Advancements and challenges in the application of noninvasive neuromodulation techniques in treatment of depression: A systematic review

Advancements and challenges in the application of noninvasive neuromodulation techniques in treatment of depression: A systematic review | 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 Advancements and challenges in the application of noninvasive neuromodulation techniques in treatment of depression: A systematic review Mohammed Gamil Mohammed Saif This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7278463/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Depressive disorders (including both unipolar and bipolar depression) continue to present treatment challenges, with many patients failing to achieve adequate symptom relief. Non-invasive neuromodulation techniques (NINTs) have emerged as promising alternative interventions, particularly valuable in resource-limited settings. Our systematic review, drawing from PubMed and Scopus databases (2016-January 2024), evaluates current evidence on NINTs protocols for depression treatment. Key findings indicate that while most clinical applications still employ open-loop systems, closed-loop approaches utilizing EEG biomarkers (notably alpha peak frequency and frontal-midline theta power) demonstrate enhanced treatment precision. However, significant challenges remain in establishing reliable biomarker protocols for closed-loop implementation. NINTs offer particular advantages for lower middle-income countries (LMICs) through their cost-effectiveness, scalability, and minimal infrastructure requirements, though initial costs and regulatory barriers limit widespread adoption. This review highlights the urgent need for standardized protocols and identifies promising research directions to optimize NINTs' therapeutic potential. The transition from open-loop to biomarker-guided closed-loop systems represents a critical frontier in depression treatment innovation. Cognitive Neuroscience Depression Electroencephalography Neurofeedback Non-invasive neuromodulation Transcranial direct current stimulation Transcranial magnetic neurostimulation. Figures Figure 1 1. Introduction Depression is a prevalent psychiatric disorder that negatively affects the quality of life of millions of people worldwide and can lead to suicide in severe cases (J. Liu, Liu, Ma, Tong, & Zheng, 2024 ). Although a definitive and universally accepted classification system for depression remains elusive, the American Psychiatric Association categorizes depressive disorders into several subtypes, including major depressive disorder (MDD), dysthymia (Gao et al., 2025 ; Zhang, Ren, & Zhang, 2023 ). While there are many options currently available for the treatment of depressive disorders, it is estimated that 70% of depressed people in general and 10 to 30% of MDD patients remain untreated (Cheng et al., 2023 ; G. Liu et al., 2023 ). Non-invasive neuromodulation techniques (NINTs) represent an expanding frontier in the management of neurological and neuropsychiatric conditions, such as depressive disorders (De Koninck, Brazeau, Guay, Herrero Babiloni, & De Beaumont, 2023 ). These methods employ physical interventions to modulate, suppress, enhance, or otherwise regulate neural activity without requiring surgical implantation (Hernandez-Pavon et al., 2023 ). Drug therapy can achieve the same therapeutic outcomes in some cases, while physical neuromodulation offers the advantage of avoiding the systematic side effects of pharmacotherapies (Bledsoe, Viser, & San Luciano, 2020 ). The most common NINTs include repetitive transcranial magnetic stimulation (rTMS) (Lanza et al., 2023 ), transcranial alternating current stimulation (tACS) (D. Li et al., 2024 ), transcranial direct current stimulation (tDCS) (Murphy et al., 2023 ), and neurofeedback based on real-time measurements of electroencephalography (EEG) (Saif, 2023 ). rTMS operates through high-intensity magnetic pulses applied over the scalp that induce electrical currents in the targeted cortex (Slan et al., 2024 ). It is thought that the application of low frequency rTMS, equal to or less than 1 Hz, produces an inhibitory effect on the cerebral cortex, whereas high frequency rTMS, greater than 1 Hz, results in a stimulating effect (Zaidi et al., 2024 ). TMS was approved by the Food and Drug Administration (FDA) in the United States in 2008 for treatment of major depressive disorder through applying rTMS over the cortex thought to have decreased neuronal activity (S. Han et al., 2023 ). While tACS involves applying low-intensity sinusoidal currents to the scalp (Shao et al., 2025 ), tDCS consists of the application of a weak direct current, typically 1–2 mA, to modulate cortical activity (Chen et al., 2023 ). Neurofeedback training is an emerging neuromodulation modality based on the recording of EEG and simultaneously providing real-time visual or auditory feedback (Saif & Sushkova, 2023 ). NINTs provide cost-effective, scalable, and culturally acceptable treatments for depression, particularly in lower- and middle-income countries (LMICs) where mental health resources are limited (Belay, Engel, Lee, Le, & Mihalopoulos, 2023 ) (K. W. W. Mudiyanselage et al., 2024 ); these techniques require minimal infrastructure and training, making them suitable for primary healthcare settings (Mutyambizi-Mafunda et al., 2023 ). Their portability and lower recurring costs enhance accessibility in underserved areas (Vlaicu & and Bustuchina Vlaicu, 2020 ). However, initial investment and regulatory frameworks remain challenges (Xie & Zhang, 2022 ). Given these advantages, NINTs hold promise for bridging the mental health treatment gap in LMICs (Klooster, Voetterl, Baeken, & Arns, 2024 ). Owing to the ability of NINTs to modify cortical activity with little or no side effects, there is a growing research interest among neuroscientists in the application of NINTs for treatment of depressive disorders (Cindik-Herbrüggen & Duymaz, 2023 ; W.-Y. Hsu, Zanto, Park, Gazzaley, & Bove, 2023 ; Vigod et al., 2019 ). Yuan et al investigated and compared the efficacy of 10Hz-rTMS and intermittent theta burst stimulation (iTBS) in treatment of post-traumatic stress disorder (PTSD) and found that both 10Hz-rTMS and iTBS resulted in significant improvements in the symptoms of PTSD, with no significant difference in the efficacy of 10Hz-rTMS from that of iTBS (Yuan et al., 2023 ). Han et al showed that 10 sessions of a 2 mA tDCS stimulation applied for treatment of patients with post-traumatic stress disorder, with the anode positioned over the F3 area and the cathode over the F4, resulted in a significant reduction in the severity and frequency of post-traumatic stress disorder in approximately 60% of the participating patients (J. Han et al., 2022 ). EEG based brain-computer interface, as a communication system between the brain and a computer, is used to automate the process of neuromodulation through monitoring the brain’s response to neuromodulation procedures and adjusting the stimulation parameters in real time, and thereby increasing the effect of neuromodulation (Alam, Rodrigues, Pham, & Thakor, 2016 ; Merk et al., 2022 ). Nevertheless, the use of NINTs for treating depression is not without controversy. While some studies (Miuli et al., 2021 ; Shamabadi et al., 2023 ) have reported significant effects of NINTs in the treatment of depressive disorders, other studies (Cai et al., 2024 ; Konstantinou et al., 2022 ) showed no significant effects of the same NINTs applied to the same depressive disorder. It is still challenging for the neuroscience community to determine more acceptable and efficacious NINTs protocols for the treatment of depressive disorders as there are no sufficient studies that directly compare the efficacy of different NINTs protocols (C.-W. Hsu et al., 2024 ). Thus, this review synthesized research that focused on the application of NINTs for the treatment of depressive disorders. The aim of this review was to provide a direct comparison of the efficacy of NINTs and to ascertain whether there is a possibility that different protocols of neuromodulation within each neuromodulation technique may exhibit different levels of clinical efficacy in the treatment of depressive disorders. 2. Material and Methods The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) (Page et al., 2021) was used in this review as shown in Fig. 1. 2.1. Search strategy The Scopus and PubMed databases were searched for articles published between 2016 and 2024 using the following search terms: ("Transcranial Direct Current Stimulation"[Mesh] OR "noninvasive neuromodulation method*"[tw] OR tDCS [tw] OR tACS [tw] OR rTMS[tw] OR neurofeedback[tw] OR "ultrasonic stimulation"[tw] OR TUS[tw] OR "near-infrared laser stimulation"[tw] OR "magnetic stimulation"[tw] OR "direct current stimulation"[tw] OR "alternating current stimulation"[tw] OR iTBS[tw] OR "theta burst stimulation"[tw]) AND ("Bipolar Disorder"[Mesh] OR "bipolar depression" [tw] OR "manic depression" [tw]) in PubMed. ("Transcranial Direct Current Stimulation" OR "noninvasive neuromodulation method*" OR tDCS OR tACS OR rTMS OR neurofeedback OR "ultrasonic stimulation" OR TUS OR "near-infrared laser stimulation" OR "magnetic stimulation" OR "direct current stimulation" OR "alternating current stimulation" OR iTBS OR "theta burst stimulation" AND ("bipolar disorder" OR "bipolar depression" OR "manic depression")) in Scopus. 2.2. Eligibility criteria Eligibility criteria were set according to the patient or population/problem, intervention, comparison and outcomes (PICO) format as follows: Population - patients with depressive disorders; Intervention – non-invasive neuromodulation techniques; Comparison - controlled conditions; Outcome - Clinical improvement of depression symptoms. Systematic reviews of brain stimulation studies were included if they were published between 2016 and Jan. 2024 in a peer-reviewed journal. The publication language was limited to English. 2.3. Identification and data collection process The search for relevant publications was performed on two electronic databases as mentioned above and any duplication of publications was removed. Following the screening of the titles and abstracts of the articles, all articles that were not in the scope of the review, despite mentioning the search terms, were excluded. The full texts of publications that met the inclusion criteria outlined above were then downloaded, and carefully reviewed to ensure their relevance. If the full-text of an article was not retrievable, those articles were excluded as well. This process is illustrated in a PRISMA flow diagram in Fig. 1. The data extracted from the included systematic reviews was as follows: Review aim; number of included studies; report of risk of bias; characteristics of neuromodulation protocols; conclusion; challenge or recommendation for future research. 2.4. Assessment of study quality The methodological quality of the included systematic reviews was independently evaluated by two reviewers (Al-harosh Mugeb and Lyudmila Sushkova) using A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR-2). Reviews were categorized based on their overall confidence rating: "High" (no critical flaws across all seven critical domains and ≤ 1 non-critical weakness), "Moderate" (one critical flaw, excluding domains 2, 4, or 7, with minor non-critical weaknesses), "Low" (multiple critical flaws or a major flaw in domains 2, 4, or 7), or "Critically Low" (multiple critical flaws rendering the review unreliable). Only systematic reviews achieving "High," "Moderate," or "Low" confidence ratings were included in the final analysis; those rated as "Critically Low" were excluded (See Table 1 , Table 2 , and Table 3 ). 3. Results 3.1. Included articles Literature search using the above-mentioned search terms resulted in a total of 232 references; 56 publications found in PubMed database and 176 in Scopus. Following the removing of duplicates, 229 publications remained, of which only 17 publications met the eligibility criteria and were included. A total of 306 primary studies were analyzed across the systematic reviews. 3.2. Characteristics of the included studies The 17 included studies were classified into three groups based on the brain stimulation technique applied for treating patients with depressive disorders. The included studies show that TMS, TES, and neurofeedback training (NFT) are the most common techniques applied for non-invasive brain stimulation of patients with depressive disorders. 3.2.1. TMS protocols TMS, in general, operates through high-intensity magnetic pulses applied over the scalp that induce electrical currents in the targeted cortex. Shamabadi et al (Shamabadi et al., 2023 ) explored the performance of different TMS protocols in treatment of bipolar depression; the TMS protocols were rTMS and intermittent theta burst stimulation (iBTS) with multiple parameters, such as frequency which varied between 1 and 20 Hz, number of sessions that fluctuated in the 10–100 range and duration of the intervention that was within the range of 10 days to 4 weeks. As a result of the application of TMS in treating patients with BD, there were significant effects on functional connectivity, and metabolic changes in cortical and subcortical brain areas. Cai et al (Cai et al., 2024 ) examined the efficacy of the continuous TBS (cTBS) protocol in treating depressive disorders. The explored parameters of the cTBS protocol were duration of treatment that fluctuated within the range of 1 to 14 weeks, number of sessions that varied between 10 and 15 sessions, number of pulses per session that was within the range of 600 to 3600 pulses, frequency that was 50 Hz, and the site of neurostimulation over the cortex that was right dorsolateral prefrontal cortex (rDLPFC); however, results showed that cTBS was ineffective in treatment of depressive disorder. Konstantinou et al (Konstantinou et al., 2022 ) investigated the evidence on the use of TMS protocols in different stages of BD, such as manic and mixed episodes and have concluded that there is still a lack of information on whether the effect of TMS extends to manic or mixed episodes (See Table 1 ). Chu et al (Chu et al., 2021 ) compared the efficacy of the standard rTMS and TBS protocols in treating depressive disorders and found that TBS treatment was more efficient in terms of time and energy than the standard rTMS as it is shown in Table 1 . The risk of developing a hypomanic/manic switch (HMS) during the application of TMS protocols in treating mood disorders was investigated by Miuli et al (Miuli et al., 2021 ), who found that TMS seems not to be related to HMS development. The key challenges in the application of TMS in treating depressive disorders, as it was reported in the included studies, were the lack of standardized TMS protocols, and the lack of conclusive neuroimaging and clinical biomarkers that can be used for prediction and optimization of response to TMS as shown in Table 1 and Table 1.1 . Table 1 Characteristics of the included TMS studies Source Review aim No of included studies Overall Confidence Rating According to AMSTAR-2 Country Conclusion Challenge (Shamabadi et al., 2023 ) To collect all available evidence on neuroimaging findings, indicating functional, structural, and metabolic brain changes associated with rTMS in individuals with BD 11 Moderate USA, New Zealand, Canada, Others rTMS has significant effects on brain activation, functional connectivity and brain metabolism of cortical and subcortical brain areas in BD There are still no conclusive neuroimaging and clinical biomarkers that can be used for prediction and optimization of response to rTMS in BD (Cai et al., 2024 ) To examine the clinical efficacy and acceptability of cTBS for MDD or BD patients 3 High Taiwan, India, Israel cTBS was not more efficacious than sham cTBS for MDD or BD patients with major depressive episode Future large-scale studies are warranted to assess the efficacy of cTBS for MDD or BD patients with a major depressive episode (Konstantinou et al., 2022 ) To review the evidence on the use of rTMS across the different stages of BD 31 Moderate Nr There is no consensus on the most effective rTMS protocol, and more adequately powered sham-controlled studies are required to verify the efficacy of rTMS in BD The current data regarding the application of rTMS in BD patients remain limited (Miuli et al., 2021 ) To examine the risk of developing HMS during active TMS treatment of mood disorders 25 High Canada, Japan, Taiwan, Others TMS seems not to be related to HMS development Nr (Nguyen, Hieronymus, Lorentzen, McGirr, & Østergaard, 2021 ) To provide an estimate of the efficacy of rTMS in bipolar depression 20 Moderate USA, Switzerland, Australia, Others rTMS seems effective in the treatment of bipolar depression The lack of sufficiently powered confirmatory RCTs Table 1 (continued). Characteristics of the included TMS studies (Sciortino et al., 2021 ) To summarize the results of RCTs using rTMS for improving cognitive symptoms in SCZ and BD 15 Low China, Germany, UK, Others In BD, rTMS seemed to improve cognitive domains in euthymic patients, while its effect during acute phases, especially depression, appeared limited Standardized protocols of rTMS are still lacking (Chu et al., 2021 ) To examine the studies on efficacy and tolerability of TBS in patients with MD 10 Moderate Taiwan, Germany, Belgium, Others TBS treatment was more efficient in terms of time and energy than the standard rTMS was Nr (Hett & Marwaha, 2020 ) To review the extant literature on the use of rTMS to treat BD across different mood states 34 Moderate Belgium, USA, Italy, Others rTMS appears to be efficacious in treating BD and mania. However, when compared with sham treatments, most RCTs reported no significant differences in symptom There is a lack of any adequately powered trial and the ideal rTMS treatment parameters to help better determine the efficacy of rTMS in the treatment of BD (Tee & Au, 2020 ) To summarize the available data from RCTs on the treatment efficacy of rTMS for bipolar depression and mania 11 Moderate China, Brazil, India, Others rTMS appears safe and effective in treating bipolar depression More Stringent RCTs in this area will still be needed before the treatment can be recommended in BD (Gold et al., 2019 ) To evaluate the existing literature on TMS as a treatment for BD across varied mood states 23 Low USA, Iran, France, Others Transcranial magnetic stimulation is a promising approach for treating patients with BD who have failed to respond to pharmacological or psychosocial treatment Future research should more clearly elucidate which TMS protocols may be most effective for a given bipolar patient Note : BD: bipolar depression; rTMS: repetitive transcranial magnetic stimulation; TBS: theta burst stimulation; Nr: not reported; HMS: hypomanic/ manic switch; cTBS: Continuous TBS; MDD: Major depressive disorder; RCTs: randomized controlled trials; SCZ: Schizophrenia. Table 1.1 Parameters of the TMS protocols applied for treating depressive disorders Source Depressive disorder Mode of neurostimulation Duration of neurostimulation Site of stimulation Imaging modality or Depression rating scale (Shamabadi et al., 2023 ) MDD; BD; BD-1; BD-2 (1–20) Hz rTMS; iTBS- 600 pulses each session, delivered as triplets of 50 Hz repeated at 5 Hz (2–4) weeks, 5 times a week dmPFC; sgACC; mPFC; SMN; SN; RSNs; rFPN; PET; fMRI; ECD SPECT; PET + MRI; FDG-PET/H 15 2 O; MRI + [18F]-FDG-PET; MRI (T1) (Cai et al., 2024 ) MDD; BD; TRD cTBS: (600–3600) pulses per session (1–2) weeks rDLPFC DSM-IV; ICD-10 (Konstantinou et al., 2022 ) BD; Mania; mixed episode (1–50) Hz rTMS; 50 Hz iTBS; cTBS1200; cTBS1800; cTBS3600 (10–30) sessions of (10–60) seconds Right DLPFC; Left DLPFC Nr (Miuli et al., 2021 ) Late-life TRD; MDE; BD 1980 impulse/session of 18 Hz dTMS; (1–18) Hz rTMS with (300-12000) impulse/session; (1–10) Hz Bilateral rTMS; 990 impulse/session of 50 Hz iTBS (5–30) sessions LDLPFC; RDLPFC Nr (Nguyen et al., 2021 ) BD (1–10) Hz Bilateral rTMS (10–30) sessions LDLPFC; RDLPFC HRDS, MADRS (Sciortino et al., 2021 ) BD-I; BD-II LDLPFC 10Hz rTMS and RDLPFC 1Hz rTMS 30 trains of 4 s at 10 Hz and 80% MT followed by 12 s off (1200 pulses) at LDLPFC; 120 trains of 10 s at 1Hz and 80% MT followed by 2 s off (1200 pulses) at RDLPFC LDLPFC; RDLPFC WAIS-III; RAVLT; Chinese versions of WCST, Stroop Test, and TMT (Chu et al., 2021 ) MDD cTBS; iTBS; bilateral TBS (1–6) weeks, (10–30) sessions LDLPFC + RDLPFC; LDLPFC; RDLPFC HDRS; MADRS Table 1.1 (continued). Parameters of the TMS protocols applied for treating depressive disorders (Hett & Marwaha, 2020 ) BD; bipolar mania (1–20) Hz rTMS; Theta-burst (50Hz) (10–250) trains, (2s -30min) duration with a (2s-1min) interval, (150–1000) pulses RDLPFC; LDLPFC HAM-D; MADRS; BDI; QIDS (Tee & Au, 2020 ) BD; Bipolar mania (1–50) Hz rTMS; (10–20) sessions, (800–1980) pulses per session RDLPFC; LDLPFC HDRS; MADRS; HAM-D; YMRS; HAM-A; CGI (Gold et al., 2019 ) Mania; BD; Mixed (right-sided, bilateral deep, 20 Hz rTMS); iTBS (8–20) sessions RDLPFC HAM-D; YMRS; MADRS; CGI Note : BD: bipolar disorder; MDD: major depressive disorder; BD-1: bipolar disorder type 1; BD-2: bipolar disorder type 2; ECD: 99mTc-ethyl cysteinate dimer; fMRI: functional magnetic resonance imaging; PET: positron emission tomography; SPECT: single photon emission computed tomography; FDG-PET: fluorodeoxyglucose positron emission tomography; sgACC: the subgenual region of the anterior cingulate cortex; dmPFC: dorsomedial prefrontal cortex; SMN: sensorimotor network; SN: salience network; RSNs: resting state networks; rFPN: right frontoparietal network; iTBS: intermittent theta-burst stimulation; cTBS : continuous TBS; treatment refractory depression; rDLPFC: right dorsolateral prefrontal cortex; NR: not reported; MDE: Major depressive episode; dTMS: Deep TMS; HDRS: Hamilton Depression Rating Scale; MADRS: Montgomery-Asberg Depression Rating Scale; WAIS-III Wechsler Adult Intelligence Test-III; TMT: Trail Making Test; RAVLT: Rey Auditory Verbal Learning Test; MT: Motor Threshold; WCST: Wisconsin Cars Sorting Test; HAM-D: Hamilton Depression Rating Scale; BDI: the Beck Depression Inventory; QIDS: the Quick Inventory of Depressive Symptomology; YMRS: Young Mania Rating Scale; HAM-A: Hamilton Anxiety Rating Scale; CGI: Clinical Global Impressions Scale; ICD-10: International Classification of Diseases, 10th edition; DSM IV: Diagnostic and Statistical Manual of Mental Disorders 4th edition; TRD: Treatment-resistant depression 3.2.2. TES protocols TES is performed through direct current (DC), alternating current (AC), or random noise (RN) that is applied to a specific area of the cortex in order to alter neuronal excitability (Reed & Cohen Kadosh, 2018 ). D'Urso et al (D'Urso et al., 2023 ) evaluated the performance of tDCS protocols in treating BD as shown in Table 2 . The parameters of tDCS included anode position that was F3 or left DLPFC, cathode position that was F4, right DLPFC, F8, Fp2, or EC, electrode size in square centimeter was 25, or 35, current intensity was 2 mA, or 2.5 mA, session duration that fluctuated within the range of 20 to 30 min, number of sessions that ranged between 10 and 30 sessions, and frequency of sessions that was within the range of 2x/10 days to 1x/day. Donde et al (C. Dondé et al., 2017 ) also explored the parameters of tDCS protocol in treating BD; the parameters were anode-cathode positions on the scalp that were and cathode positions that were F3-Fp2, F3-F8, F3-F4, F3-EC, F3-Fp2, or Fp2-F3; size of electrode that fluctuated within the range of 25 to 35 cm 2 ; current intensity that ranged between 1 and 2 mA; session duration that was within the range of 5 to 30 min, number of sessions that fluctuated within the range of 10 to 30 sessions, sessions period that was within the range of 1 to 6 weeks, and frequency of sessions that was 1x/weekday or 2x/weekday; the percentage of improvement in depressive symptoms ranged from 21–96% according to Montgomery-Asberg Depression Rating Scale (MADRS) and Beck's Depression Inventory (BDI). The key challenge in the application of tDCS in treating depressive disorders is the lack of standardized tDCS protocols (See Table 2 and Table 2.1 ). Table 2 Characteristics of the included tDCS studies Source Review aim No of included studies Overall Confidence Rating According to AMSTAR-2 Country Conclusion Challenge (D'Urso et al., 2023 ) To examine the efficacy, safety, and putative neurobiological underpinnings of tDCS in bipolar depression 33 Moderate Nr tDCS might be a promising therapeutic modality for BD, even more than for unipolar depression More specific neurobiological studies and RCTs are required to definitively conclude whether tDCS has utility for the prevention of bipolar depression (Dondé, Neufeld, & Geoffroy, 2018 ) To review the risks and benefits of tDCS in BD across mood states 19 Moderate Australia, Italy, Taiwan Preliminary data suggests that tDCS holds promise as a treatment for BD, especially during depressive episodes More sufficiently powered randomized controlled trials are needed to clarify the effectiveness of tDCS (Clément Dondé et al., 2017 ) To evaluate efficacy and tolerability of tDCS in patients fulfilling DSM-IV-TR criteria for BD 7 Moderate Australia, Italy, Taiwan Depressive symptoms respond to tDCS in patients with BD More RCTs are needed to clarify the effectiveness of tDCS in BD, and which tDCS modalities are most efficient Note : BD: Bipolar depression; rTMS: Repetitive transcranial magnetic stimulation; DSM-IV-TR: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; tDCS: Transcranial direct current stimulation; RCTs: Randomized controlled trials. Table 2.1 Parameters of the tDCS protocols applied for treating depressive disorders Source Depressive disorder Mode of neurostimulation Duration of neurostimulation Site of stimulation (Anode – cathode on the scalp) Imaging modality or Depression rating scale (D'Urso et al., 2023 ) BD (2mA) tDCS (1–8) weeks, (10–30) sessions of (20–30) min F3-F4; F3-F8; F3-FP2; F3-EC; left DLPFC- right- DLPFC HDRS; MADRS; BDI (Dondé et al., 2018 ) BD; BD1; MDE; BDII/MDE; BDI/II tDCS (1–3) week, (2–15) daily sessions F3-F4; F3-F8; F3-EC; FP2-F3; F3-FP2 MADRS; HAMA; YMRS; BDI; MADRS/HDRS; WCST; NOSIE (Clément Dondé et al., 2017 ) BD; BDI/II; (2mA) tDCS (1–6) week, (10–30) sessions of (20–30) min F3-FP2; F3-F8; F3-F4; F3-EC; FP2-F3 MADRS; BDI Note : BD: Bipolar disorder; MDE: Major depressive episode; HAMA: Hamilton Anxiety Rating Scale; YMRS: Young Mania Rating Scale; BDI: Beck Depression Inventory; MADRS: Montgomery-Åsberg Depression Rating Scale; NOSIE: Nurses’ Observation Scale for Inpatient Evaluation; WCST, Wisconsin Card Sorting Test; HDRS: Hamilton Depression Rating Scale 3.2.3. NFT protocols NFT can result in altering brain activation without applying electrical potentials or magnetic fields, or pharmaceutical drugs (Saif, Hasan, Vuckovic, Fraser, & Qazi, 2021 ; Saif & Sushkova, 2023 ). Patil et al (Fernández-Alvarez et al., 2022 ; Hong & Park, 2022 ; Patil et al., 2023 ) explored the parameters of the NFT protocols applied in treating BD; the parameters included EEG frequency band targeted by NFT as follows: ↑Beta at F3 and ↑theta/↓alpha at Pz; ↓Alpha asymmetry at F3 and F4; ↑Frontal alpha asymmetry at F3, F4 referenced at Cz; ↓High beta at P3 and P4; ↓Theta, ↓alpha and ↑ beta at F3; ↑SMR/↑beta at T4 for SMR and F3/T3 for Beta; ↑Alpha and theta at Fz and Pz; ↑Peak alpha at Fp1 and Fp2. The remaining parameters were number of sessions that fluctuated within the range of 8 to 30 sessions, duration of sessions that ranged between 20 and 60 min, and period of NFT that fluctuated within the range of 2 to 10 weeks. NFT has resulted in significant improvements in depression symptoms; however, the key challenge in the application of NFT in treating depressive disorders is the lack of standardized NFT protocols as shown in Table 3 and Table 3.1 . Table 3 Characteristics of the included NFT studies Source Review aim No of included studies Overall Confidence Rating According to AMSTAR-2 Country Conclusion Challenge (Patil et al., 2023 ) To review the literature on EEG-NFT for people with depression 12 Moderate Turkey, Spain, Korea, Others EEG-NFT for the treatment of depression produces statistically significant clinical improvements More RCTs are needed to better understand the efficacy of EEG-NFT in treating depression (Fernández-Alvarez et al., 2022 ) To examine the effectiveness of NFT on depressive symptomatology 21 High Sweden, Taiwan, Austria, Others neurofeedback constitutes a promising technique for the reduction of depressive symptomatology in many diverse populations, including patients with MDD The complexity of neural patterns suggests the convenience of adopting statistical strategies that can foster the identification of individual patterns (Hong & Park, 2022 ) To evaluate the effects of fMRI-NFT and EEG-NFT with PTSD participants compared to sham-NFT and no intervention 7 Moderate Nr EEG-based neuro-feedback training was more helpful for training PTSD symptoms Further research is needed to establish a gold standard protocol for the EEG-NFT method for PTSD symptoms (Trambaiolli, Kohl, Linden, & Mehler, 2021 ) To review EEG-NFT, or fMRI-NFT protocols in depressive patients 24 Moderate US, Taiwan, Spain, Others Patients have shown significant clinical improvements as well as cognitive and neural changes following EEG-NFT and fMRI-based protocols The lack of study preregistration, the use of mostly small and/or unbalanced samples as well as the lack of control conditions, randomized treatment allocation or blinding render the evaluation of clinical effects difficult and require improvements in future studies Note : EEG-NFT: EEG-based neurofeedback; fMRI-NFT: Neurofeedback based on functional magnetic resonance imaging; RCTs: Randomized controlled trials; NFT: Neurofeedback; PTSD: Post-traumatic stress disorder; EEG: Electroencephalography. Table 3.1 Parameters of the NFT protocols applied for treating depressive disorders Source Depressive disorder Mode of neurofeedback Duration of NFT or number of sessions Location of electrodes on the scalp Imaging modality or Depression rating scale (Patil et al., 2023 ) MDD EEG-NF, ↑ Frontal alpha asymmetry; ↓ Alpha asymmetry; ↑ Beta, ↑ theta/ ↓ alpha, ↑ Mid-frontal alpha (5–10) weeks, (10–24) sessions of (30–45) min Alpha training: F3, F4 referenced at Cz; Alpha asymmetry training: F3- F4; Mid-frontal training: Fz; Beta training: F3; Alpha/theta training: Pz EEG; HAM-D; HAM-A; BDI-II; BAI (Fernández-Alvarez et al., 2022 ) MDD fMRI-NFT; TBR EEG-NFT; alpha-theta NFT (1–5) sessions Nr fMRI, EEG. HDRS; MADRS; BDI-I (Hong & Park, 2022 ) PTSD fMRI-NFT; EEG-NFT; fMRI with simultaneous EEG procedure (8–16) weeks, (3–25) sessions Pz channel; Mid and Frontal areas; Left amygdala fMRI, EEG. HDRS; MADRS; BDI-I; CAPS; IES-R (Trambaiolli et al., 2021 ) MDD EEG-NFT, ↑ or ↓ slow cortical potentials; ↑ beta and ↓ alpha and theta; ↑ alpha asymmetry; ↓ alpha and ↑ beta; ↓ beta; ↑ of amygdala during affective memory recall (1–24) sessions of 30–60 minutes ↑ or ↓ slow cortical potentials in Cz; ↑ beta and ↓ alpha and theta in Fp1 and F3; ↓ beta in AF3, AF4, T3 and T4; ↑ alpha asymmetry in F3 and F4; ↓ alpha and ↑ beta in Fp2; ↑ alpha asymmetry in F3 and F4; ↓ beta in P3 and P4 MMPI; HDRS; MADRS; BDI Note : EEG-NFT: EEG-based neurofeedback; fMRI-NFT: Neurofeedback based on functional magnetic resonance imaging; NFT: neurofeedback; EEG: Electroencephalography; Nr: not reported; PTSD: post-traumatic stress disorder; TBR: theta/beta ratio; CAPS: Clinician-Administered PTSD Scale; BDI: Beck Depression Inventory; IES-R: Impact of the Event Scale-revised; BAI: Beck Anxiety Inventory; ↑ = upregulation; ↓ = downregulation; MMPI: Minnesota Multiphasic Personality Inventory; MDD: Major depressive disorder 4. Discussion This review discusses the current advancements and challenges in the application of NINTs in the treatment of depressive disorders. The review primarily focuses on investigating the rationale behind the lack of consensus on the efficacy of NINTs in treating depressive disorders as some studies report positive effects of NINTs, while others show conflicting or inconclusive outcomes as is demonstrated in the results of this review. The results of this review indicate that the most common NINTs applied in treating depressive disorders are rTMS, iTBS, tDCS, and NFT, which is consistent with the literature on non-invasive neuromodulation for treating depressive symptoms (C.-W. Hsu et al., 2024 ); these techniques are relatively easy to apply for modulation of brain activity and are well-tolerated by depressed patients. Notably, these techniques offer cost-effective, scalable, and culturally acceptable treatment options, particularly in LMICs, where mental health resources are limited (Belay et al., 2023 ). They require minimal infrastructure and training, making them suitable for primary healthcare settings, and provide alternatives for treatment-resistant cases while reducing reliance on medications or specialized care (Kalpani Wijekoon Wijekoon Mudiyanselage et al., 2024 ). Their portability and lower recurring costs enhance accessibility in underserved areas, though initial investment and regulatory frameworks remain challenges (Alokaily, Almeteb, Althabiti, Alshahrani, & Applications, 2022). However, there are significant challenges in the use of NINTs in treating depressed people in terms of unstable therapeutic effects as shown in the results of this review, which complies with the existing literature (Dobbins, Bastos, Ratis, Silva, & Bonini, 2023 ). The cornerstone in the application of these techniques is the selection of a neuromodulation protocol (Garcia Pimenta, Brown, Arns, & Enriquez-Geppert, 2021 ). The review findings highlight the absence of standardized protocols for NINTs. Key parameters—such as pulse frequency in TMS, current intensity in tDCS, session duration and frequency, number of pulses per session, and cortical electrode placement—exhibit significant variability across studies. This methodological heterogeneity likely contributes to the inconsistent findings in the literature regarding the efficacy of NINTs (Piccoli et al., 2022 ). Furthermore, TMS and tDCS traditionally operate in an open-loop approach in delivery of stimuli without a responsive interaction between the nervous system, which is dynamic, and stimuli that may lead to degradation of the efficacy of the neuromodulation process or potentially produce side effects (Zanos, 2019 ). Additionally, limited penetration depth and uncertainty of the effect persistence of the NINTs are considered to be among the limitations of these neuromodulation techniques (Z.-J. Li, Zhang, Chen, & Hu, 2023 ). Addressing these challenges in NINTs, applied for treating depressive disorders, requires first of all to individualize and adapt the neurostimulation protocol to a specific state of the nervous system of each patient based on individual physiological state, inferred by biomarkers of depressive disorders. Applying a uniform neurostimulation protocol to all depressed patients—a common practice in neurostimulation-based therapy—may reduce treatment efficacy. This is because depression, whether unipolar or bipolar, is a clinically heterogeneous disorder with diverse symptomatic manifestations (Parker, Spoelma, & Tavella, 2022 ; van Loo et al., 2023 ). Nonetheless, continuous or open-loop neurostimulation is a common practice among clinicians that may constitute the reason behind the controversy over the efficacy of neurostimulation in treating depressive disorders (Sellers et al., 2023 ). Therefore, there is a desperate need for the application of individualized and responsive neurostimulation protocols in treating depressive disorders. Katherine W et al (Scangos et al., 2021 ) have applied personalized and closed-loop neurostimulation for treating depression and found that there was a rapid and sustained improvement in depressive symptoms. Furthermore, Garcia Pimenta et al (Garcia Pimenta et al., 2021 ) compared the efficacy of personalized non-invasive neuromodulation protocol, neurofeedback, in treating attention deficit hyperactivity disorder to that of non-personalized neurofeedback and found that the efficacy of personalized neurofeedback was superior to that of non-personalized. However, behavioral observations and self-report are still the main methods in the diagnosis of psychiatric disorders including depressive disorders (Farzan, 2024 ). The identification of reliable biomarkers for real-time monitoring of non-invasive neurostimulation effects in depressive disorders remains a critical challenge in developing personalized neuromodulation protocols (Price et al., 2020 ). Some studies have reported that latency and density of rapid eye movement could be used as biomarkers for monitoring depression (Arıkan et al., 2024 ). Klooster et al (Klooster et al., 2024 ) investigated the potential brain biomarkers that could be used for evaluating response to NINTs in depression, and concluded that individual alpha peak frequency and frontal-midline–elicited theta power, after task of activation of the rostral anterior cingulate cortex, are promising EEG biomarkers; however, there is still room for more research in order to examine the actionability of these EEG biomarkers (Klooster et al., 2024 ). Thus, there is a need for further research on biomarkers that can be applied reliably to monitor the response to non-invasive neurostimulation in depression in order to establish optimal neurostimulation protocols that may lead to a clear understanding of the mechanism of neurostimulation in depression. This review has a number of limitations to be acknowledged. First, the number of included studies is low; all non-English publications were excluded, which increases the concern about missing important relevant studies. Second, studies were stratified by non-invasive neuromodulation technique, yet substantial methodological variability—particularly in (1) participant selection criteria and baseline characteristics, (2) neurostimulation parameters (including device specifications and treatment protocols), (3) control conditions, and (4) outcome assessment measures with their corresponding analytical approaches—precluded quantitative synthesis. Finally, the authors of the included studies have not been contacted for seeking clarification on whether there is a misinterpretation of their studies in this review. 5. Conclusion Despite an increasing number of research projects and publications on NINTs applied for the treatment of depressive disorders in the last ten years, there is still no consensus on the efficacy of neuromodulation techniques as is demonstrated in this systematic review. The selection of the appropriate protocol is the main focus of the neurostimulation process as the neurostimulation effect on brain functioning depends mainly on the kind of protocol and its procedure for implementation. The selection of reliable biomarkers that can be used for real-time evaluation of the non-invasive neurostimulation process in treating depressive disorders is still a major impediment to the development of personalized non-invasive neuromodulation protocols. Based on the articles reviewed, the individual alpha peak frequency and frontal-midline–elicited theta power, after the task of activation of the rostral anterior cingulate cortex, are promising EEG biomarkers that could be used for evaluating response to NINTs in depression; however, there is still a need for more research in order to examine the actionability of these EEG biomarkers. Declarations Ethical approval This systematic review adheres to the highest ethical standards in research. Since this study involves the synthesis and analysis of existing published literature and does not involve direct interaction with human or animal subjects, formal ethical approval from an institutional review board (IRB) or ethics committee is not typically required. Compliance with research integrity guidelines The review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure transparency and reproducibility. 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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-7278463","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":494689086,"identity":"459babe5-0c1a-4aa7-9da0-e44d4b0a8c19","order_by":0,"name":"Mohammed Gamil Mohammed Saif","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABE0lEQVRIiWNgGAWjYFACxoYPDAwHwEyJj3/+yYEYBx7g19I4A6ZFcmbDAWOwlgQC1sC1SPM2HEhsALHwaZFvP9zYdKPijrzutMMHb/PuuJM+P+zwQ6AtdnK6Ddi1GJxJbGzOOfPMcNvttGTLuWee5W68nWYA1JJsbHYAhxaGxPbHuW2HGbfdzjGTeMPGnLtxdgJIy4HEbTi0yPc/bGwGarHfdjv/mwQPG3O64ez0D3i1MNxIBGtJBNrCJsnbdjhBXjoHvy0GNx6C/HI4GegXY8sZZ9IMN0jnFBxIMMDtF/n+9IfNORWHbbfdTn5440OFjbz87PTNHz5U2Mnh0oLF3gOQYCEByDeQonoUjIJRMApGAgAAQVh0Swjih/EAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-5978-9961","institution":"Vladimir State University named after Alexander and Nikolay Stoletovs, Department of electronics, instrumentation and biotechnical systems; Vladimir, Russia","correspondingAuthor":true,"prefix":"","firstName":"Mohammed","middleName":"Gamil Mohammed","lastName":"Saif","suffix":""}],"badges":[],"createdAt":"2025-08-02 13:09:37","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7278463/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7278463/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88348907,"identity":"0e66d590-0dda-4c70-b8b5-d69e2958c149","added_by":"auto","created_at":"2025-08-05 14:02:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":49316,"visible":true,"origin":"","legend":"\u003cp\u003ePreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram of study selection.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7278463/v1/fc64dc319ddb8b6aa46e0745.png"},{"id":88351954,"identity":"1241b4d6-87a0-4fa4-84e8-39b7c0ef9b2d","added_by":"auto","created_at":"2025-08-05 14:26:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1377299,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7278463/v1/991b7a7c-9c6d-4387-9c09-e44bc70bc5c5.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eAdvancements and challenges in the application of noninvasive neuromodulation techniques in treatment of depression: A systematic review\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eDepression is a prevalent psychiatric disorder that negatively affects the quality of life of millions of people worldwide and can lead to suicide in severe cases (J. Liu, Liu, Ma, Tong, \u0026amp; Zheng, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Although a definitive and universally accepted classification system for depression remains elusive, the American Psychiatric Association categorizes depressive disorders into several subtypes, including major depressive disorder (MDD), dysthymia (Gao et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Zhang, Ren, \u0026amp; Zhang, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While there are many options currently available for the treatment of depressive disorders, it is estimated that 70% of depressed people in general and 10 to 30% of MDD patients remain untreated (Cheng et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; G. Liu et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Non-invasive neuromodulation techniques (NINTs) represent an expanding frontier in the management of neurological and neuropsychiatric conditions, such as depressive disorders (De Koninck, Brazeau, Guay, Herrero Babiloni, \u0026amp; De Beaumont, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). These methods employ physical interventions to modulate, suppress, enhance, or otherwise regulate neural activity without requiring surgical implantation (Hernandez-Pavon et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Drug therapy can achieve the same therapeutic outcomes in some cases, while physical neuromodulation offers the advantage of avoiding the systematic side effects of pharmacotherapies (Bledsoe, Viser, \u0026amp; San Luciano, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The most common NINTs include repetitive transcranial magnetic stimulation (rTMS) (Lanza et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), transcranial alternating current stimulation (tACS) (D. Li et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), transcranial direct current stimulation (tDCS) (Murphy et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and neurofeedback based on real-time measurements of electroencephalography (EEG) (Saif, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). rTMS operates through high-intensity magnetic pulses applied over the scalp that induce electrical currents in the targeted cortex (Slan et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). It is thought that the application of low frequency rTMS, equal to or less than 1 Hz, produces an inhibitory effect on the cerebral cortex, whereas high frequency rTMS, greater than 1 Hz, results in a stimulating effect (Zaidi et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). TMS was approved by the Food and Drug Administration (FDA) in the United States in 2008 for treatment of major depressive disorder through applying rTMS over the cortex thought to have decreased neuronal activity (S. Han et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While tACS involves applying low-intensity sinusoidal currents to the scalp (Shao et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), tDCS consists of the application of a weak direct current, typically 1\u0026ndash;2 mA, to modulate cortical activity (Chen et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Neurofeedback training is an emerging neuromodulation modality based on the recording of EEG and simultaneously providing real-time visual or auditory feedback (Saif \u0026amp; Sushkova, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). NINTs provide cost-effective, scalable, and culturally acceptable treatments for depression, particularly in lower- and middle-income countries (LMICs) where mental health resources are limited (Belay, Engel, Lee, Le, \u0026amp; Mihalopoulos, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) (K. W. W. Mudiyanselage et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); these techniques require minimal infrastructure and training, making them suitable for primary healthcare settings (Mutyambizi-Mafunda et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Their portability and lower recurring costs enhance accessibility in underserved areas (Vlaicu \u0026amp; and Bustuchina Vlaicu, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, initial investment and regulatory frameworks remain challenges (Xie \u0026amp; Zhang, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Given these advantages, NINTs hold promise for bridging the mental health treatment gap in LMICs (Klooster, Voetterl, Baeken, \u0026amp; Arns, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eOwing to the ability of NINTs to modify cortical activity with little or no side effects, there is a growing research interest among neuroscientists in the application of NINTs for treatment of depressive disorders (Cindik-Herbr\u0026uuml;ggen \u0026amp; Duymaz, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; W.-Y. Hsu, Zanto, Park, Gazzaley, \u0026amp; Bove, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Vigod et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Yuan et al investigated and compared the efficacy of 10Hz-rTMS and intermittent theta burst stimulation (iTBS) in treatment of post-traumatic stress disorder (PTSD) and found that both 10Hz-rTMS and iTBS resulted in significant improvements in the symptoms of PTSD, with no significant difference in the efficacy of 10Hz-rTMS from that of iTBS (Yuan et al., \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Han et al showed that 10 sessions of a 2 mA tDCS stimulation applied for treatment of patients with post-traumatic stress disorder, with the anode positioned over the F3 area and the cathode over the F4, resulted in a significant reduction in the severity and frequency of post-traumatic stress disorder in approximately 60% of the participating patients (J. Han et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). EEG based brain-computer interface, as a communication system between the brain and a computer, is used to automate the process of neuromodulation through monitoring the brain\u0026rsquo;s response to neuromodulation procedures and adjusting the stimulation parameters in real time, and thereby increasing the effect of neuromodulation (Alam, Rodrigues, Pham, \u0026amp; Thakor, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Merk et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Nevertheless, the use of NINTs for treating depression is not without controversy. While some studies (Miuli et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Shamabadi et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) have reported significant effects of NINTs in the treatment of depressive disorders, other studies (Cai et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Konstantinou et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) showed no significant effects of the same NINTs applied to the same depressive disorder. It is still challenging for the neuroscience community to determine more acceptable and efficacious NINTs protocols for the treatment of depressive disorders as there are no sufficient studies that directly compare the efficacy of different NINTs protocols (C.-W. Hsu et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, this review synthesized research that focused on the application of NINTs for the treatment of depressive disorders. The aim of this review was to provide a direct comparison of the efficacy of NINTs and to ascertain whether there is a possibility that different protocols of neuromodulation within each neuromodulation technique may exhibit different levels of clinical efficacy in the treatment of depressive disorders.\u003c/p\u003e"},{"header":"2. Material and Methods","content":"\u003cp\u003eThe Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) (Page et al., 2021) was used in this review as shown in Fig.\u0026nbsp;1.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Search strategy\u003c/h2\u003e\u003cp\u003eThe Scopus and PubMed databases were searched for articles published between 2016 and 2024\u003c/p\u003e\u003cp\u003eusing the following search terms: (\"Transcranial Direct Current Stimulation\"[Mesh] OR \"noninvasive neuromodulation method*\"[tw] OR tDCS [tw] OR tACS [tw] OR rTMS[tw] OR neurofeedback[tw] OR \"ultrasonic stimulation\"[tw] OR TUS[tw] OR \"near-infrared laser stimulation\"[tw] OR \"magnetic stimulation\"[tw] OR \"direct current stimulation\"[tw] OR \"alternating current stimulation\"[tw] OR iTBS[tw] OR \"theta burst stimulation\"[tw]) AND (\"Bipolar Disorder\"[Mesh] OR \"bipolar depression\" [tw] OR \"manic depression\" [tw]) in PubMed.\u003c/p\u003e\u003cp\u003e(\"Transcranial Direct Current Stimulation\" OR \"noninvasive neuromodulation method*\" OR tDCS OR tACS OR rTMS OR neurofeedback OR \"ultrasonic stimulation\" OR TUS OR \"near-infrared laser stimulation\" OR \"magnetic stimulation\" OR \"direct current stimulation\" OR \"alternating current stimulation\" OR iTBS OR \"theta burst stimulation\" AND (\"bipolar disorder\" OR \"bipolar depression\" OR \"manic depression\")) in Scopus.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Eligibility criteria\u003c/h2\u003e\u003cp\u003eEligibility criteria were set according to the patient or population/problem, intervention, comparison and outcomes (PICO) format as follows: Population - patients with depressive disorders; Intervention \u0026ndash; non-invasive neuromodulation techniques; Comparison - controlled conditions; Outcome - Clinical improvement of depression symptoms. Systematic reviews of brain stimulation studies were included if they were published between 2016 and Jan. 2024 in a peer-reviewed journal. The publication language was limited to English.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. Identification and data collection process\u003c/h2\u003e\u003cp\u003eThe search for relevant publications was performed on two electronic databases as mentioned above and any duplication of publications was removed. Following the screening of the titles and abstracts of the articles, all articles that were not in the scope of the review, despite mentioning the search terms, were excluded. The full texts of publications that met the inclusion criteria outlined above were then downloaded, and carefully reviewed to ensure their relevance. If the full-text of an article was not retrievable, those articles were excluded as well. This process is illustrated in a PRISMA flow diagram in Fig.\u0026nbsp;1. The data extracted from the included systematic reviews was as follows: Review aim; number of included studies; report of risk of bias; characteristics of neuromodulation protocols; conclusion; challenge or recommendation for future research.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e\u003cb\u003e2.4. Assessment of study quality\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe methodological quality of the included systematic reviews was independently evaluated by two reviewers (Al-harosh Mugeb and Lyudmila Sushkova) using A MeaSurement Tool to Assess Systematic Reviews 2 (AMSTAR-2). Reviews were categorized based on their overall confidence rating: \"High\" (no critical flaws across all seven critical domains and \u0026le;\u0026thinsp;1 non-critical weakness), \"Moderate\" (one critical flaw, excluding domains 2, 4, or 7, with minor non-critical weaknesses), \"Low\" (multiple critical flaws or a major flaw in domains 2, 4, or 7), or \"Critically Low\" (multiple critical flaws rendering the review unreliable). Only systematic reviews achieving \"High,\" \"Moderate,\" or \"Low\" confidence ratings were included in the final analysis; those rated as \"Critically Low\" were excluded (See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Included articles\u003c/h2\u003e\u003cp\u003eLiterature search using the above-mentioned search terms resulted in a total of 232 references; 56 publications found in PubMed database and 176 in Scopus. Following the removing of duplicates, 229 publications remained, of which only 17 publications met the eligibility criteria and were included. A total of 306 primary studies were analyzed across the systematic reviews.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Characteristics of the included studies\u003c/h2\u003e\u003cp\u003eThe 17 included studies were classified into three groups based on the brain stimulation technique applied for treating patients with depressive disorders. The included studies show that TMS, TES, and neurofeedback training (NFT) are the most common techniques applied for non-invasive brain stimulation of patients with depressive disorders.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e3.2.1. TMS protocols\u003c/h2\u003e\u003cp\u003eTMS, in general, operates through high-intensity magnetic pulses applied over the scalp that induce electrical currents in the targeted cortex. Shamabadi et al (Shamabadi et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) explored the performance of different TMS protocols in treatment of bipolar depression; the TMS protocols were rTMS and intermittent theta burst stimulation (iBTS) with multiple parameters, such as frequency which varied between 1 and 20 Hz, number of sessions that fluctuated in the 10\u0026ndash;100 range and duration of the intervention that was within the range of 10 days to 4 weeks. As a result of the application of TMS in treating patients with BD, there were significant effects on functional connectivity, and metabolic changes in cortical and subcortical brain areas. Cai et al (Cai et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) examined the efficacy of the continuous TBS (cTBS) protocol in treating depressive disorders. The explored parameters of the cTBS protocol were duration of treatment that fluctuated within the range of 1 to 14 weeks, number of sessions that varied between 10 and 15 sessions, number of pulses per session that was within the range of 600 to 3600 pulses, frequency that was 50 Hz, and the site of neurostimulation over the cortex that was right dorsolateral prefrontal cortex (rDLPFC); however, results showed that cTBS was ineffective in treatment of depressive disorder. Konstantinou et al (Konstantinou et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) investigated the evidence on the use of TMS protocols in different stages of BD, such as manic and mixed episodes and have concluded that there is still a lack of information on whether the effect of TMS extends to manic or mixed episodes (See Table\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Chu et al (Chu et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) compared the efficacy of the standard rTMS and TBS protocols in treating depressive disorders and found that TBS treatment was more efficient in terms of time and energy than the standard rTMS as it is shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The risk of developing a hypomanic/manic switch (HMS) during the application of TMS protocols in treating mood disorders was investigated by Miuli et al (Miuli et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who found that TMS seems not to be related to HMS development. The key challenges in the application of TMS in treating depressive disorders, as it was reported in the included studies, were the lack of standardized TMS protocols, and the lack of conclusive neuroimaging and clinical biomarkers that can be used for prediction and optimization of response to TMS as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1.1\u003c/span\u003e.\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\u003eCharacteristics of the included TMS studies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReview aim\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo of included studies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall Confidence Rating According to AMSTAR-2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eChallenge\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Shamabadi et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo collect all available evidence on neuroimaging findings, indicating functional, structural, and metabolic brain changes associated with rTMS in individuals with BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUSA, New Zealand, Canada, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003erTMS has significant effects on brain activation, functional connectivity and brain metabolism of cortical and subcortical brain areas in BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThere are still no conclusive neuroimaging and clinical biomarkers that can be used for prediction and optimization of response to rTMS in BD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Cai et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo examine the clinical efficacy and acceptability of cTBS for MDD or BD patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTaiwan, India, Israel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ecTBS was not more efficacious than sham cTBS for MDD or BD patients with major depressive episode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFuture large-scale studies are warranted to assess the efficacy of cTBS for MDD or BD patients with a major depressive episode\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Konstantinou et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo review the evidence on the use of rTMS across the different stages of BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eThere is no consensus on the most effective rTMS protocol, and more adequately powered sham-controlled studies are required to verify the efficacy of rTMS in BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThe current data regarding the application of rTMS in BD patients remain limited\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Miuli et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo examine the risk of developing HMS during active TMS treatment of mood disorders\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCanada, Japan, Taiwan, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTMS seems not to be related to HMS development\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Nguyen, Hieronymus, Lorentzen, McGirr, \u0026amp; \u0026Oslash;stergaard, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo provide an estimate of the efficacy of rTMS in bipolar depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUSA, Switzerland,\u003c/p\u003e\u003cp\u003eAustralia, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003erTMS seems effective in the treatment of bipolar depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThe lack of sufficiently powered confirmatory RCTs\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003e(continued).\u003c/b\u003e Characteristics of the included TMS studies\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Sciortino et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo summarize the results of RCTs using rTMS for improving cognitive symptoms in SCZ and BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChina, Germany, UK, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIn BD, rTMS seemed to improve cognitive domains in euthymic patients, while its effect during acute phases, especially depression, appeared limited\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eStandardized protocols of rTMS are still lacking\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Chu et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo examine the studies on efficacy and tolerability of TBS in patients with MD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTaiwan, Germany, Belgium, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTBS treatment was more efficient in terms of time and energy than the standard rTMS was\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hett \u0026amp; Marwaha, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo review the extant literature on the use of rTMS to treat BD across different mood states\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBelgium, USA, Italy, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003erTMS appears to be efficacious in treating BD and mania. However, when compared with sham treatments, most RCTs reported no significant differences in symptom\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThere is a lack of any adequately powered trial and the ideal rTMS treatment parameters to help better determine the efficacy of rTMS in the treatment of BD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Tee \u0026amp; Au, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo summarize the available data from RCTs on the treatment efficacy of rTMS for bipolar depression and mania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChina, Brazil, India, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003erTMS appears safe and effective in treating bipolar depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMore Stringent RCTs in this area will still be needed before the treatment can be recommended in BD\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Gold et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo evaluate the existing literature on TMS as a treatment for BD across varied mood states\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUSA, Iran, France, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eTranscranial magnetic stimulation is a promising approach for treating patients with BD who have failed to respond to pharmacological or psychosocial treatment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFuture research should more clearly elucidate which TMS protocols may be most effective for a given bipolar patient\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: BD: bipolar depression; rTMS: repetitive transcranial magnetic stimulation; TBS: theta burst stimulation; Nr: not reported; HMS: hypomanic/ manic switch; cTBS: Continuous TBS; MDD: Major depressive disorder; RCTs: randomized controlled trials; SCZ: Schizophrenia.\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=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1.1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameters of the TMS protocols applied for treating depressive disorders\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepressive disorder\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMode of neurostimulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDuration of neurostimulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSite of stimulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eImaging modality or\u003c/p\u003e\u003cp\u003eDepression rating scale\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Shamabadi et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD; BD; BD-1; BD-2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1\u0026ndash;20) Hz rTMS; iTBS-\u003c/p\u003e\u003cp\u003e600 pulses each session, delivered as triplets of 50 Hz repeated at 5 Hz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(2\u0026ndash;4) weeks, 5 times a week\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003edmPFC; sgACC; mPFC; SMN; SN; RSNs; rFPN;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePET; fMRI; ECD SPECT; PET\u0026thinsp;+\u0026thinsp;MRI; FDG-PET/H\u003csup\u003e15\u003c/sup\u003e\u003csub\u003e2\u003c/sub\u003eO; MRI + [18F]-FDG-PET; MRI (T1)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Cai et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD; BD; TRD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecTBS: (600\u0026ndash;3600) pulses per session\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;2) weeks\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003erDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDSM-IV; ICD-10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Konstantinou et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD; Mania; mixed episode\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1\u0026ndash;50) Hz rTMS; 50 Hz iTBS; cTBS1200; cTBS1800; cTBS3600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(10\u0026ndash;30) sessions of (10\u0026ndash;60) seconds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRight DLPFC; Left DLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Miuli et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLate-life\u003c/p\u003e\u003cp\u003eTRD;\u003c/p\u003e\u003cp\u003eMDE; BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1980 impulse/session of 18 Hz dTMS; (1\u0026ndash;18) Hz rTMS with (300-12000) impulse/session; (1\u0026ndash;10) Hz Bilateral rTMS; 990 impulse/session of 50 Hz iTBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(5\u0026ndash;30) sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLDLPFC;\u003c/p\u003e\u003cp\u003eRDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Nguyen et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1\u0026ndash;10) Hz Bilateral rTMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(10\u0026ndash;30) sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLDLPFC; RDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHRDS, MADRS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Sciortino et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD-I;\u003c/p\u003e\u003cp\u003eBD-II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eLDLPFC 10Hz rTMS and RDLPFC 1Hz rTMS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 trains of 4 s at 10 Hz and 80% MT followed by\u003c/p\u003e\u003cp\u003e12 s off (1200 pulses) at LDLPFC; 120 trains of 10 s at 1Hz and 80% MT followed by 2 s off (1200 pulses) at RDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLDLPFC;\u003c/p\u003e\u003cp\u003eRDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWAIS-III; RAVLT; Chinese versions of WCST, Stroop Test, and TMT\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Chu et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ecTBS; iTBS; bilateral TBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;6) weeks, (10\u0026ndash;30) sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLDLPFC\u0026thinsp;+\u0026thinsp;RDLPFC; LDLPFC; RDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHDRS; MADRS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1.1\u003c/span\u003e \u003cb\u003e(continued).\u003c/b\u003e Parameters of the TMS protocols applied for treating depressive disorders\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hett \u0026amp; Marwaha, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD; bipolar mania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1\u0026ndash;20) Hz rTMS; Theta-burst (50Hz)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(10\u0026ndash;250) trains, (2s -30min) duration with a (2s-1min) interval, (150\u0026ndash;1000) pulses\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRDLPFC; LDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHAM-D; MADRS; BDI; QIDS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Tee \u0026amp; Au, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD; Bipolar mania\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(1\u0026ndash;50) Hz rTMS;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(10\u0026ndash;20) sessions, (800\u0026ndash;1980) pulses per session\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRDLPFC; LDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHDRS; MADRS; HAM-D; YMRS; HAM-A; CGI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Gold et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMania; BD; Mixed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(right-sided, bilateral deep, 20 Hz rTMS); iTBS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(8\u0026ndash;20) sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRDLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHAM-D; YMRS; MADRS; CGI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: BD: bipolar disorder; MDD: major depressive disorder; BD-1: bipolar disorder type 1; BD-2: bipolar disorder type 2; ECD: 99mTc-ethyl cysteinate dimer; fMRI: functional magnetic resonance imaging; PET: positron emission tomography; SPECT: single photon emission computed tomography; FDG-PET: fluorodeoxyglucose positron emission tomography; sgACC: the subgenual region of the anterior cingulate cortex; dmPFC: dorsomedial prefrontal cortex; SMN: sensorimotor network; SN: salience network; RSNs: resting state networks; rFPN: right frontoparietal network; iTBS: intermittent theta-burst stimulation; cTBS : continuous TBS; treatment refractory depression; rDLPFC: right dorsolateral prefrontal cortex; NR: not reported; MDE: Major depressive episode; dTMS: Deep TMS; HDRS: Hamilton Depression Rating Scale; MADRS: Montgomery-Asberg Depression Rating Scale; WAIS-III Wechsler Adult Intelligence Test-III; TMT: Trail Making Test; RAVLT: Rey Auditory Verbal Learning Test; MT: Motor Threshold; WCST: Wisconsin Cars Sorting Test; HAM-D: Hamilton Depression Rating Scale; BDI: the Beck Depression Inventory; QIDS: the Quick Inventory of Depressive Symptomology; YMRS: Young Mania Rating Scale; HAM-A: Hamilton Anxiety Rating Scale; CGI: Clinical Global Impressions Scale; ICD-10: International Classification of Diseases, 10th edition; DSM IV: Diagnostic and Statistical Manual of Mental Disorders 4th edition; TRD: Treatment-resistant depression\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=\"Section3\"\u003e\u003ch2\u003e3.2.2. TES protocols\u003c/h2\u003e\u003cp\u003eTES is performed through direct current (DC), alternating current (AC), or random noise (RN) that is applied to a specific area of the cortex in order to alter neuronal excitability (Reed \u0026amp; Cohen Kadosh, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). D'Urso et al (D'Urso et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) evaluated the performance of tDCS protocols in treating BD as shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The parameters of tDCS included anode position that was F3 or left DLPFC, cathode position that was F4, right DLPFC, F8, Fp2, or EC, electrode size in square centimeter was 25, or 35, current intensity was 2 mA, or 2.5 mA, session duration that fluctuated within the range of 20 to 30 min, number of sessions that ranged between 10 and 30 sessions, and frequency of sessions that was within the range of 2x/10 days to 1x/day. Donde et al (C. Dond\u0026eacute; et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) also explored the parameters of tDCS protocol in treating BD; the parameters were anode-cathode positions on the scalp that were and cathode positions that were F3-Fp2, F3-F8, F3-F4, F3-EC, F3-Fp2, or Fp2-F3; size of electrode that fluctuated within the range of 25 to 35 cm\u003csup\u003e2\u003c/sup\u003e; current intensity that ranged between 1 and 2 mA; session duration that was within the range of 5 to 30 min, number of sessions that fluctuated within the range of 10 to 30 sessions, sessions period that was within the range of 1 to 6 weeks, and frequency of sessions that was 1x/weekday or 2x/weekday; the percentage of improvement in depressive symptoms ranged from 21\u0026ndash;96% according to Montgomery-Asberg Depression Rating Scale (MADRS) and Beck's Depression Inventory (BDI). The key challenge in the application of tDCS in treating depressive disorders is the lack of standardized tDCS protocols (See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e2.1\u003c/span\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 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of the included tDCS studies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReview aim\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo of included studies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall Confidence Rating According to AMSTAR-2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eChallenge\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(D'Urso et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo examine the efficacy, safety, and putative neurobiological underpinnings of tDCS in bipolar depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etDCS might be a promising therapeutic modality for BD, even more than for unipolar depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMore specific neurobiological studies and RCTs are required to definitively conclude whether tDCS has utility for the prevention of bipolar depression\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Dond\u0026eacute;, Neufeld, \u0026amp; Geoffroy, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo review the risks and benefits of tDCS in BD across mood states\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAustralia, Italy, Taiwan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePreliminary data suggests that tDCS holds promise as a treatment for BD, especially during depressive episodes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMore sufficiently powered randomized controlled trials are needed to clarify the effectiveness of tDCS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Cl\u0026eacute;ment Dond\u0026eacute; et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo evaluate efficacy and tolerability of tDCS in patients fulfilling DSM-IV-TR criteria for BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAustralia, Italy, Taiwan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDepressive symptoms respond to tDCS in patients with BD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMore RCTs are needed to clarify the effectiveness of tDCS in BD, and which tDCS modalities are most efficient\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: BD: Bipolar depression; rTMS: Repetitive transcranial magnetic stimulation; DSM-IV-TR: Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision; tDCS: Transcranial direct current stimulation; RCTs: Randomized controlled trials.\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=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2.1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameters of the tDCS protocols applied for treating depressive disorders\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepressive disorder\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMode of neurostimulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDuration of neurostimulation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSite of stimulation\u003c/p\u003e\u003cp\u003e(Anode \u0026ndash; cathode on the scalp)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eImaging modality or\u003c/p\u003e\u003cp\u003eDepression rating scale\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(D'Urso et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2mA) tDCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;8) weeks, (10\u0026ndash;30) sessions of (20\u0026ndash;30) min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF3-F4; F3-F8; F3-FP2; F3-EC; left DLPFC- right- DLPFC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHDRS; MADRS; BDI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Dond\u0026eacute; et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD; BD1; MDE; BDII/MDE; BDI/II\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003etDCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;3) week, (2\u0026ndash;15) daily sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF3-F4; F3-F8; F3-EC; FP2-F3; F3-FP2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMADRS; HAMA; YMRS; BDI; MADRS/HDRS; WCST; NOSIE\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Cl\u0026eacute;ment Dond\u0026eacute; et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBD; BDI/II;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(2mA) tDCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;6) week, (10\u0026ndash;30) sessions of (20\u0026ndash;30) min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eF3-FP2; F3-F8; F3-F4; F3-EC; FP2-F3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMADRS; BDI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: BD: Bipolar disorder; MDE: Major depressive episode; HAMA: Hamilton Anxiety Rating Scale; YMRS: Young Mania Rating Scale; BDI: Beck Depression Inventory; MADRS: Montgomery-\u0026Aring;sberg Depression Rating Scale; NOSIE: Nurses\u0026rsquo; Observation Scale for Inpatient Evaluation; WCST, Wisconsin Card Sorting Test; HDRS: Hamilton Depression Rating Scale\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=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003e3.2.3. NFT protocols\u003c/h2\u003e\u003cp\u003eNFT can result in altering brain activation without applying electrical potentials or magnetic fields, or pharmaceutical drugs (Saif, Hasan, Vuckovic, Fraser, \u0026amp; Qazi, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Saif \u0026amp; Sushkova, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Patil et al (Fern\u0026aacute;ndez-Alvarez et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Hong \u0026amp; Park, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Patil et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) explored the parameters of the NFT protocols applied in treating BD; the parameters included EEG frequency band targeted by NFT as follows: \u0026uarr;Beta at F3 and \u0026uarr;theta/\u0026darr;alpha at Pz; \u0026darr;Alpha asymmetry at F3 and F4; \u0026uarr;Frontal alpha asymmetry at F3, F4 referenced at Cz; \u0026darr;High beta at P3 and P4; \u0026darr;Theta, \u0026darr;alpha and \u0026uarr; beta at F3; \u0026uarr;SMR/\u0026uarr;beta at T4 for SMR and F3/T3 for Beta; \u0026uarr;Alpha and theta at Fz and Pz; \u0026uarr;Peak alpha at Fp1 and Fp2. The remaining parameters were number of sessions that fluctuated within the range of 8 to 30 sessions, duration of sessions that ranged between 20 and 60 min, and period of NFT that fluctuated within the range of 2 to 10 weeks. NFT has resulted in significant improvements in depression symptoms; however, the key challenge in the application of NFT in treating depressive disorders is the lack of standardized NFT protocols as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e3.1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCharacteristics of the included NFT studies\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\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\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReview aim\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo of included studies\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOverall Confidence Rating According to AMSTAR-2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eCountry\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eChallenge\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Patil et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo review the literature on EEG-NFT for people with depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTurkey, Spain, Korea, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEEG-NFT for the treatment of depression produces statistically significant clinical improvements\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMore RCTs are needed to better understand the efficacy of EEG-NFT in treating depression\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Fern\u0026aacute;ndez-Alvarez et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo examine the effectiveness of NFT on depressive symptomatology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSweden, Taiwan, Austria, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eneurofeedback constitutes a promising technique for the reduction of depressive symptomatology in many diverse populations, including patients with MDD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThe complexity of neural patterns suggests the convenience of adopting statistical strategies that can foster the identification of individual patterns\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hong \u0026amp; Park, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo evaluate the effects of fMRI-NFT and EEG-NFT with PTSD participants compared to sham-NFT and no intervention\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEEG-based neuro-feedback training was more helpful for training PTSD symptoms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eFurther research is needed to establish a gold standard protocol for the EEG-NFT method for PTSD symptoms\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Trambaiolli, Kohl, Linden, \u0026amp; Mehler, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTo review EEG-NFT, or fMRI-NFT protocols in depressive patients\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eUS, Taiwan, Spain, Others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePatients have shown significant clinical improvements as well as cognitive and neural changes following EEG-NFT and fMRI-based protocols\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eThe lack of study preregistration, the use of mostly small and/or unbalanced samples as well as the lack of control conditions, randomized treatment allocation or blinding render the evaluation of clinical effects difficult and require improvements in future studies\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: EEG-NFT: EEG-based neurofeedback; fMRI-NFT: Neurofeedback based on functional magnetic resonance imaging; RCTs: Randomized controlled trials; NFT: Neurofeedback; PTSD: Post-traumatic stress disorder; EEG: Electroencephalography.\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=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3.1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eParameters of the NFT protocols applied for treating depressive disorders\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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\u003cdiv align=\"left\" 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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSource\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDepressive disorder\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMode of neurofeedback\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDuration of NFT or number of sessions\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLocation of electrodes on the scalp\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eImaging modality or\u003c/p\u003e\u003cp\u003eDepression rating scale\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Patil et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEEG-NF, \u0026uarr; Frontal alpha asymmetry; \u0026darr; Alpha asymmetry; \u0026uarr; Beta, \u0026uarr; theta/ \u0026darr; alpha, \u0026uarr; Mid-frontal alpha\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(5\u0026ndash;10) weeks, (10\u0026ndash;24) sessions of (30\u0026ndash;45) min\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eAlpha training: F3, F4 referenced at Cz; Alpha asymmetry training: F3- F4; Mid-frontal training: Fz; Beta training: F3; Alpha/theta training: Pz\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEEG;\u003c/p\u003e\u003cp\u003eHAM-D; HAM-A; BDI-II; BAI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Fern\u0026aacute;ndez-Alvarez et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003efMRI-NFT; TBR EEG-NFT; alpha-theta NFT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;5) sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNr\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003efMRI, EEG.\u003c/p\u003e\u003cp\u003eHDRS; MADRS; BDI-I\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Hong \u0026amp; Park, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePTSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003efMRI-NFT; EEG-NFT; fMRI with simultaneous EEG procedure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(8\u0026ndash;16) weeks, (3\u0026ndash;25) sessions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003ePz channel; Mid and Frontal areas; Left amygdala\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003efMRI, EEG.\u003c/p\u003e\u003cp\u003eHDRS; MADRS; BDI-I; CAPS; IES-R\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e(Trambaiolli et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMDD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEEG-NFT, \u0026uarr; or \u0026darr; slow cortical potentials; \u0026uarr; beta and \u0026darr; alpha and theta; \u0026uarr; alpha asymmetry; \u0026darr; alpha and \u0026uarr; beta; \u0026darr; beta; \u0026uarr; of amygdala during affective memory recall\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(1\u0026ndash;24) sessions of 30\u0026ndash;60 minutes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026uarr; or \u0026darr; slow cortical potentials in Cz; \u0026uarr; beta and \u0026darr; alpha and theta in Fp1 and F3; \u0026darr; beta in AF3, AF4, T3 and T4; \u0026uarr; alpha asymmetry in F3 and F4; \u0026darr; alpha and \u0026uarr; beta in Fp2; \u0026uarr; alpha asymmetry in F3 and F4; \u0026darr; beta in P3 and P4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMMPI; HDRS; MADRS; BDI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNote\u003c/b\u003e: EEG-NFT: EEG-based neurofeedback; fMRI-NFT: Neurofeedback based on functional magnetic resonance imaging; NFT: neurofeedback; EEG: Electroencephalography; Nr: not reported; PTSD: post-traumatic stress disorder; TBR: theta/beta ratio; CAPS: Clinician-Administered PTSD Scale; BDI: Beck Depression Inventory; IES-R: Impact of the Event Scale-revised; BAI: Beck Anxiety Inventory; \u0026uarr; = upregulation; \u0026darr; = downregulation; MMPI: Minnesota Multiphasic Personality Inventory; MDD: Major depressive disorder\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\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis review discusses the current advancements and challenges in the application of NINTs in the treatment of depressive disorders. The review primarily focuses on investigating the rationale behind the lack of consensus on the efficacy of NINTs in treating depressive disorders as some studies report positive effects of NINTs, while others show conflicting or inconclusive outcomes as is demonstrated in the results of this review.\u003c/p\u003e\u003cp\u003eThe results of this review indicate that the most common NINTs applied in treating depressive disorders are rTMS, iTBS, tDCS, and NFT, which is consistent with the literature on non-invasive neuromodulation for treating depressive symptoms (C.-W. Hsu et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2024\u003c/span\u003e); these techniques are relatively easy to apply for modulation of brain activity and are well-tolerated by depressed patients. Notably, these techniques offer cost-effective, scalable, and culturally acceptable treatment options, particularly in LMICs, where mental health resources are limited (Belay et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). They require minimal infrastructure and training, making them suitable for primary healthcare settings, and provide alternatives for treatment-resistant cases while reducing reliance on medications or specialized care (Kalpani Wijekoon Wijekoon Mudiyanselage et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Their portability and lower recurring costs enhance accessibility in underserved areas, though initial investment and regulatory frameworks remain challenges (Alokaily, Almeteb, Althabiti, Alshahrani, \u0026amp; Applications, 2022). However, there are significant challenges in the use of NINTs in treating depressed people in terms of unstable therapeutic effects as shown in the results of this review, which complies with the existing literature (Dobbins, Bastos, Ratis, Silva, \u0026amp; Bonini, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The cornerstone in the application of these techniques is the selection of a neuromodulation protocol (Garcia Pimenta, Brown, Arns, \u0026amp; Enriquez-Geppert, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The review findings highlight the absence of standardized protocols for NINTs. Key parameters\u0026mdash;such as pulse frequency in TMS, current intensity in tDCS, session duration and frequency, number of pulses per session, and cortical electrode placement\u0026mdash;exhibit significant variability across studies. This methodological heterogeneity likely contributes to the inconsistent findings in the literature regarding the efficacy of NINTs (Piccoli et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Furthermore, TMS and tDCS traditionally operate in an open-loop approach in delivery of stimuli without a responsive interaction between the nervous system, which is dynamic, and stimuli that may lead to degradation of the efficacy of the neuromodulation process or potentially produce side effects (Zanos, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, limited penetration depth and uncertainty of the effect persistence of the NINTs are considered to be among the limitations of these neuromodulation techniques (Z.-J. Li, Zhang, Chen, \u0026amp; Hu, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAddressing these challenges in NINTs, applied for treating depressive disorders, requires first of all to individualize and adapt the neurostimulation protocol to a specific state of the nervous system of each patient based on individual physiological state, inferred by biomarkers of depressive disorders. Applying a uniform neurostimulation protocol to all depressed patients\u0026mdash;a common practice in neurostimulation-based therapy\u0026mdash;may reduce treatment efficacy. This is because depression, whether unipolar or bipolar, is a clinically heterogeneous disorder with diverse symptomatic manifestations (Parker, Spoelma, \u0026amp; Tavella, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; van Loo et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Nonetheless, continuous or open-loop neurostimulation is a common practice among clinicians that may constitute the reason behind the controversy over the efficacy of neurostimulation in treating depressive disorders (Sellers et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Therefore, there is a desperate need for the application of individualized and responsive neurostimulation protocols in treating depressive disorders. Katherine W et al (Scangos et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) have applied personalized and closed-loop neurostimulation for treating depression and found that there was a rapid and sustained improvement in depressive symptoms. Furthermore, Garcia Pimenta et al (Garcia Pimenta et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) compared the efficacy of personalized non-invasive neuromodulation protocol, neurofeedback, in treating attention deficit hyperactivity disorder to that of non-personalized neurofeedback and found that the efficacy of personalized neurofeedback was superior to that of non-personalized. However, behavioral observations and self-report are still the main methods in the diagnosis of psychiatric disorders including depressive disorders (Farzan, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The identification of reliable biomarkers for real-time monitoring of non-invasive neurostimulation effects in depressive disorders remains a critical challenge in developing personalized neuromodulation protocols (Price et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Some studies have reported that latency and density of rapid eye movement could be used as biomarkers for monitoring depression (Arıkan et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Klooster et al (Klooster et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) investigated the potential brain biomarkers that could be used for evaluating response to NINTs in depression, and concluded that individual alpha peak frequency and frontal-midline\u0026ndash;elicited theta power, after task of activation of the rostral anterior cingulate cortex, are promising EEG biomarkers; however, there is still room for more research in order to examine the actionability of these EEG biomarkers (Klooster et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Thus, there is a need for further research on biomarkers that can be applied reliably to monitor the response to non-invasive neurostimulation in depression in order to establish optimal neurostimulation protocols that may lead to a clear understanding of the mechanism of neurostimulation in depression.\u003c/p\u003e\u003cp\u003eThis review has a number of limitations to be acknowledged. First, the number of included studies is low; all non-English publications were excluded, which increases the concern about missing important relevant studies. Second, studies were stratified by non-invasive neuromodulation technique, yet substantial methodological variability\u0026mdash;particularly in (1) participant selection criteria and baseline characteristics, (2) neurostimulation parameters (including device specifications and treatment protocols), (3) control conditions, and (4) outcome assessment measures with their corresponding analytical approaches\u0026mdash;precluded quantitative synthesis. Finally, the authors of the included studies have not been contacted for seeking clarification on whether there is a misinterpretation of their studies in this review.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eDespite an increasing number of research projects and publications on NINTs applied for the treatment of depressive disorders in the last ten years, there is still no consensus on the efficacy of neuromodulation techniques as is demonstrated in this systematic review. The selection of the appropriate protocol is the main focus of the neurostimulation process as the neurostimulation effect on brain functioning depends mainly on the kind of protocol and its procedure for implementation. The selection of reliable biomarkers that can be used for real-time evaluation of the non-invasive neurostimulation process in treating depressive disorders is still a major impediment to the development of personalized non-invasive neuromodulation protocols. Based on the articles reviewed, the individual alpha peak frequency and frontal-midline\u0026ndash;elicited theta power, after the task of activation of the rostral anterior cingulate cortex, are promising EEG biomarkers that could be used for evaluating response to NINTs in depression; however, there is still a need for more research in order to examine the actionability of these EEG biomarkers.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003eThis systematic review adheres to the highest ethical standards in research. Since this study involves the synthesis and analysis of existing published literature and does not involve direct interaction with human or animal subjects, formal ethical approval from an institutional review board (IRB) or ethics committee is not typically required.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompliance with research integrity guidelines\u003c/h2\u003e\u003cp\u003eThe review follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to ensure transparency and reproducibility.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eConflict of interest\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no conflict of interest\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlam M, Rodrigues W, Pham BN, Thakor NV (2016) Brain-machine interface facilitated neurorehabilitation via spinal stimulation after spinal cord injury: Recent progress and future perspectives. 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J Psychiatr Res 168:52\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jpsychires.2023.10.021\u003c/span\u003e\u003cspan address=\"10.1016/j.jpsychires.2023.10.021\" targettype=\"DOI\" 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":true,"hideJournal":true,"highlight":"","institution":"Vladimir State University","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Depression, Electroencephalography, Neurofeedback, Non-invasive neuromodulation, Transcranial direct current stimulation, Transcranial magnetic neurostimulation.","lastPublishedDoi":"10.21203/rs.3.rs-7278463/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7278463/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDepressive disorders (including both unipolar and bipolar depression) continue to present treatment challenges, with many patients failing to achieve adequate symptom relief. Non-invasive neuromodulation techniques (NINTs) have emerged as promising alternative interventions, particularly valuable in resource-limited settings. Our systematic review, drawing from PubMed and Scopus databases (2016-January 2024), evaluates current evidence on NINTs protocols for depression treatment. Key findings indicate that while most clinical applications still employ open-loop systems, closed-loop approaches utilizing EEG biomarkers (notably alpha peak frequency and frontal-midline theta power) demonstrate enhanced treatment precision. However, significant challenges remain in establishing reliable biomarker protocols for closed-loop implementation. NINTs offer particular advantages for lower middle-income countries (LMICs) through their cost-effectiveness, scalability, and minimal infrastructure requirements, though initial costs and regulatory barriers limit widespread adoption. This review highlights the urgent need for standardized protocols and identifies promising research directions to optimize NINTs' therapeutic potential. The transition from open-loop to biomarker-guided closed-loop systems represents a critical frontier in depression treatment innovation.\u003c/p\u003e","manuscriptTitle":"Advancements and challenges in the application of noninvasive neuromodulation techniques in treatment of depression: A systematic review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 14:01:57","doi":"10.21203/rs.3.rs-7278463/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3b2b21d9-4da3-4c17-a357-bb235ebd7de1","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":52540576,"name":"Cognitive Neuroscience"}],"tags":[],"updatedAt":"2025-08-05T14:01:57+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-05 14:01:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7278463","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7278463","identity":"rs-7278463","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}