Introduction

Executive function (EF) is a high-level cognitive function in the human brain that regulates other behavioral processes1. It is involved in learning and decision-making and is related to neural activity in the frontal lobe. The frontal lobe is an important region for regulating autonomic behavior and can control cognition through a hierarchical network system in multiple dimensions2. Electroencephalogram (EEG) can be used to monitor brain activity in the frontal lobe area. EEG power reflects the number of neurons that synchronize their projections, which can generate neural oscillatory phenomena. These oscillations are measurable and some frequency bands, such as alpha, beta, and theta, have been associated with specific perceptual, motor, or learning behaviors3.

However, the development of modern society has led to many behaviors in daily life that can negatively affect EF. One such behavior is sedentary behavior (SB), which is the most prevalent daily habit worldwide. SB is defined as any waking behavior characterized by energy expenditure of ≤ 1.5 METs in sitting, standing, or reclining positions4. The Global Status Report on Physical Activity 2022 by the World Health Organization (WHO) states that around 28% of the world’s population experiences SB, which is increasing among young people due to factors such as academic stress and lifestyle5. Unfortunately, there is substantial evidence indicating that SB development is directly correlated with a decline in EF. Takashi discovered that chronically sedentary individuals experience a weakening of prefrontal cortex function, resulting in attention deficit and slowing of cognitive processes6. Sina’s research, on the other hand, revealed that prolonged sedentary behavior leads to abnormal changes in the dorsolateral prefrontal cortex. The decline of executive function induced by substance abuse is a hot topic in the cognitive neuroscience community. This is demonstrated by the anisotropy of the N200 waveform in response inhibition tasks, such as stop signal. The attenuation of the alpha wave reduces Theta-Gamma coupling, leading to abnormality in the P300 waveform7. To effectively address this issue, research is needed.

In response to the aforementioned situation, WHO has demonstrated in its Guidelines on Physical Activity and Sedentary Behavior that regular physical activity (PA) is an effective non-pharmacological means of improving EF and brain plasticity in individuals4. Additionally, the immediate effectiveness of acute exercise has been proven8. However, as the scientific understanding of exercise has advanced, numerous studies have found that the impact of different types of PA on EF improvement varies. This effect has also been demonstrated to be immediately effective after acute exercise. However, with the advancement of exercise science, numerous studies have identified variations in the effects of different types of PA on EF. Moderate-intensity continuous training (MICT), body weight training (BWT), and mind-body exercise (MBE) are representative of three different types of PA. Among them, MICT involves a moderate and constant load, BWT is a self-weight-based strength training that uses resistance training9, and MBE is mindfulness training that requires the mobilization of physiological and psychological co-movement10. It has been confirmed that all three types of training have quantitative and qualitative effects on improving EF. Tsubasa demonstrated that MICT was more effective than RT in improving individuals’ cognitive flexibility11. Rida’s controlled experiments found that BWT was more effective than other PA in acutely improving working memory and response inhibition12. However, Puntarik reported an EF effect of long-term MBE that was not less than that of MICT13. As of now, the amount of effect of the three remains inconclusive.

In summary, although some studies have confirmed the beneficial effects of PA on cognitive function, the amount of evidence comparing the differences in effects of different PAs on EF and dose characteristics is more limited. In similar studies, Matthew and Formenti demonstrated that the acute effects of 16–30 min of MICT on inhibitory function and reaction time were superior to MBE in adults in a randomized controlled trial with narrative review14,15. On this basis, this study was the first to take sedentary adolescents as research subjects and included three different forms of PA, namely MICT, BWT, and MBE, as independent variables to compare the differences in effects. The physiological, psychological, and neurological mechanisms of PA were explained by EEG, ERP, and internal training load (ILT), with the aim of providing sedentary adolescents with more accurate exercise prescription and theoretical references. Based on the previous findings, this study proposes the following hypotheses: (I) MICT is superior to other PA in terms of its acute effect on EF and response time. (II) BWT triggers the maximum beta oscillation with N200 and P300 amplitude increase. (III) BWT has the highest subjective and objective loads and the lowest mental bandwidth expenditure.

Materials and methods

The study design is based on cross-over repeated measure design. All participants will perform the MICT, BWT, and MBE at different times with a rest interval of at least 72 h. The study involved testing both the anterior and posterior sides of each participant’s brain using EEG recording and task paradigm testing. An exercise intervention was then administered, followed by retesting at the end of the study period, which took place from January 2023 to June 2023. Prior to the formal experiment, all subjects were required to perform at least one pre-intervention exercise to become familiar with the exercise protocol. Participants were instructed to maintain their regular diet to ensure adequate physical and mental strength for testing. Strenuous exercise was prohibited 24 h prior to each test, and heavy meals were not allowed 2 h before the test. The experimenter recorded the physiological and subjective indicators of the participants every minute during the test.

Participants

The study enrolled 59 male college students between the ages of 17 and 23. All subjects reported on the short version of the International Physical Activity Questionnaire (IPAQ)16 that they were sedentary for more than 70% of their waking hours per day or engaged in moderate to vigorous exercise for less than 20 min per day4. Prior to the experiment, all subjects signed a Subject Informed Consent Form and confirmed that they had no history of psychological disorders or brain injury, no history of cardiovascular disease, and normal right-handed vision. The procedures were conducted in accordance with the National Institutes of Health Guidelines including Continuing Responsibility - The Protection of Human Subjects that minimize risk to participants and seek all legitimate rights to information. This study adhered rigorously to the ethical principles delineated in the Declaration of Helsinki and was granted approval by the Ethics Committee of Human Experimentation of Beijing Normal University (Authorization No. TY20220629). Demographic details are presented in Table 1.

Table 1 Participants’ physical characteristics.
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Procedures

Baseline testing

Prior to the experiment, the subjects’ height, weight, and BMI were measured. Graded exercise tests (GXT) were conducted using a cycle ergometer (HPS-102, Techman Technology Co., Chengdu, China). The subjects were initially warmed up with a resistance of 50 W for 2 min, followed by an increase of 20 W every minute until complete exhaustion (cycle speed below 50 rpm). Verbal encouragement was provided by the experimenter to ensure the validity of the experiment. The POLAR Verity Sense recorded the heart rate (HR) at a sampling rate of 1 time/s. To determine the set intensity for the formal experiment, HRmax was taken as the highest value within 15–30 s after the test17.

Moderate-intensity continuous training

The MICT group used Liu’s protocol18, implemented in the form of outdoor running. The intensity range in the formal exercise was set at 60–70% HRmax, and the process was implemented without any intervals for a total of 30 min, including a 5 min warm-up and recovery session.

Body weight training

BWT utilized Ayoub’s self-weight-based Tabata course19, and adapted the implementation time to 20 min, which was conducted indoors. The course consisted primarily of 20s of lunge squat, push-up, mountain climber, and animal flow, with burpee interspersed between movements to bridge the gap. The duration of one set was 8 min, and there were two sets in total.

Mind-body exercise

MBE was implemented indoors using Li’s protocol20, in the form of Tai Chi. Tai Chi specifically uses the 24-pattern Yang style of Tai Chi Chuan, which consists of 24 standardized movements that are completed in 2 consecutive sets in a single session. The exercise lasted 20 min, including a 5 min warm-up and formal exercise.

Measurements

Electroencephalogram analysis

Resting-state EEG was recorded using a 32-channel brainwave analyzer (NeuroScan_32–128, Compumedics Neuroscan, Australia). The reference electrodes were set to the default Oz during recording, and implementation filtering was achieved using a band-pass filter with an effective frequency interval of 0.01–100 Hz. The sampling rate was 1000 Hz, and the scalp impedance of all electrodes was kept below 50 kΩ. Brain Electrical Activity Mapping (BEAM) was used to observe the time-___domain characteristics of the activation level of brain regions before and after PA. The power spectrum of the EEG response was evaluated using the multi-step method, which reduces the variance of spectral estimates by multiplying the data with orthogonal tapers known as Slepian functions21. Fourier transform was performed via MATLAB_2022 to extract specific spectra including beta-1 (13.0–20.0 Hz) and beta-2 (20.0–30.0 Hz) respectively. The event-related potential (ERP) associated with the stop signal involving N200, P300, error-related negativity (ERN), and error positivity (Pe) is also observed. Among them, P300 is analyzed by 300-500ms filtering, N200 intercepts 200-300ms filtering22, ERN in the 0-100ms band, and Pe at 200-400ms23.

Executive function testing

The stop signal task paradigm with E-prime 2.0 software was used to test the EF. The task consisted of 200 stimuli, including ‘Go stimuli’ and ‘STOP stimuli’, presented on a computer. Each stimulus was an arrow within a circle with a ‘+’ sign at the center of the screen. During the test, participants were instructed to maintain fixation on the ‘+’ for 2000ms. Following this, a Go stimulus was presented with a circle and an arrow of the same color. Participants were required to respond by pressing the key corresponding to the direction of the arrow within 50ms. In the event of a STOP stimulus, the circle turned red, and participants were instructed to withhold their response. The ratio of Go to STOP stimuli was 7:1. The stimuli were presented in a randomized order and each lasted for 1200ms. Correctness and response time were recorded. The experiment consisted of a single test with a ratio of 7:3 for Go and STOP stimuli, respectively. The rehearsal phase, described in Fig. 1.

Fig. 1
figure 1

Steps in the stop signal task paradigm.

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Heart rate and exercise perception acquisition

In this study, a POLAR Verity Sense heart rate belt was used to monitor HR during exercise, with a sampling frequency of 1 beat/s, worn on the subject’s left arm. Before the formal experiment, the experimenter will conduct a 3–5 min test. The real-time HR acquisition status was monitored through the official POLAR PC-based software, and the equipment and steps of this experiment were adjusted according to the technical problems occurring in the field.

Exercise perception was assessed using Hardy & Rejeski’s Feeling Scale (FS)24 with Borg’s Rating of Perceived Exertion Scale-10 items (RPE)25 to assess subjects’ subjective fatigue and exercise experience. The dose relationship between RPE and FS was also illustrated from two orthogonal/bipolar dimensions by dual-mode model (DMM)26. Subjects were asked to report the scores orally every minute during the training and were recorded by the experimenter27.

Internal training load evaluation

In this study, subjective and objective loads were calculated for each group of subjects by training impulse. In this case, training impulse used Foster’s session-RPE (s-RPE) (2001)28 based on subjective fatigue level with Edward’s five intervals Edward’s TRIMP (1993)29 based on heart rate characteristics. Unlike the traditional Banister’s TRIMP (1991)30, Edward’s TRIMP divides the heart rate intervals, thus not only calculating the amount of load per unit of time of an individual in a more refined way, but also reflecting the characteristics of load distribution during exercise.

① Session-RPE formula is as follows:

$$session-RPE = T \times RPE$$

② Edward’s TRIMP formula is as follows:

$$TRIMP=(T\,\times\,1)+(T\,\times\,2)+(T\,\times\,3)+(T\,\times\,4)+(T\,\times\,5)$$

HR Zones (%HRmax)

Coefficient

90–100%

5

80–90%

4

70–80%

3

60–70%

2

50–60%

1

  1. T represents the time of training. TRIMP were calculated by multiplying the duration within each interval with the corresponding weighting factor. The sum of the TRIMP for each interval is the total TRIMP for the training. The RPE was the CR-10 RPE from Borg.

Statistical analysis

The study was statistically and analytically performed by IBM SPSS Statistics_26, and descriptive statistics and reliability tests were performed after normality tests. Individual results were combined before intervention. All data are presented as mean ± standard deviation. Comparison and proofreading of each indicator of the three groups were performed by one-way ANOVA (ANOVA). The time ___domain variation of data at different time points (25%/50%/75%/100%) was evaluated using multivariate analysis of variance (MANOVA). Data that did not meet the hypotheses were corrected using the Greenhouse-Geisser method after Bartlett’s Test of Sphericity. Finally, all post hoc tests were performed using the Bonferroni test with the significance threshold set at P<0.05.

Results

No risk events occurred in this study. During the course of the experiment, 4 samples were lost in the MICT group, with 93.22% compliance; 8 samples were lost in the BWT group, with 86.44% compliance; and no samples were lost in the MBE, with 100% compliance. Because this study was a cross-over repeated measure design, autogenous contrast was used for analysis. It was verified that there were no significant differences in demographic information (age, BMI, and HR) and baseline scores on the stop signal task for all subjects across the three experiments after each sample loss (P > 0.05).

Improved effectiveness of executive function

Differences in task paradigm and ERN for three exercise conditions in this study were not significant. ANOVA post-hoc analyses showed that accuracy was highest after a single BWT in the STOP SIGNAL task (F = 16.84, P = 0.0381), and that both the MICT and the BWT significantly improved individuals’ response times (F = 58.03, P = 0.0217; F = 75.49, P = 0.0178), while before and after MBE were statistically significant. In terms of ERP, only the BWT group showed a significant increase in N200 amplitude under three conditions (F = 44.35, P = 0.0351), but the MICT group showed the most significant amount of effect in terms of reducing latency (F = 27.29, P = 0.0411).The amplitude of P300 was significantly elevated after MICT (F = 66.59, P = 0.0194), but the effect was more significant after BWT (F = 97.72, P<0.01) and narrowed part of the latency of P300 (F = 1.84, P = 0.0406). ERN and Pe, as two potentials associated with the STOP SIGNAL task that provide feedback on error and correctness, showed a significant increase in amplitude after BWT (F = 48.68, P = 0.0317; F = 29.56, P = 0.0189), whereas there was an effect of MICT only on Pe (F = 21.04, P = 0.0342), but the latencies of both did not significant changes. According to the BEAM results, the activation level of individual frontal brain regions before and after PA increased at ERN, N200, and Pe, respectively, with the most significant increase in activation in parietal regions at P300. See Table 2; Fig. 2.

Table 2 Characterization of changes in executive function and ERN following PA.
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Fig. 2
figure 2

Characterization of changes in executive function, ERN, and BEAM following PA. Note: A, B: Change in response time and accuracy of stop signal; D, E: Changes in amplitude and latency of N2; F, G: Changes in amplitude and latency of P3; H, I: Changes in amplitude and latency of ERN; J, K: Changes in amplitude and latency of Pe; L, M, O: Time ___domain of each potential.

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Effects of physical activity on central nervous system

The results showed that PA had a significant effect on the EEG and beta oscillations of individuals. ANOVA results showed all the differences in readings, although the percentage of beta-1 and beta-2 in the EEG in FOUR conditions was not statistically significant. In the β-1 band, PA could enhance its percentage as high as 2.28–2.42%, while BWT had a similar effect with MICT and was higher than MBE. β-2 band changes were similar, and both had an incremental relationship with exercise intensity. Specifically, the percentage was highest after BWT, followed by MICT and lowest by MBE. This suggests that the PA-induced increase in beta-band activity may be associated with an increase in an individual’s accuracy in the stop signal and a reduction in reaction time. The EEG results showed that PA increased the amplitude value of the overall power of the EEG of individuals. Compared to the resting condition, the power range after PA increased from the original − 20–20 Hz to -30–30 Hz. the power differences between BWT and MICT were similar in the 5–20 Hz range, whereas the differences in MBE appeared around 10–15 Hz. After calculations by the multi-step method, it was found that beta band activity increased after three exercise conditions and showed higher beta oscillations during the task than the resting group. However, the difference between exercise groups was not significant. The detail has shown in Fig. 3.

Fig. 3
figure 3

Characterization of EEG and beta band activity following PA. Note: A, B: Percentage of β-1 and β-2; C, D: EEG and power ratio in four conditions; E: Amplitude of each band following PA.

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Expression level of training load

The results showed that the difference between subjective and objective loads under three exercise conditions was highly significant. ANOVA post-hoc analyses showed that the expression of HR, RPE, and FS were directly correlated with exercise intensity. In terms of HR and RPE, the results showed that BWT > MICT > MBE (F = 202.69; F = 113.85; P<0.01). As for FS, BWT significantly reduced FS in individuals (F = 93.48, P<0.01), but MICT differed from MBE only at the peak of FS (F = 47.14, P = 0.026). The RPE time-___domain plot showed that three conditions were not all equal at all stages (MICT: F = 165.37; BWT: F = 208.69; MBE: F = 145.82). MBE and MICT showed a significant increase (P<0.01) at the beginning of the exercise (25%), respectively, followed by a flat growth. In contrast, BWT continued to climb in RPE until the middle of the exercise (50%) and continued to grow after a brief plateau at the 75% stage (P<0.01). FS was the opposite. Where MBE declined insignificantly, MICT and BWT declined significantly only at mid-exercise (50%) (MICT: F = 171.93; BWT: F = 331.45; P<0.01), and were more flat thereafter.

The results of training load showed that the subjective and objective loads in three conditions differed significantly and had the same trend of BWT > MICT > MBE (s-RPE: F = 285.94, P < 0.05; TRIMP: F = 346.86, P < 0.05). This also implies that exercise intensity is positively related to the expression of both subjective and objective loads. The DMM results showed that three conditions time-___domain characteristics differed significantly. Among them, MICT was in the vigorous-pleasant quadrant before mid-exercise (50%) but transitioned to the fatigue-pleasant quadrant afterward. BWT stayed in the vigorous-pleasant quadrant only in the pre-exercise phase (25%) and then was active in the fatigue-unpleasant quadrant until the end of the exercise. MBE was predominantly in the vigorous-pleasant quadrant and approached the fatigue-pleasant quadrant only at the end of the exercise phase (100%). fatigue-pleasant quadrant edge. This suggests that intensity-induced differences in subjective perception are generally manifested in the mid- and end-periods of exercise. The detail has shown in Table 3; Fig. 4.

Table 3 Expression of training load under three exercise conditions.
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Fig. 4
figure 4

Training load and exercise perception in three exercise conditions. Note: A, B, C: Differences between HR, RPE and FS in three conditions; D, E: Time-___domain characterization of RPE and FS; F: Time-___domain characterization of HR; G: load distribution in Edward’s TRIMP for three conditions; H, I: Physiological and perceptual load of three conditions; J: Time-___domain variation of RPE and FS based on DMM.

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Discussion

Efficient EF is crucial for an individual’s learning ability and quality of life. The International Brain Research Organization (IBRO) has categorized it as a fundamental vital sign31. While the advantages of regular PA in enhancing EF have been widely recognized, the impact may vary depending on the type of PA, and comparisons are still inconclusive. In sedentary youth, their EF is observed to be lower than that of long-term exercisers. Additionally, low motivation to exercise is a major factor32. Therefore, when assigning an exercise prescription, both the efficiency of physical activity and the individual’s specific experience of exercise should be considered.

The study’s initial finding was that BWT had an immediate positive effect on EF. The results indicated that only BWT significantly improved the STOP SIGNAL score under three exercise conditions. Although MICT also reduced individuals’ reaction time during the task, BWT had a more significant effect. Therefore, hypothesis (I) cannot be accepted, which also suggests that BWT has the best effect on EF improvement. This result is consistent with some previous studies. Liu discovered that acute high-intensity interval training (HIIT), like BWT, not only improved EF in young adults better than MICT, but also reversed the mild cognitive decline caused by PM2.518. The effect was immediate. Nicholas’ systematic review also validated the acute effects of BWT. He found that a single high-intensity, short-duration form of PA was beneficial in improving employee performance on the same day, given the work environment in the first place33. Furthermore, the various effects of BWT are more noticeable in long-term interventions. Susan discovered that after 8 weeks of BWT, subjects not only experienced improvements in cognitive flexibility and memory, but also saw an increase in cardiorespiratory fitness (CRF), which was not observed in MICT34. Jennifer found that multimodal exercise had a positive effect on complex cognitive abilities such as learning, memory, processing speed, and visuospatial ability not only in the general sample but also in individuals with mild cognitive impairment (MCI). The intervention effectively enhanced intracranial apolipoprotein E (ApoE) and brain-derived neurotrophic factor (BDNF)35. However, Rida’s study confirmed the effect of MBE as a mindfulness training, which differs from the present study. Additionally, Rida found that the combined effect of MBE and BWT on EF was greater than that of PA alone12. Similarly, Xu et al. found that Tai Chi, when used as an adjunctive therapy in combination with transcranial direct current stimulation (tDCS), improved overall EF in MCI36. However, the daily workload and stress of school make it difficult for youths to maintain the duration of a single exercise session. After comparing three different forms of PA in a cross-sectional study, the present research concluded that BWT could be a cost-effective and easy-to-administer method that significantly improves EF. It can be used in conjunction with MBE to enhance the effect size.

The study’s second finding was the effect of MICT with BWT on N200, P300, ERN, and Pe modulation, as well as inducing higher levels of β-oscillation. Previous research suggests that the N200 and P300 are commonly associated with inhibiting responses to stimuli and attentional processing37. In stop signal, ERN and Pe represent misresponses to stimuli as well as adjustment behaviors. The EEG low-frequency band β-1 is associated with attentional and cognitive processes, while the high-frequency band β-2 represents complex motor control or higher cognition in the task38. In this study, BWT significantly potentiated the 4 potentials and shortened the N200 latency. Although MICT also affected P300 and Pe, the effect was less significant. On the other hand, in low-frequency beta waves, BWT and MICT showed similarity and both were higher than MBE, but this was not the case in high-frequency beta waves. This suggests that the enhancing effect of BWT on EF may be associated with the overall potential difference during stimulation, and that the high-frequency beta-oscillation induced a temporary improvement in the individual’s motor control and high-level decision-making. Hypothesis (II) can be accepted as the reason why MICT only affected response time may be related to its fluctuation in positive potentials such as P300 vs. Pe, but the low-frequency β-oscillation reflects that it is not sensitive to high-level cognitive processes. This finding is consistent with previous studies. Meaghan found that vigorous physical activity (VPA) not only induced higher levels of frontal central negative deflection and endogenous responses to control recruitment in the flanker task than MICT, but also exhibited greater Pe, P300, and N200 amplitudes39. Matthew’s study was similar to the present study in that he found that BWT elicited greater increases in P300 amplitude and shorter latencies in the Stroop task than loadless movement40. This effect was more pronounced after long-term intervention. Sebastian’s study compared the reaction inhibition of youths with different levels of PA. The results showed that long-term high levels of PA were associated with greater P300 and PSW amplitudes compared to intermediate levels. Additionally, N200, N450, and cortical hemodynamic changes were incrementally related to PA levels. These findings suggest that high levels of PA may enhance inhibitory processing in youths22. On the other hand, Zhang found that high-frequency beta-oscillations potentially mediate the improvement of mildly impaired executive function by VPA41. After systematically evaluating seven studies, Renata found that EF improvement after acute exercise was associated with an increase in the beta and alpha bands, whereas chronic response after prolonged PA was associated with suppression of beta versus theta waves42. In combination with the results of the present study, we have innovatively discovered a potential positive correlation between the neural mechanisms of impulse control and exercise intensity. Therefore, we suggest that BWT should be prioritized for inclusion in training based on individual physical factors.

The physiological basis can explain the effects mentioned above. Elevating acute PA intensity induces higher levels of ERP and frontal β-wave activity, which improves EF. This is because BWT requires the body to mobilize stronger inotropic contraction and triggers vasoconstriction, enhancing myocardial pumping function. This process increases α-receptor agonism in vascular smooth muscle, leading to the release of higher levels of norepinephrine (NA), dopamine (DA), γ-aminobutyric acid (GABA), β-hydroxy β-methylbutyrate (HMB), and glutamate (Glu) neurotransmitter systems. This recruitment of motor units and coordination of the balance of inhibition and excitation enhances decision-making efficiency43,44,45, ultimately achieving greater activation of sympathetic nervous system activity46. Fluctuations in ERPs, such as P300 and N200, and increased activity in the beta band manifest this phenomenon. No changes in content were made. Additionally, the steps of BWT are relatively cumbersome compared to MICT, the load is not constant, and motor control requirements are high. Therefore, higher centers need to allocate more attention to ensure the cognitive processing process. The anterior cingulate cortex and anterior ventral cortex are the main areas responsible for this process. They play important roles in error monitoring and reaction inhibition47. This explains why BWT triggered larger amplitude ERN and Pe isoelectric potentials, a phenomenon also observed by BEAM. In terms of metabolic substrates, the efficiency of central feedback varies depending on the functional systems of the body mobilized by different exercises. Previous research indicates that MICT and MBE primarily activate the aerobic metabolic system (AMS), which produces H2O and CO248. In contrast, short-duration, high-intensity PA such as BWT primarily involves the phosphagen system (ATP-CP) and glycolysis, resulting in the production of lactic acid, hydrogen ions, creatine phosphate (CP), and free amino acids. These byproducts are acidic and can affect the intracranial acid-base balance49. Appropriate secretion enhances the efficiency of energy metabolism and neuronal excitability. This is supported by compensatory increases in power in prefrontal motor areas, supplementary motor areas, and the parietal β-band50. However, excessive overproduction that surpasses central tolerance and leads to motor fatigue can result in a loss of motor unit recruitment and an increase in intracranial free radicals. This can break central conductance and increase the risk of skeletal muscle injury, as indicated by the inhibition of the β-band51. Thus, while the acute effect of BWT on EF is significant, the primary factor in exerting this effect is rational control of the amount of exercise.

The study’s third finding was to reveal the subjective and objective loading characteristics of the three sports. According to the American College of Sports Medicine (ACSM), monitoring the exercise process through ITL can more accurately quantify and assess the training effect52. Additionally, a positive exercise experience contributes to the development of interest, while a negative experience is not conducive to habit formation53. This study shows a positive correlation between HR and RPE, and FS on the contrary. Additionally, the load distribution zones of the three exercise conditions differed significantly from each other, resulting in an incremental relationship between TRIMP-based objective load and subjective response s-RPE with exercise intensity. The results suggest that while BWT had the most significant objective loading and EF enhancement effect, it also resulted in a higher incidence of fatigue and a poorer exercise experience. In contrast, individuals reported feeling vigorous and pleasant during MBE. Therefore, hypothesis (III) can be accepted, which is consistent with previous findings. In terms of exercise perception, Stork found that 20 min of HIIT triggered higher levels of RPE with lower FS than one hour of MICT54. It is important to note that exercise intensity was the primary factor inducing the decrease in subjective perception during acute exercise. Li discovered that improvements in exercise form may reverse the phenomenon of decreased subjective perception during long-term exercise. The study found that 12 weeks of HIIT resulted in a more positive mood and affective valence associated with PA compared to MICT55. Additionally, the study suggests that there is still some long-term value in BWT. Specifically, Schaun’s BWT for at least 10 min produced a physiological load equivalent to MICT for 40 min. This effect was mainly seen in terms of improvements in CRF, negative mood, and learning efficiency56. Jill suggests that there may be a temporal effect to this phenomenon. Prior to the onset of fatigue, subjective and objective loading levels and intensities are proportional. However, after exercise fatigue, subjective loading of MICT may be overestimated57. This may explain why the effect of EF improvement in PA varied between studies, which the present study suggests depends on the control of subjective load. The effectiveness of EF is reduced in the presence of excessive subjective evaluations or exercise fatigue. According to the principle of appropriate load58, the over-recovery effect can only be maximally induced when the ITL is controlled within a reasonable range. Additionally, the present study suggests that an efficient exercise prescription should aim to maximize objective load while minimizing subjective load, in accordance with the stimulus-fatigue-recovery-adaptation theory59. Therefore, MBE is appropriate for generating interest and promoting adherence in the early stages of exercise, while BWT can be scheduled once a solid foundation has been established to maximize the efficiency of EF improvement.

In summary, the enhancement of higher EF depends on increased exercise intensity, while excessively high intensity can trigger a decrease in exercise perception. To maximize this effect while effectively controlling negative effects, it is not desirable to follow through with any one PA alone during the training cycle. Therefore, a combination of different programs is recommended, based on the Principle of Appropriate Load58 and the Principle of Motivation in sports60. In the early stages of exercise, traditional Chinese medicine recommends cross-listing MICT and MBE to achieve the effect of ‘association of activity and inertia. Once basic adaptation has occurred, BWT can be used as an alternative to MICT to save time and space while promoting CRF. This can enhance the efficiency of improving EF and help to establish an exercise habit.

Limitations and suggestions for future research

This study examines the acute improvement effect of different PA on EF in sedentary youth using cross-repeated measures. The principle and physiological basis of the effect are explained from the perspective of neural electrical activity and training load. During the experiment, we maintained strict control over the three PAs and monitored both subjective and objective indicators. However, there were still two limitations and shortcomings in the experimental design.

The purpose of the PA comparison in this study was to provide sedentary youth with a more efficient exercise program for improving EF. Therefore, it is recommended to expand the sample size as much as possible during the population inclusion process to enhance the validity of the final results and reduce heterogeneity. However, in this study, recruiting subjects in the early stage was difficult. We recruited a total of 71 subjects, of which only 7 were female and 5 were professional athletes. To ensure standardization of the study and to address specific scientific questions, we ultimately selected only 59 male sedentary youth to minimize the impact of gender and training level differences on the results.

The study focuses on the outcome metric of EF, which includes cognitive flexibility, inhibitory function, and working memory. The classic stop signal paradigm used in this experiment addresses cognitive flexibility and inhibitory function, but not all types of EF were tested separately. This is because we included 2-Back vs. Stroop tests in the pre-experimental phase, but the effect of the different paradigms resulted in excessive heterogeneity of results and long experimental periods. To minimize the negative impact of this factor, we adopted the stop signal paradigm, which is the most representative and widely used paradigm for testing executive function internationally.

However, it is important to address the issues mentioned above. Therefore, this study will focus on researching gender differences and other aspects of EF in future programs. Additionally, a longitudinal study will be conducted to improve the scientific validity of the comparative results. The goal is to provide sedentary youth with more specific and efficient exercise prescriptions to improve EF.

Conclusion

Three exercise conditions significantly improved EF in sedentary youth. However, the use of BWT increased the effectiveness of this improvement. It is important to note that BWT has a higher subjective load on the individual and may result in a less enjoyable exercise experience, which could hinder the development of exercise habits in youths. To maximize the benefits of PA while ensuring an individual’s exercise feeling, it is recommended to cross-schedule MICT with MBE at the beginning of the exercise period and replace MBE with BWT after a certain foundation.