Effect of an acute bout of high- vs. low-intensity physical exercise on attentional networks.

Effect of an acute bout of high- vs. low-intensity physical exercise on attentional networks. | 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 Article Effect of an acute bout of high- vs. low-intensity physical exercise on attentional networks. Enrique Sanchis-Navarro, Fernando Gabriel Luna, Juan Lupiañez, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3973814/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract The effects of physical exercise on attentional performance have received considerable interest in recent years. Most of previous studies that assessed the effect of an acute bout of exercise on attentional performance have generally been approached by analysing single attentional functions in isolation, thus ignoring the functioning of other attentional functions, which characterizes the real perception-action environmental conditions. Here, we investigated the effect of two different intensities (low vs. high) of acute exercise on attentional performance by using the ANTI-Vea, a behavioral task that simultaneously measures three attentional functions (phasic alertness, orienting, and cognitive control) and the executive and arousal components of vigilance. 30 participants completed three experimental sessions: the first one to assess their physical fitness and baseline performance in the ANTI-Vea, and the other two sessions to assess changes in attentional and vigilance performance after an acute bout of high- vs. low-intensity physical exercise (in a counterbalanced order between participants). Beneficial effects on some accuracy scores (i.e., overall higher accuracy in the attentional sub-task and fewer false alarms in the executive vigilance sub-task) were observed in the low-intensity exercise condition compared to baseline and high-intensity. Additionally, the RT score of phasic alertness was increased after the low-intensity exercise in comparison with baseline. The present findings suggest that a bout of acute exercise at low-intensity might induce some short-term beneficial effects on some aspects of attention and vigilance. Biological sciences/Neuroscience Biological sciences/Psychology Exercise attention executive control orienting phasic alertness vigilance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Attention comprises a set of cognitive processes highly involved in daily life activities, such as working, studying, and sport tasks. The attentional networks model by Posner and colleagues proposes that attentional functions are supported by three independent but interactive networks, i.e., alerting, orienting and cognitive control 1,2 . The cognitive control network modulates inhibition and cognitive flexibility by a set of process such as planning, decision making, error detection, and execution of novel responses 3 . The orienting network regulates allocation of attention over a target or location in a voluntary-endogenous or involuntary-exogenous way, enhancing target processing while ignoring irrelevant objects/locations 4 . The alerting network is responsible of maintaining a general arousal and preparatory state for the quick detection of the expected stimulus. The alerting network supports two different functions: phasic alertness and sustained attention. Phasic alertness is modulated by warning signals and increases arousal momentarily to act quickly. Instead, sustained attention, also known as vigilance, is responsible of maintaining a continuous state of activation during long periods, to correctly detect and quickly react to stimuli in the environment 5,6 . In the past few years, it has been proposed that vigilance can be considered as two dissociated components, which modulate different behavioral responses of sustained attention 7–10 . On the one hand, executive vigilance (EV) can be defined as the ability to sustain attention for monitoring and detecting rare but critical events over an extended period. On the other hand, arousal vigilance (AV) rather reflects the capacity to quickly react to stimuli in the environment over long periods, without much control over responses 7 . How physical exercises affects these attentional functions has been studied in previous years 11–13 , either during 9 , immediately after 14 , or even after several days 15 or weeks 16 . However, and critically, the effects of acute and chronic exercise on attentional networks’ functions seem to be relatively diverse, depending on the characteristics of the exercise condition demanded (i.e., intensity 17 or duration 18 ), the attentional function assessed 19 , or even the cardio-respiratory fitness of participants 11,13,20 . Previous experimental research has shown that a single bout of exercise may be feasible to modulate the attentional networks functioning 14,21 . However, other studies did not observe an effect of a single bout of different intensities of exercise on attentional networks performance 22 . Empirical 17,23,24 and meta-analytical 11 research has shown that, although acute moderate exercise has in general a positive impact on attentional networks, there is a great variability in the observed outcomes, which seems to depend on, among other factors, the time relation between physical exercise and the cognitive task used, exercise intensity, and exercise mode. Previous studies have examined the effects of different exercise’s nature (i.e., resistance and endurance) and intensities on attentional networks’ functions using single behavioral tasks, with particular interest on the assessment of cognitive control. A study by Córdova et al. compared the effects of three different modes of an acute bout of exercise (endurance, strength, and coordination) with a control group without exercise on cognitive control in adolescents, using the revised d2-test of attention 25 . The results indicated that all three exercise groups exhibited similar improvements in performance compared to the control group. Engeroff et al. compared different intensities of resistance exercises, showing that cognitive control improved after exercising at moderate 75% and vigorous 90% intensities of the One Repetition Maximum (1RM) 14 . In a study conducted with cyclists comparing different endurance exercises, it was observed that cognitive control improved only after the highest intensity (95% of the Maximum Mean Power, MMP) and in the shortest duration (~ 3 min) condition 17 . Moreover, Mehren et al. 26 used a Go/No go task and a Flanker task to examine the effect of continuous vs. interval training endurance exercises, showing that cognitive control was improved after a moderate 30 min exercise at 50–70% of Maximum Heart Rate (HR max ) compared to 21 min of high-intensity interval training. Regarding the alerting network, the effect of acute exercise at different intensities was compared on phasic alertness in physically active elderly women 25 . The study by Córdova et al. found that acute cycling at 60, 90, or 110% of anaerobic threshold accelerated responses in a Simple RT task, a result that the authors interpreted as increased phasic alertness 25 . Concerning the orienting network, Llorens et al. 27 examined the effect of a bout of intense exercise on exogenous spatial orienting under three different conditions: at rest (without prior effort), immediately after an incremental exercise until reaching Heart Rate at the anaerobic threshold (HR AT ), and after recovery period following intense exercise. Conversely to the positive effects of acute exercise observed on phasic alertness and cognitive control, the results did not reveal any effect of intense acute exercise on the exogenous spatial task´s performance. The effects of two exercise conditions on attentional orienting were also examined on performance in a visual search task: at rest vs. immediately after an acute bout of intense exercise (15 min at HR AT ) 28 . Again, the results did not reveal any significant effect of the exercise condition on the detection of new objects. However, Sanabria et al. found that an acute bout of aerobic exercise modulates orienting, showing that the inhibition of return effect was eliminated under physical (aerobic) workload, and more interestingly, that such effect vanishes even when the exercise was performed prior to the cognitive task 29 . Considering these previous findings, results are relatively diverse on how such acute exercise intensity modulates the different attentional functions, showing positive effects as an increase in accuracy, especially in cognitive control 17,30 , or even null effects in other attentional functions 14,26 . It should be noted that most of previous research analyzing the effects of acute exercise on attentional networks’ functioning have mainly used behavioral tasks measuring a single attentional function in isolation. Importantly, in the last decades, there has been a growing effort in behavioral research to develop suitable tasks for simultaneously assessing multiple attentional functions, such as the attentional networks test (ANT) and its variations (for a review, see de Souza Almeida and colleagues 31 ). Attentional networks tasks are useful to overcome some methodological limitations, by assessing several attentional functions under the same participants’ physical and attentional state, thus reducing variability of outcomes between studies that measures one attentional component at the time with single tasks. Previous studies that have analyzed the effects of acute bout of exercise on attention performance using variations of attentional networks tasks are considerably scarce. For instance, Chang et al. compared the after-effects of spinning for 30 min at 70–85% of HR max against reading a book on attentional networks measured with the ANT 32 . The authors observed that physical exercise improved cognitive control but did not modulate phasic alertness nor orienting. A recent study investigated the effects of an acute exercise at 65% of HR max under different cognitive challenges conditions on attentional networks functioning using the ANT-Revised task 33 . Results revealed a beneficial effect of exercise on executive control after the high-challenge condition. A series of studies about the effects of exercise intensity on attentional networks functions have been conducted in our labs, showing different effects as a function of exercise condition. Using the ANT for Interactions task, Huertas et al. 34 explored the effects of three different activity conditions with a group of cyclist. They observed that, during aerobic exercise, there was an acceleration in RT and a reduction in the phasic alertness effect. Later on, using the same attentional task, the effect of caffeine intake on attentional networks’ functioning during aerobic cycling (80% of lactate threshold ) or rest were examined 35 . Results showed that exercise led to faster RT and a reduced orienting effect. Similarly, in a recent study using the ANT for Interactions and Vigilance – executive and arousal components, (i.e., the ANTI-Vea, see section 2.4 for a detailed description), it was found that moderate exercise intensity at 80% of second ventilatory threshold specifically improved RT for EV but not AV, compared to light exercise (80% of first ventilatory threshold), without impairing error rates 9 . Note that the above cited studies 9,34,35 analyzed the effect of physical effort during exercise or at rest, but not after performing exercise. Indeed, to the best of our knowledge, there are no studies that have analyzed the effects of different intensities of acute bout of exercise just after finishing it when multiple attentional and vigilance functions are simultaneously measured. Considering the relative contradictory outcomes on how acute exercise affects the functioning of the attentional networks when measured by single attentional tasks, and noting that only a few studies have addressed the effects of exercise intensities on several attentional functions measured at the same time, we decided to conduct the present study. We aimed to analyze the effects of an acute bout of low- vs. high-intensity exercise on phasic alertness, orienting, and cognitive control, as well as on executive and arousal components of vigilance just after finishing exercise. Following the previous literature 14,17,25–28 , we expected to observe improved overall performance (i.e., faster reaction times and higher accuracy), and especially a benefit in cognitive control functioning (i.e., reduced interference), after an acute bout of low-intensity than after an acute-bout of high intensity-exercise. 2. Materials and methods 2.1 Participants 36 were part of the present study. However, 6 participants were discarded from data analysis due to the following reasons: 4 because they withdraw from the study without completing all the sessions, 1 due to exclusion criteria, and another one because of technical issues with data collected with the online ANTI-Vea task. Therefore, 30 young physical active participants (21 men and 9 women), with an average age of 20.93 years (SD = 1.51 ) , participated in the study. They were undergraduate university students who did not follow a structured or supervised training plan, did not compete at federative level, and did not practice cycling or spinning more than 2 hours per week. Their average absolute MMP was of 225 W (SD = 51 ) and their average of relative MMP was of 3.34 W.Kg -1 (SD = 0.58). An a-priori estimation of sample size was conducted using G* power 3.1 36 , based on the effect size (η p 2 = .18 ) of exercise for overall RT in the ANTI sub-task of Sanchis et al. 9 . We estimated that at least 14 participants would be needed to replicate the above-mentioned effect with a power of 1-β = .95 and a significance criterion of α = .05 through a repeated-measures ANOVA with the design of the present study, that is, one within-participant factor (exercise intensity) of three levels (baseline/low-intensity/high-intensity). We decided to increase the estimated a-priori sample size and collect data from 30 participants, similar to the sample size of Sanchis et al. with the ANTI-Vea task 9 . Participation in this study was voluntary, although some participants received course credits for their participation according to the regulations of Catholic University of Valencia. All participants were properly informed regarding the potential risks and benefits of the study and signed an informed consent document prior to participation. The study was conducted according to the ethical standards of the 1964 Declaration of Helsinski (last update: Fortaleza, 2013) and approved by the Ethical Committee of the Universidad Católica de Valencia “San Vicente Martir” (project code UCV/2020–2021/173). 2.2 Material An indoor cycling trainer Cardgirus W3+ (G&G Innovation, Sabadell, Spain) was used to measure the MMP and for controlling exercise intensity during the experimental sessions. HR was monitored with a chest band by Garmin (Garmin HRM-Dual ™ , USA). The online ANTI-Vea 37,38 was run in a desktop computer from the ANTI-Vea-UGR platform ( https://anti-vea.ugr.es ). 2.3 Procedure Participants were cited at the laboratory in 3 sessions at different days, separated by at least 72 hours (average days between sessions = 8.2; SD = 4.6). In addition, 48 hours prior to the first session, aiming to familiarize the participants with the task, they completed at home the standard practice blocks of the ANTI-Vea task (i.e., three progressive practice blocks with visual feedback and half of an experimental block without visual feedback) plus one experimental block. These results were analysed with the aim to guarantee a minimum level of comprehension of the task, but these were not included in the planned statistical analyses. In the first session, the ANTI-Vea was completed as baseline before an incremental cycling physical fitness test. During the following two sessions, the ANTI-Vea was performed after a high or a low-intensity exercise in a counterbalanced order across participants. To avoid any residual fatigue, participants were asked to refrain strenuous exercise at least 72 hours before each experimental session. 2.3.1 First session: Baseline and incremental test Participants completed three experimental blocks of the ANTI-Vea task 7 that were considered as baseline (i.e., attentional functioning under rest condition). Subsequently, an incremental cycling test with an initial power of 20 W was carried out, which was increased progressively and automatically by 5 W every 15 sec, until the participant was unable to maintain a cadence above 60 rpm for more than 5 sec, or when the participant’s HR reached 95% of its theoretical maximum from Karvonen’s formula 39 . The aim of this test was to establish the individual MMP, which was used to define the exercise workload for the following sessions. MMP was calculated as the average of maximum power during 30 sec. 2.3.2 Acute bout of exercise sessions: High- vs. Low-intensity exercise The high-intensity session included an incremental exercise until the participant´s exhaustion or when the participant was unable to maintain a cadence above 60 rpm for more than 5 sec. When participant’s MMP value was between 200 W and 230 W, the workload was increased by 5 W every 40 sec. In case the participant’s MMP value was between 230 and 260 W, the workload was increased by 5 W every 35 sec and so on, i.e. for every 30 W interval, the time needed to increase the power by 5 W was reduced by 5 sec. This manipulation was done to maintain the duration of the exercise between participants. The average time for participants to reach exhaustion was 23 min 9 sec (SD = 3,1). The low-intensity session consisted of 21 min exercise, structured in a 2 min warm up cycling at 20% of participant’s MMP, following 18 min at 30% MMP, and a final cool down of 1 min at 20% MMP. HR, power output and the Rate of Perceived Exertion (RPE) were recorded during both exercise sessions to check that the manipulation of exercise intensity modulates the external and internal load. RPE scale was based on a range between 6, being the least amount of exertion, and 20 being the maximum level of exertion 40 . RPE was asked each minute during the high-intensity exercise and every five minutes during low-intensity exercise. Immediately after ending the high or low intensity exercise in each session, participants sat in front of the computer to complete three experimental blocks of the ANTI-Vea task. 2.4 Behavioral task: ANTI-Vea The online version of the ANTI-Vea task was used ( https://anti-vea.ugr.es/ ). The ANTI-Vea 7 is a behavioral task suitable to assess the independence and interactions of the attentional functions measured by the ANT for Interactions task 41 (i.e, phasic alertness, orienting and cognitive control), and two vigilance components (i.e., EV and AV). The ANTI-Vea task combines three different types of trials, which are randomly presented: ANTI (60%), EV (20%) and AV (20%). Participants completed three experimental blocks without breaks (duration of task: 16 min and 24 sec). In the ANTI trials, a string of five arrows is presented and participants had to respond according to the direction pointed by the target, i.e., the central arrow, while ignoring the direction of the surrounding flanking arrows (see Fig. 1 panel a). The target could be anticipated by an auditory warning signal and a visual spatial cue. Cognitive control was measured as a function of the interference between the flanking and target arrows, i.e., the difference between congruent trials (50% of ANTI trials) and incongruent trials (50% of ANTI trials) (see Fig. 1 panel d). Orienting was measured as a function of the location of the visual cue regarding the target position (see Fig. 1 , panel c), i.e., valid cue (33,33% of ANTI trials), invalid cue (33,33% of ANTI trials), and no cue (33,33% of ANTI trials) (see Fig. 1 panel c). Phasic alertness was measured as a function of the presence (tone condition, 50% of ANTI trials) or absence (no tone condition, 50% of ANTI trials) of the auditory warning signal presented before target onset (see Fig. 1 panel a). EV trials had the same procedure than the ANTI ones, except that the target was vertically displaced from its central position. Participants had to detect the infrequent vertical displacement of the target by pressing the space bar key, while ignoring the direction pointed by the target (see Fig. 1 , panel d). For measuring EV, hits were computed as the percentage of correct responses in EV trials And false alarms (FA) as the percentage of space bar responses in ANTI trials, that is, when the target was not largely displaced, following the procedure by Luna et al. 42 . Lastly, in AV trials, no tone, visual cue, or arrows were presented, and instead a red millisecond counter appeared in the centre of the screen, starting at 1000 and going down to zero (see Fig. 1 , panel b). Participants were asked to stop the counter as fast as they could by pressing any key of the keyboard (see Fig. 1 , panel d). For measuring AV, mean RT, SD of RT, and the percentage of lapses (i.e., responses slower than 600 ms) were computed as dependent variables in AV trials. 2.5 Statistical analyses All statistical analyses were performed using JASP software (Version 0.14.1.0, JASP Team, The Netherlands) 44 . Paired t -tests were used to analyze the effect of exercise conditions (low- vs. high-intensity) on the internal and external load (mean power output, RPE and HR). In the ANTI trials, for RT analyses, trials with incorrect responses (5.48%) and those with RT below 200 ms or above 1500 ms (0.83%) were excluded, as in Luna et al. 37 . Then, repeated-measures ANOVAs were conducted, including exercise condition (baseline, high-intensity, low-intensity), and tone (no tone, tone) for phasic alertness, cue (invalid, no cue, valid) for orienting, or congruency (incongruent, congruent) for cognitive control, as within-participant factors, and mean correct RT or the percentage of correct responses as dependent variable. Pairwise comparisons were conducted to further explore significant main effects and interactions. For EV trials, separated repeated-measures ANOVAs were conducted, with exercise (baseline, high-intensity, low-intensity) as within-participant factor and the percentage of hits, FA, or mean RT on hits (1.29% of trials with RT below 200 ms or above 1500 ms excluded) as dependent variable. Finally, for AV trials, three repeated-measures ANOVAs were performed with mean RT, SD of RT, or the percentage of lapses as dependent variable, and including exercise (baseline, high-intensity, low-intensity) as a within-participant factor. Then, to determine the available evidence in favour or against our hypotheses, Bayesian analyses for each attentional effect and vigilance measure of interest were conducted as a function of exercise conditions. For Null Hypothesis Significance Testing (NHST) analyses, the alpha level was set at p .01), moderate ( η 2 p > .06), or strong ( η 2 p > .14) effect sizes. The Cohen’s d effect size is reported in t -tests, which indicates small ( d > 0.2), medium ( d > 0.5), and large effect sizes ( d > 0.8) 45–47 . Bayesian’s results revealed whether data provide evidence supporting the alternative hypothesis with Bayes Factors (BF) as BF 10 larger than 3, or supporting the null hypothesis, when the value of BF 01 is larger than 3 48,49 . 3. Results 3.1. Exercise effect on physiological variables As expected, the load adjustment showed differences in the physiological dependent variables, evidenced by higher values in Power Output, t ( 29 ) = 10.99, p < .001, d = 2.04; Relative Power Output, t ( 29 ) = 12.395, p < . 001, d = 2.263; HR, t ( 29 ) = 15.24, p < . 001, d = 2.19; and RPE, t ( 29 ) = 17.48, p < . 001, d = 3.25, for the high than for the low intensity condition (see Table 1 ). Table 1 . Mean and standard deviation (between parentheses) of physiological variables measured at different exercising conditions. Variables High Intensity Low Intensity Power Output (W)* 109.90 (32.79) 66.87 (15.08) Relative Power Output (W.kg − 1 )* 1.63 (0.45) 1.00 (0.25) HR (bpm)* 157.02 (19.16) 118.88 (15.31) RPE * 17.67 (10.06) 10.06 (2.25) Note: Heart Rate (HR); Beats per minute (bpm); Rate of Perceived Exertion (RPE) * p < .001. 3.2. Attentional Functioning Table 2 and Figure 2 show the descriptive results across all attentional networks and effort conditions. RT analyses showed the typical main effects usually observed with the ANTI-Vea 7 , supporting the effectiveness of the task in assessing the classic attentional functions in the current study. A significant main effect of tone was observed, F( 1, 29 )= 51.14 , p<. 001 ,η 2 p =. 64, with faster responses in the tone than in the no tone condition. The main effect of orienting was also significant, F( 2, 58 )= 52.05 , p<. 001 , η 2 p =. 64 , with faster responses in the valid than in no cue, t (29)=3.76 p<. 001 , d= 0,686 and invalid trials, t (29)=10.09 p<. 001 , d= 1,84 , and faster responses in the no cue than in the invalid trials t (29)=6.36 p<. 001 , d= 1,16, p<. 001. Lastly, the main effect of congruency was also significant, F ( 1, 29 )= 20.12 , p<. 001 , η 2 p = .41 , with faster responses in the congruent than in the incongruent condition . Regarding accuracy, the main effect of visual cue was significant F( 2, 58 )= 4.84 , p= .011 , η 2 p =. 14 , with higher accuracy in invalid than valid trials, t (29)=2.84 p=. 019 , d= 0,58 , and with higher accuracy in no cue than in valid trials, t (29)=2.53 p=. 028 , d= 0,462, being not significant the difference between invalid and no cue trials, t (29)=0.31 p= . 762 , d= 0,06. The main effect of congruency was also significant, F( 1, 29 )= 10.65 , p=. 003 , η 2 p =. 26 , showing a reversed pattern of outcomes, with higher accuracy in incongruent than congruent trials. Lastly, response accuracy was not modulated by tone, F( 1, 29 )= 1.82 , p= .188 , η 2 p =. 01 (see Table 2). Table 2 Mean and SD (between parentheses) of attentional networks functions for mean correct RT (ms) and Accuracy (%) as a function of exercise condition. Attentional measures Baseline Low Intensity High Intensity Factor Levels RT Accuracy RT Accuracy RT Accuracy Alertness * Tone 656(111) 94.10(5.80) 635(85) 96.70(4.90) 632 (93) 95.10(6.80) No tone 678(107) 94.40(6.80) 673 (87) 95.10(6.00) 672 (97) 93.70(6.00) Index 22 ( 33 ) -0.30(6.00) 39( 39 ) 1.60(5.10) 41( 37 ) 1.40(4.30) Orienting Valid cue 653(110) 92.20(6.00) 641(93) 95.70(5.20) 641(101) 92.90(6.00) No cue 667(107) 94.20(5.60) 654(84) 95.90(4.90) 652(93) 94.40(6.10) Invalid 691( 11 ) 94.30(5.50) 675(99) 96.50(4.50) 671(99) 94.20(5.30) Index 38 ( 37 ) 2.10 (4.70) 33 ( 21 ) 0.80 (3.60) 30 ( 28 ) 1.30(4.70) Cognitive Control Congruent 662(111) 92.60(6.30) 648(93) 95.40(5.60) 651(99) 92.70(7.00) Incongruent 679(110) 94.50(5.60) 665(91) 96.70 (3.50) 659(97) 95.00(4.10) Index 16( 25 ) 1.90(4.30) 16( 22 ) 1.30(3.20) 8( 26 ) 2.30 (4.90) Note= RT Phasic alertness Index=No tone - Tone ; RT Orienting index= Invalid – Valid ; RT Cognitive control index= Incongruent – Congruent. ; Accuracy Phasic alertness Index=Tone – No Tone; Accuracy Orienting index= Valid – Invalid; Accuracy Cognitive control index= Congruent - Incongruent. *p< .05 between exercise conditions. 3.3. Attentional functioning and exercising condition 3.3.1 Overall performance in ANTI trials Exercise condition did not modulate the overall mean RT, F ( 2 , 58 ) = 1.52, p = . 227, η 2 p = .05. However, the overall response accuracy was influenced by exercise, F ( 2 , 58 ) = 7.49, p = .001, η 2 p = .205, showing higher values in the low (M = 96,00 %; SD = 4.40 %) than in the high intensity condition (M = 93.80%; SD = 5.60), t ( 29 ) = 3.16, p = . 005, d = 0.58, and the baseline condition, (M = 93.80%; SD = 5.20), t ( 29 ) = 3.52, p = .003, d = 0.64, with no statistical differences between high intensity and baseline, t ( 29 ) = 0.34, p = .718, d = 0.07 (see Fig. 3 ). The Bayesian analysis showed strong evidence for larger accuracy after the low intensity exercise than after high intensity exercise (BF 10 = 29.82) and during the baseline- resting condition (BF 10 = 23.11). In other words, the presence of a beneficial effect of low intensity exercise was 23 times more likely than its absence, in comparison to baseline (almost 30 times more likely in comparison with high intensity). In contrast, Bayesian analysis rather showed evidence supporting the absence of any effect of exercise for overall RT (BF 01 = 5.05). 3.3.2 Phasic alertness Exercise had a significant, albeit small, modulatory effect on phasic alertness in the RT score, F ( 2 , 58 ) = 3.20 p = .048, η 2 p = .01. The two exercise intensity conditions did not significantly differ from each other, t ( 29 ) = 0.20, p = .842 d = 0.04. However, a larger phasic alertness effect was observed in the high intensity condition compared to the baseline, t ( 29 ) = 2.97, p = .006, d = 0.54, and in the low intensity condition compared to the baseline, t ( 29 ) = 2.07, p = .047, d = 0.38. Concerning accuracy, the analysis did not reveal any significant modulation of exercise on phasic alertness F ( 2 , 58 ) = 1.44, p = .246, η 2 p = .05. The Bayesian analysis of the modulation of exercise on phasic alertness for RT showed moderate evidence for the presence of a beneficial effect of low intensity in comparison to baseline (BF 10 = 4.10), whereas evidence was inconsistent regarding the difference of high intensity against baseline (BF 10 = 1.25). In contrast, for accuracy, evidence analyzed supported the absence of any type of exercise effect (BF 01 = 5.10). 3.3.3 Orienting Exercise did not significantly influence orienting for RT, F( 4, 116 ) = 0.34, p = .854, η 2 p = .01, nor response accuracy, F( 4, 116 ) = 0.87, p = .482, η 2 p = .03. The Bayesian analysis showed evidence supporting the absence of a modulation of exercise on orienting for both RT (BF 01 = 4.57) and accuracy (BF 01 = 4.27). 3.3.4 Cognitive control Cognitive control was not modulated by exercise cognition neither for RT, F ( 2 , 58 ) = 1.31, p = .277, η 2 p = .04, nor for accuracy, F ( 2 , 58 ) = 0.63, p = .537, η 2 p = .02. The results of Bayesian analysis provided evidence supporting the absence of modulation of exercise intensity on cognitive control, both for RT (BF 01 = 2.42) and accuracy (BF 01 = 2.60). 3.3.5 Executive vigilance (EV) Exercise condition modulated the percentage of FAs, F ( 2 , 58 ) = 5.97, p = .004, η 2 p = .17. As depicted in Fig. 4 , participants showed lower percentage of FAs after the low than the high intensity exercise, t ( 29 ) = 2.9, p = .011, d = 0.53, and after the low than the baseline condition t ( 29 ) = 3.08, p = .010, d = 0.56. FAs were not significantly different between the high intensity and the baseline condition t ( 29 ) = 0.18, p = . 860, d = 0.03. Exercise did not significantly modulate the percentage of hits, F ( 2 , 58 ) = 0.07, p = . 931, η 2 p < . 01 (see Table 3 and Fig. 4 ). Furthermore, although mean RT in hits is not typically analyzed for EV in the ANTI-Vea, we nevertheless analyzed it in an exploratory way, motivated by previous findings of effect of exercise intensity on RT of EV 9 . Our results showed a significant main effect of exercise for mean RT in hits, F ( 2 , 58 ) = 3.59, p = .034, η 2 p = .11. Responses were faster after the high compared to the low intensity condition, t ( 29 ) = 2.55, p = .040, d = 0.47, while no significant differences were found between high intensity and baseline, t ( 29 ) = 1.98, p = .104, d = 0.36, nor between low intensity and baseline conditions, t ( 29 ) = 0.57, p = . 570, d = 0.19 (see Table 3 and Fig. 4 ). Table 3 Mean and SD (between parentheses) for executive vigilance (EV) scores as a function of exercise condition. EV Baseline Low Intensity High Intensity False alarms (%) 10.80 (9.20) 7.00 (7.60) 10.50 (10,00) Hits (%) 84,10 (11.00) 83,80 (12.30) 84 ,40( 13 , 20 ) Mean RT (ms) 725 (84) 731 (91) 706 (78) The Bayesian analysis showed strong evidence for fewer FAs after the low intensity exercise than after high intensity exercise (BF 10 = 26.47) and in the baseline (BF 10 = 25.71). In other words, the presence of a beneficial effect of low intensity exercise was 26 times more likely than its absence, in comparison to baseline (26 times more likely in comparison with high intensity). The analysis of RT in hits also showed substantial evidence supporting faster responses after high intensity than after low intensity (BF 10 = 10.27), with evidence supporting the lack of differences between baseline and low intensity exercise (BF 01 = 7.55). In contrast, the Bayesian analysis showed evidence supporting the absence of an effect of exercise intensity on hits (BF 01 = 4.60). 3.3.6 Arousal Vigilance (AV) Exercise condition did not modulate response RT, F ( 2 , 58 ) = 1.86, p = .172, η 2 p = .06, nor SD of RT, F ( 2 , 58 ) = 0.08, p = .919, η 2 p < .01, nor the percentage of lapses, F ( 2 , 58 ) = 0.18, p = .834, η 2 p = < . 01 (see Table 4 and Fig. 5 ). Table 4 Mean and SD (between parentheses) for arousal vigilance scores as a function of exercise condition. AV score Baseline Low Intensity High Intensity Mean RT (ms) 490.03 (67.62) 484.83 (73.78) 483.16 (71.88) SD of RT (ms) 65.95 ( 15 ) 65.61 (20.94) 64.18 (22.88) Lapses 11.40 (24.60) 10.80 (22.10) 11.00 (22.90) The results of Bayesian analysis showed evidence supporting the absence of an effect of exercise on all the dependent variables for AV: BF 01 = 4.60 for mean RT, BF 01 = 4.96 for SD of RT, and BF 01 = 5.05 for the percentage of lapses. 4. Discussion The present study aimed to analyze the effects of an acute bout of low- vs. high-intensity exercise on several attentional and vigilance components. To do so, an experimental and crossover study was conducted. Participants completed three sessions to compare attentional functioning during a baseline- resting situation with two exercise conditions (after low- vs. after high-intensity cycling) using the ANTI-Vea task. To the best of our knowledge, this study represents the first attempt to investigate the effects of an acute bout of different physical exercise intensities on phasic alertness, orienting, cognitive control, as well as EV and AV. Previous studies analyzed the effects of acute exercise performed at different intensities on the different attentional networks 14,26 , although using behavioral tasks measuring a single attentional function. However, it is worth noting that Chang et al. examined the effect of acute exercise on phasic alertness, orienting and cognitive control by using the ANT 51 , which did not measure the EV and AV 32 . Additionally, the study by Chang et al. 32 did not compare different exercise intensities. As expected, our manipulation of exercise condition on the physiological response was confirmed by the overall values of power output, relative power output, HR, and RPE. In addition, the typical main effects usually observed by the ANTI-Vea were observed in RT analyses, supporting the effectiveness of the task in measuring attentional functioning in the present study. More importantly, and regarding the effect of the exercise on attentional functioning, our results showed that, while an acute bout of low-intensity of exercise improved overall accuracy, reduced false alarms, and increased the RT score of phasic alertness, a high-intensity exercise seemed to reduce RT in the EV sub-task. In line with our predictions, overall response accuracy improved after a low-intensity exercise in comparison to both the baseline condition and after a high intensity exercise in the attentional networks sub-task. These results are consistent with previous research in which participants performed physical exercise before attentional tasks 14,20 . This beneficial effect of low-intensity exercise on response accuracy could be attributed to the fact that moderate-intensity exercise optimally increases the concentration of cortisol and catecholamines in the brain. On the other hand, exercising at higher intensity results in an excessive increase in this hormone and neurotransmitter concentration, which may not have a beneficial effect and could even be detrimental to the speed and accuracy of motor responses 52–54 . Nevertheless, and contrary to our hypothesis and previous studies in the field 9 , exercise condition did not modulated the overall RT. It is noticeable that the difference between our study and the previous one by Sanchis et al. remains in the fact that they compared the online effects of light vs. moderate intensity during exercise 9 whereas we analysed post- exercise effects. These controversy between finding obtained in the above mentioned study (cycling + manual response to stimuli during exercise) 9 and our study (response after ending the exercise) could be explained by the different cognitive and motor resources assigned during dual task or single context of response respectively. Additionally, and although exercise can increase dopamine, norepinephrine, cortisol and catecholamine concentrations during and after physical activity 20,52–54 , this unexpected result might be attributed to the fact that activating effects on RT, related with motor response, disappear more quickly than on accuracy, more related with perception and decision making, after exercise cessation 55 . In any case, differences in the effect of exercise on response depending on the contextual demands (single vs. dual task) should be further examined in future studies in which participants could be tested in all the exercise and contextual conditions in a counterbalanced order. Regarding the effect of exercise condition on attentional functioning, and contrary to our hypothesis based on previous studies 14,17,25,26 , our results showed that executive control was not modulated by exercise. However, it is important to note that our descriptive results revealed a reduced congruency effect of 13.7 ms on average with respect to other previous studies using the ANTI-Vea (e.g., 44 ms in Luna et al., 37 and 35 ms in Sanchis et al., 9 ). This reduced congruency effect, evidenced even in the baseline condition (17 ms), raises questions about the discrepancy between our study and the trend generally observed in the ANTI-Vea task, which seems to be due to different reasons. One possibility might be that participants only performed three blocks of trials in our study, while 6 blocks are typically performed, and the congruency effect has been shown to increase across blocks of trials in the ANTI-Vea 56 . It could also be plausible that this pattern is specific to the sample of participants in the present study, although this cannot be confirmed. In any case, it is worth noting that such small congruency effect may complicate the detection of significant changes due to the exercise conditions in the present study. Therefore, we consider crucial to replicate these findings in future studies, especially that involving task familiarisation, baseline, and exercise sessions conditions, to gain a more complete and accurate understanding of the modulation of online/offline exercise intensities on executive control. Concerning phasic alertness, our results showed that both exercise conditions led to a significant enhancement of alerting effect compared to the baseline based on the reduction of RT in the tone condition. However, Bayesian analysis showed that evidence was inconsistent regarding the difference between high intensity and baseline, as BF 10 < 3. Hence, our study’s results align with previous studies in terms of observing faster RT after exercise, which only occurred when taking advantage of the alerting tone. The results of Huertas et al. 34 showed faster RT during moderate aerobic than in rest condition, although contrary to our findings the exercise effect was larger in no-tone trials than in tone trials. The fact that tone reduces RT more in low intensity condition could be explained by the optimal effect of low intensity exercise in modulating the secretion of different neurochemical factors (catecholamines and cortisol). The lack of effect in high intensity exercise compared to baseline, might be due to the high intensity exercise generating excessive catecholamine and cortisol concentration according to an inverted U-shape relation between exercise intensity and hormones secretion regulating the tonic alertness response 52–54 . With regards to the functioning of the orienting network, and according to previous studies 27,28,32,33 , our results did not show any modulation of exercise on the visual cue effect. Only Llorens et al. revealed that, after the bout of high intensity exercise, only low-fit participants showed a reduced orienting (exogeneous spatial attention) effects compared to rest conditions, whereas fit participants showed similar performance in both experiment conditions 27 . It might be the case that participants of the present study (which most of them were students of Sport Sciences) were enough fit to not show any effect of exercise on orienting. Divergences among the present study also emerged with findings by Sanabria et al., showing that spatial orienting was modulated both during and after exercise in comparison with rest condition 29 . Interestingly, the differences between our results and those obtained by Sanabria et al. could be related to the different measure of the orienting function. Our study employed the ANTI-Vea, which measures facilitation of attentional orienting, whereas Sanabria et al. used a paradigm suitable to measure facilitation and inhibition of return respectively in the long and large SOA conditions. Indeed, Sanabria et al. found no effect of exercise at the short SOA, where facilitation was observed, as in our study. The modulation of exercise was exclusively observed at the long SOAs where an IOR effect was only observed in the baseline condition. Therefore, our results are coherent with those of Sanabria et al. (short SOA) and the work by Sanchis et al. using the same task as in our study, although comparing the online effects of light vs. moderate exercise, showing no modulation of orienting during exercise 9 . Future studies examining the impact of acute exercise on attention might include groups with different fitness level using different exercise intensities and baseline, and investigate different aspects of exogenous and endogenous orienting, to gain a more accurate understanding of these effects and interactions. Regarding the effect of acute exercise affects over Executive Vigilance (EV), our results showed a lower percentage of FAs after the low-intensity exercise, although without influence of exercise on hits. These results are in line with those reported by Mehren et al. who investigated the effects of acute exercise at moderate and high intensities on executive function, including functional MRI. Results showed a tendency towards improved behavioural performance in the Go/No-go task, interpreted as improved ability to inhibit a prepotent response and to sustain attention, and increased brain activation, as changes in BOLD response, in frontal areas following low intensity exercise compared to high intensity 26 . Nevertheless, our results revealed no difference between rest and high intensity condition. It is worth mentioning that mean RT on hits was also dependent on exercise intensity showing that participants were faster after performing the high than the low intensity condition. In a study aiming to investigate the acute effect of cycling at different intensities, results showed better selective attention especially for congruent stimuli 17 after the highest intensity (95% of the MMP) and in the shortest duration (~ 3 min) compared to the baseline. It is noteworthy that the high intensity exercise in our study has an average duration of 23 minutes, significantly longer than the 3 minutes duration of the above-mentioned study, which could explain the different results. Our high intensity condition involves an incremental effort until exhaustion. However, finding by Sudo et al. 53 investigating the effects of an incremental exercise to exhaustion revealed no modulation in RT within a cognitive task combining a Spatial Delayed-Response task and a Go/No-Go task. Furthermore, the controversial outcomes between our results and previous ones could be explained based on the different complexity of the task used to measure selective attention and the different attentional set ups required in the ANTI-Vea task. To deep into the influence of the time course on this effect, we explored whether there was a decrement in percentage of hits during our longer 3 blocks of ANTI-Vea task (i.e. more than 16 min) confirming no vigilance decrement in neither of the three activity conditions. Future research could extend the task to 6 blocks in order to see how performance evolves over longer times and whether vigilance decrement across time on task is modulated or not by exercise. With respect to Arousal Vigilance (AV), we observe no modulation of exercise intensities on AV scores. These results are similar to those reported by previous studies comparing the immediate and short-term effects of 35 min of aerobic (55% of MMP) cycling exercise 55 , or the meta-analysis by Chang et al. 11 . This well-known pattern of results suggests that effects of exercise on simple RT task disappear very quickly after exercise cessation. Notably, there are scarce studies as ours analysing AV specifically along with other attentional networks in a complex task, being a factor that influences vigilance performance 9,32 . Our work could complement the findings by Sanchis et al. 9 suggesting that exercise may not significantly modulate AV when assessed using a complex task performed both during and after exercise. It is interesting that after high-intensity exercise, or during exercise in Sanchis et al., responses were faster in EV, but not in AV trials, adding more evidence in favour that task demands and cognitive resources assigned to the task modulate the effect of exercise on response. It is important to note that the present study is not exempted from some limitations. The fact that the baseline session was not counterbalanced could constraint the interpretation of the differences between the rest and both exercise conditions due to practice effects. This decision was made based on the difficulties to include four experimental sessions, and trying to reduce the risk of participants dropping out of the study given its duration. We tried to mitigate this by the inclusion of a previous familiarization session at home with ANTI-Vea before the baseline session. Nevertheless, a proper counterbalancing of all conditions would have allowed us to more confidently compare the three activity conditions. In any case, it is important to consider that no large practice effects have been observed with the ANTI-Vea across the 10 sessions 57 . Similarly, a previous study examining the efficacy of the ANT and ANT for Interactions tasks over ten sessions found no evidence of an increase in phasic alertness effect between the second and third sessions 58 . Therefore, considering that our participants performed the task immediately after physical exercise, which was their third or fourth time completing it, it could be argued that the observed larger alertness effect observed with RT after the exercised, compared to baseline cannot be fully explained as a practice effect. These two studies suggests that the larger alertness effect observed with RT in the current study would not be due to the practice effect. 5. Conclusions To conclude, our results reveal that an acute bout of exercise modulates different attentional and vigilance scores but depending on the exercise intensity. First, while high intensity exercise does not modulate overall performance, low intensity exercise improves the overall accuracy in the attentional networks sub-task. Regarding the attentional functioning, a modulation of exercise over phasic alertness was observed, accelerating the response to the acoustic stimuli, although without affecting the orienting and executive control networks. With respect to the vigilance components, executive vigilance (EV) was improved by high intensity exercise, showing faster responses in hits, while low intensity exercise improved accuracy by reducing the false alarms rate compared to the other two conditions. Arousal vigilance (AV) was not modulated by the activity condition. To further clear the existing controversy in the literature, future research should compare the effect of exercise at different intensities on the attentional networks, EV and AV including participant of diverse fitness level to check the modulatory effect of fitness level and task demands on attentional functioning. Declarations Acknowledgements: To Spanish MCIN/AEI/10.13039/501100011033/, through grant number PID2020-114790GB-I00. Author Contributions: E. S-N. and F.H developed the study idea and methodology. E.S-N. collected and compiled subject’s data. E.S-N., F.L., F.H. and J.L wrote the whole paper as a team. E.S-N., F.H., F.L., and J.L completed the statistical analysis. F.L elaborated the figures. Data Availability Statement: The dataset generated during the current study is available in the OSF repository, https://osf.io/mpkej/ . Funding: Juan Lupiáñez was funded by the Spanish MCIN/AEI/10.13039/501100011033/, through grant number PID2020-114790GB-I00. References Posner, M. I. & Petersen, S. E. The attention system of the human brain. Annu Rev Neurosci 13 , 25–42. https://doi.org/10.1146/annurev.ne.13.030190.000325 (1990). Petersen, S. E. & Posner, M. I. The attention system of the human brain: 20 years after. Annu Rev Neurosci 35 , 73–89. https://doi.org/10.1146/annurev-neuro-062111-150525 (2012). Miller, E. K. The prefrontal cortex and cognitive control. Nat Rev Neurosci 1 , 59–65. https://doi.org/10.1038/35036228 (2000). Posner, M. I. Orienting of attention. Q J Exp Psychol 32 , 3–25. https://doi.org/10.1080/00335558008248231 (1980). Roca, J., Castro, C., López-Ramón, M. F. & Lupiáñez, J. Measuring vigilance while assessing the functioning of the three attentional networks: the ANTI-Vigilance task. J Neurosci Methods 198 , 312–324 https://doi.org/10.1016/j.jneumeth.2011.04.014 (2011). Husain, M. & Rorden, C. Non-spatially lateralized mechanisms in hemispatial neglect. Nat Rev Neurosci 4 , 26–36. https://doi.org/10.1038/nrn1005 (2003). Luna, F. G., Marino, J., Roca, J. & Lupiáñez, J. Executive and arousal vigilance decrement in the context of the attentional networks: The ANTI-Vea task. J Neurosci Methods 306 , 77–87. https://doi.org/10.1016/j.jneumeth.2018.05.011 (2018). Luna, F. G., Román-Caballero, R., Barttfeld, P., Lupiáñez, J. & Martín-Arévalo, E. A High-Definition tDCS and EEG study on attention and vigilance: Brain stimulation mitigates the executive but not the arousal vigilance decrement. Neuropsychologia 142 , 107447. https://doi.org/10.1016/j.neuropsychologia.2020.107447 (2020). Sanchis, C., Blasco Herraiz, E., Luna, F. & Lupiáñez, J. Effects of caffeine intake and exercise intensity on executive and arousal vigilance. Sci Rep 10 , 8393. https://doi.org/10.1038/s41598-020-65197-5 (2020). Luna, F. G. et al. Different oscillatory rhythms anticipate failures in executive and arousal vigilance. Front Cognit 2 . https://doi.org/10.3389/fcogn.2023.1128442 (2023). Chang, Y., Labban, J., Gapin, J. & Etnier, J. The effects of acute exercise on cognitive performance: A meta-analysis. Brain Res 1453 , 87–101. https://doi.org/10.1016/j.brainres.2012.02.068 (2012). Donnelly, J. E. et al. Physical activity, fitness, cognitive function, and academic achievement in children: A systematic review. Med Sci Sports Exerc. 48 , 1197–1222. https://doi.org/10.1249/MSS.0000000000000901 (2016). Etnier, J. L. et al. The influence of physical fitness and exercise upon cognitive functioning: a meta-analysis. J Sport Exerc Psychol 19 , 249–277. https://doi.org/10.1123/jsep.19.3.249 (1997). Engeroff, T., Banzer, W. & Niederer, D. The impact of regular activity and exercise intensity on the acute effects of resistance exercise on cognitive function. Scand J Med Sci Sports 32 , 94–105. https://doi.org/10.1111/sms.14050 (2022). ten Haaf, T. et al. Changes in choice reaction time during and after 8 days exhaustive cycling are not related to changes in physical performance. Int J Sports Physiol Perform 13 , 428–433. https://doi.org/10.1123/ijspp.2017-0218 (2018). Dupuy, O. et al. Effect of overreaching on cognitive performance and related cardiac autonomic control. Scand J Med Sci Sports 24, 234–242. https://doi.org/10.1111/j.1600-0838.2012.01465.x (2014). Kunzler, M. R. & Carpes, F. P. Intense cycling exercise improves acute cognitive responses. Int J Sports Med 41 , 879–884. 10.1055/a-1114-6170 (2020). Crush, E. A. & Loprinzi, P. D. Dose-response effects of exercise duration and recovery on cognitive functioning. Percept Mot Skills 124 , 1164–1193. https://doi.org/10.1177/0031512517726920 (2017). Chang, Y.-K. & Etnier, J. L. Effects of an acute bout of localized resistance exercise on cognitive performance in middle-aged adults: A randomized controlled trial study. Psychol Sport Exerc 10 , 19–24. https://doi.org/10.1016/j.psychsport.2008.05.004 (2009). McMorris, T. & Hale, B. J. Differential effects of differing intensities of acute exercise on speed and accuracy of cognition: A meta-analytical investigation. Brain Cogn 80 , 338–351. https://doi.org/10.1016/j.bandc.2012.09.001 (2012). Irwin, C., Campagnolo, N., Iudakhina, E., Cox, G. R. & Desbrow, B. Effects of acute exercise, dehydration and rehydration on cognitive function in well-trained athletes. J Sports Sci 36 , 247–255. https://doi.org/10.1080/02640414.2017.1298828 (2018). Stroth, S. et al. Physical fitness, but not acute exercise modulates event-related potential indices for executive control in healthy adolescents. Brain Res 1269 , 114–124. https://doi.org/10.1016/j.brainres.2009.02.073 (2009). Moore, R., Romine, Mathew., O’connor, P. & Tomporowski, P. The influence of exercise-induced fatigue on cognitive function. J Sports Sci 30 , 841–850. https://doi.org/10.1080/02640414.2012.675083 (2012). Zhou, F. & Qin, C. Acute moderate-intensity exercise generally enhances attentional resources related to perceptual processing. Front psychol 10 . https://doi.org/10.3389/fpsyg.2019.02547 (2019). Córdova, C., Silva, V. C., Moraes, C. F., Simões, H. G. & Nóbrega, O. T. Acute exercise performed close to the anaerobic threshold improves cognitive performance in elderly females. Braz J Med Biol Res 42 , 458–464. https://doi.org/10.1590/S0100-879X2009000500010 (2009). Mehren, A. et al. Intensity-dependent effects of acute exercise on executive function. Neural Plast 2019 . https://doi.org/10.1155/2019/8608317 (2019). Llorens, F., Sanabria, D. & Huertas, F. The influence of acute intense exercise on exogenous spatial attention depends on physical fitness level. Exp Psychol 62 , 20–29. https://doi.org/10.1027/1618-3169/a000270 (2014). Llorens, F., Sanabria, D., Huertas, F., Molina, E. & Bennett, S. Intense physical exercise reduces overt attentional capture. J Sport Exercise Psy 37 , 559–564. https://doi.org/10.1123/jsep.2015-0087 (2015). Sanabria, D. et al. Effects of acute aerobic exercise on exogenous spatial attention. Psychol Sport Exerc 12 , 570–574. https://doi.org/10.1016/j.psychsport.2011.04.002 (2011). Senécal, I., Howarth, S. J., Wells, G. D., Raymond, I. & Mior, S. The impact of moderate and high intensity cardiovascular exertion on sub-elite soccer referee’s cognitive performance: A lab-based study. J Sci Med Sport 20 , 618–625. https://doi.org/10.52082/jssm.2021.618 (2021). de Souza Almeida, R., Faria-Jr, A. & Klein, R. M. On the origins and evolution of the Attention Network Tests. Neurosci Biobehav Rev 126 , 560–572. https://doi.org/10.1016/j.neubiorev.2021.02.028 (2021). Chang, Y.-K., Pesce, C., Chiang, Y.-T., Kuo, C.-Y. & Fong, D.-Y. Antecedent acute cycling exercise affects attention control: an ERP study using attention network test. Front Hum Neurosci 9 , 156. https://doi.org/10.3389/fnhum.2015.00156 (2015). Anzeneder, S., Zehnder, C., Martin-Niedecken, A. L., Schmidt, M. & Benzing, V. Acute exercise and children’s cognitive functioning: What is the optimal dose of cognitive challenge? Psychol Sport Exerc 66 , 102404. https://doi.org/10.1016/j.psychsport.2023.102404 (2023). Huertas, F., Zahonero, J., Sanabria, D. & Lupiáñez, J. Functioning of the attentional networks at rest vs. during acute bouts of aerobic exercise. J Sport Exercise Psy 33 , 649–665. https://doi.org/10.1123/jsep.33.5.649 (2011). Huertas, F., Blasco, E., Moratal, C. & Lupiañez, J. Caffeine intake modulates the functioning of the attentional networks depending on consumption habits and acute exercise demands. Sci Rep 9 , 10043. https://doi.org/10.1038/s41598-019-46524-x (2019). Faul, F., Erdfelder, E., Lang, A.-G. & Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39 , 175–191. https://doi.org/10.3758/bf03193146 (2007). Luna, F. G., Roca, J., Martín-Arévalo, E. & Lupiáñez, J. Measuring attention and vigilance in the laboratory vs. online: The split-half reliability of the ANTI-Vea. Behav Res 53 , 1124–1147. https://doi.org/10.3758/s13428-020-01483-4 (2021). Coll-Martín, T. et al. The ANTI-Vea-UGR Platform: A Free Online Resource To Measure Attentional Networks (Alertness, Orienting, and Executive Control) Functioning and Executive/Arousal Vigilance . https://doi.org/10.20944/preprints202306.1031.v1 (2023) Karvonen, M. J., Kentala, E. & Mustala, O. The effects of training on heart rate; a longitudinal study. Ann Med Exp Biol Fenn 35 , 307–315 (1957). Borg, G. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 14 , 377–381. https://doi.org/10.1249/00005768-198205000-00012 (1982). Callejas, A., Lupianez, J. & Tudela, P. The three attentional networks: On their independence and interactions. Brain Cogn 54 , 225–227. https://doi.org/10.1016/j.bandc.2004.02.012 (2004). Luna, F. G., Barttfeld, P., Martín-Arévalo, E. & Lupiáñez, J. The ANTI-Vea task: Analyzing the executive and arousal vigilance decrements while measuring the three attentional networks. Psicológica 42 , 1–26. https://doi.org/10.2478/psicolj-2021-0001 (2021). Cásedas, L., Cebolla, A. & Lupiáñez, J. Individual differences in dispositional mindfulness predict attentional networks and vigilance performance. Mindfulness 13 , 967–981. https://doi.org/10.1007/s12671-022-01850-6 (2022). JASP Team. https://jasp-stats.org/ . Cohen, J. Statistical Power Analysis for the Behavioral Sciences . (L. Erlbaum Associates, Hillsdale, N.J, 1988). Cumming, G. The new statistics: Why and how. Psychol Sci 25 , 7–29. https://doi.org/10.1177/0956797613504966 (2014). Kelley, K. & Preacher, K. J. On effect size. Psychol Methods 17 , 137–152. https://doi.org/10.1037/a0028086 (2012). Jarosz, A. F. & Wiley, J. What are the odds? A practical guide to computing and reporting bayes factors. J Probl Solving 7 . https://doi.org/10.7771/1932-6246.1167 (2014). Wagenmakers, E.-J. et al. Bayesian inference for psychology. Part II: Example applications with JASP. Psychon Bull Rev 25 , 58–76. https://doi.org/10.3758/s13423-017-1323-7 (2018). Morey, R. Confidence intervals from normalized data: A correction to Cousineau (2005). Quant Meth Psych 4 . https://doi.org/10.20982/tqmp.04.2.p061. (2008). Fan, J., McCandliss, B. D., Sommer, T., Raz, A. & Posner, M. I. Testing the efficiency and independence of attentional networks. J Cogn Neurosci 14 , 340–347. https://doi.org/10.1162/089892902317361886 (2002). Cooper, C. J. Anatomical and physiological mechanisms of arousal, with special reference to the effects of exercise. Ergonomics 16 , 601–609. https://doi.org/10.1080/00140137308924551 (1973). Sudo, M. et al. Executive function after exhaustive exercise. Eur J Appl Physiol 117 , 2029–2038. https://doi.org/10.1016/j.brainres.2009.02.073 (2017). McMorris, T. Exercise-Cognition Interaction: Neuroscience Perspectives . (Academic Press, 2015). Audiffren, M., Tomporowski, P. D. & Zagrodnik, J. Acute aerobic exercise and information processing: energizing motor processes during a choice reaction time task. Acta Psychol (Amst) 129 , 410–419. https://doi.org/10.1016/j.actpsy.2008.09.006 (2008). Luna, F. G., Tortajada, M., Martín-Arévalo, E., Botta, F. & Lupiáñez, J. A vigilance decrement comes along with an executive control decrement: Testing the resource-control theory. Psychon Bull Rev. https://doi.org/10.3758/s13423-022-02089-x (2022) Gabriela, A. & Anahí, Y. Estabilidad y confiabilidad en la tarea ANTI-Vea online. Manuscript in preparation . Ishigami, Y. & Klein, R. M. Repeated measurement of the components of attention using two versions of the Attention Network Test (ANT): Stability, isolability, robustness, and reliability. J Neurosci Methods 190 , 117–128. https://doi.org/10.1016/j.jneumeth.2010.04.019 (2010). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 28 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 31 May, 2024 Reviews received at journal 20 May, 2024 Reviews received at journal 17 May, 2024 Reviewers agreed at journal 03 May, 2024 Reviewers agreed at journal 02 May, 2024 Reviewers invited by journal 01 May, 2024 Editor assigned by journal 01 May, 2024 Editor invited by journal 14 Apr, 2024 Submission checks completed at journal 14 Apr, 2024 First submitted to journal 20 Feb, 2024 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-3973814","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":273956661,"identity":"0d46a183-f527-43c1-8f08-5ab4ede0718d","order_by":0,"name":"Enrique Sanchis-Navarro","email":"","orcid":"","institution":"Catholic University of Valencia “San Vicente Mártir”","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Enrique","middleName":"","lastName":"Sanchis-Navarro","suffix":""},{"id":273956662,"identity":"ea0b6f25-f353-4f30-b0e9-dc21ca5ee86a","order_by":1,"name":"Fernando Gabriel Luna","email":"","orcid":"","institution":"Universidad Nacional de Córdoba","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fernando","middleName":"Gabriel","lastName":"Luna","suffix":""},{"id":273956663,"identity":"b8208a8f-722d-47ee-848f-04d77fd724f2","order_by":2,"name":"Juan Lupiañez","email":"","orcid":"","institution":"University of Granada","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Juan","middleName":"","lastName":"Lupiañez","suffix":""},{"id":273956664,"identity":"7a061bae-d886-44d2-94a3-a8bd85f23794","order_by":3,"name":"Florentino Huertas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYBAC9nYIzQPEbFAx5gN4tfAcBlMGcC0SQDqBKC0MSFp4DPBrYWY+9uHjjj8y5uwNbI95Ku7V8fef+Sbxs41BTr4Blxa25JkzzxjwWPYcYDfmOVMsIXEjd5tkbxuDsQEOL9kz8xgz87YZ8BjcSGCT5m1LkGC4wbtNmuEMQ+IGnA4DavkL1/IvQUL+/JlnIC3183E6DKiFEa6lIUHC4EAOmzRDBUMCAw6HgfzC2NtmzGNw5mCb5JxjCZIbb6QZW/ZUSBhuwKWFvfkww882OXuD483HJN7UJPDLnT/88MYPAxt5XCGGBBhRlEgQVD8KRsEoGAWjADcAABsXTFpNR+xnAAAAAElFTkSuQmCC","orcid":"","institution":"Catholic University of Valencia “San Vicente Mártir”","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Florentino","middleName":"","lastName":"Huertas","suffix":""}],"badges":[],"createdAt":"2024-02-20 20:44:43","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3973814/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3973814/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-77175-2","type":"published","date":"2024-10-28T16:20:36+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":51563691,"identity":"1f68a36d-457b-4a62-943a-1d0049252862","added_by":"auto","created_at":"2024-02-23 18:47:05","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1544870,"visible":true,"origin":"","legend":"\u003cp\u003eANTI-Vea design. Experimental procedure and stimuli sequence of (a) both ANTI and executive vigilance trials and (b) arousal vigilance trials. (c) Example of visual cue conditions. (d) Correct responses for each type of trial. Figure modified from Luna et al. \u003csup\u003e43\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"Figure1ANTIVea.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3973814/v1/33824109b6cd3b2a3c8f20df.jpg"},{"id":51563692,"identity":"1c55702a-4f9b-4864-8905-f6383be38767","added_by":"auto","created_at":"2024-02-23 18:47:05","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1356546,"visible":true,"origin":"","legend":"\u003cp\u003eAttentional RT index. Color dots represents the mean and bars the 95% confidence intervals of the mean computed by the Cosineau method, corrected by Morey (2008) \u003csup\u003e50\u003c/sup\u003e. Gray dots represent each participant’ score on each exercise condition, linked to each other through gray lines.\u003c/p\u003e","description":"","filename":"Figure2ANTIscoresRTbyExercise.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3973814/v1/c3a18b570c55a56c7eb57a78.jpg"},{"id":51563693,"identity":"0fa590e2-74f9-4311-bf14-820b39c5e006","added_by":"auto","created_at":"2024-02-23 18:47:05","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":889583,"visible":true,"origin":"","legend":"\u003cp\u003eOverall performance in ANTI trials. Color dots represents the mean and bars the 95% confidence intervals of the mean computed by the Cosineau method, corrected by Morey (2008) \u003csup\u003e50\u003c/sup\u003e. Gray dots represent each participant’ score on each exercise condition, linked to each other through gray lines.\u003c/p\u003e","description":"","filename":"Figure3OverallANTIbyExercise.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3973814/v1/722a1b439eb6e58757a3c85f.jpg"},{"id":51564214,"identity":"442167c8-e145-4cff-9ff5-b1ea269f5fab","added_by":"auto","created_at":"2024-02-23 18:55:05","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1333049,"visible":true,"origin":"","legend":"\u003cp\u003eOverall performance in EV. Color dots represents the mean and bars the 95% confidence intervals of the mean computed by the Cosineau method, corrected by Morey (2008) \u003csup\u003e50\u003c/sup\u003e.\u0026nbsp; Gray dots represent each participant’ score on each exercise condition, linked to each other through gray lines.\u003c/p\u003e","description":"","filename":"Figure4OverallEVbyExercise.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3973814/v1/60c19372d008dd33f94f2be5.jpg"},{"id":51563695,"identity":"a894b22b-9cdc-45f3-ae6d-6f2fe0ac006d","added_by":"auto","created_at":"2024-02-23 18:47:05","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1226004,"visible":true,"origin":"","legend":"\u003cp\u003eOverall performance in AV. Color dots represents the mean and bars the 95% confidence intervals of the mean computed by the Cosineau method, corrected by Morey (2008) \u003csup\u003e50\u003c/sup\u003e.\u0026nbsp; Gray dots represent each participant’ score on each exercise condition, linked to each other through gray lines.\u003c/p\u003e","description":"","filename":"Figure5OverallAVbyExercise.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3973814/v1/94c31b3c0051b78f72db5dee.jpg"},{"id":68207319,"identity":"3d2dfc34-03de-480b-853b-239267371813","added_by":"auto","created_at":"2024-11-04 16:36:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7279498,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3973814/v1/48c9892c-ea7f-4494-9235-0a5db461d363.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eEffect of an acute bout of high- vs. low-intensity physical exercise on attentional networks.\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAttention comprises a set of cognitive processes highly involved in daily life activities, such as working, studying, and sport tasks. The attentional networks model by Posner and colleagues proposes that attentional functions are supported by three independent but interactive networks, i.e., alerting, orienting and cognitive control \u003csup\u003e1,2\u003c/sup\u003e. The cognitive control network modulates inhibition and cognitive flexibility by a set of process such as planning, decision making, error detection, and execution of novel responses \u003csup\u003e3\u003c/sup\u003e. The orienting network regulates allocation of attention over a target or location in a voluntary-endogenous or involuntary-exogenous way, enhancing target processing while ignoring irrelevant objects/locations \u003csup\u003e4\u003c/sup\u003e. The alerting network is responsible of maintaining a general arousal and preparatory state for the quick detection of the expected stimulus. The alerting network supports two different functions: phasic alertness and sustained attention. Phasic alertness is modulated by warning signals and increases arousal momentarily to act quickly. Instead, sustained attention, also known as vigilance, is responsible of maintaining a continuous state of activation during long periods, to correctly detect and quickly react to stimuli in the environment \u003csup\u003e5,6\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn the past few years, it has been proposed that vigilance can be considered as two dissociated components, which modulate different behavioral responses of sustained attention \u003csup\u003e7\u0026ndash;10\u003c/sup\u003e. On the one hand, executive vigilance (EV) can be defined as the ability to sustain attention for monitoring and detecting rare but critical events over an extended period. On the other hand, arousal vigilance (AV) rather reflects the capacity to quickly react to stimuli in the environment over long periods, without much control over responses \u003csup\u003e7\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHow physical exercises affects these attentional functions has been studied in previous years \u003csup\u003e11\u0026ndash;13\u003c/sup\u003e, either during \u003csup\u003e9\u003c/sup\u003e, immediately after \u003csup\u003e14\u003c/sup\u003e, or even after several days \u003csup\u003e15\u003c/sup\u003e or weeks \u003csup\u003e16\u003c/sup\u003e. However, and critically, the effects of acute and chronic exercise on attentional networks\u0026rsquo; functions seem to be relatively diverse, depending on the characteristics of the exercise condition demanded (i.e., intensity \u003csup\u003e17\u003c/sup\u003e or duration \u003csup\u003e18\u003c/sup\u003e), the attentional function assessed \u003csup\u003e19\u003c/sup\u003e, or even the cardio-respiratory fitness of participants \u003csup\u003e11,13,20\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePrevious experimental research has shown that a single bout of exercise may be feasible to modulate the attentional networks functioning \u003csup\u003e14,21\u003c/sup\u003e. However, other studies did not observe an effect of a single bout of different intensities of exercise on attentional networks performance \u003csup\u003e22\u003c/sup\u003e. Empirical \u003csup\u003e17,23,24\u003c/sup\u003e and meta-analytical \u003csup\u003e11\u003c/sup\u003e research has shown that, although acute moderate exercise has in general a positive impact on attentional networks, there is a great variability in the observed outcomes, which seems to depend on, among other factors, the time relation between physical exercise and the cognitive task used, exercise intensity, and exercise mode.\u003c/p\u003e \u003cp\u003ePrevious studies have examined the effects of different exercise\u0026rsquo;s nature (i.e., resistance and endurance) and intensities on attentional networks\u0026rsquo; functions using single behavioral tasks, with particular interest on the assessment of cognitive control. A study by C\u0026oacute;rdova et al. compared the effects of three different modes of an acute bout of exercise (endurance, strength, and coordination) with a control group without exercise on cognitive control in adolescents, using the revised d2-test of attention \u003csup\u003e25\u003c/sup\u003e. The results indicated that all three exercise groups exhibited similar improvements in performance compared to the control group. Engeroff et al. compared different intensities of resistance exercises, showing that cognitive control improved after exercising at moderate 75% and vigorous 90% intensities of the One Repetition Maximum (1RM) \u003csup\u003e14\u003c/sup\u003e. In a study conducted with cyclists comparing different endurance exercises, it was observed that cognitive control improved only after the highest intensity (95% of the Maximum Mean Power, MMP) and in the shortest duration (~\u0026thinsp;3 min) condition \u003csup\u003e17\u003c/sup\u003e. Moreover, Mehren et al. \u003csup\u003e26\u003c/sup\u003e used a Go/No go task and a Flanker task to examine the effect of continuous vs. interval training endurance exercises, showing that cognitive control was improved after a moderate 30 min exercise at 50\u0026ndash;70% of Maximum Heart Rate (HR\u003csub\u003emax\u003c/sub\u003e) compared to 21 min of high-intensity interval training.\u003c/p\u003e \u003cp\u003eRegarding the alerting network, the effect of acute exercise at different intensities was compared on phasic alertness in physically active elderly women \u003csup\u003e25\u003c/sup\u003e. The study by C\u0026oacute;rdova et al. found that acute cycling at 60, 90, or 110% of anaerobic threshold accelerated responses in a Simple RT task, a result that the authors interpreted as increased phasic alertness \u003csup\u003e25\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConcerning the orienting network, Llorens et al. \u003csup\u003e27\u003c/sup\u003e examined the effect of a bout of intense exercise on exogenous spatial orienting under three different conditions: at rest (without prior effort), immediately after an incremental exercise until reaching Heart Rate at the anaerobic threshold (HR\u003csub\u003eAT\u003c/sub\u003e), and after recovery period following intense exercise. Conversely to the positive effects of acute exercise observed on phasic alertness and cognitive control, the results did not reveal any effect of intense acute exercise on the exogenous spatial task\u0026acute;s performance. The effects of two exercise conditions on attentional orienting were also examined on performance in a visual search task: at rest vs. immediately after an acute bout of intense exercise (15 min at HR\u003csub\u003eAT\u003c/sub\u003e) \u003csup\u003e28\u003c/sup\u003e. Again, the results did not reveal any significant effect of the exercise condition on the detection of new objects. However, Sanabria et al. found that an acute bout of aerobic exercise modulates orienting, showing that the inhibition of return effect was eliminated under physical (aerobic) workload, and more interestingly, that such effect vanishes even when the exercise was performed prior to the cognitive task \u003csup\u003e29\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsidering these previous findings, results are relatively diverse on how such acute exercise intensity modulates the different attentional functions, showing positive effects as an increase in accuracy, especially in cognitive control \u003csup\u003e17,30\u003c/sup\u003e, or even null effects in other attentional functions \u003csup\u003e14,26\u003c/sup\u003e. It should be noted that most of previous research analyzing the effects of acute exercise on attentional networks\u0026rsquo; functioning have mainly used behavioral tasks measuring a single attentional function in isolation. Importantly, in the last decades, there has been a growing effort in behavioral research to develop suitable tasks for simultaneously assessing multiple attentional functions, such as the attentional networks test (ANT) and its variations (for a review, see de Souza Almeida and colleagues \u003csup\u003e31\u003c/sup\u003e). Attentional networks tasks are useful to overcome some methodological limitations, by assessing several attentional functions under the same participants\u0026rsquo; physical and attentional state, thus reducing variability of outcomes between studies that measures one attentional component at the time with single tasks.\u003c/p\u003e \u003cp\u003ePrevious studies that have analyzed the effects of acute bout of exercise on attention performance using variations of attentional networks tasks are considerably scarce. For instance, Chang et al. compared the after-effects of spinning for 30 min at 70\u0026ndash;85% of HR\u003csub\u003emax\u003c/sub\u003e against reading a book on attentional networks measured with the ANT \u003csup\u003e32\u003c/sup\u003e. The authors observed that physical exercise improved cognitive control but did not modulate phasic alertness nor orienting. A recent study investigated the effects of an acute exercise at 65% of HR\u003csub\u003emax\u003c/sub\u003e under different cognitive challenges conditions on attentional networks functioning using the ANT-Revised task \u003csup\u003e33\u003c/sup\u003e. Results revealed a beneficial effect of exercise on executive control after the high-challenge condition.\u003c/p\u003e \u003cp\u003eA series of studies about the effects of exercise intensity on attentional networks functions have been conducted in our labs, showing different effects as a function of exercise condition. Using the ANT for Interactions task, Huertas et al. \u003csup\u003e34\u003c/sup\u003e explored the effects of three different activity conditions with a group of cyclist. They observed that, during aerobic exercise, there was an acceleration in RT and a reduction in the phasic alertness effect. Later on, using the same attentional task, the effect of caffeine intake on attentional networks\u0026rsquo; functioning during aerobic cycling (80% of lactate threshold ) or rest were examined \u003csup\u003e35\u003c/sup\u003e. Results showed that exercise led to faster RT and a reduced orienting effect. Similarly, in a recent study using the ANT for Interactions and Vigilance \u0026ndash; executive and arousal components, (i.e., the ANTI-Vea, see section \u003cspan refid=\"Sec8\" class=\"InternalRef\"\u003e2.4\u003c/span\u003e for a detailed description), it was found that moderate exercise intensity at 80% of second ventilatory threshold specifically improved RT for EV but not AV, compared to light exercise (80% of first ventilatory threshold), without impairing error rates \u003csup\u003e9\u003c/sup\u003e. Note that the above cited studies \u003csup\u003e9,34,35\u003c/sup\u003e analyzed the effect of physical effort during exercise or at rest, but not after performing exercise. Indeed, to the best of our knowledge, there are no studies that have analyzed the effects of different intensities of acute bout of exercise just after finishing it when multiple attentional and vigilance functions are simultaneously measured.\u003c/p\u003e \u003cp\u003eConsidering the relative contradictory outcomes on how acute exercise affects the functioning of the attentional networks when measured by single attentional tasks, and noting that only a few studies have addressed the effects of exercise intensities on several attentional functions measured at the same time, we decided to conduct the present study. We aimed to analyze the effects of an acute bout of low- vs. high-intensity exercise on phasic alertness, orienting, and cognitive control, as well as on executive and arousal components of vigilance just after finishing exercise. Following the previous literature \u003csup\u003e14,17,25\u0026ndash;28\u003c/sup\u003e, we expected to observe improved overall performance (i.e., faster reaction times and higher accuracy), and especially a benefit in cognitive control functioning (i.e., reduced interference), after an acute bout of low-intensity than after an acute-bout of high intensity-exercise.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Participants\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e36 were part of the present study. However, 6 participants were discarded from data analysis due to the following reasons: 4 because they withdraw from the study without completing all the sessions, 1 due to exclusion criteria, and another one because of technical issues with data collected with the online ANTI-Vea task. Therefore, 30 young physical active participants (21 men and 9 women), with an average age of 20.93 years \u003cem\u003e(SD\u0026thinsp;=\u003c/em\u003e\u0026thinsp;1.51\u003cem\u003e)\u003c/em\u003e, participated in the study. They were undergraduate university students who did not follow a structured or supervised training plan, did not compete at federative level, and did not practice cycling or spinning more than 2 hours per week. Their average absolute MMP was of 225 W \u003cem\u003e(SD\u0026thinsp;=\u003c/em\u003e\u0026thinsp;51\u003cem\u003e)\u003c/em\u003e and their average of relative MMP was of 3.34 W.Kg\u003csup\u003e-1\u003c/sup\u003e\u003cem\u003e(SD\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.58). An a-priori estimation of sample size was conducted using G* power 3.1 \u003csup\u003e36\u003c/sup\u003e, based on the effect size \u003cem\u003e(η\u003c/em\u003e\u003csup\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.18 \u003cem\u003e)\u003c/em\u003e of exercise for overall RT in the ANTI sub-task of Sanchis et al. \u003csup\u003e9\u003c/sup\u003e. We estimated that at least 14 participants would be needed to replicate the above-mentioned effect with a power of 1-β\u0026thinsp;=\u0026thinsp;.95 and a significance criterion of α\u0026thinsp;=\u0026thinsp;.05 through a repeated-measures ANOVA with the design of the present study, that is, one within-participant factor (exercise intensity) of three levels (baseline/low-intensity/high-intensity). We decided to increase the estimated a-priori sample size and collect data from 30 participants, similar to the sample size of Sanchis et al. with the ANTI-Vea task \u003csup\u003e9\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eParticipation in this study was voluntary, although some participants received course credits for their participation according to the regulations of Catholic University of Valencia. All participants were properly informed regarding the potential risks and benefits of the study and signed an informed consent document prior to participation. The study was conducted according to the ethical standards of the 1964 Declaration of Helsinski (last update: Fortaleza, 2013) and approved by the Ethical Committee of the Universidad Cat\u0026oacute;lica de Valencia \u0026ldquo;San Vicente Martir\u0026rdquo; (project code UCV/2020\u0026ndash;2021/173).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Material\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAn indoor cycling trainer Cardgirus W3+ (G\u0026amp;G Innovation, Sabadell, Spain) was used to measure the MMP and for controlling exercise intensity during the experimental sessions. HR was monitored with a chest band by Garmin (Garmin HRM-Dual\u003csup\u003e\u0026trade;\u003c/sup\u003e, USA). The online ANTI-Vea \u003csup\u003e37,38\u003c/sup\u003e was run in a desktop computer from the ANTI-Vea-UGR platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://anti-vea.ugr.es\u003c/span\u003e\u003cspan address=\"https://anti-vea.ugr.es\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Procedure\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eParticipants were cited at the laboratory in 3 sessions at different days, separated by at least 72 hours (average days between sessions\u0026thinsp;=\u0026thinsp;8.2; \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.6). In addition, 48 hours prior to the first session, aiming to familiarize the participants with the task, they completed at home the standard practice blocks of the ANTI-Vea task (i.e., three progressive practice blocks with visual feedback and half of an experimental block without visual feedback) plus one experimental block. These results were analysed with the aim to guarantee a minimum level of comprehension of the task, but these were not included in the planned statistical analyses. In the first session, the ANTI-Vea was completed as baseline before an incremental cycling physical fitness test. During the following two sessions, the ANTI-Vea was performed after a high or a low-intensity exercise in a counterbalanced order across participants. To avoid any residual fatigue, participants were asked to refrain strenuous exercise at least 72 hours before each experimental session.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1 First session: Baseline and incremental test\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eParticipants completed three experimental blocks of the ANTI-Vea task \u003csup\u003e7\u003c/sup\u003e that were considered as baseline (i.e., attentional functioning under rest condition). Subsequently, an incremental cycling test with an initial power of 20 W was carried out, which was increased progressively and automatically by 5 W every 15 sec, until the participant was unable to maintain a cadence above 60 rpm for more than 5 sec, or when the participant\u0026rsquo;s HR reached 95% of its theoretical maximum from Karvonen\u0026rsquo;s formula \u003csup\u003e39\u003c/sup\u003e. The aim of this test was to establish the individual MMP, which was used to define the exercise workload for the following sessions. MMP was calculated as the average of maximum power during 30 sec.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2 Acute bout of exercise sessions: High- vs. Low-intensity exercise\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003e The high-intensity session included an incremental exercise until the participant\u0026acute;s exhaustion or when the participant was unable to maintain a cadence above 60 rpm for more than 5 sec. When participant\u0026rsquo;s MMP value was between 200 W and 230 W, the workload was increased by 5 W every 40 sec. In case the participant\u0026rsquo;s MMP value was between 230 and 260 W, the workload was increased by 5 W every 35 sec and so on, i.e. for every 30 W interval, the time needed to increase the power by 5 W was reduced by 5 sec. This manipulation was done to maintain the duration of the exercise between participants. The average time for participants to reach exhaustion was 23 min 9 sec (SD\u0026thinsp;=\u0026thinsp;3,1).\u003c/p\u003e\u003cp\u003eThe low-intensity session consisted of 21 min exercise, structured in a 2 min warm up cycling at 20% of participant\u0026rsquo;s MMP, following 18 min at 30% MMP, and a final cool down of 1 min at 20% MMP.\u003c/p\u003e\u003cp\u003eHR, power output and the Rate of Perceived Exertion (RPE) were recorded during both exercise sessions to check that the manipulation of exercise intensity modulates the external and internal load. RPE scale was based on a range between 6, being the least amount of exertion, and 20 being the maximum level of exertion \u003csup\u003e40\u003c/sup\u003e. RPE was asked each minute during the high-intensity exercise and every five minutes during low-intensity exercise. Immediately after ending the high or low intensity exercise in each session, participants sat in front of the computer to complete three experimental blocks of the ANTI-Vea task.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Behavioral task: ANTI-Vea\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe online version of the ANTI-Vea task was used (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://anti-vea.ugr.es/\u003c/span\u003e\u003cspan address=\"https://anti-vea.ugr.es/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e The ANTI-Vea \u003csup\u003e7\u003c/sup\u003e is a behavioral task suitable to assess the independence and interactions of the attentional functions measured by the ANT for Interactions task \u003csup\u003e41\u003c/sup\u003e (i.e, phasic alertness, orienting and cognitive control), and two vigilance components (i.e., EV and AV). The ANTI-Vea task combines three different types of trials, which are randomly presented: ANTI (60%), EV (20%) and AV (20%). Participants completed three experimental blocks without breaks (duration of task: 16 min and 24 sec).\u003c/p\u003e \u003cp\u003eIn the ANTI trials, a string of five arrows is presented and participants had to respond according to the direction pointed by the target, i.e., the central arrow, while ignoring the direction of the surrounding flanking arrows (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e panel a). The target could be anticipated by an auditory warning signal and a visual spatial cue. Cognitive control was measured as a function of the interference between the flanking and target arrows, i.e., the difference between congruent trials (50% of ANTI trials) and incongruent trials (50% of ANTI trials) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e panel d). Orienting was measured as a function of the location of the visual cue regarding the target position (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panel c), i.e., valid cue (33,33% of ANTI trials), invalid cue (33,33% of ANTI trials), and no cue (33,33% of ANTI trials) (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e panel c). Phasic alertness was measured as a function of the presence (tone condition, 50% of ANTI trials) or absence (no tone condition, 50% of ANTI trials) of the auditory warning signal presented before target onset (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e panel a).\u003c/p\u003e \u003cp\u003eEV trials had the same procedure than the ANTI ones, except that the target was vertically displaced from its central position. Participants had to detect the infrequent vertical displacement of the target by pressing the space bar key, while ignoring the direction pointed by the target (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panel d). For measuring EV, hits were computed as the percentage of correct responses in EV trials And false alarms (FA) as the percentage of space bar responses in ANTI trials, that is, when the target was not largely displaced, following the procedure by Luna et al. \u003csup\u003e42\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLastly, in AV trials, no tone, visual cue, or arrows were presented, and instead a red millisecond counter appeared in the centre of the screen, starting at 1000 and going down to zero (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panel b). Participants were asked to stop the counter as fast as they could by pressing any key of the keyboard (see Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, panel d). For measuring AV, mean RT, SD of RT, and the percentage of lapses (i.e., responses slower than 600 ms) were computed as dependent variables in AV trials.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analyses\u003c/h2\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eAll statistical analyses were performed using JASP software (Version 0.14.1.0, JASP Team, The Netherlands) \u003csup\u003e44\u003c/sup\u003e. Paired \u003cem\u003et\u003c/em\u003e-tests were used to analyze the effect of exercise conditions (low- vs. high-intensity) on the internal and external load (mean power output, RPE and HR). In the ANTI trials, for RT analyses, trials with incorrect responses (5.48%) and those with RT below 200 ms or above 1500 ms (0.83%) were excluded, as in Luna et al. \u003csup\u003e37\u003c/sup\u003e. Then, repeated-measures ANOVAs were conducted, including exercise condition (baseline, high-intensity, low-intensity), and tone (no tone, tone) for phasic alertness, cue (invalid, no cue, valid) for orienting, or congruency (incongruent, congruent) for cognitive control, as within-participant factors, and mean correct RT or the percentage of correct responses as dependent variable. Pairwise comparisons were conducted to further explore significant main effects and interactions.\u003c/p\u003e\u003cp\u003eFor EV trials, separated repeated-measures ANOVAs were conducted, with exercise (baseline, high-intensity, low-intensity) as within-participant factor and the percentage of hits, FA, or mean RT on hits (1.29% of trials with RT below 200 ms or above 1500 ms excluded) as dependent variable. Finally, for AV trials, three repeated-measures ANOVAs were performed with mean RT, SD of RT, or the percentage of lapses as dependent variable, and including exercise (baseline, high-intensity, low-intensity) as a within-participant factor.\u003c/p\u003e\u003cp\u003eThen, to determine the available evidence in favour or against our hypotheses, Bayesian analyses for each attentional effect and vigilance measure of interest were conducted as a function of exercise conditions.\u003c/p\u003e\u003cp\u003eFor Null Hypothesis Significance Testing (NHST) analyses, the alpha level was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.05 for paired \u003cem\u003et\u003c/em\u003e-test and repeated-measures ANOVAs. The partial eta squared (\u003cem\u003eη\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e) effect size is reported in ANOVAs, which indicates small (\u003cem\u003eη\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.01), moderate (\u003cem\u003eη\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.06), or strong (\u003cem\u003eη\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u0026gt;\u0026thinsp;.14) effect sizes. The Cohen\u0026rsquo;s \u003cem\u003ed\u003c/em\u003e effect size is reported in \u003cem\u003et\u003c/em\u003e-tests, which indicates small (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.2), medium (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.5), and large effect sizes (\u003cem\u003ed\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.8) \u003csup\u003e45\u0026ndash;47\u003c/sup\u003e. Bayesian\u0026rsquo;s results revealed whether data provide evidence supporting the alternative hypothesis with Bayes Factors (BF) as BF\u003csub\u003e10\u003c/sub\u003e larger than 3, or supporting the null hypothesis, when the value of BF\u003csub\u003e01\u003c/sub\u003e is larger than 3 \u003csup\u003e48,49\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e3.1. Exercise effect on physiological variables\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eAs expected, the load adjustment showed differences in the physiological dependent variables, evidenced by higher values in Power Output, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;=\u0026thinsp;10.99, \u003cem\u003ep\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;.001, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;2.04; Relative Power Output, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;12.395, \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.\u003c/em\u003e001, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;2.263; HR, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;15.24, \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.\u003c/em\u003e001, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;2.19; and RPE, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;17.48, \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;.\u003c/em\u003e001, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;3.25, for the high than for the low intensity condition (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\"\u003e\u003cstrong\u003eTable \u0026nbsp;1\u003c/strong\u003e. Mean and standard deviation (between parentheses) of physiological variables measured at different exercising conditions.\u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Taba\" border=\"1\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePower Output (W)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109.90 (32.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66.87 (15.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRelative Power Output (W.kg\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.63 (0.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.00 (0.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHR (bpm)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e157.02 (19.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e118.88 (15.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRPE *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.67 (10.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.06 (2.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eNote: Heart Rate (HR); Beats per minute (bpm); Rate of Perceived Exertion (RPE) *\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;.001.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003e3.2. Attentional Functioning\u003c/h2\u003e\n \u003cp\u003eTable 2 and Figure 2 show the descriptive results across all attentional networks and effort conditions. RT analyses showed the typical main effects usually observed with the ANTI-Vea\u003csup\u003e7\u003c/sup\u003e, supporting the effectiveness of the task in assessing the classic attentional functions in the current study. A significant main effect of tone was observed, \u003cem\u003eF(\u003c/em\u003e1, 29\u003cem\u003e)=\u003c/em\u003e51.14\u003cem\u003e, p\u0026lt;.\u003c/em\u003e001\u003cem\u003e,\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e =.\u003c/em\u003e64, with faster responses in the tone than in the no tone condition. The main effect of orienting was also significant, \u003cem\u003eF(\u003c/em\u003e2, 58\u003cem\u003e)=\u003c/em\u003e52.05\u003cem\u003e,\u0026nbsp;p\u0026lt;.\u003c/em\u003e001\u003cem\u003e, \u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e =.\u003c/em\u003e64\u003cem\u003e,\u003c/em\u003e with faster responses in the valid than in no cue, \u003cem\u003et\u003c/em\u003e(29)=3.76 \u003cem\u003ep\u0026lt;.\u003c/em\u003e001\u003cem\u003e, d=\u003c/em\u003e0,686 and invalid trials, \u003cem\u003et\u003c/em\u003e(29)=10.09 \u003cem\u003ep\u0026lt;.\u003c/em\u003e001\u003cem\u003e, d=\u003c/em\u003e1,84\u003cem\u003e,\u0026nbsp;\u003c/em\u003eand faster responses in the no cue than in the invalid trials \u003cem\u003et\u003c/em\u003e(29)=6.36 \u003cem\u003ep\u0026lt;.\u003c/em\u003e001\u003cem\u003e, d=\u003c/em\u003e1,16, \u003cem\u003ep\u0026lt;.\u003c/em\u003e001. Lastly, the main effect of congruency was also significant, \u003cem\u003eF (\u003c/em\u003e1, 29\u003cem\u003e)=\u0026nbsp;\u003c/em\u003e20.12\u003cem\u003e, p\u0026lt;.\u003c/em\u003e001\u003cem\u003e,\u003c/em\u003e \u003cem\u003e\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e =\u003c/em\u003e.41\u003cem\u003e,\u0026nbsp;\u003c/em\u003ewith faster responses in the congruent than in the incongruent condition\u003cem\u003e.\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003eRegarding accuracy, the main effect of visual cue was significant \u003cem\u003eF(\u003c/em\u003e2, 58\u003cem\u003e)=\u003c/em\u003e4.84\u003cem\u003e, p=\u003c/em\u003e.011\u003cem\u003e, \u0026nbsp;\u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e =.\u003c/em\u003e14\u003cem\u003e,\u003c/em\u003e with higher accuracy in invalid than valid trials, \u003cem\u003et\u003c/em\u003e(29)=2.84 \u003cem\u003ep=.\u003c/em\u003e019\u003cem\u003e, d=\u003c/em\u003e0,58\u003cem\u003e,\u003c/em\u003e and with higher accuracy in no cue than in valid trials, \u003cem\u003et\u003c/em\u003e(29)=2.53 \u003cem\u003ep=.\u003c/em\u003e028\u003cem\u003e, d=\u003c/em\u003e0,462, being not significant the difference between invalid and no cue trials, \u003cem\u003et\u003c/em\u003e(29)=0.31 \u003cem\u003ep= .\u003c/em\u003e762\u003cem\u003e, d=\u003c/em\u003e0,06. The main effect of congruency was also significant, \u003cem\u003eF(\u003c/em\u003e1, 29\u003cem\u003e)=\u003c/em\u003e10.65\u003cem\u003e, p=.\u003c/em\u003e003\u003cem\u003e, \u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e =.\u003c/em\u003e26\u003cem\u003e,\u003c/em\u003e showing a reversed pattern of outcomes, with higher accuracy in incongruent\u003cem\u003e\u0026nbsp;\u003c/em\u003ethan congruent trials. Lastly, response accuracy was not modulated by tone, \u003cem\u003eF(\u003c/em\u003e1, 29\u003cem\u003e)=\u003c/em\u003e1.82\u003cem\u003e, p=\u003c/em\u003e.188\u003cem\u003e, \u0026eta;\u003csup\u003e2\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e =.\u003c/em\u003e01\u003cem\u003e\u0026nbsp;\u003c/em\u003e(see Table 2).\u003c/p\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean and SD (between parentheses) of attentional networks functions for mean correct RT (ms) and Accuracy (%) as a function of exercise condition.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eAttentional measures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLow Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHigh Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFactor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevels\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAccuracy\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAlertness *\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e656(111)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.10(5.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e635(85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.70(4.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e632 (93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.10(6.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo tone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e678(107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.40(6.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e673 (87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.10(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e672 (97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93.70(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-0.30(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39(\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.60(5.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41(\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40(4.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eOrienting\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eValid cue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e653(110)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.20(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e641(93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.70(5.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e641(101)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.90(6.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo cue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e667(107)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.20(5.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e654(84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.90(4.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e652(93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.40(6.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvalid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e691(\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.30(5.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e675(99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.50(4.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e671(99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.20(5.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.10 (4.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (\u003cspan class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.80 (3.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30(4.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCognitive Control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCongruent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e662(111)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.60(6.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e648(93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.40(5.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e651(99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92.70(7.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncongruent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e679(110)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94.50(5.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e665(91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.70 (3.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e659(97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95.00(4.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.90(4.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(\u003cspan class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30(3.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.30 (4.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003cp\u003eNote= RT Phasic alertness Index=No tone - Tone ; RT Orienting index= Invalid \u0026ndash; Valid ; RT Cognitive control index= Incongruent \u0026ndash; Congruent. ; Accuracy Phasic alertness Index=Tone \u0026ndash; No Tone; Accuracy Orienting index= Valid \u0026ndash; Invalid; Accuracy Cognitive control index= \u0026nbsp;Congruent - Incongruent. *p\u0026lt; .05 between exercise conditions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003e3.3. Attentional functioning and exercising condition\u003c/h2\u003e\n \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.1 Overall performance in ANTI trials\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eExercise condition did not modulate the overall mean RT, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.52, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;.\u003c/em\u003e227, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.05. However, the overall response accuracy was influenced by exercise, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;7.49, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.001, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.205, showing higher values in the low \u003cem\u003e(M\u0026thinsp;=\u003c/em\u003e\u0026thinsp;96,00\u003cem\u003e%; SD\u0026thinsp;=\u003c/em\u003e\u0026thinsp;4.40\u003cem\u003e%)\u003c/em\u003e than in the high intensity condition (M\u0026thinsp;=\u0026thinsp;93.80%; SD\u0026thinsp;=\u0026thinsp;5.60), \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;3.16, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;.\u003c/em\u003e005, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.58, and the baseline condition, (M\u0026thinsp;=\u0026thinsp;93.80%; SD\u0026thinsp;=\u0026thinsp;5.20), \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;3.52, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.003, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.64, with no statistical differences between high intensity and baseline, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.34, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.718, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.07 (see Fig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n \u003c/div\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eThe Bayesian analysis showed strong evidence for larger accuracy after the low intensity exercise than after high intensity exercise (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;29.82) and during the baseline- resting condition (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;23.11). In other words, the presence of a beneficial effect of low intensity exercise was 23 times more likely than its absence, in comparison to baseline (almost 30 times more likely in comparison with high intensity). In contrast, Bayesian analysis rather showed evidence supporting the absence of any effect of exercise for overall RT (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5.05).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.2 Phasic alertness\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eExercise had a significant, albeit small, modulatory effect on phasic alertness in the RT score, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;3.20 \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.048, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.01. The two exercise intensity conditions did not significantly differ from each other, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.20,\u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.842 \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.04. However, a larger phasic alertness effect was observed in the high intensity condition compared to the baseline, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;2.97, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.006, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.54, and in the low intensity condition compared to the baseline, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;2.07, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.047, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.38. Concerning accuracy, the analysis did not reveal any significant modulation of exercise on phasic alertness \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.44, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.246, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.05.\u003c/p\u003e\n \u003cp\u003eThe Bayesian analysis of the modulation of exercise on phasic alertness for RT showed moderate evidence for the presence of a beneficial effect of low intensity in comparison to baseline (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.10), whereas evidence was inconsistent regarding the difference of high intensity against baseline (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.25). In contrast, for accuracy, evidence analyzed supported the absence of any type of exercise effect (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5.10).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.3 Orienting\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eExercise did not significantly influence orienting for RT, \u003cem\u003eF(\u003c/em\u003e4, 116\u003cem\u003e)\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.34, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.854, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.01, nor response accuracy, \u003cem\u003eF(\u003c/em\u003e4, 116\u003cem\u003e)\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.87, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.482, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.03.\u003c/p\u003e\n \u003cp\u003eThe Bayesian analysis showed evidence supporting the absence of a modulation of exercise on orienting for both RT (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.57) and accuracy (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.27).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.4 Cognitive control\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eCognitive control was not modulated by exercise cognition neither for RT, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.31, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.277, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.04, nor for accuracy, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.63, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.537, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.02.\u003c/p\u003e\n \u003cp\u003eThe results of Bayesian analysis provided evidence supporting the absence of modulation of exercise intensity on cognitive control, both for RT (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2.42) and accuracy (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;2.60).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.5 Executive vigilance (EV)\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eExercise condition modulated the percentage of FAs, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;5.97, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.004, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.17. As depicted in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, participants showed lower percentage of FAs after the low than the high intensity exercise, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;2.9, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.011, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.53, and after the low than the baseline condition \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;3.08, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.010, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.56. FAs were not significantly different between the high intensity and the baseline condition \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.18, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;.\u003c/em\u003e860, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.03. Exercise did not significantly modulate the percentage of hits, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.07, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;.\u003c/em\u003e931, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e\u0026lt;\u0026thinsp;.\u003c/em\u003e01 (see Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eFurthermore, although mean RT in hits is not typically analyzed for EV in the ANTI-Vea, we nevertheless analyzed it in an exploratory way, motivated by previous findings of effect of exercise intensity on RT of EV \u003csup\u003e\u003cem\u003e9\u003c/em\u003e\u003c/sup\u003e. Our results showed a significant main effect of exercise for mean RT in hits, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;3.59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;.034, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003ep\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;.11. Responses were faster after the high compared to the low intensity condition, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;2.55, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.040, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.47, while no significant differences were found between high intensity and baseline, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.98, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.104, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.36, nor between low intensity and baseline conditions, \u003cem\u003et\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.57, \u003cem\u003ep\u0026thinsp;=\u0026thinsp;.\u003c/em\u003e570, \u003cem\u003ed\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.19 (see Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean and SD (between parentheses) for executive vigilance (EV) scores as a function of exercise condition.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFalse alarms (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.80 (9.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.00 (7.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.50 (10,00)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHits (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84,10 (11.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83,80 (12.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84 ,40(\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean RT (ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e725 (84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e731 (91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e706 (78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eThe Bayesian analysis showed strong evidence for fewer FAs after the low intensity exercise than after high intensity exercise (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;26.47) and in the baseline (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;25.71). In other words, the presence of a beneficial effect of low intensity exercise was 26 times more likely than its absence, in comparison to baseline (26 times more likely in comparison with high intensity). The analysis of RT in hits also showed substantial evidence supporting faster responses after high intensity than after low intensity (BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;10.27), with evidence supporting the lack of differences between baseline and low intensity exercise (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;7.55). In contrast, the Bayesian analysis showed evidence supporting the absence of an effect of exercise intensity on hits (BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.60).\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\n \u003ch2\u003e3.3.6 Arousal Vigilance (AV)\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eExercise condition did not modulate response RT, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;1.86, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.172, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;.06, nor SD of RT, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.08, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.919, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e\u0026lt;\u003c/em\u003e\u0026thinsp;.01, nor the percentage of lapses, \u003cem\u003eF\u003c/em\u003e(\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e)\u0026thinsp;\u003cem\u003e=\u003c/em\u003e\u0026thinsp;0.18, \u003cem\u003ep\u0026thinsp;=\u003c/em\u003e\u0026thinsp;.834, \u003cem\u003e\u0026eta;\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003csub\u003e\u003cem\u003ep\u003c/em\u003e\u003c/sub\u003e\u0026thinsp;\u003cem\u003e=\u0026thinsp;\u0026lt;\u0026thinsp;.\u003c/em\u003e01 (see Table \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMean and SD (between parentheses) for arousal vigilance scores as a function of exercise condition.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAV score\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLow Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHigh Intensity\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMean RT (ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e490.03 (67.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e484.83 (73.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e483.16 (71.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD of RT (ms)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.95 (\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65.61 (20.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64.18 (22.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLapses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.40 (24.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.80 (22.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.00 (22.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eThe results of Bayesian analysis showed evidence supporting the absence of an effect of exercise on all the dependent variables for AV: BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.60 for mean RT, BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;4.96 for SD of RT, and BF\u003csub\u003e01\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;5.05 for the percentage of lapses.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe present study aimed to analyze the effects of an acute bout of low- vs. high-intensity exercise on several attentional and vigilance components. To do so, an experimental and crossover study was conducted. Participants completed three sessions to compare attentional functioning during a baseline- resting situation with two exercise conditions (after low- vs. after high-intensity cycling) using the ANTI-Vea task.\u003c/p\u003e\u003cp\u003eTo the best of our knowledge, this study represents the first attempt to investigate the effects of an acute bout of different physical exercise intensities on phasic alertness, orienting, cognitive control, as well as EV and AV. Previous studies analyzed the effects of acute exercise performed at different intensities on the different attentional networks \u003csup\u003e14,26\u003c/sup\u003e, although using behavioral tasks measuring a single attentional function. However, it is worth noting that Chang et al. examined the effect of acute exercise on phasic alertness, orienting and cognitive control by using the ANT \u003csup\u003e51\u003c/sup\u003e, which did not measure the EV and AV \u003csup\u003e32\u003c/sup\u003e. Additionally, the study by Chang et al. \u003csup\u003e32\u003c/sup\u003e did not compare different exercise intensities.\u003c/p\u003e\u003cp\u003eAs expected, our manipulation of exercise condition on the physiological response was confirmed by the overall values of power output, relative power output, HR, and RPE. In addition, the typical main effects usually observed by the ANTI-Vea were observed in RT analyses, supporting the effectiveness of the task in measuring attentional functioning in the present study. More importantly, and regarding the effect of the exercise on attentional functioning, our results showed that, while an acute bout of low-intensity of exercise improved overall accuracy, reduced false alarms, and increased the RT score of phasic alertness, a high-intensity exercise seemed to reduce RT in the EV sub-task.\u003c/p\u003e\u003cp\u003eIn line with our predictions, overall response accuracy improved after a low-intensity exercise in comparison to both the baseline condition and after a high intensity exercise in the attentional networks sub-task. These results are consistent with previous research in which participants performed physical exercise before attentional tasks \u003csup\u003e14,20\u003c/sup\u003e. This beneficial effect of low-intensity exercise on response accuracy could be attributed to the fact that moderate-intensity exercise optimally increases the concentration of cortisol and catecholamines in the brain. On the other hand, exercising at higher intensity results in an excessive increase in this hormone and neurotransmitter concentration, which may not have a beneficial effect and could even be detrimental to the speed and accuracy of motor responses \u003csup\u003e52\u0026ndash;54\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNevertheless, and contrary to our hypothesis and previous studies in the field \u003csup\u003e9\u003c/sup\u003e, exercise condition did not modulated the overall RT. It is noticeable that the difference between our study and the previous one by Sanchis et al. remains in the fact that they compared the online effects of light vs. moderate intensity during exercise \u003csup\u003e9\u003c/sup\u003e whereas we analysed post- exercise effects. These controversy between finding obtained in the above mentioned study (cycling\u0026thinsp;+\u0026thinsp;manual response to stimuli during exercise) \u003csup\u003e9\u003c/sup\u003e and our study (response after ending the exercise) could be explained by the different cognitive and motor resources assigned during dual task or single context of response respectively. Additionally, and although exercise can increase dopamine, norepinephrine, cortisol and catecholamine concentrations during and after physical activity \u003csup\u003e20,52\u0026ndash;54\u003c/sup\u003e, this unexpected result might be attributed to the fact that activating effects on RT, related with motor response, disappear more quickly than on accuracy, more related with perception and decision making, after exercise cessation \u003csup\u003e55\u003c/sup\u003e. In any case, differences in the effect of exercise on response depending on the contextual demands (single vs. dual task) should be further examined in future studies in which participants could be tested in all the exercise and contextual conditions in a counterbalanced order.\u003c/p\u003e\u003cp\u003eRegarding the effect of exercise condition on attentional functioning, and contrary to our hypothesis based on previous studies \u003csup\u003e14,17,25,26\u003c/sup\u003e, our results showed that executive control was not modulated by exercise. However, it is important to note that our descriptive results revealed a reduced congruency effect of 13.7 ms on average with respect to other previous studies using the ANTI-Vea (e.g., 44 ms in Luna et al., \u003csup\u003e37\u003c/sup\u003e and 35 ms in Sanchis et al., \u003csup\u003e9\u003c/sup\u003e). This reduced congruency effect, evidenced even in the baseline condition (17 ms), raises questions about the discrepancy between our study and the trend generally observed in the ANTI-Vea task, which seems to be due to different reasons. One possibility might be that participants only performed three blocks of trials in our study, while 6 blocks are typically performed, and the congruency effect has been shown to increase across blocks of trials in the ANTI-Vea \u003csup\u003e56\u003c/sup\u003e. It could also be plausible that this pattern is specific to the sample of participants in the present study, although this cannot be confirmed. In any case, it is worth noting that such small congruency effect may complicate the detection of significant changes due to the exercise conditions in the present study. Therefore, we consider crucial to replicate these findings in future studies, especially that involving task familiarisation, baseline, and exercise sessions conditions, to gain a more complete and accurate understanding of the modulation of online/offline exercise intensities on executive control.\u003c/p\u003e\u003cp\u003eConcerning phasic alertness, our results showed that both exercise conditions led to a significant enhancement of alerting effect compared to the baseline based on the reduction of RT in the tone condition. However, Bayesian analysis showed that evidence was inconsistent regarding the difference between high intensity and baseline, as BF\u003csub\u003e10\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;3. Hence, our study\u0026rsquo;s results align with previous studies in terms of observing faster RT after exercise, which only occurred when taking advantage of the alerting tone. The results of Huertas et al. \u003csup\u003e34\u003c/sup\u003e showed faster RT during moderate aerobic than in rest condition, although contrary to our findings the exercise effect was larger in no-tone trials than in tone trials. The fact that tone reduces RT more in low intensity condition could be explained by the optimal effect of low intensity exercise in modulating the secretion of different neurochemical factors (catecholamines and cortisol). The lack of effect in high intensity exercise compared to baseline, might be due to the high intensity exercise generating excessive catecholamine and cortisol concentration according to an inverted U-shape relation between exercise intensity and hormones secretion regulating the tonic alertness response \u003csup\u003e52\u0026ndash;54\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWith regards to the functioning of the orienting network, and according to previous studies \u003csup\u003e27,28,32,33\u003c/sup\u003e, our results did not show any modulation of exercise on the visual cue effect. Only Llorens et al. revealed that, after the bout of high intensity exercise, only low-fit participants showed a reduced orienting (exogeneous spatial attention) effects compared to rest conditions, whereas fit participants showed similar performance in both experiment conditions \u003csup\u003e27\u003c/sup\u003e. It might be the case that participants of the present study (which most of them were students of Sport Sciences) were enough fit to not show any effect of exercise on orienting. Divergences among the present study also emerged with findings by Sanabria et al., showing that spatial orienting was modulated both during and after exercise in comparison with rest condition \u003csup\u003e29\u003c/sup\u003e. Interestingly, the differences between our results and those obtained by Sanabria et al. could be related to the different measure of the orienting function. Our study employed the ANTI-Vea, which measures facilitation of attentional orienting, whereas Sanabria et al. used a paradigm suitable to measure facilitation and inhibition of return respectively in the long and large SOA conditions. Indeed, Sanabria et al. found no effect of exercise at the short SOA, where facilitation was observed, as in our study. The modulation of exercise was exclusively observed at the long SOAs where an IOR effect was only observed in the baseline condition. Therefore, our results are coherent with those of Sanabria et al. (short SOA) and the work by Sanchis et al. using the same task as in our study, although comparing the online effects of light vs. moderate exercise, showing no modulation of orienting during exercise \u003csup\u003e9\u003c/sup\u003e. Future studies examining the impact of acute exercise on attention might include groups with different fitness level using different exercise intensities and baseline, and investigate different aspects of exogenous and endogenous orienting, to gain a more accurate understanding of these effects and interactions.\u003c/p\u003e\u003cp\u003eRegarding the effect of acute exercise affects over Executive Vigilance (EV), our results showed a lower percentage of FAs after the low-intensity exercise, although without influence of exercise on hits. These results are in line with those reported by Mehren et al. who investigated the effects of acute exercise at moderate and high intensities on executive function, including functional MRI. Results showed a tendency towards improved behavioural performance in the Go/No-go task, interpreted as improved ability to inhibit a prepotent response and to sustain attention, and increased brain activation, as changes in BOLD response, in frontal areas following low intensity exercise compared to high intensity \u003csup\u003e26\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNevertheless, our results revealed no difference between rest and high intensity condition. It is worth mentioning that mean RT on hits was also dependent on exercise intensity showing that participants were faster after performing the high than the low intensity condition. In a study aiming to investigate the acute effect of cycling at different intensities, results showed better selective attention especially for congruent stimuli \u003csup\u003e17\u003c/sup\u003e after the highest intensity (95% of the MMP) and in the shortest duration (~\u0026thinsp;3 min) compared to the baseline. It is noteworthy that the high intensity exercise in our study has an average duration of 23 minutes, significantly longer than the 3 minutes duration of the above-mentioned study, which could explain the different results. Our high intensity condition involves an incremental effort until exhaustion. However, finding by Sudo et al. \u003csup\u003e53\u003c/sup\u003e investigating the effects of an incremental exercise to exhaustion revealed no modulation in RT within a cognitive task combining a Spatial Delayed-Response task and a Go/No-Go task. Furthermore, the controversial outcomes between our results and previous ones could be explained based on the different complexity of the task used to measure selective attention and the different attentional set ups required in the ANTI-Vea task. To deep into the influence of the time course on this effect, we explored whether there was a decrement in percentage of hits during our longer 3 blocks of ANTI-Vea task (i.e. more than 16 min) confirming no vigilance decrement in neither of the three activity conditions. Future research could extend the task to 6 blocks in order to see how performance evolves over longer times and whether vigilance decrement across time on task is modulated or not by exercise.\u003c/p\u003e\u003cp\u003eWith respect to Arousal Vigilance (AV), we observe no modulation of exercise intensities on AV scores. These results are similar to those reported by previous studies comparing the immediate and short-term effects of 35 min of aerobic (55% of MMP) cycling exercise \u003csup\u003e55\u003c/sup\u003e, or the meta-analysis by Chang et al.\u003csup\u003e11\u003c/sup\u003e. This well-known pattern of results suggests that effects of exercise on simple RT task disappear very quickly after exercise cessation. Notably, there are scarce studies as ours analysing AV specifically along with other attentional networks in a complex task, being a factor that influences vigilance performance \u003csup\u003e9,32\u003c/sup\u003e. Our work could complement the findings by Sanchis et al. \u003csup\u003e9\u003c/sup\u003e suggesting that exercise may not significantly modulate AV when assessed using a complex task performed both during and after exercise. It is interesting that after high-intensity exercise, or during exercise in Sanchis et al., responses were faster in EV, but not in AV trials, adding more evidence in favour that task demands and cognitive resources assigned to the task modulate the effect of exercise on response.\u003c/p\u003e\u003cp\u003eIt is important to note that the present study is not exempted from some limitations. The fact that the baseline session was not counterbalanced could constraint the interpretation of the differences between the rest and both exercise conditions due to practice effects. This decision was made based on the difficulties to include four experimental sessions, and trying to reduce the risk of participants dropping out of the study given its duration. We tried to mitigate this by the inclusion of a previous familiarization session at home with ANTI-Vea before the baseline session. Nevertheless, a proper counterbalancing of all conditions would have allowed us to more confidently compare the three activity conditions. In any case, it is important to consider that no large practice effects have been observed with the ANTI-Vea across the 10 sessions \u003csup\u003e57\u003c/sup\u003e. Similarly, a previous study examining the efficacy of the ANT and ANT for Interactions tasks over ten sessions found no evidence of an increase in phasic alertness effect between the second and third sessions \u003csup\u003e58\u003c/sup\u003e. Therefore, considering that our participants performed the task immediately after physical exercise, which was their third or fourth time completing it, it could be argued that the observed larger alertness effect observed with RT after the exercised, compared to baseline cannot be fully explained as a practice effect. These two studies suggests that the larger alertness effect observed with RT in the current study would not be due to the practice effect.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTo conclude, our results reveal that an acute bout of exercise modulates different attentional and vigilance scores but depending on the exercise intensity. First, while high intensity exercise does not modulate overall performance, low intensity exercise improves the overall accuracy in the attentional networks sub-task. Regarding the attentional functioning, a modulation of exercise over phasic alertness was observed, accelerating the response to the acoustic stimuli, although without affecting the orienting and executive control networks. With respect to the vigilance components, executive vigilance (EV) was improved by high intensity exercise, showing faster responses in hits, while low intensity exercise improved accuracy by reducing the false alarms rate compared to the other two conditions. Arousal vigilance (AV) was not modulated by the activity condition.\u003c/p\u003e \u003cp\u003eTo further clear the existing controversy in the literature, future research should compare the effect of exercise at different intensities on the attentional networks, EV and AV including participant of diverse fitness level to check the modulatory effect of fitness level and task demands on attentional functioning.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eTo Spanish MCIN/AEI/10.13039/501100011033/, through grant number PID2020-114790GB-I00.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e E. S-N. and F.H developed the study idea and methodology. E.S-N. collected and compiled subject\u0026rsquo;s data. E.S-N., F.L., F.H. and J.L wrote the whole paper as a team. E.S-N., F.H., F.L., and J.L completed the statistical analysis. F.L elaborated the figures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u0026nbsp;\u003c/strong\u003eThe dataset generated during the current study is available in the OSF repository, https://osf.io/mpkej/ .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e Juan Lupi\u0026aacute;\u0026ntilde;ez was funded by the Spanish MCIN/AEI/10.13039/501100011033/, through grant number PID2020-114790GB-I00.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePosner, M. I. \u0026amp; Petersen, S. E. The attention system of the human brain. \u003cem\u003eAnnu Rev Neurosci\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 25\u0026ndash;42. https://doi.org/10.1146/annurev.ne.13.030190.000325 (1990).\u003c/li\u003e\n \u003cli\u003ePetersen, S. E. \u0026amp; Posner, M. I. The attention system of the human brain: 20 years after. \u003cem\u003eAnnu Rev Neurosci\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 73\u0026ndash;89. https://doi.org/10.1146/annurev-neuro-062111-150525 (2012).\u003c/li\u003e\n \u003cli\u003eMiller, E. K. The prefrontal cortex and cognitive control. \u003cem\u003eNat Rev Neurosci\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 59\u0026ndash;65. https://doi.org/10.1038/35036228 (2000).\u003c/li\u003e\n \u003cli\u003ePosner, M. I. Orienting of attention. \u003cem\u003eQ J Exp Psychol\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 3\u0026ndash;25. https://doi.org/10.1080/00335558008248231 (1980).\u003c/li\u003e\n \u003cli\u003eRoca, J., Castro, C., L\u0026oacute;pez-Ram\u0026oacute;n, M. F. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. Measuring vigilance while assessing the functioning of the three attentional networks: the ANTI-Vigilance task. \u003cem\u003eJ Neurosci Methods\u003c/em\u003e \u003cstrong\u003e198\u003c/strong\u003e, 312\u0026ndash;324 https://doi.org/10.1016/j.jneumeth.2011.04.014 (2011).\u003c/li\u003e\n \u003cli\u003eHusain, M. \u0026amp; Rorden, C. Non-spatially lateralized mechanisms in hemispatial neglect. \u003cem\u003eNat Rev Neurosci\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e, 26\u0026ndash;36. https://doi.org/10.1038/nrn1005 (2003).\u003c/li\u003e\n \u003cli\u003eLuna, F. G., Marino, J., Roca, J. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. Executive and arousal vigilance decrement in the context of the attentional networks: The ANTI-Vea task. \u003cem\u003eJ Neurosci Methods\u003c/em\u003e \u003cstrong\u003e306\u003c/strong\u003e, 77\u0026ndash;87. https://doi.org/10.1016/j.jneumeth.2018.05.011 (2018).\u003c/li\u003e\n \u003cli\u003eLuna, F. G., Rom\u0026aacute;n-Caballero, R., Barttfeld, P., Lupi\u0026aacute;\u0026ntilde;ez, J. \u0026amp; Mart\u0026iacute;n-Ar\u0026eacute;valo, E. A High-Definition tDCS and EEG study on attention and vigilance: Brain stimulation mitigates the executive but not the arousal vigilance decrement. \u003cem\u003eNeuropsychologia\u003c/em\u003e \u003cstrong\u003e142\u003c/strong\u003e, 107447. https://doi.org/10.1016/j.neuropsychologia.2020.107447 (2020).\u003c/li\u003e\n \u003cli\u003eSanchis, C., Blasco Herraiz, E., Luna, F. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. Effects of caffeine intake and exercise intensity on executive and arousal vigilance. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 8393. https://doi.org/10.1038/s41598-020-65197-5 (2020).\u003c/li\u003e\n \u003cli\u003eLuna, F. G. \u003cem\u003eet al.\u003c/em\u003e Different oscillatory rhythms anticipate failures in executive and arousal vigilance. \u003cem\u003eFront Cognit\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e2\u003c/strong\u003e. https://doi.org/10.3389/fcogn.2023.1128442 (2023).\u003c/li\u003e\n \u003cli\u003eChang, Y., Labban, J., Gapin, J. \u0026amp; Etnier, J. The effects of acute exercise on cognitive performance: A meta-analysis. \u003cem\u003eBrain Res\u003c/em\u003e \u003cstrong\u003e1453\u003c/strong\u003e, 87\u0026ndash;101. https://doi.org/10.1016/j.brainres.2012.02.068 (2012).\u003c/li\u003e\n \u003cli\u003eDonnelly, J. E. \u003cem\u003eet al.\u003c/em\u003e Physical activity, fitness, cognitive function, and academic achievement in children: A systematic review. \u003cem\u003eMed Sci Sports Exerc.\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 1197\u0026ndash;1222. https://doi.org/10.1249/MSS.0000000000000901 (2016).\u003c/li\u003e\n \u003cli\u003eEtnier, J. L. \u003cem\u003eet al.\u003c/em\u003e The influence of physical fitness and exercise upon cognitive functioning: a meta-analysis. \u003cem\u003eJ Sport Exerc Psychol\u003c/em\u003e \u003cstrong\u003e19\u003c/strong\u003e, 249\u0026ndash;277. https://doi.org/10.1123/jsep.19.3.249 (1997).\u003c/li\u003e\n \u003cli\u003eEngeroff, T., Banzer, W. \u0026amp; Niederer, D. The impact of regular activity and exercise intensity on the acute effects of resistance exercise on cognitive function. \u003cem\u003eScand J Med Sci Sports\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 94\u0026ndash;105. https://doi.org/10.1111/sms.14050 (2022).\u003c/li\u003e\n \u003cli\u003eten Haaf, T. et al. Changes in choice reaction time during and after 8 days exhaustive cycling are not related to changes in physical performance. \u003cem\u003eInt J Sports Physiol Perform\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 428\u0026ndash;433. https://doi.org/10.1123/ijspp.2017-0218 (2018).\u003c/li\u003e\n \u003cli\u003eDupuy, O. et al. Effect of overreaching on cognitive performance and related cardiac autonomic control. \u003cem\u003eScand J Med Sci Sports\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e24,\u003c/strong\u003e 234\u0026ndash;242. https://doi.org/10.1111/j.1600-0838.2012.01465.x (2014).\u003c/li\u003e\n \u003cli\u003eKunzler, M. R. \u0026amp; Carpes, F. P. Intense cycling exercise improves acute cognitive responses. \u003cem\u003eInt J Sports Med\u003c/em\u003e \u003cstrong\u003e41\u003c/strong\u003e, 879\u0026ndash;884. 10.1055/a-1114-6170 (2020).\u003c/li\u003e\n \u003cli\u003eCrush, E. A. \u0026amp; Loprinzi, P. D. Dose-response effects of exercise duration and recovery on cognitive functioning. \u003cem\u003ePercept Mot Skills\u003c/em\u003e \u003cstrong\u003e124\u003c/strong\u003e, 1164\u0026ndash;1193. https://doi.org/10.1177/0031512517726920 (2017).\u003c/li\u003e\n \u003cli\u003eChang, Y.-K. \u0026amp; Etnier, J. L. Effects of an acute bout of localized resistance exercise on cognitive performance in middle-aged adults: A randomized controlled trial study. \u003cem\u003ePsychol Sport Exerc\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 19\u0026ndash;24. https://doi.org/10.1016/j.psychsport.2008.05.004 (2009).\u003c/li\u003e\n \u003cli\u003eMcMorris, T. \u0026amp; Hale, B. J. Differential effects of differing intensities of acute exercise on speed and accuracy of cognition: A meta-analytical investigation. \u003cem\u003eBrain Cogn\u003c/em\u003e \u003cstrong\u003e80\u003c/strong\u003e, 338\u0026ndash;351. https://doi.org/10.1016/j.bandc.2012.09.001 (2012).\u003c/li\u003e\n \u003cli\u003eIrwin, C., Campagnolo, N., Iudakhina, E., Cox, G. R. \u0026amp; Desbrow, B. Effects of acute exercise, dehydration and rehydration on cognitive function in well-trained athletes. \u003cem\u003eJ Sports Sci\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 247\u0026ndash;255. https://doi.org/10.1080/02640414.2017.1298828 (2018).\u003c/li\u003e\n \u003cli\u003eStroth, S. \u003cem\u003eet al.\u003c/em\u003e Physical fitness, but not acute exercise modulates event-related potential indices for executive control in healthy adolescents. \u003cem\u003eBrain Res\u003c/em\u003e \u003cstrong\u003e1269\u003c/strong\u003e, 114\u0026ndash;124. https://doi.org/10.1016/j.brainres.2009.02.073 (2009).\u003c/li\u003e\n \u003cli\u003eMoore, R., Romine, Mathew., O\u0026rsquo;connor, P. \u0026amp; Tomporowski, P. The influence of exercise-induced fatigue on cognitive function. \u003cem\u003eJ Sports Sci\u003c/em\u003e \u003cstrong\u003e30\u003c/strong\u003e, 841\u0026ndash;850. https://doi.org/10.1080/02640414.2012.675083 (2012).\u003c/li\u003e\n \u003cli\u003eZhou, F. \u0026amp; Qin, C. Acute moderate-intensity exercise generally enhances attentional resources related to perceptual processing. \u003cem\u003eFront psychol\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e. https://doi.org/10.3389/fpsyg.2019.02547 (2019).\u003c/li\u003e\n \u003cli\u003eC\u0026oacute;rdova, C., Silva, V. C., Moraes, C. F., Sim\u0026otilde;es, H. G. \u0026amp; N\u0026oacute;brega, O. T. Acute exercise performed close to the anaerobic threshold improves cognitive performance in elderly females. \u003cem\u003eBraz J Med Biol Res\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 458\u0026ndash;464. https://doi.org/10.1590/S0100-879X2009000500010 (2009).\u003c/li\u003e\n \u003cli\u003eMehren, A. \u003cem\u003eet al.\u003c/em\u003e Intensity-dependent effects of acute exercise on executive function. \u003cem\u003eNeural Plast\u003c/em\u003e \u003cstrong\u003e2019\u003c/strong\u003e. https://doi.org/10.1155/2019/8608317 (2019).\u003c/li\u003e\n \u003cli\u003eLlorens, F., Sanabria, D. \u0026amp; Huertas, F. The influence of acute intense exercise on exogenous spatial attention depends on physical fitness level. \u003cem\u003eExp Psychol\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 20\u0026ndash;29. https://doi.org/10.1027/1618-3169/a000270 (2014).\u003c/li\u003e\n \u003cli\u003eLlorens, F., Sanabria, D., Huertas, F., Molina, E. \u0026amp; Bennett, S. Intense physical exercise reduces overt attentional capture. \u003cem\u003eJ Sport Exercise Psy\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e37\u003c/strong\u003e, 559\u0026ndash;564. https://doi.org/10.1123/jsep.2015-0087 (2015).\u003c/li\u003e\n \u003cli\u003eSanabria, D. \u003cem\u003eet al.\u003c/em\u003e Effects of acute aerobic exercise on exogenous spatial attention. \u003cem\u003ePsychol Sport Exerc\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 570\u0026ndash;574. https://doi.org/10.1016/j.psychsport.2011.04.002 (2011).\u003c/li\u003e\n \u003cli\u003eSen\u0026eacute;cal, I., Howarth, S. J., Wells, G. D., Raymond, I. \u0026amp; Mior, S. The impact of moderate and high intensity cardiovascular exertion on sub-elite soccer referee\u0026rsquo;s cognitive performance: A lab-based study. \u003cem\u003eJ Sci Med Sport\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 618\u0026ndash;625. https://doi.org/10.52082/jssm.2021.618 (2021).\u003c/li\u003e\n \u003cli\u003ede Souza Almeida, R., Faria-Jr, A. \u0026amp; Klein, R. M. On the origins and evolution of the Attention Network Tests. \u003cem\u003eNeurosci Biobehav Rev\u003c/em\u003e \u003cstrong\u003e126\u003c/strong\u003e, 560\u0026ndash;572. https://doi.org/10.1016/j.neubiorev.2021.02.028 (2021).\u003c/li\u003e\n \u003cli\u003eChang, Y.-K., Pesce, C., Chiang, Y.-T., Kuo, C.-Y. \u0026amp; Fong, D.-Y. Antecedent acute cycling exercise affects attention control: an ERP study using attention network test. \u003cem\u003eFront Hum Neurosci\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 156. https://doi.org/10.3389/fnhum.2015.00156 (2015).\u003c/li\u003e\n \u003cli\u003eAnzeneder, S., Zehnder, C., Martin-Niedecken, A. L., Schmidt, M. \u0026amp; Benzing, V. Acute exercise and children\u0026rsquo;s cognitive functioning: What is the optimal dose of cognitive challenge? \u003cem\u003ePsychol Sport Exerc\u003c/em\u003e \u003cstrong\u003e66\u003c/strong\u003e, 102404. https://doi.org/10.1016/j.psychsport.2023.102404 (2023).\u003c/li\u003e\n \u003cli\u003eHuertas, F., Zahonero, J., Sanabria, D. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. Functioning of the attentional networks at rest vs. during acute bouts of aerobic exercise. \u003cem\u003eJ Sport Exercise Psy\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e33\u003c/strong\u003e, 649\u0026ndash;665. https://doi.org/10.1123/jsep.33.5.649 (2011).\u003c/li\u003e\n \u003cli\u003eHuertas, F., Blasco, E., Moratal, C. \u0026amp; Lupia\u0026ntilde;ez, J. Caffeine intake modulates the functioning of the attentional networks depending on consumption habits and acute exercise demands. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e9\u003c/strong\u003e, 10043. https://doi.org/10.1038/s41598-019-46524-x (2019).\u003c/li\u003e\n \u003cli\u003eFaul, F., Erdfelder, E., Lang, A.-G. \u0026amp; Buchner, A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. \u003cem\u003eBehav Res Methods\u003c/em\u003e \u003cstrong\u003e39\u003c/strong\u003e, 175\u0026ndash;191. https://doi.org/10.3758/bf03193146 (2007).\u003c/li\u003e\n \u003cli\u003eLuna, F. G., Roca, J., Mart\u0026iacute;n-Ar\u0026eacute;valo, E. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. Measuring attention and vigilance in the laboratory vs. online: The split-half reliability of the ANTI-Vea. \u003cem\u003eBehav Res\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, 1124\u0026ndash;1147. https://doi.org/10.3758/s13428-020-01483-4 (2021).\u003c/li\u003e\n \u003cli\u003eColl-Mart\u0026iacute;n, T. \u003cem\u003eet al.\u003c/em\u003e \u003cem\u003eThe ANTI-Vea-UGR Platform: A Free Online Resource To Measure Attentional Networks (Alertness, Orienting, and Executive Control) Functioning and Executive/Arousal Vigilance\u003c/em\u003e. https://doi.org/10.20944/preprints202306.1031.v1 (2023)\u003c/li\u003e\n \u003cli\u003eKarvonen, M. J., Kentala, E. \u0026amp; Mustala, O. The effects of training on heart rate; a longitudinal study. \u003cem\u003eAnn Med Exp Biol Fenn\u003c/em\u003e \u003cstrong\u003e35\u003c/strong\u003e, 307\u0026ndash;315 (1957).\u003c/li\u003e\n \u003cli\u003eBorg, G. Psychophysical bases of perceived exertion. \u003cem\u003eMed Sci Sports Exerc\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 377\u0026ndash;381. https://doi.org/10.1249/00005768-198205000-00012 (1982).\u003c/li\u003e\n \u003cli\u003eCallejas, A., Lupianez, J. \u0026amp; Tudela, P. The three attentional networks: On their independence and interactions. \u003cem\u003eBrain Cogn\u0026nbsp;\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 225\u0026ndash;227. https://doi.org/10.1016/j.bandc.2004.02.012 (2004).\u003c/li\u003e\n \u003cli\u003eLuna, F. G., Barttfeld, P., Mart\u0026iacute;n-Ar\u0026eacute;valo, E. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. The ANTI-Vea task: Analyzing the executive and arousal vigilance decrements while measuring the three attentional networks. \u003cem\u003ePsicol\u0026oacute;gica\u003c/em\u003e \u003cstrong\u003e42\u003c/strong\u003e, 1\u0026ndash;26. https://doi.org/10.2478/psicolj-2021-0001 (2021).\u003c/li\u003e\n \u003cli\u003eC\u0026aacute;sedas, L., Cebolla, A. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. Individual differences in dispositional mindfulness predict attentional networks and vigilance performance. \u003cem\u003eMindfulness\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 967\u0026ndash;981. https://doi.org/10.1007/s12671-022-01850-6 (2022).\u003c/li\u003e\n \u003cli\u003eJASP Team. https://jasp-stats.org/ .\u003c/li\u003e\n \u003cli\u003eCohen, J. \u003cem\u003eStatistical Power Analysis for the Behavioral Sciences\u003c/em\u003e. (L. Erlbaum Associates, Hillsdale, N.J, 1988).\u003c/li\u003e\n \u003cli\u003eCumming, G. The new statistics: Why and how. \u003cem\u003ePsychol Sci\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 7\u0026ndash;29. https://doi.org/10.1177/0956797613504966 (2014).\u003c/li\u003e\n \u003cli\u003eKelley, K. \u0026amp; Preacher, K. J. On effect size. \u003cem\u003ePsychol Methods\u003c/em\u003e \u003cstrong\u003e17\u003c/strong\u003e, 137\u0026ndash;152. https://doi.org/10.1037/a0028086 (2012).\u003c/li\u003e\n \u003cli\u003eJarosz, A. F. \u0026amp; Wiley, J. What are the odds? A practical guide to computing and reporting bayes factors. \u003cem\u003e\u0026nbsp;J Probl Solving\u0026nbsp;\u003c/em\u003e\u003cstrong\u003e7\u003c/strong\u003e. https://doi.org/10.7771/1932-6246.1167 (2014).\u003c/li\u003e\n \u003cli\u003eWagenmakers, E.-J. \u003cem\u003eet al.\u003c/em\u003e Bayesian inference for psychology. Part II: Example applications with JASP. \u003cem\u003ePsychon Bull Rev\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 58\u0026ndash;76. https://doi.org/10.3758/s13423-017-1323-7 (2018).\u003c/li\u003e\n \u003cli\u003eMorey, R. Confidence intervals from normalized data: A correction to Cousineau (2005). \u003cem\u003eQuant Meth Psych\u003c/em\u003e \u003cstrong\u003e4\u003c/strong\u003e. https://doi.org/10.20982/tqmp.04.2.p061. (2008).\u003c/li\u003e\n \u003cli\u003eFan, J., McCandliss, B. D., Sommer, T., Raz, A. \u0026amp; Posner, M. I. Testing the efficiency and independence of attentional networks. \u003cem\u003eJ Cogn Neurosci\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 340\u0026ndash;347. https://doi.org/10.1162/089892902317361886 (2002).\u003c/li\u003e\n \u003cli\u003eCooper, C. J. Anatomical and physiological mechanisms of arousal, with special reference to the effects of exercise. \u003cem\u003eErgonomics\u003c/em\u003e \u003cstrong\u003e16\u003c/strong\u003e, 601\u0026ndash;609. https://doi.org/10.1080/00140137308924551 (1973).\u003c/li\u003e\n \u003cli\u003eSudo, M. \u003cem\u003eet al.\u003c/em\u003e Executive function after exhaustive exercise. \u003cem\u003eEur J Appl Physiol\u003c/em\u003e \u003cstrong\u003e117\u003c/strong\u003e, 2029\u0026ndash;2038. https://doi.org/10.1016/j.brainres.2009.02.073 (2017).\u003c/li\u003e\n \u003cli\u003eMcMorris, T. \u003cem\u003eExercise-Cognition Interaction: Neuroscience Perspectives\u003c/em\u003e. (Academic Press, 2015).\u003c/li\u003e\n \u003cli\u003eAudiffren, M., Tomporowski, P. D. \u0026amp; Zagrodnik, J. Acute aerobic exercise and information processing: energizing motor processes during a choice reaction time task. \u003cem\u003eActa Psychol (Amst)\u003c/em\u003e \u003cstrong\u003e129\u003c/strong\u003e, 410\u0026ndash;419. https://doi.org/10.1016/j.actpsy.2008.09.006 (2008).\u003c/li\u003e\n \u003cli\u003eLuna, F. G., Tortajada, M., Mart\u0026iacute;n-Ar\u0026eacute;valo, E., Botta, F. \u0026amp; Lupi\u0026aacute;\u0026ntilde;ez, J. A vigilance decrement comes along with an executive control decrement: Testing the resource-control theory. \u003cem\u003ePsychon Bull Rev.\u0026nbsp;\u003c/em\u003ehttps://doi.org/10.3758/s13423-022-02089-x (2022)\u003c/li\u003e\n \u003cli\u003eGabriela, A. \u0026amp; Anah\u0026iacute;, Y. Estabilidad y confiabilidad en la tarea ANTI-Vea online. \u003cem\u003eManuscript in preparation\u003c/em\u003e.\u003c/li\u003e\n \u003cli\u003eIshigami, Y. \u0026amp; Klein, R. M. Repeated measurement of the components of attention using two versions of the Attention Network Test (ANT): Stability, isolability, robustness, and reliability. \u003cem\u003eJ Neurosci Methods\u003c/em\u003e \u003cstrong\u003e190\u003c/strong\u003e, 117\u0026ndash;128. https://doi.org/10.1016/j.jneumeth.2010.04.019 (2010).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Exercise, attention, executive control, orienting, phasic alertness, vigilance","lastPublishedDoi":"10.21203/rs.3.rs-3973814/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3973814/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe effects of physical exercise on attentional performance have received considerable interest in recent years. Most of previous studies that assessed the effect of an acute bout of exercise on attentional performance have generally been approached by analysing single attentional functions in isolation, thus ignoring the functioning of other attentional functions, which characterizes the real perception-action environmental conditions. Here, we investigated the effect of two different intensities (low vs. high) of acute exercise on attentional performance by using the ANTI-Vea, a behavioral task that simultaneously measures three attentional functions (phasic alertness, orienting, and cognitive control) and the executive and arousal components of vigilance. 30 participants completed three experimental sessions: the first one to assess their physical fitness and baseline performance in the ANTI-Vea, and the other two sessions to assess changes in attentional and vigilance performance after an acute bout of high- vs. low-intensity physical exercise (in a counterbalanced order between participants). Beneficial effects on some accuracy scores (i.e., overall higher accuracy in the attentional sub-task and fewer false alarms in the executive vigilance sub-task) were observed in the low-intensity exercise condition compared to baseline and high-intensity. Additionally, the RT score of phasic alertness was increased after the low-intensity exercise in comparison with baseline. The present findings suggest that a bout of acute exercise at low-intensity might induce some short-term beneficial effects on some aspects of attention and vigilance.\u003c/p\u003e","manuscriptTitle":"Effect of an acute bout of high- vs. low-intensity physical exercise on attentional networks.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-23 18:47:00","doi":"10.21203/rs.3.rs-3973814/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-31T05:25:28+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-20T14:24:44+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-18T02:48:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"223743370088180636980548394653976204282","date":"2024-05-03T11:08:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216113844833651227763537831560779401238","date":"2024-05-02T12:01:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-01T09:35:46+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-01T09:07:47+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-14T13:49:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-14T13:48:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-02-20T20:34:40+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"273c1b69-d09b-4df0-b50b-af50fc4fdff4","owner":[],"postedDate":"February 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":28929419,"name":"Biological sciences/Neuroscience"},{"id":28929420,"name":"Biological sciences/Psychology"}],"tags":[],"updatedAt":"2024-11-04T16:29:27+00:00","versionOfRecord":{"articleIdentity":"rs-3973814","link":"https://doi.org/10.1038/s41598-024-77175-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2024-10-28 16:20:36","publishedOnDateReadable":"October 28th, 2024"},"versionCreatedAt":"2024-02-23 18:47:00","video":"","vorDoi":"10.1038/s41598-024-77175-2","vorDoiUrl":"https://doi.org/10.1038/s41598-024-77175-2","workflowStages":[]},"version":"v1","identity":"rs-3973814","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3973814","identity":"rs-3973814","version":["v1"]},"buildId":"ApUGefWb6u5IBVtyqm6d5","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}