Impact of transcranial direct current stimulation on physical performance, fatigue resistance, perceptual and physiological responses during high-intensity functional training

Impact of transcranial direct current stimulation on physical performance, fatigue resistance, perceptual and physiological responses during high-intensity functional training | 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 Research Article Impact of transcranial direct current stimulation on physical performance, fatigue resistance, perceptual and physiological responses during high-intensity functional training Maicon Teixeira de Almeida, Carla Christina Ade Caldas, Raquel Carvalho Castiglione, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9317035/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background High-intensity functional training (HIFT) involves complex multimodal demands in which performance depends on both central and peripheral fatigue. Transcranial direct current stimulation (tDCS) has emerged as a non-invasive neuromodulatory strategy capable of enhancing cortical excitability and influencing exercise outcomes. However, its effects during high-intensity, non-cyclical exercise such as HIFT remain unclear. This study evaluated the impact of tDCS on physical performance, fatigue resistance, and perceptual and physiological responses during HIFT. Methods Thirteen male HIFT-trained participants completed a randomized, crossover, sham-controlled study under three experimental conditions: control (no stimulation), sham, and anodal tDCS. Each session consisted of four rounds of HIFT, including thrusters, box jumps, and power cleans, performed under standardized conditions. During all HIFT sessions performance (repetitions), fatigue index (%FI), rate of perceived exertion (RPE), visual analog scale (VAS), blood lactate (BLC), heart rate (HR), and training impulse (TRIMP) were measured. Data were analyzed using repeated-measures analysis of variance or non-parametric equivalents, with post hoc comparisons when appropriate. Statistical significance was set at p < 0.05. Results Anodal tDCS significantly increased the number of repetitions compared to both control (239.8 ± 22.2 vs. 219.0 ± 22.4) and sham (228.0 ± 20.5) conditions (p < 0.0001). The fatigue index was significantly lower in the anodal condition compared to both sham and control (p < 0.05), indicating enhanced fatigue resistance. Perceptual responses were attenuated, with reduced perceived exertion (7.9 ± 0.6 vs. 8.8 ± 0.6) and muscle pain scores (7.4 ± 1.1 vs. 8.7 ± 0.8) compared to control (p < 0.0001). Physiologically, anodal tDCS resulted in higher blood lactate concentrations (14.5 ± 1.7 mM vs. 11.5 ± 1.2 mM), alongside reductions in maximum heart rate (181.1 ± 5.0 vs. 186.0 ± 5.7 bpm) and training impulse (63.3 ± 7.8 vs. 72.9 ± 8.9) compared to control (p < 0.0001). Conclusion Anodal tDCS enhances performance and fatigue resistance during HIFT while reducing perceptual and cardiovascular strain. These findings suggest that tDCS may serve as an effective non-pharmacological ergogenic strategy to optimize performance and modulate internal load during high-intensity multimodal exercise. Transcranial direct current stimulation high-intensity functional training exercise performance fatigue resistance central fatigue neuromodulation perceived exertion lactate heart rate training load Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction High-intensity physical training is associated with the development of mechanisms that limit physical performance through central and peripheral influences [ 1 , 2 ]. Although nutritional ergogenic aids have been extensively investigated, their effectiveness is variable and may be associated with adverse effects, highlighting the need for alternative non-pharmacological strategies [ 3 , 4 ]. Transcranial direct current stimulation (tDCS) has emerged as a neuromodulatory technique capable of modulating cortical excitability and influencing performance-related outcomes [ 5 , 6 ]. However, its effects on exercise performance are generally modest and dependent on stimulation parameters, including cortical target, electrode montage, and exercise modality [ 7 , 8 ]. In addition, findings remain inconsistent, particularly in complex and multimodal exercise contexts. High-intensity functional training (HIFT) is characterized by varied functional movements performed at high intensity, either in short bouts aimed at maximizing power output or in resistance-based formats targeting the highest number of repetitions within a predefined time, with the goal of improving both cardiorespiratory and muscular endurance [ 9 , 10 ]. This training approach aims to optimize performance across multiple domains, including cardiorespiratory endurance, muscular endurance, strength, flexibility, power, speed, coordination, and agility. Previous studies on HIFT have primarily focused on chronic adaptations and physiological responses to specific exercise protocols [ 11 ]. In addition to its metabolic and neuromuscular demands, HIFT involves cognitive and perceptual components, such as decision-making under fatigue, pacing regulation, and tolerance to discomfort. These characteristics suggest that performance in HIFT may be influenced not only by peripheral factors but also by central mechanisms. A recent study by our group [ 12 ] showed that β-alanine supplementation improved localized muscular resistance during HIFT; however, its use has been criticized due to side effects such as paresthesia [ 13 ]. Therefore, alternative strategies targeting central mechanisms without pharmacological intervention may be relevant in this context. The dorsolateral prefrontal cortex (DLPFC) is involved in executive function, decision-making, and regulation of perceived effort during exercise, influencing pacing strategies and fatigue tolerance [ 14 , 15 ]. Although tDCS has been studied in cyclic and isolated exercise modalities, its effects in high-intensity, non-cyclical, and multimodal exercise formats such as HIFT remain poorly understood. Training load in HIFT is commonly monitored using internal parameters, including rate of perceived exertion (RPE), visual analogue scale (VAS), blood lactate concentration (BLC), heart rate (HR), and training impulse (TRIMP) [ 16 , 17 ]. While these variables are associated with performance and internal load control, to date, no study has simultaneously investigated the effects of tDCS on both performance outcomes and internal load parameters during high-intensity functional training. Understanding these effects is essential to clarify the role of central neuromodulation in complex, high-intensity exercise and to support the development of effective non-pharmacological strategies to enhance performance. Therefore, this study aimed to evaluate the impact of tDCS on physical performance, fatigue resistance, and internal load parameters (RPE, LOAD, VAS, BLC, HR, and TRIMP) during high-intensity functional training. We hypothesized that anodal tDCS applied over the left DLPFC would improve performance (total repetitions), reduce fatigue index, and attenuate perceptual responses, potentially through modulation of central fatigue. Materials and Methods Participants and Ethical Standards Thirteen healthy male participants engaged in high-intensity functional training (HIFT) for at least two years volunteered for this study. An a priori sample size estimation was conducted using G*Power software (version 3.1.9.7 for Windows), assuming a moderate-to-large effect size (f = 0.40), an alpha level of 0.05, and statistical power (1 − β) of 0.80, indicating a minimum sample size of 12 participants. Inclusion criteria were age between 18 and 40 years, regular engagement in HIFT training, and classification as low cardiovascular risk according to the American College of Sports Medicine guidelines [ 18 ]. Exclusion criteria included musculoskeletal injury, smoking, regular alcohol consumption, chronic disease diagnosis, and contraindications to transcranial direct current stimulation (tDCS), such as history of epilepsy, neurological disorders, or presence of implanted electronic devices. All participants were informed about the experimental procedures and provided written informed consent prior to participation. The experimental protocol followed the principles outlined in the Declaration of Helsinki for research involving human participants. The study protocol was approved by the Research Ethics Committee of Universidade Salgado de Oliveira, Brazil (approval number: CAAE 02469418.2.0000.5289). Experimental Procedure This study was designed as a randomized, sham-controlled, crossover trial aimed at evaluating the effects of transcranial direct current stimulation (tDCS) on physical performance, fatigue resistance, and internal load during high-intensity functional training. The participants were instructed to attend the training center on three separate occasions (Fig. 1 ). All experimental procedures were conducted at a certified high-intensity functional training facility under controlled laboratory conditions. At the first visit, participants were informed about all experimental procedures, signed an informed consent form, and underwent anthropometric and physical assessments. Each participant underwent three HIFT sessions under different experimental conditions: control (no stimulation), sham tDCS, and anodal tDCS. A randomized crossover design was adopted using a computer-generated randomization sequence ( www.randomizer.org ), ensuring that the order of conditions was counterbalanced across participants. The interval between sessions was standardized to 72 h to minimize potential carryover and fatigue effects. Participants were blinded to the stimulation condition, and the sham protocol was designed to mimic the sensory experience of active stimulation. Outcome assessors were not involved in the stimulation procedures. All sessions were conducted under controlled environmental conditions (temperature: 22–24°C; relative humidity: 50–60%). Participants were instructed to avoid caffeine, alcohol, and strenuous physical activity for at least 24 h prior to each session. Heart rate (HR) was continuously recorded throughout the sessions to determine the mean and maximum HR, as well as the training impulse (TRIMP). Each HIFT session consisted of four 4-min exercise bouts separated by 2-min recovery intervals. The rate of perceived exertion (RPE), visual analog scale (VAS) for muscle pain, and blood lactate concentration (BLC) were measured at the end of each exercise bout. Anthropometric and Physical Assessments For anthropometric measurements, body mass and height were recorded using an analog scale with 100 g precision and a stadiometer with 1.0 cm increments (Filizola, Brazil). Body mass index (BMI) was calculated as the ratio of body mass (kg) to the square of height (m²). Body density was estimated from the sum of three skinfold measurements, as recommended by Jackson and Pollock for males (pectoral, subscapular, and triceps), and body fat percentage was subsequently calculated using Siri’s equation. All measurements were performed in triplicate by the same trained evaluator, and the mean value was used for analysis. Skinfold thickness was measured using a 5 MHz ultrasound device (Body Metrix Pro; IntelaMetrix, Concord, CA, USA) that emits high-frequency waves to distinguish tissue interfaces within the layers. Measurements were taken by positioning the device perpendicular to the specified points for approximately five seconds. Cardiopulmonary exercise testing (CET) was performed using a rowing ergometer (Concept II, Inc., Morrisville, VT, USA). After a five-minute warm-up period, the participants rowed at a self-selected pace for five minutes at a consistent power of 75 W. Thereafter, the power was increased by 25 W every minute until volitional exhaustion. The rowing ergometer was chosen because of the participants’ familiarity with it and the established validity of the incremental protocol used [ 19 ]. The test was terminated based on volitional exhaustion, inability to maintain cadence, or a rating of perceived exertion (RPE) ≥ 9. Throughout the test, oxygen consumption (VO₂) was continuously monitored using a portable device (PNOE, ENDO Medical, Palo Alto, CA, USA) with a breath-by-breath sampling frequency. The maximum oxygen consumption (VO₂ max) was determined as the highest recorded VO₂ value. Prior to testing, the equipment was calibrated in accordance with the manufacturer's guidelines. High Intensity Interval Training Protocol and Transcranial Direct Current Stimulation (tDCS) Performance assessment during HIFT consisted of four different rounds of exercises, each interspersed with a 2-min rest period [ 20 ]. In detail, the rounds consisted of 4 min of as many rounds as possible (AMRAP) of five thrusters (60 kg for men and 43 kg for women) and 10 box jumps (round 1); 4 min of 10 power cleans (60 kg for men and 43 kg for women) and 20 pull-ups (round 2); 4 min of 15 shoulder to overhead (60 kg for men and 43 kg for women) and 30 toes to bar (round 3); and 4 min of 20 row calories and 40 wall ball shots (9 kg for men and 6 kg for women) (round 4). Physical performance was quantified as the total number of repetitions completed across all four rounds. Although absolute loads were used to reflect ecological validity and real-world HIFT practices, this approach may introduce inter-individual variability in relative intensity, which is acknowledged as a limitation. To calculate the fatigue index percentage (%FI), each 4-min round was divided into 1-min windows (four 1-min windows per AMRAP), resulting in a total of 16 windows. The number of repetitions performed in each window was quantified using video recordings (iPhone 14 Pro Max, 4 K at 60 fps; Apple Inc., Cupertino, CA, USA). The %FI was calculated using the following equation: %FI = [(max repetitions-min repetitions) / max repetitions] × 100. To minimize external influences on performance, no verbal encouragement was provided, and environmental stimuli (e.g., music) were standardized across all sessions. For anodal tDCS application, stimulation was delivered using a Striat device (Striat™, Ibramed, Amparo, SP, Brazil). The anodal electrode was positioned over the left DLPFC, and the cathodal electrode (reference) was positioned over the right supraorbital cortex, according to the international 10–20 EEG system [ 21 ]. The stimulus was applied at an intensity of 2 mA for a duration of 20 min [ 17 ]. In the sham condition, electrode placement was identical to that in the anodal condition; however, stimulation was applied for only 30 s and then turned off, whereas participants remained with the electrodes in place for the full 20 min period [ 22 ]. Rating of Perceived Exertion and Visual Analog Scales for Resistance Exercise RPE was assessed using the OMNI-RES scale, which is specifically designed for resistance exercise and includes verbal and pictorial descriptors ranging from 0 (extremely easy) to 10 (extremely difficult). Prior to data collection, all participants were familiarized with the use of the RPE scale during a preliminary session to ensure the reliability and consistency of responses. Session load (LOAD) was calculated using the session RPE method based on the CR-10 scale, obtained at the end of each session, and multiplied by the total session duration, following established procedures. The visual analog scale (VAS) was used to assess muscle pain, with values ranging from 0 (no pain) to 10 (worst possible pain). The participants were also familiarized with the VAS prior to testing to ensure proper understanding and reproducibility of the measurements [ 12 ]. Blood Lactate Measurement Blood lactate concentration (BLC) was measured using a portable lactate analyzer (Accutrend® Plus System; Roche Bioelectronics, Basel, Switzerland), which has been previously validated for use in exercise settings. Capillary blood samples were collected from the fingertips immediately after each exercise bout. Although lactate was not measured at its peak time point, the same collection timing was applied across all experimental conditions to ensure internal validity and allow for consistent comparisons between conditions. Heart Rate and Training Impulse (TRIMP) Heart rate (HR) was continuously monitored throughout all HIFT sessions using a real-time monitoring system (Firstbeat Technologies Ltd., Jyväskylä, Finland), which has been validated for exercise monitoring. The mean HR and maximum HR values were extracted for each exercise bout. TRIMP was calculated using the Banister method, which incorporates exercise duration and heart rate response to quantify the internal training load [ 10 , 12 , 23 ]. Statistical Analysis All statistical analyses were conducted utilizing GraphPad Prism version 8.4.2 (GraphPad Software, San Diego, CA, USA). The data are expressed as mean ± standard deviation (SD). The normality of data distribution was evaluated using the Shapiro–Wilk test, while sphericity was assessed via Mauchly’s test. In instances where the assumption of sphericity was violated, Greenhouse–Geisser corrections were applied. Comparisons among the experimental conditions (control, sham, and anodal) were executed using a one-factor repeated-measures analysis of variance (ANOVA), with condition considered as a within-subject factor. This methodological choice was informed by the crossover design, wherein the same participants were subjected to all experimental conditions. Post hoc analyses were performed using Tukey’s test for parametric data. For variables that did not satisfy normality assumptions, the Friedman test followed by appropriate post hoc comparisons was employed. The effect size was calculated using partial eta squared (η²p), with interpretations as small (0.01–0.06), medium (0.06–0.14), and large (> 0.14). The criterion for statistical significance was set at p < 0.05. Results Sample Characterization Physical characteristics of the participants are listed in Table 1 . Table 1 Physical characteristics of the Participants. Variables Mean ± SD Age (years) 27.3 ± 4.4 Body mass (kg) 85.5 ± 6.5 Height (cm) 176.7 ± 3.8 Body mass index (kg/m2) 27.3 ± 3.1 Body fat (%) 8.7 ± 0.9 Max Power (Watts) 359.6 ± 49.5 Max HR (bpm) 192.2 ± 7.9 VO 2 max (ml.kg.min-1) 55.8 ± 5.2 Max Power = maximum power production. Max HR = maximum heart rate. VO 2 max = maximum oxygen consumption. Physical Performance and Fatigue Index Percentage As shown in Fig. 2A, both the sham (228.0 ± 20.5 repetitions; F 2,24 = 62.34, P < 0.0001) and anodal (239.8 ± 22.2 repetitions; F 2,24 = 62.34, P < 0.0001) conditions showed significantly more repetitions than the control (219.0 ± 22.4), compared to the control condition. Notably, the Anodal condition produced significantly more repetitions than the sham condition ( F 2,24 = 62.34, P < 0.0001). Figure 2 Effects of a-tDCS on Performance and Fatigue Index (%FI). Left: Number of repetitions in control, sham, and a-tDCS groups. a-tDCS showed significantly more repetitions than both control ( *** P = 0.001) and sham ( ### P < 0.001); sham also exceeded control ( *** P = 0.001). Right: FI (%) across groups. a-tDCS had significantly lower %IF than control (*** P = 0.001) and sham ( # P = 0.05); Sham was also lower than control ( * P = 0.05). Figure 2B shows that both the Sham and Anodal conditions resulted in a lower fatigue index (%FI) than the control ( F 2,24 = 84.53; P = 0.002 and P < 0.0001, respectively). Furthermore, the anodal group exhibited a significantly lower fatigue index percentage (%FI) than the sham group ( F 2,24 = 84.53; P < 0.0001). Perceptual Effort Scales and LOAD Figure 3 Effects of a-tDCS on perceived exertion and training load. (A) Rate of Perceived Exertion (RPE, CR-10 scale); (B) Visual Analogue Scale (VAS); (C) Training Load (RPE × time). Symbols indicate significant differences: * P = 0.01, ** P = 0.001, *** P = 0.001 vs. control; ## P = 0.02 vs. sham. In Fig. 3 A, the control presented a mean RPE of 8.8 ± 0.6 a.u., while the sham presented a RPE of 8.3 ± 0.5 a.u. ( Z = 1.47, P = 0.42). On the other hand, the anodal group presented a lower mean RPE (7.9 ± 0.6 a.u.), which differed significantly from both the sham ( Z = 2.65, P = 0.02) and the control ( Z = 4.12, P = 0.0001) groups. Similarly, as shown in Fig. 3 B, the control group had a mean VAS score of 8.7 ± 0.8 a.u. The sham group exhibited a significantly lower VAS score (7.9 ± 0.9 a.u.; Z = 2.55, P = 0.03) compared to the control group. The anodal group showed a significantly lower mean VAS value (7.4 ± 1.1 a.u.) than the control group (Z = 4.22, P = 0.0001) but not compared to the sham group (Z = 1.67, P = 0.29). For LOAD (RPE × time), the results mirrored those of the RPE (Fig. 3 C). The control’s average LOAD was 140.2 ± 9.0, while sham’s was 133.2 ± 5.3 ( Z = 1.47, P = 0.42). Anodal exhibited the lowest value (128.1 ± 12.1), significantly lower than both control ( Z = 4.12, P = 0.0001) and sham ( Z = 2.65, P = 0.02) groups. Physiological Parameters Figure 4 Physiological responses in control, sham, and a-tDCS groups during HIFT. (A) Blood lactate (mM): *** P = 0.0001 vs. control; # P = 0.01 vs. sham. (B) Max HR (bpm): *** P = 0.0001 vs. control; ### P = 0.0001 vs. sham. (C) Mean HR (bpm): *** P = 0.0001 vs. control; ###p < 0.0001 vs. sham. (D) TRIMP (a.u.): *** P < 0.0001 vs. control; ## P = 0.01 vs. sham. Blood lactate was significantly higher in the sham (13.3 ± 1.1 mM; F 1,15 = 15.18, P = 0.008) and a-tDCS (14.5 ± 1.7 mM; F 1,15 = 15.18, P = 0.003) groups than in the control group (11.5 ± 1.2 mM), with Anodal also significantly higher than sham ( F 1,15 = 15.18; P = 0.01) (Fig. 4 A). Regarding maximum HR (Fig. 4 B), the sham group reduced max HR (183.8 ± 5.2 bpm; F 1,17 = 88.78; P = 0.0001) compared to the control group (186.0 ± 5.7 bpm). a-tDCS stimulation showed a further reduction (181.1 ± 5.0 bpm), which was significantly lower than that in the control and sham groups ( F 1,17 = 88.78, P = 0.0001). The mean HR (Fig. 4 C) followed the same trend: Sham (157.4 ± 3.2 bpm; F 1,14 = 56.50, P = 0.0001) was lower than control (161.2 ± 2.7 bpm), and a-tDCS (153.4 ± 4.9 bpm) was significantly lower than both ( F 1,14 = 56.50, P = 0.0001). ​For TRIMP (Fig. 4 D), the sham group had lower values (68.0 ± 8.7 a.u) than the control group (72.9 ± 8.9 a.u; F 1,20 = 89.13, P = 0.0001). Anodal displayed the lowest TRIMP (63.3 ± 7.8 a.u), significantly reduced compared to both Sham ( F 1,20 = 89.13, P = 0.002) and Control ( F 1,20 = 89.13​, P = 0.0001). In summary, both sham and anodal conditions resulted in significant reductions in blood lactate, maximum HR, mean HR, and TRIMP compared with the control, with anodal conditions producing the most pronounced effects across all variables. Effect Size The effect sizes from the One-Way ANOVA are shown in Table 2 . Table 2 Comparisons related to the effect size of the One-Way ANOVA were attributed to the partial eta squared (η 2 p). Variables Control Sham Anodal η2p Repetitions 219.0 ± 22.4 228.0 ± 20.5 239.8 ± 22.2 0.14 (Large) % FI 67.7 ± 4.6 64.8 ± 3.9 57.9 ± 2.6 0.56 (Large) RPE (a.u) 8.8 ± 0.6 8.3 ± 0.3 8.0 ± 0.8 0.24 (Large) VAS (a.u) 8.7 ± 0.9 7.9 ± 0.9 7.4 ± 1.1 0.25 (Large) LOAD (a.u) 140.2 ± 9.0 133.2 ± 5.3 128.1 ± 12.1 0.24 (Large) BLC (mM) 14.3 ± 1.6 12.9 ± 1.1 11.5 ± 1.8 0.39 (Large) Max HR (bpm) 185.9 ± 5.8 183.8 ± 5.3 181.1 ± 6.1 0.13 (Medium) Mean HR (bpm) 161.2 ± 2.8 157.8 ± 3.2 153.8 ± 5.0 0.41 (Large) TRIMP (a.u) 72.9 ± 9.0 68.0 ± 8.8 63.3 ± 7.9 0.19 (Large) %FI = fatigue index percentage. RPE = rate of perceived exertion. VAS = visual analogue scale. BLC = blood lactate concentration. Max HR = maximum heart rate. Mean HR = average heart rate. TRIMP = training impulse. Anodal stimulation exhibited significant impacts across various physical performance and fatigue measures, with large partial eta squared values for all outcomes except maximum HR, which showed a medium effect. These results further support the efficacy of both interventions, with Anodal demonstrating the most substantial overall benefits. Pearson Correlation Coefficients Finally, Table 3 presents the Pearson correlation coefficients between performance variables and physiological measures in the anodal condition. %FI showed a strong, significant correlation with the number of repetitions (r = 0.8; P = 0.001), highlighting a close relationship between these parameters. The VAS and TRIMP scores exhibited moderate but significant correlations with repetitions (r = 0.5, P = 0.02; r = 0.5; P = 0.04, respectively). Additionally, TRIMP was strongly correlated with %IF (r = 0.7; P = 0.005), suggesting that as fatigue resistance improved, the overall training impulse was similarly affected. Table 3 Correlation between variables related to physical performance with RPE, VAS, Lactate, HR max, HR mean, and TRIMP in a-tDCS. Variables Repetitions RPE (a.u) VAS (a.u) LOAD (a.u) BLC (mM) HR max (bpm) HR mean (bpm) TRIMP (a.u) Repetitions ------- -0.11 P = 0.39 0.55* P = 0.04 -0.26 P = 0.39 -0.34 P = 0.26 -0.17 P = 0.57 0.28 P = 0.35 0.54* P = 0.04 %FI 0.60* P = 0.04 -0.42 P = 0.15 0.34 P = 0.90 -0.42 P = 0.15 -0.04 P = 0.90 0.31 P = 0.29 0.78* P = 0.002 0.61* P = 0.03 %FI = fatigue index percentage. RPE = rate of perceived exertion. VAS = visual analogue scale. BLC = blood lactate concentration. Max HR = maximum heart rate. Mean HR = average heart rate. TRIMP = training impulse. Discussion This study evaluated the impact of transcranial direct current stimulation (tDCS) on various key physiological and perceptual parameters during high-intensity functional training (HIFT), including physical performance, fatigue index percentage (%FI), rate of perceived exertion (RPE), training LOAD (RPE × time), muscle pain via the visual analogue scale (VAS), blood lactate concentration (BLC), heart rate (HR), and training impulse (TRIMP). The findings revealed significant differences between experimental conditions, with the Anodal stimulation condition yielding the most pronounced enhancements in physical performance, fatigue resistance, perceptual markers, and physiological internal load. Although previous research has shown limited improvements in performance with tDCS during short-duration maximal efforts, such as sprinting [ 24 ], various studies have demonstrated significant enhancements in performance during long-duration cyclical modalities [ 7 , 25 ]. These findings align with the outcomes of the present study, where both the Sham and Anodal conditions resulted in a significantly greater number of repetitions than the control group. Notably, the Anodal condition produced a significantly higher number of repetitions than the sham condition, which may indicate a more robust ergogenic effect when employing anodal stimulation. This is consistent with the literature suggesting that tDCS can enhance physical performance through mechanisms involving increased cortical excitability and recruitment of additional muscle fibers within a motor unit [ 7 , 8 ]. Moreover, Angius et al. [ 14 ] investigated the effects of tDCS applied to the motor cortex on exercise-induced pain and endurance performance. Their study utilized a stimulation protocol comparable to that of the present investigation with 2 mA of anodal current for 20 min prior to exercise. They observed that anodal stimulation significantly reduced the perception of pain and prolonged the time to exhaustion (TTE) compared to both placebo and cathodal tDCS. These findings support the hypothesis that tDCS, as a non-invasive neuromodulatory technique, can modulate cortical excitability and, consequently, reduce the sensory perception of pain, thereby enhancing exercise tolerance and performance. In the current study, while both the Sham and Anodal conditions led to reductions in %FI, RPE, and VAS, the reductions were more substantial with anodal stimulation, reinforcing its superiority in modulating fatigue. The prefrontal cortex, particularly the lateral prefrontal cortex (LPFC), plays a key role in regulating decision-making and pacing during exhaustive exercise tasks, which is consistent with evidence showing reduced perception of effort and increased time to exhaustion following tDCS [ 25 ]. The LPFC integrates afferent physiological signals with motivational and emotional inputs from structures such as the anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC), thereby modulating behavioral responses such as acceleration, maintenance, or reduction in exercise intensity [ 14 ]. The present findings are further corroborated by research demonstrating that tDCS can reduce the perception of central fatigue. The proposed mechanisms involve tDCS-induced modulation of cortical excitability, which alters the processing and perception of nociceptive inputs. Stimulation of the LPFC may dampen the affective and cognitive components of pain, thereby decreasing the subjective discomfort associated with exhaustive physical activity. This modulation holds substantial promise as a non-pharmacological intervention for athletes seeking to enhance endurance and mitigate discomfort during high-intensity exercise without relying on analgesic medication [ 14 ]. ​Furthermore, beyond influencing cortical excitability, tDCS may affect perceived exertion through additional psychological mechanisms. Various bodily sensations can serve as psychological triggers that influence the interpretation of effort and fatigue ​during exercise [ 15 , 26 ]. The central nervous system, by integrating sensory feedback from muscles and joints, plays a pivotal role in the experience and regulation of central fatigue [ 27 ]. Consequently, applying anodal tDCS to areas such as the motor cortex and LPFC may offer potential benefits by not only enhancing motivation and performance but also attenuating perceptions of muscle pain and exertional discomfort [ 28 ]. In support of these assertions, a recent study conducted by our research group evaluated RPE, VAS, and BLC across two different HIFT protocols, each characterized by distinct neuromuscular and metabolic demands [ 12 ]. One protocol emphasized gymnastic movements with isometric contractions, whereas the other was characterized by dynamic contractions combined with cardiorespiratory exercises. The results indicated no significant differences in RPE between the protocols; however, the gymnastic method elicited significantly higher VAS and BLC levels, highlighting the importance of VAS as a sensitive marker of muscle discomfort and metabolic stress [ 12 ]. This observation underscores the relevance of using the VAS alongside other metrics when evaluating interventions such as tDCS that aim to attenuate fatigue-related sensations. Thus, the findings of the present study suggest that anodal tDCS may attenuate central and perceptual components of fatigue during muscular endurance tasks typical of HIFT, as evidenced by reductions in RPE and VAS, alongside increased blood lactate concentrations, which may reflect greater exercise tolerance and metabolic demand. Although the literature on the specific effects of tDCS on BLC is limited, Angius et al. [ 29 ] examined bilateral anodal stimulation at C3, C4, and F3 and found significant improvements in endurance performance, notably increased TTE, along with elevated BLC relative to the control. This is congruent with our observations, where anodal stimulation over the left dorsolateral prefrontal cortex and a reference cathodal electrode over the right supraorbital cortex resulted in enhanced muscular endurance, decreased %FI, and increased BLC in the Anodal condition compared to the control. The underlying rationale for these observations is grounded in the premise that anodal tDCS enhances cortical excitability, reduces perceived exertion and muscle pain, and improves inhibitory control, collectively enabling individuals to sustain high-intensity training stimuli for a longer duration, which in turn elevates BLC due to the increased metabolic demand. These adaptations are crucial for athletes engaged in sports requiring sustained efforts, as they suggest the potential of tDCS to augment training-induced physiological adaptations. Moreover, several studies have explored the broader impact of tDCS on cardiovascular parameters, including HR, TRIMP, and HRV [ 29 , 30 , 31 ]. HR serves as a fundamental indicator of cardiovascular strain and adaptation during exhaustive exercise, with max HR frequently used to define the cardiovascular performance ceiling. In the current study, sham stimulation resulted in a significant reduction in max HR compared to the Control, with Anodal stimulation producing an even greater reduction relative to both Sham and Control. These findings may suggest that tDCS, particularly anodal stimulation, is associated with altered cardiovascular responses during exercise, thereby reducing peak cardiovascular stress during exertion [ 32 ]. Consistent with these findings, Montenegro et al. [ 33 ] reported that anodal tDCS significantly modulates autonomic cardiac control, enhancing the parasympathetic influence and reducing sympathetic drive. These effects were associated with decreased HR and changes in autonomic markers, reflecting improved autonomic regulation and cardiovascular efficiency. Such modulation may confer protective cardiovascular benefits during sustained physical efforts and mitigate the risks associated with excessive sympathetic activation. Similarly, Okano et al. [ 32 ] demonstrated that tDCS may modulate the autonomic nervous system by reducing sympathetic and enhancing parasympathetic activity, resulting in improved physical performance during maximal exercise. Complementing these findings, Gu et al. [ 34 ] investigated high-definition tDCS and its effects on HR and HRV in healthy individuals, concluding that anodal tDCS reduced HR and favorably modulated HRV, reinforcing the role of tDCS in optimizing autonomic and cardiovascular control. Muniz-Pardos et al. [ 35 ] further examined the acute effects of tDCS on professional cyclists’ cardiovascular responses during TTE. Their results revealed that tDCS significantly reduced HR during exercise, which may suggest an adaptive physiological response that enhances the cardiovascular efficiency. A lower HR during exertion implies a reduction in cardiovascular strain, allowing for more sustainable high-intensity efforts, which is particularly advantageous for endurance athletes. Collectively, these findings elucidate how tDCS may influence autonomic function by attenuating sympathetic activity while enhancing parasympathetic tone, leading to a reduced HR during high-intensity exercise. This modulation may indicate a beneficial effect on cardiovascular efficiency and overall athletic performance. Understanding these mechanisms contributes substantially to our comprehension of how brain stimulation influences physiological responses during physical activity and how it can be harnessed to optimize endurance and training outcomes. Limitations This study has some limitations that should be considered. The relatively small sample size and inclusion of only male, trained participants limit the generalizability of the findings. The crossover design minimizes inter-individual variability; however, potential residual or placebo effects associated with sham stimulation cannot be fully excluded. Additionally, the study focused on acute responses, preventing conclusions about long-term adaptations to repeated tDCS application. Furthermore, no direct neurophysiological or autonomic measurements (e.g., cortical excitability or heart rate variability) were obtained, limiting mechanistic interpretation. Finally, the use of absolute loads in the HIFT protocol may have introduced variability in relative intensity among participants. Conclusion In conclusion, this study showed that anodal tDCS was associated with reductions in perceived exertion, muscle pain, mean and maximal HR, and TRIMP during HIFT. These findings suggest that anodal tDCS may enhance performance and modulate internal load during high-intensity functional training. The present results highlight the potential relevance of tDCS as a non-pharmacological strategy in high-intensity multimodal exercise, particularly for improving exercise tolerance and performance-related outcomes. However, further studies are needed to confirm these findings and to elucidate the underlying physiological and neurobiological mechanisms. Abbreviations tDCS Transcranial direct current stimulation HIFT High-intensity functional training FI Fatigue index RPE Rating of perceived exertion VAS Visual analog scale BLC Blood lactate concentration HR Heart rate TRIMP Training impulse LOAD Training load (RPE × time) DLPFC Dorsolateral prefrontal cortex LPFC Lateral prefrontal cortex ACC Anterior cingulate cortex OFC Orbitofrontal cortex TTE Time to exhaustion VO₂max Maximal oxygen consumption BMI Body mass index CET Cardiopulmonary exercise testing ANOVA Analysis of variance SD Standard deviation Declarations Ethics approval and consent to participate The study protocol was approved by the Research Ethics Committee of Universidade Salgado de Oliveira, Brazil (CAAE: 02469418.2.0000.5289). All procedures were conducted in accordance with the principles of the Declaration of Helsinki. All participants were informed about the aims, procedures, potential risks, and benefits of the study and provided written informed consent prior to participation. Clinical trial number Not applicable Consent for publication The manuscript does not contain any individual person’s data in any form, including individual details, images, or videos. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to privacy and confidentiality considerations involving human participants but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding Raquel Carvalho Castiglione (Grant No. E-26/204.411/2025) and Silvio Rodrigues Marques Neto (Grant No. E-26/204.447/2025) are fellows of the Young Scientist of Our State Program funded by the Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ), Brazil. Authors’ contributions MTA contributed to the study conception, data collection, data analysis, and drafting of the manuscript. CCAC contributed to data interpretation, critical revision of the manuscript, and intellectual content. RCC contributed to study supervision, interpretation of the findings, and critical revision of the manuscript. SRMN conceived and designed the study, supervised all stages of the research, contributed to data interpretation, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript. Acknowledgements The authors would like to thank the Box Experience Training Center for allowing the study to be conducted with its athletes and facilities. The authors also thank all participants for their time, commitment, and willingness to take part in the study. References Márquez G, Romero-Arenas S, Marín-Pagán C, Vera-Ibañez A, Del FernáNdez M, Taube W. Peripheral and central fatigue after high intensity resistance circuit training. Muscle Nerve. 2017;56(1):152–9. 10.1002/mus.25460 . O'Leary TJ, Collett J, Howells K, Morris MG. Endurance capacity and neuromuscular fatigue following high- vs moderate-intensity endurance training: A randomized trial. Scand J Med Sci Sports. 2017;27(12):1648–61. 10.1111/sms.12854 . Bonilla DA, Boullosa D, Del Coso J. Advances in nutrition and ergogenic aids for performance. Nutrients. 2023;15(10):2246. https://doi.org/10.3390/nu15102246 . Mabrey G, Koozehchian MS, Newton AT, Naderi A, Forbes SC, Haddad M. The Effect of Creatine Nitrate and Caffeine Individually or Combined on Exercise Performance and Cognitive Function: A Randomized, Crossover, Double-Blind, Placebo-Controlled Trial. Nutrients. 2024;16(6):766. 10.3390/nu16060766 . Polanía R, Paulus W, Nitsche MA. Modulating cortico-striatal and thalamo-cortical functional connectivity with transcranial direct current stimulation. Hum Brain Mapp. 2012;33(10):2499–508. 10.1002/hbm.21380 . Bonaiuto JJ, Bestmann S. Understanding nonlinear physiological and behavioral effects of tDCS. Prog Brain Res. 2015;222:75–103. https://doi:10.1016/bs.pbr.2015.06.013 . Machado DGDS, Unal G, Andrade SM, et al. Effect of transcranial direct current stimulation on exercise performance: A systematic review and meta-analysis. Brain Stimul. 2019;12(3):593–605. 10.1016/j.brs.2018.12.227 . Lattari E, Oliveira BRR, Monteiro Júnior RS, et al. Acute effects of single dose transcranial direct current stimulation on muscle strength: A systematic review and meta-analysis. PLoS ONE. 2018;13(12):e0209513. 10.1371/journal.pone.0209513 . Published 2018 Dec 26. Heinrich KM, Becker C, Carlisle T, et al. High-intensity functional training improves functional movement and body composition among cancer survivors: a pilot study. Eur J Cancer Care (Engl). 2015;24(6):812–7. 10.1111/ecc.12338 . Feito Y, Heinrich KM, Butcher SJ, Poston WSC. High-Intensity Functional Training (HIFT): Definition and Research Implications for Improved Fitness. Sports (Basel). 2018;6(3):76. 10.3390/sports6030076 . Drum SN, Bellovary BN, Jensen RL, Moore MT, Donath L. Perceived demands and postexercise physical dysfunction in CrossFit® compared to an ACSM based training session. J Sports Med Phys Fit. 2017;57(5):604–9. 10.23736/S0022-4707.16.06243-5 . Dos Santos DAA, Reis VMMR, Monteiro ER, Santos JM, Guimarães TT, de Figueiredo TC, Castiglione RC, Neto M, S. R. Comparison between acute effects of β-alanine supplementation on psychophysiological scales, blood lactate, training impulse and heart rate variability during high-intensity functional training. Cuad De Educación Y Desarrollo. 2023;15(5):4017–38. https://doi.org/10.55905/cuadv15n5-006 . Saunders B, Elliott-Sale K, Artioli GG, et al. β-alanine supplementation to improve exercise capacity and performance: a systematic review and meta-analysis. Br J Sports Med. 2017;51(8):658–69. 10.1136/bjsports-2016-096396 . Angius L, Hopker JG, Marcora SM, Mauger AR. The effect of transcranial direct current stimulation of the motor cortex on exercise-induced pain. Eur J Appl Physiol. 2015;115(11):2311–9. https://doi:10.1007/s00421-015-3212-y . Robertson CV, Marino FE. Last Word on Viewpoint: A role for the prefrontal cortex in exercise tolerance and termination. J Appl Physiol (1985). 2016;120(4):470. 10.1152/japplphysiol.01010.2015 . Peeling P, Binnie MJ, Goods PSR, Sim M, Burke LM. Evidence-Based Supplements for the Enhancement of Athletic Performance. Int J Sport Nutr Exerc Metab. 2018;28(2):178–87. 10.1123/ijsnem.2017-0343 . Lattari E, Vieira LAF, Oliveira BRR, et al. Effects of Transcranial Direct Current Stimulation With Caffeine Intake on Muscular Strength and Perceived Exertion. J Strength Cond Res. 2019;33(5):1237–43. 10.1519/JSC.0000000000003123 . Thompson PD, Arena R, Riebe D, Pescatello LS. New preparticipation health screening recommendations. In: Pescatello LS, Arena R, Riebe D, Thompson PD, editors. ACSM’s Guidelines for Exercise Testing and Prescription. 9th ed. Philadelphia: Lippincott Williams & Wilkins; 2013. pp. 18–38. Celik O, Koşar SN, Korkusuz F, Bozkurt M. Reliability and validity of the modified Conconi test on concept II rowing ergometers. J Strength Cond Res. 2005;19(4):871–7. 10.1519/R-15754.1 . Tibana RA, de Sousa Neto IV, Sousa NMF, et al. Local Muscle Endurance and Strength Had Strong Relationship with CrossFit ® Open 2020 in Amateur Athletes. Sports (Basel). 2021;9(7):98. 10.3390/sports9070098 . Published 2021 Jul 6. Klem GH, Lüders HO, Jasper HH, Elger C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalogr Clin Neurophysiol Suppl. 1999;52:3–6. Gandiga PC, Hummel FC, Cohen LG. Transcranial DC stimulation (tDCS): a tool for double-blind sham-controlled clinical studies in brain stimulation. Clin Neurophysiol. 2006;117(4):845–50. 10.1016/j.clinph.2005.12.003 . Foster C, Rodriguez-Marroyo JA, de Koning JJ. Monitoring Training Loads: The Past, the Present, and the Future. Int J Sports Physiol Perform. 2017;12(Suppl 2):S22–8. 10.1123/ijspp.2016-0388 . Alix-Fages C, Romero-Arenas S, Calderón-Nadal G, Jerez-Martínez A, Pareja-Blanco F, Colomer-Poveda D, et al. Transcranial direct current stimulation and repeated sprint ability: no effect on sprint performance or ratings of perceived exertion. J Sports Sci. 2022;40(5):569–78. https://doi:10.1080/17461391.2021.1883124 . Lattari E, de Oliveira BS, Oliveira BRR, de Mello Pedreiro RC, Machado S, Neto GAM. Effects of transcranial direct current stimulation on time limit and ratings of perceived exertion in physically active women. Neurosci Lett. 2018;662:12–6. 10.1016/j.neulet.2017.10.007 . Groslambert A, Mahon AD. Perceived exertion: influence of age and cognitive development. Sports Med. 2006;36(11):911–28. 10.2165/00007256-200636110-00001 . Noakes TD, St Clair Gibson A, Lambert EV. From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans: summary and conclusions. Br J Sports Med. 2005;39(2):120–4. 10.1136/bjsm.2003.010330 . Cogiamanian F, Marceglia S, Ardolino G, Barbieri S, Priori A. Improved isometric force endurance after transcranial direct current stimulation over the human motor cortical areas. Eur J Neurosci. 2007;26(1):242–9. 10.1111/j.1460-9568.2007.05633.x . Angius L, Mauger AR, Hopker J, Pascual-Leone A, Santarnecchi E, Marcora SM. Bilateral extracephalic transcranial direct current stimulation improves endurance performance in healthy individuals. Brain Stimul. 2018;11(1):108–17. https://doi:10.1016/j.brs.2017.09.017 . Brunoni AR, Vanderhasselt MA, Boggio PS, et al. Polarity- and valence-dependent effects of prefrontal transcranial direct current stimulation on heart rate variability and salivary cortisol. Psychoneuroendocrinology. 2013;38(1):58–66. 10.1016/j.psyneuen.2012.04.020 . Schmaußer M, Hoffmann S, Raab M, Laborde S. The effects of noninvasive brain stimulation on heart rate and heart rate variability: A systematic review and meta-analysis. J Neurosci Res. 2022;100(9):1664–94. 10.1002/jnr.25062 . Okano AH, Fontes EB, Montenegro RA, et al. Brain stimulation modulates the autonomic nervous system, rating of perceived exertion and performance during maximal exercise. Br J Sports Med. 2015;49(18):1213–8. 10.1136/bjsports-2012-091658 . Montenegro RA, Farinatti Pde T, Fontes EB, et al. Transcranial direct current stimulation influences the cardiac autonomic nervous control. Neurosci Lett. 2011;497(1):32–6. 10.1016/j.neulet.2011.04.019 . Gu Z, Chen W, Lu Q, et al. Anodal high-definition transcranial direct current stimulation reduces heart rate and modulates heart-rate variability in healthy young people: A randomized cross-controlled trial. Front Cardiovasc Med. 2022;9:1070157. 10.3389/fcvm.2022.1070157 . Muniz-Pardos B, et al. Acute effects of transcranial direct current stimulation on cycling performance in trained male athletes. Translational Exerc Biomed. 2024;1(1):60–70. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 10 Apr, 2026 Reviewers invited by journal 09 Apr, 2026 Editor invited by journal 09 Apr, 2026 Editor assigned by journal 08 Apr, 2026 Submission checks completed at journal 08 Apr, 2026 First submitted to journal 03 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9317035","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622080892,"identity":"44a03367-467b-4abc-abaa-bac317c2aff1","order_by":0,"name":"Maicon Teixeira de Almeida","email":"","orcid":"","institution":"Universidade do Estado do Rio de Janeiro (UERJ)","correspondingAuthor":false,"prefix":"","firstName":"Maicon","middleName":"Teixeira","lastName":"de Almeida","suffix":""},{"id":622080894,"identity":"5fbe0a91-91da-44fe-8503-2fa23b13621e","order_by":1,"name":"Carla Christina Ade Caldas","email":"","orcid":"","institution":"Universidade do Estado do Rio de Janeiro (UERJ)","correspondingAuthor":false,"prefix":"","firstName":"Carla","middleName":"Christina Ade","lastName":"Caldas","suffix":""},{"id":622080895,"identity":"d3832e4f-6bec-41a5-b3c7-36846e16d93b","order_by":2,"name":"Raquel Carvalho Castiglione","email":"","orcid":"","institution":"Universidade do Estado do Rio de Janeiro (UERJ)","correspondingAuthor":false,"prefix":"","firstName":"Raquel","middleName":"Carvalho","lastName":"Castiglione","suffix":""},{"id":622080898,"identity":"6183adbd-c4aa-4345-ab34-284583f59eb8","order_by":3,"name":"Silvio Rodrigues Marques-Neto","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBADHj4GxgaGD0AWGzuxWtiAWhhngLQwE2sNGxAz84BYhLTotp99eJunok6GTSK58bHNr23yfMwMjB8+5uDWYnYm3dia58xhHjaJxGbj3L7bhm3MDMySM7fh0XIgjU2at+0ADxvPwTbp3J7bjEAtbMy8+LScfwbU8q8OosWy57Y9YS03QLY0MPOwsTe2STP8uJ1IhJZnzJZzjh0GaWk27G24ndzGzNiM3y/n0xhvvKmps+dnZn/44Mef27bz25sPfviIRwsISMBZjG1gsgG/ehQtDH8IKh4Fo2AUjIIRCAAoU0fRfrEKVAAAAABJRU5ErkJggg==","orcid":"","institution":"Universidade do Estado do Rio de Janeiro (UERJ)","correspondingAuthor":true,"prefix":"","firstName":"Silvio","middleName":"Rodrigues","lastName":"Marques-Neto","suffix":""}],"badges":[],"createdAt":"2026-04-04 02:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9317035/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9317035/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107482525,"identity":"ddf389eb-e9dc-4955-8ea0-825971eec97a","added_by":"auto","created_at":"2026-04-22 02:23:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":101745,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental design. Anodal transcranial direct current stimulation (a-tDCS) protocol during HIFT control (without stimulus), sham (0 mA for 20 min), and a-tDCS (2 mA for 20 min) groups. The performance evaluation during HIFT involved four distinct rounds of two exercises, each separated by a 2-minute rest interval.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9317035/v1/190aacd241811e121c235207.png"},{"id":107256077,"identity":"c76fba55-42b0-4dba-9094-21cd4c88340a","added_by":"auto","created_at":"2026-04-19 12:15:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":62441,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of a-tDCS on Performance and Fatigue Index (%FI). Left: Number of repetitions in control, sham, and a-tDCS groups. a-tDCS showed significantly more repetitions than both control (\u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e = 0.001) and sham (\u003csup\u003e### \u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001); sham also exceeded control (\u003csup\u003e*** \u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e = 0.001). Right: FI (%) across groups. a-tDCS had significantly lower %IF than control (*** \u003cem\u003eP\u003c/em\u003e = 0.001) and sham (\u003csup\u003e#\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e = 0.05); Sham was also lower than control (\u003csup\u003e*\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e = 0.05).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9317035/v1/bb9940dcfd64faa959f9e171.png"},{"id":107484632,"identity":"fb421a41-7d70-4342-b47a-7330975d26cc","added_by":"auto","created_at":"2026-04-22 02:32:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63686,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of a-tDCS on perceived exertion and training load. (A) Rate of Perceived Exertion (RPE, CR-10 scale); (B) Visual Analogue Scale (VAS); (C) Training Load (RPE × time). Symbols indicate significant differences: \u003csup\u003e* \u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e = 0.01, \u003csup\u003e** \u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e = 0.001, \u003csup\u003e*** \u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e\u0026nbsp; = 0.001 vs. control; \u003csup\u003e##\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e = 0.02 vs. sham.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9317035/v1/6e4d7707bf48dc17aaced871.png"},{"id":107256079,"identity":"9c54a10a-b537-4a9e-90c3-c7057bd074a3","added_by":"auto","created_at":"2026-04-19 12:15:09","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":193928,"visible":true,"origin":"","legend":"\u003cp\u003ePhysiological responses in control, sham, and a-tDCS groups during HIFT. (A) Blood lactate (mM): \u003csup\u003e***\u003c/sup\u003e\u003cem\u003e P\u003c/em\u003e = 0.0001 vs. control; \u003csup\u003e#\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e =0.01 vs. sham. (B) Max HR (bpm): \u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e = 0.0001 vs. control; \u003csup\u003e### \u003c/sup\u003e\u003cem\u003eP\u003c/em\u003e = 0.0001 vs. sham. (C) Mean HR (bpm): \u003csup\u003e***\u003c/sup\u003e\u003cem\u003e P\u003c/em\u003e = 0.0001 vs. control; ###p \u0026lt; 0.0001 vs. sham. (D) TRIMP (a.u.): ***\u003cem\u003e P\u003c/em\u003e \u0026lt; 0.0001 vs. control; \u003csup\u003e##\u003c/sup\u003e\u003cem\u003e P\u003c/em\u003e = 0.01 vs. sham.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9317035/v1/b0ac3ed2252fb692d8be21cf.png"},{"id":107486989,"identity":"7c5a2656-9560-4d17-8749-2c367dbe6fb7","added_by":"auto","created_at":"2026-04-22 02:39:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":863553,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9317035/v1/cc54f893-e5bd-4e8d-8964-0f92c6693b44.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of transcranial direct current stimulation on physical performance, fatigue resistance, perceptual and physiological responses during high-intensity functional training","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHigh-intensity physical training is associated with the development of mechanisms that limit physical performance through central and peripheral influences [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although nutritional ergogenic aids have been extensively investigated, their effectiveness is variable and may be associated with adverse effects, highlighting the need for alternative non-pharmacological strategies [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTranscranial direct current stimulation (tDCS) has emerged as a neuromodulatory technique capable of modulating cortical excitability and influencing performance-related outcomes [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, its effects on exercise performance are generally modest and dependent on stimulation parameters, including cortical target, electrode montage, and exercise modality [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In addition, findings remain inconsistent, particularly in complex and multimodal exercise contexts.\u003c/p\u003e \u003cp\u003eHigh-intensity functional training (HIFT) is characterized by varied functional movements performed at high intensity, either in short bouts aimed at maximizing power output or in resistance-based formats targeting the highest number of repetitions within a predefined time, with the goal of improving both cardiorespiratory and muscular endurance [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This training approach aims to optimize performance across multiple domains, including cardiorespiratory endurance, muscular endurance, strength, flexibility, power, speed, coordination, and agility. Previous studies on HIFT have primarily focused on chronic adaptations and physiological responses to specific exercise protocols [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to its metabolic and neuromuscular demands, HIFT involves cognitive and perceptual components, such as decision-making under fatigue, pacing regulation, and tolerance to discomfort. These characteristics suggest that performance in HIFT may be influenced not only by peripheral factors but also by central mechanisms.\u003c/p\u003e \u003cp\u003eA recent study by our group [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] showed that β-alanine supplementation improved localized muscular resistance during HIFT; however, its use has been criticized due to side effects such as paresthesia [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Therefore, alternative strategies targeting central mechanisms without pharmacological intervention may be relevant in this context.\u003c/p\u003e \u003cp\u003eThe dorsolateral prefrontal cortex (DLPFC) is involved in executive function, decision-making, and regulation of perceived effort during exercise, influencing pacing strategies and fatigue tolerance [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough tDCS has been studied in cyclic and isolated exercise modalities, its effects in high-intensity, non-cyclical, and multimodal exercise formats such as HIFT remain poorly understood.\u003c/p\u003e \u003cp\u003eTraining load in HIFT is commonly monitored using internal parameters, including rate of perceived exertion (RPE), visual analogue scale (VAS), blood lactate concentration (BLC), heart rate (HR), and training impulse (TRIMP) [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. While these variables are associated with performance and internal load control, to date, no study has simultaneously investigated the effects of tDCS on both performance outcomes and internal load parameters during high-intensity functional training. Understanding these effects is essential to clarify the role of central neuromodulation in complex, high-intensity exercise and to support the development of effective non-pharmacological strategies to enhance performance.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to evaluate the impact of tDCS on physical performance, fatigue resistance, and internal load parameters (RPE, LOAD, VAS, BLC, HR, and TRIMP) during high-intensity functional training. We hypothesized that anodal tDCS applied over the left DLPFC would improve performance (total repetitions), reduce fatigue index, and attenuate perceptual responses, potentially through modulation of central fatigue.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and Ethical Standards\u003c/h2\u003e \u003cp\u003eThirteen healthy male participants engaged in high-intensity functional training (HIFT) for at least two years volunteered for this study. An a priori sample size estimation was conducted using G*Power software (version 3.1.9.7 for Windows), assuming a moderate-to-large effect size (f\u0026thinsp;=\u0026thinsp;0.40), an alpha level of 0.05, and statistical power (1\u0026thinsp;\u0026minus;\u0026thinsp;β) of 0.80, indicating a minimum sample size of 12 participants. Inclusion criteria were age between 18 and 40 years, regular engagement in HIFT training, and classification as low cardiovascular risk according to the American College of Sports Medicine guidelines [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Exclusion criteria included musculoskeletal injury, smoking, regular alcohol consumption, chronic disease diagnosis, and contraindications to transcranial direct current stimulation (tDCS), such as history of epilepsy, neurological disorders, or presence of implanted electronic devices.\u003c/p\u003e \u003cp\u003e All participants were informed about the experimental procedures and provided written informed consent prior to participation. The experimental protocol followed the principles outlined in the Declaration of Helsinki for research involving human participants. The study protocol was approved by the Research Ethics Committee of Universidade Salgado de Oliveira, Brazil (approval number: CAAE 02469418.2.0000.5289).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExperimental Procedure\u003c/h3\u003e\n\u003cp\u003eThis study was designed as a randomized, sham-controlled, crossover trial aimed at evaluating the effects of transcranial direct current stimulation (tDCS) on physical performance, fatigue resistance, and internal load during high-intensity functional training. The participants were instructed to attend the training center on three separate occasions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAll experimental procedures were conducted at a certified high-intensity functional training facility under controlled laboratory conditions.\u003c/p\u003e \u003cp\u003e At the first visit, participants were informed about all experimental procedures, signed an informed consent form, and underwent anthropometric and physical assessments.\u003c/p\u003e \u003cp\u003eEach participant underwent three HIFT sessions under different experimental conditions: control (no stimulation), sham tDCS, and anodal tDCS. A randomized crossover design was adopted using a computer-generated randomization sequence (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.randomizer.org\" target=\"_blank\"\u003ewww.randomizer.org\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.randomizer.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), ensuring that the order of conditions was counterbalanced across participants. The interval between sessions was standardized to 72 h to minimize potential carryover and fatigue effects.\u003c/p\u003e \u003cp\u003e Participants were blinded to the stimulation condition, and the sham protocol was designed to mimic the sensory experience of active stimulation. Outcome assessors were not involved in the stimulation procedures. All sessions were conducted under controlled environmental conditions (temperature: 22\u0026ndash;24\u0026deg;C; relative humidity: 50\u0026ndash;60%). Participants were instructed to avoid caffeine, alcohol, and strenuous physical activity for at least 24 h prior to each session.\u003c/p\u003e \u003cp\u003eHeart rate (HR) was continuously recorded throughout the sessions to determine the mean and maximum HR, as well as the training impulse (TRIMP). Each HIFT session consisted of four 4-min exercise bouts separated by 2-min recovery intervals. The rate of perceived exertion (RPE), visual analog scale (VAS) for muscle pain, and blood lactate concentration (BLC) were measured at the end of each exercise bout.\u003c/p\u003e\n\u003ch3\u003eAnthropometric and Physical Assessments\u003c/h3\u003e\n\u003cp\u003eFor anthropometric measurements, body mass and height were recorded using an analog scale with 100 g precision and a stadiometer with 1.0 cm increments (Filizola, Brazil). Body mass index (BMI) was calculated as the ratio of body mass (kg) to the square of height (m\u0026sup2;).\u003c/p\u003e \u003cp\u003eBody density was estimated from the sum of three skinfold measurements, as recommended by Jackson and Pollock for males (pectoral, subscapular, and triceps), and body fat percentage was subsequently calculated using Siri\u0026rsquo;s equation. All measurements were performed in triplicate by the same trained evaluator, and the mean value was used for analysis.\u003c/p\u003e \u003cp\u003eSkinfold thickness was measured using a 5 MHz ultrasound device (Body Metrix Pro; IntelaMetrix, Concord, CA, USA) that emits high-frequency waves to distinguish tissue interfaces within the layers. Measurements were taken by positioning the device perpendicular to the specified points for approximately five seconds.\u003c/p\u003e \u003cp\u003eCardiopulmonary exercise testing (CET) was performed using a rowing ergometer (Concept II, Inc., Morrisville, VT, USA). After a five-minute warm-up period, the participants rowed at a self-selected pace for five minutes at a consistent power of 75 W. Thereafter, the power was increased by 25 W every minute until volitional exhaustion. The rowing ergometer was chosen because of the participants\u0026rsquo; familiarity with it and the established validity of the incremental protocol used [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe test was terminated based on volitional exhaustion, inability to maintain cadence, or a rating of perceived exertion (RPE)\u0026thinsp;\u0026ge;\u0026thinsp;9. Throughout the test, oxygen consumption (VO₂) was continuously monitored using a portable device (PNOE, ENDO Medical, Palo Alto, CA, USA) with a breath-by-breath sampling frequency. The maximum oxygen consumption (VO₂ max) was determined as the highest recorded VO₂ value. Prior to testing, the equipment was calibrated in accordance with the manufacturer's guidelines.\u003c/p\u003e\n\u003ch3\u003eHigh Intensity Interval Training Protocol and Transcranial Direct Current Stimulation (tDCS)\u003c/h3\u003e\n\u003cp\u003ePerformance assessment during HIFT consisted of four different rounds of exercises, each interspersed with a 2-min rest period [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In detail, the rounds consisted of 4 min of as many rounds as possible (AMRAP) of five thrusters (60 kg for men and 43 kg for women) and 10 box jumps (round 1); 4 min of 10 power cleans (60 kg for men and 43 kg for women) and 20 pull-ups (round 2); 4 min of 15 shoulder to overhead (60 kg for men and 43 kg for women) and 30 toes to bar (round 3); and 4 min of 20 row calories and 40 wall ball shots (9 kg for men and 6 kg for women) (round 4).\u003c/p\u003e \u003cp\u003ePhysical performance was quantified as the total number of repetitions completed across all four rounds. Although absolute loads were used to reflect ecological validity and real-world HIFT practices, this approach may introduce inter-individual variability in relative intensity, which is acknowledged as a limitation.\u003c/p\u003e \u003cp\u003eTo calculate the fatigue index percentage (%FI), each 4-min round was divided into 1-min windows (four 1-min windows per AMRAP), resulting in a total of 16 windows. The number of repetitions performed in each window was quantified using video recordings (iPhone 14 Pro Max, 4 K at 60 fps; Apple Inc., Cupertino, CA, USA). The %FI was calculated using the following equation: %FI = [(max repetitions-min repetitions) / max repetitions] \u0026times; 100.\u003c/p\u003e \u003cp\u003e To minimize external influences on performance, no verbal encouragement was provided, and environmental stimuli (e.g., music) were standardized across all sessions.\u003c/p\u003e \u003cp\u003eFor anodal tDCS application, stimulation was delivered using a Striat device (Striat\u0026trade;, Ibramed, Amparo, SP, Brazil). The anodal electrode was positioned over the left DLPFC, and the cathodal electrode (reference) was positioned over the right supraorbital cortex, according to the international 10\u0026ndash;20 EEG system [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The stimulus was applied at an intensity of 2 mA for a duration of 20 min [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the sham condition, electrode placement was identical to that in the anodal condition; however, stimulation was applied for only 30 s and then turned off, whereas participants remained with the electrodes in place for the full 20 min period [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eRating of Perceived Exertion and Visual Analog Scales for Resistance Exercise\u003c/h3\u003e\n\u003cp\u003eRPE was assessed using the OMNI-RES scale, which is specifically designed for resistance exercise and includes verbal and pictorial descriptors ranging from 0 (extremely easy) to 10 (extremely difficult). Prior to data collection, all participants were familiarized with the use of the RPE scale during a preliminary session to ensure the reliability and consistency of responses.\u003c/p\u003e \u003cp\u003eSession load (LOAD) was calculated using the session RPE method based on the CR-10 scale, obtained at the end of each session, and multiplied by the total session duration, following established procedures.\u003c/p\u003e \u003cp\u003eThe visual analog scale (VAS) was used to assess muscle pain, with values ranging from 0 (no pain) to 10 (worst possible pain). The participants were also familiarized with the VAS prior to testing to ensure proper understanding and reproducibility of the measurements [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBlood Lactate Measurement\u003c/h2\u003e \u003cp\u003eBlood lactate concentration (BLC) was measured using a portable lactate analyzer (Accutrend\u0026reg; Plus System; Roche Bioelectronics, Basel, Switzerland), which has been previously validated for use in exercise settings. Capillary blood samples were collected from the fingertips immediately after each exercise bout. Although lactate was not measured at its peak time point, the same collection timing was applied across all experimental conditions to ensure internal validity and allow for consistent comparisons between conditions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHeart Rate and Training Impulse (TRIMP)\u003c/h3\u003e\n\u003cp\u003eHeart rate (HR) was continuously monitored throughout all HIFT sessions using a real-time monitoring system (Firstbeat Technologies Ltd., Jyv\u0026auml;skyl\u0026auml;, Finland), which has been validated for exercise monitoring. The mean HR and maximum HR values were extracted for each exercise bout.\u003c/p\u003e \u003cp\u003eTRIMP was calculated using the Banister method, which incorporates exercise duration and heart rate response to quantify the internal training load [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were conducted utilizing GraphPad Prism version 8.4.2 (GraphPad Software, San Diego, CA, USA). The data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). The normality of data distribution was evaluated using the Shapiro\u0026ndash;Wilk test, while sphericity was assessed via Mauchly\u0026rsquo;s test. In instances where the assumption of sphericity was violated, Greenhouse\u0026ndash;Geisser corrections were applied.\u003c/p\u003e \u003cp\u003eComparisons among the experimental conditions (control, sham, and anodal) were executed using a one-factor repeated-measures analysis of variance (ANOVA), with condition considered as a within-subject factor. This methodological choice was informed by the crossover design, wherein the same participants were subjected to all experimental conditions. Post hoc analyses were performed using Tukey\u0026rsquo;s test for parametric data. For variables that did not satisfy normality assumptions, the Friedman test followed by appropriate post hoc comparisons was employed.\u003c/p\u003e \u003cp\u003eThe effect size was calculated using partial eta squared (η\u0026sup2;p), with interpretations as small (0.01\u0026ndash;0.06), medium (0.06\u0026ndash;0.14), and large (\u0026gt;\u0026thinsp;0.14). The criterion for statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSample Characterization\u003c/h2\u003e \u003cp\u003ePhysical characteristics of the participants are listed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\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\u003ePhysical characteristics of the Participants.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c3\" namest=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e85.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e176.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e27.3\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody fat (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMax Power (Watts)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e359.6\u0026thinsp;\u0026plusmn;\u0026thinsp;49.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMax HR (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e192.2\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVO\u003csub\u003e2\u003c/sub\u003emax (ml.kg.min-1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e55.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2\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\u003eMax Power\u0026thinsp;=\u0026thinsp;maximum power production. Max HR\u0026thinsp;=\u0026thinsp;maximum heart rate. VO\u003csub\u003e2\u003c/sub\u003emax\u0026thinsp;=\u0026thinsp;maximum oxygen consumption.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePhysical Performance and Fatigue Index Percentage\u003c/h2\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;2A, both the sham (228.0\u0026thinsp;\u0026plusmn;\u0026thinsp;20.5 repetitions; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,24\u003c/sub\u003e = 62.34, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) and anodal (239.8\u0026thinsp;\u0026plusmn;\u0026thinsp;22.2 repetitions; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,24\u003c/sub\u003e = 62.34, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) conditions showed significantly more repetitions than the control (219.0\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4), compared to the control condition. Notably, the Anodal condition produced significantly more repetitions than the sham condition (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,24\u003c/sub\u003e = 62.34, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e Effects of a-tDCS on Performance and Fatigue Index (%FI). Left: Number of repetitions in control, sham, and a-tDCS groups. a-tDCS showed significantly more repetitions than both control (\u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and sham (\u003csup\u003e###\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); sham also exceeded control (\u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). Right: FI (%) across groups. a-tDCS had significantly lower %IF than control (*** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and sham (\u003csup\u003e#\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05); Sham was also lower than control (\u003csup\u003e*\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;2B shows that both the Sham and Anodal conditions resulted in a lower fatigue index (%FI) than the control (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,24\u003c/sub\u003e = 84.53; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively). Furthermore, the anodal group exhibited a significantly lower fatigue index percentage (%FI) than the sham group (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e2,24\u003c/sub\u003e = 84.53; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePerceptual Effort Scales and LOAD\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e Effects of a-tDCS on perceived exertion and training load. (A) Rate of Perceived Exertion (RPE, CR-10 scale); (B) Visual Analogue Scale (VAS); (C) Training Load (RPE \u0026times; time). Symbols indicate significant differences: \u003csup\u003e*\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01, \u003csup\u003e**\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, \u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001 vs. control; \u003csup\u003e##\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02 vs. sham.\u003c/p\u003e \u003cp\u003eIn Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA, the control presented a mean RPE of 8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a.u., while the sham presented a RPE of 8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 a.u. (\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.47, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.42). On the other hand, the anodal group presented a lower mean RPE (7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6 a.u.), which differed significantly from both the sham (\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.65, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) and the control (\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.12, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001) groups.\u003c/p\u003e \u003cp\u003eSimilarly, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, the control group had a mean VAS score of 8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8 a.u. The sham group exhibited a significantly lower VAS score (7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9 a.u.; Z\u0026thinsp;=\u0026thinsp;2.55, P\u0026thinsp;=\u0026thinsp;0.03) compared to the control group. The anodal group showed a significantly lower mean VAS value (7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 a.u.) than the control group (Z\u0026thinsp;=\u0026thinsp;4.22, P\u0026thinsp;=\u0026thinsp;0.0001) but not compared to the sham group (Z\u0026thinsp;=\u0026thinsp;1.67, P\u0026thinsp;=\u0026thinsp;0.29).\u003c/p\u003e \u003cp\u003eFor LOAD (RPE \u0026times; time), the results mirrored those of the RPE (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). The control\u0026rsquo;s average LOAD was 140.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0, while sham\u0026rsquo;s was 133.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3 (\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.47, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.42). Anodal exhibited the lowest value (128.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1), significantly lower than both control (\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.12, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001) and sham (\u003cem\u003eZ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.65, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePhysiological Parameters\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e Physiological responses in control, sham, and a-tDCS groups during HIFT. (A) Blood lactate (mM): \u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001 vs. control; \u003csup\u003e#\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01 vs. sham. (B) Max HR (bpm): \u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001 vs. control; \u003csup\u003e###\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001 vs. sham. (C) Mean HR (bpm): \u003csup\u003e***\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001 vs. control; ###p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 vs. sham. (D) TRIMP (a.u.): *** \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 vs. control; \u003csup\u003e##\u003c/sup\u003e \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01 vs. sham.\u003c/p\u003e \u003cp\u003eBlood lactate was significantly higher in the sham (13.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1 mM; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,15\u003c/sub\u003e = 15.18, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008) and a-tDCS (14.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.7 mM; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,15\u003c/sub\u003e = 15.18, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003) groups than in the control group (11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.2 mM), with Anodal also significantly higher than sham (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,15\u003c/sub\u003e = 15.18; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eRegarding maximum HR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eB), the sham group reduced max HR (183.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2 bpm; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,17\u003c/sub\u003e = 88.78; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001) compared to the control group (186.0\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 bpm). a-tDCS stimulation showed a further reduction (181.1\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0 bpm), which was significantly lower than that in the control and sham groups (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,17\u003c/sub\u003e = 88.78, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eThe mean HR (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eC) followed the same trend: Sham (157.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 bpm; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,14\u003c/sub\u003e = 56.50, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001) was lower than control (161.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 bpm), and a-tDCS (153.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 bpm) was significantly lower than both (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,14\u003c/sub\u003e = 56.50, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003e​For TRIMP (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eD), the sham group had lower values (68.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7 a.u) than the control group (72.9\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9 a.u; \u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,20\u003c/sub\u003e = 89.13, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001). Anodal displayed the lowest TRIMP (63.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 a.u), significantly reduced compared to both Sham (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,20\u003c/sub\u003e = 89.13, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and Control (\u003cem\u003eF\u003c/em\u003e\u003csub\u003e1,20\u003c/sub\u003e = 89.13​, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001). In summary, both sham and anodal conditions resulted in significant reductions in blood lactate, maximum HR, mean HR, and TRIMP compared with the control, with anodal conditions producing the most pronounced effects across all variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eEffect Size\u003c/h2\u003e \u003cp\u003eThe effect sizes from the One-Way ANOVA are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparisons related to the effect size of the One-Way ANOVA were attributed to the partial eta squared (η\u003csup\u003e2\u003c/sup\u003ep).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSham\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnodal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eη2p\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRepetitions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e219.0\u0026thinsp;\u0026plusmn;\u0026thinsp;22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e228.0\u0026thinsp;\u0026plusmn;\u0026thinsp;20.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e239.8\u0026thinsp;\u0026plusmn;\u0026thinsp;22.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.14 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e% FI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.7\u0026thinsp;\u0026plusmn;\u0026thinsp;4.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e57.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.56 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRPE (a.u)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVAS (a.u)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.25 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLOAD (a.u)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e133.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e128.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.24 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBLC (mM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.3\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.9\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMax HR (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e185.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e183.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e181.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.13 (Medium)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean HR (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e157.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.41 (Large)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRIMP (a.u)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.9\u0026thinsp;\u0026plusmn;\u0026thinsp;9.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.19 (Large)\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%FI\u0026thinsp;=\u0026thinsp;fatigue index percentage. RPE\u0026thinsp;=\u0026thinsp;rate of perceived exertion. VAS\u0026thinsp;=\u0026thinsp;visual analogue scale. BLC\u0026thinsp;=\u0026thinsp;blood lactate concentration. Max HR\u0026thinsp;=\u0026thinsp;maximum heart rate. Mean HR\u0026thinsp;=\u0026thinsp;average heart rate. TRIMP\u0026thinsp;=\u0026thinsp;training impulse.\u003c/p\u003e \u003cp\u003eAnodal stimulation exhibited significant impacts across various physical performance and fatigue measures, with large partial eta squared values for all outcomes except maximum HR, which showed a medium effect. These results further support the efficacy of both interventions, with Anodal demonstrating the most substantial overall benefits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePearson Correlation Coefficients\u003c/h2\u003e \u003cp\u003eFinally, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the Pearson correlation coefficients between performance variables and physiological measures in the anodal condition. %FI showed a strong, significant correlation with the number of repetitions (r\u0026thinsp;=\u0026thinsp;0.8; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001), highlighting a close relationship between these parameters. The VAS and TRIMP scores exhibited moderate but significant correlations with repetitions (r\u0026thinsp;=\u0026thinsp;0.5, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02; r\u0026thinsp;=\u0026thinsp;0.5; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04, respectively). Additionally, TRIMP was strongly correlated with %IF (r\u0026thinsp;=\u0026thinsp;0.7; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), suggesting that as fatigue resistance improved, the overall training impulse was similarly affected.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation between variables related to physical performance with RPE, VAS, Lactate, HR max, HR mean, and TRIMP in a-tDCS.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRepetitions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRPE (a.u)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVAS\u003c/p\u003e \u003cp\u003e(a.u)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLOAD (a.u)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBLC (mM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHR max (bpm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHR mean (bpm)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTRIMP (a.u)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRepetitions\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-------\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55*\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.54*\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e%FI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.60*\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.04\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.78*\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.61*\u003c/p\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03\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%FI\u0026thinsp;=\u0026thinsp;fatigue index percentage. RPE\u0026thinsp;=\u0026thinsp;rate of perceived exertion. VAS\u0026thinsp;=\u0026thinsp;visual analogue scale. BLC\u0026thinsp;=\u0026thinsp;blood lactate concentration. Max HR\u0026thinsp;=\u0026thinsp;maximum heart rate. Mean HR\u0026thinsp;=\u0026thinsp;average heart rate. TRIMP\u0026thinsp;=\u0026thinsp;training impulse.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated the impact of transcranial direct current stimulation (tDCS) on various key physiological and perceptual parameters during high-intensity functional training (HIFT), including physical performance, fatigue index percentage (%FI), rate of perceived exertion (RPE), training LOAD (RPE \u0026times; time), muscle pain via the visual analogue scale (VAS), blood lactate concentration (BLC), heart rate (HR), and training impulse (TRIMP). The findings revealed significant differences between experimental conditions, with the Anodal stimulation condition yielding the most pronounced enhancements in physical performance, fatigue resistance, perceptual markers, and physiological internal load.\u003c/p\u003e \u003cp\u003eAlthough previous research has shown limited improvements in performance with tDCS during short-duration maximal efforts, such as sprinting [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], various studies have demonstrated significant enhancements in performance during long-duration cyclical modalities [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. These findings align with the outcomes of the present study, where both the Sham and Anodal conditions resulted in a significantly greater number of repetitions than the control group.\u003c/p\u003e \u003cp\u003eNotably, the Anodal condition produced a significantly higher number of repetitions than the sham condition, which may indicate a more robust ergogenic effect when employing anodal stimulation. This is consistent with the literature suggesting that tDCS can enhance physical performance through mechanisms involving increased cortical excitability and recruitment of additional muscle fibers within a motor unit [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMoreover, Angius \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] investigated the effects of tDCS applied to the motor cortex on exercise-induced pain and endurance performance. Their study utilized a stimulation protocol comparable to that of the present investigation with 2 mA of anodal current for 20 min prior to exercise. They observed that anodal stimulation significantly reduced the perception of pain and prolonged the time to exhaustion (TTE) compared to both placebo and cathodal tDCS. These findings support the hypothesis that tDCS, as a non-invasive neuromodulatory technique, can modulate cortical excitability and, consequently, reduce the sensory perception of pain, thereby enhancing exercise tolerance and performance.\u003c/p\u003e \u003cp\u003eIn the current study, while both the Sham and Anodal conditions led to reductions in %FI, RPE, and VAS, the reductions were more substantial with anodal stimulation, reinforcing its superiority in modulating fatigue. The prefrontal cortex, particularly the lateral prefrontal cortex (LPFC), plays a key role in regulating decision-making and pacing during exhaustive exercise tasks, which is consistent with evidence showing reduced perception of effort and increased time to exhaustion following tDCS [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe LPFC integrates afferent physiological signals with motivational and emotional inputs from structures such as the anterior cingulate cortex (ACC) and orbitofrontal cortex (OFC), thereby modulating behavioral responses such as acceleration, maintenance, or reduction in exercise intensity [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe present findings are further corroborated by research demonstrating that tDCS can reduce the perception of central fatigue. The proposed mechanisms involve tDCS-induced modulation of cortical excitability, which alters the processing and perception of nociceptive inputs. Stimulation of the LPFC may dampen the affective and cognitive components of pain, thereby decreasing the subjective discomfort associated with exhaustive physical activity. This modulation holds substantial promise as a non-pharmacological intervention for athletes seeking to enhance endurance and mitigate discomfort during high-intensity exercise without relying on analgesic medication [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e​Furthermore, beyond influencing cortical excitability, tDCS may affect perceived exertion through additional psychological mechanisms. Various bodily sensations can serve as psychological triggers that influence the interpretation of effort and fatigue ​during exercise [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The central nervous system, by integrating sensory feedback from muscles and joints, plays a pivotal role in the experience and regulation of central fatigue [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Consequently, applying anodal tDCS to areas such as the motor cortex and LPFC may offer potential benefits by not only enhancing motivation and performance but also attenuating perceptions of muscle pain and exertional discomfort [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn support of these assertions, a recent study conducted by our research group evaluated RPE, VAS, and BLC across two different HIFT protocols, each characterized by distinct neuromuscular and metabolic demands [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. One protocol emphasized gymnastic movements with isometric contractions, whereas the other was characterized by dynamic contractions combined with cardiorespiratory exercises. The results indicated no significant differences in RPE between the protocols; however, the gymnastic method elicited significantly higher VAS and BLC levels, highlighting the importance of VAS as a sensitive marker of muscle discomfort and metabolic stress [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This observation underscores the relevance of using the VAS alongside other metrics when evaluating interventions such as tDCS that aim to attenuate fatigue-related sensations.\u003c/p\u003e \u003cp\u003eThus, the findings of the present study suggest that anodal tDCS may attenuate central and perceptual components of fatigue during muscular endurance tasks typical of HIFT, as evidenced by reductions in RPE and VAS, alongside increased blood lactate concentrations, which may reflect greater exercise tolerance and metabolic demand.\u003c/p\u003e \u003cp\u003eAlthough the literature on the specific effects of tDCS on BLC is limited, Angius et al. [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] examined bilateral anodal stimulation at C3, C4, and F3 and found significant improvements in endurance performance, notably increased TTE, along with elevated BLC relative to the control. This is congruent with our observations, where anodal stimulation over the left dorsolateral prefrontal cortex and a reference cathodal electrode over the right supraorbital cortex resulted in enhanced muscular endurance, decreased %FI, and increased BLC in the Anodal condition compared to the control.\u003c/p\u003e \u003cp\u003eThe underlying rationale for these observations is grounded in the premise that anodal tDCS enhances cortical excitability, reduces perceived exertion and muscle pain, and improves inhibitory control, collectively enabling individuals to sustain high-intensity training stimuli for a longer duration, which in turn elevates BLC due to the increased metabolic demand. These adaptations are crucial for athletes engaged in sports requiring sustained efforts, as they suggest the potential of tDCS to augment training-induced physiological adaptations.\u003c/p\u003e \u003cp\u003eMoreover, several studies have explored the broader impact of tDCS on cardiovascular parameters, including HR, TRIMP, and HRV [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. HR serves as a fundamental indicator of cardiovascular strain and adaptation during exhaustive exercise, with max HR frequently used to define the cardiovascular performance ceiling.\u003c/p\u003e \u003cp\u003eIn the current study, sham stimulation resulted in a significant reduction in max HR compared to the Control, with Anodal stimulation producing an even greater reduction relative to both Sham and Control. These findings may suggest that tDCS, particularly anodal stimulation, is associated with altered cardiovascular responses during exercise, thereby reducing peak cardiovascular stress during exertion [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent with these findings, Montenegro et al. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] reported that anodal tDCS significantly modulates autonomic cardiac control, enhancing the parasympathetic influence and reducing sympathetic drive. These effects were associated with decreased HR and changes in autonomic markers, reflecting improved autonomic regulation and cardiovascular efficiency. Such modulation may confer protective cardiovascular benefits during sustained physical efforts and mitigate the risks associated with excessive sympathetic activation.\u003c/p\u003e \u003cp\u003eSimilarly, Okano et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] demonstrated that tDCS may modulate the autonomic nervous system by reducing sympathetic and enhancing parasympathetic activity, resulting in improved physical performance during maximal exercise. Complementing these findings, Gu \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] investigated high-definition tDCS and its effects on HR and HRV in healthy individuals, concluding that anodal tDCS reduced HR and favorably modulated HRV, reinforcing the role of tDCS in optimizing autonomic and cardiovascular control.\u003c/p\u003e \u003cp\u003eMuniz-Pardos \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] further examined the acute effects of tDCS on professional cyclists\u0026rsquo; cardiovascular responses during TTE. Their results revealed that tDCS significantly reduced HR during exercise, which may suggest an adaptive physiological response that enhances the cardiovascular efficiency. A lower HR during exertion implies a reduction in cardiovascular strain, allowing for more sustainable high-intensity efforts, which is particularly advantageous for endurance athletes.\u003c/p\u003e \u003cp\u003eCollectively, these findings elucidate how tDCS may influence autonomic function by attenuating sympathetic activity while enhancing parasympathetic tone, leading to a reduced HR during high-intensity exercise. This modulation may indicate a beneficial effect on cardiovascular efficiency and overall athletic performance. Understanding these mechanisms contributes substantially to our comprehension of how brain stimulation influences physiological responses during physical activity and how it can be harnessed to optimize endurance and training outcomes.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has some limitations that should be considered. The relatively small sample size and inclusion of only male, trained participants limit the generalizability of the findings. The crossover design minimizes inter-individual variability; however, potential residual or placebo effects associated with sham stimulation cannot be fully excluded. Additionally, the study focused on acute responses, preventing conclusions about long-term adaptations to repeated tDCS application. Furthermore, no direct neurophysiological or autonomic measurements (e.g., cortical excitability or heart rate variability) were obtained, limiting mechanistic interpretation. Finally, the use of absolute loads in the HIFT protocol may have introduced variability in relative intensity among participants.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study showed that anodal tDCS was associated with reductions in perceived exertion, muscle pain, mean and maximal HR, and TRIMP during HIFT. These findings suggest that anodal tDCS may enhance performance and modulate internal load during high-intensity functional training. The present results highlight the potential relevance of tDCS as a non-pharmacological strategy in high-intensity multimodal exercise, particularly for improving exercise tolerance and performance-related outcomes. However, further studies are needed to confirm these findings and to elucidate the underlying physiological and neurobiological mechanisms.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003etDCS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTranscranial direct current stimulation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIFT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHigh-intensity functional training\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFatigue index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRPE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRating of perceived exertion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVAS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eVisual analog scale\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBLC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood lactate concentration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHeart rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTRIMP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTraining impulse\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLOAD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTraining load (RPE \u0026times; time)\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDLPFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDorsolateral prefrontal cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLPFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLateral prefrontal cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnterior cingulate cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOFC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOrbitofrontal cortex\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTTE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTime to exhaustion\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVO₂max\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaximal oxygen consumption\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBody mass index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCET\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCardiopulmonary exercise testing\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANOVA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAnalysis of variance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eStandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Research Ethics Committee of Universidade Salgado de Oliveira, Brazil (CAAE: 02469418.2.0000.5289). All procedures were conducted in accordance with the principles of the Declaration of Helsinki. All participants were informed about the aims, procedures, potential risks, and benefits of the study and provided written informed consent prior to participation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe manuscript does not contain any individual person\u0026rsquo;s data in any form, including individual details, images, or videos.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to privacy and confidentiality considerations involving human participants but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaquel Carvalho Castiglione (Grant No. E-26/204.411/2025) and Silvio Rodrigues Marques Neto (Grant No. E-26/204.447/2025) are fellows of the Young Scientist of Our State Program funded by the Carlos Chagas Filho Foundation for Research Support of the State of Rio de Janeiro (FAPERJ), Brazil.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMTA contributed to the study conception, data collection, data analysis, and drafting of the manuscript. CCAC contributed to data interpretation, critical revision of the manuscript, and intellectual content. RCC contributed to study supervision, interpretation of the findings, and critical revision of the manuscript. SRMN conceived and designed the study, supervised all stages of the research, contributed to data interpretation, and critically revised the manuscript for important intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Box Experience Training Center for allowing the study to be conducted with its athletes and facilities. The authors also thank all participants for their time, commitment, and willingness to take part in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eM\u0026aacute;rquez G, Romero-Arenas S, Mar\u0026iacute;n-Pag\u0026aacute;n C, Vera-Iba\u0026ntilde;ez A, Del Fern\u0026aacute;Ndez M, Taube W. Peripheral and central fatigue after high intensity resistance circuit training. Muscle Nerve. 2017;56(1):152\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/mus.25460\u003c/span\u003e\u003cspan address=\"10.1002/mus.25460\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eO'Leary TJ, Collett J, Howells K, Morris MG. Endurance capacity and neuromuscular fatigue following high- vs moderate-intensity endurance training: A randomized trial. Scand J Med Sci Sports. 2017;27(12):1648\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/sms.12854\u003c/span\u003e\u003cspan address=\"10.1111/sms.12854\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonilla DA, Boullosa D, Del Coso J. Advances in nutrition and ergogenic aids for performance. Nutrients. 2023;15(10):2246. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/nu15102246\u003c/span\u003e\u003cspan address=\"10.3390/nu15102246\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMabrey G, Koozehchian MS, Newton AT, Naderi A, Forbes SC, Haddad M. The Effect of Creatine Nitrate and Caffeine Individually or Combined on Exercise Performance and Cognitive Function: A Randomized, Crossover, Double-Blind, Placebo-Controlled Trial. Nutrients. 2024;16(6):766. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu16060766\u003c/span\u003e\u003cspan address=\"10.3390/nu16060766\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePolan\u0026iacute;a R, Paulus W, Nitsche MA. Modulating cortico-striatal and thalamo-cortical functional connectivity with transcranial direct current stimulation. Hum Brain Mapp. 2012;33(10):2499\u0026ndash;508. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/hbm.21380\u003c/span\u003e\u003cspan address=\"10.1002/hbm.21380\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonaiuto JJ, Bestmann S. Understanding nonlinear physiological and behavioral effects of tDCS. Prog Brain Res. 2015;222:75\u0026ndash;103. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi:10.1016/bs.pbr.2015.06.013\u003c/span\u003e\u003cspan address=\"https://doi:10.1016/bs.pbr.2015.06.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMachado DGDS, Unal G, Andrade SM, et al. Effect of transcranial direct current stimulation on exercise performance: A systematic review and meta-analysis. Brain Stimul. 2019;12(3):593\u0026ndash;605. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.brs.2018.12.227\u003c/span\u003e\u003cspan address=\"10.1016/j.brs.2018.12.227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLattari E, Oliveira BRR, Monteiro J\u0026uacute;nior RS, et al. Acute effects of single dose transcranial direct current stimulation on muscle strength: A systematic review and meta-analysis. PLoS ONE. 2018;13(12):e0209513. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0209513\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0209513\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2018 Dec 26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHeinrich KM, Becker C, Carlisle T, et al. High-intensity functional training improves functional movement and body composition among cancer survivors: a pilot study. Eur J Cancer Care (Engl). 2015;24(6):812\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/ecc.12338\u003c/span\u003e\u003cspan address=\"10.1111/ecc.12338\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFeito Y, Heinrich KM, Butcher SJ, Poston WSC. High-Intensity Functional Training (HIFT): Definition and Research Implications for Improved Fitness. Sports (Basel). 2018;6(3):76. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/sports6030076\u003c/span\u003e\u003cspan address=\"10.3390/sports6030076\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDrum SN, Bellovary BN, Jensen RL, Moore MT, Donath L. Perceived demands and postexercise physical dysfunction in CrossFit\u0026reg; compared to an ACSM based training session. J Sports Med Phys Fit. 2017;57(5):604\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.23736/S0022-4707.16.06243-5\u003c/span\u003e\u003cspan address=\"10.23736/S0022-4707.16.06243-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDos Santos DAA, Reis VMMR, Monteiro ER, Santos JM, Guimar\u0026atilde;es TT, de Figueiredo TC, Castiglione RC, Neto M, S. R. Comparison between acute effects of β-alanine supplementation on psychophysiological scales, blood lactate, training impulse and heart rate variability during high-intensity functional training. Cuad De Educaci\u0026oacute;n Y Desarrollo. 2023;15(5):4017\u0026ndash;38. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.55905/cuadv15n5-006\u003c/span\u003e\u003cspan address=\"10.55905/cuadv15n5-006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSaunders B, Elliott-Sale K, Artioli GG, et al. β-alanine supplementation to improve exercise capacity and performance: a systematic review and meta-analysis. Br J Sports Med. 2017;51(8):658\u0026ndash;69. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bjsports-2016-096396\u003c/span\u003e\u003cspan address=\"10.1136/bjsports-2016-096396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAngius L, Hopker JG, Marcora SM, Mauger AR. The effect of transcranial direct current stimulation of the motor cortex on exercise-induced pain. Eur J Appl Physiol. 2015;115(11):2311\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi:10.1007/s00421-015-3212-y\u003c/span\u003e\u003cspan address=\"https://doi:10.1007/s00421-015-3212-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobertson CV, Marino FE. Last Word on Viewpoint: A role for the prefrontal cortex in exercise tolerance and termination. J Appl Physiol (1985). 2016;120(4):470. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1152/japplphysiol.01010.2015\u003c/span\u003e\u003cspan address=\"10.1152/japplphysiol.01010.2015\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePeeling P, Binnie MJ, Goods PSR, Sim M, Burke LM. Evidence-Based Supplements for the Enhancement of Athletic Performance. Int J Sport Nutr Exerc Metab. 2018;28(2):178\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1123/ijsnem.2017-0343\u003c/span\u003e\u003cspan address=\"10.1123/ijsnem.2017-0343\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLattari E, Vieira LAF, Oliveira BRR, et al. Effects of Transcranial Direct Current Stimulation With Caffeine Intake on Muscular Strength and Perceived Exertion. J Strength Cond Res. 2019;33(5):1237\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1519/JSC.0000000000003123\u003c/span\u003e\u003cspan address=\"10.1519/JSC.0000000000003123\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson PD, Arena R, Riebe D, Pescatello LS. New preparticipation health screening recommendations. In: Pescatello LS, Arena R, Riebe D, Thompson PD, editors. ACSM\u0026rsquo;s Guidelines for Exercise Testing and Prescription. 9th ed. Philadelphia: Lippincott Williams \u0026amp; Wilkins; 2013. pp. 18\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCelik O, Koşar SN, Korkusuz F, Bozkurt M. Reliability and validity of the modified Conconi test on concept II rowing ergometers. J Strength Cond Res. 2005;19(4):871\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1519/R-15754.1\u003c/span\u003e\u003cspan address=\"10.1519/R-15754.1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTibana RA, de Sousa Neto IV, Sousa NMF, et al. Local Muscle Endurance and Strength Had Strong Relationship with CrossFit\u003csup\u003e\u0026reg;\u003c/sup\u003e Open 2020 in Amateur Athletes. Sports (Basel). 2021;9(7):98. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/sports9070098\u003c/span\u003e\u003cspan address=\"10.3390/sports9070098\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Published 2021 Jul 6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlem GH, L\u0026uuml;ders HO, Jasper HH, Elger C. The ten-twenty electrode system of the International Federation. The International Federation of Clinical Neurophysiology. Electroencephalogr Clin Neurophysiol Suppl. 1999;52:3\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGandiga PC, Hummel FC, Cohen LG. Transcranial DC stimulation (tDCS): a tool for double-blind sham-controlled clinical studies in brain stimulation. Clin Neurophysiol. 2006;117(4):845\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clinph.2005.12.003\u003c/span\u003e\u003cspan address=\"10.1016/j.clinph.2005.12.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFoster C, Rodriguez-Marroyo JA, de Koning JJ. Monitoring Training Loads: The Past, the Present, and the Future. Int J Sports Physiol Perform. 2017;12(Suppl 2):S22\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1123/ijspp.2016-0388\u003c/span\u003e\u003cspan address=\"10.1123/ijspp.2016-0388\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlix-Fages C, Romero-Arenas S, Calder\u0026oacute;n-Nadal G, Jerez-Mart\u0026iacute;nez A, Pareja-Blanco F, Colomer-Poveda D, et al. Transcranial direct current stimulation and repeated sprint ability: no effect on sprint performance or ratings of perceived exertion. J Sports Sci. 2022;40(5):569\u0026ndash;78. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi:10.1080/17461391.2021.1883124\u003c/span\u003e\u003cspan address=\"https://doi:10.1080/17461391.2021.1883124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLattari E, de Oliveira BS, Oliveira BRR, de Mello Pedreiro RC, Machado S, Neto GAM. Effects of transcranial direct current stimulation on time limit and ratings of perceived exertion in physically active women. Neurosci Lett. 2018;662:12\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neulet.2017.10.007\u003c/span\u003e\u003cspan address=\"10.1016/j.neulet.2017.10.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroslambert A, Mahon AD. Perceived exertion: influence of age and cognitive development. Sports Med. 2006;36(11):911\u0026ndash;28. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2165/00007256-200636110-00001\u003c/span\u003e\u003cspan address=\"10.2165/00007256-200636110-00001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoakes TD, St Clair Gibson A, Lambert EV. From catastrophe to complexity: a novel model of integrative central neural regulation of effort and fatigue during exercise in humans: summary and conclusions. Br J Sports Med. 2005;39(2):120\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bjsm.2003.010330\u003c/span\u003e\u003cspan address=\"10.1136/bjsm.2003.010330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCogiamanian F, Marceglia S, Ardolino G, Barbieri S, Priori A. Improved isometric force endurance after transcranial direct current stimulation over the human motor cortical areas. Eur J Neurosci. 2007;26(1):242\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/j.1460-9568.2007.05633.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1460-9568.2007.05633.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAngius L, Mauger AR, Hopker J, Pascual-Leone A, Santarnecchi E, Marcora SM. Bilateral extracephalic transcranial direct current stimulation improves endurance performance in healthy individuals. Brain Stimul. 2018;11(1):108\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi:10.1016/j.brs.2017.09.017\u003c/span\u003e\u003cspan address=\"https://doi:10.1016/j.brs.2017.09.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrunoni AR, Vanderhasselt MA, Boggio PS, et al. Polarity- and valence-dependent effects of prefrontal transcranial direct current stimulation on heart rate variability and salivary cortisol. Psychoneuroendocrinology. 2013;38(1):58\u0026ndash;66. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.psyneuen.2012.04.020\u003c/span\u003e\u003cspan address=\"10.1016/j.psyneuen.2012.04.020\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchmau\u0026szlig;er M, Hoffmann S, Raab M, Laborde S. The effects of noninvasive brain stimulation on heart rate and heart rate variability: A systematic review and meta-analysis. J Neurosci Res. 2022;100(9):1664\u0026ndash;94. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/jnr.25062\u003c/span\u003e\u003cspan address=\"10.1002/jnr.25062\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkano AH, Fontes EB, Montenegro RA, et al. Brain stimulation modulates the autonomic nervous system, rating of perceived exertion and performance during maximal exercise. Br J Sports Med. 2015;49(18):1213\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bjsports-2012-091658\u003c/span\u003e\u003cspan address=\"10.1136/bjsports-2012-091658\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontenegro RA, Farinatti Pde T, Fontes EB, et al. Transcranial direct current stimulation influences the cardiac autonomic nervous control. Neurosci Lett. 2011;497(1):32\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.neulet.2011.04.019\u003c/span\u003e\u003cspan address=\"10.1016/j.neulet.2011.04.019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGu Z, Chen W, Lu Q, et al. Anodal high-definition transcranial direct current stimulation reduces heart rate and modulates heart-rate variability in healthy young people: A randomized cross-controlled trial. Front Cardiovasc Med. 2022;9:1070157. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fcvm.2022.1070157\u003c/span\u003e\u003cspan address=\"10.3389/fcvm.2022.1070157\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuniz-Pardos B, et al. Acute effects of transcranial direct current stimulation on cycling performance in trained male athletes. Translational Exerc Biomed. 2024;1(1):60\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Transcranial direct current stimulation, high-intensity functional training, exercise performance, fatigue resistance, central fatigue, neuromodulation, perceived exertion, lactate, heart rate, training load","lastPublishedDoi":"10.21203/rs.3.rs-9317035/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9317035/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh-intensity functional training (HIFT) involves complex multimodal demands in which performance depends on both central and peripheral fatigue. Transcranial direct current stimulation (tDCS) has emerged as a non-invasive neuromodulatory strategy capable of enhancing cortical excitability and influencing exercise outcomes. However, its effects during high-intensity, non-cyclical exercise such as HIFT remain unclear. This study evaluated the impact of tDCS on physical performance, fatigue resistance, and perceptual and physiological responses during HIFT.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThirteen male HIFT-trained participants completed a randomized, crossover, sham-controlled study under three experimental conditions: control (no stimulation), sham, and anodal tDCS. Each session consisted of four rounds of HIFT, including thrusters, box jumps, and power cleans, performed under standardized conditions. During all HIFT sessions performance (repetitions), fatigue index (%FI), rate of perceived exertion (RPE), visual analog scale (VAS), blood lactate (BLC), heart rate (HR), and training impulse (TRIMP) were measured. Data were analyzed using repeated-measures analysis of variance or non-parametric equivalents, with post hoc comparisons when appropriate. Statistical significance was set at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnodal tDCS significantly increased the number of repetitions compared to both control (239.8 ± 22.2 vs. 219.0 ± 22.4) and sham (228.0 ± 20.5) conditions (p \u0026lt; 0.0001). The fatigue index was significantly lower in the anodal condition compared to both sham and control (p \u0026lt; 0.05), indicating enhanced fatigue resistance. Perceptual responses were attenuated, with reduced perceived exertion (7.9 ± 0.6 vs. 8.8 ± 0.6) and muscle pain scores (7.4 ± 1.1 vs. 8.7 ± 0.8) compared to control (p \u0026lt; 0.0001). Physiologically, anodal tDCS resulted in higher blood lactate concentrations (14.5 ± 1.7 mM vs. 11.5 ± 1.2 mM), alongside reductions in maximum heart rate (181.1 ± 5.0 vs. 186.0 ± 5.7 bpm) and training impulse (63.3 ± 7.8 vs. 72.9 ± 8.9) compared to control (p \u0026lt; 0.0001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnodal tDCS enhances performance and fatigue resistance during HIFT while reducing perceptual and cardiovascular strain. These findings suggest that tDCS may serve as an effective non-pharmacological ergogenic strategy to optimize performance and modulate internal load during high-intensity multimodal exercise.\u003c/p\u003e","manuscriptTitle":"Impact of transcranial direct current stimulation on physical performance, fatigue resistance, perceptual and physiological responses during high-intensity functional training","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-19 12:14:54","doi":"10.21203/rs.3.rs-9317035/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-23T09:57:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256569233013200400653194817325590902935","date":"2026-04-10T08:21:52+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-09T14:35:07+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-09T07:55:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-09T01:14:38+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-09T01:13:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Sports Science, Medicine and Rehabilitation","date":"2026-04-04T02:50:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-sports-science-medicine-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ssmr","sideBox":"Learn more about [BMC Sports Science, Medicine and Rehabilitation](http://bmcsportsscimedrehabil.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ssmr/default.aspx","title":"BMC Sports Science, Medicine and Rehabilitation","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"adf5cda3-c0f5-41a4-bafe-09d48286ea5b","owner":[],"postedDate":"April 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-19T12:14:54+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-19 12:14:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9317035","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9317035","identity":"rs-9317035","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}