Acute effect of combined exercise with aerobic and resistance exercises on executive function

Introduction

Acute exercise, also known as a single bout of exercise, is linked to a wide range of cognitive functions, including problem-solving (Frith, Miller & Loprinzi, 2022), verbal fluency (Aguirre-Loaiza et al., 2019), decision-making (Lefferts et al., 2019), attention, and executive functions (Basso & Suzuki, 2017; Tsuk et al., 2019). Recent meta-analytical reviews have further suggested that cognitive performance is improved, regardless of whether it is measured during exercise or after the cessation of exercise (Chang et al., 2012; Ishihara et al., 2021; Johnson et al., 2016). The beneficial effects of acute exercise on cognitive function are believed to be due to the induction of the circulating brain-derived neurotrophic factor (Ekblom et al., 2022; Hung et al., 2018; Tsai et al., 2021), insulin-like growth factor 1 (Arazi et al., 2021; De Alcantara Borba et al., 2020; Stein et al., 2018), and neural plasticity (Ben-Zeev, Shoenfeld & Hoffman, 2022; Walsh & Tschakovsky, 2018). Despite the cognitive benefits of acute exercise, its effects on cognitive function are heterogenous, suggesting that they might be moderated (Chang et al., 2012; Johnson et al., 2016). For instance, while aerobic exercise (AE) leads to positive effects on cognitive function, anaerobic exercise leads to negative effects; interestingly, the combination of the two exercise types shows the largest positive effect (Chang et al., 2012), highlighting the importance of determining the exercise type in order to maximize the benefits for cognitive function.

Combined exercise (CE), also known as concurrent exercise (Brito, Soares & Silva, 2019), has been recognized as an effective and viable approach to enhance physical fitness (Bouamra et al., 2022; Markov, Hauser & Chaabene, 2022; Moghadam et al., 2020). CE involves the integration of AE and resistance exercise (RE) within a single exercise session, and its initial investigation dates back to Hickson’s study in 1980 (Hickson, 1980). The main appeal of CE is that it not only meets the World Health Organization’s guidelines on physical activity, which emphasize the importance of aerobic exercise and muscle-strengthening exercise (Bull et al., 2020; WHO, 2020), but also can be completed in a short period of time while having the same physiological adaptations compared to doing AE or RE separately (Markov, Hauser & Chaabene, 2022). Indeed, CE is recognized as a time-saving and beneficial strategy for improving body composition, strength, and hypertrophy and may have additional benefits compared to doing RE or AE separately.

Nevertheless, the acute effects of CE on cognitive function are still unknown. In fact, to the best of our knowledge, only two studies have investigated this topic. Chang et al. (2017) found that low-intensity total-body machine-based RE performed in a circuit-training mode combining low intensity aerobic exercise, such as walking on a treadmill, improves information processing speed and inhibition control of young college females. Interestingly, Wen & Tsai (2020) found that a single session of moderate-intensity body weight or dumbbell resistance exercise combined with moderate intensity aerobic dance exercise in a circuit-training form improves the neurophysiological inhibition control of obese women but does not improve behavioral performance parameters, such as accuracy rates and reaction times. In summary, investigations of the acute effects of CE on cognitive function are relatively limited, the findings of previous studies are inconsistent, and the mechanism underlying the enhancement of exercise-induced cognitive function remains unknown. Furthermore, whether different modes of CE, which combine traditional sequential movement resistance exercise, are beneficial for exercise-induced cognitive function remains to be clarified. Furthermore, acute RE has garnered recognition as a significant and promising exercise modality within the realm of exercise and cognitive function (Huang et al., 2022; Wilke et al., 2019); however, there are relatively few studies investigating the effects of RE on cognitive function compared to study targeted on AE (Chow et al., 2021). Therefore, the present study specifically incorporates RE condition for comparison, aiming to address the limitations of previous studies in this area.

The aim of the present study was to investigate the immediate effects of moderate CE and to compare these effects with those of RE on cognitive function, utilizing behavioral measures as the primary assessment tool. Based on previous findings (Chang et al., 2017; Wen & Tsai, 2020), this study expected that the behavioral performance measures would be higher after the two exercise sessions compared to a control session of sitting.

Furthermore, this study hypothesized that behavioral performance after CE would be better than that after RE in both response time and accuracy rate.

Methods

Experimental procedure

The study consisted of one screening visit and three experimental sessions at the weight training room of the Department of Aquatic Sport, University of Taipei (Tian-Mu campus) from November 2020 to June 2021. These sessions were conducted over approximately 4 weeks with a week-long rest interval and counterbalanced order. Participants were instructed to avoid any strenuous exercise for 24 h and abstain from ergogenic aids, alcohol, caffeine, and medications before each experimental session to rule out possible effects on exercise and cognitive performance. The test environment was set at a minimum noise level and a temperature of 24–26 °C. To control alterations to the circadian rhythm, all participants engaged in the exercise sessions in the morning (8 am to 12 pm).

On their first visit to the laboratory, the participants received a detailed explanation of each experimental procedure. Before each formal intervention began, all participants underwent a pre-experiment assessment, including V̇O_2peak and 10-repetition maximum (10 RM) assessment of the upper extremity, in the laboratory. Their body composition was also measured using bioelectrical impedance analysis. In addition, participants were instructed to practice and familiarize themselves with the cognitive task. All participants were instructed to complete practice trials of the Stroop Color and Word Test for all three conditions until they achieved an accuracy rate of 85% (Chang et al., 2015).

The experimental sessions comprised CE, RE, and sitting control (SC) sessions. The heart rate (HR), blood lactate, and rating of perceived exertion (RPE) were used to assess the exercise manipulation. To measure the HR, a telemetric BioHarness™ 3.0 chest strap (ZephyrTM Technology, Medtronic, Annapolis, USA) was secured round the participant’s chest just below the sternum. It detected and recorded the HR continually and shared it via Bluetooth (802.15.4 protocol) with the Zephyr™ Echo Gateway. The HR reading was displayed on a laptop monitor throughout each intervention session. After finishing each session, the heartbeat data were exported via OmniSense™ Live Software version 5.0. Blood lactate levels (mmol/L) were assessed at three time points: pre-session, during the session (approximately 20 min after the initiation of each session), and post-session. The measurements were conducted using a lactate analyzer (EDGE: Blood Lactate Monitoring System, Hsinchu Science Park, Hsinchu, Taiwan, ROC). In the case of RPE, the Borg psychophysiological rating (6–20 scale) (Borg, 1970; Borg, 1982) was applied to assess individuals’ subjective psychophysiological feelings regarding their RPE. This study also used the RPE Borg 6–20 scale to record participants’ 10 RM RE and aerobic exercise assessment exertion status. Furthermore, RPE was recorded at five-minute intervals during each RE and CE session. The experimental procedure is shown as Fig. 1.

Results

Descriptive statistics for participant demographic and anthropometric characteristics and cardiovascular fitness assessment results were shown in Table 1. Descriptive data for the RE and AE exercise intensity manipulation were shown in Table 2.

Behavioral data

Response time

The main effect of intervention on response time was significant (F(2, 28) = 3.91, p = .03, ${\eta }_{\mathrm{p}}^2$ = .22), with a shorter mean response time for the CE (21.49 ± 1.04 s) than for the SC (23.72 ± 1.00 s; p < .05). Furthermore, the mean response time of RE (22.03 ± 1.13 s) was not significantly different with CE (p = 1.00) and SC (p = .23). The main effects of condition was significant (F(1.07, 15.01) = 97.00, p < .001, ${\eta }_{\mathrm{p}}^2$ = .87), with a shorter mean response time for the neutral (17.32 ± 0.59 s) and the congruent conditions (17.01 ± 0.66 s) than for the incongruent condition (32.92 ± 1.89 s). However, there was no significant difference between the neutral and the congruent conditions. The intervention × condition interaction was not significant (F(2.47, 34.52) = 1.20, p = .32, ${\eta }_{\mathrm{p}}^2$ = .079; see Fig. 2A).

Accuracy rate

The main effect of intervention on the accuracy rate was not significant (F(2, 28) = 3.23, p = .06, ${\eta }_{\mathrm{p}}^2$ = .19; CE: 98.93 ± 0.28%; RE: 99.51 ± 0.15%; SC: 98.58 ± 0.30%). The main effects of condition was significant (F(1.27, 17.71) = 32.63, p < .001, ${\eta }_{\mathrm{p}}^2$ = .70), with a highest accuracy rate for the neutral (99.73 ± 0.13%), followed by congruent (99.38 ± 0.15%), and incongruent conditions (97.91 ± 0.27%; ps < .05). The intervention × condition interaction was not significant (F(4, 56) = 1.81, p = .14, ${\eta }_{\mathrm{p}}^2$ = .12.; see Fig. 2B).

Discussion

The present study explored whether acute CE affects cognitive function. To the best of our knowledge, this study is among the first to investigate the effects of acute CE on cognitive function in sedentary males and compare the results to the effects of traditional sequential movement resistance training. Our main findings demonstrated that acute CE, with 20 min of upper extremity RE, combined with 20 min of lower extremity cycling on an ergometer, decreased the SCWT response time, regardless of the SCWT conditions, i.e., neutral, congruent, and incongruent, and the effects were similar to RE. Furthermore, accuracy rates showed nonsignificant differences between the three sessions. While these findings are consistent with previous research demonstrating that a single bout of CE, consisting of low-intensity resistance and aerobic exercise, may enhance the SCWT response time in a young female college student population (Chang et al., 2017), our findings extend the previous study by demonstrating cognitive benefits after moderate-intensity CE consisting of upper extremity RE and lower extremity AE. Our study thus highlights potential avenues of exploration for prescribing CE, in relation to intensity, duration, type, order of exercise, and applied population domain, to induce optimal cognitive performance.

Our findings pertaining to the different cognitive conditions in the SCWT are consistent with previous research (Chang et al., 2015; Chang et al., 2014; Wang et al., 2019). These studies have consistently observed the presence of the “Stroop effect”, wherein response times were slower and accuracy was reduced in the incongruent condition compared to the congruent condition. The alignment of our results with these prior findings lends support to the validity of our manipulation of the cognitive task in the present study. Additionally, the observed improvements in cognitive performance in both RE and CE were in line with a previous meta-analysis indicating that acute RE leads to moderate cognitive improvements compared to a no-exercise control (Wilke et al., 2019). A randomized controlled trial with a small sample size showed that acute CE leads to better SCWT performance, compared to high-intensity RE and AE (Chang et al., 2017). However, our findings are inconsistent with those of a study showing that acute CE does not enhance the behavioral indices of SCWT (Wen & Tsai, 2020). However, the acute CE in the previous study consisted of 30 min of moderate-intensity body weight or dumbbell RE (12–16 repetitions) combined with a moderate-intensity aerobic dance exercise (55% of heart rate reserve (HRR)) in circuit-training form (Wen & Tsai, 2020); therefore, it is possible that both the RE and AE might not have been intense enough to improve behavioral performance in the SCWT (Braga et al., 2022; Peruyero et al., 2017; Zhou & Qin, 2019)

In addition, the duration of exercise (Basso & Suzuki, 2017; Chang et al., 2019) as well as the type of exercise (Fiorelli et al., 2019; Hacker et al., 2020; Ishihara et al., 2021) may exert an influence on the acute effects of exercise on domain-specific cognitive function, potentially varying across different populations, age groups, and genders. Chang et al. (2015) found that the acute exercise duration has dose–response relationships with acute-exercise-induced cognitive function improvement. They suggested that 20 min of acute moderate-to-vigorous intensity exercise might be the optimal modality for basic information processing and executive function improvements. Thus, the findings of the present study corresponded with the results obtained by the aforementioned studies, since the RE was composed of four RE movements with four sets and 10 repetitions, with rest periods of two minutes between sets, i.e., the actual exercise duration of the RE was approximately 15 min. Compared to the RE, the CE was composed of RE and AE in a single bout of the session; as a result, the total exercise duration of the CE might be too lengthy to induce better executive function performance due to physiological and mental fatigue, which might be the reason for the lack of significant differences between CE and RE regimens in response times and accuracy rates of the SCWT.

Different types of CE modes might also affect the results. Wen & Tsai (2020) showed that acute CE, consisting of a combination of aerobic dance as an AE and circuit training involving body weight and dumbbell RE, might improve neurophysiological inhibition control but not the performance of behavioral indices among obese women. Chang et al. (2017) specified another mode of CE combining machine-based circuit-training RE (30% 1 RM, 12 repetitions) with low-intensity walking on a treadmill (50–60% of HRR), which may enhance both the accuracy rate and response times in the SCWT. In contrast, the present study did not observe a significant difference in accuracy rate between the three sessions. As a result, irrespective of exercise duration and intensity, the exercise type might also play a significant mediator role in exercise-induced enhancement of cognitive function.

To date, only a few experimental studies have explored the mechanisms behind improved cognitive function after acute CE. The general exercise-induced improvements in cognition might be influenced by blood or systemic lactate levels (Ben-Zeev, Shoenfeld & Hoffman, 2022). Lactate is not only an important energy source for replacing glucose during exercise, but also a signaling molecule for modulation of neural plasticity through specific activation of signal receptors and subsequent downstream signaling pathways (Xue et al., 2022). The degree of exercise-induced executive function improvements may be associated with blood lactate levels, which is probably due to elevated cerebral lactate metabolism, since prolonged exercise may decrease cerebral oxygenation. Furthermore, lactate, as an exercise-induced myokine, may play an important role as mediator and modulator of brain adaptation and be a myokine for activating certain brain areas (Chen et al., 2021; Hashimoto et al., 2021; Severinsen & Pedersen, 2020). In the present study, blood lactate levels were not altered significantly during SC, but they were slightly different and increased during RE and CE. Huang et al. (2021) found that moderate-intensity RE increased cerebral lactate metabolism immediately after exercise, compared to pre-exercise. As a result, the potential impact of CE and RE on postexercise EF enhancements may be due to the increase in blood lactate levels, the metabolism of cerebral lactate, and cerebral oxygenation. Chang et al. (2017) also indicated a similar potential mechanism (via the tissue oxygen index) in the prefrontal cortex, implying that low-intensity CE enhances oxygen and nutrient distribution throughout the brain via oxygen saturation and increased blood flow and that increased oxygenated hemoglobin concentration in the prefrontal cortex might activate cognition-related nerves, consequently improving exercise-induced cognitive performance.

In addition to the manipulation of exercise intervention parameters such as intensity, duration, and type of exercise, the enhancements in EF induced by CE may also be influenced by other factors, including variations in lactate levels and cerebral oxygenation levels. Apart from the aforementioned mechanism potentially influencing exercise-induced EF improvements, recent studies have also investigated the relationship between exercise-induced EF enhancement and arousal based on arousal–performance interaction theory (Chou et al., 2021). Acute bouts of RE might induce alterations of the endocrine system, nervous system, and subsequent changes in the level of arousal (Tsukamoto et al., 2017). Wang et al. (2019) also suggested that exercise may induce eustress, which may be correlated with EF improvement and the neural activation process via neuroendocrinological responses. Their study showed that exercise-induced modification of the perceptual response may also be associated with the locus coeruleus-norepinephrine (LC-NE) functional coupling system, which may also modulate acute exercise-induced cognitive performance (Grueschow, Kleim & Ruff, 2022). Collectively, despite the lack of a direct evidential relationship between exercise-induced cognitive performance and phasic activation of the LE-NE system, the aforementioned research contributes to a broader understanding of the potential factors and mechanisms that may underlie the manifestation of improved performance on the SCWT following CE.

The main strength of the present study is the investigation of the effects of acute CE on multiple aspects of executive function in sedentary male individuals. However, the study also has some limitations. Firstly, acute exercise interventions might be influenced by participants’ daily lifestyle behaviors, physical activity status, and dietary habits outside of the intervention period. While our study employed a counter-balanced design, similar to previous studies (Drollette et al., 2014; Hillman et al., 2009; Ludyga et al., 2020), it is important to acknowledge that day-to-day variability could not be completely eliminated as a potential confounding factor. Despite reminding and instructing all participants to maintain their regular daily lifestyles and levels of physical activity, it is possible that some individuals did not strictly adhere to these guidelines. Future studies should consider incorporating pre-test and post-test measurements within a crossover experimental design to mitigate the impact of such variability. In addition, the duration of the exercise interventions in this study might have been influenced by exercise type, i.e., the actual exercise duration of RE was less than that of other sessions due to the rest periods between sets. Given the exploratory nature of our study, we recruited as many participants as possible, resulting in a sample size of n = 15, which is consistent with the experimental design employed in previous similar studies (Chang et al., 2014; Tsukamoto et al., 2017). It is important to note that the relatively small sample size and the inclusion of only sedentary male adults in our study may limit the generalizability of our findings to the broader population. Future studies should aim to recruit larger sample sizes to enhance statistical power and improve generalizability. Furthermore, since we conducted only one cognitive assessment following each session, the duration of the session-induced increase in cognitive task performance remains unclear. Further research on CE should be undertaken with different orders, intensities, patterns, and exercise durations in order to investigate the optimal combination that might induce the highest enhancement of cognitive function performance.

Conclusion

This study demonstrated that a single session of moderate-intensity CE resulted in a significant improvement in response time in the SCWT. The effect of CE was found to be comparable to that of RE. These findings highlight the potential effectiveness of CE as a viable exercise modality for enhancing cognitive function. Considering the recognized efficacy and accessibility of CE, as well as its additive physiological benefits observed across different settings, future research should continue to explore and deepen our understanding of the cognitive benefits associated with this type of exercise, along with other exercise modalities.

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