Can electroencephalography-based neurofeedback treat post-traumatic stress disorder? A meta-analysis study

Can electroencephalography-based neurofeedback treat post-traumatic stress disorder? A meta-analysis study | 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 Can electroencephalography-based neurofeedback treat post-traumatic stress disorder? A meta-analysis study Kana Matsuyanagi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3644363/v3 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Mar, 2025 Read the published version in Applied Psychophysiology and Biofeedback → Version 3 posted 9 You are reading this latest preprint version Show more versions Abstract Objective: Post-traumatic stress disorder (PTSD) remains a significant clinical challenge with limited treatment options. Although electroencephalogram (EEG) neurofeedback has garnered attention as a prospective treatment modality for PTSD, no comprehensive meta-analysis has been conducted to assess its efficacy and compare different treatment protocols. This study aims to provide a multi-variable meta-regression analysis of EEG neurofeedback's impact on PTSD symptoms, while also assessing variables that may influence treatment outcomes. Methods: A systematic review was performed to identify controlled studies exploring for the efficacy of EEG neurofeedback on PTSD. The overall effectiveness was evaluated through meta-analysis, and a multi-variable meta-regression was employed to discern fact0rs affecting the EEG neurofeedback efficacy. Results: EEG neurofeedback yielded a statistically significant reduction in PTSD symptoms immediately post-intervention, with sustained effects at one and three months follow-up. A sub-analysis of sham-controlled studies confirmed that outcomes were not driven by placebo effects. Our findings also identified the target frequency and region, as well as feedback modality, as significant factors for treatment success. In contrast, variables related to treatment duration were not found to be significant moderators, suggesting cost-effectiveness. Conclusions: EEG neurofeedback emerges as a promising and cost-effective treatment modality for PTSD with the potential for long-term benefits. Our findings challenge commonly utilized protocols and advocate for further research into alternative methodologies to improve treatment efficacy. PTSD EEG Neurofeedback Meta-analysis Meta-regression Treatment Protocols Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 1 Introduction 1.1 PTSD Post-Traumatic Stress Disorder (PTSD) is a psychiatric disorder that arises in response to experiencing or witnessing a traumatic event (American Psychiatric Association, 2013 ). These can include combat exposure, physical or sexual assault, natural disasters, or accident. The hallmark symptoms of PTSD include intrusive memories, flashbacks, avoidance behaviors, negative alterations in cognition and mood, and hyperarousal. The persistence and intensity of these symptoms can significantly impair an individual's daily functioning, quality of life, and interpersonal relationships. 1.2 Current Treatment Approaches for PTSD Current treatment approaches for PTSD involve psychotherapy and pharmacotherapy (Schrader & Ross, 2021 ). Cognitive-behavioral therapy (CBT), especially exposure therapy, helps modify maladaptive thought patterns and behaviors by encouraging patients to confront traumatic memories in a controlled environment (Schrader & Ross, 2021 ). However, its efficacy depends on patient engagement, and the distress of re-experiencing trauma can lead to dropout or worsened symptoms. Pharmacotherapy, mainly selective serotonin reuptake inhibitors (SSRIs), alleviates symptoms of depression and anxiety, stabilizing mood and improving overall functioning (Schrader & Ross, 2021 ). Limitations include variability in drug efficacy and potential side effects, addressing only symptomatic relief rather than the root cause of PTSD. With these limitations, many individuals still continue to experience chronic symptoms. 1.3 EEG Neurofeedback Electroencephalogram (EEG) neurofeedback is another, less common therapeutic approach in treating PTSD. EEG neurofeedback aims to modulate brainwave activity through real-time feedback (Marzbani et al., 2016 ). This non-invasive method involves training individuals to self-regulate their brain activity by monitoring and receiving feedback on their EEG signals. EEG neurofeedback involves placing electrodes on the scalp to measure electrical activity and targeting specific frequency bands based on symptoms. Individuals receive feedback for their brainwave activity, encouraging self-regulation and achieving desired brain states. Repeated sessions can lead to improved self-regulation and symptom reduction. There is a recent increase of interest in EEG neurofeedback for PTSD treatment. The first study that showed for the first time a significant reduction in PTSD symptoms with the EEG neurofeedback was by Peniston et al. who gave veterans an alpha-theta targeted neurofeedback (Peniston & Kulkosky, 1991 ). Studies indicate that individuals with PTSD exhibit abnormal EEG patterns, such as increased spectral power of low beta waves, which are correlated with high anxiety levels (Shim et al., 2017 ) and EEG neurofeedback can normalize these patterns, potentially promoting better emotional and cognitive functioning. 1.4 Limitations and gaps in knowledge Given the evolving landscape of research on EEG neurofeedback for PTSD, there is a pressing need for a comprehensive meta-analysis that not only assesses its efficacy as a standalone or adjunct treatment but also integrates the wealth of findings emerging from recent studies. While there are four existing meta-analyses on this topic (Choi et al., 2023 ; Hong & Park, 2022 ; Russo et al., 2022 ; Steingrimsson et al., 2020 ), their scopes and methodologies exhibit significant limitations. The analyses from 2022 (Hong & Park, 2022 ; Russo et al., 2022 ) do not account for the surge of recent studies, underscoring the need for an updated review. Another recent analysis (Choi et al., 2023 ) does not distinguish between EEG-based neurofeedback and fMRI-based neurofeedback. As these two methods are considered to have a fundamental difference in their mechanism, it is necessary to evaluate the effect of EEG neurofeedback on PTSD specifically. The fourth analysis (Steingrimsson et al., 2020 ) overlooks the impact of critical moderators such as feedback modality and target brain area, which are crucial for understanding treatment efficacy. Our proposed meta-analysis is distinct in its methodological rigor, aiming to fill these gaps by employing advanced statistical techniques such as meta-regression to explore the impact of various moderators that have been neglected previously. This includes examining the influence of simultaneous treatments, neurofeedback target areas, target frequencies, and feedback modalities on treatment outcomes. Moreover, we conduct detailed subgroup analyses to uncover how demographics, intervention types, and clinical settings differentially affect treatment effectiveness. This approach allows for a comprehensive understanding of EEG neurofeedback’s efficacy across diverse patient populations and treatment environments, moving beyond the generalized findings of prior reviews. Additionally, our study is unique in its effort to connect empirical findings to underlying theoretical frameworks, specifically focusing on the neural network modulation that may underlie the mechanism of neurofeedback effects on PTSD. This integration not only aims to elucidate the therapeutic mechanisms of EEG neurofeedback but also to guide future research and clinical practice by linking observed outcomes to neurobiological processes. By synthesizing the latest evidence, including the most recent studies, our meta-analysis seeks to overcome the limitations inherent in individual investigations, offering robust conclusions about the effectiveness of EEG neurofeedback for PTSD. Our comprehensive approach aims to evaluate the efficacy of EEG neurofeedback, reveal the most effective feedback protocols and intervention designs, and, crucially, to advance our theoretical understanding of its mechanisms. 2 Method 2.1 Search strategy To identify relevant studies, a comprehensive search was conducted across multiple databases, including PubMed, ScienceDirect, ClinicalTrials.gov, and the Wiley Online Library. This search covered the period up to and including December 2023 from December 2012, to ensure the inclusion of all relevant studies published by the end of that year. The entire search and selection process was carried out by the author, utilizing the PICOS framework to guide the search strategy. The PICOS elements defined were: P (Patient) as PTSD patients, I (Intervention) as EEG-based Neurofeedback, C (Comparison) as Control (PTSD patients receiving either no treatment or treatments other than EEG-based neurofeedback), O (Outcomes) as psychometric assessments of PTSD, and S (Study Design) as Controlled Studies. The search terms employed were (trauma OR (PTSD OR post-traumatic stress disorder)) AND (Neurofeedback OR NF) AND (EEG OR Electroencephalography). 2.2 Inclusion and Exclusion Criteria The search results were combined from all the databases and were initially deleted for duplicates. Studies were included if they met the following criteria: Language: English Design: Controlled Study Intervention: EEG neurofeedback additional with any protocol Control group: PTSD patients receiving another form of treatment or being waitlisted Participant: PTSD patients Evaluation: PTSD assessment scale Year: 2013 ~ 2023 Studies were excluded if they were conference abstracts, not full texts, didn’t have a control, or didn’t provide their detailed outcome results in numbers. Studies were not limited to a randomized controlled study. The inclusion years of 2013 to 2023 for our meta-analysis are chosen based on significant trends in the field and technological advancements. Firstly, research on neurofeedback, especially EEG-based studies, notably increased starting in 2013, with minimal publications before this year. Secondly, advancements in EEG technology after 2013 have greatly enhanced study reliability and comparability, making earlier studies less compatible with current research due to technological disparities. 2.3 Quality Evaluation Risk of bias was assessed at each study level using the Cochrane risk of bias (RoB) tool in randomized controlled trials (RCTs) (Higgins et al., 2011 ). The criteria included selection bias, allocation bias, detection bias, performance bias, attrition bias, and reporting bias. These risks were evaluated in three levels (i.e. low, unclear, and high) [Fig. 2 ]. To test for the publication bias, the asymmetry of the funnel plot is assessed by visual inspection and by Egger’s regression test (Lin & Chu, 2018 ) [Figs. 3 and 4 ]. 2.4 Data Extraction Data was extracted manually upon reading the paper. The data extraction process was reviewed thoroughly to ensure there was no mistake in the extraction process. The primary outcome measure of each study was extracted as our intervention effect evaluation metric. Data was all rounded to the hundredth degree. The same measurement was used to investigate the effect at the follow-up phase (if applicable). If any studies did not report the standard deviation (SD) of their outcome measure but instead reported the confidence interval (CI), the following formula was used to convert that CI to SD: $$SD=\sqrt{N}\times \frac{UpperLimit-LowerLimit}{t}$$ N is the sample size of the study and t is a value from the t-distribution with the appropriate tail according to the CI interval and degree of freedom being N-1. For specific measurements and their characteristics, readers are referred to section 3.2 . As well as outcome measurements, basic information about the study itself, study design, neurofeedback protocol characteristics, and participant characteristics were extracted. Readers are referred to Table 1 for the details of all the specific variables other than the outcome measurements extracted from the studies. If a study did not provide information on any of the variables later used for subsequent data analysis, it is left blank and that study is excluded from that specific analysis. Table 1 Table of variables extracted from the studies other than the outcome measurement Category Items Description Basic information Reference Link to the study Authors Publication Year Journal Country of recruited Patient Where the patients were recruited Year of Recruitment Year of Research Recruitment and the research may be done on different years. Study Design follow up duration When was the follow-up conducted after the experiment? (if applicable) Losses to follow up 2 = losses to follow up were less than 15% of total cases 1 = losses were greater than 15% 0 = not reported Enrollment condition of study 2 = all cases were recruited 1 = just pick up convenient cases 0 = not reported All Outcome Measure All metrics the study utilizes to evaluate their intervention. Primary outcome measure Their primary outcome measure among all. Control group intervention Additional intervention Some studies also allowed participants to continue receiving their prescribed treatment. Inclusion criteria Exclusion criteria Distribution of patients 2 = patients are randomized on both methods 1 = each patient underwent both methods 0 = two non-randomized groups of patients Control Sample size Sample size of a control group. Experimental group sample size Sample size of an experimental group. Feedback Protocol Feedback duration Duration of the intervention in weeks. Total number of sessions Total number of sessions held during the whole intervention. # of session in a week Duration of one session Feedback Modality Modality in which participants receive their feedback (ex. auditory, visual). Extracted Feature Which feature of the brain wave were given feedback on as well as whether it was aimed to enhance or reduce that feature. Target Region The region of electrode which was targeted. Neurofeedback threshold Threshold it was used to determine the feedback. Characteristics of participants Age (Year) Mean and SD for each control and experimental group. Gender Ratio for each control and experimental group. Chronicity 1 = Chronic (Treatment Resistant) 0 = Not chronic Time since trauma Mean and SD 2.5 Statistical Analysis All analyses were conducted and plots generated using the R package “metafor” (Viechtbauer, 2010 ). The effect of EEG neurofeedback on PTSD symptoms was quantified using Hedge’s g (Lakens, 2013 ) with a 95% confidence interval. Hedge’s g, a variation of Cohen’s d, corrects for bias and is suitable for small sample sizes. Negative values indicate a beneficial intervention effect, while positive values indicate no effect or a negative intervention effect. Values less than 0.5 are considered small, 0.5 to 0.8 medium, and greater than 0.8 large. Heterogeneity was assessed using REML estimation (τ²) (Corbeil & Searle, 1976 ) and I² statistics (Higgins & Thompson, 2002 ). I² statistics measure the proportion of variance due to heterogeneity rather than sampling variance, with I² > 25%, 50%, and 70% indicating small, medium, and high heterogeneity, respectively. Due to observed heterogeneity, a random effects model (REM) was used to estimate the average treatment effect size. Meta-regressions were conducted to identify variables contributing to the heterogeneity. 3 Methodological Results 3.1 Search Results The literature search identified 218 records after the removal of duplicates. After reading the abstracts, 172 articles were excluded according to the inclusion and exclusion criteria. The remaining 46 articles were each screened upon further reading into the full text in which subsequent 35 articles were excluded. For detailed reasons for exclusion, readers are referred to Fig. 1 . In the end, 11 studies were left to include in our study [Table 2 ] (Bell et al., 2019 ; du Bois et al., 2021 ; Fruchtman-Steinbok et al., 2021 ; Leem et al., 2021 ; Nicholson et al., 2023 , 2020 ; Noohi et al., 2016 ; Shaw et al., 2023 ; van der Kolk et al., 2016 ; Yasuko, 2013 ). 3.2 Study Characteristics This meta-analysis included 306 participants from eleven studies, eight of which were randomized controlled trials. Most studies used frequency training (n = 8), with one using the LORETA protocol, and another using the AmygdalaEFP protocol. The primary outcome measure was the change in PTSD symptom assessments, predominantly using the Clinician-Administered PTSD Scale for DSM (CAPS-5) (n = 5) and the PTSD Checklist for DSM (PCL-5) (n = 4). Some studies also investigated changes in anxiety (n = 3), depression (n = 3), emotion (n = 2), executive control (n = 2), alpha amplitude (n = 2), and fMRI signals (n = 2). Most studies allowed simultaneous treatment with the EEG neurofeedback intervention. Tables 2 and 3 summarize the study characteristics and outcome measures. Detailed summaries of each study can be found in the OSF repository (refer to the code and data availability section). Table 2 Study characteristics of the included studies other than its outcome measurements. VA = visual + auditory, VAT = visual + auditory + tactile Author/Year Published/Country of Patient NF Sample size Control Sample size Feedback Duration Total number of sessions # of session in one week Duration of one session Feedback Modality Extracted Feature Target Region Neurofeedback threshold Follow up duration Age (mean year) Gender (% of Male) Chronicity Time since trauma (mean year) Kelson/2013/USA 5 5 4 20 5 30 VAT ? ? ? Non 51.8 100.0 ? ? Van der Kolk/2016/USA 22 22 12 24 2 30 VA Increase alpha (10–13 Hz) and decrease theta/delta & High beta (2–6 Hz, 22–36 Hz) T4 % of time spent in that certain frequency range 1 month 44.4 14.3 ? ? Noohi/2016/Iran 15 15 4 25 4 35 Auditory Increase theta waves ratio (4 to 8 Hz) in relative to alpha waves (8 to 12 Hz) Pz, P3, P4, O1, O2 ? 6w ? 100.0 ? ? Askovic/2019/Australia 13 13 46 27 1 or 2 20 Auditory Increase SMR (12 ~ 15 Hz) and 8 ~ 10/6 ~ 9 Hz Cz, C4, T4, and P4 ? Non 44.8 65.4 ? ? Bell/2019/USA 12 11 8 15 2 20 VA Decrease z-score on three network(DMN, CEN, SN)’s amplitude, coherence, phase, phase shift, phase lock ? 40–60% reward Non 44.2 ? ? ? Nicholson/2020/Canada 18 18 20 20 1 20 VA Decrease alpha wave Pz 65% reward 3 months 43.3 27.8 ? ? Fruchtman-Steinbok/2021/Israel 13 13 13 15 2, than 1 30 VA AmygdalaEFP ? Determined by (current delta - baseline delta)/SD 3 and 6 months 36.1 50.0 ? 8.7 Bois/2021/Rwanda 10 9 ? 7 ? 30 Visual Decrease alpha wave Pz If it’s at least 60% smaller than the preceding trial Non 53.7 0.0 ? ? Leem/2021/Korea 10 9 8 16 2 30 Auditory Increase Alpha(8–12) & Theta(4–7) and decrease Beta Pz ? 1 month 44.0 10.5 ? ? Nicholson/2023/Canada 20 18 20 20 1 20 VA Decrease alpha wave Pz 65% reward 3 months 42.7 28.9 ? ? Shaw/2023/Canada 18 17 20 20 1 20 VA Decrease alpha wave Pz 65% reward 3 months 43.1 28.6 ? ? Table 3 Outcome measurements for each study. When applicable, standard deviations are given in brackets() Author/Year Published/Country of Patient Primary Outcome Measure NF : Mean Before NF : Mean After NF : Follow-Up CT : Mean Before CT : Mean After CT : Follow-Up Other outcome measurement Other Treatment in NF group Kelson/2013/USA Original 72.8 44.2(9.55) / 69.4 78.8(9.01) / None None Van der Kolk/2016/USA CAPS-4 80.98 44.12(19.02) 40.23(20.52) 75.18 65.68(20.18) 64.68(21.49) None Continue ongoing treatment (psychotherapeutic, medication) Noohi/2016/Iran IES-R 47.20(7.63) 30.40(6.23) 30.46(5.20) 51.07(5.37) 51.14(6.18) 51.21(6.25) Executive control None Askovic/2019/Australia HTQ 2.8(0.4) 1.9(0.5) / 3.2(0.5) 3.1(0.6) / Anxiety and Depression, Cognitive control Trauma counseling Bell/2019/USA PCL-5 46.17(14.23) 18.08(12.65) / 49.82(10.16) 31.18(13.53) / Anxiety continue ongoing treatment Nicholson/2020/Canada CAPS-5 36.86(10.36) 24.39(15.61) 23.58(14.09) 39.94(7.83) 32.78(12.27) 31.78(12.86) fMRI analysis Continue ongoing medication, not therapy Fruchtman-Steinbok/2021/Israel PCL-5 53.75(16.49) 46.58(14.01) 46.1(16.56) 59.46(11.23) 61.33(10.33) 59.6(17.24) Anxiety, depression, Emotion continue ongoing treatment Bois/2021/Rwanda PCL-5 38.9(16.7) 11(5.52) 34.44(23.84) 28.66(20.08) Resilience, Mental wellbeing, Alpha amplitude Nothing Leem/2021/Korea PCL-5 44.3(10.8) 19.4(7.75) 19.4(6.52) 35.1(18.5)) 31(14.92) 29.4(13.99) Anxiety, Depression, Emotion, Cost effectiveness Continue ongoing treatment Nicholson/2023/Canada CAPS-5 36.52(9.71) 23.19(15.37) 23.65(13.71) 39.94(7.83) 32.78(12.27) 31.78(12.89) Alpha amplitude Continue ongoing medication, not therapy Shaw/2023/Canada CAPS-5 36.86(10.36) 24.42(17.59) 23.59(17.23) 39.64(7.97) 34.04(11.21) 32.82(19.71) fMRI analysis Continue ongoing medication, not therapy 3.3 Risk of Bias Figure 2 summarizes the RoB assessment. All eleven studies showed a low risk of attrition and reporting bias. However, selection bias was high in two studies due to non-random participant allocation. Six studies exhibited a high risk of bias in participant blinding, and four of these also had high detection bias. Some studies claimed randomization but did not detail the process, causing uncertainty in allocation bias. 3.4 Publication Bias Studies were plotted by their standard error against the standard mean difference (Cohen’s d) to create a funnel plot and assess publication bias [Figure 3 ]. Statistically significant asymmetry (p < 0.001) using Egger’s regression test indicates potential publication bias (Lin & Chu, 2018 ). A Contour-Enhanced funnel plot [Figure 4 ] also suggests publication bias, as fewer studies appear in the areas indicating statistical insignificance (0.1 < p < 1). However, the small number of studies (n = 11) limits the reliability of these tests (Lin & Chu, 2018 ). Additionally, no correlation between study size and effect size (p = 0.1697) was found, but the small study effect and potential heterogeneity remain considerations (Sterne et al., 2011 ). 4 Contextual Results 4.1 PTSD symptom decreases immediately after the treatment but with high heterogeneity between studies All included studies assessed PTSD symptoms immediately after the intervention. Figure 5 shows a high effect size of EEG neurofeedback (Cohen’s d = -1.28, CI: -1.76 to -0.80, p < 0.0001) with the upper confidence interval still negative. However, there is high heterogeneity among the studies (τ² = 0.4488, I² = 71.57%, p < 0.01). 4.2 Placebo effect not found Three studies included a sham control and were analyzed separately for placebo effects. Figure 6 shows that even with sham control, EEG neurofeedback had a high effect size (Cohen’s d = -0.63, CI: -1.01 to -0.2, p 0.05). This consistency may be due to using the same neurofeedback protocol (alpha wave down-regulation at Pz) and a similar population (treatment-resistant PTSD patients in Canada). 4.3 EEG neurofeedback yields long-term effects Three studies conducted a 1-month follow-up, and four studies conducted a 3-month follow-up to test the long-term effects of EEG neurofeedback. Figure 7 shows the meta-analysis results. None of the studies conducted both 1-month and 3-month follow-ups. One study with a 6-week follow-up was included in the 1-month group. The 1-month follow-up showed a substantial effect (Cohen’s d = -1.72, CI: -3.13 to -0.30, p < 0.05) but with high heterogeneity (τ² = 1.3533, I² = 87.17%, p < 0.01). The 3-month follow-up showed a moderate effect size (Cohen’s d = -0.72, CI: -1.07 to -0.37, p < 0.0001) with no heterogeneity. All three of the four 3-month follow-up studies used the same neurofeedback protocol (alpha down-regulation at Pz) and a similar population (Canadian), while one used a different protocol and population (AmygEFP with an Israeli population). This suggests consistent effects of EEG neurofeedback up to 3 months, regardless of the protocol or population, but the small sample size limits the interpretation. Overall, these results support that EEG neurofeedback can improve PTSD symptoms for up to 3 months. 4.4 Moderators Given the high heterogeneity across studies, several within-study factors may contribute to this. 4.4.1 # of session, # of weeks, duration of session Figure 8, 9, and 10 shows the meta-regression computed with the total number of EEG-neurofeedback sessions, total number of weeks spent on the intervention, and duration of each session, respectively, as a moderator. For all moderators, there is still a significant amount of heterogeneity left (i.e. 71%, 80%, and 73%) and the effect of the moderator is not statistically significant (p > 0.05). Thus, these indicate that these do not affect the outcome. 4.4.2 Year Figure 11 shows the meta-regression using the year of publication as a moderator. Despite significant residual heterogeneity (55%, p < 0.05), the moderator effect is statistically significant (p < 0.01). This indicates that more recent studies show a reduced effect size. 4.4.3 Simultaneous Treatment Three out of eleven studies had an experimental group without additional treatment (e.g., psychotherapy, medication), and the control group received no medical treatment. In the other eight studies, participants continued their ongoing PTSD treatments. Of these, three allowed psychotropic medication but no other psychotherapy, one required traditional trauma counseling alongside EEG neurofeedback for all participants, and four allowed any treatment outside the experiment. All eight studies prohibited changing treatments during the experiment. Figure 12 shows meta-regression results with simultaneous treatment as a moderator. The residual heterogeneity remains significant (49%, p < 0.05), but the moderator test is statistically significant (p < 0.0001). Studies without simultaneous treatment showed a larger estimated effect size (Cohen’s d = -2.3377) compared to those with simultaneous treatment (Cohen’s d = -0.949). 4.4.5 Targeting Pz Five out of eleven studies targeted the Pz region, located on the midline parietal lobe. Figure 13 shows meta-regression results using this factor as a moderator. Despite significant residual heterogeneity (65%, p < 0.01), the moderator is statistically significant (p < 0.0001). Studies not targeting Pz showed a larger effect size (Cohen’s d = -1.4983) compared to those targeting Pz (Cohen’s d = -0.8562), opposing the current trend to focus on the Pz region. 4.4.6 Pz Targeted down-regulation of Alpha Wave Four out of five studies targeting the Pz electrode used an alpha down-regulation neurofeedback protocol. Figure 14 shows the meta-regression with this factor as a moderator. Although there is significant residual heterogeneity (τ² = 0.4488, I² = 54.94%, p < 0.05), 45% of the heterogeneity was explained by this moderator (p < 0.0001). The effect size was larger for studies not using the Pz alpha down-regulation protocol (Cohen’s d = -1.4879) compared to those using it (Cohen’s d = -0.7339), despite its frequent use. 4.4.7 Increasing Alpha Wave Four out of eleven studies used an alpha up-regulation neurofeedback protocol. Figure 15 shows the meta-regression with this factor as a moderator. Despite significant residual heterogeneity (50%, p < 0.05), the moderator effect is statistically significant (p < 0.0001). Interestingly, studies with alpha up-regulation showed about twice the effect size (Cohen’s d = -1.7090) compared to those without it (Cohen’s d = -0.8262), contrary to the trend of down-regulating alpha. 4.4.8 Feedback Modality The feedback modality was evaluated as a moderator in eleven studies, categorized as visual only, auditory only, visual + auditory (VA), or visual + auditory + tactile (VAT). Figure 16 shows the results, indicating that feedback modality explained 92% of the heterogeneity. The estimated effect sizes are: VAT = -3.3643 (p < 0.001), Auditory = -2.0186 (p < 0.0001), Visual = -1.1756 (p < 0.05), VA = -0.8258 (p < 0.0001). VAT yielded the highest effect, though based on a single study with a small sample size (n = 10). Interestingly, single modalities (auditory or visual) had higher effect sizes than combined modalities (VA). 5 Discussion In the last 10 years, there has been a rapid increase in studies that test the efficiency of EEG neurofeedback for treating PTSD. This meta-analysis demonstrated the importance of neurofeedback protocol in efficacy and overall strongly supports a need for future research. 5.1 EEG neurofeedback can treat PTSD symptoms Meta-analytic evidence suggests that EEG neurofeedback is a promising treatment for PTSD symptoms, showing high effect sizes that are statistically significant. Sham-controlled studies confirm that these benefits are not due to placebo effects. High effect sizes persist at both one-month and three-month follow-ups, despite broad confidence intervals likely due to small sample sizes, indicating potential long-term therapeutic effects of EEG neurofeedback. 5.2 EEG neurofeedback can alter neural activity The premise that brainwave patterns can be modulated through neurofeedback, particularly in treating PTSD with EEG neurofeedback, requires validation. Despite its crucial role in treatment efficacy, comprehensive studies substantiating this for PTSD patients are scarce. Three studies (du Bois et al., 2021 ; Nicholson et al., 2023 ; Shaw et al., 2023 ) focused on downregulating alpha wave amplitude in the Pz region and assessing changes during treatment sessions, consistently demonstrating expected alterations in alpha wave amplitude. One study (Nicholson et al., 2023 ) observed a significant increase in alpha power in the medial frontal gyrus post-intervention, compared to reduced alpha power at baseline. These results support that neurofeedback can modulate brainwave activity. 5.3 Mechanisms underlying EEG neurofeedback might be the normalization of broad neural network Empirical evidence indicates EEG neurofeedback can modulate brain activity, but specific mechanisms affecting PTSD patients remain unidentified. A prevailing hypothesis suggests targeted manipulation of brainwave patterns modifies neural networks, especially the brain’s intrinsic connectivity networks (ICNs) (Nicholson et al., 2020 ; Shaw et al., 2023 ). The ICNs include the central executive network (CEN), default mode network (DMN), and salient network (SN) (Menon, 2011 ). Consistent indications of dysfunction in these networks among PTSD patients are identified (Akiki et al., 2017 ; Holmes et al., 2018 ; Kennis et al., 2016 ; Shang et al., 2014 ). Thus, normalization of these networks could potentially alleviate PTSD symptoms. Among the eleven reviewed studies, two specifically assessed ICNs before and after EEG neurofeedback (Nicholson et al., 2020 ; Shaw et al., 2023 ). Both experimental and control groups underwent fMRI assessments pre- and post-intervention to quantify changes in ICN activity and connectivity. The studies consistently employed an EEG neurofeedback protocol targeting alpha wave reduction at the Pz electrode location. Results demonstrated significant normalization in ICNs among PTSD patients who received EEG neurofeedback. The experimental group exhibited reduced connectivity within the DMN, suggesting normalization of hyperactive posterior DMN activity and improved executive control. Within the SN, diminished connectivity was observed between the right anterior insula and SN, supporting the restorative effects of EEG neurofeedback on system connectivity. 5.4 Midline parietal lobe targeted EEG neurofeedback does not yield a higher effect size This meta-analysis reveals that protocols targeting the Pz electrode, located over the midline parietal lobe, are associated with smaller effect sizes compared to those targeting other regions. Moreover, our specific examination of alpha wave down-regulation, as studied by Kluetsch et al. (Kluetsch et al., 2014 ), who explored the ‘alpha rebound effect’—where alpha waves return to a baseline level following down-regulation through EEG neurofeedback, showed that while this approach seemed promising for conditions like PTSD, where reduced alpha waves are common (Eidelman-Rothman et al., 2016 ), it did not yield higher effect sizes. In contrast, protocols aiming to increase alpha wave activity exhibited higher effect sizes. Thus, while Pz-targeted alpha down-regulation has potential, our findings suggest a need for reevaluating targeted protocols to optimize EEG neurofeedback outcomes. 5.5 Different feedback modalities yield different effect size Among prevalent neurofeedback modalities, visual and auditory feedback are most extensively utilized across various studies. Currently, no definitive guidelines specify which modality is superior. Data from a single study indicates a highest effect size for a multi-sensory modality combining visual, auditory, and tactile feedback. Auditory feedback alone follows in effect size, with visual feedback alone next. Surprisingly, a combined visual and auditory feedback modality yielded the lowest effect size. This finding challenges the notion that multi-sensory feedback inherently enhances neuroplastic learning. These provisional findings suggest future research should focus on the efficacy and cost-effectiveness of single-modal feedback mechanisms. 5.6 More feedback sessions are not more effective Our analysis revealed no significant impact of the number of training sessions on PTSD treatment outcomes. Neither the duration of individual sessions nor the overall length of the intervention period were significant factors. These findings suggest that EEG neurofeedback can be effective within a brief intervention period, reducing both financial costs for patients and resource burdens for clinics. 5.7 Simultaneous treatment tends to decrease the efficacy of the neurofeedback Neurofeedback is often used alongside other therapies, but data indicated that studies prohibiting concurrent treatments yielded higher effect sizes. Studies disallowing additional therapies often involved participants from countries with lower medical standards, while those permitting concomitant therapies involved participants from countries with high-quality medical care. This suggests the efficacy of EEG neurofeedback could be higher in populations with limited access to quality medical care. Future research is necessary to explore these relationships. 6 Limitations 6.1 Limitations of the Studies Many studies lack explicit details on neurofeedback protocols. Future research must specify attributes such as feedback modality, target features, target regions, feedback threshold, duration, and frequency of sessions. Moreover, the role of PTSD chronicity is often overlooked, potentially skewing outcomes. Future studies should assess trauma chronology and control for this variable. Sample sizes are also generally small (max = 44), compromising statistical power. A sample size larger than 70 is recommended [44, 80]. Lastly, less than half of the studies used a double-blind design. Adopting double-blind, randomized controlled trials is crucial for rigor and reliability. 6.2 Limitations of this Study Due to the nascent state of this field and the predominance of studies with limited sample sizes, drawing definitive conclusions remains challenging. 7 Conclusion EEG neurofeedback has emerged as a potential treatment for PTSD, with an increasing number of controlled trials evaluating its efficacy. Despite this, no comprehensive meta-analysis has systematically assessed these studies or quantified EEG neurofeedback’s therapeutic impact on PTSD. Furthermore, there is a lack of meta-analytic evaluations comparing different EEG neurofeedback protocols. In this study, we assessed the overall effectiveness of EEG neurofeedback in mitigating PTSD symptoms. A meta-regression determined that EEG neurofeedback significantly impacted PTSD symptoms immediately post-intervention and sustained this effect over the long term (one and three months), not driven by placebo effects. The feedback protocol, specifically target frequency and region, and the feedback modality, were identified as the most influential factors in treatment success. In contrast, treatment duration, number, frequency, and session number did not influence the outcome. Contrary to the prevalent focus on down-regulating alpha waves at the midline parietal region, our meta-regression indicated that alternative protocols might offer better outcomes. Future studies should investigate other protocols. Similarly, our findings suggest that a single-modality approach, especially auditory feedback, may be more effective and cost-efficient than a multi-modality approach. Based on these results, we encourage future research to explore alternative regions and feedback modalities to enhance treatment effectiveness. Registration and Protocol This review was not registered. The review protocol was developed based on Tawfik’s guideline of a systematic review and a meta-analysis (Tawfik et al., 2019 ). Statements and Declarations Data Availability: All data generated or analyzed during this study are available from the OSF repository (https://osf.io/bca82/). Funding Statement: This research was not funded. Competing Interest: The author declares that they have no competing interests, financial or otherwise, that have influenced the research and the development of this paper. Acknowledgements: I would like to extend my deepest gratitude to Sophie Rogers of Pennsylvania University for her invaluable guidance on research methodology and result synthesis throughout the course of this research endeavor. Her meticulous review of the final manuscript has been instrumental in enhancing the quality of this work. Conflict of Interest The author declares that there are no competing interests in the publication of this paper. No funds, grants, or other support was received. There are no financial, personal, or professional relationships that could potentially influence or bias the work presented herein. All procedures and methodologies were conducted impartially and without any conflict of interest. Code and Data Availability All data and code used in the meta-analysis presented in this paper are openly available for the benefit of the scientific community and to ensure the transparency and reproducibility of our work. The datasets, along with the associated code, have been deposited in the Open Science Framework (OSF) repository (bca82). This allows for both the validation of the results reported here and the potential for further analysis by other researchers. 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Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ (Clinical Research Ed) , 343 (jul22 1), d4002. https://doi.org/10.1136/bmj.d4002 . Tawfik, G. M., Dila, K. A. S., Mohamed, M. Y. F., Tam, D. N. H., Kien, N. D., Ahmed, A. M., & Huy, N. T. (2019). A step by step guide for conducting a systematic review and meta-analysis with simulation data. Tropical Medicine and Health , 47 (1), 46. https://doi.org/10.1186/s41182-019-0165-6 . 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 . Viechtbauer, W. (2010). Conducting Meta-Analyses inRwith themetaforPackage. Journal of Statistical Software , 36 (3), 1–48. https://doi.org/10.18637/jss.v036.i03 . Yasuko, K. C. (2013). Veterans Symptoms of Posttraumatic Stress Disorder (PTSD). ProQuest . -origsite=gscholar&cbl=18750&diss=y. http://search.proquest.com/openview/019272465d8a47db88d836776a6a0ccb/1?pq . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 12 Mar, 2025 Read the published version in Applied Psychophysiology and Biofeedback → Version 3 posted Editorial decision: Revision requested 19 Nov, 2024 Reviews received at journal 19 Nov, 2024 Reviewers agreed at journal 19 Nov, 2024 Reviews received at journal 11 Nov, 2024 Reviewers agreed at journal 11 Nov, 2024 Reviewers invited by journal 10 Jun, 2024 Editor assigned by journal 05 Jun, 2024 Submission checks completed at journal 05 Jun, 2024 First submitted to journal 04 Jun, 2024 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3644363","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[{"code":1,"date":"2023-11-25 13:17:51","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}},{"code":2,"date":"2024-07-23 13:33:51","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}}],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":333774833,"identity":"610055c4-c2db-4729-85c1-1e7411d495f8","order_by":0,"name":"Kana Matsuyanagi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACCRDx8U9NfT97A5BlYEGcFsaZDccYZ/YcAGmRIE4LM28DM+OGGwlwW/EDyfazBz/z7mBjZrj5/OqGHwUSDPzt3Ql4tUjz5CVLzj0jw8Y4O6fsZg/QYRJnzm7Aq0WOIcdA4g0bGw+zdE7aDR6gFgOJXAJa+N8Y/+BhY5ZgkzyTdvMPMVqkJXLMJHnbmA14JNiP3SbKFskZb8wsZ5w5liDBk8N2W8ZAgoegXyTO5xjf+FBRk2B//Pizm2/+2Mjxt/fi14IEeAzAJLHKQYD9ASmqR8EoGAWjYAQBAMoYRcxSyV9kAAAAAElFTkSuQmCC","orcid":"","institution":"Brigham Young University online high school","correspondingAuthor":true,"prefix":"","firstName":"Kana","middleName":"","lastName":"Matsuyanagi","suffix":""}],"badges":[],"createdAt":"2023-11-21 13:44:24","currentVersionCode":3,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-3644363/v3","doiUrl":"https://doi.org/10.21203/rs.3.rs-3644363/v3","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10484-025-09701-5","type":"published","date":"2025-03-12T15:58:27+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":63286902,"identity":"09a5499f-84a7-42e2-be08-9cc56b704d3e","added_by":"auto","created_at":"2024-08-26 13:48:03","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":77908,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA flow diagram\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/37d7eb1c977095c50ba8da1a.png"},{"id":63289336,"identity":"8a9ab12c-4347-4a75-bc1f-d1282a9ad478","added_by":"auto","created_at":"2024-08-26 14:04:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":422530,"visible":true,"origin":"","legend":"\u003cp\u003eRisk of bias assessments in all eleven studies using the Cochrane risk of bias (RoB) assessment tool for random controlled trials (RCTs). UC = Unclear\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/4c1dffaf94eb4d8f89838b4a.png"},{"id":63286903,"identity":"7cb5177b-3d61-4981-bb55-db0683821671","added_by":"auto","created_at":"2024-08-26 13:48:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":26019,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot of the eleven studies. Standard errors of each study are plotted as a function of the standard mean difference. In agreement with the visual inspection of the plot, Egger’s regression test revealed a statistically significant asymmetry (p \u0026lt; 0.0001). However given the small sample size included in this test (n = 11), this interpretation is hard.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/881b4e15f461a7441cbf1cb6.png"},{"id":63288295,"identity":"0b5a6d8c-86da-442c-9635-5454924fc822","added_by":"auto","created_at":"2024-08-26 13:56:03","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":43806,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot with the contour-enhanced plot. Because studies are all in the gray area (p \u0026lt; 0.1) and there are no studies located in the white area (p \u0026gt; 0.1), it is a sign of a publication bias. However, again, given the small number of studies included in this test, publication bias can not be tested reliably.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/7f0c1e1a8f2a3f0e1862c197.png"},{"id":63288294,"identity":"96fb25d9-4e81-4350-9c1e-74f437dc250d","added_by":"auto","created_at":"2024-08-26 13:56:03","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":156293,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for the effect size and its 95% confidence interval for all eleven studies. The effect sizes indicated on the right-hand side of the figure (Cohen’s d), are calculated based on the score of the PTSD symptom assessment test right after the intervention (~ 1 week). The negative value indicates that the result of the study was in favor of the EEG-neurofeedback (EEG-NF). The higher the absolute value is, the more effect the EEG-NF had on PTSD symptoms. The overall estimated effect size of EEG-NF based on these eleven studies is -1.28 (CI: -1.76 ~ -0.80 p \u0026lt; 0.0001). Notably, the upper confidence interval is still negative. Together with the p-value (p \u0026lt; 0.0001), this implies that the EEG-NF can decrease PTSD symptom scores when measured right after the intervention. However, there is a high heterogeneity among the studies (τ² = 0.4488, I² = 71.57%, p \u0026lt; 0.01) indicating the need for further analysis of the moderators.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/fd501306a3e41042591cc04d.png"},{"id":63286909,"identity":"cd3eaf56-5813-46d2-9f2c-25f81df96a9c","added_by":"auto","created_at":"2024-08-26 13:48:09","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":83001,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot with studies that had a sham control group (n = 3). The effect size here is calculated based on the score of the PTSD symptom assessment test right after the intervention (~ 1 week) as in Figure 7. The overall estimated effect size of EEG-NF based on these sham-controlled studies is -0.63 (CI: -1.01 ~ -0.25, p \u0026lt; 0.05). Compared to Figure 7, the estimated effect size is smaller but, a significant effect of EEG-NF can be still observed indicating that the placebo effect is, at least, not the single driver of the treatment effect. Note that the upper confidence interval is also still negative. Also, there was no heterogeneity (𝜏² = 0, I² = 0%, p = 0.9835) among these studies. This may be attributed to the fact that all these studies used the same neurofeedback protocol: down-regulation of the alpha wave at the Pz region.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/846ee75be3c1870cc688d5d2.png"},{"id":63288307,"identity":"38a28b28-8b60-4fa8-8c59-03a2f2e48dc4","added_by":"auto","created_at":"2024-08-26 13:56:09","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":112429,"visible":true,"origin":"","legend":"\u003cp\u003eThe top half shows the forest plot for studies that conducted a 1-month follow-up (n = 3). The lower half shows the forest plot for studies that conducted a 3-month follow-up (n = 4). Note that studies included in each forest plot are different. The overall estimated effect size of EEG-NF on 1-month follow-up is –1.72 (CI: -3.13 ~ -0.30, p \u0026lt; 0.05). The overall estimated effect size of EEG-NF on a 3-month follow-up is -0.72 (CI: -1.07 ~ -0.3, p \u0026lt; 0.0001). Both are statistically significant but 1 month follow-up has a higher effect size. However, the confidence intervals of the 3-month follow-up are inside the 1-month follow-up’s confidence interval and thus it cannot be determined whether there is a decrease in effect size during the 1-month and 3-month follow-up. Note that the upper confidence interval is also still negative here for both 1 and 3-month follow-up. Notably, there was no heterogeneity (𝜏² = 0, I² = 0%, p = 0.7685) among the studies that conducted 3-month follow-up. This may be partly because 3 out of 4 studies that were included in the 3-month follow-up used the same neurofeedback protocol (i.e. alpha down-regulation at Pz region) as well as a similar population (i.e. Canadian). However, regarding that, at least one study used a completely different neurofeedback protocol as well as population (i.e. AmygEFP protocol to an Israel population), and still, the heterogeneity is 0, this result may indicate that the effect of EEG-NF shows a strong consistency after 3 months whatever the population/intervention method was.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/e1d4e4c4b8e29ab9b953ba8d.png"},{"id":63286898,"identity":"6ec2cb0d-2720-4993-82a0-628bf7be306b","added_by":"auto","created_at":"2024-08-26 13:48:03","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":30418,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of the number of sessions. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid line) with corresponding confidence interval bounds (the dashed line) are also shown. The size of each plot represents the reliability of the study. It is proportional to the inverse of the sampling error, which is the square root of the sampling variance (1/√vi). Notably, several sessions resulted in being not statistically significant (p = 0.1940) as a moderator. The residual heterogeneity (τ² = 0.4290, I² = 70.8771%, p \u0026lt; 0.01) is also still statistically significant.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/210c6f9a25f9cb54d99ec22a.png"},{"id":63286918,"identity":"0334a7ca-911b-4759-a327-c62d9f0c46f1","added_by":"auto","created_at":"2024-08-26 13:48:11","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":30758,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of the number of weeks spent for the EEG-NF intervention. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid line) with corresponding confidence interval bounds (the dashed line) are also shown. The size of each plot represents the reliability of the study. It is proportional to the inverse of the sampling error, which is the square root of the sampling variance (1/√vi). Notably, the total number of sessions resulted in being not statistically significant (p = 0.6982) as a moderator. The residual heterogeneity(τ² = 0.6665, I² = 79.77%, p \u0026lt; 0.0001) is also still statistically significant.\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/009d7e9a5922e5353f488d52.png"},{"id":63286904,"identity":"0101f57d-b563-47ef-a058-60a71c7a4647","added_by":"auto","created_at":"2024-08-26 13:48:08","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":36574,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of the duration of the single session for the EEG-NF intervention. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid line) with corresponding confidence interval bounds (the dashed line) are also shown. The size of each plot represents the reliability of the study. It is proportional to the inverse of the sampling error, which is the square root of the sampling variance (1/√vi). Notably, the duration of a session resulted in being not statistically significant (p = 0.4033) as a moderator. The residual heterogeneity (τ² = 0.4782, I² = 72.93%, p \u0026lt; 0.01) is also still statistically significant.\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/3c470218f9e1512bfe074b01.png"},{"id":63286910,"identity":"b139d0e6-c92e-4142-b8c8-93bc75e4ec1a","added_by":"auto","created_at":"2024-08-26 13:48:09","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":36518,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of published year. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid line) with corresponding confidence interval bounds (the dashed line) are also shown. The size of each plot represents the reliability of the study. It is proportional to the inverse of the sampling error, which is the square root of the sampling variance (1/√vi). The published year resulted in being statistically significant (p \u0026lt; 0.01) as a moderator. EEG-NF yields a smaller effect size the more recently it is published. But the residual heterogeneity (τ² = 0.2212, I² = 54.55%, p \u0026lt; 0.05) is still statistically significant.\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/a9d8754ae027a4ae6454aaa9.png"},{"id":63288305,"identity":"dda389bf-ff19-4553-868c-4faf07145410","added_by":"auto","created_at":"2024-08-26 13:56:09","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":35954,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of whether the neurofeedback aimed for a down-regulation of the alpha wave at the Pz region for the EEG-NF intervention. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid dot) with corresponding confidence interval bounds (the line that goes through the dot) are also shown. Whether the study protocol aimed for a down-regulation in alpha waves or not showed a statistically significant (p \u0026lt; 0.0001) effect on the outcome of the EEG-NF. The studies that did aim for down-regulation show a lower effect size compared to those which didn’t although part of their confidence interval do overlap. However, the residual heterogeneity (τ² = 0.1638, I² = 48.71%, p \u0026lt; 0.05) is still statistically significant.\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/8d6ab2e252d9e466a8b5a711.png"},{"id":63290296,"identity":"121b3f6e-1b3e-46e0-8bce-a138b316f2cf","added_by":"auto","created_at":"2024-08-26 14:12:09","extension":"png","order_by":13,"title":"Figure 13","display":"","copyAsset":false,"role":"figure","size":31369,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of whether the neurofeedback targeted the Pz region. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid dot) with corresponding confidence interval bounds (the line that goes through the dot) are also shown. Whether the study protocol targeted Pz or not shows a statistically significant (p \u0026lt; 0.0001) effect on the outcome of the EEG-NF which indicates the importance of the target region of EEG-NF as a protocol. The studies that did target Pz show a lower effect size compared to those that did not, although part of their confidence interval does overlap. This is an interesting result since a lot of EEG-NF for PTSD currently targets Pz. However, the residual heterogeneity (τ² = 0.3082, I² =64.86%, p \u0026lt; 0.01) is still statistically significant.\u003c/p\u003e","description":"","filename":"13.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/96a636d4e43354ea8309b7e2.png"},{"id":63289337,"identity":"f77eb85e-925b-41ae-b8b7-01c86dc01f40","added_by":"auto","created_at":"2024-08-26 14:04:09","extension":"png","order_by":14,"title":"Figure 14","display":"","copyAsset":false,"role":"figure","size":34118,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of whether the neurofeedback aimed for a down-regulation of the alpha wave at the Pz region for the EEG-NF intervention. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid dot) with corresponding confidence interval bounds (the line that goes through the dot) are also shown. Whether the study protocol aimed for a down-regulation in alpha wave or not showed a statistically significant (p \u0026lt; 0.0001) effect on the outcome of the EEG-NF. The studies that did aim for down-regulation show a lower effect size compared to those which didn’t although part of their confidence interval do overlap. However, the residual heterogeneity (τ² = 0.2039, I² = 54.94%, p \u0026lt; 0.05) is still statistically significant.\u003c/p\u003e","description":"","filename":"14.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/7adf54ada1021bbd63e47e7e.png"},{"id":63286915,"identity":"a5382e9f-9774-4132-93d7-c037e9f7125a","added_by":"auto","created_at":"2024-08-26 13:48:09","extension":"png","order_by":15,"title":"Figure 15","display":"","copyAsset":false,"role":"figure","size":29902,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of whether the neurofeedback aimed for an up-regulation of an alpha wave for the EEG-NF intervention. Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid dot) with corresponding confidence interval bounds (the line that goes through the dot) are also shown. Whether the study protocol aimed for an up-regulation in alpha wave or not showed a statistically significant (p \u0026lt; 0.0001) effect on the outcome of the EEG-NF. The studies that did aim for an up-regulation show a higher effect size compared to those which didn’t although part of their confidence interval do overlap. However, the residual heterogeneity (τ² = 0.1680, I² = 50.29%, p \u0026lt; 0.05) is still statistically significant.\u003c/p\u003e","description":"","filename":"15.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/5f3cb951ceb23f87789ff551.png"},{"id":63288309,"identity":"fae9b6fc-ac83-46c1-9295-5b1aa4ff2c7c","added_by":"auto","created_at":"2024-08-26 13:56:10","extension":"png","order_by":16,"title":"Figure 16","display":"","copyAsset":false,"role":"figure","size":34382,"visible":true,"origin":"","legend":"\u003cp\u003ePlot of Cohen's d as a function of what feedback modality the study used (i.e. visual or auditory or visual and auditory or visual and auditory and tactile). Note that the y-axis is intentionally reversed so that the higher effect size is located at the top. The estimated effect sizes (the solid dot) with corresponding confidence interval bounds (the line that goes through the dot) are also shown. Interestingly, it accounted for about 70% of the heterogeneity and the residual heterogeneity now remains statistically insignificant (τ² = 0.0635, I² = 29.41%, p = 0.0987). Consistently, the test of moderators shows a statistically significant (p \u0026lt; 0.0001) effect on the outcome of the EEG-NF. To summarize, although a lot of EEG-NF studies currently use a combination of visual and auditory as their feedback modality based on the intuition that the more feedback the user receives, the better their performance would be, this analysis shows that that might not be true.\u003c/p\u003e","description":"","filename":"16.png","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/fb451b26c4347429687e9cef.png"},{"id":78689610,"identity":"853c0f75-76cf-44a3-a291-a9ea464b53b6","added_by":"auto","created_at":"2025-03-17 16:12:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2543071,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3644363/v3/015f0815-70ec-41f9-8f2a-f840e2376109.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Can electroencephalography-based neurofeedback treat post-traumatic stress disorder? A meta-analysis study","fulltext":[{"header":"1 Introduction","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003e1.1 PTSD\u003c/h2\u003e \u003cp\u003ePost-Traumatic Stress Disorder (PTSD) is a psychiatric disorder that arises in response to experiencing or witnessing a traumatic event (American Psychiatric Association, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). These can include combat exposure, physical or sexual assault, natural disasters, or accident. The hallmark symptoms of PTSD include intrusive memories, flashbacks, avoidance behaviors, negative alterations in cognition and mood, and hyperarousal. The persistence and intensity of these symptoms can significantly impair an individual's daily functioning, quality of life, and interpersonal relationships.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.2 Current Treatment Approaches for PTSD\u003c/h2\u003e \u003cp\u003eCurrent treatment approaches for PTSD involve psychotherapy and pharmacotherapy (Schrader \u0026amp; Ross, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Cognitive-behavioral therapy (CBT), especially exposure therapy, helps modify maladaptive thought patterns and behaviors by encouraging patients to confront traumatic memories in a controlled environment (Schrader \u0026amp; Ross, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, its efficacy depends on patient engagement, and the distress of re-experiencing trauma can lead to dropout or worsened symptoms. Pharmacotherapy, mainly selective serotonin reuptake inhibitors (SSRIs), alleviates symptoms of depression and anxiety, stabilizing mood and improving overall functioning (Schrader \u0026amp; Ross, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Limitations include variability in drug efficacy and potential side effects, addressing only symptomatic relief rather than the root cause of PTSD. With these limitations, many individuals still continue to experience chronic symptoms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e1.3 EEG Neurofeedback\u003c/h2\u003e \u003cp\u003eElectroencephalogram (EEG) neurofeedback is another, less common therapeutic approach in treating PTSD. EEG neurofeedback aims to modulate brainwave activity through real-time feedback (Marzbani et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This non-invasive method involves training individuals to self-regulate their brain activity by monitoring and receiving feedback on their EEG signals. EEG neurofeedback involves placing electrodes on the scalp to measure electrical activity and targeting specific frequency bands based on symptoms. Individuals receive feedback for their brainwave activity, encouraging self-regulation and achieving desired brain states. Repeated sessions can lead to improved self-regulation and symptom reduction.\u003c/p\u003e \u003cp\u003eThere is a recent increase of interest in EEG neurofeedback for PTSD treatment. The first study that showed for the first time a significant reduction in PTSD symptoms with the EEG neurofeedback was by Peniston et al. who gave veterans an alpha-theta targeted neurofeedback (Peniston \u0026amp; Kulkosky, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). Studies indicate that individuals with PTSD exhibit abnormal EEG patterns, such as increased spectral power of low beta waves, which are correlated with high anxiety levels (Shim et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and EEG neurofeedback can normalize these patterns, potentially promoting better emotional and cognitive functioning.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e1.4 Limitations and gaps in knowledge\u003c/h2\u003e \u003cp\u003eGiven the evolving landscape of research on EEG neurofeedback for PTSD, there is a pressing need for a comprehensive meta-analysis that not only assesses its efficacy as a standalone or adjunct treatment but also integrates the wealth of findings emerging from recent studies. While there are four existing meta-analyses on this topic (Choi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hong \u0026amp; Park, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Russo et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Steingrimsson et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), their scopes and methodologies exhibit significant limitations. The analyses from 2022 (Hong \u0026amp; Park, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Russo et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) do not account for the surge of recent studies, underscoring the need for an updated review. Another recent analysis (Choi et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) does not distinguish between EEG-based neurofeedback and fMRI-based neurofeedback. As these two methods are considered to have a fundamental difference in their mechanism, it is necessary to evaluate the effect of EEG neurofeedback on PTSD specifically. The fourth analysis (Steingrimsson et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) overlooks the impact of critical moderators such as feedback modality and target brain area, which are crucial for understanding treatment efficacy.\u003c/p\u003e \u003cp\u003eOur proposed meta-analysis is distinct in its methodological rigor, aiming to fill these gaps by employing advanced statistical techniques such as meta-regression to explore the impact of various moderators that have been neglected previously. This includes examining the influence of simultaneous treatments, neurofeedback target areas, target frequencies, and feedback modalities on treatment outcomes. Moreover, we conduct detailed subgroup analyses to uncover how demographics, intervention types, and clinical settings differentially affect treatment effectiveness. This approach allows for a comprehensive understanding of EEG neurofeedback\u0026rsquo;s efficacy across diverse patient populations and treatment environments, moving beyond the generalized findings of prior reviews. Additionally, our study is unique in its effort to connect empirical findings to underlying theoretical frameworks, specifically focusing on the neural network modulation that may underlie the mechanism of neurofeedback effects on PTSD. This integration not only aims to elucidate the therapeutic mechanisms of EEG neurofeedback but also to guide future research and clinical practice by linking observed outcomes to neurobiological processes.\u003c/p\u003e \u003cp\u003eBy synthesizing the latest evidence, including the most recent studies, our meta-analysis seeks to overcome the limitations inherent in individual investigations, offering robust conclusions about the effectiveness of EEG neurofeedback for PTSD. Our comprehensive approach aims to evaluate the efficacy of EEG neurofeedback, reveal the most effective feedback protocols and intervention designs, and, crucially, to advance our theoretical understanding of its mechanisms.\u003c/p\u003e \u003c/div\u003e"},{"header":"2 Method","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Search strategy\u003c/h2\u003e \u003cp\u003eTo identify relevant studies, a comprehensive search was conducted across multiple databases, including PubMed, ScienceDirect, ClinicalTrials.gov, and the Wiley Online Library. This search covered the period up to and including December 2023 from December 2012, to ensure the inclusion of all relevant studies published by the end of that year. The entire search and selection process was carried out by the author, utilizing the PICOS framework to guide the search strategy. The PICOS elements defined were: P (Patient) as PTSD patients, I (Intervention) as EEG-based Neurofeedback, C (Comparison) as Control (PTSD patients receiving either no treatment or treatments other than EEG-based neurofeedback), O (Outcomes) as psychometric assessments of PTSD, and S (Study Design) as Controlled Studies. The search terms employed were (trauma OR (PTSD OR post-traumatic stress disorder)) AND (Neurofeedback OR NF) AND (EEG OR Electroencephalography).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Inclusion and Exclusion Criteria\u003c/h2\u003e \u003cp\u003eThe search results were combined from all the databases and were initially deleted for duplicates. Studies were included if they met the following criteria:\u003c/p\u003e \u003cp\u003eLanguage: English\u003c/p\u003e \u003cp\u003eDesign: Controlled Study\u003c/p\u003e \u003cp\u003eIntervention: EEG neurofeedback additional with any protocol\u003c/p\u003e \u003cp\u003eControl group: PTSD patients receiving another form of treatment or being waitlisted\u003c/p\u003e \u003cp\u003eParticipant: PTSD patients\u003c/p\u003e \u003cp\u003eEvaluation: PTSD assessment scale\u003c/p\u003e \u003cp\u003eYear: 2013\u0026thinsp;~\u0026thinsp;2023\u003c/p\u003e \u003cp\u003eStudies were excluded if they were conference abstracts, not full texts, didn\u0026rsquo;t have a control, or didn\u0026rsquo;t provide their detailed outcome results in numbers. Studies were not limited to a randomized controlled study.\u003c/p\u003e \u003cp\u003eThe inclusion years of 2013 to 2023 for our meta-analysis are chosen based on significant trends in the field and technological advancements. Firstly, research on neurofeedback, especially EEG-based studies, notably increased starting in 2013, with minimal publications before this year. Secondly, advancements in EEG technology after 2013 have greatly enhanced study reliability and comparability, making earlier studies less compatible with current research due to technological disparities.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Quality Evaluation\u003c/h2\u003e \u003cp\u003eRisk of bias was assessed at each study level using the Cochrane risk of bias (RoB) tool in randomized controlled trials (RCTs) (Higgins et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The criteria included selection bias, allocation bias, detection bias, performance bias, attrition bias, and reporting bias. These risks were evaluated in three levels (i.e. low, unclear, and high) [Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]. To test for the publication bias, the asymmetry of the funnel plot is assessed by visual inspection and by Egger\u0026rsquo;s regression test (Lin \u0026amp; Chu, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) [Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data Extraction\u003c/h2\u003e \u003cp\u003eData was extracted manually upon reading the paper. The data extraction process was reviewed thoroughly to ensure there was no mistake in the extraction process. The primary outcome measure of each study was extracted as our intervention effect evaluation metric. Data was all rounded to the hundredth degree. The same measurement was used to investigate the effect at the follow-up phase (if applicable). If any studies did not report the standard deviation (SD) of their outcome measure but instead reported the confidence interval (CI), the following formula was used to convert that CI to SD:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$SD=\\sqrt{N}\\times \\frac{UpperLimit-LowerLimit}{t}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eN is the sample size of the study and t is a value from the t-distribution with the appropriate tail according to the CI interval and degree of freedom being N-1. For specific measurements and their characteristics, readers are referred to section \u003cspan refid=\"Sec14\" class=\"InternalRef\"\u003e3.2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eAs well as outcome measurements, basic information about the study itself, study design, neurofeedback protocol characteristics, and participant characteristics were extracted. Readers are referred to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for the details of all the specific variables other than the outcome measurements extracted from the studies. If a study did not provide information on any of the variables later used for subsequent data analysis, it is left blank and that study is excluded from that specific analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTable of variables extracted from the studies other than the outcome measurement\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDescription\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBasic information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLink to the study\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublication Year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCountry of recruited Patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhere the patients were recruited\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear of Recruitment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYear of Research\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRecruitment and the research may be done on different years.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy Design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003efollow up duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhen was the follow-up conducted after the experiment? (if applicable)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLosses to follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026thinsp;=\u0026thinsp;losses to follow up were less than 15% of total cases\u003c/p\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;losses were greater than 15%\u003c/p\u003e \u003cp\u003e0\u0026thinsp;=\u0026thinsp;not reported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEnrollment condition of study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026thinsp;=\u0026thinsp;all cases were recruited\u003c/p\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;just pick up convenient cases\u003c/p\u003e \u003cp\u003e0\u0026thinsp;=\u0026thinsp;not reported\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll Outcome Measure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAll metrics the study utilizes to evaluate their intervention.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary outcome measure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTheir primary outcome measure among all.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl group intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdditional intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSome studies also allowed participants to continue receiving their prescribed treatment.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInclusion criteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExclusion criteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistribution of patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u0026thinsp;=\u0026thinsp;patients are randomized on both methods\u003c/p\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;each patient underwent both methods\u003c/p\u003e \u003cp\u003e0\u0026thinsp;=\u0026thinsp;two non-randomized groups of patients\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl Sample size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample size of a control group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExperimental group sample size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample size of an experimental group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFeedback Protocol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFeedback duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDuration of the intervention in weeks.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal number of sessions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal number of sessions held during the whole intervention.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e# of session in a week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration of one session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFeedback Modality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eModality in which participants receive their feedback (ex. auditory, visual).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtracted Feature\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWhich feature of the brain wave were given feedback on as well as whether it was aimed to enhance or\u003c/p\u003e \u003cp\u003ereduce that feature.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTarget Region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe region of electrode which was targeted.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeurofeedback threshold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThreshold it was used to determine the feedback.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics of participants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge (Year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean and SD for each control and experimental group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRatio for each control and experimental group.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChronicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u0026thinsp;=\u0026thinsp;Chronic (Treatment Resistant)\u003c/p\u003e \u003cp\u003e0\u0026thinsp;=\u0026thinsp;Not chronic\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTime since trauma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean and SD\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll analyses were conducted and plots generated using the R package \u0026ldquo;metafor\u0026rdquo; (Viechtbauer, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The effect of EEG neurofeedback on PTSD symptoms was quantified using Hedge\u0026rsquo;s g (Lakens, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) with a 95% confidence interval. Hedge\u0026rsquo;s g, a variation of Cohen\u0026rsquo;s d, corrects for bias and is suitable for small sample sizes. Negative values indicate a beneficial intervention effect, while positive values indicate no effect or a negative intervention effect. Values less than 0.5 are considered small, 0.5 to 0.8 medium, and greater than 0.8 large.\u003c/p\u003e \u003cp\u003eHeterogeneity was assessed using REML estimation (τ\u0026sup2;) (Corbeil \u0026amp; Searle, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1976\u003c/span\u003e) and I\u0026sup2; statistics (Higgins \u0026amp; Thompson, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). I\u0026sup2; statistics measure the proportion of variance due to heterogeneity rather than sampling variance, with I\u0026sup2; \u0026gt; 25%, 50%, and 70% indicating small, medium, and high heterogeneity, respectively. Due to observed heterogeneity, a random effects model (REM) was used to estimate the average treatment effect size. Meta-regressions were conducted to identify variables contributing to the heterogeneity.\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Methodological Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Search Results\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe literature search identified 218 records after the removal of duplicates. After reading the abstracts, 172 articles were excluded according to the inclusion and exclusion criteria. The remaining 46 articles were each screened upon further reading into the full text in which subsequent 35 articles were excluded. For detailed reasons for exclusion, readers are referred to Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In the end, 11 studies were left to include in our study [Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e] (Bell et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; du Bois et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Fruchtman-Steinbok et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Leem et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nicholson et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Noohi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Shaw et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; van der Kolk et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yasuko, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Study Characteristics\u003c/h2\u003e \u003cp\u003eThis meta-analysis included 306 participants from eleven studies, eight of which were randomized controlled trials. Most studies used frequency training (n\u0026thinsp;=\u0026thinsp;8), with one using the LORETA protocol, and another using the AmygdalaEFP protocol.\u003c/p\u003e \u003cp\u003eThe primary outcome measure was the change in PTSD symptom assessments, predominantly using the Clinician-Administered PTSD Scale for DSM (CAPS-5) (n\u0026thinsp;=\u0026thinsp;5) and the PTSD Checklist for DSM (PCL-5) (n\u0026thinsp;=\u0026thinsp;4). Some studies also investigated changes in anxiety (n\u0026thinsp;=\u0026thinsp;3), depression (n\u0026thinsp;=\u0026thinsp;3), emotion (n\u0026thinsp;=\u0026thinsp;2), executive control (n\u0026thinsp;=\u0026thinsp;2), alpha amplitude (n\u0026thinsp;=\u0026thinsp;2), and fMRI signals (n\u0026thinsp;=\u0026thinsp;2). Most studies allowed simultaneous treatment with the EEG neurofeedback intervention.\u003c/p\u003e \u003cp\u003eTables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e summarize the study characteristics and outcome measures. Detailed summaries of each study can be found in the OSF repository (refer to the code and data availability section).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudy characteristics of the included studies other than its outcome measurements. VA\u0026thinsp;=\u0026thinsp;visual\u0026thinsp;+\u0026thinsp;auditory, VAT\u0026thinsp;=\u0026thinsp;visual\u0026thinsp;+\u0026thinsp;auditory\u0026thinsp;+\u0026thinsp;tactile\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor/Year Published/Country of Patient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNF Sample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl Sample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFeedback Duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal number of sessions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e# of session in one week\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDuration of one session\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eFeedback Modality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExtracted Feature\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTarget Region\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNeurofeedback threshold\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eFollow up duration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eAge (mean year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003eGender (% of Male)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003eChronicity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003eTime since trauma (mean year)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKelson/2013/USA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVan der Kolk/2016/USA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIncrease alpha (10\u0026ndash;13 Hz) and decrease theta/delta \u0026amp; High beta (2\u0026ndash;6 Hz, 22\u0026ndash;36 Hz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eT4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e% of time spent in that certain frequency range\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e14.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNoohi/2016/Iran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAuditory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIncrease theta waves ratio (4 to 8 Hz) in relative to alpha waves (8 to 12 Hz)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePz, P3, P4, O1, O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e6w\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAskovic/2019/Australia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 or 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAuditory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIncrease SMR (12\u0026thinsp;~\u0026thinsp;15 Hz) and 8\u0026thinsp;~\u0026thinsp;10/6\u0026thinsp;~\u0026thinsp;9 Hz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eCz, C4, T4, and P4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e65.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBell/2019/USA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDecrease z-score on three network(DMN, CEN, SN)\u0026rsquo;s amplitude, coherence, phase, phase shift, phase lock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e40\u0026ndash;60% reward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNicholson/2020/Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDecrease alpha wave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65% reward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e43.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e27.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruchtman-Steinbok/2021/Israel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2, than 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAmygdalaEFP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eDetermined by (current delta - baseline delta)/SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3 and 6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e36.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBois/2021/Rwanda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVisual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDecrease alpha wave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eIf it\u0026rsquo;s at least 60% smaller than the preceding trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eNon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e53.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeem/2021/Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAuditory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIncrease Alpha(8\u0026ndash;12) \u0026amp; Theta(4\u0026ndash;7) and decrease Beta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1 month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e44.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNicholson/2023/Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDecrease alpha wave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65% reward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e42.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e28.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShaw/2023/Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eVA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDecrease alpha wave\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePz\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e65% reward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e43.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e28.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003e?\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcome measurements for each study. When applicable, standard deviations are given in brackets()\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAuthor/Year Published/Country of Patient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary Outcome Measure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNF : Mean Before\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNF : Mean After\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNF : Follow-Up\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCT : Mean Before\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCT : Mean After\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCT : Follow-Up\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eOther outcome measurement\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eOther Treatment in NF group\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKelson/2013/USA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOriginal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.2(9.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e69.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e78.8(9.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVan der Kolk/2016/USA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAPS-4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e80.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44.12(19.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.23(20.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e75.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e65.68(20.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e64.68(21.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eContinue ongoing treatment (psychotherapeutic, medication)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNoohi/2016/Iran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIES-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.20(7.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30.40(6.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.46(5.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e51.07(5.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e51.14(6.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e51.21(6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eExecutive control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAskovic/2019/Australia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHTQ\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.8(0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.9(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.2(0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3.1(0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAnxiety and Depression, Cognitive control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eTrauma counseling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBell/2019/USA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCL-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.17(14.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.08(12.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e49.82(10.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31.18(13.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAnxiety\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003econtinue ongoing treatment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNicholson/2020/Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAPS-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.86(10.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.39(15.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.58(14.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39.94(7.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.78(12.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.78(12.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003efMRI analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eContinue ongoing medication, not therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFruchtman-Steinbok/2021/Israel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCL-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.75(16.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46.58(14.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46.1(16.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e59.46(11.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e61.33(10.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e59.6(17.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAnxiety, depression, Emotion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003econtinue ongoing treatment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBois/2021/Rwanda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCL-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.9(16.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11(5.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e34.44(23.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e28.66(20.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eResilience, Mental wellbeing, Alpha amplitude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eNothing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeem/2021/Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCL-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.3(10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19.4(7.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.4(6.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e35.1(18.5))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31(14.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e29.4(13.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAnxiety, Depression, Emotion, Cost effectiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eContinue ongoing treatment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNicholson/2023/Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAPS-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.52(9.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e23.19(15.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.65(13.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39.94(7.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.78(12.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31.78(12.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAlpha amplitude\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eContinue ongoing medication, not therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eShaw/2023/Canada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAPS-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.86(10.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e24.42(17.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.59(17.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e39.64(7.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34.04(11.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e32.82(19.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003efMRI analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eContinue ongoing medication, not therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Risk of Bias\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the RoB assessment. All eleven studies showed a low risk of attrition and reporting bias. However, selection bias was high in two studies due to non-random participant allocation. Six studies exhibited a high risk of bias in participant blinding, and four of these also had high detection bias. Some studies claimed randomization but did not detail the process, causing uncertainty in allocation bias.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Publication Bias\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStudies were plotted by their standard error against the standard mean difference (Cohen\u0026rsquo;s d) to create a funnel plot and assess publication bias [Figure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e]. Statistically significant asymmetry (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) using Egger\u0026rsquo;s regression test indicates potential publication bias (Lin \u0026amp; Chu, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). A Contour-Enhanced funnel plot [Figure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e] also suggests publication bias, as fewer studies appear in the areas indicating statistical insignificance (0.1\u0026thinsp;\u0026lt;\u0026thinsp;p\u0026thinsp;\u0026lt;\u0026thinsp;1). However, the small number of studies (n\u0026thinsp;=\u0026thinsp;11) limits the reliability of these tests (Lin \u0026amp; Chu, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, no correlation between study size and effect size (p\u0026thinsp;=\u0026thinsp;0.1697) was found, but the small study effect and potential heterogeneity remain considerations (Sterne et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Contextual Results","content":"\u003ch2\u003e4.1 PTSD symptom decreases immediately after the treatment but with high heterogeneity between studies\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAll included studies assessed PTSD symptoms immediately after the intervention. Figure 5 shows a high effect size of EEG neurofeedback (Cohen\u0026rsquo;s d = -1.28, CI: -1.76 to -0.80, p \u0026lt; 0.0001) with the upper confidence interval still negative. However, there is high heterogeneity among the studies (\u0026tau;\u0026sup2; = 0.4488, I\u0026sup2; = 71.57%, p \u0026lt; 0.01).\u003c/p\u003e\n\u003ch2\u003e4.2 Placebo effect not found\u003c/h2\u003e\n\u003cp\u003eThree studies included a sham control and were analyzed separately for placebo effects. Figure 6 shows that even with sham control, EEG neurofeedback had a high effect size (Cohen\u0026rsquo;s d = -0.63, CI: -1.01 to -0.2, p \u0026lt; 0.05) with no heterogeneity (\u0026tau;\u0026sup2; = 0, I\u0026sup2; = 0%, p \u0026gt; 0.05). This consistency may be due to using the same neurofeedback protocol (alpha wave down-regulation at Pz) and a similar population (treatment-resistant PTSD patients in Canada).\u003c/p\u003e\n\u003ch2\u003e4.3 EEG neurofeedback yields long-term effects\u003c/h2\u003e\n\u003cp\u003eThree studies conducted a 1-month follow-up, and four studies conducted a 3-month follow-up to test the long-term effects of EEG neurofeedback. Figure 7 shows the meta-analysis results. None of the studies conducted both 1-month and 3-month follow-ups. One study with a 6-week follow-up was included in the 1-month group. The 1-month follow-up showed a substantial effect (Cohen\u0026rsquo;s d = -1.72, CI: -3.13 to -0.30, p \u0026lt; 0.05) but with high heterogeneity (\u0026tau;\u0026sup2; = 1.3533, I\u0026sup2; = 87.17%, p \u0026lt; 0.01). The 3-month follow-up showed a moderate effect size (Cohen\u0026rsquo;s d = -0.72, CI: -1.07 to -0.37, p \u0026lt; 0.0001) with no heterogeneity. All three of the four 3-month follow-up studies used the same neurofeedback protocol (alpha down-regulation at Pz) and a similar population (Canadian), while one used a different protocol and population (AmygEFP with an Israeli population). This suggests consistent effects of EEG neurofeedback up to 3 months, regardless of the protocol or population, but the small sample size limits the interpretation. Overall, these results support that EEG neurofeedback can improve PTSD symptoms for up to 3 months.\u003c/p\u003e\n\u003ch2\u003e4.4 Moderators\u003c/h2\u003e\n\u003cp\u003eGiven the high heterogeneity across studies, several within-study factors may contribute to this.\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003e4.4.1 # of session, # of weeks, duration of session\u003c/h3\u003e\n\u003cp\u003eFigure 8, 9, and 10 shows the meta-regression computed with the total number of EEG-neurofeedback sessions, total number of weeks spent on the intervention, and duration of each session, respectively, as a moderator. For all moderators, there is still a significant amount of heterogeneity left (i.e. 71%, 80%, and 73%) and the effect of the moderator is not statistically significant (p \u0026gt; 0.05). Thus, these indicate that these do not affect the outcome.\u003c/p\u003e\n\u003ch3\u003e4.4.2 Year\u003c/h3\u003e\n\u003cp\u003eFigure 11 shows the meta-regression using the year of publication as a moderator. Despite significant residual heterogeneity (55%, p \u0026lt; 0.05), the moderator effect is statistically significant (p \u0026lt; 0.01). This indicates that more recent studies show a reduced effect size.\u003c/p\u003e\n\u003ch3\u003e4.4.3 Simultaneous Treatment\u003c/h3\u003e\n\u003cp\u003eThree out of eleven studies had an experimental group without additional treatment (e.g., psychotherapy, medication), and the control group received no medical treatment. In the other eight studies, participants continued their ongoing PTSD treatments. Of these, three allowed psychotropic medication but no other psychotherapy, one required traditional trauma counseling alongside EEG neurofeedback for all participants, and four allowed any treatment outside the experiment. All eight studies prohibited changing treatments during the experiment. Figure 12 shows meta-regression results with simultaneous treatment as a moderator. The residual heterogeneity remains significant (49%, p \u0026lt; 0.05), but the moderator test is statistically significant (p \u0026lt; 0.0001). Studies without simultaneous treatment showed a larger estimated effect size (Cohen\u0026rsquo;s d = -2.3377) compared to those with simultaneous treatment (Cohen\u0026rsquo;s d = -0.949).\u003c/p\u003e\n\u003ch3\u003e4.4.5 Targeting Pz\u003c/h3\u003e\n\u003cp\u003eFive out of eleven studies targeted the Pz region, located on the midline parietal lobe. Figure 13 shows meta-regression results using this factor as a moderator. Despite significant residual heterogeneity (65%, p \u0026lt; 0.01), the moderator is statistically significant (p \u0026lt; 0.0001). Studies not targeting Pz showed a larger effect size (Cohen\u0026rsquo;s d = -1.4983) compared to those targeting Pz (Cohen\u0026rsquo;s d = -0.8562), opposing the current trend to focus on the Pz region.\u003c/p\u003e\n\u003ch3\u003e4.4.6 Pz Targeted down-regulation of Alpha Wave\u003c/h3\u003e\n\u003cp\u003eFour out of five studies targeting the Pz electrode used an alpha down-regulation neurofeedback protocol. Figure 14 shows the meta-regression with this factor as a moderator. Although there is significant residual heterogeneity (\u0026tau;\u0026sup2; = 0.4488, I\u0026sup2; = 54.94%, p \u0026lt; 0.05), 45% of the heterogeneity was explained by this moderator (p \u0026lt; 0.0001). The effect size was larger for studies not using the Pz alpha down-regulation protocol (Cohen\u0026rsquo;s d = -1.4879) compared to those using it (Cohen\u0026rsquo;s d = -0.7339), despite its frequent use.\u003c/p\u003e\n\u003ch3\u003e4.4.7 Increasing Alpha Wave\u003c/h3\u003e\n\u003cp\u003eFour out of eleven studies used an alpha up-regulation neurofeedback protocol. Figure 15 shows the meta-regression with this factor as a moderator. Despite significant residual heterogeneity (50%, p \u0026lt; 0.05), the moderator effect is statistically significant (p \u0026lt; 0.0001). Interestingly, studies with alpha up-regulation showed about twice the effect size (Cohen\u0026rsquo;s d = -1.7090) compared to those without it (Cohen\u0026rsquo;s d = -0.8262), contrary to the trend of down-regulating alpha.\u003c/p\u003e\n\u003ch3\u003e4.4.8 Feedback Modality\u003c/h3\u003e\n\u003cp\u003eThe feedback modality was evaluated as a moderator in eleven studies, categorized as visual only, auditory only, visual + auditory (VA), or visual + auditory + tactile (VAT). Figure 16 shows the results, indicating that feedback modality explained 92% of the heterogeneity. The estimated effect sizes are: VAT = -3.3643 (p \u0026lt; 0.001), Auditory = -2.0186 (p \u0026lt; 0.0001), Visual = -1.1756 (p \u0026lt; 0.05), VA = -0.8258 (p \u0026lt; 0.0001). VAT yielded the highest effect, though based on a single study with a small sample size (n = 10). Interestingly, single modalities (auditory or visual) had higher effect sizes than combined modalities (VA).\u003c/p\u003e"},{"header":"5 Discussion","content":"\u003cp\u003eIn the last 10 years, there has been a rapid increase in studies that test the efficiency of EEG neurofeedback for treating PTSD. This meta-analysis demonstrated the importance of neurofeedback protocol in efficacy and overall strongly supports a need for future research.\u003c/p\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e5.1 EEG neurofeedback can treat PTSD symptoms\u003c/h2\u003e \u003cp\u003eMeta-analytic evidence suggests that EEG neurofeedback is a promising treatment for PTSD symptoms, showing high effect sizes that are statistically significant. Sham-controlled studies confirm that these benefits are not due to placebo effects. High effect sizes persist at both one-month and three-month follow-ups, despite broad confidence intervals likely due to small sample sizes, indicating potential long-term therapeutic effects of EEG neurofeedback.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e5.2 EEG neurofeedback can alter neural activity\u003c/h2\u003e \u003cp\u003eThe premise that brainwave patterns can be modulated through neurofeedback, particularly in treating PTSD with EEG neurofeedback, requires validation. Despite its crucial role in treatment efficacy, comprehensive studies substantiating this for PTSD patients are scarce. Three studies (du Bois et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nicholson et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Shaw et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) focused on downregulating alpha wave amplitude in the Pz region and assessing changes during treatment sessions, consistently demonstrating expected alterations in alpha wave amplitude. One study (Nicholson et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) observed a significant increase in alpha power in the medial frontal gyrus post-intervention, compared to reduced alpha power at baseline. These results support that neurofeedback can modulate brainwave activity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003e5.3 Mechanisms underlying EEG neurofeedback might be the normalization of broad neural network\u003c/h2\u003e \u003cp\u003eEmpirical evidence indicates EEG neurofeedback can modulate brain activity, but specific mechanisms affecting PTSD patients remain unidentified. A prevailing hypothesis suggests targeted manipulation of brainwave patterns modifies neural networks, especially the brain\u0026rsquo;s intrinsic connectivity networks (ICNs) (Nicholson et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shaw et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The ICNs include the central executive network (CEN), default mode network (DMN), and salient network (SN) (Menon, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Consistent indications of dysfunction in these networks among PTSD patients are identified (Akiki et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Holmes et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kennis et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Shang et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Thus, normalization of these networks could potentially alleviate PTSD symptoms.\u003c/p\u003e \u003cp\u003eAmong the eleven reviewed studies, two specifically assessed ICNs before and after EEG neurofeedback (Nicholson et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shaw et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Both experimental and control groups underwent fMRI assessments pre- and post-intervention to quantify changes in ICN activity and connectivity. The studies consistently employed an EEG neurofeedback protocol targeting alpha wave reduction at the Pz electrode location. Results demonstrated significant normalization in ICNs among PTSD patients who received EEG neurofeedback. The experimental group exhibited reduced connectivity within the DMN, suggesting normalization of hyperactive posterior DMN activity and improved executive control. Within the SN, diminished connectivity was observed between the right anterior insula and SN, supporting the restorative effects of EEG neurofeedback on system connectivity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec33\" class=\"Section2\"\u003e \u003ch2\u003e5.4 Midline parietal lobe targeted EEG neurofeedback does not yield a higher effect size\u003c/h2\u003e \u003cp\u003eThis meta-analysis reveals that protocols targeting the Pz electrode, located over the midline parietal lobe, are associated with smaller effect sizes compared to those targeting other regions. Moreover, our specific examination of alpha wave down-regulation, as studied by Kluetsch et al. (Kluetsch et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), who explored the \u0026lsquo;alpha rebound effect\u0026rsquo;\u0026mdash;where alpha waves return to a baseline level following down-regulation through EEG neurofeedback, showed that while this approach seemed promising for conditions like PTSD, where reduced alpha waves are common (Eidelman-Rothman et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), it did not yield higher effect sizes. In contrast, protocols aiming to increase alpha wave activity exhibited higher effect sizes. Thus, while Pz-targeted alpha down-regulation has potential, our findings suggest a need for reevaluating targeted protocols to optimize EEG neurofeedback outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec34\" class=\"Section2\"\u003e \u003ch2\u003e5.5 Different feedback modalities yield different effect size\u003c/h2\u003e \u003cp\u003eAmong prevalent neurofeedback modalities, visual and auditory feedback are most extensively utilized across various studies. Currently, no definitive guidelines specify which modality is superior. Data from a single study indicates a highest effect size for a multi-sensory modality combining visual, auditory, and tactile feedback. Auditory feedback alone follows in effect size, with visual feedback alone next. Surprisingly, a combined visual and auditory feedback modality yielded the lowest effect size. This finding challenges the notion that multi-sensory feedback inherently enhances neuroplastic learning. These provisional findings suggest future research should focus on the efficacy and cost-effectiveness of single-modal feedback mechanisms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec35\" class=\"Section2\"\u003e \u003ch2\u003e5.6 More feedback sessions are not more effective\u003c/h2\u003e \u003cp\u003eOur analysis revealed no significant impact of the number of training sessions on PTSD treatment outcomes. Neither the duration of individual sessions nor the overall length of the intervention period were significant factors. These findings suggest that EEG neurofeedback can be effective within a brief intervention period, reducing both financial costs for patients and resource burdens for clinics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec36\" class=\"Section2\"\u003e \u003ch2\u003e5.7 Simultaneous treatment tends to decrease the efficacy of the neurofeedback\u003c/h2\u003e \u003cp\u003eNeurofeedback is often used alongside other therapies, but data indicated that studies prohibiting concurrent treatments yielded higher effect sizes. Studies disallowing additional therapies often involved participants from countries with lower medical standards, while those permitting concomitant therapies involved participants from countries with high-quality medical care. This suggests the efficacy of EEG neurofeedback could be higher in populations with limited access to quality medical care. Future research is necessary to explore these relationships.\u003c/p\u003e \u003c/div\u003e"},{"header":"6 Limitations","content":"\u003cdiv id=\"Sec38\" class=\"Section2\"\u003e \u003ch2\u003e6.1 Limitations of the Studies\u003c/h2\u003e \u003cp\u003eMany studies lack explicit details on neurofeedback protocols. Future research must specify attributes such as feedback modality, target features, target regions, feedback threshold, duration, and frequency of sessions. Moreover, the role of PTSD chronicity is often overlooked, potentially skewing outcomes. Future studies should assess trauma chronology and control for this variable. Sample sizes are also generally small (max\u0026thinsp;=\u0026thinsp;44), compromising statistical power. A sample size larger than 70 is recommended [44, 80]. Lastly, less than half of the studies used a double-blind design. Adopting double-blind, randomized controlled trials is crucial for rigor and reliability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec39\" class=\"Section2\"\u003e \u003ch2\u003e6.2 Limitations of this Study\u003c/h2\u003e \u003cp\u003eDue to the nascent state of this field and the predominance of studies with limited sample sizes, drawing definitive conclusions remains challenging.\u003c/p\u003e \u003c/div\u003e"},{"header":"7 Conclusion","content":"\u003cp\u003eEEG neurofeedback has emerged as a potential treatment for PTSD, with an increasing number of controlled trials evaluating its efficacy. Despite this, no comprehensive meta-analysis has systematically assessed these studies or quantified EEG neurofeedback\u0026rsquo;s therapeutic impact on PTSD. Furthermore, there is a lack of meta-analytic evaluations comparing different EEG neurofeedback protocols. In this study, we assessed the overall effectiveness of EEG neurofeedback in mitigating PTSD symptoms. A meta-regression determined that EEG neurofeedback significantly impacted PTSD symptoms immediately post-intervention and sustained this effect over the long term (one and three months), not driven by placebo effects. The feedback protocol, specifically target frequency and region, and the feedback modality, were identified as the most influential factors in treatment success. In contrast, treatment duration, number, frequency, and session number did not influence the outcome. Contrary to the prevalent focus on down-regulating alpha waves at the midline parietal region, our meta-regression indicated that alternative protocols might offer better outcomes. Future studies should investigate other protocols. Similarly, our findings suggest that a single-modality approach, especially auditory feedback, may be more effective and cost-efficient than a multi-modality approach. Based on these results, we encourage future research to explore alternative regions and feedback modalities to enhance treatment effectiveness.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRegistration and Protocol\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis review was not registered. The review protocol was developed based on Tawfik\u0026rsquo;s guideline of a systematic review and a meta-analysis (Tawfik et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e"},{"header":"Statements and Declarations","content":"\u003cp\u003eData Availability: All data generated or analyzed during this study are available from the OSF repository (https://osf.io/bca82/).\u003c/p\u003e\n\u003cp\u003eFunding Statement: This research was not funded.\u003c/p\u003e\n\u003cp\u003eCompeting Interest: The author declares that they have no competing interests, financial or otherwise, that have influenced the research and the development of this paper.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcknowledgements: I would like to extend my deepest gratitude to Sophie Rogers of Pennsylvania University for her invaluable guidance on research methodology and result synthesis throughout the course of this research endeavor. Her meticulous review of the final manuscript has been instrumental in enhancing the quality of this work.\u003c/p\u003e\n\u003cp\u003eConflict of Interest\u003c/p\u003e\n\u003cp\u003eThe author declares that there are no competing interests in the publication of this paper.\u0026nbsp;No funds, grants, or other support was received.\u0026nbsp;There are no financial, personal, or professional relationships that could potentially influence or bias the work presented herein. All procedures and methodologies were conducted impartially and without any conflict of interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCode and Data Availability\u003c/p\u003e\n\u003cp\u003eAll data and code used in the meta-analysis presented in this paper are openly available for the benefit of the scientific community and to ensure the transparency and reproducibility of our work. The datasets, along with the associated code, have been deposited in the Open Science Framework (OSF) repository (bca82). 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(2013). \u003cem\u003eVeterans Symptoms of Posttraumatic Stress Disorder (PTSD). ProQuest\u003c/em\u003e. -origsite=gscholar\u0026amp;cbl=18750\u0026amp;diss=y. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://search.proquest.com/openview/019272465d8a47db88d836776a6a0ccb/1?pq\u003c/span\u003e\u003cspan address=\"http://search.proquest.com/openview/019272465d8a47db88d836776a6a0ccb/1?pq\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"PTSD, EEG Neurofeedback, Meta-analysis, Meta-regression, Treatment Protocols","lastPublishedDoi":"10.21203/rs.3.rs-3644363/v3","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3644363/v3","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eObjective: Post-traumatic stress disorder (PTSD) remains a significant clinical challenge with limited treatment options. Although electroencephalogram (EEG) neurofeedback has garnered attention as a prospective treatment modality for PTSD, no comprehensive meta-analysis has been conducted to assess its efficacy and compare different treatment protocols. This study aims to provide a multi-variable meta-regression analysis of EEG neurofeedback's impact on PTSD symptoms, while also assessing variables that may influence treatment outcomes.\u003c/p\u003e\n\u003cp\u003eMethods: A systematic review was performed to identify controlled studies exploring for the efficacy of EEG neurofeedback on PTSD. The overall effectiveness was evaluated through meta-analysis, and a multi-variable meta-regression was employed to discern fact0rs affecting the EEG neurofeedback efficacy.\u003c/p\u003e\n\u003cp\u003eResults: EEG neurofeedback yielded a statistically significant reduction in PTSD symptoms immediately post-intervention, with sustained effects at one and three months follow-up. A sub-analysis of sham-controlled studies confirmed that outcomes were not driven by placebo effects. Our findings also identified the target frequency and region, as well as feedback modality, as significant factors for treatment success. In contrast, variables related to treatment duration were not found to be significant moderators, suggesting cost-effectiveness.\u003c/p\u003e\n\u003cp\u003eConclusions: EEG neurofeedback emerges as a promising and cost-effective treatment modality for PTSD with the potential for long-term benefits. Our findings challenge commonly utilized protocols and advocate for further research into alternative methodologies to improve treatment efficacy.\u003c/p\u003e","manuscriptTitle":"Can electroencephalography-based neurofeedback treat post-traumatic stress disorder? A meta-analysis study","msid":"","msnumber":"","nonDraftVersions":[{"code":"","date":"2025-02-19 02:23:08","doi":"","editorialEvents":[{"type":"decision","content":"Accepted","date":"2025-02-24T20:52:05+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-20T04:49:26+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Psychophysiology and Biofeedback","date":"2025-02-19T02:07:50+00:00","index":"","fulltext":""}],"status":"private","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}},{"code":"","date":"2025-02-10 03:23:13","doi":"","editorialEvents":[{"type":"decision","content":"Revision requested","date":"2025-02-13T19:08:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-10T08:24:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Psychophysiology and Biofeedback","date":"2025-02-10T03:11:37+00:00","index":"","fulltext":""}],"status":"private","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}},{"code":3,"date":"2024-08-26 13:47:49","doi":"10.21203/rs.3.rs-3644363/v3","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision 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Biofeedback","date":"2024-06-04T06:58:42+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6bf9df56-d658-475f-a3ee-bfc0e1cefed6","owner":[],"postedDate":"August 26th, 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