Boosting brain functions combining tDCS with virtual reality: a systematic review in a healthy population

Boosting brain functions combining tDCS with virtual reality: a systematic review in a healthy population | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 9 January 2026 V1 Latest version Share on Boosting brain functions combining tDCS with virtual reality: a systematic review in a healthy population Authors : Chiara Milasi 0009-0007-8532-4563 , Maria Grazia Maggio , Giuseppe Perrotti , Paola Barbuto , Marina Barberio , Alfredo Albertini , Nicola Tallarico , … Show All … , Federico Rocca , Marianna Contrada , Francesca Gallivanone , Andrea Gaggioli , Rocco Salvatore Calabrò , Cristina Segura-Garcia , Domenico Bosco , and Antonio Cerasa 0000-0002-8022-4770 [email protected] Show Fewer Authors Info & Affiliations https://doi.org/10.22541/au.176794215.54896385/v1 488 views 106 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Objectives : This systematic review examines the combined use of transcranial direct current stimulation (tDCS) and virtual reality (VR) in healthy populations, with the aim of clarifying their synergistic potential for enhancing cognitive performance, emotional regulation, and general skills in non-clinical contexts. Methods : Following PRISMA guidelines, a comprehensive search of electronic databases (2000–September 2025) identified randomized and non-randomized studies employing simultaneous tDCS and VR in healthy individuals. Studies reporting psychological or cognitive quantitative outcomes were included. Risk of bias was assessed using RoB-2 and ROBINS-I tools. Results: Thirteen studies met inclusion criteria. Despite methodological heterogeneity in VR systems, stimulation parameters, and targeted brain regions, several convergent findings emerged. Significant enhancements were observed in sustained attention, inhibitory control, signal detection, and task learning. Emotional-regulation benefits were reported in impulsivity reduction and anxiety attenuation, particularly when anodal tDCS targeted prefrontal areas during VR exposure. Improvements in motor and procedural skills were also documented. Conversely, no consistent effects were found for cybersickness reduction, postural balance training, or spatial navigation. Neurophysiological correlates of behavioral change remain inconclusive across studies. Conclusions: Evidence suggests that combined tDCS–VR protocols may produce additive or synergistic effects on attention, inhibitory control, and anxiety modulation in healthy individuals, outperforming single-modality interventions in several domains. Future research should optimize stimulation targeting, define VR environments tailored for enhancement, and validate neurophysiological markers to advance the preventive and functional potential of this multimodal approach. INTRODUCTION Positive technologies (PTs) are a new scientific and practical approach thought to develop new methods aimed at improving the quality of the human experience by encouraging good emotions, well-being, engagement, and social connectivity (Riva & Gaggioli, 2014). These developments show promise for enhancing therapeutic efficacy and, more generally, quality of life, but they are not meant to take the place of conventional clinical therapies (Hirschtritt & Insel, 2018). PTs include a variety of tools like virtual reality (VR), telemedicine tools like mobile applications (Apps), and digital gadgets like smartwatches or electronic wristbands (Chen et al., 2023). PTs seek to improve cognitive function, encourage active participation, and advance a higher quality of life rather than just treating particular symptoms or diseases. Because of this, investigating the use of such tools in healthy individuals offers a worthwhile research opportunity as well as an exciting challenge that could lead to new theoretical and applied perspectives in the field of mental health. Apps for smartphones are essential to these PTs because they facilitate Positive Psychology Interventions (PPIs) that aim to improve emotional self-regulation and resilience (Feijt et al., 2023) and deliver self-guided cognitive-behavioral therapy (CBT) modules that have been shown to be effective in reducing symptoms of anxiety and depression (Fairburn & Patel, 2017). Wearable technology and biofeedback programs for stress self-management are two other real-world examples of PTs that have already been proven and put into practice. By monitoring bio-behavioural parameters (like sleep and physical activity) and providing real-time objective data, these devices aid in rehabilitation through Digital Phenotyping. These tools are essential for customising interventions for a range of clinical and medical conditions (Gaggioli et al., 2014; Guerrero-Jiménez et al., 2023). Among PTs methods, VR has attracted increasing interest as a tool for its translational applications in several psychopathological domains, since this offers immersive, controllable, and ecologically valid environments (Riva & Serino, 2020). VR systems enable users to interact meaningfully with simulated scenarios, which can promote emotional change, awareness and psychological well-being by allowing a strong sense of “presence” (Riva & Serino, 2020). In the case of eating disorders, Riva et al. (2021a) proposed four different VR‐based clinical approaches. These were VR cue exposure (VR-CET), visual reference frame shifting, correcting body distortions, and attentional bias modification. In VR-CET the aim is to extinguish/habituate craving and anxiety responses to food cues. It achieves this goal through a classical conditioning binge eating model, with the addition of VR technology that can generate a safe ecological simulation of real-life scenarios. In Visual Reference Frame shifting and the correction of body distortions, eating disorders patients are considered to be locked in a body they detest, according to the Allocentric Lock theory. VR instruments help patients re-experience episodes of their life through custom-made simulations and both an Ego-centric and Allocentric perspective in order to achieve integration. In attentional bias modification, a new perspective can be instilled in the patient through their exposure to digitalized images and realistic avatars of their body in conditions of underweight, normal weight and overweight. They found that particularly VR exposure and reference frame shifting have reached substantial evidence and may provide advantages over standard CBT in the reduction of cravings and anxiety, for bulimia nervosa and binge eating disorder (BED) (Riva et al., 2021b). VR therapies have also shown efficacy in other psychiatric conditions, such as anxiety disorders, post‐traumatic stress disorder, phobias, schizophrenia, and addiction (Kim & Kim, 2020). According to Kim & Kim (2020) and Riva & Serino (2020), interventions of this type frequently enable repeated exposures, a gradual modification of difficulty, and a personalization customized to the patient’s demands, making VR a flexible adjunct—or, in certain situations, an alternative—to traditional therapies. For example, VR exposure has been shown to be very effective in treating certain phobias and, more generally, anxiety disorders. Several studies report sustained improvements up to 3–6 months after treatment, along with lower dropout rates and a strong patient preference for virtual environments over real-life situations. The ability to recreate controlled social environments or contexts typical of panic attack onset allows for gradual and safe exposure in patients with social anxiety disorder or panic disorder with agoraphobia. This is further supported by real-time biofeedback monitoring, which allows for instantaneous adjustment of stimulus intensity. In a similar vein, people with post-traumatic stress disorders (PTSD) can confront memories that would otherwise be impossible to evoke without taking undue risks thanks to the VR technique. Significant improvements in post-treatment symptoms and favorable acceptance ratings have also been documented in this setting (Kim & Kim, 2020; Riva & Serino, 2020). Moreover, VR is also being used to target transdiagnostic psychological factors such as emotion regulation, avoidance, impulsivity, cognitive reappraisal, and aggression. VR-based therapies often improve all three factors, with results that are often sustained up to a 12-month follow-up, according to a systematic analysis by Gardini et al. (2022). For instance, patients with specific phobias or social anxiety disorder can progressively and repeatedly approach fearful stimuli with Virtual Reality Exposure Therapy (VRET), which is the preferred treatment for tackling avoidance. This procedure stops the vicious cycle that sustains anxiety and aids in the extinction of fear responses. In terms of emotion regulation, VR facilitates the acquisition of coping mechanisms by offering both mindfulness-based scenarios intended to promote relaxation and lower physiological arousal as well as virtual social contexts where people can practice controlling and modulating the expression of strong emotions like rage. Similar to this, in situations involving impulsivity or aggression, the virtual environment can mimic aggressive or frustrating circumstances, providing a secure setting where patients can actively practice alternative problem-solving techniques and non-impulsive responses, giving them more control over their reaction patterns. Lastly, by allowing people to actively experience and change interpretative biases within certain circumstances, VR can help cognitive restructuring (Gardini et al., 2022). Finally a recent systematic review (Milasi et al., 2025) demonstrated that mindfulness-based interventions (MBI) mediated by VR induced a prolonged and defined impact on emotional regulation in healthy individuals. In the last few years, it has been demonstrated that when PTs applications are combined with non-invasive brain stimulation (NIBS) methods, such as transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS), significant boosting effects were described. Generally tDCS alone has been used to supplement and improve treatments for neurological or psychiatric disorders (Kang et al., 2024). This NIBS method modifies neuronal excitability by applying weak electrical currents to cortical areas through electrodes applied to the scalp. This modulation has been associated with changes in synaptic plasticity, which in turn can enhance cognitive functions and emotional regulation (Dedoncker et al., 2016). Over the past decade, tDCS has been emerging as a potential therapeutic tool in the psychiatric field, due to its ability to modulate abnormal brain activity in disorders such as depression, anxiety disorders, schizophrenia, substance use disorders, and eating disorders (Kar & Vidya, 2025). For example, a large meta-analysis demonstrated that active tDCS was superior to sham stimulation in improving response and remission rates in patients with major depression, indicating its added benefit when combined with conventional therapy (Moffa et al., 2020). Numerous other studies highlight the effectiveness of tDCS in managing depressive episodes (Kumari et al., 2023; Razza et al., 2020; Wang, 2019; Zhang et al., 2021), including when combined with psychotherapeutic (e.g., Bajbouj et al., 2018) or pharmacological treatments (e.g., Brunoni et al., 2019; Fregni et al., 2021). Indeed, the combination of tDCS with antidepressant medication can yield improved clinical outcomes, especially in treatment-resistant cases (Brunoni et al., 2017). For depressive disorders, most studies employ anodal stimulation of the left DLPFC and cathodal stimulation of the right DLPFC (Kumari et al., 2023; Zhang et al., 2021). Another application of tDCS is the management of substance use disorders and behavioral addictions (Hyde et al., 2022; Johnstone et al., 2022; Song et al., 2022; Stanković et al., 2023). In most studies, the DLPFC is the common target area for neuromodulation in the treatment of substance use disorders (Hyde et al., 2022; Johnstone et al., 2022; Kim & Kang, 2021; Song et al., 2022; Stanković et al., 2023). Several studies report that multisession neuromodulation protocols lead to a reduction in substance use and craving compared with single-session interventions (Kim & Kang, 2021; Song et al., 2019). Emerging evidence also supports the use of tDCS in eating disorders. Some studies have evaluated the effectiveness of tDCS in patients with anorexia nervosa, showing improvements in anorexia symptoms and other psychopathological features associated with the condition (e.g., Costanzo et al., 2018; Khedr et al., 2014). Kekic et al. (2017) found tDCS to be effective in patients with bulimia nervosa, reporting improvements in binge eating symptoms and mood. Other studies indicate that the use of tDCS in patients with BED may lead to improvements such as reduced binge frequency, decreased food craving, and enhanced inhibitory control toward rewarding food stimuli (Burgess et al., 2016; Max et al., 2021). When PTs and non-invasive stimulation tools are used in combination a significant behavioral boosting has been described combined (Cheng et al., 2024). The effectiveness of this combined strategy has widely been validated in the neurological realm across a range of pathological contexts (Cassani et al., 2020) . For example, in patients with chronic stroke, the targeted use of anodal tDCS combined with gait rehabilitation in a VR setting has exceeded the Minimal Clinically Important Difference (MCID) threshold for gait speed, resulting in a clinically significant and quantifiable improvement in ambulation (Marks et al., 2025).For example, cerebellar tDCS combined with an Augmented Reality treadmill (C-Mill VR+) has been specifically tested for the treatment of movement disorders like Parkinson’s Disease (PD) with Freezing of Gait (FoG), demonstrating to boost postural stability (Pisano et al., 2024). The combined method has also been extended to the treatment of chronic pain in patients with spinal cord injury (SCI). It was found that multichannel tDCS using electrodes in the neoprene cap, with the anode targeting the motor cortex (M1) and the cathode covering the contralateral supraorbital area, and the visual illusion system using the patient’s upper body image and a complementary image of an animated digital image showing the movement of walking arms or legs have been found to have an analgesic impact in neuropathic pain, with favorable effects on mood and sleep quality (Soler et al., 2021). Despite the validated application in the neurological realm, the combination of tDCS with VR has also been widely applied in psychiatric disorders. For instance VRET and tDCS has shown promising results in the reduction of symptoms in anxiety and traumatic disorders. The use of tDCS anodically during VR exposure for PTSD has resulted in a significant reduction in the severity of symptoms within a month (van’t Wout-Frank et al., 2024), and a similar effect on the reduction of symptoms has been linked to tDCS and VRET in the treatment of acrophobia (Hui et al., 2024). Therefore, the scientific literature converges on the effectiveness of the tDCS-VR paradigm, reporting an increasing number of studies conducted in clinical populations, while also highlighting promising results in the general population. For instance, several studies suggest that meditation practices, mediated by VR, may enhance cognitive functions such as memory and attention, as well as act as a protective factor against age-related cognitive decline (Chételat et al., 2017; Gard et al., 2014). Moreover, such practices appear to foster neuroplastic effects, including both structural and functional brain changes (Abellaneda-Pérez et al., 2024), and to promote psychological well-being while reducing negative affective states (Milasi et al., 2025). However, the novel investigative approach combining neuromodulation techniques with VR environments—aimed at cognitive enhancement and emotional regulation—is still in its early stages. There are now a number of controlled and systematic studies that hinder a full understanding of the potential of these technologies to improve psychological well-being and cognitive, affective, and behavioral functioning. Thus, the current systematic review aims to fill this gap by offering an extension of the tDCS–VR paradigm beyond the therapeutic domain, examining how and which studies have focused on their analysis of the non-clinical population, analyzing the results, and moving toward a functional and preventive potentialization model. Protocol The protocol of this systematic review was registered on PROSPERO (CRD420251169010), following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Page et al., 2021). Main outcomes Given the growing integration of technologies into health promotion and preventive care, this review aims to provide a comprehensive overview of the outcomes reported in studies investigating the combined use of tDCS and VR. The review specifically addresses the question: What are the effects of combining tDCS with VR on the non-clinical population? The primary outcomes include psychological and cognitive variables, such as improvements in psychological well-being, stress, anxiety, positive and negative affect, depressive symptoms, sustained and selective attention, and working memory, as measured using standardised psychometric instruments. Secondary outcomes include measures of intervention acceptability, sensory immersion, and methodological variables such as the duration, content, and format of the VR experience, as well as neurophysiological indicators (e.g., electroencephalography (EEG) or fNIRS measures of cortical excitability), user engagement and presence, task performance metrics, motor learning or skill acquisition, cognitive workload, fatigue, and adverse effects or tolerability of tDCS. By providing an updated synthesis of the field and identifying the most effective design features of practices combining tDCS with VR, this review aims to support further research and guide the application of innovative and immersive technologies for psychological health and enhancement in non-clinical populations. PICO model The methods to define search terms according to the PICO model: population, intervention, comparison and outcome (Brown, 2019). We included only studies where tDCS-VR was applied to non-clinical populations. The comparison included participants who received either sham tDCS with VR or active tDCS without VR, and the outcome was a psychological assessment or cognitive assessment (see the paragraph “main outcomes”). Search strategy Articles published between January 2000 and September 2025 were reported using electronic bibliographic databases such as PubMed, Scopus, and IEEXplore. To improve the search strategy, keywords including “text words” and MeSH were used. The search terms incorporated the following keywords: (”tDCS” OR ”transcranial direct current stimulation”) AND (”VR” OR ”virtual reality” OR ”immersive reality”). The inclusion and exclusion criteria were defined a priori. Inclusion criteria were (a) Studies on humans without diagnosed pathologies; (b) Simultaneous tDCS and VR intervention; (c) Original reports (clinical trials, pilot studies, case series); (d) English language; (e) From 2000 to September 2025. In addition, we excluded (i) animal studies, (ii) studies focusing solely on other innovative approaches (such as exergaming or serious games without the use of smartphones or tablets), and (iii) studies involving individuals with diagnosed psychiatric or medical conditions. Article selection was carried out based on titles and abstracts by five independent researchers (C.M.; M.B; P.B; N.T; A.A. ), who also conducted data extraction separately in order to minimize the risk of bias (i.e., the bias associated with the omission of relevant findings). In cases of disagreement, consensus was achieved through discussion and, if necessary, the involvement of a sixth researcher (A.C.). The list of articles was then refined for relevance, revised, and summarized, with the key themes identified from the summary based on the inclusion/exclusion criteria. Synthesis of evidence A total of 1,067 articles were identified through searches in online databases. We excluded 679 articles that did not meet criteria using automated techniques (Database filters applied: language – English; species – humans; and 18 duplicates; only research articles) and 11 duplicates. We screened the titles and abstracts of 377 articles and removed 362 articles that did not meet the eligibility criteria. A full-text screening of 15 articles was conducted, and 2 articles were removed. Finally, we included and analyzed 13 articles (Figure 1). Quality assessment and risk of bias in randomized control trial (RCT) The risk of bias in each study was assessed using tools selected according to the specific study design. Eight out of thirteen studies were assessed using the revised Cochrane risk-of-bias tool for randomized trials (RoB 2) (Sterne et al., 2019). This tool evaluates five key domains: i) bias from the randomization process, ii) bias due to deviations from the intended interventions, iii) bias from missing outcome data, iv) bias in outcome measurement, v) bias in the selection of reported results (Figure 2). The Risk of Bias in Non-randomized Studies of Interventions (Robins-I) For the five non-randomized experimental studies, the ROBINS-I tool was used to assess risk of bias. (Sterne et al., 2016). This tool assesses seven key areas: i) bias due to confounding; ii) bias in selection of participants into the study; iii) bias in classification of intervention; iv) bias due to deviations from intended interventions; v) bias due to missing data; vi) bias in measurement of outcomes; and vii) bias in the selection of the reported result (Figure 3). RESULTS The electronic search strategy conducted across four bibliographic databases retrieved 1,067 studies. After screening titles and abstracts and removing duplicates, 15 studies remained for full-text review. Of these, 2 studies were excluded because they did not use VR or did not have a healthy population. Ultimately, 13 articles were included in this review. TABLE 1 . Characteristics of studies applying VR systems and tDCS. Author(s) Year Country Population Aims Study design VR-System Type of tDCS stimulation Outcome measures Main Results Freire-Santos et al. 2025 Portugal •Sample size: 107; •Population: healthy participants(university students); •Age: 18 to 50; •Sex: 81 females, 26 males. The effects of a single VR-FM session, a single tDCS session, and their combination on sustained attention, attentional control, and inhibitory control. RCT - Five group: •Experimental 1: VR-FM and anodal tDCS ( n =21) •Experimental 2: VR-MW + anodal tDCS (n = 22) •Experimental 3: VR-FM + sham tDCS ( n= 21) •Experimental 4: VR-MW + sham tDCS ( n= 22) •Control: no intervention ( n =21). Oculus Rift S VR System •Region: left dlPFC •Position: anode at F3, cathode at F4. •Application: experimental 1 and 2 at 2 mA for 20 min; experimental 3 and 4 at 0.3 mA for 20 min. •EST •SART •DASS-21 •MAAS •TMT •DERS-SF •nsSCR Between-group results: ↓ Reduced nsSCR in experimental1 respect to experimental4 (p= .014). Berger et al. 2024 Austria •Sample size:41 •Population: university students; •Age: 18 to 34. •Sex: 21 females, 20 males. tDCS placebo intervention can influence CS symptoms in a VR-based NF training and whether CS affects NF performance. Placebo-intervention affects potential side effects of VR interaction and consequently NF training performance. RCT- Two groups •Experimental: VR + sham tDCS ( n= 21) •Control: VR + no-treatment ( n= 20) HTC Vive Pro-System •Region: dlPFC •Position: anode at F3, cathode at C4. •Application: experimental 1mA for 3 min. •SSQ Between-group results: No significant effect. Hui et al. 2024 China •Sample size: 61; •Population: university students; •Age: 23 to 35; •Sex: 32 females, 29 males. tDCS can enhance the efficacy of VRET. RCT- Two groups •Experimental:anodal tDCS + VRET ( n= 30) •Control: tDCS sham + VRET ( n= 31) Oculus Quest 2 •Region: mPFC •Position: anode at FPZ, cathodes at AF7, AF8, F3, and F4. •Application: experimental 1,5 mA for 20 min; sham 0 mA for 20 min. •AQ •HIQ •STAI-Y •BAI •SUDS Between-group results: ↓ Reduced in psychometric level and behavioral anxiety in the experimental group compared to the control group ( p < 0.001). Shahbazi et al. 2024 Iran •Sample size: 36; •Population: sedentary teenage girls; •Age: 15 to 18; •Sex: 36 females. Effects of repetitive unihemispheric concurrent dual-site a-tDCSUHCDS associated with the use of VR games on the motor coordination of sedentary adolescent girls. RCT- Three groups • Experimental1: VR + anodal tDCS UHCDS ( n= 12) • Experimental 2: VR + sham-tDCSUHCDS ( n= 12) • Control: no-treatment ( n= 12) Xbox 360 and Kinect Xbox 360, Microsoft •Region: M1 and dlPFC •Position: two anode electrodes at C3 and F3. Two cathode electrodes at AF4 and one centered between Fpz and AFz. •Application: experimental1 at 2 mA for 20 min; experimental2 at 2-mA only for 30 s. •IPAQ •Automatic Mirror Trace (EHC) •Two-Arm Coordination Test device (BC) Between-group results: ↑ Improved EHC post-intervention in experimental 1 ( p <0.001) and experimental 2 ( p <0.0001 ) compared to control. ↑ improved EHC at the retention in experimental 2 compared to control ( p <0.001) ↑ improved BC post-intervention in experimental1 ( p <0.001) and experimental2 ( p <0.0001) compared to control ↑ improved BC at the retention in experimental1 ( p <0.001) and experimental2 ( p <0.001) compared to control Yang et al. 2023 Seoul, Republic of Korea •Sample size: 10; •Population: healthy participants; •Age: M =24,3, DS= 1,5 •Sex: 10 male Anodal HD-tDCS effects on the right rVLPFC in 3D sustained attention tasks (VR). Repeated measurements design: • Experimental: VR + anodal HD-tDCS • Control: VR + sham HD-tDCS VR Oculus Quest (The Meta Inc., Menlo Park, CA, USA) •Region: rVLPFC •Position: anode at FC6, cathode in 4×1 ring at F4, F8, C4, T8. •Application: Experimental 1 mA for 10.5 min (15 s fade-in/out); Control 1 mA during both the first and last 30 s •Go-Nogo task •EEG (ERPs) •Self-reports of attentional level Between-group results: ↑ Increased perceived attention in experimental compared to control ( p =0.005). ↑ Increased accuracy in experimental compared to control ( p =0.005). ↑ Increased reaction time in experimental compared to control ( p =0.047 ). Corrêa et al. 2023 Brazil •Sample size: 57; •Population: healthy older women; •Age: 60 to 80 •Sex: 57 females tDCS can enhance the effect of VGT on improving the postural balance of healthy older women. RCT- Three groups • Experimental1: VGT + anodal tDCS ( n= 19) • Experimental 2: VGT + sham tDCS ( n= 19) • Control: VGT ( n= 19) Sony VPL‐DX120 •Region: dlPFC •Position: anode F3, cathode at right supraorbital region •Application: experimental1 and 2 at 2 mA for 20 minutes; control only for 60 seconds. •MMSE •BDI Between-group results: No significant effect. Bulteau et al. 2022 France •Sample size: 25; •Population: healthy participants; •Age: M =37 •Sex: 18 females, 7 males. Investigate the feasibility of combining tDCS and wireless 360° fully immersive active and embodied VRET to reduce height-induced anxiety. RCT- Two groups • Experimental: anodal tDCS+VRET ( n= 11) •Control: sham tDCS + VRET ( n= 14) HTC Vive CV1 •Region: vmPFC •Position: anode at FpZ, cathode under the chin. •Application: experimental 1 mA anodal stimulation for 20 min; control 30 seconds of stimulation ramp-on and ramp-up. •AQ •ATHQ •HIQ •vHIQ •STAI-Y •CGI •SUD •IPQ •SSQ Between-group results: No significant effect. Ferrucci et al. 2019 United Kingdom •Sample size: 40; •Population: healthy participants; •Age: M= 26.65 •Sex: 24 females,16 males. Cerebellar tDCS influences spatial navigation using VR. RCT- Two groups • Experimental1: anodal tDCS + VR •Control: sham tDCS + VR HMD Oculus Rift DK2 •Region: Cerebellum Position: anode on the median line 2 cm below the inion; cathode over the right deltoid muscle. •Application: experimental1, 2 mA for 20 min; control, for 20 seconds. •RTs •CSSL Between-group results: No significant effect. Takeuchi et al. 2018 Japan •Sample size: 20; •Population: healthy participants; •Age: M =21.5, SD =1.1; •Sex: 11 females, 9 males. VR-related sickness could be relieved by the modulation of cortical excitability in the TPJ. Repeated measurements design. •Experimental 1: tDCS anodal + VR •Experimental 2: tDCS cathodal + VR •Control: tDCS sham + VR HTC VINE •Region: TPJ •Position: anode CP6, cathode Cz. •Application: anodal and cathodal condition at 1.5 mA for 15 minutes; sham condition 1.5mA for 30 seconds. • SSQ •Heart rate • COP baseline Between-group results: No significant effect. Ciechanski et al. 2017 Canada •Sample size: 22; •Population: medical students; •Age: M =25.2; •Sex: 16 females, 6 males. Effects of tDCS on simulation-based neurosurgical skill Acquisition using VR. RCT - double blind •Experimental: anodal tDCS + VR ( n= 11) •Control: tDCS sham +VR ( n= 11) NeuroTouch Neurosurgical Simulator •Region: M1 •Position: anode C3, cathode C4. •Application: Experimental at 1 mA for 20 min; control at 1 mA for 60 seconds. •Percentage of tumor resected •Volume of healthy brain resected • Time of excessive forces Between-group results: ↑ Improved resection efficiency in experimental respect to control ( p= 0.006). No significant effect in tumor resected, brain resected, resection effectiveness and excessive force. Coffman et al. 2012 USA •Sample size: 55; •Population: healthy participants; •Age: M =23.7; •Sex: 22 females, 33 males. Cognitive mechanisms of anodal tDCS that lead to enhanced performance during learning of a difficult VR-based target detection task. Two-arm, mixed •Experiment 1 ( n= 36) Experimental 1: 2.0 mA tDCS +VR ( n= 13) Experimental 2: 0.1 mA tDCS +VR ( n= 23) •Experiment 2 ( n= 19) Experimental3: 2.0 mA tDCS +VR( n= 9) Experimental4: 0.1 mA tDCS +VR ( n= 10) DARWARS VR-training environment •Region: IFC •Position: Anode F10, cathode was placed on the subject’s left upper arm. •Application: 30 min experimental 2 and 4 at 0.1 mA; experimental 1 and 3 at 2.0 mA. •Testing stimuli: images containing objects Between-group results: ↑ Improvement signal detention in Experimental 1 and 3 respect to experimental 2 and 4 ( p= 2.73e−4) Clark et al. 2012 USA •Sample size: 83; •Population: healthy participants; •Age: M =24.1; •Sex: 30 females, 53 males. Cognitive mechanisms of anodal tDCS that lead to enhanced performance during learning of a difficult VR-based target detection task. Four-arm, mixed design •Experiment 1 Experimental1: full-current tDCS F10 + VR ( n =13) Experimental2: low-current tDCS F10+ VR ( n =14) •Experiment 2 Experimental3: full-current tDCS F10+ VR ( n =13) Experimental4: low-current tDCS F10 + VR ( n =23) •Experiment3 Experimental5: intermediate-current tDCS +VR ( n =8) •Experiment4 Experimental6: full-current anodal tDCS P4 +VR ( n =12) “DARWARS Ambush!” VR training environment (MacMillan et al., 2005; Raybourn, 2009) •Region: right IFC; right parietal cortex. •Position: Experiment 1,2,3 the anode was placed on F10, cathode at contralateral arm; experiment 4 the anode was placed on P4. •Application: 30 min, experimental 2 and experimental 4 at 0.1 mA; experimental 1, 3 and 6 at 2.0 mA; experimental 5 at 0.6 mA. •Testing stimuli: images containing objects •Self-reported skill sensation Between-group results: ↑ Increased learning in Experimental 1 respect to experimental 2 ( p= 0.0006) No significant effect between other experimental groups. Beeli et al. 2008 Switzerland •Sample size: 35; •Population: university students; •Age: M =20.9, SD= 3.7; •Sex: 17 females, 18 males. How modulation of right dlPFC activity affects autonomic nervous system responses and impulsivity Repeated measurements design , participants were randomly assigned at three different tDCS treatments: •Experimental 1: anodal tDCS +VR •Experimental 2: Cathodal tDCS +VR •Control: Sham tDCS +VR Computer screen placed at a distance of 60 cm in front of them. (http://www.nolimitscoaster.com.). •Region: right dlPFC •Position: In experimental1 anode electrode on FC3 and cathode electrode on the ipsilateral mastoid. In experimental2 were switched. For control was switched off. •Application: lasted 5.5 min at a constant current intensity of 1.5 mA. •EDA: SCR and SCL •EMG •Go-Nogo task •MEC-SPQ •SAM Between-group results: ↑ Enhanced Impulsive behavior control in experimental 2 respect the experimental 1 and control ( p <0.03) ↑ Enhanced SCL in experimental 2 respect to experimental 1 and control ( p <0.01) No significant effect in MEC-SPQ and SAM. Legend: AQ: Acrophobia Questionnaire; a-tDCSUHCDS: repetitive unihemispheric concurrent dual-site anodal transcranial direct current stimulation; ATHQ: Attitude Towards Heights Questionnaire; BAI: Beck Anxiety Inventory; BC: bimanual coordination; BDI: Beck Depression Inventory; CGI: Clinical Global Impression; COP: center of pressure; CSSL: Corsi Supra-span Learning; CS: cybersickness; DASS-21: depression anxiety and stress scale; DERS-SF: difficulties in emotion regulation scale-short form; dlPFC: dorsal lateral pre-frontal cortex; EDA: electro-dermal activity; EEG: Electroencephalography; EHC: Eye-hand coordination; EMG: electro-myogram; ERPs: event-related potentials; EST: emotional stroop; FM: Focused Mindfulness meditation; HD-tDCS: high-definition transcranial direct current stimulation; HIQ: Heights Interpretation Questionnaire; IFC: inferior frontal cortex; IPAQ: International physical activity questionnaire; IPQ: Igroup Presence Questionnaire; MAAS: Mindful attention and awareness scale; MMSE: Mini‐Mental State Examination; M1: primary motor cortex; MEC-SPQ: spatial pres-ence questionnaire; mPFC: medial prefrontal cortex; MW: Mind-wandering; NF: neurofeedback; nsSCR: non-specific skin conductance response; RCT: randomized control trial; RTs: Simple visual reaction times; rVLPFC: ventrolateral prefrontal cortex ; SAM: Self Assessment Manikin; SART: sustained attention to response task; SCL:skin conductance level; SCR: skin conductance responses; SSQ: simulator sickness questionnaire; STAI-Y: State-Trait Anxiety Inventory Form Y; s-tDCSUHCDS: sham condition; SUD: Subjective Units of Distress; SUDS: Subjective Units of Discomfort; TMT: trail making test A and B; TPJ: temporoparietal junction; VGT: video game training; vHIQ: Visual Height Intolerance questionnaire; vmPFC: ventromedial prefrontal cortex; VRET: Virtual Reality Exposure Therapy; Study and sample characteristics The sample sizes of the 13 studies included in this analysis varied from 10 to 107 participants, with over 100 participants in only one study (Freire-Santos et al., 2025). The participants’ ages ranged from 15 to 80 years old. Eight studies included healthy volunteers not divided by social/work classes ( n= 397) (Bulteau et al., 2022; Clark et al., 2012; Coffman et al., 2012; Corrêa et al., 2023; Ferrucci et al., 2019; Freire-Santos et al., 2025; Takeuchi et al., 2018; Yang et al., 2023), four studies included university students ( n= 159) (Beeli et al., 2008; Berger et al., 2024; Ciechanski et al., 2017; Hui et al., 2024), and only one study included sedentary teenage girls ( n= 36) (Shahbazi et al., 2024). Both male ( n= 227) and female ( n= 365) individuals were included. Eight studies are RCTs, three use a repeated-measures design, and two use a mixed design. Quality of Included Studies: Risk of Bias Eight of the thirteen studies were evaluated using the revised Cochrane Risk of Bias tool for randomized trials (RoB 2) (Sterne et al., 2019). The domains in which the greatest concerns were observed were Domain 1 (bias arising from the randomization process) and Domain 5 (bias in selection of the reported result). Regarding Domain 1, three out of eight studies (Bulteau et al., 2022; Ciechanski et al., 2017; Ferrucci et al., 2019) were rated as having some concerns, mainly because the method of sequence concealment was not described. Moreover, the study by Berger et al. (2024) was judged as high risk, since not only was the sequence concealment method not described, but a “pseudo-random randomization” procedure was reported to ensure equally sized groups, without clarifying how the randomization was conducted. This raises the risk that the enrolling investigator or the participant could have had knowledge of the forthcoming allocation. Issues in randomization reduce confidence in group comparability at baseline. The studies by Freire-Santos et al. (2025); Hui et al. (2024); Shahbazi et al. (2024); and Corrêa et al. (2023) were rated as low risk, reflecting adequate methodological transparency. In Domain 5, four out of eight studies (Berger et al., 2024; Ferrucci et al., 2019; Freire-Santos et al., 2025; Hui et al., 2024) were judged as having some concerns, due to the absence of a registered protocol or a pre-specified analysis plan. This may lead to selective reporting, especially in studies employing multiple outcome measures without clarifying which analyses were planned in advance. In Domain 2 (bias due to deviations from the intended interventions) all studies were rated as low risk of bias, except for Ferrucci et al. (2019) which was rated as having some concerns. This is because the study does not specify if participants had missing data or were excluded after randomization due to not completing the task or failing to provide outcome data. In Domain 3 (bias due to missing outcome data), all studies were rated as low risk of bias, as outcome data were largely complete. This indicates that the study conclusions were not distorted by participant dropout or inappropriate handling of missing data. Similarly, in Domain 4 (bias in measurement of the outcome), all studies were rated as low risk of bias, reflecting strong adherence to protocol and objective outcome measurements. Overall, one (Berger et al., 2024) out of eight studies was rated as having some concerns due to methodological limitations in reporting randomization and the absence of a pre-registered analysis plan. Ferrucci et al. (2019) was rated as high risk of bias due to having some concerns in domains 1, 2 and 5, which may compromise the validity of the study by reducing confidence in baseline group comparability, the effect of the intervention as assigned, and the reliability of the reported results. The remaining six studies were classified as low overall risk, reflecting more robust study design and transparent reporting practices. For the five non-randomized experimental studies, the risk of bias was assessed using the ROBINS-I tool (Sterne et al., 2016). The domains with the greatest concerns are Domain 1 (bias from confounding) and Domain 7 (bias in the reporting of results). Specifically, all five studies (Beeli et al., 2008; Clark et al., 2012; Coffman et al., 2012; Takeuchi et al., 2018; Yang et al., 2023) were rated as having some concerns in Domain 1, mainly because of incomplete or absent management of potential confounders (e.g., individual factors such as prior experience with VR tasks are not evaluated). Similarly, in Domain 7, all five studies were assessed with some concerns, primarily due to the absence of a pre-registered research protocol or a predefined analysis plan, which increases the risk of selectively reporting results. The other domains generally present a low risk profile. Specifically, Domain 2 (bias in participant selection) shows a low risk in all studies, with pre-intervention selection and rigorous protocols. Domain 3 (bias in intervention classification) also exhibits low risk thanks to clear and well-defined intervention assignment. Domain 4 (bias from deviations from the intended intervention) is rated as low risk across all studies, with strict adherence to protocols. In Domain 5, only one study (Clark et al., 2012) was judged to have some concerns, primarily due to post hoc data exclusions for which the authors did not clarify the criteria adopted nor whether these exclusions materially affected the study outcomes. The remaining articles are rated as low risk, as they are based on complete participant data. In Domain 6 (bias in outcome measurement), one study also received a rating of some concerns, mainly due to the lack of transparency regarding assessor blinding. The other articles received a low risk rating. Overall, two out of five studies (Beeli et al., 2008; Clark et al., 2012) obtained an overall score of some concerns, largely due to confounder-related issues, while most studies displayed a low risk across the other domains. This reflects a generally more robust study design and reporting practices. Outcome As shown in the last column of Table 1, the application of combined VR+tDCS approach yields different successful and unsuccessful outcomes. Moreover, the tDCS application on brain regions is also characterized by spatial heterogeneity. For this reason, Figure 4 summarizes the main outcomes, categorized as emotional control (anxiety, impulsivity, and skin conductance response), cognitive abilities (attention and spatial navigation), general skills (motor coordination, neurosurgical skills, motor balance), and cybersickness, over the brain stimulated regions. Cognitive outcome Six of the thirteen studies included in this review aims to investigate cognitive processes: sustained attention, attentional control, inhibitory control and spatial navigation. Four of these six studies showed significant results (see Figure 2). In Yang et al. (2023) results there was a significant difference between anodal tDCS and sham tDCS. In fact, increased perceived attention ( p= 0.005), accuracy ( p= 0.005) and reaction time ( p= 0.047) were observed. Clark et al. (2012), using a target detection task, found that anodal tDCS increased discovery-learning with respect to cathodal tDCS ( p= 0.0006). Using the same task as Clark et al. (2012), Coffman et al. (2012) showed improvement in signal detection ( p= 2.73e−4) with the 2.0 mA tDCS stimulation technique compared to 1.0mA tDCS. For impulsive control, Beeli et al. (2008) enhanced impulsive behavior in an anodal tDCS group compared to a cathodal or sham tDCS group ( p< 0.03). Psychological outcome Four of the thirteen studies included in our review used psychometric tests to examine psychological outcomes, with a specific focus on depression, stress, and anxiety (Bulteau et al., 2022; Corrêa et al., 2023; Freire-Santos et al., 2025; Hui et al., 2024). A more objective assessment of the effects was made possible by these studies’ use of validated measurement instruments to examine changes in participants’ psychological states after the intervention. However, a statistically significant effect was only observed by Hui et al. (2024). Participants in the experimental group of this study, which received active tDCS in conjunction with VR, showed a significantly greater reduction in anxiety levels than those in the control group, which received sham tDCS in combination with VR ( p< 0.001). Other outcome In addition to cognitive and psychological outcomes, two of the thirteen studies included in our review reported improvements in motor coordination and neurosurgical skills. Shahbazi et al. (2024) observed consistent improvements in both hand-eye coordination and bimanual coordination, with effects that were maintained at least 2 weeks after the end of training in those who received VR-tDCS ( p< 0.001) compared to control group (no-treatment). Specifically, hand-eye coordination improved post-intervention with sham+VR compared to control ( p< 0.001). Bimanual coordination improved in the sham+VR tDCS intervention compared to control ( p< 0.001), and finally, improved retention was observed in both groups compared to control ( p< 0.001). Ciechanski et al. (2017) led to improvements in the efficacy of resection in those who received tDCS with VR and there was an increase in the amount of tumor removed compared to the control group (tDCS sham + VR) ( p =0.006). Methodological approaches to implementing VR and tDCS In every study included in this review, the methodological approaches used were the combination of VR and tDCS. The combined use of these two technologies resulted in significant variation among investigations, in fact, numerous tools and approaches have been used to provide VR, and different areas of the brain have been the focus of different investigations. The VR systems used in the thirteen studies included in this review are immersive or semi-immersive. The immersive VR systems are the 3D headset: Oculus Rift (Ferrucci et al., 2019; Freire-santos et al., 2025), HTC Vive Pro system (Berger et al., 2024; Bulteau et al.,2022; Takeuchi et al., 2018), Oculus quest 2 (Hui et al., 2024), Oculus quest (Yang et al., 2023). The semi-immersive VR systems are delivered by computer (Beeli et al., 2012; Clark et al., 2012; Coffman et al., 2012 ), Xbox360 (Shahbazi et al., 2024), projector (Corrêa et al.,2023) and stereovision system (Ciechanski et al., 2017). Since the EEG 10–20 approach was used in all research to locate the cortical areas of interest, the tDCS systems were uniform in their design. However, as Figure 2 shows, there were significant differences between studies in terms of both the stimulation sites and the applied intensities. Twelve studies used anodal stimulation to target different parts of the brain in relation to the active experimental groups: Clark et al. (2012) and Coffman et al. (2012) at the IFC, Beeli et al. (2008), Corrêa et al. (2023) and Freire-Santos et al. (2025) at the dlPFC, Bulteau et al.(2022) at the vmPFC, Ferrucci et al. (2019) at the cerebellum, Ciechanski et al. (2017) at the M1, Hui et al. (2024) at the mPFC, Shahbazi et al. (2024) at the M1 and dlPFC, Takeuchi et al. (2018) at the TPJ, and Yang et al. (2023) at the rVLPFC. Cathodal stimulation in the active group was applied in two studies: Beeli et al. (2008) at the r-dlPFC and Takeuchi et al. (2018) at the TPJ. The experimental group in five investigations (Beeli et al., 2008; Berger et al., 2024; Corrêa et al., 2023; Freire-Santos et al., 2025; Shahbazi et al., 2024) was designed to include a sham tDCS condition. For the control group, four studies included a no-tDCS condition (Berger et al., 2024; Corrêa et al., 2023; Freire-Santos et al., 2025; Shahbazi et al., 2024), while six studies used sham-tDCS (Bulteau et al., 2022; Ciechanski et al., 2017; Ferrucci et al., 2019; Hui et al., 2024; Takeuchi et al., 2018; Yang et al., 2023). DISCUSSION The combination of PTs and non-invasive neuromodulation tools is a new field of study that has already been effective in neurological and psychiatric populations (Cassani et al., 2020; van ’t Wout-Frank et al., 2024 ), but it is in its relative infancy in non-clinical populations. The reason behind this approach is that combining the power of VR applications with tDCS might boost the effectiveness of specific symptomatologies compared to the separated use. In several neurological and psychiatric disorders this new combined approach would seem to be effective in reducing several symptoms (pain, motor disorders, anxiety disorders, etc). In non-clinical populations we evaluated if this approach can be applied to stimulate cognitive resources, boosting emotional control and general skills. What clearly emerged from this systematic review was that a small number of studies have been conducted employing this combination with respect to the separated employment and that in the majority of studies significant positive effects were detected. Cognitive abilities (attention), emotional control (impulsivity, anxiety, skin conductance) and specific skills (motor coordination medical abilities) are the three main behavioral domains that benefited from the combined employment of tDCS and VR systems. Otherwise, this approach did not produce significant effects with respect to the separated employment in other behavioral domains or cognitive abilities (i.e. cybersickness, spatial navigation). Positive effects combining VR + tDCS Using only VR applications to enhance attentional skills in healthy people show benefits for sustained attention, promoting alertness (Szczepocka et al., 2024) and improving sustained attention recovery through mindfulness-based VR exercises (Asati & Miyachi, 2019). Research on the use of tDCS to enhance attentional skills in healthy adults has often focused on specific attention-related cortical networks. For example, Wei et al. (2024) demonstrated how tDCS can alter sustained attention and vigilance by showing that network-based tDCS applied to attentional networks in healthy young people improving executive components of the Attention Network Test. Similarly, Miler et al. (2018) showed that when compared to sham stimulation, 20 minutes of anodal tDCS across the dlPFC improved executive attention ability in healthy participants. Combining tDCS and VR techniques, Yang et al. (2023) found significant gains in perceived attention, accuracy, and reaction speed in anodal tDCS over rVLPFC and VR with respect to sham tDCS. Again, Coffman et al. (2012) showed that tDCS stimulation with 2.0 mA, in conjunction with VR, produced better visual attention in comparison with tDCS stimulation with 1.0 mA. Otherwise, Clark et al. (2012) discovered that anodal tDCS combined with a VR-based target detection task boosted discovery-learning with respect to low-current tDCS. What clearly emerged from these studies was that the combination (tDCS+VR) seems to have more substantial and powerful effects on vigilance than either tDCS or VR alone. Compared to interventions using tDCS or VR separately, the combination appears to produce stronger and more robust effects on vigilance, sustained attention, and task performance, highlighting the potential of multimodal approaches for cognitive enhancement in non-clinical populations. It’s interesting to note that while gains in attentional performance are reported in both single-modality studies (tDCS or VR alone) and combined tDCS-VR protocols, the effects seem to be more significant and consistent in the multimodal therapies. This implies that VR and tDCS may work in concert to improve attentional outcomes beyond what would be possible with each intervention alone, with VR offering immersive cognitive engagement and tDCS altering neuronal excitability. Simultaneously, the single-modality investigations demonstrated that VR and tDCS can both successfully target attentional networks on their own, suggesting that these methods share an underlying mechanism of attention modulation. As concerns emotional control, VR-mediated approaches as well as tDCS have been demonstrated to be effective in reducing impulsive attitudes. For instance the use of VRET methods (Roncero et al., 2025) has been shown to produce statistically significant reductions in impulsivity ( p< 0.001) compared with passive control groups or those receiving conventional therapies, suggesting that VR constitutes an effective intervention for enhancing individuals’ inhibitory behavioural control. It has also been demonstrated that anodal tDCS stimulation over the orbitofrontal cortex enhances cognitive impulse control and decision-making ability (Ouellet et al., 2015), while anodal stimulation of the right DLPFC can modify inhibitory control skills in tasks measuring reaction time (Friehs & Frings, 2019). On the other hand, in clinical populations, the combined montage of left-cathodal and right-anodal stimulation of the DLPFC seems to have the opposite effect, making people with substance-use disorders more impulsive (Jiang et al., 2022). Compared to anodal tDCS and sham tDCS, the combination of VR and cathodal tDCS over the dlPFC resulted in improved impulsive behavior control (Beeli et al., 2008), which correlated with vegetative nervous system’s reactivity (SCR measures). As concerns anxiety level, several studies demonstrated the effectiveness of the VRET approach, which induces significant improvement similar to in vivo exposure (Wechsler et al., 2019). tDCS over mPFC improves or speeds up the effectiveness of in vivo exposure-based treatments (Adams et al., 2021; Cobb et al., 2021; van’t Wout-Frank et al., 2019). Hui et al. (2024) found a much larger effect than VRET alone when they combined anodal tDCS over the mPFC with VRET. Finally, as concerns the effect of PTs and neuromodulation tools for influencing skin conductance conflicting results have been reported. In particular, Costa et al. (2020) found reductions in electrodermal activity after meditation in a nature-inspired VR environment, while Cosme and Wiens (2015) did not find significant differences in SCR between experienced meditators and novices in response to emotional stimuli. Similarly, several studies have focused on the efficacy of anodal tDCS over the IFG in modulating physiological stress responses as indexed by SCR, observing a significant reduction in SCR during an emotional-threat task (Hart-Pomerantz et al., 2025). On the other hand, the study by Freire-Santos et al. (2025) showed that combining VR-FM with anodal tDCS over the dlPFC resulted in a larger reduction in SCR compared to VR-MW with sham tDCS, thus indicating that the combination of the two approaches has shown substantial effects. Regarding motor function, some research indicates that VR improves EHC and eye-body coordination in kids and teenagers (Caro et al. 2017, Ma & Qu, 2016). According to recent research, anodal tDCS across the M1 region accelerates the acquisition of new skills (Kunaratnam et al., 2022). This evidence disagrees with findings reported by Shahbazi et al.(2024), who found no differences between the combined approach between the VR and tDCS over the M1 with respect to the VR method alone for promoting motor abilities. Negative effects combining VR + tDCS The combination of VR+tDCS tools could get unsuccessful data in specific domains (see Figure 2b). Berger et al. (2024) found a number of concurrent elements that contribute to the failure of using combined tDCS at dlPFC and VR on cybersickness. The lack of significant outcome may be dependent on the fact that they did not target the neurovestibular circuits (vestibular apparatus, brainstem, cerebellum, thalamus, vestibular cortex, limbic/autonomic systems) that cause cybersickness. Second, placebo-induced expectation effects may have diminished participants’ capacity to self-regulate brain activity. Furthermore, individual variations in cybersickness susceptibility—especially the higher susceptibility seen in women—probably increased discomfort and obscured any possible advantages of stimulation. Lastly, the minor benefits of tDCS may have been ”overridden” by the complexity and intensity of the VR environment (a forest setting) during the neurofeedback training task, which imposes a high sensory load. Takeuchi et al. (2018) also tried employing tDCS applied to the right temporo-parietal region, which is important for balance and spatial orientation, to lessen cybersickness (discomfort and disorientation in VR). These authors found that anodal stimulation enhanced postural stability during VR exposure and decreased symptoms compared to the sham group. The stimulation had a beneficial effect in this trial, in contrast to many others where tDCS did not yield significant results when combined with VR. However, the employment of a single-session design and small sample number precluded between-group analyses. According to Correa et al. (2023), tDCS with video game training did not improve postural balance in older women more than video game training alone. The primary cause of this result, according to the authors, was a ceiling effect: the video game program on its own showed adequate efficacy in improving balance, which decreased the possibility of finding additional effects from the addition of tDCS. Additionally, the stimulation may not have been appropriately directed towards the brain regions more directly involved in postural control because it focused on the dorsolateral prefrontal cortex. The sample’s limited clinical vulnerability is another potential contributing factor. The participants were older women who lived in the community rather than people with severe motor impairments, so their margin for improvement was constrained. In conclusion, the combination of these elements seems to be the cause of the combined intervention’s failure. Bulteau et al. (2022) examined the lack of impact on psychological outcomes and found that tDCS administered to the vmPFC did not improve the therapeutic effects of VR on anxiety or discomfort associated with height. The tDCS stimulation may not have been strong enough or specifically focused to regulate the cortical regions linked to acrophobia (such as the insula and parietal regions involved in visuo-vestibular processing). Furthermore, as baseline symptoms were relatively low, the selection of healthy individuals with just mild types of visual intolerance may have limited the detection of any clinically significant effect. Additionally, the authors hypothesized that VR itself would have a ceiling effect: immersive exposure alone appeared to be adequate in lowering anxiety and boosting familiarity with heights, making it challenging to identify any further advantages from tDCS. In conclusion, the study did not show a clear benefit of brain stimulation over VR exposure alone, despite establishing the viability and safety of combining VR and tDCS. Ferrucci et al. (2019) found multiple possible explanations for the combined failure of tDCS and VR in their investigation of spatial navigation abilities. Since allocentric/egocentric processing and spatial navigation involve more complex neural circuits (like the hippocampus) that are not directly stimulated, the cerebellum may not be the best target for modulating the retrieval phase of spatial mapping in VR. Additionally, cerebellar tDCS is still poorly characterized in terms of stimulation parameters (electrode montage, intensity, and duration). Additionally, the chance to alter spatial learning in real time may have been diminished because stimulation was given before the retrieval phase rather than during active navigation. LIMITLESS AND FUTURE RESEARCH The evidence reviewed in this paper suggests that the combined use of tDCS and VR holds promise for enhancing attentional processes and strengthening emotional-regulation mechanisms in healthy individuals. Although the limited amount of existing studies, converging positive results, specifically in tasks involving sustained attention, inhibitory control, and physiological indices of emotional reactivity, indicates that tDCS-VR integration may produce synergistic effects beyond those obtained by each modality alone. However, it remains to be an improved theoretical basis for choosing the best brain region to stimulate with defined parameters. Indeed, tDCS’s effects may depend on the stimulation parameters (i.e., stimulation target, duration, current density and the use of offline or online protocols), the applied measures and participants’ characteristics (Teti Mayer et al., 2020). Given the high level of methodological quality among the considered studies (as highlighted by Risk of Bias assessment) and the low variability in stimulation site selection (predominantly targeting prefrontal regions) future research should extend and consolidate the above findings by developing and validating VR scenarios specifically designed for cognitive enhancement (sustained and selective attention) and emotion-related outcomes (inhibitory control, impulsive responding). These steps will be essential to determine if the combination of tDCS-VR approach can evolve into a reliable, scalable and ecologically valid tool for cognitive and emotional enhancement in non clinical population. 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Authors Affiliations Chiara Milasi 0009-0007-8532-4563 Institute of bioimaging and complex biological systems (IBSBC) National Research Council of Italy (CNR View all articles by this author Maria Grazia Maggio IRCCS Centro Neurolesi Bonino Pulejo View all articles by this author Giuseppe Perrotti Institute of bioimaging and complex biological systems (IBSBC) National Research Council of Italy (CNR View all articles by this author Paola Barbuto Universita degli Studi Magna Graecia di Catanzaro View all articles by this author Marina Barberio Universita degli Studi Magna Graecia di Catanzaro View all articles by this author Alfredo Albertini Universita degli Studi Magna Graecia di Catanzaro View all articles by this author Nicola Tallarico Universita degli Studi Magna Graecia di Catanzaro View all articles by this author Federico Rocca Institute of bioimaging and complex biological systems (IBSBC) National Research Council of Italy (CNR View all articles by this author Marianna Contrada Istituto S Anna Unita Gravi Cerebrolesioni View all articles by this author Francesca Gallivanone Institute of bioimaging and complex biological systems (IBSBC) National Research Council of Italy (CNR View all articles by this author Andrea Gaggioli Universita Cattolica del Sacro Cuore Dipartimento di Psicologia View all articles by this author Rocco Salvatore Calabrò IRCCS Centro Neurolesi Bonino Pulejo View all articles by this author Cristina Segura-Garcia Universita degli studi Magna Graecia di Catanzaro Dipartimento di Scienze della Salute View all articles by this author Domenico Bosco Azienda Ospedaliero Universitaria Renato Dulbecco di Catanzaro View all articles by this author Antonio Cerasa 0000-0002-8022-4770 [email protected] Institute of bioimaging and complex biological systems (IBSBC) National Research Council of Italy (CNR View all articles by this author Metrics & Citations Metrics Article Usage 488 views 106 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Chiara Milasi, Maria Grazia Maggio, Giuseppe Perrotti, et al. Boosting brain functions combining tDCS with virtual reality: a systematic review in a healthy population. Authorea . 09 January 2026. DOI: https://doi.org/10.22541/au.176794215.54896385/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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