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date: 23 September 2017

Physical Activity, Physical Fitness, and Cognition

Summary and Keywords

There is substantial interest in identifying the behavioral means by which to improve cognitive performance. Recent research and commercial ventures have focused on cognitive training interventions, but evidence suggests that the effects of these programs are small and task-specific. Researchers have also shown interest in exploring the potential benefits of physical activity for cognitive performance. Because the effects of physical activity have been found to be small to moderate and to be more global in nature, interest in physical activity has been growing over the past several decades. Evidence regarding the efficacy of physical activity is provided through cross-sectional studies, longitudinal prospective studies, and randomized controlled trials. When reviewed meta-analytically, small-to-moderate beneficial effects are reported for children, adults, older adults, and cognitively impaired older adults, and these effects are evident for a wide range of cognitive domains, including executive function, memory, and information processing. Researchers are currently focused on identifying the mechanisms of these effects. Most of this research has been conducted using animal models, but there is a growing body of literature with humans. From this evidence, there is support for the role of changes in cerebral structure, hippocampal perfusion, and growth factors in explaining the observed benefits. Thus far, however, the literature is quite sparse, and future research is needed to clarify our understanding of the mechanisms that provide the causal link between physical activity and cognitive performance. Research is also focused on understanding how to increase the benefits by potentially combining cognitive training with physical activity and by identifying the genetic moderators of the effects. These lines of work are designed to elucidate ways of increasing the magnitude of the benefits that can be obtained. At this point in time, the evidence with respect to the potential of physical activity for benefiting cognitive performance is quite promising, but it is critical that funding agencies commit their support to the continued exploration necessary to allow us to ultimately be able to prescribe physical activity to specific individuals with the express purpose of improving cognition.

Keywords: exercise, epidemiology, BDNF, VEGF, IGF-I, hippocampus

Introduction

Interest in the development of effective interventions to benefit cognition has surged in recent years, as demonstrated by the unprecedented research attention leveraged through efforts such as U.S. President Barack Obama’s commitment of $300 million to brain research in 2013–2014 and the European Brain Council’s naming of 2014 as the Year of the Brain. Much of this research has focused on interventions for older adults because of the known association between advancing age and cognitive decline (Schaie, 1994; Verhaeghen & Salthouse, 1997) and in anticipation of the predicted rise in prevalence of age-related cognitive decline, Alzheimer’s disease, and dementia that will accompany the growth in the population of older adults (Alzheimer’s Association, 2014; Hebert, Scherr, Bienias, Bennett, & Evans, 2003).

In considering ways to improve cognitive performance, researchers are pursuing many directions. One popular option is cognitive training with a particular recent interest in computerized cognitive training. Evidence supports the feasibility and efficacy of cognitive training programs that have been shown to improve performance in the targeted cognitive domains (Ball et al., 2002; Rebok, Carlson, & Langbaum, 2007; Stine-Morrow, Parisi, Morrow, Greene, & Park, 2007; Willis & Schaie, 1986; Willis et al., 2006). When reviewed meta-analytically, evidence supports the thesis that cognitive training provides modest cognitive performance benefits for cognitively normal older adults (Kelly et al., 2014a; Lampit, Hallock, & Valenzuela, 2014) and for individuals with dementia (Garcia-Casal et al., 2016). The promising gains in cognitive performance in response to training have likely contributed to the burgeoning “brain training” industry—a nearly billion-dollar industry (“Brain sells: Commercialising neuroscience,” 2013) that is clearly meeting a perceived need by the public for interventions to improve cognitive performance. However, these cognitive training interventions may have limited public health implications because the reported effects have typically been modest in size and restricted in scope (Ball et al., 2002; Rebok et al., 2007; Willis et al., 2006). That is, one of the challenges of cognitive interventions is that they tend to be task specific, with improvements in performance and retention of training gains typically being demonstrated only for cognitive domains that have been specifically trained (i.e., near transfer). Additionally, meta-analytic results indicate that there are no benefits in response to unsupervised at-home training, as is typical with commercial, computerized brain-training products (Lampit et al., 2014).

Although there is an ongoing debate in the peer-reviewed literature (Owen et al., 2010; Rabipour & Raz, 2012) and the popular press (Hambrick, 2014; Mole, 2016) regarding the potential of computerized cognitive brain training, at this time the research evidence does not support broad cognitive benefits from cognitive training programs. Fortunately, physical activity (PA) provides a viable alternative because of its potential to achieve more general cognitive benefits that are evident in measures of global cognition and across cognitive domains.

In light of the sedentary lifestyle that is increasingly prevalent in modern societies, it is important to recognize that increases in PA may be critical not only for physical health, but also for brain health. Importantly, PA has been shown to benefit cognitive performance across many cognitive domains, and these effects have been observed across the life span. These pervasive effects may be due to the fact that PA has been shown to have positive effects on cerebral structure and/or growth factors supporting brain health. This article reviews evidence relative to the benefits of chronic PA for adults and children, mechanisms of the effects, a genetic factor that may moderate the effects, and the effects of combined cognitive training and PA interventions.

Physical Activity and Cognition in Adults

Cross-sectional research

Early research in the area of PA and cognitive performance adopted cross-sectional designs and focused on behavioral measures of cognitive performance. The seminal study was conducted by Spirduso (1975) who compared reaction time performance between older men who were lifetime racketsports players and a group of sedentary individuals. Results showed that reaction time was faster for the active older adults, suggesting a benefit of regular PA participation. However, these results were limited by the use of a cross-sectional design, which precludes our ability to determine causation. In other words, although it is possible that participation in racketsports resulted in faster reaction times, it is equally plausible that faster reaction times provided a competitive advantage that attracted these older men to play racketsports. Importantly, more recent evidence from longitudinal prospective studies and from randomized controlled trials (RCTs) has demonstrated similar findings and provides stronger evidence of a causal link between PA and cognition.

Prospective studies

Longitudinal prospective studies have focused almost exclusively on older adults. In these studies, participants are recruited and screened for cognitive normality at baseline. PA or aerobic fitness is also measured at baseline and is used to predict changes in cognitive performance that occur over time. Typically, participants are followed for several years (the range for currently published studies being 1–21 years), and cognition is measured one or more times over the course of the study. Numerous prospective studies have been conducted with cognitively normal individuals, who are then followed over time to assess change in cognitive performance using standardized cognitive measures or to evaluate clinical cognitive impairment through diagnostic measures. Many of these studies have been criticized for relying on self-report measures of PA (Schlosser Covell et al., 2015). However, there is one study in which an objective measure of PA was used (Buchman et al., 2012) and this study provides a good exemplar of the evidence showing a protective effect of PA on subsequent cognitive performance.

Buchman and colleagues (2012) measured cognitive performance at baseline and follow-up (average = 3.5 years after baseline) and assessed total daily PA at baseline by asking participants to wear an accelerometer 24-hours a day for 10 days. Data were available for 716 individuals who were cognitively normal at baseline, who were present for both cognitive assessments, and who had sufficient accelerometer data for inclusion. The results of this study indicated that those who had more total daily PA at baseline were significantly less likely to be diagnosed with Alzheimer’s disease over the next ~3.5 years (hazard ratio, HR = 0.477). This protective effect remained even after controlling for age, sex, education, self-reported PA, and frequency of participation in social and cognitive activities. Based on these findings, the authors concluded that PA was associated with a lower risk of developing Alzheimer’s disease and suggested that PA should be encouraged in older adults. However, they also recognized that the relationship they observed might not be causal, and so they explored alternative explanations for their observed relationships. Given that data prior to PA assessment was available for many of the participants in this study, the authors tested two competing reasons for their results.

First, they tested the hypothesis that lower cognitive performance might lead to less PA. In 438 participants with two or more cognitive tests prior to PA assessment, they found that the rate of cognitive decline prior to PA assessment was not predictive of total PA. Second, they considered the hypothesis that baseline cognitive performance might predict a subsequent decline in PA. In 595 participants with two or more measures of PA, they found that baseline cognitive performance was not predictive of a decline in PA. Given that they were able to rule out these competing explanations of their results, this study provides strong prospective evidence supporting their conclusion that “physical activity may be protective of and forestall the development of AD [Alzheimer’s disease]” (Buchman et al., 2012, p. 1328).

There are also some studies in which objective measures of physical fitness were used (e.g., peak VO2, VO2max) (Barnes, Yaffe, Satariano, & Tager, 2003; Nyberg et al., 2014; Wendell et al., 2014; Zhu et al., 2014) as a predictor of subsequent cognitive performance. The distinction between exploring PA and physical fitness as the predictor of interest is an important one. Although PA clearly contributes to greater levels of physical fitness, it is important to recognize that a substantial portion of the variability in VO2max (the gold standard measure of aerobic fitness) in children (Schutte, Nederend, Hudziak, Bartels, & de Geus, 2016) and adults (Bouchard et al., 1998) is genetically determined. Hence, although these studies consistently demonstrate that lower levels of baseline fitness are predictive of subsequent cognitive decline, the use of fitness as the predictor introduces potential confounds and is not merely a proxy measure of PA.

At this point in time, over 25 nonexperimental prospective studies on PA and cognition have been conducted, and this evidence has been meta-analytically reviewed on three occasions. A meta-analytic review is a statistical review in which authors collect all of the studies on a given well-defined topic, calculate one or more average effect sizes for each study, and then calculate average effect sizes either across the entire body of literature or for subsets of the literature identified by the levels of a moderating variable (e.g., sex or age group). The meta-analytic reviews of prospective studies consistently support the idea that participation in PA is associated with better cognitive performance in the future. Specifically, the meta-analyses show that PA reduces cognitive decline over time (Sofi et al., 2011), decreases the risk of Alzheimer’s disease (Daviglus et al., 2011; Hamer & Chida, 2009), and lessens the risk of dementia (Hamer & Chida, 2009). Odds ratios from these reviews indicate that those in the highest PA group benefit from a reduction in the risk of negative cognitive outcomes by 28 to 45 percent as compared to the least active comparison group. Thus, overall, the evidence from prospective studies helps confirm that PA protects cognitive performance by older adults in the face of advancing age or clinical cognitive impairment.

Although the evidence from prospective studies is supportive of a protective effect of PA on cognitive performance in advancing age, one of the primary limitations of this body of evidence is that the variable that is viewed as the independent variable (PA in this case) is not experimentally manipulated. Although statistical tests can be used to assess the extent to which changes in measured variables (i.e., PA or cognition) outside the study “window” are predictive of baseline or follow-up measures (i.e., Buchman et al., 2012), there is, of course, no way to consider variables that are not actually assessed in the study design. Thus, it is possible that those who are more physically active at baseline are already different from those who are not as physically active (perhaps in terms of genetic determinants, underlying brain structure, or prodromal Alzheimer’s disease), and that these differences are themselves the causal link to cognition irrespective of PA. Given this limitation, RCTs are critical so that PA can be experimentally manipulated, resultant changes in cognition can be observed, and causal relationships can be inferred.

Randomized controlled trials (RCTs)

At this time, there are numerous RCTs in which participants have been randomly assigned to an exercise program or a control condition for a period of weeks or months. Differences in cognitive behavior at the posttest or differences in changes in cognitive behavior from pretest to posttest are then observed relative to group assignment. In these studies, the length of intervention ranges from weeks to months, and the PA program typically includes aerobic activities (e.g., walking, Tai Chi) and/or resistance training. Across most of these studies, evidence is provided of beneficial effects of PA on cognitive performance. However, there is substantial variability in terms of which cognitive domains have been shown to be sensitive to the effects of exercise. Because of the variability in findings, meta-analyses provide us with important information relative to the overall effect of a PA manipulation on cognitive performance. This literature has been reviewed meta-analytically on several occasions, with some reviews focused on all cognitively normal adults, others on cognitively normal older adults, and still others on adults with clinical cognitive impairment.

Cognitively normal adults

The first meta-analytic review of this literature was conducted by Etnier et al. (1997), who used broad inclusion criteria and concluded that chronic PA had a significant positive effect on cognitive performance (g = 0.33). The authors then presented results for 17 studies in which an experimental design was used and reported a small positive average effect size (g = 0.18). This finding for the RCTs is consistent with that reported more recently by Smith et al. (2010) who meta-analytically reviewed 29 RCTs conducted with adults (≥ 18 yrs). They analyzed average effect sizes relative to cognitive domain and reported that aerobic exercise has a significant small benefit for measures of attention and processing speed (g = 0.16), executive function (g = 0.12), and memory (g = 0.13).

Cognitively normal older adults

Several meta-analytic reviews have limited their inclusion criteria to only look at RCTs conducted with older adults. These reviews have also generally supported a beneficial effect of exercise but differ with regard to the effects for specific cognitive domains.

Colcombe and Kramer (2003) reviewed 18 RCTs with older (average age > 55 yrs) adults and reported a significant moderate effect size across all studies (g = 0.48). They then examined cognitive domain as a moderating variable and reported that the greatest effects were observed for studies assessing measures of executive function (g = 0.68) as compared to other cognitive domains (controlled: g = 0.46, spatial: g = 0.43; speed: g = 0.28). In conjunction with the frontal lobe hypothesis which proposes that PA preferentially benefits frontal lobe activities (which include executive function) (Kramer, Humphrey, Larish, Logan, & Strayer, 1994), this finding was the impetus behind a nearly exclusive focus on executive function outcomes for an extended period of time. However, this focus may in some ways have been premature because there is some evidence to suggest that the large effect size (ES) reported for executive function measures in this review might not have been representative of the literature. In particular, Smith et al. (2010) pointed out that Colcombe and Kramer included in their review two relatively large effect sizes from studies that did not meet the inclusion criteria (because they were not RCTs). Smith et al. suggest that this may have artificially inflated the reported effect size for executive function. Additionally, Etnier and Chang (2009) have pointed out that executive function is a broad umbrella term that encompasses different types of cognitive function (e.g., shifting, updating, inhibition) that control other basic cognitive processes. Given that the effects of PA on cognitive performance appear to be task specific, future researchers in this area should recognize that the beneficial effects of PA on cognitive performance are evident across many cognitive domains and are very complex. This point is also made evident by the results of a meta-analytic review on memory in which effect sizes were shown to differ, depending on the specific type of memory being assessed (Roig, Nordbrandt, Geertsen, & Nielsen, 2013). Roig and colleagues meta-analytically reviewed randomized and nonrandomized controlled trials and trials using within-subjects designs to explore the effects of chronic PA on memory performance by adults. Their results showed that for chronic PA programs, there was a small positive effect on short-term memory (SMD = 0.15), but that effects were negligible for long-term memory (SMD = 0.07). Hence, even within a cognitive domain (e.g., memory), the effects of exercise appear to have task-specificity.

In contrast to the moderate effect size reported by Colcombe and Kramer (2003) for RCTs conducted with older adults, other meta-analytic reviews have published much less promising results. These meta-analyses are mentioned here because it is important to consider what these less promising reviews mean in terms of our interest in continuing to pursue PA as a means to improve cognitive performance. Importantly, there is a critical limitation of these reviews which should be considered in judging the veracity of this evidence.

Angevaren and colleagues published two meta-analyses reviewing RCTs with older adults (> 55 years). An additional inclusion criterion was that the studies had to be designed to improve cardiovascular fitness. Importantly, these reviews should be considered together because there is substantial overlap in the studies included in the reviews. Angevaren, Aufdemkampe, Verhaar, Aleman, and Vanhees (2008) report on 11 studies, and Young, Angevaren, Rusted, and Tabet (2015) report on 12 studies, but both include 9 of the same studies. Thus, these meta-analytic reviews provide evidence from essentially the same body of literature. Angevaren et al. concluded that there is evidence for small improvements in cognitive speed (SMD = 0.26) and attention (SMD = 0.26), but observed that the majority of comparisons yielded nonsignificant effects. Similarly, Young et al. reported that “[t]here was no evidence of benefit of the aerobic exercise intervention in any cognitive domain” (p. 2). A critical limitation of these meta-analyses is that the reviewers did not calculate an overall effect size for the effects of PA on cognitive performance, but rather calculated average effect sizes in 25 smaller subgroups of the data which then included only 1–8 effect sizes. Given the small number of effects considered and the previous evidence suggesting that the expected effect sizes are in the small-to-moderate range, the variability in effect sizes would have likely outweighed the magnitude of the effect, so that the summary statistics were not statistically different from zero. Further, the studies reviewed also represented a wide variety in the cognitive tasks used (more than 30 different tests) and used interventions of relatively short length (average of approximately 15 weeks), which would have further limited the ability to observe significant benefits.

Another relatively recent meta-analytic review has also reported findings that are not indicative of strong benefits of PA for cognitive performance. Kelly et al. (2014b) included RCTs testing the effects of aerobic exercise, resistance training, or Tai Chi on executive function or memory in older adults (> 50 years) and conducted between 2002 and 2012. They found 25 studies that met their inclusion criteria, but in their review they also did not calculate a single overall effect size, but rather calculated average effect sizes in small subsets of studies identified based on all possible combinations (n = 81) of exercise condition (n = 3), comparison condition (n = 3), and cognitive domain (n = 9). Hence, they reported average effects when combining only 2–6 effect sizes across studies and, again, not surprisingly reported that the majority of the comparisons (n = 26) resulted in effect sizes that were not statistically different from 0. However, they did report that resistance exercise significantly improved reasoning as compared to stretching/toning, and that Tai Chi significantly improved attention and processing speed relative to a no-treatment control. Hence, these findings again indicate that the effects of physical activity on cognitive performance are small but also suggest that they may differ based on the particular mode of physical activity performed.

Summary for cognitively normal

To summarize the evidence from meta-analytic review of RCTs conducted with cognitively normal adults and older adults, it appears that PA results in a small positive effect for most cognitive domains. This is evident in all of the reviews that report an effect size for cognitive performance overall or for a broadly defined cognitive domain (e.g., executive function) when comparing PA (broadly defined) to a control condition (broadly defined). Although there are also meta-analyses that report negligible effects of PA on cognitive performance, it is important to emphasize that these reviews provide an illustration of the importance of using meta-analytic techniques to provide a statistically powerful summary of a large body of empirical evidence, so that small effects can be identified which might otherwise be masked by large variability across effects and small sample sizes within individual studies. In addition, the relationship between PA and cognition may be moderated by many variables, including the length of the exercise program conducted, the type of cognitive function assessed, the cognitive task employed, and the exercise modality examined. The overall message from this literature appears to be that the effects of PA on cognitive performance in cognitively normal adults are small and that large sample sizes are necessary for these effects to be shown to be reliable.

Clinically cognitively impaired adults

The aforementioned meta-analytic reviews were limited to RCTs with cognitively normal individuals. There is also evidence supporting the beneficial effects of PA for cognitive performance by those who are already experiencing clinical cognitive impairment. As one might expect, a relatively small number of RCTs have been conducted with persons with mild cognitive impairment (MCI) or Alzheimer’s disease. Given the small number of trials, it is promising that significant positive effects have been observed in meta-analytic reviews of this literature. Gates et al. (2013) reported on studies with older adults (> 65 yrs) diagnosed with MCI and found that the effect sizes for executive function, memory, and information processing were not significant, but that a small positive effect was observed for verbal fluency. Wang et al. (2014) conducted a meta-analysis on nonpharmacological interventions with patients with MCI. They calculated ES for cognitive training protocols (standard mean difference, SMD = 0.37) and for aerobic exercise (SMD = 0.25) and reported significant positive benefits for both. Subsequently, Zheng, Xia, Zhou, Tao, and Chen (2016) reviewed 11 RCTs with participants with mild cognitive impairment (MCI) and reported that PA resulted in significant improvements in global cognitive ability assessed using the Mini-Mental State Exam (mean difference, MD = 0.98) and the Montreal Cognitive Assessment (MD = 2.7) and in smaller significant improvements in immediate recall (SMD = 0.29) and delayed recall (SMD = 0.22).

Two meta-analyses have also been conducted to summarize the literature on PA and cognitive performance in persons with dementia. Forbes et al. (2013) reviewed 14 RCTs and reported a significant positive effect (SMD = 0.55). Strohle et al. (2015) identified a small number of RCTs conducted with persons diagnosed with Alzheimer’s disease based on established clinical criteria or MCI based on Petersen criteria and found that significant positive benefits resulted from aerobic exercise programs for both (Alzheimer’s: n = 4, effect size = 0.83; MCI: n = 6, effect size = 0.20).

Summary for clinically cognitively impaired

In summary, although a smaller number of RCTs have been conducted with clinically cognitively impaired adults, the results are extremely promising. Meta-analytic reviews show that small-to-moderate effects can be observed in response to PA programs.

Overall summary

Across various adult populations, participation in PA programs results in statistically significant benefits to cognitive performance. However, these positive effects are not observed in all RCTs and are only modest in size. One of the most important challenges for future researchers is to gain a better understanding of the variability in the results of these RCTs so that PA programs can be more consistently administered to achieve cognitive benefits. One way to do this is by understanding more about the mechanisms that explain the observed benefits. Understanding the mechanisms may provide insight into the exercise prescription that is needed to achieve benefits. That is, at this time, the specifics of the exercise itself that are essential have not been elucidated. Given that exercise is a complex behavior that includes modality (e.g., aerobic, Tai Chi, resistance training), duration (minutes per session), intensity (low, moderate, vigorous), frequency (days per week), and length (e.g., weeks, months, years), an understanding of mechanisms is critical to guiding our design of PA programs. A second way to better understand the variability in previous findings is to further consider individual characteristics that might moderate the efficacy of PA. Current evidence with respect to mechanisms is discussed first for adults and children and this is followed by a consideration of individual characteristics that have the potential to moderate the effects.

Mechanisms

Foundational to understanding how PA might be implemented to benefit cognitive performance, it is important to identify the mechanisms through which such effects may occur. Early research focused on cardiovascular fitness as a potential mediator of the effects, but meta-analytic evidence does not support this putative mechanism (Etnier, Nowell, Landers, & Sibley, 2006). More recently, there is a growing body of literature focused on cerebral structure and growth factors as potential underlying mechanisms of cognitive benefits. These are important directions for research as the elucidation of the specific mechanisms supporting behavioral benefits is a necessary step toward being able to prescribe PA to improve cognitive performance.

Cerebral Structure

There is evidence supporting the possibility that PA benefits cognitive performance because of associated benefits to cerebral structure. Evidence supporting this contention comes from animal studies that have consistently reported angiogenesis (increases in vasculature) and neurogenesis (increases in neural cells) in response to exercise (Cotman & Berchtold, 2002; van Praag, Christie, Sejnowski, & Gage, 1999; van Praag, Kempermann, & Gage, 1999; van Praag, Shubert, Zhao, & Gage, 2005). Importantly, animal studies also show that these changes in cerebral structure are paralleled by improvements in behavioral measures of cognitive performance (van Praag, Christie, et al., 1999; van Praag et al., 2005).

Studies with humans rely on noninvasive measures of cerebral structure through the use of magnetic resonance imaging (MRI). Through a series of studies, evidence has matured from cross-sectional to experimental and has begun to establish ties to behavioral outcomes. Colcombe and colleagues (2003) conducted the seminal study with humans demonstrating a relationship between aerobic fitness and cerebral structure. In cognitively normal older (> 55 yrs) adults, they observed that the brain regions most affected by age-related deteriorations in gray and white matter were the same brain regions that showed the greatest benefits associated with aerobic fitness.

Colcombe and colleagues (2006) then followed up this work with an RCT designed to test the causal relationship between PA and cerebral structure. In this study, healthy, sedentary older adults (60–79 yrs) (n = 59) were randomly assigned to an aerobic exercise group or a toning and stretching control group. Both groups met for 1 hour, 3 days per week for 6 months. Results indicated that the aerobic exercise group experienced significant increases in gray and white matter volume in prefrontal and temporal regions that had been previously shown to undergo age-related deterioration. This finding extended previous work by providing evidence that the manipulation of PA resulted in changes in cerebral structure and, importantly, these changes were consistent with expectations based on known age-related changes in cerebral structure.

Erickson and colleagues (2011) further advanced our understanding of these relationships by also including measures of cognitive behavior so that a link between structural changes and behavioral changes could be explored. In their study, they looked specifically at the effects of PA on the hippocampus and memory performance. Older adults without dementia (n = 120) were randomly assigned to attend an aerobic exercise condition or a stretching control condition 3 days/week for one year. Those in the exercise condition had increases in hippocampal volume, while those in the control condition had decreases in hippocampal volume (which might be expected over a one-year period for older adults). Although there were not significant differences in memory improvement as a function of condition, there was a significant relationship between hippocampal volume and memory performance for those in the exercise condition. Specifically, older adults who experienced the largest increases in hippocampal volume in response to the year-long exercise program also demonstrated the biggest gains in memory performance. This is an important extension to previous work because of the initial evidence regarding a link between PA, hippocampal structure, and cognitive performance. That being said, one shortcoming of this study is that changes in hippocampal structure were not statistically tested as a mediator of effects of exercise on memory performance.

This shortcoming was addressed in a recent study by Maass et al. (2015). In their study, sedentary older adults (n = 40; M age = 68.4 years) were matched for age, gender, body mass index, self-reported PA, and a measure of verbal memory and were randomly assigned to an aerobic exercise condition or a control condition. Exercise consisted of 30 minutes of interval training 3 days/week for 12 weeks, while the control condition was a progressive muscle relaxation and stretching program for 45 minutes, 2 days/week for 12 weeks. Results showed that after controlling for age, there were significant changes in hippocampal perfusion for the exercise condition that were not observed in the control condition. Although there were no between-group differences in cognitive performance or hippocampal head volume in response to the intervention, there was evidence that changes in aerobic fitness were predictive of changes in cognitive performance. Hence, the authors took the important next step of using path analyses to explore the potential mediating role of hippocampal head volume and perfusion on the relationship between aerobic fitness and cognitive performance. Their results indicated that the most parsimonious explanation of the link between these four variables was that increases in aerobic fitness were predictive of increases in hippocampal perfusion which were predictive of improvements in recognition memory and increases in hippocampal head volume.

Summary

There is promising evidence that PA results in changes in cerebral structure. A meta-analytic review of this literature indicates that changes in white matter in response to exercise are modest in size (Sexton et al., 2016). In particular, evidence shows that higher levels of fitness or PA are associated with greater white matter volume (ES = 0.22) and reductions in white matter lesions (ES = –0.165). Importantly, however, there is limited experimental evidence in this area (Colcombe, Erickson, et al., 2006; Erickson et al., 2011; Maass et al., 2015; Voss et al., 2013), which restricts our ability to draw firm causal conclusions. Of note, however, is a recent experimental study by Maass et al. (2015) in which an experimental design was used and changes in hippocampal perfusion were demonstrated to mediate the effects of aerobic fitness on cognitive performance and hippocampal volume. The authors suggest that hippocampal perfusion might itself exert its influence on neuronal function through influences on growth factors. This then moves us to consideration of another possible mechanistic link between PA and cognitive performance.

Growth factors

Neurotrophic factors (e.g., brain-derived neurotrophic factor, BDNF, and insulin-like growth factor-I, IGF-I) and angiogenic growth factors (e.g., vascular endothelial growth factor, VEGF) have been identified as putative mechanisms for links between PA, brain health, and cognitive performance (see Cotman, Berchtold, & Christie, 2007; Duzel, van Praag, & Sendtner, 2016 for review). Neurotrophic and angiogenic growth factors are proteins that are present both centrally (in the brain) and peripherally (in the bloodstream). They have complex and intertwined effects on brain structure and have been found to be influenced directly or indirectly by exercise in rodent models (Lista & Sorrentino, 2010).

The growth factor that has received the most attention in the research on PA and cognition is BDNF. This growth factor is important for neuroplasticity, neuroprotection, and neural growth and differentiation. There is a fairly well-developed literature with animal models that has begun to explore the links between PA, growth factors, and cognition. Neeper et al. (1996) were the first to demonstrate a link between PA and BDNF with evidence that exercise led to increases in BDNF mRNA in the hippocampus and caudal cortex. Since that early study, others have also shown that exercise increases BDNF in regions of the brain that are important for cognitive performance (Cotman et al., 2007; Sleiman & Chao, 2015). Evidence with respect to IGF-I is less well developed; however, IGF-I has also been shown to be important for hippocampal neurogenesis and angiogenesis in response to exercise (Carro, Trejo, Busiguina, & Torres-Aleman, 2001). Intriguingly, IGF-I may in part exert its influence on angiogenesis through an increase in VEGF. There is evidence that IGF-I and VEGF are upregulated in response to exercise and that these increases lead to increases in vasculature (Ding et al., 2004). In sum, the impact of exercise on neurotrophic and growth factors in the brain has been demonstrated in rodent models, with evidence that these effects occur in areas of the brain important for cognitive performance. There is also some evidence that the changes in BDNF are critical for the exercise-induced improvements in hippocampal-dependent memory (Vaynman, Ying, & Gomez-Pinilla, 2004).

In human studies, the evidence with respect to the potential role of these proteins is less well developed and the results are less compelling. Although there is evidence that chronic PA increases resting BDNF (g = 0.28) (Szuhany, Bugatti, & Otto, 2015), this same level of evidence is not available for IGF-I and VEGF. With respect to VEGF, Vital et al. (2014) pointed out that almost all evidence comes from studies with older adults with arterial pathology and that increases in VEGF are only evident in two chronic PA studies with frequent days (3–5 days/week) of exercise training. In addition, at this time, there is a paucity of evidence on the potential role of these proteins in explaining the effects of PA on cognitive performance in humans.

In the study by Erickson et al. (2011) described earlier in the section on cerebral structure, researchers also measured changes in resting levels of serum BDNF in response to the one-year exercise program. Although there were no significant differences in the change in BDNF across time as a function of treatment conditions, a significant correlation was found between changes in BDNF and changes in hippocampal volume for the exercise group. Given that there was also a significant correlation between change in hippocampal volume and memory performance, the authors concluded that this study supports a link between PA, BDNF, cell proliferation or dendritic growth, hippocampal volume, and memory performance. However, the evidence from this study is not strong because associations cannot be used to judge causation and statistical techniques necessary to establish mediation were not employed.

In the study by Maass et al. (2015), also described in the section on cerebral structure, researchers explored the potential role of BDNF, IGF-I, and VEGF in explaining changes in hippocampal volume and perfusion observed in response to a 3-month PA program (Maass et al., 2016). In their study, changes in these proteins did not differ between the two treatment groups, and the observed fitness-related benefits to hippocampal perfusion and volume were not explained by changes in these proteins. As such, Maass et al. (2016) point out that pre-post changes in resting levels of BDNF, IGF-I, and VEGF may not be the critical factor, but rather encourage future researchers to consider looking at the time course of exercise-induced changes in neurotrophic and growth factors, perfusion and volume, and behavioral measures of performance.

In considering this literature, an important point to consider is that there is a distinction in the types of measurements of growth factors that can be made in animal models as compared to human models. In rodent models, growth factors are measured in the brain itself, whereas in human models, these proteins are measured peripherally. This dramatically limits the extent to which findings from the animal literature can be generalized to make predictions for humans. For example, although BDNF is produced centrally and peripherally (by skeletal muscle) and crosses the blood-brain barrier, and there is an association between peripheral and central levels of BDNF, it is not clear how the peripheral levels of BDNF assessed in serum or plasma relate to the central levels of BDNF and, ultimately, to changes in cerebral structure or cognitive performance. Hence, it is not surprising that in human studies where growth factors can only be measured peripherally, strong evidence regarding their role in cognitive performance is not available. Additionally, it is important to note another complicating factor with BDNF that may impact our current ability to understand the potential mechanistic role of BDNF in this relationship. BDNF exists in two isoforms (pro and mature) which serve complementary functions (see Piepmeier & Etnier, 2015). These isoforms have differential effects on cognitive performance and may be impacted differently by exercise. Hence, studies that rely on measures of total protein content may be introducing additional variability into their measure, which increases the difficulty of establishing causal significance.

Summary

Evidence in animal models shows that exercise increases levels of BDNF, IGF-I, and VEGF in the brain. There is additional evidence that these increases are responsible for increased angiogenesis and neurogenesis that result in improvements in behavioral measures of cognition. However, these relationships are not clearly evident in studies with humans. Although exercise has been shown to result in small increases in BDNF and VEGF in the periphery, evidence supporting a link between these increases and structural, functional, or behavioral measures relevant to cognition is inadequate. Current limitations in our ability to measure these proteins centrally in humans may make the establishment of clear causal links impractical at this time. That being said, the quest for mechanisms is critically important in the effort to understand how to prescribe exercise to specifically benefit cognitive performance.

PA and Cognitive Performance by Children

In contrast to the relatively substantive experimental evidence exploring the benefits of PA for cognitive performance by adults and older adults, there is little research with children. Furthermore, the evidence available for children is largely nonexperimental. With respect to experimental studies, only one has tested the effects of an in-school PA program on cognitive performance (Chang, Tsai, Chen, & Hung, 2013) and only a small number of experimental studies have been conducted to test the effects of after-school PA.

The extant literature with children has been meta-analytically reviewed on two occasions. Sibley and Etnier (2003) reported a small positive benefit from exercise participation (ES = 0.29). More recently, Fedewa and Ahn (2011) also reported a small average effect (ES = 0.35) for 39 experimental and quasi-experimental studies. In the largest systematic review of this literature to date, Donnelly et al. (2016) conclude that RCTs consistently support benefits to cognitive performance achieved by children in response to PA. However, these authors also note that there are only 11 publications on the effects of RCTs on cognitive performance by children and that these reflect data from only four unique studies. Hence, it is essential that future research be conducted to contribute to our understanding of potential causal effects of PA on cognition in children.

Mechanisms

With respect to our understanding of the impact of PA on putative mechanisms in children, evidence is even more limited. At this time, there are only two publications (Krafft et al., 2014; Schaeffer et al., 2014) from a small RCT in which changes in white matter microstructure have been examined using diffusion tensor imaging (DTI). Results suggest that PA does have a positive effect on this aspect of cerebral structure. This finding may be important because the areas in which the changes were observed have been linked to the neural network that supports executive functions.

Summary

Given the potential benefits of PA for cognitive performance by children and the promising initial evidence, it is critical that additional experimental studies be conducted. Additionally, given the paucity of evidence with respect to mechanisms, future research is desperately needed to advance our understanding of the mechanisms at work in achieving exercise-induced cognitive benefits by children.

Individual Characteristics

In considering the evidence presented in this article thus far, it is clear that while there are promising findings, there is also substantial variability in the observed results in response to PA. One potential reason for the inconsistent results that have been reported in RCTs relates to the possibility that individual difference variables influence the extent to which PA might benefit a person’s cognitive performance. One variable that has received considerable attention is apolipoprotein E (APOE). APOE is a susceptibility gene for Alzheimer’s disease. The risk of this disease increases with each increase in the number of epsilon 4 (ε‎4) alleles. The interesting question then is whether or not APOE ε‎4 carrier status moderates the potential benefits of PA on cognitive performance. The majority of the prospective studies indicate that APOE ε‎4 status does moderate the effects, such that PA reduces the risk of subsequent cognitive decline more for those at greatest genetic risk for Alzheimer’s disease (Kivipelto et al., 2001; Niti, Yap, Kua, Tan, & Ng, 2008; Rovio et al., 2005; Schuit, Feskens, Launer, & Kromhout, 2001). That being said, the largest prospective study (Podewils et al., 2005) that has addressed this issue reported just the opposite, with the only relationship between energy expenditure and risk of dementia being evident for APOE ε‎4 noncarriers (HR = 0.68).

Smith et al. (2014) recently reported on the moderating role of APOE carrier status on the relationship between PA and changes in hippocampal volume in older adults observed over an 18-month period. Older adults (65–89 years) were categorized as being APOE ε‎4 carriers or noncarriers and as being low or high active. Results indicated that low active APOE ε‎4 carriers experienced a 3 percent decline in hippocampal volume, while all other groups showed a maintenance of hippocampal volume over this time period. This suggests, then, that PA serves a protective function for the APOE carriers such that they do not experience the age-related decline in hippocampal volume that is typical in sedentary carriers.

Recently, Etnier et al. (in review) completed a case study in which older cognitively normal adults participated in an 8-month PA program and changes in cognitive performance over time were compared between APOE ε‎4 carriers and noncarriers. Results indicated that both groups improved in cognitive performance over time. When compared to data from a longitudinal study of older adults who were not part of an exercise trial, results suggested that these improvements were a response to the exercise intervention. Thus, this evidence further supports the hypothesis that PA is beneficial for cognitive performance even in persons at genetic risk for Alzheimer’s disease (i.e., APOE e4 carriers).

Summary

Evidence suggests that APOE moderates the relationship between PA and cognitive performance, with some evidence that PA is particularly beneficial for APOE ε‎4 carriers. Given that these individuals have a heightened risk of Alzheimer’s disease, this is an important avenue for future research. Additionally, given evidence that the relationship between PA and cognitive performance is moderated by this genotype, future study may uncover additional gene x behavior interactions that may help us to further understand the variability in findings from RCTs.

Placebo Effect

In considering the evidence relative to the potential benefits of chronic PA on cognitive performance, it is important to recognize that criticisms have been raised regarding the selection of appropriate comparison groups. In particular, by comparing an exercise condition to a no-treatment control condition, researchers have not appropriately controlled for nonexercise treatment effects (e.g., attention, social interactions) or for placebo effects. In fact, this is also a limitation of the cognitive-training literature with meta-analytic evidence showing that cognitive training has significant positive effects for memory when compared to a no-treatment control, but that these effects are not significant when compared to an active control condition (Kelly et al., 2014a). In contrast, the effects of exercise on psychological outcomes (cognition, depression, anxiety) have been shown to be stronger (ES = 0.37) than the observed effects for placebo control conditions (ES = 0.20) (Lindheimer, O’Connor, & Dishman, 2015). Thus, although placebo effects are evident for these outcomes, the effects that have been reported in response to exercise exceed the observed placebo effects. A limitation of the Lindheimer et al. review relative to the topic of interest herein is that cognitive outcomes were not examined separately. However, the important point to be made here is that researchers should carefully consider the design of their control conditions to ensure that placebo effects are not confounding their results.

Combined Interventions

Given that both cognitive training and PA have been shown to have small to moderate effects on cognitive performance, interest in exploring potential combined effects has been growing. This is supported by evidence from animal studies that are conceptually similar in that they have explored the effects of environmentally engaging (EE) conditions to those of more sterile control conditions. The EE conditions include both PA (typically through voluntary access to a running wheel) and cognitive engagement (typically through provision of stimulating home cage environments), while the control conditions do not include a wheel or any stimuli in the home cage. Results from animal studies consistently show benefits for the EE condition, and this has been demonstrated in terms of angiogenesis, synaptogenesis, and cognitive behavior (Black, Isaacs, Anderson, Alcantara, & Greenough, 1990; Leal-Galicia, Castaneda-Bueno, Quiroz-Baez, & Arias, 2008; Nippak, Mendelson, Muggenburg, & Milgram, 2007).

In human studies, a small number of RCTs have been conducted in which comparisons have typically been made between PA alone, cognitive training alone, and a combined program (Fabre, Chamari, Mucci, Masse-Biron, & Prefaut, 2002; Masley, Weaver, Peri, & Phillips, 2008; Rahe et al., 2015; Small et al., 2006). In general, these studies show promising results, with larger effects observed for the combined program in comparison to treatments in isolation. However, one criticism of these studies is that they have typically implemented the interventions as isolated units rather than as integrative wholes. In other words, in the EE studies with animals, animals are typically exposed to PA and cognitive engagement simultaneously, while in the human studies, the programs are administered asynchronously. It is possible that even larger benefits might be achieved if cognitively engaging PA programs were implemented. This notion is starting to be pursued in research with children in studies considering the qualitative aspects of PA (Pesce, 2012), but clearly more research is needed in this area.

Conclusion

Research exploring the potential benefits of PA for cognitive performance tends to support the thesis that there are small to moderate benefits for children, adults, older adults, and cognitively impaired older adults. This presents a tantalizing direction for research, as the identification of behavioral means by which to improve cognitive performance has important implications for public health and for education. Given the promising extant literature, it is critical that future research use experimental designs, sophisticated techniques, and mechanistic approaches to advance our understanding of how and for whom to prescribe PA to benefit cognitive performance. This research requires substantial funding; hence, it is paramount that funding agencies recognize the potential of these studies and the need to support this line of work (Etnier, 2015).

As a final point, paradoxically, individuals are spending money and time using computerized cognitive training programs in an attempt to enhance their cognitive performance when the evidence does not support the effectiveness of such programs in an unsupervised setting. By contrast, the evidence for PA is much stronger when PA is performed in a variety of settings, using a variety of modalities, and across a range of intensities. Hence, it is important to share this information regarding the potential benefits of PA with people interested in improving or protecting their cognitive performance.

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