Effects of Acute Physical Exercise Characteristics on Cognitive Performance
The effect of physical exercise on mental function has been widely studied from the beginning of the 20th century. However, the contradictory findings of experimental research have led authors to identify several methodological factors to control in such studies including: (i) the nature of the psychological task; and (ii) the intensity and duration of physical exercise. The purpose of this article is to provide information, from the perspective of performance optimisation, on the main effects of physical task characteristics on cognitive performance. Within this framework, some consistent results have been observed during the last decade. Recent studies, using mainly complex decisional tasks, have provided the research community with clear support for an improvement of cognitive performance during exercise. Diverse contributing factors have been suggested to enhance cognitive efficacy. First, an increase in arousal level related to physical exertion has been hypothesised. Improvement in decisional performance has been observed immediately after the adrenaline threshold during incremental exercise. Such positive effects could be enhanced by nutritional factors, such as carbohydrate or fluid ingestion, but did not seem to be influenced by the level of fitness. Second, the mediating role of resource allocation has been suggested to explain improvement in cognitive performance during exercise. This effect highlights the importance of motivational factors in such tasks. Finally, when the cognitive performance was performed during exercise, consistent results have indicated that the dual task effect was strongly related to energetic constraints of the task. The greater the energy demand, the more attention is used to control movements.
In many sports, participants have to simultaneously perform mechanical work with a great physical demand and a decisional or perceptual task. Over the last several decades, much research has been carried out to identify the influence of acute physical exercise on cognitive processes using several cognitive tasks. However, despite the abundance of research (more than 200 studies from 1930 to 1999), the issue of the physiological effect of exercise on cognitive performance remains. Tomporowski and Ellis classified the results from these studies into four categories: those finding a beneficial relationship, those finding a detrimental relationship, those finding both a beneficial and a detrimental relationship, and those finding no relationship. Therefore, interpretation of results has been diverse. On the one hand, a positive or a negative effect of exercise on cognitive functioning has been explained (often a posteriori) by the action of an intermediate factor influenced by exercise. The intermediate factor might be the level of arousal, blood acidosis or accumulation of metabolic waste and/or involvement of different metabolic systems, changes in attentional strategy and modification in humoral function. On the other hand when cognitive performance is performed during exercise, individuals confront a principal physical task of locomotion (e.g. treadmill walking, treadmill running or cycling) and an added cognitive task such as reaction time (RT). Within this framework, a significant decrease in simple reaction time (SRT) performance has been observed during moderate exercise. Considering the imposed physical task, results might be interpreted in terms of attentional resource allocation to running and RT performance which has been defined as dual task when the two are combined.
Literature reviews have proposed that conflicting results could be caused by, in part, the diversity of cognitive tasks used and the various physiological requirements of the exercise bouts. Recently, the statistical technique of meta-analysis has provided researchers with subjective information.[9,10] When no experimental variables were considered, these results have confirmed that acute exercise had no real effect on cognitive performance (effect size ranging from 0.17 ± 0.75 to 0.26 ± 0.69, respectively, for Arcelin et al. and Etnier et al.). However, meta-analytic techniques also allow the ability to identify variables associated with the larger size effects and variables that did not affect cognitive performance. Among them, descriptive reviews or meta-analyses have highlighted the importance of physical task characteristics. The study of the acute physical exercise influence on cognitive functioning could be an interesting approach of the various processes of performance optimisation. The importance of the link between sport performance and cognitive functioning has been highlighted by coaches and athletes as attentional and decisional strategies are frequently important parameters in achieving good performances in sport. This seems particularly true in sports in which there is much information to process in a short time. Athletes are confronted with critical signals and have to extract the significant clues to optimise the signal/noise ratio. For example, in a dual sport performance the opponent tries to mask his intention and one of the athlete’s tasks is to distinguish between feints and the relevant information. Within this framework the chronometric method has been used to study the noise/signal ratio according to the level of expertise; the period of training indicating, for example, a significant effect of expertise level in sport on attentional processes. In the context of the performance optimisation, knowing variables affecting the interaction between physiological and cognitive processes during acute exercise might have practical effects such as training procedures improvement or competition strategies. Therefore, the purpose of this article is to provide the reader with information on the main effects of physical task characteristics on cognitive performance and to provide practical recommendations from the perspective of performance optimisation.
1. Influence of Exercise Intensity
Generally, acute exercise has been claimed to have an inverted U-effect on the performance of a cognitive task. In the literature, an increase in arousal is induced by exercise intensity and has been linked, for example, to an increased heart rate and/or an increased level of perceived exertion (RPE). According to Easterbrook’s cue utilisation theory, a moderate-intensity exercise could improve performance whereas high-intensity exercise would lead to a decrease in cognitive performance. Classically, in exercise physiology moderate intensity corresponds to an exercise intensity below the lactate threshold [LT, i.e. ≈ <70% maximal oxygen uptake (V̇ O2max)] whereas heavy exercise corresponds to an exercise intensity above LT. In such an approach, exercise intensity is associated with changes in the arousal of the central nervous system (CNS). This model describes a curvilinear relationship between the arousal level and the performance so that the optimal performance level corresponds to an intermediate arousal level. As arousal increases, attention narrows and an optimal level is reached when only relevant cues are processed. Further increases in arousal leads to a subsequent attention narrowing and even relevant cues may be missed. This hypothesis of a relationship between exercise-induced arousal and cognitive performance has been tested using electrophysiological techniques such as electroencephalography (EEG). During aerobic exercise, an increase in ‘brain arousal’ has been shown through an increase in beta activity and a decrease in alpha activity. Recent studies investigating the effect of exercise on event-related potentials (ERP), particularly on the P300 component, have given some evidence for the relationship between exercise-induced arousal and cognitive performance improvement.[15,16] P300 reflects the neural activity underlying basic aspects of cognition. An increase in P300 amplitude could be related to allocation of attentional resources. In that context, an increase in P300 amplitude and a decrease in P300 latency have been observed after moderate or heavy aerobic exercise.[15,16] However, using meta-analysis techniques it could be observed that experimental results do not fully support this hypothesis. Furthermore, significant interaction effects between the nature of the cognitive task and exercise intensity may be identified (figure 1). For simple tasks, such as perceptual tasks, a decrease in performance has been observed at all ranges of intensity (effect size ranging from +0.5 to +11) whereas significant improvement has been observed for complex tasks such as decisional tasks at moderate or heavy intensities (effect size: -0.8 and -0.6, respectively).
Therefore, as far as practical implications are concerned, one difficulty is to determine precisely the point where the differences are meaningful in terms of complex cognitive performance. However, there is little quantitative information available about the metabolic load necessary for optimal function in a cognitive task during exercise (table I). Firstly, studies using different incremental protocols have indicated that the optimal zone for cognitive performance ranged from 40 to 60% of V̇ O2max; however, a significant improvement in cognitive performance has been observed for higher intensities in aerobically fit individuals. A theoretical hypothesis was advanced by Chmura et al. to explain the cognitive performance improvement. The improvement effect is explained by a positive effect activation of the CNS linked to the rate of elevation of catecholamines. Recently, Chmura et al. have proposed to use the concept of adrenaline threshold (defined as a sudden increase in blood adrenaline concentration with exercise intensity[6,19]) as an indirect measure of arousal level. They have shown that decisional performance was greater [i.e. choice reaction time (CRT) faster] immediately after the blood adrenaline threshold was reached. In this study, the blood adrenaline concentrations were measured during 20 minutes of exercise. A significant increase in these concentrations was observed at the same time as the cognitive performance improvement. It has been suggested that high levels of blood adrenaline are associated with changes in the CNS that might improve cognitive performance.[20,21] Indirect evidence for this hypothesis has been provided by animal studies showing that a high adrenaline concentration in the brain was associated with an improvement in memory capacities or information processing efficacy. For one particular individual, it would be of interest to use the adrenaline threshold determination to identify the intensity associated with an improvement in memory capacities and information processing performance. Furthermore, in humans, higher plasma adrenaline and noradrenaline levels have been reported after training at the same relative intensity (from 65 to 85% V̇ O2max ). This result which related to a greater stimulation of the sympathetic nervous system, could also explain the beneficial effects of physical training and aerobic physical fitness on cognitive performance during exercise.
2. Effects of Physical Fitness
The hypothesis of an effect of physical fitness on cognitive performance during exercise has been suggested. The failure to control for physical fitness is one of the methodological problems often proposed to explain the diversity of experimental results.[2,27] In early studies, the physical fitness of participants was rarely estimated. Furthermore, when a physical fitness test was performed, the main criterion for physical fitness was aerobic aptitude as assessed by a V̇ O2max test on a treadmill or on a cycle ergometer. This was true regardless of the particular energy demand of the physical task used in the study. Tomporowski and Ellis’s review claimed that physically fit individuals could better perform cognitive tasks than less physically fit individuals. Numerous longitudinal studies have examined the impact of changes in physical fitness upon cognitive performance indicating, for example, that exercise rehabilitation programmes in older adults contribute to improvements in physical functioning and also enhance cognitive functioning and psychological well-being.[28,29] Furthermore, indirect evidence for a positive effect of aerobic physical fitness on cognitive performance has been obtained from comparative electrophysiological studies. For example, increased alpha activity (from the EEG) has been reported in highly aerobically fit (relative to unfit) individuals. Moreover, a positive effect of physical training has been observed on the P300 component. It has been suggested that physical training positively affects ERP by improving cerebral blood flow.
Although evidence for an effect of aerobic physical fitness improvement on cognitive performance has been obtained for chronic exercise, contradictory findings exist relative to the effect of aerobic fitness level on cognitive performance during acute exercise. Recently Magnié et al. did not find any difference in P300 or N400 between sedentary individuals and cyclists after a maximal test to exhaustion. They suggested that the previously observed relationship between physical training and P300 parameters might not necessarily be related to aerobic physical fitness, but to the specificity of the type of training that differs in preferential information processing. In this study, participants were homogenous and performed the same aerobic sport. No significant differences were observed in ERP or P300 component parameters (e.g. mental performance). Furthermore, meta-analyses have provided equivocal conclusions regarding this effect. For example, Etnier et al. have reported an effect size (ES) of 0.33 for studies implementing a chronic exercise and an ES of 0.54 for studies which combined cross-sectional measures with acute bouts of exercise. Furthermore, when a physical fitness indicator was reported, Arcelin did not observe any difference in ES between highly fit individuals (i.e. V̇ O2max > 60ml O2/kg/min) and less fit individuals (V̇ O2max < 60ml O2/kg/min); ES = 0.22 ± 0.20 vs 0.18 ± 0.15, respectively.
In summary, experimental results indicate that improvement in physical fitness level following a training programme leads to an improvement in cognitive functioning, but relatively few studies have examined the effect of physical fitness on cognitive performance during or after an acute bout of exercise. Within this framework, the general positive effect of arousal induced by exercise on cognitive performance seems to be observed independently of aerobic fitness level. These results remain difficult to compare, because of differences in physical tasks used and because only comparative studies are available. It would be of interest to carry out longitudinal studies to better understand the effect of physical fitness change on cognitive performance during or after acute exercise.
3. Influence of Exercise Duration
During prolonged exercise at moderate intensity the physiological effects of exercise duration are well known. Numerous studies have shown a progressive increase in metabolic load with increased sweating, an enhanced heart rate and respiratory rate or a change in plasma levels of adrenaline or noradrenaline. Therefore, according to the Inverted U Hypothesis, an improvement in cognitive performance could be expected for a moderate increase in metabolic load. For example, in a meta-analytic review, Petruzzello et al. indicated that acute exercise lasting at least 20 minutes leads to a reduction in state and trait anxiety. However, when exercise duration lasts more than 1 hour the appearance of fatigue symptoms have (generally) been reported. Thus, it is possible that beyond 1 hour of exercise a further increase in exercise duration leads to an alteration of cognitive performance.
Increased fatigue has commonly been observed after sustained exercise although detrimental effects on mood or mental performance seem small.[2,33] Whether there is a deterioration in cognitive performance or not after prolonged exercise remains unclear. Since few studies were available on this topic before 1998, meta-analysis failed to give any consistent results. Etnier et al. found no relationship between exercise duration and cognitive performance (R2 = 0.02, ES not reported) while Arcelin, using nine studies indicated a slight, but nonsignificant improvement in cognitive performance for exercise longer than 10 minutes (ES = -0.13). Tomporowski and Ellis suggested that well-trained individuals could compensate for the negative effects of fatigue when they have to perform cognitive tasks in extremely fatiguing conditions. The fatigue effect could be modified by incentive variables such as an individual’s motivation. After such exercises, well-trained individuals have been reported to be tired, but not exhausted, since no significant depression of CNS was observed (from the critical flicker fusion test2).
However, in trained individuals and for exercise lasting more than 20 minutes, recent studies have consistently indicated a positive effect of exercise duration on cognitive processes. When a complex (e.g. CRT) or a simple (e.g. SRT) cognitive task was performed during or immediately after exercise, an improvement in cognitive performance was observed with long-term exercise.[6,34,35] The hypothesis behind this result is that the increase in metabolic load associated with long-duration exercise induces an increase in arousal level that would improve cognitive functioning. Moreover, physiological changes observed during prolonged exercise are observed when the arousal level increases. Diverse contributing factors could be proposed to interpret enhancement of cognitive efficacy during exercise. First, contemporary neurophysiological studies have identified several mechanisms that could explain a causal link between the physiological state during exercise and cognitive performance. It has been suggested that during prolonged exercise an increase in cerebral blood flow or in brain neurotransmitter levels, such as catecholamines and/or endorphins,[21,36] could lead to an improvement in cognitive performance. For example, as observed for exercise intensity, experimental results showed that improvements in cognitive performance during a 1-hour exercise period were concomitant with increases in catecholamine levels. Although various theories have been proposed, actual mechanisms supporting a functional link between neurotransmitter changes, prolonged exercise and cognition are certainly complex and still unknown. Therefore, it is difficult to identify practical recommendations from these observations.
Secondly, altered resource allocation may play an important role. Recent studies have suggested the role of resource allocation as an explanation for an improvement in complex cognitive performance during exercise. According to Kahneman, attentional resource capacity is variable and related to an estimation of task requirements, the more attractive the task perceived, the more the individual releases in that task processing capacity. This hypothesis is in agreement with Tomporowski and Ellis. If the cognitive task is without challenge for the individual and does not require enough attentional resources, no exercise effect is observed on the cognitive performance. These conclusions indicated the importance of motivational factors in the relationship between exercise and cognitive processes. These authors highlighted the importance of mental strategy preparation during sports requiring both cognitive and physiological demands.
However, when exercise duration lasts more than an hour, the appearance of fatigue symptoms is commonly reported. One of the main effects of prolonged exercise is heat stress induced by physical work. Numerous studies have analysed the effect of heat stress on cognitive performance. It has been suggested that cognitive performance could be altered as thermal homeostasis of the exercising participant is disturbed. Furthermore, during prolonged exercise several factors such as dehydration or hypoglycaemia are associated with heat stress and could lead to the appearance of central fatigue and a decrease in cognitive performance.
3.1 Effects of Exercise-Induced Heat Stress and Dehydration on Cognitive Performance: The Role of Fluid Ingestion
Heat production is low at rest, but can exceed 80 kJ/min at a high work rate. This stress is directly related to the capacity to perform long-duration exercise. Several reports have indicated reduced running performance at rectal temperatures between 39.7 and 40.3°C. This negative effect can be enhanced by environmental conditions under which the exercise is performed. When ambient temperature and humidity are high, the capacity to sustain prolonged exercise is reduced. Therefore, heat stress needs to be expressed as effective temperature (ET)3 or wet bulb globe temperature (WBGT). The effect of raised body temperature on cognitive performance seems to depend on the cognitive task. Some results have indicated that a small increase in core body temperature of 2°C could improve speed of calculation or reasoning while other authors observed that accuracy in mathematics was impaired at a body temperature of 38.6°C.[43,44]
These results suggest a categorisation of heat stress effects of exercise on cognitive performance similar to those found for environmental heat stress. It has been reported that perceptual or simple tasks were not affected by heat exposure and may have enhanced levels of performance. In contrast, for more complex tasks, decrements in performance have been shown to occur systematically for a 31 to 35°C ET range of temperature. Furthermore, one of the main physiological processes associated with heat stress is the increase in sweating rate, which prevents body temperature from rising. This results in loss of body water and electrolytes leading to dehydration. Several studies have shown that the response to dehydration was a significant reduction in cognitive performance for various abilities such as decisional or perceptual tasks.[45–47] After exercise-induced dehydration (2 hours on a treadmill), Cian et al. indicated that the time response was lengthened for both perceptual and decisional tasks. This reduction in performance occurred irrespective of the dehydration mode (exercise or heat environment) and seems to be proportionate to the degree of dehydration becoming significant after a loss of 2% bodyweight. When dehydration was followed by fluid ingestion corresponding to 100% of bodyweight loss (euhydration), significant improvement in cognitive performance (long-term memory) was observed (figure 2). The amount of fluid ingested also affects cognitive performance during prolonged exercise. Recently, Cian et al. reported a significant improvement in short-term memory during hyperhydration (21 ml/kg of bodyweight) compared with euhydration after a 2-hour run. Several factors have been suggested to explain the beneficial effect of hydration during or after exercise. These include a decrease in cortisol levels, an increase in serum arginine, increased vasopressin release, and an increase in glycerol. Hydration leads to a decrease in cortisol levels, which are known to increase with dehydration and to have a detrimental effect on memory. Similarly, fluid ingestion is related to cerebral vasopressin levels, which have a positive effect on memory, and glycerol levels, which have an effect on cognitive performance, through glucose supply to the CNS.[46,47] However, even if the relationship between fluid intake and cognitive performance is not clearly understood, regular hydration during exercise is necessary to balance the negative effects of exercise-induced heat stress or dehydration on cognitive performance.
3.2 Effects of Carbohydrate Availability
Several mechanisms have been suggested to explain fatigue during prolonged exercise. Among them, muscle glycogen depletion and/or hypoglycaemia have been related to muscle fatigue as well as central fatigue. Considerable data are available from pharmacological studies indicating that hypoglycaemia affects brain function, operationalised as cognitive performance or ERP (P300). Furthermore, cognitive dysfunction induced by hypoglycaemia did not improve immediately following elevation of plasma glucose levels. The period required for full recovery of cerebral function after intravenous glucose was longer than 30 minutes and depended on the severity of hypoglycaemia.
Ingesting a carbohydrate-electrolyte (CHO-E) solution during prolonged submaximal exercise has been reported to delay the onset of fatigue and to improve endurance performance. The influence of carbohydrate ingestion on cognition during prolonged exercise has generally been studied from ratings of RPE. Results indicate that carbohydrate availability attenuates the exertion perception during the later stages of exercise. A few studies have investigated the effect of CHO-E supplementation on cognitive performance following a prolonged exercise lasting more than an hour with mixed results. Reilly and Lewis showed that carbohydrate ingestion could be beneficial to cognitive performance during a 120-minute cycling task at 60% V̇ O2max. However, Ivy et al. failed to observe any effect of carbohydrate ingestion on RT performance during a 150-minute walk at 40% V̇ O2max. Recently, results presented by Collardeau et al. seemed to confirm the previous study of Reilly and Lewis for exercise intensities above 60% V̇ O2max. Collardeau et al. indicated that complex cognitive performance could be improved after a 2-hour run performed at 75% V̇ O2max (15.4 ± 0.5 km/h) by well-trained triathletes drinking a 5.5% CHO-E solution (glucose, fructose, maltodextrins, sodium: 20 mEq, potassium: 5 mEq) every 15 minutes (2 ml/kg of bodyweight) [figure 3]. Ingesting carbohydrate during exercise minimised the negative effect of central fatigue induced by prolonged exercise on cognitive performance.
It has been suggested that brain tryptophan levels increase during sustained exercise resulting in central fatigue. Tryptophan levels have been reported to affect behavioural responses and recent research involving tryptophan and fatigue indicate that nutrition could play an important role. It has been observed that the ingestion of a 6% CHO-E solution during exercise might lead to a decrease in plasma fatty acids and plasma tryptophan levels delaying the onset of fatigue. However, even if recent studies have focused on the role of tryptophan, it should be noted that central fatigue is more complex than an increase in serotonin levels in the brain and further studies are needed to validate the importance of tryptophan increases on cognitive function, and to identify the role of other central factors on cognitive performance.
Recent studies have also highlighted the role of resource allocation to explain improvement of cognitive performance during exercise.[38,56] Relationships have been observed between mental load and resource allocation as well as the rating of RPE. The role of carbohydrate ingestion on RPE has been widely studied and an improvement of RPE (lower scores) with carbohydrate ingestion has been classically described. Therefore, drinking a CHO-E solution during exercise could lead to a decrease in mental load associated with the perception of effort and to a higher involvement in attentional resources during the RT task. This last hypothesis emphasises the role of motivational factors in long-duration events indicating that the effect of fatigue could be modified by a positive effect of an increase in arousal level during exercise and/or by incentive variables.
4. Influence of Physical Task Complexity
During experimental studies, most physical tasks are cyclic exercise such as cycling, walking and running. Interactions between energetics and cognitive processes are studied using a dual task paradigm. The participant simultaneously performs a mechanical work task and a controlled and/or varying intensity cognitive task. In the past decade some consistent results have been observed showing a decrement of SRT during moderate exercise. With regard to the imposed physical task, the result may be interpreted by the allocation of attention during dual task performance. More recently several studies have related cognitive performance during a dual task to the constraints imposed by the underlying coordination mechanisms.[58–60]
Within this framework, the behavioural adaptation of the individual is commonly described as a function of: (i) the task constraints; and (ii) the constraints of the performer.
During dual task performance, the increase in metabolic load induces a significant change in the relationship between the constraints of the task and those of the performer. It has been suggested that an optimal zone exists for the energetic and cognitive systems.[7,58] Optimal mechanisms in tasks requiring the use of cyclical skills have been well documented. Investigators have demonstrated optimal walking speed, optimal ratio between stride length and rate during both walking and running, and the optimal pedalling rate on a bicycle. Several optimal criteria have been described such as metabolic or mechanical cost, neuromuscular fatigue and RPE. Research has also demonstrated the individual’s ability to identify among these different criteria the level of optimal demand with great precision when the task is familiar, that is, he/she would spontaneously choose an optimal walking speed, stride length or rate, and rate of pedalling.
The effects of an optimal or non-optimal demand on cognitive processes have been tested in only two studies. Sajiki et al. observed that the walking cadence at which physiological cost was minimised matched that at which SRT was the shortest. This result could be compared with the study conducted by Brisswalter et al. using a cycling task. These authors observed a strong correlation between oxygen uptake and SRT performance. RT was shorter at the energetically optimal cadence (60 rpm) compared with 30, 40 or 80 rpm. Furthermore, no significant difference was found between an RT at 60 rpm and at the freely chosen rate (63 ± 2.5 rpm). These results suggest that, for a given task and a constant power output, the attentional demand of each task could vary with its energy demand.
Recently, attentional demand associated with cyclic patterns has been analysed.[58–60] Using a bimanual coordination task, these experiments have been designed to assess the attentional demand required by the CNS to maintain and stabilise different coordination patterns at different frequencies. These results have indicated that pattern stability and attentional demand co-varied. The steadiest pattern was more economical to maintain and a loss of pattern stability observed around the freely chosen frequency was related to an increase in central cost (figure 4). It could be suggested that modifications in metabolic or neuromuscular constraints during cycling, running or walking tasks would be reflected in CNS cost. This hypothesis is in agreement with the self-optimisation approach developed in dynamic models of locomotor patterns. This approach postulates that biological systems coordinate in ways to give ultimate performance at the least cost; however, the nature of the cost must be identified. The optimal criteria could also be the minimisation of metabolic and/or mechanical cost, the impact force, the effort to maintain the stability of pattern,[31,61] or the attentional cost.[58,60]
When physical parameters are measured, recent studies have indicated that it is possible to improve cognitive performance during acute exercise. The rationale behind this observation is that physiological changes from exercise are described as increases in arousal. However, the relationship between arousal and exercise is still not clear. Arousal is a non-unitary concept and there are complex interactions between arousal and several multidimensional psychological concepts such as motivation and attention.
Despite the lack of a clear functional hypothesis to explain the relationship between exercise and cognitive processes, several recent experimental findings should be emphasised. For decisional tasks, an optimal zone of exercise intensity seems to exist for cognitive performance improvement at moderate to heavy exercise intensities (≈40 to 80% V̇ O2max). The beginning of this zone has been reported to coincide with the adrenaline threshold calculated during incremental exercise. In addition, during prolonged exercise, a decrement in cognitive performance has rarely been observed. In contrast, despite the possible appearance of fatigue, significant improvements in both perceptual and decisional tasks have been observed for moderate exercise lasting more than 20 minutes. This improvement could be enhanced by carbohydrate or fluid ingestion during exercise. Finally, during cyclic tasks, a zone of optimal cognitive functioning seems to exist at the freely chosen pattern. This suggests a relationship between biomechanical or energetic constraints and cognitive constraints during physical exercise. One surprising conclusion is the apparent lack of physical fitness effect on cognitive performance during exercise. Further research is needed for determining functional factors relating to optimal cognitive performance during exercise that could be improved through physical training.
Apositive effect size represents an impairment of performance (e.g. longer reaction time),while a negative effect size represents an improvement (e.g. shorter reaction time).
Effective temperature (ET) and wet bulb globe temperature (WBGT) are global indices using dry temperature, relative humidity and air velocity.