscillatory activity with high spatial precision, though cost is an issue. Additionally, NF targeting novel signals (e.g., coherence between brain regions, or even peripheral-neural signals combined) could open up new ways to influence complex emotional states. Understanding Individual Differences : Research should also focus on why some people respond better to NF. Are there neural indicators (like better initial neural flexibility, or particular EEG phenotypes) that predict NF success? If so, those could be used to personalize therapy or to counsel patients on likely benefit. Clinical Implementation Considerations As evidence grows, we may see NF clinics becoming more common. For clinicians considering NF, it is crucial to manage expectations – NF is not a magic bullet or a rapid fix; it requires active patient participation over multiple weeks. Proper screening for patients who are likely to engage (and who have the time/resources) is important. Additionally, integrating NF with a holistic treatment plan (including psychosocial support) is recommended, rather than viewing it as a standalone cure. In terms of insurance and acceptance, accumulating meta-analytic support (like that by Russo et al. for anxiety​ (Russo et al., 2022 ) and others for ADHD) is pivotal. With evidence of efficacy and cost analyses showing that NF’s effects can last (potentially reducing long-term costs of care), more healthcare systems may cover NF in the future. Limitations of the Current Review We synthesized a wide array of studies, which introduces some limitations. The inclusion of non-RCT studies means some positive findings might be from less controlled contexts. We attempted to highlight meta-analyses and RCT results as more reliable indicators. Also, different disorders have different volumes of research – our treatment of each is necessarily uneven (with ADHD and PTSD having detailed data, whereas others like OCD had sparse coverage). Nonetheless, by spanning multiple conditions, we aimed to capture general trends and the versatility of NF. Conclusion Neurofeedback (NF) has evolved over the past decade from an experimental idea to a therapy with growing evidence across psychiatry. This review demonstrates that NF can facilitate meaningful improvements in ADHD, mood disorders, anxiety disorders (including PTSD), schizophrenia, and more, with many gains sustained beyond training (Doren et al., 2019 ; Voigt et al., 2024 ). NF induces objective shifts in brain function, highlighting its capacity for neuroplasticity and self-regulation (Opera et al., 2024). With minimal risk, NF serves as a safe adjunct or alternative to traditional interventions. In ADHD and PTSD, it fosters lasting skills; in schizophrenia, it addresses negative symptoms and cognitive deficits often resistant to medication (Duan et al., 2025 ). However, NF is not a panacea. Challenges remain in standardization, placebo control, and training consistency. More rigorous trials are needed to refine protocols and define optimal applications. Nevertheless, NF exemplifies a shift toward empowering patients to modify their brain states. As neuroscience and technology advance, NF’s role is likely to expand, aligning with the future of personalized mental health care. Embracing neurofeedback could open new therapeutic frontiers, leveraging the brain’s adaptability as a core strategy for treating psychiatric illness. Declarations Funding and Disclosure No specific funding was obtained for this review. The authors declare no conflicts of interest. Author Contribution J.R. and N.G. conceptualized the review and designed the methodology. J.R. conducted the literature search, data extraction, and wrote the initial draft of the manuscript. R.R. contributed to literature synthesis and editing of the manuscript. N.G. supervised the project and provided critical revisions. All authors reviewed and approved the final version of the manuscript. References Arnold, L. E., Arns, M., Barterian, J., Bergman, R., Black, S., Conners, C. K., ... & Williams, C. E. (2021). Double-blind placebo-controlled randomized clinical trial of neurofeedback for attention-deficit/hyperactivity disorder with 13-month follow-up. Journal of the american academy of child & adolescent psychiatry, 60(7), 841-855. https://doi.org/10.1016/j.jaac.2020.07.906 Cheon, E. J., Koo, B. H., & Choi, J. H. (2016). The efficacy of neurofeedback in patients with major depressive disorder: An open labeled prospective study. Applied psychophysiology and biofeedback, 41, 103-110. https://doi:10.1007/s10484-015-9315-8 Duan, Y., Li, S., Jia, S., Yu, F., Wang, X., & Long, Y. (2025). Systematic review and meta-analysis of the effects of EEG neurofeedback combined with pharmacological treatment on the positive and negative symptoms in patients with schizophrenia. Frontiers in Psychiatry, 16, 1537329. https://doi.org/10.3389/fpsyt.2025.1537329 Duan, Y., Li, S., Jia, S., Yu, F., Wang, X., & Long, Y. (2025). Systematic review and meta-analysis of the effects of EEG neurofeedback combined with pharmacological treatment on the positive and negative symptoms in patients with schizophrenia. Frontiers in Psychiatry, 16, 1537329. https://doi.org/10.3389/fpsyt.2025.1537329 Hou, Y., Zhang, S., Li, N., Huang, Z., Wang, L., & Wang, Y. (2021). Neurofeedback training improves anxiety trait and depressive symptom in GAD. Brain and behavior, 11(3), e02024. https://doi.org/10.1002/brb3.2024 Janssen, T. W., Bink, M., Weeda, W. D., Geladé, K., van Mourik, R., Maras, A., & Oosterlaan, J. (2017). Learning curves of theta/beta neurofeedback in children with ADHD. European Child & Adolescent Psychiatry, 26, 573–582. https://doi.org/10.1007/s00787-016-0920-8 Lubianiker, N., Paret, C., Dayan, P., & Hendler, T. (2022). Neurofeedback through the lens of reinforcement learning. Trends in Neurosciences, 45(8), 579-593. https://doi.org/10.1016/j.tins.2022.03.008 Mennella, R., Patron, E., & Palomba, D. (2017). Frontal alpha asymmetry neurofeedback for the reduction of negative affect and anxiety. Behaviour research and therapy, 92, 32-40. https://doi:10.1016/j.brat.2017.02.002 Oprea, D. C., Mawas, I., Moroșan, C. A., Iacob, V. T., Cămănaru, E. M., Cristofor, A. C., Dobrin, R. P., Gireadă, B., Petrariu, F. D., & Chiriță, R. (2024). A Systematic Review of the Effects of EEG Neurofeedback on Patients with Schizophrenia. Journal of Personalized Medicine, 14(7), 763. https://doi.org/10.3390/jpm14070763 Patil, A. U., Lin, C., Lee, S. H., Huang, H. W., Wu, S. C., Madathil, D., & Huang, C. M. (2023). Review of EEG-based neurofeedback as a therapeutic intervention to treat depression. Psychiatry research. Neuroimaging, 329, 111591. https://doi.org/10.1016/j.pscychresns.2023.111591 Russo, G. M., Balkin, R. S., & Lenz, A. S. (2022). "A Meta-Analysis of Neurofeedback for Treating Anxiety-Spectrum Disorders". Journal of Counseling & Development, 100(3), 236-251. https://doi.org/10.1002/jcad.12424 Van der Kolk, B. A., Hodgdon, H., Gapen, M., Musicaro, R., Suvak, M. K., Hamlin, E., & Spinazzola, J. (2016). A randomized controlled study of neurofeedback for chronic PTSD. PloS one, 11(12), e0166752. https://doi.org/10.1371/journal.pone.0166752 Van Doren, J., Arns, M., Heinrich, H., Vollebregt, M. A., Strehl, U., & K Loo, S. (2019). Sustained effects of neurofeedback in ADHD: a systematic review and meta-analysis. European child & adolescent psychiatry, 28(3), 293–305. https://doi.org/10.1007/s00787-018-1121-4 Voigt, J. D., Mosier, M., & Tendler, A. (2024). Systematic review and meta-analysis of neurofeedback and its effect on posttraumatic stress disorder. Frontiers in Psychiatry, 15, 1323485. https://doi.org/10.3389/fpsyt.2024.1323485 Young, K. D., Siegle, G. J., Zotev, V., Phillips, R., Misaki, M., Yuan, H., Drevets, W. C., & Bodurka, J. (2017). Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall. The American journal of psychiatry, 174(8), 748–755. https://doi.org/10.1176/appi.ajp.2017.16060637 Zhao, Z., Duek, O., Seidemann, R., Gordon, C., Walsh, C., Romaker, E., ... & Harpaz-Rotem, I. (2023). Amygdala downregulation training using fMRI neurofeedback in post-traumatic stress disorder: a randomized, double-blind trial. Translational psychiatry, 13(1), 177. https://doi.org/10.1038/s41398-023-02467-6 Zotev, V., Mayeli, A., Misaki, M., & Bodurka, J. (2020). Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback. NeuroImage. Clinical, 27, 102331. https://doi.org/10.1016/j.nicl.2020.102331 Additional Declarations No competing interests reported. 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Neural signals, typically electroencephalogram (EEG) rhythms or functional MRI signals, are monitored and fed back visually or auditorily to facilitate brain self-regulation. During training sessions, desired changes in brain activity are reinforced using positive feedback, often presented through games or displays (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Repeated sessions are hypothesized to induce neuroplastic changes, promoting sustained improvements in self-regulation and symptom reduction (Opera et al., 2024).\u003c/p\u003e \u003cp\u003eInterest in neurofeedback (NF) as a psychiatric therapeutic tool has grown substantially over the past decade, driven by its non-invasive, medication-free nature and its ability to target specific neural dysregulations (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Unlike pharmacotherapy, which broadly affects neuromodulatory systems, NF offers more precise modulation of relevant brain regions with fewer side effects (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Early EEG-based NF studies in the late 20th century demonstrated that patients with attention-deficit/hyperactivity disorder (ADHD) and epilepsy could learn to alter brainwave patterns and improve clinical outcomes. Since then, NF has been applied to ADHD, mood disorders (major depression, dysthymia), anxiety disorders (generalized anxiety, phobias, obsessive-compulsive disorder), post-traumatic stress disorder (PTSD), and schizophrenia. Protocols are tailored to neural abnormalities, such as training sensorimotor rhythm in ADHD or normalizing frontal alpha asymmetry in depression (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite promising reports, the clinical efficacy and mechanisms of neurofeedback (NF) remain debated. Early reviews noted mixed results and suggested that improvements might stem from placebo or non-specific effects, such as patient engagement or therapist interaction, rather than brain self-regulation (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Studies have varied in training protocols, feedback algorithms, session duration, and outcome measures, with small sample sizes and inadequate blinding complicating interpretation (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Over the past decade, research has emphasized larger randomized controlled trials (RCTs), sham-controlled designs, meta-analyses, and neuroimaging to verify NF-induced brain changes. New modalities such as real-time fMRI neurofeedback (rt-fMRI NF) and functional near-infrared spectroscopy (fNIRS) NF have emerged, allowing feedback targeting deep brain regions involved in emotion and connectivity (Opera et al., 2024).\u003c/p\u003e \u003cp\u003eGiven the rapid expansion of neurofeedback (NF) research in psychiatry, a comprehensive review of recent literature is warranted. Here, we present a systematic review of studies published from 2015 to 2025 on NF for psychiatric disorders, encompassing all study designs (case reports to randomized controlled trials) to capture clinical breadth. We synthesize findings on: (1) clinical outcomes of NF interventions in major psychiatric conditions (ADHD, depression, anxiety disorders, PTSD, schizophrenia); (2) training protocols and paradigms (EEG vs. fMRI, targeted frequency bands or regions, session parameters); (3) underlying mechanisms and learning processes, including neural plasticity; and (4) neuroimaging and neurophysiological findings informing NF\u0026rsquo;s effects. We also discuss strengths, limitations, and future directions, aiming to clarify current evidence and guide future research and clinical application in mental health care.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eLiterature Search and Selection\u003c/h2\u003e \u003cp\u003eWe conducted a systematic search of the literature from January 2015 through March 2025 to identify studies evaluating neurofeedback interventions in psychiatric conditions. The search strategy utilized multiple databases, including PubMed, PsycINFO, Web of Science, and Scopus. Key search terms included combinations of \u0026ldquo;neurofeedback\u0026rdquo; or \u0026ldquo;EEG biofeedback\u0026rdquo; or \u0026ldquo;real-time fMRI\u0026rdquo; with specific disorders (e.g., \u0026ldquo;ADHD\u0026rdquo;, \u0026ldquo;depression\u0026rdquo;, \u0026ldquo;anxiety\u0026rdquo;, \u0026ldquo;PTSD\u0026rdquo;, \u0026ldquo;schizophrenia\u0026rdquo;, \u0026ldquo;OCD\u0026rdquo;, \u0026ldquo;bipolar\u0026rdquo;, etc.) and outcome-related terms (e.g., \u0026ldquo;symptoms\u0026rdquo;, \u0026ldquo;RCT\u0026rdquo;, \u0026ldquo;clinical trial\u0026rdquo;, \u0026ldquo;EEG\u0026rdquo;, \u0026ldquo;fMRI\u0026rdquo;, \u0026ldquo;connectivity\u0026rdquo;). We also searched reference lists of relevant review articles and meta-analyses for additional studies.\u003c/p\u003e \u003cp\u003eAll study types were considered, reflecting our goal of inclusivity: randomized controlled trials, non-randomized and open-label trials, single-case studies, case series, and meta-analyses/systematic reviews were included if they reported clinical or neurophysiological outcomes of a neurofeedback intervention in patients with a diagnosed psychiatric disorder. We included both pediatric and adult populations. Exclusion criteria were: studies not involving a clinical sample (e.g. basic research on healthy participants unless directly tied to mechanisms relevant for clinical translation), studies of biofeedback targeting exclusively peripheral signals (e.g. heart rate variability) without any direct neurofeedback component, and articles not available in English.\u003c/p\u003e \u003cp\u003eTwo reviewers independently screened titles and abstracts for relevance. Potentially eligible full-text articles were then retrieved and evaluated against inclusion criteria. Disagreements on inclusion were resolved through discussion or consultation with a third reviewer. Given the heterogeneity of study designs, we did not impose a strict quality cutoff; even exploratory studies were included to ensure comprehensive coverage. However, when summarizing results, we considered study quality (e.g. presence of control group, sample size) in interpreting the level of evidence.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Extraction and Synthesis\u003c/h3\u003e\n\u003cp\u003eFrom each included study, we extracted key data regarding: the psychiatric condition and sample characteristics, the type of NF modality (e.g., EEG, fMRI, etc.) and training protocol used (targeted brain activity, reinforcement paradigm, number and length of sessions), presence of control groups (sham feedback, treatment-as-usual, waitlist, etc.), clinical outcome measures (symptom rating scales, behavioral or cognitive tests), and main results on outcomes. We also noted any reported neurobiological measures (EEG changes, fMRI activation/connectivity changes, or other biomarkers) and adverse events. For meta-analyses, we recorded the aggregate effect size estimates for NF vs control on relevant outcomes.\u003c/p\u003e \u003cp\u003e Given the narrative nature of this review, we qualitatively synthesized findings across studies for each condition. We first organize results by psychiatric disorder, summarizing the evidence of NF efficacy and key aspects of protocols. Within each disorder, we highlight notable studies (e.g. large RCTs or meta-analyses) and then discuss patterns or discrepancies among the broader literature. We next integrate neuroimaging findings and mechanistic insights, comparing evidence across disorders to identify common principles or unique mechanisms. Throughout, we report effect size metrics or statistical significance when available, and we cite representative studies to ground each conclusion in the literature. The review is reported in accordance with PRISMA guidelines for transparency, although a formal PRISMA flow diagram is not included due to the broad scope and inclusion of diverse study designs.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eAttention-Deficit/Hyperactivity Disorder (ADHD)\u003c/h2\u003e \u003cp\u003e \u003cem\u003eOverview of Studies\u003c/em\u003e: ADHD is one of the most extensively studied indications for neurofeedback (NF). Over the past decade, numerous randomized controlled trials (RCTs) and meta-analyses have evaluated EEG-based NF for pediatric ADHD (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Most protocols target electrophysiological markers of ADHD, with three standard approaches: (a) Theta/Beta training\u0026mdash;reducing the elevated theta/beta ratio by inhibiting slow theta (4\u0026ndash;8 Hz) and rewarding beta (15\u0026ndash;20 Hz) activity; (b) Sensorimotor Rhythm (SMR) training\u0026mdash;enhancing 12\u0026ndash;15 Hz oscillations over the sensorimotor cortex to improve behavioral inhibition; and (c) Slow Cortical Potential (SCP) training\u0026mdash;modulating DC shifts to enhance attention and preparatory responses (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These protocols, grounded in ADHD neurophysiology, are applied with some consistency, though feedback and reward mechanisms vary. More recently, fMRI-based NF has been explored, targeting regulation of default mode network or striatal activity, though EEG-NF remains predominant due to greater accessibility and broader clinical application.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eClinical Outcomes\u003c/strong\u003e \u003cp\u003eMeta-analytic evidence supports neurofeedback (NF) as yielding moderate improvements in core ADHD symptoms, particularly inattention. A 2019 meta-analysis by Van Doren et al. examined 10 RCTs with follow-up data, showing parent-rated inattention improved with a medium effect size (~\u0026thinsp;0.6) post-treatment, growing to a large effect (~\u0026thinsp;0.8) at 6\u0026ndash;12 months (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Hyperactivity/impulsivity improved with medium effect sizes (~\u0026thinsp;0.5) post-treatment, maintained or slightly increasing at follow-up (~\u0026thinsp;0.6). NF\u0026rsquo;s benefits appeared more durable than non-active controls, with NF groups sustaining or enhancing gains, while placebo groups often regressed (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), suggesting NF fosters lasting neural changes via procedural learning.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eComparisons with stimulant medications indicate that while medications produce larger immediate symptom reductions (e.g., methylphenidate SMD\u0026thinsp;~\u0026thinsp;1.1), NF's effects persist longer, narrowing the gap over time (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Some NF-treated children have reduced or discontinued medication, though more systematic evidence is needed.\u003c/p\u003e \u003cp\u003eHowever, not all trials have shown uniformly positive results. A double-blind sham-controlled RCT (Arnold et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found no significant NF advantage at 13-month follow-up, raising concerns about specificity. Placebo-controlled NF trials face challenges like imperfect blinding (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). A meta-analysis by the European ADHD Guidelines Group found a small but significant effect (~\u0026thinsp;0.3) for NF versus controls on blinded outcomes, with larger effects in unblinded parent ratings (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Enduring parent-rated improvements after NF suggest genuine neurobiological change rather than transient placebo effects.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNeurophysiological and Mechanistic Findings\u003c/strong\u003e \u003cp\u003eMany ADHD neurofeedback (NF) studies have measured EEG changes to confirm that targeted brain activity was modified. Successful training is reflected in increased power in rewarded bands (e.g., SMR or beta) and/or decreased power in inhibited bands (e.g., theta) during tasks. Learning curves showing progressive EEG pattern control have been documented (Janssen et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Several studies link greater EEG changes\u0026mdash;such as reductions in theta/beta ratio or improved SCP amplitude control\u0026mdash;to larger ADHD symptom improvements (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), supporting a specific NF effect. Beyond EEG, some studies using fMRI or fNIRS before and after EEG-NF have observed enhanced functional connectivity in attention networks and normalization of atypical activation patterns (e.g., reduced hyperactivity in default-mode regions). Although data remain limited, findings suggest NF may induce broader network-level changes consistent with improved attention regulation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTraining Protocol Considerations\u003c/strong\u003e \u003cp\u003eThe lack of standardization in neurofeedback (NF) protocols for ADHD complicates interpretation of results (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). While most studies use standard protocols (theta/beta, SMR, or SCP), some employ alternative or individualized approaches. Session numbers vary (~\u0026thinsp;20\u0026ndash;40\u0026thinsp;+\u0026thinsp;sessions), as does the use of concurrent therapies like medication. Meta-analyses suggest standard protocols yield more consistent outcomes and that an adequate \u0026ldquo;dose\u0026rdquo; (~\u0026thinsp;30 sessions) is important (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). NF is generally well-tolerated, with no severe adverse events reported; minor frustration or boredom may occur, but most children enjoy the games. Overall, evidence from the past decade supports NF as a viable ADHD treatment, especially for families seeking non-pharmacological options or adjunctive therapies. Clinical guidelines in some countries now list NF as an evidence-based ADHD treatment, although they emphasize that treatment fidelity and patient engagement are critical for success.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMajor Depressive Disorder (Depression)\u003c/h3\u003e\n\u003cp\u003e \u003cstrong\u003eOverview of Studies\u003c/strong\u003e \u003cp\u003eNeurofeedback (NF) applications in depression have expanded, though the evidence base remains smaller than for ADHD. Depression NF studies include EEG- and fMRI-based approaches targeting different neural mechanisms. A common EEG-NF protocol is frontal alpha asymmetry training, aimed at increasing left-frontal activity to promote a positive emotional state. Several open-label studies and at least one placebo-controlled trial (e.g., Choi et al., 2011; Patil et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) reported symptom reductions with active NF versus sham. Other EEG-NF approaches target beta activity (alertness), enhance SMR, or train high-frequency heart-rate variability to address autonomic dysregulation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eReal-time fMRI neurofeedback (rt-fMRI NF) enables direct training of emotion-related brain regions like the amygdala, often blunted in depression (Young et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In a double-blind RCT, Young et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found that patients using rt-fMRI feedback to upregulate left amygdala activity showed significantly greater mood improvements than a sham group. At one-week follow-up, 63% of the NF group met response criteria compared to 12% of controls, with a remission rate of 32% versus 6%. Other rt-fMRI NF studies targeting limbic hyperactivity or enhancing frontal-limbic connectivity have also reported symptom improvements, supporting the feasibility and promise of rt-fMRI NF in depression.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eClinical Outcomes\u003c/strong\u003e \u003cp\u003eOverall, neurofeedback (NF) shows potential for alleviating depressive symptoms, though results are mixed and often pilot-scale. A 2023 systematic review identified about 20 EEG-NF studies over the past decade, with most reporting significant pre- to post-training improvements on depression scales, particularly in open-label designs (Patil et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In controlled studies, NF groups often outperformed waitlist or treatment-as-usual groups. For instance, in treatment-resistant depression (TRD), Cheon et al. (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found greater reductions in depression severity with EEG-NF plus standard care compared to standard care alone (Patil et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Although some studies assessed peripheral markers like BDNF, findings were unclear. Nonetheless, improvements in TRD highlight NF\u0026rsquo;s potential as an adjunctive intervention.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eRandomized controlled trials (RCTs) specifically isolating NF\u0026rsquo;s effects remain limited. Sham conditions for EEG-NF are difficult to design; some used replayed or random feedback. In these, active NF generally outperformed sham on mood ratings and cognitive measures (Patil et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). However, at least one sham-controlled study (Mennella et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found mood improvements in both NF and sham groups, suggesting placebo effects. Thus, while evidence tilts positive, further RCTs with better blinding are needed to draw firm conclusions.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNeuroimaging and Mechanisms\u003c/strong\u003e \u003cp\u003eBoth EEG and fMRI studies provide insight into how NF may be working in depression. EEG-NF targeting alpha asymmetry has been shown to shift the asymmetry in the desired direction (i.e. relatively greater left frontal activation) in responders​ (Patil et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Depressed patients who achieved a more balanced alpha power between hemispheres reported reductions in negative automatic thoughts and improved mood​ (Patil et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This aligns with the hypothesized mechanism that increasing left frontal activity fosters a more approach-oriented emotional style.\u003c/p\u003e \u003c/p\u003e \u003cp\u003efMRI neurofeedback (NF) studies have directly demonstrated changes in brain activation and connectivity. Beyond amygdala upregulation, Young et al. (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) found NF training increased the percentage of specific positive memories patients could recall, addressing overgeneral memory retrieval common in depression. Zotev et al. (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) showed that training happy emotion circuits not only boosted activity during NF but also enhanced resting-state connectivity between the amygdala and prefrontal cortex, suggesting improved emotion regulation. Other mechanistic findings include EEG spectral changes, with some studies reporting increases in beta and gamma power (linked to cognitive processing), and reductions in peripheral stress markers such as cortisol after NF for stress or depression (Zotev et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These results highlight the potential of NF to produce both neural and behavioral changes relevant to depressive symptom improvement.\u003c/p\u003e \u003cp\u003e \u003cem\u003eTraining Protocols\u003c/em\u003e: There is considerable diversity in neurofeedback (NF) protocols for depression. Key approaches include: alpha asymmetry training; alpha/theta training (rewarding increased theta and alpha during eyes-closed relaxation to promote calm and insight, originally developed for PTSD/substance use); beta uptraining (to counter slow-wave activity and low arousal); and hemodynamic NF (rt-fMRI targeting emotion regions or hemoencephalography). Typical dosing is 10\u0026ndash;20 sessions, though some fMRI-NF studies have reported effects with as few as 2\u0026ndash;5 sessions (Zotev et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). An emerging concept is personalized NF: selecting protocols based on individual neurophysiological profiles (e.g., frontal asymmetry or attentional impairments). As of 2025, no consensus \"best\" protocol for depression has been established, reflecting the disorder\u0026rsquo;s heterogeneity.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSafety and Tolerability\u003c/strong\u003e \u003cp\u003eNF in depression appears safe. Unlike some medications, NF does not generally induce side effects like sexual dysfunction, weight gain, or sedation. Mild fatigue or frustration can occur, and in rare instances transient headache after EEG-NF has been reported (possibly from muscle tension or staring at a screen). There have been no reports of NF worsening depression; at worst, some patients might feel it was not beneficial. On the positive side, patients often find NF engaging as it gives a sense of agency in their treatment, potentially empowering their self-efficacy in managing their mood​ (Opera et al., 2024).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eIn summary, NF for depression has shown encouraging results, especially in modulating neural circuits of emotion. Clinical improvements have been documented, but evidence is still emerging. The next steps include larger controlled trials and examining how NF might complement established treatments like cognitive-behavioral therapy (for example, using NF to prime the brain for better CBT engagement). Combining NF with psychotherapy or medication is a logical avenue, as NF could alter brain function in a way that makes patients more receptive to other interventions (or vice versa, therapy might enhance NF learning).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnxiety Disorders (including PTSD)\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eGeneralized Anxiety and Other Anxiety Disorders\u003c/strong\u003e \u003cp\u003eAnxiety disorders have also been targets for neurofeedback (NF), with fewer studies than ADHD or depression but growing interest. Many anxiety disorders involve hyperarousal and excessive activity in fear circuits, so NF strategies often aim to enhance relaxation indicators or reduce fast activity. A prominent EEG-NF approach is alpha enhancement training. Increasing alpha power (8\u0026ndash;12 Hz), particularly over parietal/occipital regions, induces calm attentiveness to counter anxiety. A controlled trial in Generalized Anxiety Disorder (GAD) patients found that 10 sessions of parietal alpha-NF significantly reduced state and trait anxiety (Hou et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Improvements appeared after five sessions and strengthened after ten, persisting for a month post-training. Alpha training at either left or right sites produced similar benefits (Hou et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Other EEG protocols for anxiety include sensorimotor rhythm (SMR) training to enhance relaxation and beta down-training for patients with excessive fast beta, though the latter is less common due to risks of drowsiness.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eBeyond EEG, some studies have explored fMRI-based neurofeedback (NF) for anxiety and OCD. Pilot trials have targeted the insula, amygdala, or orbitofrontal-striatal circuits, aiming to modulate stress responses or compulsive behaviors. Initial results suggest feasibility and symptom improvement, though larger studies are needed to confirm efficacy.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003ePost-Traumatic Stress Disorder (PTSD)\u003c/strong\u003e \u003cp\u003ePTSD neurofeedback (NF) research has expanded over the past decade. Early EEG alpha-theta protocols aimed to aid trauma processing by inducing a twilight state, showing symptom relief in veterans. Modern studies have built on this foundation, introducing fMRI-based NF targeting dysregulated fear and memory networks. A 2024 meta-analysis synthesized evidence from 17 RCTs (628 patients), with 10 suitable for quantitative analysis (Voigt et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). NF was associated with significant reductions in PTSD symptoms compared to controls, with moderate to large pooled effect sizes. Follow-up assessments often showed maintained or even enhanced gains, suggesting lasting self-regulation skills, mirroring patterns seen in ADHD research. The quality of evidence, assessed by GRADE criteria, was rated moderate to high (Voigt et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eNewer NF techniques, particularly rt-fMRI targeting deep brain regions, yielded stronger effects. For example, a double-blind trial showed that NF patients significantly reduced amygdala activation compared to a sham group, with better PTSD outcomes (Zhao et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Similarly, van der Kolk et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) found that EEG-NF (alpha-theta training) led to greater symptom reduction and affect regulation improvements compared to waitlist controls, with some patients no longer meeting PTSD diagnostic criteria.\u003c/p\u003e \u003cp\u003e \u003cem\u003eNeuroimaging and Mechanisms in PTSD/Anxiety\u003c/em\u003e: Neurofeedback (NF) directly targeting brain regions in PTSD allows clear mechanistic observations: patients can learn to alter activity in threat-processing centers. After amygdala-downregulation NF, patients showed reduced amygdala responses to trauma cues and strengthened prefrontal control. EEG-NF studies reported increased resting alpha power (calmer brain) and decreased high-beta power (reduced hyperarousal). Alpha-theta NF has been associated with higher theta/alpha ratios during sessions, promoting deep relaxation and vivid imagery. This state may facilitate memory reconsolidation, potentially aiding trauma reprocessing, although this remains theoretical.\u003c/p\u003e \u003cp\u003eFunctional imaging pre- and post-neurofeedback (NF) is rare for generalized anxiety or panic, but it is likely that NF reduces overactivity in limbic and default mode regions implicated in anxiety. A 2022 meta-analysis by Russo et al. found that NF interventions across anxiety-spectrum disorders (including PTSD) led to nearly a one standard deviation reduction in symptoms (SMD ~ -0.9) compared to baseline or controls (Russo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This robust effect suggests significant central nervous system changes. Despite this efficacy, the authors noted that NF remains classified as \u0026ldquo;experimental\u0026rdquo; by many payers, calling for broader recognition.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eProtocols and Training for Anxiety/PTSD\u003c/strong\u003e \u003cp\u003eAlongside alpha/theta and alpha-increase protocols, some practitioners combine heart rate variability (HRV) biofeedback with neurofeedback (NF) for anxiety, though neural NF remains more common in research. PTSD studies typically provide 20\u0026ndash;30 NF sessions, while fMRI-NF studies use fewer (3\u0026ndash;5 sessions) but still report significant, rapid brain changes\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSafety\u003c/strong\u003e \u003cp\u003eNeurofeedback (NF) for anxiety and PTSD has not shown significant adverse effects. Unlike some exposure therapies, NF is generally tolerable as patients focus on brain signals rather than directly reliving trauma. Even in designs incorporating memory recall, the process remains under patient control. Many PTSD participants describe NF sessions, particularly alpha-theta training, as relaxing or even spiritual, likely due to the deep meditative states induced. If a patient becomes overly emotional, sessions can be paused, though such instances are rare. Overall, NF offers a gentle method to modulate fear networks from the \"inside out\".\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSchizophrenia\u003c/h3\u003e\n\u003cp\u003e \u003cstrong\u003eOverview of Studies\u003c/strong\u003e \u003cp\u003eSchizophrenia involves positive, negative, and cognitive symptoms, with traditional medications mainly addressing psychosis (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Neurofeedback (NF) has been explored as an adjunct therapy to improve symptoms medications may not fully resolve. Most research uses EEG-NF alongside antipsychotics, with few studies employing fMRI or other modalities. Early evidence for neurofeedback (NF) in schizophrenia came from case reports and small trials, with larger RCTs emerging recently, particularly in China. A 2025 meta-analysis (Duan et al.) identified 14 RCTs (N\u0026thinsp;=\u0026thinsp;1371) comparing NF plus medication to medication alone, offering a clearer view of NF\u0026rsquo;s potential.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eClinical Outcomes\u003c/em\u003e: The meta-analysis found that adding EEG-neurofeedback (NF) to pharmacological treatment significantly improved both positive and negative symptoms of schizophrenia compared to medication alone (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Pooled effect sizes were SMD = -0.87 for positive symptoms and SMD = -1.28 for negative symptoms, favoring NF augmentation (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Subgroup analyses revealed that older patients (\u0026ge;\u0026thinsp;45 years) benefited more, showing larger improvements. Higher NF dose\u0026mdash;at least 8 weeks and four sessions per week (\u0026ge;\u0026thinsp;32 sessions total)\u0026mdash;was associated with greater symptom reductions (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Chronicity also mattered: longer illness duration (\u0026ge;\u0026thinsp;5 years) predicted better positive symptom improvement, while shorter duration (\u0026lt;\u0026thinsp;5 years) was linked to greater negative symptom gains. This suggests early NF may prevent consolidation of negative symptoms, while chronic patients can still benefit regarding persistent psychotic symptoms.\u003c/p\u003e \u003cp\u003eSeveral studies in the meta-analysis reported improvements on standardized scales like the Positive and Negative Syndrome Scale (PANSS), with greater reductions in positive and negative symptoms in NF groups. Some studies also noted cognitive gains (e.g., attention, working memory), although cognitive outcomes were not consistently assessed across trials.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eTraining Protocols\u003c/strong\u003e \u003cp\u003eMost neurofeedback (NF) trials in schizophrenia used SMR or beta uptraining protocols, aiming to enhance sensorimotor rhythm (12\u0026ndash;15 Hz) or low beta (15\u0026ndash;20 Hz) activity (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Increasing these rhythms may stabilize thalamocortical circuits and improve information processing. The meta-analysis found that SMR and beta-targeted protocols were associated with significant improvements in both positive and negative symptoms (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Some studies also targeted frontal theta/beta ratios or increased frontal alpha power to reduce cognitive noise and enhance executive function. Additionally, one group used slow cortical potential (SCP) training, teaching patients to generate positive SCP shifts to potentially downregulate hyperexcitability linked to hallucinations. SCP learning correlated with some symptom improvement, though sample sizes were small (Opera et al., 2024).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eA unique aspect in schizophrenia NF is that often it\u0026rsquo;s paired with cognitive or psychosocial rehabilitation. For instance, a protocol might involve NF feedback that is contingent on not only brain activity but also performance in a cognitive task (like a working memory game). This hybrid approach tries to directly link brain self-regulation to functional outcomes.\u003c/p\u003e \u003cp\u003e \u003cem\u003eNeurophysiological Findings\u003c/em\u003e: Schizophrenia neurofeedback (NF) studies have documented various brain changes. EEG outcomes include increased SMR or beta power post-training, as intended. Some studies also reported normalization of EEG microstate properties, often disrupted in schizophrenia. Neuroimaging findings, though fewer, showed similar effects: PET scans revealed increased frontal metabolic activity, and fMRI demonstrated enhanced activation of task-positive networks during cognitive tasks. These objective changes align with patient-reported improvements in concentration and motivation, suggesting broader neural and functional recovery.\u003c/p\u003e \u003cp\u003eThe MDPI 2024 review emphasized that NF induces lasting brain changes, with neuroimaging and EEG showing persistent effects beyond training (Opera et al., 2024). This indicates true neural plasticity, supporting NF\u0026rsquo;s potential for durable therapeutic impact in schizophrenia. Mechanistically, NF may improve positive symptoms by reinforcing neural rhythms that enhance sensory gating and reduce aberrant activity. For example, increasing low-beta (~\u0026thinsp;18 Hz) in the left temporal lobe has been linked to reduced auditory hallucinations. For negative symptoms, NF may enhance frontal engagement and reward system function by targeting frontal beta or parietal alpha rhythms. Evidence suggesting greater gains in younger patients for negative symptoms hints that early neuroplasticity could be leveraged to improve functional outcomes.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSafety and Feasibility\u003c/strong\u003e \u003cp\u003eWorking with schizophrenia patients on neurofeedback (NF) can be challenging due to cognitive deficits and occasional paranoia, but studies report that most patients tolerate NF well and find it engaging. No serious adverse events are known apart from occasional frustration. Care is taken to ensure patients understand the process. Although theoretically NF could reinforce pathological patterns if protocols are poorly chosen, protocols typically target beneficial frequencies, and early monitoring ensures safety. No studies have reported increases in psychotic symptoms; instead, symptom reductions are consistently observed, supporting NF\u0026rsquo;s safety and feasibility in this population.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOverall efficacy\u003c/strong\u003e \u003cp\u003eWhile neurofeedback (NF) in schizophrenia is emerging, evidence shows patients can learn to control brain activity, leading to symptom improvement. Combining NF with medication appears more effective than medication alone (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), supporting an integrative approach focused on functional recovery and patient empowerment in modern psychiatry.\u003c/p\u003e \u003c/p\u003e\n\u003ch3\u003eOther Psychiatric Conditions\u003c/h3\u003e\n\u003cp\u003eAlthough our primary focus is on the above major disorders, it is worth noting that neurofeedback has also been explored in other conditions over the past decade:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eSubstance Use Disorders\u003c/em\u003e: Building on early studies in alcoholism (the Peniston protocol of alpha-theta training), recent trials have applied NF in stimulant use disorder and opioid use disorder. Some have found that alpha-theta NF can reduce craving and improve abstinence duration, presumably by improving stress tolerance and emotional regulation. However, sample sizes are small and there is risk of bias.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eAutism Spectrum Disorder (ASD)\u003c/em\u003e: NF has been investigated as a tool to improve attention and reduce stereotyped behaviors in ASD. Multiple uncontrolled studies show improvements in ADHD-like symptoms in autistic children after NF. One RCT in 2019 found NF improved social responsiveness modestly. Still, more research is needed to validate NF specifically for core ASD symptoms.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eBipolar Disorder\u003c/em\u003e: Very limited research exists, but a few case studies attempted NF training (e.g., alpha asymmetry) for bipolar depression or for stabilization. Some mood improvement was reported, but it\u0026rsquo;s too preliminary to draw conclusions.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eInsomnia\u003c/em\u003e: Though not a psychiatric illness per se, insomnia often co-occurs with anxiety/depression. NF protocols like SMR uptraining can improve sleep quality. Some controlled trials in primary insomnia showed NF yielded longer sleep duration and better sleep efficiency compared to sham.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eEach of these areas merits mention as part of the broad landscape of NF in mental health, but the level of evidence ranges from preliminary to moderate.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOver the last ten years, neurofeedback has transitioned from a niche, somewhat experimental therapy to a more mainstream consideration in the realm of psychiatric treatment. Our systematic review of the literature from 2015\u0026ndash;2025 reveals that NF has been applied to a wide spectrum of mental health conditions with generally positive outcomes. Below, we discuss the implications of these findings, the proposed mechanisms of NF\u0026rsquo;s action, challenges in the field, and future directions for research and clinical practice.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEfficacy Across Disorders\u003c/strong\u003e \u003cp\u003eIn synthesizing results, neurofeedback (NF) appears to offer at least modest efficacy across multiple disorders, with the strongest evidence in ADHD and PTSD. In ADHD, NF consistently produces medium effect size symptom reductions that often persist for months, suggesting durable self-regulation rather than transient symptom masking (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This durability hints that NF could alter developmental trajectories if applied early. In PTSD, NF yields substantial symptom reductions (Voigt et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), which is notable given the chronic, refractory nature of many participants. Incorporating fMRI-guided NF seems to enhance outcomes by training specific neural circuits of fear and memory (Voigt et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eFor depression and anxiety disorders, the evidence is promising but mixed. While many studies report improvements, rigorous controls highlight that NF\u0026rsquo;s effects may vary across patients, likely reflecting neurobiological heterogeneity. Meta-analytic data for anxiety-spectrum disorders are encouraging (Russo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), though condition-specific analyses (e.g., NF for GAD vs. OCD) are still needed. Schizophrenia NF research remains early but promising, especially regarding negative symptom improvement\u0026mdash;a domain few interventions effectively address. If replicated, NF could become a valuable component of comprehensive schizophrenia care, promoting functional recovery through neural self-modulation.\u003c/p\u003e \u003cp\u003e \u003cem\u003eMechanisms of Action\u003c/em\u003e: A key question is how neurofeedback (NF) leads to clinical changes. The likely mechanism is reinforcement learning-induced neuroplasticity (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Opera et al., 2024). NF engages the brain\u0026rsquo;s reward system: when patients produce desired brain patterns, rewards (points, auditory/visual cues) dopaminergically reinforce the involved networks (Lubianiker et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Repeated reinforcement strengthens synaptic connections, akin to practicing a mental skill. Lasting EEG/fMRI changes, such as normalized theta/beta ratios in ADHD or sustained frontal alpha increases in depression, suggest trait-level neuroplasticity (Opera et al., 2024). NF may also leverage cognitive-behavioral mechanisms, fostering concentration, relaxation, and an internal locus of control over mental processes.\u003c/p\u003e \u003cp\u003eNF likely alters large-scale brain networks. Increasing beta/SMR rhythms may suppress inappropriate default mode network (DMN) activity, improving focus in ADHD and schizophrenia, while alpha training may downregulate hyperactive circuits, reducing anxiety or PTSD hypervigilance. fMRI-NF provides mechanistic specificity by showing that patients can modulate subcortical structures like the amygdala and ventral striatum, offering causal evidence for symptom links (Young et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough some improvements may stem from non-specific factors, NF imparts active learning. Unlike placebo effects, which usually wane, NF-related gains often increase at follow-up, supporting genuine neuroplastic change (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNeuroimaging Correlates\u003c/strong\u003e \u003cp\u003e Our review highlights that many neurofeedback (NF) studies include direct measures of brain changes, a major strength compared to therapies where mechanisms are inferred indirectly. EEG studies confirm that NF trainees can willfully alter brain oscillations as trained. fMRI studies show changes in connectivity, such as stronger frontal-limbic coupling after emotion-regulation NF in depression, while PET scans reveal increased cerebral blood flow in engaged regions. These findings reinforce NF\u0026rsquo;s neurobiological impact. Particularly compelling are brain-behavior correlations, such as reductions in theta/beta ratio correlating with improved inattention in ADHD (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) or increases in left frontal activation correlating with mood improvement in depression, validating that NF targets are symptom-relevant.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eAdvantages and Limitations\u003c/strong\u003e \u003cp\u003eNeurofeedback (NF) offers a personalized, patient-centered treatment approach, tailoring training to individual brain profiles. It is engaging, often experienced as a game, and empowering, fostering a sense of agency. NF has a strong safety profile, with no significant psychiatric side effects documented (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), contrasting with medication risks. It can also be combined synergistically with medications, therapy, or neurostimulation, potentially enhancing overall treatment outcomes.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eNeurofeedback (NF) faces challenges, including the time commitment of 20\u0026ndash;40 sessions and issues with adherence. Variability in response is another concern; while some patients show strong learning and symptom improvement, others show minimal change. Research is exploring factors like motivation, attention, and genetics influencing NF trainability. Methodological challenges persist in neurofeedback (NF) research, as true double-blinding is difficult; participants often detect sham feedback. Although engaging sham protocols have been attempted, expectancy effects remain a concern. Experts recommend emphasizing objective outcomes, such as cognitive tests or blinded observer ratings, to strengthen NF trial validity.\u003c/p\u003e \u003cp\u003eLack of standardization in neurofeedback (NF) protocols complicates comparisons across studies. Consensus on protocol selection and standardized manuals are needed. The CRED-nf checklist (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e) offers guidelines to improve study design and reporting, and wider adoption will help aggregate evidence more reliably across sites.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFuture Directions\u003c/strong\u003e \u003cp\u003eThe next decade of NF research is poised to refine and expand this therapy. Key future directions include\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eLarge-Scale Controlled Trials\u003c/em\u003e: Especially for conditions like depression and anxiety, more multicenter RCTs with adequate power are needed to conclusively establish efficacy. These trials should incorporate sham controls or comparative treatments (e.g., compare NF to cognitive training or meditation) to parse specific effects.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eMechanistic Studies\u003c/em\u003e: Further work using neuroimaging (fMRI, EEG source localization, MEG) during and after NF can elucidate how brain networks reconfigure with training. Questions such as \u0026ldquo;Does NF increase neurochemical markers of plasticity (like BDNF)?\u0026rdquo;, \u0026ldquo;What changes in functional connectivity underlie the clinical improvements?\u0026rdquo; and \u0026ldquo;How does the brain\u0026rsquo;s reward system encode NF learning?\u0026rdquo; remain ripe for exploration.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003ePersonalization and Adaptive Protocols\u003c/em\u003e: Rather than a one-size-fits-all, NF could become more adaptive. For example, machine learning algorithms might adjust the difficulty or targets in real-time based on patient progress (\u0026ldquo;closed-loop\u0026rdquo; adaptations). If a patient plateaus, the system could switch to a different frequency band or add a secondary target (like coherence between two regions) to encourage further learning.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eCombining NF with Other Therapies\u003c/em\u003e: Some studies already hint at benefits of combining NF with standard treatments (e.g., medication in schizophrenia​ (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), therapy in PTSD). Future research could formally test NF as an augmentation strategy: does adding NF to exposure therapy improve outcomes in PTSD by calming the brain between sessions? Could NF before a therapy session prime the brain for neuroplasticity, akin to how exercise has pro-cognitive effects? There is also interest in pairing NF with brain stimulation (like transcranial magnetic stimulation) \u0026ndash; for instance, using NF to maintain the effects of TMS for depression by teaching the patient to keep brain activity in the desired state after stimulation.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eNew Modalities and Targets\u003c/em\u003e: Technological advances might broaden NF\u0026rsquo;s capabilities. Functional near-infrared spectroscopy (fNIRS) NF is being explored for its portability \u0026ndash; one could imagine home-based NF training using a simple fNIRS headband for conditions like anxiety or ADHD. Magnetoencephalography (MEG) NF could target very specific oscillatory activity with high spatial precision, though cost is an issue. Additionally, NF targeting novel signals (e.g., coherence between brain regions, or even peripheral-neural signals combined) could open up new ways to influence complex emotional states.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cem\u003eUnderstanding Individual Differences\u003c/em\u003e: Research should also focus on why some people respond better to NF. Are there neural indicators (like better initial neural flexibility, or particular EEG phenotypes) that predict NF success? If so, those could be used to personalize therapy or to counsel patients on likely benefit.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eClinical Implementation Considerations\u003c/strong\u003e \u003cp\u003e \u003cem\u003eAs\u003c/em\u003e evidence grows, we may see NF clinics becoming more common. For clinicians considering NF, it is crucial to manage expectations \u0026ndash; NF is not a magic bullet or a rapid fix; it requires active patient participation over multiple weeks. Proper screening for patients who are likely to engage (and who have the time/resources) is important. Additionally, integrating NF with a holistic treatment plan (including psychosocial support) is recommended, rather than viewing it as a standalone cure.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eIn terms of insurance and acceptance, accumulating meta-analytic support (like that by Russo et al. for anxiety​ (Russo et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and others for ADHD) is pivotal. With evidence of efficacy and cost analyses showing that NF\u0026rsquo;s effects can last (potentially reducing long-term costs of care), more healthcare systems may cover NF in the future.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLimitations of the Current Review\u003c/strong\u003e \u003cp\u003eWe synthesized a wide array of studies, which introduces some limitations. The inclusion of non-RCT studies means some positive findings might be from less controlled contexts. We attempted to highlight meta-analyses and RCT results as more reliable indicators. Also, different disorders have different volumes of research \u0026ndash; our treatment of each is necessarily uneven (with ADHD and PTSD having detailed data, whereas others like OCD had sparse coverage). Nonetheless, by spanning multiple conditions, we aimed to capture general trends and the versatility of NF.\u003c/p\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eNeurofeedback (NF) has evolved over the past decade from an experimental idea to a therapy with growing evidence across psychiatry. This review demonstrates that NF can facilitate meaningful improvements in ADHD, mood disorders, anxiety disorders (including PTSD), schizophrenia, and more, with many gains sustained beyond training (Doren et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Voigt et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). NF induces objective shifts in brain function, highlighting its capacity for neuroplasticity and self-regulation (Opera et al., 2024). With minimal risk, NF serves as a safe adjunct or alternative to traditional interventions. In ADHD and PTSD, it fosters lasting skills; in schizophrenia, it addresses negative symptoms and cognitive deficits often resistant to medication (Duan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2025\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, NF is not a panacea. Challenges remain in standardization, placebo control, and training consistency. More rigorous trials are needed to refine protocols and define optimal applications. Nevertheless, NF exemplifies a shift toward empowering patients to modify their brain states. As neuroscience and technology advance, NF\u0026rsquo;s role is likely to expand, aligning with the future of personalized mental health care. Embracing neurofeedback could open new therapeutic frontiers, leveraging the brain\u0026rsquo;s adaptability as a core strategy for treating psychiatric illness.\u003c/p\u003e "},{"header":"Declarations","content":"\u003ch2\u003eFunding and Disclosure\u003c/h2\u003e \u003cp\u003eNo specific funding was obtained for this review. The authors declare no conflicts of interest.\u003c/p\u003e \n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.R. and N.G. conceptualized the review and designed the methodology. J.R. conducted the literature search, data extraction, and wrote the initial draft of the manuscript. R.R. contributed to literature synthesis and editing of the manuscript. N.G. supervised the project and provided critical revisions. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArnold, L. E., Arns, M., Barterian, J., Bergman, R., Black, S., Conners, C. K., ... \u0026amp; Williams, C. E. (2021). Double-blind placebo-controlled randomized clinical trial of neurofeedback for attention-deficit/hyperactivity disorder with 13-month follow-up. Journal of the american academy of child \u0026amp; adolescent psychiatry, 60(7), 841-855. https://doi.org/10.1016/j.jaac.2020.07.906\u003c/li\u003e\n\u003cli\u003eCheon, E. J., Koo, B. H., \u0026amp; Choi, J. H. (2016). The efficacy of neurofeedback in patients with major depressive disorder: An open labeled prospective study. Applied psychophysiology and biofeedback, 41, 103-110. https://doi:10.1007/s10484-015-9315-8\u003c/li\u003e\n\u003cli\u003eDuan, Y., Li, S., Jia, S., Yu, F., Wang, X., \u0026amp; Long, Y. (2025). Systematic review and meta-analysis of the effects of EEG neurofeedback combined with pharmacological treatment on the positive and negative symptoms in patients with schizophrenia. Frontiers in Psychiatry, 16, 1537329. https://doi.org/10.3389/fpsyt.2025.1537329\u003c/li\u003e\n\u003cli\u003eDuan, Y., Li, S., Jia, S., Yu, F., Wang, X., \u0026amp; Long, Y. (2025). Systematic review and meta-analysis of the effects of EEG neurofeedback combined with pharmacological treatment on the positive and negative symptoms in patients with schizophrenia. Frontiers in Psychiatry, 16, 1537329. https://doi.org/10.3389/fpsyt.2025.1537329\u003c/li\u003e\n\u003cli\u003eHou, Y., Zhang, S., Li, N., Huang, Z., Wang, L., \u0026amp; Wang, Y. (2021). Neurofeedback training improves anxiety trait and depressive symptom in GAD. Brain and behavior, 11(3), e02024. https://doi.org/10.1002/brb3.2024\u003c/li\u003e\n\u003cli\u003eJanssen, T. W., Bink, M., Weeda, W. D., Gelad\u0026eacute;, K., van Mourik, R., Maras, A., \u0026amp; Oosterlaan, J. (2017). Learning curves of theta/beta neurofeedback in children with ADHD. European Child \u0026amp; Adolescent Psychiatry, 26, 573\u0026ndash;582. https://doi.org/10.1007/s00787-016-0920-8\u003c/li\u003e\n\u003cli\u003eLubianiker, N., Paret, C., Dayan, P., \u0026amp; Hendler, T. (2022). Neurofeedback through the lens of reinforcement learning. Trends in Neurosciences, 45(8), 579-593. https://doi.org/10.1016/j.tins.2022.03.008\u003c/li\u003e\n\u003cli\u003eMennella, R., Patron, E., \u0026amp; Palomba, D. (2017). Frontal alpha asymmetry neurofeedback for the reduction of negative affect and anxiety. Behaviour research and therapy, 92, 32-40. https://doi:10.1016/j.brat.2017.02.002\u003c/li\u003e\n\u003cli\u003eOprea, D. C., Mawas, I., Moroșan, C. A., Iacob, V. T., Cămănaru, E. M., Cristofor, A. C., Dobrin, R. P., Gireadă, B., Petrariu, F. D., \u0026amp; Chiriță, R. (2024). A Systematic Review of the Effects of EEG Neurofeedback on Patients with Schizophrenia. Journal of Personalized Medicine, 14(7), 763. https://doi.org/10.3390/jpm14070763\u003c/li\u003e\n\u003cli\u003ePatil, A. U., Lin, C., Lee, S. H., Huang, H. W., Wu, S. C., Madathil, D., \u0026amp; Huang, C. M. (2023). Review of EEG-based neurofeedback as a therapeutic intervention to treat depression. Psychiatry research. Neuroimaging, 329, 111591. https://doi.org/10.1016/j.pscychresns.2023.111591\u003c/li\u003e\n\u003cli\u003eRusso, G. M., Balkin, R. S., \u0026amp; Lenz, A. S. (2022). \u0026quot;A Meta-Analysis of Neurofeedback for Treating Anxiety-Spectrum Disorders\u0026quot;. Journal of Counseling \u0026amp; Development, 100(3), 236-251. https://doi.org/10.1002/jcad.12424\u003c/li\u003e\n\u003cli\u003eVan der Kolk, B. A., Hodgdon, H., Gapen, M., Musicaro, R., Suvak, M. K., Hamlin, E., \u0026amp; Spinazzola, J. (2016). A randomized controlled study of neurofeedback for chronic PTSD. PloS one, 11(12), e0166752. https://doi.org/10.1371/journal.pone.0166752\u003c/li\u003e\n\u003cli\u003eVan Doren, J., Arns, M., Heinrich, H., Vollebregt, M. A., Strehl, U., \u0026amp; K Loo, S. (2019). Sustained effects of neurofeedback in ADHD: a systematic review and meta-analysis. European child \u0026amp; adolescent psychiatry, 28(3), 293\u0026ndash;305. https://doi.org/10.1007/s00787-018-1121-4\u003c/li\u003e\n\u003cli\u003eVoigt, J. D., Mosier, M., \u0026amp; Tendler, A. (2024). Systematic review and meta-analysis of neurofeedback and its effect on posttraumatic stress disorder. Frontiers in Psychiatry, 15, 1323485. https://doi.org/10.3389/fpsyt.2024.1323485\u003c/li\u003e\n\u003cli\u003eYoung, K. D., Siegle, G. J., Zotev, V., Phillips, R., Misaki, M., Yuan, H., Drevets, W. C., \u0026amp; Bodurka, J. (2017). Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall. The American journal of psychiatry, 174(8), 748\u0026ndash;755. https://doi.org/10.1176/appi.ajp.2017.16060637\u003c/li\u003e\n\u003cli\u003eZhao, Z., Duek, O., Seidemann, R., Gordon, C., Walsh, C., Romaker, E., ... \u0026amp; Harpaz-Rotem, I. (2023). Amygdala downregulation training using fMRI neurofeedback in post-traumatic stress disorder: a randomized, double-blind trial. Translational psychiatry, 13(1), 177. https://doi.org/10.1038/s41398-023-02467-6\u003c/li\u003e\n\u003cli\u003eZotev, V., Mayeli, A., Misaki, M., \u0026amp; Bodurka, J. (2020). Emotion self-regulation training in major depressive disorder using simultaneous real-time fMRI and EEG neurofeedback. NeuroImage. Clinical, 27, 102331. https://doi.org/10.1016/j.nicl.2020.102331\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Neurofeedback, Psychiatric Disorders, Self-Regulation, Neuroimaging, Clinical Outcomes","lastPublishedDoi":"10.21203/rs.3.rs-6556201/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6556201/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNeurofeedback (NF) has emerged as a promising neuromodulation therapy in psychiatry, offering real-time feedback to help patients self-regulate brain activity. Over the past decade, NF applications across psychiatric disorders have been extensively studied.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003e We systematically reviewed NF research in psychiatry (2015\u0026ndash;2025), including all study types, to evaluate clinical outcomes, mechanisms, training protocols, and neuroimaging findings in ADHD, depression, anxiety disorders, PTSD, and schizophrenia.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA comprehensive literature search identified clinical studies using EEG, fMRI, or other modalities. We included randomized trials, open-label studies, case series, and meta-analyses. Data on NF protocols, symptom outcomes, and neurophysiological measures were synthesized.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAcross disorders, NF was generally associated with symptom improvements. In ADHD, randomized trials and meta-analyses report moderate improvements in attention and impulsivity that often persist at follow-up. Depression studies using EEG and real-time fMRI show symptom reductions, though sample sizes remain modest. Anxiety-spectrum disorders, including PTSD, demonstrate significant symptom reductions, with meta-analytic effect sizes nearing one standard deviation. PTSD shows robust evidence, with a meta-analysis of 17 studies supporting sustained improvements. Schizophrenia studies suggest NF can reduce positive and negative symptoms, particularly using SMR and beta protocols. Neuroimaging confirms NF-induced brain activity and connectivity changes paralleling symptom improvements.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNF shows durable clinical benefits with minimal adverse effects, supporting its potential as an adjunctive treatment. However, methodological variability warrants further rigorous studies optimizing protocols, controls, and mechanistic investigations.\u003c/p\u003e","manuscriptTitle":"Neurofeedback in Psychiatry: A Decade of Clinical and Neuroimaging Insights","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-09 10:48:56","doi":"10.21203/rs.3.rs-6556201/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6e7126b9-3c6e-498f-99b1-908948544078","owner":[],"postedDate":"May 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-24T18:23:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-09 10:48:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6556201","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6556201","identity":"rs-6556201","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}