Free Access
Mov Sport Sci/Sci Mot
Number 104, 2019
Masters athletes: Age is just a number / Les athlètes masters : l’âge n’est qu’un nombre
Page(s) 55 - 67
Published online 22 October 2019

© ACAPS, 2019

1 Introduction

The aging process is associated with structural and functional changes in the brain such as atrophy of both white and grey matter (Colcombe, et al., 2003) and impairment of vascular function (Lucas, et al., 2012; Murrell, et al., 2011a, b). These alterations in cerebrovascular functions and structural changes are associated with cognitive decline, increased risk of stroke and neurodegenerative diseases like Alzheimer’s (de la Torre, 2010a, b) and Parkinson’s disease (Wan, et al., 2019). One brain region that demonstrates a more rapid atrophy than other brain regions is the prefrontal cortex (PFC) (Yuki, et al., 2012), a region that has been associated with executive functions (planning, switching, coordinating; [Miyake, et al., 2000]). Cognitive aging is more associated to a decline in executive function than crystallized function in cognitive domain (Drag & Bieliauskas, 2010; Salthouse, 2010), in part due to these rapid changes in the PFC.

However, the cognitive decline during “normal” aging (non-pathological) seems to be slowed down by positive health factors, such as regular physical activity and cardiorespiratory fitness (CRF) (Bherer, 2015; Bherer, Erickson, & Liu-Ambrose, 2013). Physical activity can be defined as any body movement produced by skeletal muscles, which is responsible for an increase in energy expenditure (Saunders, Chaput, & Tremblay, 2014). In this line, highly active older adults have been found to display better cognitive performance than less active older adults. On the other side, CRF is defined as the ability of the circulatory and respiratory systems to supply oxygen to skeletal muscles during sustained physical activity and is classically measured by maximum oxygen uptake (VO2max). The benefit that CRF brings to cognitive performance seems to preferentially affect executive functions. Colcombe et al., in their two meta-analysis on this topic (Colcombe & Kramer, 2003; Kramer & Colcombe, 2018), reported that cardiorespiratory fitness has large positive benefits on executive function that are greater than the effect on other cognitive processes (i.e., visuospatial, speed, etc.). These results suggest that CRF can have a direct impact on cognitive health and the level of fitness seems to play a major role.

The clinical benefits of CRF on cognitive function appears in the form of enhanced brain functioning, as suggested by some neuroimaging studies, which report better brain activity in physically active older subjects when compared to less active (Voelcker-Rehage & Niemann, 2013). Many underlying neurophysiologic structural changes seem to explain this improved brain functioning (Hillman, Erickson, & Kramer, 2008; Ploughman, 2008). Structural brain changes after physical training, such as both the improvement of the density and integrity of grey and white matter (Sexton, et al., 2016; Voelcker-Rehage & Niemann, 2013), as well as a better brain vascularization, is due to the release and synthesis of several growth factors related to better cognitive functioning, neurogenesis, synaptogenesis and angiogenesis (Stillman & Erickson, 2018).

One particular group of older adults that is representative of individuals who maintain a high level of physical activity and have a high CRF are Master Athletes. Masters Athletes are a category of older adults who have participated in life-long exercise training and may benefit from the physiological and neurophysiological benefits of such training (Aengevaeren, Claassen, Levine, & Zhang, 2013; Tseng, et al., 2013a, b). Previous research has reported cardiovascular benefits accredited to life-long aerobic training compared to less active older adults. Indeed, Master Athletes demonstrate higher VO2max, often comparable to younger populations. Interestingly, high level of CRF has a positive impact on mortality (Antero-Jacquemin, et al., 2015; Marijon, et al., 2013). Considering all these health benefits, Master Athletes could be considered as exemplars of successful aging (Geard, Reaburn, Rebar, & Dionigi, 2017).

Based on the evidence that physical activity and CRF have an impact on cognition and brain functioning, we can hypothesize that Master Athletes would have better cognitive functioning than less active populations at the same age. However, the dose-response relationship between fitness level and cognitive function benefits in older adults is unclear. To date, the cardiorespiratory level that induces the greatest improvements in cognition and the impact of life-long aerobic training on brain structure and function remains unclear. The aim of this review was to examine the link between physical activity, CRF, and the neurophysiological mechanisms that could explain the better cognitive performance of Master Athletes.

2 Cognitive performance in Master Athletes

Few studies have assessed cognitive function in Master Athletes. These cross-sectional studies have compared cognitive performance of Masters Athletes with sedentary or less fit people. In the first study, Tseng et al. (2013a) recruited 12 Master Athletes (72.4 ± 5.6 years) and compared their cognitive performance with age-matched older adults and also with younger adults (27.2 ± 3.6 years). For the cognitive assessment, the authors conducted several cognitive tests. Global intelligence was assessed using the Wechsler Test of Adult Reading. Executive function was assessed using the Delis-Kaplan Executive Function System, Trail Making Tests (Trails-A and B), and Stroop Color-Word Test. The California Verbal Learning Test-II was also administered to measure declarative memory. Finally, working memory, processing speed, and reaction time were measured using the Automated Neuropsychological Assessment Metrics battery. The major findings of this study were that Master Athletes displayed better letter fluency and category fluency (executive and memory domain) and better scores on the Wechsler Test of Adult Reading than sedentary subjects. Interestingly, Master Athletes also performed better than younger adults on the letter fluency test. In line with these findings, Tarumi et al. (2013, 2015) have also assessed cognitive performance on middle-aged adults with endurance training who demonstrate a VO2max similar to Master Athletes. They reported better cognitive performance in those that were trained versus untrained participants. These participants displayed higher scores in measures of executive, attention and memory functions. Similarly, these results align with Taran, Taivassalo, & Sabiston (2013) who reported better performances on verbal learning and memory tasks (Rey Auditory Verbal Learning Test) as well as faster processing speed (Trail Making Test) in Master Athletes compared to sedentary controls. Also, Zhao et al. (2016) showed significantly better performance on a verbal memory task and a reaction time test (Immediate Post-concussion Assessment and Cognitive Testing (ImPACT)). More recently, Schott & Krull (2019) reported that Master Athletes displayed better cognitive performance in both working memory performance (n-back task) as well as inhibitory control (Flanker task) compared to sedentary controls. Although these studies are very interesting and support the proposal that lifelong physical training promotes improved cognitive functioning, these results do not permit to identify the dose-response relationship between cardiorespiratory fitness and brain function in the absence of experimental less active group.

This raises an important question: Are Masters Athletes better cognitively than their less fit counterparts? A recent study aimed to answer this question and compare within a sample Master Athletes, the influence of fitness level on cognitive performance. (Dupuy, Bosquet, Fraser, Labelle, & Bherer, 2018) recruited 39 Athletes (aged between 49 and 70 years) and split the sample into two groups (higher/lower fit) based on their CRF (i.e., VO2max). In this study, the participants completed neuropsychological tests including the Stroop Test, the Trail A and B Test, and the Digit Symbol Substitution Test. In addition, the participants completed a computerized cognitive dual-task (Bherer, et al., 2008). This task includes an auditory task (discrimination between two sounds: low: 440 Hz; high: 990 Hz), and a visual task (identification of three geometric forms: triangle, circle or square). In the single pure trials, participants had to respond to trials of each task alone. The participant completed 20 single task trials in the auditory task, by pressing one of two keys on a response box using the major (high sound) or index (low sound) finger of the left hand and 30 single task trials of the visual task by answering with the index (triangle), the major (circle) or the ring (square) finger of the right hand on the same response box. The dual-mixed condition consisted of single mixed and dual-mixed trials. Participants had to be prepared to answer to both trial types (visual and auditory) at all times but only had to perform the two tasks concurrently in the dual-mixed trials. Similar to Tseng et al. (2013a), the findings of Dupuy et al. (2018) confirm that higher fit Master Athletes are no better at Stroop, Trail or Digit Symbol tests than those that are lower fit. However, the higher fit Master Athletes did display fewer errors in the most difficult (executive condition) of the computerized dual-task. Also, bivariate correlations of the entire sample help elucidate the dose-response relationship since the findings demonstrate a negative correlation between CRF level and reaction times and errors produced in this task respectively. This correlation supports the proposal that a higher fitness level (even among Master Athletes) is associated with faster reaction times and lower error rates.

Although all these results are encouraging and corroborate the dose response relationship between CRF and brain functioning in older adults, the limited number of studies available makes it difficult to draw definitive conclusions.

3 Neurophysiological mechanisms

3.1 Structural changes

Several studies suggest that greater CRF and higher level of physical activity may be related to greater grey matter density and integrity in several brain regions. The following section discusses this point presenting cross sectional and longitudinal studies in healthy older adults.

3.1.1 Gray matter Cross-sectional studies (CRF and gray matter)

Based on the evidence that gray volume matter in several brain regions is related to cognitive performance (Ruscheweyh, et al., 2013; Taki, et al., 2011), several researchers have put forth the hypothesis that regular physical activity and/or better CRF could have a positive impact on brain structures. Using magnetic resonance imagery techniques, Colcombe et al. (2003) were among the first to establish the link between the CRF with gray matter volume. These authors reported in 55 older adults (age between 55 and 79 years old), that the subjects with higher CRF displayed a greater gray matter volume in the prefrontal, temporal and parietal cortices than the subjects with lower CRF. These associations were more recently confirmed by several authors (Erickson, et al., 2007; Gordon, et al., 2008; Weinstein, et al., 2012) using voxel based methods which confirmed that CRF, measured by VO2max, was associated to greater gray matter volume in frontal and temporal lobes in older adults. More recently, Williams et al. (2017) found a positive association between CRF and cortical thickness among older adults, more specifically, in left parahippocampal, paracentral, precuneus, and supramarginal cortices, as well as right middle temporal and lateral orbitofrontal areas.

Other studies have replicated the associations with CRF and others larger brain regions. One of other brain region of interest is the hippocampus since this region is implicated to memory function. To test the hypothesis in which the CRF could have a positive impact on volume of hippocampus, Erickson et al. (2009) assessed the CRF (VO2max) on 165 older adults and the size of their hippocampus. The authors reported that higher CRF was associated to larger size of hippocampus as well as to better memory performance. These results were more recently supported by Bugg, Shah, Villareal & Head (2012) and Szabo et al. (2011). Finally, Verstynen et al. (2012) examined the impact of CFR (VO2max) on the size of the basal ganglia. Similar to the prefrontal and hippocampus regions, basal ganglia was found to be related to CRF, which was also associated with better performances in a switching task. Cross-sectional studies (physical activity level and gray matter)

The results from cross-sectional studies of physical activity level on gray matter are less consistent than studies assessing the impact of CRF on gray matter. Using questionnaire on physical activity level Benedict et al. (2013) and Arenaza-Urquijo et al. (2017) found that higher physical activity score was strongly correlated with greater gray matter volume. Also, Erickson et al. (2010) found convincing evidence of a link between self reported physical activity and brain volume. Meanwhile, several other studies have reported that physical activity is not significantly correlated with either gray matter volume or gray matter network. Davis, Nagamatsu, Hsu, Beattie & Liu-Ambrose (2012) using the Physical Activities Scale for the Elderly (PASE) questionnaire, and Seider et al. (2016) the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire, reported no association between physical activity and gray matter volume. More recently, Masouleh et al. (2018) utilized the international physical activity questionnaire (IPAQ) and also found no association between physical activity and gray matter network. The difference in the questionnaire used and the subjective nature of the physical activity questionnaires may influence the inconsistency on the association of physical activity and gray matter between studies in older adults. The utilization of accelerometer as the objective measurement of physical activity should help to clarify the relationship between physical activity and gray matter. Longitudinal and randomized trials studies

As described previously in cross-sectional studies, the association between self-reported physical activity and gray matter in older adults has resulted in inconsistent results particularly in associations with gray matter volume. Such heterogeneity in the findings could indicate that cross-sectional assessments of physical activity are confounded by potential inaccuracies in self-reported assessments of physical activity. Longitudinal studies that follow individuals over an extended period, or randomized controlled trials that examine whether randomly assigning individuals to receive monitored and structured exercise for an extended period, provide greater control over several of these potential problems with cross-sectional investigations.

Longitudinal and randomized trials studies using magnetic resonance imaging (MRI) to assess structural changes due to physical activity level or CRF have reported increases in gray matter in frontal brain regions (Colcombe, et al., 2006) and in the hippocampus (Erickson, et al., 2011; Pajonk, et al., 2010) in humans. In a longitudinal study in healthy older adults, Lee et al. (2019) followed 767 community-dwelling participants (50 years or older) for 4 years. The results of this study suggest that older adults with higher physical activity scores demonstrated greater hippocampal volumes, total gray matter, parietal gray matter, and temporal gray matter compared to older adults with a lower physical activity scores. Similar results have also been reported from longitudinal studies that examined populations with health risks. Raji et al. (2016) analyzed the gray matter of 876 participants in a multisite population-based longitudinal study in persons aged 65 and older recruited for the Cardiovascular Health Study. Regardless of cognitive status, higher CRF was associated with larger gray matter volumes in frontal, temporal, and parietal lobes, as well as hippocampus, thalamus, and basal ganglia. Smith et al. (2014) analyzed the effect of physical activity and risk of Alzheimer’s disease (AD) by following 97 participants between 71–74 years old for 18 months. Participants were classified as high active or low active based on a self-report questionnaire of frequency and intensity of exercise and risk status for AD was defined by the presence or absence of the apolipoprotein E-epsilon 4 (APOE-ε4) allele. The results suggest that physical activity may help to preserve hippocampal volume in individuals at increased genetic risk for AD (those with the APOE-ε4 allele).

From the controlled intervention of physical activity study, Tamura et al. (2015) randomized 110 healthy older adults over 65 years old. A mild-intensity aerobic training for 2 years was employed as the intervention for the exercise group. Neuroimaging analysis revealed the significant preservation of bilateral prefrontal gray matter volume in the exercise group that was not seen in the control group. Tao et al. (2017) also reported the benefit of the intervention of physical activity as having a significant increase of gray matter volume in 12-week Tai-Chi Chuan and Baduanjin groups compared to a control group. Both of those interventional studies highlight the beneficial effect of physical activity program in healthy older adults. Furthermore, the benefits of physical exercise program were also reported in an overweight population. Prehn et al. (2019) randomized 29 overweight older subjects took either part in a moderate aerobic exercise program over 6 months or control condition of non-aerobic stretching and toning. The aerobic exercise group showed an increase of gray matter volume in the middle cingulate cortex, the middle/superior temporal gyrus, and the temporal pole compared to the non-aerobic group. Taken together, longitudinal studies in older adults suggest gray matter benefits of physical activity/CRF healthy older adults and at-risk populations.

However, more recently, Matura et al. (2017) reported that 12-week of aerobic exercise did not lead to increased or greater total grey matter volume compared to control group. As opposed from the previous study by Tao et al. (2017) which also proposed a 12-week interventional aerobic exercise program, negative finding for physical activity effect on gray matter volume could be due to the dose of the training. Even though both studies have the same duration but the participant in exercise group of Tao et al. (2017) received a greater amount of exercise training at a frequency of 5 days per week for 60 minutes per day compared to 3 days per week for 30 minutes per day in Matura et al. (2017).

Overall, longitudinal and interventional studies examining physical activity/CRF/exercise program and gray matter volume have shown that physical activity level and exercise program give beneficial effect to gray matter volume (see Matura, et al., 2017 for exception). All longitudinal studies have shown that physical activity positively associated with gray matter volume either healthy older adults or older adults with the risk of Alzheimer’s disease. This association is independent from cognitive status of the participants. From interventional studies, the conclusions indicate that at least 12 weeks of aerobic exercise program are required for giving advantageous effect compared to control.

The positive association of physical activity with cortical gray matter volume was found when comparing low to high spectrum of physical activity and this association still appeared when comparing on a very high level of physical activity in older adults. Master Athletes, which have a higher score in physical activity, have shown a greater cortical gray matter compared to healthy active older adults (Tseng, et al., 2013a; Wood, Nikolov, & Shoemaker, 2016), suggesting a possibility of dose-response association on the relationship between physical activity and gray matter in older adults. Tseng et al. (2013a) reported that compared to inactive elderly controls Master Athletes displayed greater posterior cortical thickness in the cuneus and precuneus. Similarly, these results align with Wood et al. (2016) who reported that Master Athletes demonstrated greater whole-brain cortical thickness and more specifically in the medial prefrontal cortex, pre and postcentral gyri, and insula compared to sedentary couterparts. These results suggest that cortical areas that are associated with higher cognitive functions (i.e.; executive functions) may be most sensitive to variation in CRF.

3.1.2 White matter

Several studies suggest that greater CRF may be related to greater white matter (WM) density and integrity in several brain regions. The following section discusses this point presenting cross sectional and longitudinal studies in healthy older adults. Cross-sectional study White matter volume

Studies examining the effect of physical activity (PA) on white matter volume have reported inconsistent results in older adults. Davis et al. (2012) used the Physical Activities Scale for the Elderly (PASE) questionnaire to 79 healthy females and found that physical activity levels were not associated with white matter volume. A similar result has also been reported by Seider et al. (2016) which reported no significant associations observed between the white matter volumes and engagement in physical activity recorded on the Community Healthy Activities Model Program for Seniors (CHAMPS) questionnaire. In contrast to these findings, Benedict et al. (2013) used self-reported light and hard physical activities for at least 30 minutes per week and found that physical activity (PA) was positively correlated with white matter volume. Unlike in the studies of Davis et al. (2012) and Seider et al. (2016) that included only healthy older adults in their studies, Benedict et al. (2013) also included participants with diabetes mellitus. The deteriorating effect of diabetes to brain structure might accentuate the benefit of physical activity on white matter volume in this sample of older adults. White matter hyperintensities / hypointensities

White matter hyperintensities in the brain can be detected on MRI. The underlying pathology of these hyperintensities mostly reflects demyelination and axonal loss as a consequence of chronic ischemia caused by cerebral small vessel disease (microangiopathy). Research has shown that the presence and extent of white matter hyperintensities in MRI scans are essential for clinical assessments of cognitive and functional impairment. Also white-matter hypointensities provide an index of cerebrovascular disease and cognitive decline, as people with greater hypointensities demonstrating the greatest decline (Debette & Markus, 2010).

Some studies included in this review that examined the association between cardiovascular fitness or physical activity level in older adults and white matter hyperintensities have given consistent results. Vesperman et al. (2018) reported that higher cardiovascular fitness attenuates the adverse effect of age on white matter hyperintensities (WMH). Also, Tseng et al. (2013b) reported an 83% reduction in deep WMH volume in Master Athletes relative to their sedentary counterparts. In a study by Fleischman et al. (2015) using of actigraphy to calculate physical activity, higher levels of physical activity may reduce the effect of WMH on motor function in healthy older adults. Only one study about physical activity and white matter hypointensity was reported since 2012. Wood et al. (2016) reported no differences in white matter hypointensities between Master Athlete and healthy older adult. Nevertheless, other studies comparing cardiovascular fitness and physical activity with white matter structure supported the association between physical activity and white matter hyperintensities in older adults. White matter integrity

Diffusion tensor imaging is a relatively new MRI technique that identifies changes in the white matter microstructure by quantifying directional diffusion. Diffusion tensor imaging has become one of the imaging tools available to understand the pathophysiological mechanisms of cerebrovascular diseases on brain structure. Diffusion tensor imaging is based on the theory that water molecules follow a physiological perpendicular path through the long axis of neural fibers and bundles, formed by the integrity of the axons and the thick myelin membrane surrounding them. Any alteration in the integrity of the white matter fibers will result in changes in the water diffusion and consequently in the diffusion tensor imaging parameters. Fractional anisotropy is the main diffusion tensor imaging parameters used to identify alterations in white matter integrity. These imaging parameters provide information about the density of the white matter fiber, the diameter of the axon and degree of myelination based on a quantitative measure of the diffusion anisotropy.

Some studies in older adults that examined the association between CRF and physical activity with white matter integrity, gave consistent results. Oberlin et al. (2016) reported that higher VO2max was associated with higher fractional anisotropy that suggests better white matter microstructural organization in higher fit older adults. Johnson, Kim, Clasey, Bailey & Gold (2012) reported a positive correlation between VO2peak and fractional anisotropy. These studies showed that either higher CRF is associated with greater white matter integrity in healthy older adults.

Only three studies that have explored the effect of physical activity on white matter integrity have been published since 2012. The first study was Tseng et al. (2013b) which reported that Master Athletes showed higher fractional anisotropy values when compared to sedentary older adults. Also, Gow et al. (2012) reported that a higher level of physical activity was associated with higher fractional anisotrophy. Lastly, Burzynska et al. (2014), using accelerometer to quantify physical activity for 7 days, reported a positive association between physical activity and white matter integrity and also found that sedentary behaviour was associated with lower white matter integrity in healthy low-fit older adults. All of these studies displayed a great range of physical activity level in their participants, suggesting the advantage of physical activity on white matter integrity can be gained by participants with various physical activity levels from low levels to Master Athletes level and this is not limited to a certain level of physical activity.

Overall, cross-sectional studies of the relationship between physical activities on white matter integrity have consistent results. Cardiovascular fitness or physical activity showed a promising effect on brain structure health, primarily to prevent or reduce white matter hyperintensities and maintain white matter integrity. The only inconsistent result is the relationship between physical activity and white matter volume. Again, as discussed earlier, the subjective nature of self-reported physical activity questionnaires may influence the results. In addition, the characteristics of participants should be evaluated as this also may influence the relationship between physical activity and white matter volume. Longitudinal study

Smith et al. (2014) did a longitudinal study in 97 older adults to analyze the effect of physical activity and risk of Alzheimer’s disease on white matter volume. Participants were classified as high active or low active based on a self-report questionnaire of frequency and intensity of exercise and risk status was defined by the presence or absence of the apolipoprotein E-epsilon 4 (APOE-ε4) allele. The results suggest that no significant main effects or interactions were observed between genetic risk and PA on cortical white matter volume. Furthermore, another study from Smith et al. (2016) with similar classification of participants’ group, reported greater levels of physical activity were associated with greater fractional anisotropy in healthy older adults who did not possess the APOE-ε4 allele. These results support that existing cross-sectional study results in healthy older adults demonstrate the beneficial effect of physical activity on white matter integrity but not white matter volume.

In interventional studies, Voss et al. (2013) randomized 70 sedentary healthy older adults into aerobic walking group or a flexibility, toning and balance control group. Both the walking and control programs were one year in duration and consisted of three structured forty-minute exercise sessions per week led by a trained exercise leader. The results showed that greater aerobic fitness after the walking program was associated with greater change in white matter integrity compared to the flexibility, toning and balance control group. In another study, 174 healthy but low-active older participants were randomized into 4 groups (dance, walking, walking + nutrition, and control) and were followed for 6 months. Diffusion tensor imaging showed white matter integrity declined over 6 months in all groups but increased in the dance group. These studies suggested that aging of the brain is detectable on the scale of 6-months and more physically active lifestyle is associated with better white matter integrity in healthy sedentary older adults.

Taken together, cross-sectional as well as longitudinal studies have provided results in favour of beneficial effects of physical activity or CRF on cognitive on grey and white matter density and thickness. To date, very few studies corroborate brain plasticity in Master Athletes. Tseng et al. (2013a, b) and Wood et al. (2016) reported that Master Athletes demonstrated greater density in grey matter and white matter integrity in several brain regions and could explain their improved cognitive performance.

3.2 Cerebrovascular changes

Aerobic exercise might induce beneficial effects on brain functions by changes in blood flow and vascularization, which could lead to an overall better energy and oxygen supply to the brain. The following section discusses this point presenting cross sectional and longitudinal studies in healthy older adults.

3.2.1 Cerebral blood flow and cerebral oxygenation

Sedentary lifestyle has recently been associated with reduced cerebral blood flow (CBF), which increases the risk of a more rapid decline in aging or a higher risk of stroke or neurodegenerative disorders (Carter et al., 2018). However, the increase of walking time every day could counteract this sedentary effect (Carter, et al., 2018). Furthermore, several cross sectional studies, which compared higher active people to less active or sedentary people, confirm the positive impact of CRF on cerebral blood supply. Higher fit people have higher CBF during rest or during tilt test or during exercise than lower fit people (Murrell, et al., 2011a, b). This improved cerebral perfusion was measured using transcranial Echo-Doppler or functional MRI techniques, either at the carotid arteries, at the median cerebral arteries, or at the level of the hippocampus. Using functional near-infrared spectroscopy techniques, several studies have also reported that cardiorespiratory fitness has positive effect on cerebral oxygenation, and higher fit people displayed greater cerebral oxygenation responses during exercise (Rooks, Thom, McCully, & Dishman, 2010) or during cognitive task (Agbangla, Audiffren, Pylouster, & Albinet, 2019; Albinet, Mandrick, Bernard, Perrey, & Blain, 2014; Dupuy, et al., 2015).

In a randomized controlled trial, (Chapman et al., 2013) demonstrated that a 12-week aerobic exercise intervention significantly increased regional cerebral blood flow in the anterior cingulate cortex of sedentary older adults (Chapman, et al., 2013). Murrell et al. (2013) also observed a similar increase of middle cerebral artery blood velocity after 12 weeks of aerobic training in young and older adults. Likewise, a cross-sectional study by Thomas showed that Master Athletes had significantly greater regional CBF in the posterior cingulate cortex than age-matched sedentary controls (Thomas, et al., 2013).

The increase in cerebral perfusion improving the oxygen and nutrient supply would partly explain the improvement in cognitive status after exercise training. Davenport, Hogan, Eskes, Longman & Poulin (2012) hypothesized that the larger the cerebrovascular reserve, the better the participants’ cognitive performance were. This hypothesis was confirmed by several studies in healthy and non-healthy subjects (Gayda, et al., 2017). These authors reported that better cognitive performance was associated with the amplitude of cerebral oxygenation during exercise.

Beyond the increase in CBF, this cerebrovascular reserve is also under the influence of vascular mechanisms such as the regulation, the vasoreactivity and the arterial stiffness.

3.2.2 Arterial stiffness

Several studies support the hypothesis that cognitive performance in aging is linked to vascular health (Barnes & Corkery, 2018). Indeed, one of the main mechanisms that explain cognitive decline during the aging process is the increase in blood pressure. Hypertension is one of major vascular risk factors for cognitive decline. Several studies have reported that hypertensive subjects have poorer cognitive performance than their counterpart with normal blood pressure (Hajjar, et al., 2011; Iadecola, et al., 2016; Novak & Hajjar, 2010). Even in the absence of hypertension, higher blood pressure is associated to cognitive impairment (Tsivgoulis, et al., 2009). The relationship between blood pressure and cognition seems to be mediated by the state of the vasculature. Indeed, higher blood pressure may reduce CBF (Deverdun, et al., 2016), increase cerebral bleeds and white matter hyperintintesities (Tsivgoulis, et al., 2009). Also, the high blood pressure may cause the rigidity of arteries. Several cross sectional studies have reported that higher carotid stiffness (Tarumi, et al., 2013) and higher aortic pulse wave velocity are associated to poorer cognitive performance (Gauthier, et al., 2015) possibly mediated by a lower cerebral oxygenation. Nevertheless, CRF appears to improve arterial stiffness thus preserving cognitive decline in the elderly. All these studies support the hypothesis that preservation or the improvement of vessel elasticity may be one of the key mechanisms by which CRF attenuates cognitive aging. Regarding Masters Athletes, it has been reported that this population has a very good vascular health, which could explain their better cognitive performance (Tarumi, et al., 2013).

3.2.3 Cerebro-reactivity/regulation

Cerebral blood flow decreases approximately 5% per decade (Grolimund & Seiler, 1988). This results in a decrease of 25 to 30% between the ages of 20 and 80 years (Ainslie, et al., 2008; Krejza, et al., 1999). The reduction of CBF and the impairment of his regulation are risk factors for cerebrovascular disease. Reduced CBF can lead to a cerebrovascular accident such as stroke (Markus, 2004) and may be a risk factor for dementia and neurodegenerative disorder such as Alzheimer’s disease (de la Torre, 2010a, b). Since, the CBF is largely controlled by the partial pressure of arterial carbon dioxide (PaCO2), impaired ability of the cerebrovascular system to respond to changes in PaCO2 (called cerebrovascular responsiveness) is a risk factor for cerebrovascular disease (Markus & Cullinane, 2001).

Several cross sectional studies have been shown that higher fit subject displayed better vascular reactivity and regulation (Barnes, Taylor, Kluck, Johnson, & Joyner, 2013) than lower fit counterpart. Longitudinal studies have also found the similar pattern. Murrell et al. (2013) and Tyndall et al. (2013) found an increase of vasoreactivity and regulation after 3 months and 6 months of training. Also, Ivey et al. (2011) demonstrated an elevation in cerebrovascular reactivity to CO2 following 6 months of exercise training in stroke survivors.

3.3 Neurotrophin release

Using magnetic resonance spectroscopy, Erickson et al. (2012a, b) measured N-acetylaspartate (NAA) levels in the frontal cortex of older adults. N-acetylaspartate is only found in neuronal tissue and has been recognized as a marker of neuronal health (Moffett, Ross, Arun, Madhavarao, & Namboodiri, 2007). Erickson et al. (2012a, b) reported a positive correlation between NAA levels, cardiovascular fitness and working memory. Gonzales et al. (2013) supported these findings and found higher NAA levels in middle-aged endurance athletes compare to sedentary controls. These results highlight the potential contribution of growth factors that allow for the maintenance and renewal of neuronal health. Growing evidence suggests that acute and chronic exercise influence the brain through circulating growth factors like neurotrophins, modulated several mechanisms for cognition. Among these factors, brain-derived neurotrophic factor (BDNF), insulin-like growth factor-1 (IGF-1) and vascular endothelial growth factor (VEGF) have been designated as the main factors that produce cerebral plasticity.

3.3.1 BDNF

Evidence on the effect of BDNF on neurogenesis and synaptic plasticity comes from animal studies (Marie, et al., 2018). In humans, it’s well documented that acute bouts of exercise increase the plasmatic concentration of BDNF (Ferris, Williams, & Shen, 2007; Hakansson, et al., 2017; Schmolesky, Webb, & Hansen, 2013). Moreover, Winter et al. (2007) reported an increase in BDNF in humans running at a high intensity and that this BDNF release accelerated learning. Furthermore, several studies have reported changes in the BDNF level after chronic exercise (Leckie, et al., 2014; Seifert, et al., 2010). More recently, Szuhany, Bugatti & Otto (2015) performed a meta-analysis and supported elevations in plasmatic BDNF levels in humans after chronic exercise. This elevation seems to be responsible for cognitive performance improvement and increased hippocampal volume (Erickson et al., 2012a, b). In addition, Engeroff et al. (2018) found that BDNF was negatively associated with sedentary time but beneficially related to total activity counts (via accelerometer) and moderate to vigorous physical activity.

Beyond its crucial role in neuroplasticity, BDNF up-regulates the production of insulin-like growth factor 1 (IGF-1) and works in conjunction with it, to promote both neurogenesis and angiogenesis (Ding, Vaynman, Akhavan, Ying, & Gomez-Pinilla, 2006). Also, although lactate has been incorrectly considered as a factor of fatigue, it appears, based on the recent work, to be an important metabolic derivate for the brain. It can be considered as a source of energy for the brain and also as a growth factor for BDNF and VEGF (E, Lu, Selfridge, Burns, & Swerdlow, 2013; El Hayek, et al., 2019; Schiffer, et al., 2011).

3.3.2 IGF-1

IGF-1 is also considered a growth factor for the brain and involved in neurogenesis and synaptogenesis (Aleman & Torres-Aleman, 2009). In studies with older adults, high plasmatic IGF-1 concentrations are associated with improved cognitive performance while for older adults with cognitive impairment, low IGF-1 concentrations were associated with poorer cognitive performance (Stein, et al., 2018). In response to acute exercise, plasmatic IGF-1 concentrations are increased (Schwarz, Brasel, Hintz, Mohan, & Cooper, 1996). This finding was supported by a recent systematic review, which reported a positive relationship between physical exercise and increased IGF plasmatic concentrations (Arwert, Deijen, & Drent, 2005). This increase seems to be related to higher cognitive status in healthy older adults and play an essential role for neurogenesis. Chronic exercise, particularly resistance training, has been found to increase the plasmatic IGF-1 concentrations (Cassilhas, et al., 2007; Koziris, et al., 1999). Recently, Maas et al. (2016) reported that changes in IGF-I levels were positively correlated with hippocampal volume changes and delayed verbal recall performance.

3.3.3 VEGF

More physically active older adults have been found to display a higher number of small cerebral vessels than less physically active older adults (Bullitt, et al., 2009). It’s well known that VEGF regulates endothelial cell proliferation and angiogenesis (Cotman & Berchtold, 2002). Exercise increases the production of plasmatic VEGF which is the main growth factor associated with capillary formation in the brain (Cotman & Berchtold, 2002; Duman, 2005). Along this line, Pereira et al. (2007) observed an in vivo neurogenesis and angiogenesis in the adult dentate gyrus that was induced by exercise and an increase of cerebral blood volume in this specific area. Furthermore, acute aerobic exercise elevates plasmatic and hippocampal VEGF (Tang, Xia, Wagner, & Breen, 2010), and promotes endothelial nitric oxide synthase (eNOS) (Gertz, et al., 2006). The production of eNOS supports the maintenance of the vascular endothelium (Forstermann & Munzel, 2006) and contributes to angiogenesis (Gertz, et al., 2006). Cerebral angiogenesis increases cerebral circulation (Pereira, et al., 2007) and cerebral oxygenation (Dupuy, et al., 2015). This is associated with transiently increased permeability of the blood brain barrier (Bailey, et al., 2011) which may facilitate the proliferation of these growth factors. All of these mechanisms are likely responsible for more efficient bloodstream delivery of neurotrophins influencing brain plasticity during or following exercise. Currently, no data are available to confirm these neurotrophic hypotheses in the Master Athletes. Future studies will be necessary to support these hypotheses.

All these neurophysiological mechanisms are represented in the Figure 1.

thumbnail Fig. 1

Summary of the possible neurophysiological mechanisms underlines cognitive improvement after long life intense training.

4 Conclusion

This review highlighted the possible neurophysiological mechanisms that could explain the better cognitive performance observed in Masters Athletes. Several studies have indeed observed that this population has better cognitive performance than sedentary subjects or even active subjects of low CRF level. It has also been shown that the Master Athletes possessed brain volumes of gray and white matter larger than sedentary subjects. Also, cerebro-vascular health seems to be improved in these athletes. Although all these results are encouraging and corroborate the dose response relationship between CRF and brain functioning in older adults, the limited number of studies available makes it difficult to draw definitive conclusions. Future studies seem necessary to confirm that Masters Athletes have higher cognitive and brain abilities than their lower-level counterparts.


  • Aengevaeren, V.L., Claassen, J.A., Levine, B.D., & Zhang, R. (2013). Cardiac baroreflex function and dynamic cerebral autoregulation in elderly Masters athletes. Journal of Applied Physiology , 114, 195–202. [CrossRef] [PubMed] [Google Scholar]
  • Agbangla, N.F., Audiffren, M., Pylouster, J., & Albinet, C.T. (2019). Working memory, cognitive load and cardiorespiratory fitness: Testing the CRUNCH model with near-infrared spectroscopy. Brain Sciences , 9(2): E38. [CrossRef] [PubMed] [Google Scholar]
  • Ainslie, P.N., Cotter, J.D., George, K.P., Lucas, S., Murrell, C., Shave, R., Thomas, K.N., Williams, M.J., & Atkinson, G. (2008). Elevation in cerebral blood flow velocity with aerobic fitness throughout healthy human ageing. The Journal of Physiology , 586, 4005–4010. [CrossRef] [PubMed] [Google Scholar]
  • Albinet, C.T., Mandrick, K., Bernard, P.L., Perrey, S., & Blain, H. (2014). Improved cerebral oxygenation response and executive performance as a function of cardiorespiratory fitness in older women: A fNIRS study. Frontiers in Aging Neuroscience , 6, 272. [CrossRef] [PubMed] [Google Scholar]
  • Aleman, A., & Torres-Aleman, I. (2009). Circulating insulin-like growth factor I and cognitive function: Neuromodulation throughout the lifespan. Progress in Neurobiology , 89, 256–265. [CrossRef] [PubMed] [Google Scholar]
  • Antero-Jacquemin, J., Rey, G., Marc, A., Dor, F., Haida, A., Marck, A., Berthelot, G., Calmat, A., Latouche, A., & Toussaint, J.F. (2015). Mortality in female and male French Olympians: A 1948–2013 cohort study. The American Journal of Sports Medicine , 43, 1505–1512. [CrossRef] [PubMed] [Google Scholar]
  • Arenaza-Urquijo, E.M., de Flores, R., Gonneaud, J., Wirth, M., Ourry, V., Callewaert, W., Landeau, B., Egret, S., Mézenge, F., Desgranges, B., & Chételat, G. (2017). Distinct effects of late adulthood cognitive and physical activities on gray matter volume. Brain Imaging and Behavior , 11(2), 346–356. [CrossRef] [PubMed] [Google Scholar]
  • Arwert, L.I., Deijen, J.B., & Drent, M.L. (2005). The relation between insulin-like growth factor I levels and cognition in healthy elderly: A meta-analysis. Growth Hormone and IGF Research , 15, 416–422. [CrossRef] [Google Scholar]
  • Bailey, D.M., Evans, K.A., McEneny, J., Young, I.S., Hullin, D.A., James, P.E., Ogoh, S., Ainslie, P.N., Lucchesi, C., Rockenbauer, A., Culcasi, M., & Pietri, S. (2011). Exercise-induced oxidative-nitrosative stress is associated with impaired dynamic cerebral autoregulation and blood-brain barrier leakage. Experimental Physiology , 96, 1196–1207. [CrossRef] [PubMed] [Google Scholar]
  • Barnes, J.N., & Corkery, A.T. (2018). Exercise improves vascular function, but does this translate to the brain? Brain Plasticity , 4, 65–79. [CrossRef] [Google Scholar]
  • Barnes, J.N., Taylor, J.L., Kluck, B.N., Johnson, C.P., & Joyner, M.J. (2013). Cerebrovascular reactivity is associated with maximal aerobic capacity in healthy older adults. Journal of Applied Physiology , 114, 1383–1387. [CrossRef] [PubMed] [Google Scholar]
  • Benedict, C., Brooks, S.J., Kullberg, J., Nordenskjöld, R., Burgos, J., Le Grevès, M., Kilander, L., Larsson, E.M., Johansson, L., Ahlström, H., Lind, L., & Schiöth, H.B. (2013). Association between physical activity and brain health in older adults. Neurobiology of Aging , 34(1):83–90. [CrossRef] [PubMed] [Google Scholar]
  • Bherer, L. (2015). Cognitive plasticity in older adults: Effects of cognitive training and physical exercise. Annals of the New York Academy of Sciences , 1337, 1–6. [CrossRef] [PubMed] [Google Scholar]
  • Bherer, L., Kramer, A.F., Peterson, M.S., Colcombe, S., Erickson, K., & Becic, E. (2008). Transfer effects in task-set cost and dual-task cost after dual-task training in older and younger adults: Further evidence for cognitive plasticity in attentional control in late adulthood. Experimental Aging Research , 34, 188–219. [CrossRef] [PubMed] [Google Scholar]
  • Bherer, L., Erickson, K.I., & Liu-Ambrose, T. (2013). A Review of the effects of physical activity and exercise on cognitive and brain functions in older adults. Journal of Aging Research , 2013, 657508. [PubMed] [Google Scholar]
  • Bugg, J.M., Shah, K., Villareal, D.T., & Head, D. (2012). Cognitive and neural correlates of aerobic fitness in obese older adults. Experimental Aging Research , 38, 131–145. [CrossRef] [PubMed] [Google Scholar]
  • Bullitt, E., Rahman, F.N., Smith, J.K., Kim, E., Zeng, D., Katz, L.M., & Marks, B.L. (2009). The effect of exercise on the cerebral vasculature of healthy aged subjects as visualized by MR angiography. AJNR. American Journal of Neuroradiology , 30, 1857–1863. [CrossRef] [PubMed] [Google Scholar]
  • Burzynska, A.Z., Chaddock-Heyman, L., Voss, M.W., Wong, C.N., Gothe, N.P., Olson, E.A., Knecht, A., Lewis, A., Monti, J.M., Cooke, G.E., Wojcicki, T.R., Fanning, J., Chung, H.D., Awick, E., McAuley, E., & Kramer, A.F. (2014). Physical activity and cardiorespiratory fitness are beneficial for white matter in low-fit older adults. PLoS One , 9(9), e107413. [CrossRef] [PubMed] [Google Scholar]
  • Carter, S.E., Draijer, R., Holder, S.M., Brown, L., Thijssen, D.H.J., & Hopkins, N.D. (2018). Regular walking breaks prevent the decline in cerebral blood flow associated with prolonged sitting. Journal of Applied Physiology , 125, 790–798. [CrossRef] [PubMed] [Google Scholar]
  • Cassilhas, R.C., Viana, V.A., Grassmann, V., Santos, R.T., Santos, R.F., Tufik, S., & Mello, M.T. (2007). The impact of resistance exercise on the cognitive function of the elderly. Medicine and Science in Sports and Exercise , 39, 1401–1407. [CrossRef] [PubMed] [Google Scholar]
  • Chapman, S.B., Aslan, S., Spence, J.S., Defina, L.F., Keebler, M.W., Didehbani, N., & Lu, H. (2013). Shorter term aerobic exercise improves brain, cognition, and cardiovascular fitness in aging. Frontiers in Aging Neuroscience , 5, 75. [CrossRef] [PubMed] [Google Scholar]
  • Colcombe, S., & Kramer, A.F. (2003). Fitness effects on the cognitive function of older adults: A meta-analytic study. Psychological Science , 14, 125–130. [CrossRef] [PubMed] [Google Scholar]
  • Colcombe, S.J., Erickson, K.I., Raz, N., Webb, A.G., Cohen, N.J., McAuley, E., & Kramer, A.F. (2003). Aerobic fitness reduces brain tissue loss in aging humans. The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences , 58, 176–180. [CrossRef] [PubMed] [Google Scholar]
  • Colcombe, S.J., Erickson, K.I., Scalf, P.E., Kim, J.S., Prakash, R., McAuley, E., Elavsky, S., Marquez, D.X., Hu, L., & Kramer, A.F. (2006). Aerobic exercise training increases brain volume in aging humans. The Journals of Gerontology. Series A, Biological Sciences and Medical Science , 61, 1166–1170. [CrossRef] [PubMed] [Google Scholar]
  • Cotman, C.W., & Berchtold, N.C. (2002). Exercise: A behavioral intervention to enhance brain health and plasticity. Trends in Neurosciences , 25, 295–301. [CrossRef] [PubMed] [Google Scholar]
  • Davenport, M.H., Hogan, D.B., Eskes, G.A., Longman, R.S., & Poulin, M.J. (2012). Cerebrovascular reserve: The link between fitness and cognitive function? Exercise and Sport Sciences Reviews , 40, 153–158. [PubMed] [Google Scholar]
  • Davis, J.C., Nagamatsu, L.S., Hsu, C.L., Beattie, B.L., & Liu-Ambrose, T. (2012). Self-efficacy is independently associated with brain volume in older women. Age Ageing , 41(4), 495–501. [CrossRef] [PubMed] [Google Scholar]
  • Debette, S., & Markus, H.S. (2010). The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: Systematic review and meta-analysis. British Medical Journal , 341, c3666. [CrossRef] [PubMed] [Google Scholar]
  • de la Torre, J.C. (2010a). The vascular hypothesis of Alzheimer’s disease: Bench to bedside and beyond. Neurodegenerative Diseases , 7, 116–121. [CrossRef] [Google Scholar]
  • de la Torre, J.C. (2010b). Vascular risk factor detection and control may prevent Alzheimer’s disease. Aging Research Reviews , 9, 218–225. [CrossRef] [Google Scholar]
  • Deverdun, J., Akbaraly, T.N., Charroud, C., Abdennour, M., Brickman, A.M., Chemouny, S., Steffener, J., Portet, F., Bonafe, A., Stern, Y., Ritchie, K., Molino, F., Le Bars, E., & Menjot de Champfleur, N. (2016). Mean arterial pressure change associated with cerebral blood flow in healthy older adults. Neurobiology of Aging , 46, 49–57. [CrossRef] [PubMed] [Google Scholar]
  • Ding, Q., Vaynman, S., Akhavan, M., Ying, Z., & Gomez-Pinilla, F. (2006). Insulin-like growth factor I interfaces with brain-derived neurotrophic factor-mediated synaptic plasticity to modulate aspects of exercise-induced cognitive function. Neuroscience , 140, 823–833. [PubMed] [Google Scholar]
  • Drag, L.L., & Bieliauskas, L.A. (2010). Contemporary Review 2009: Cognitive Aging. Journal of Geriatric Psychiatry and Neurology , 23, 75–93. [CrossRef] [PubMed] [Google Scholar]
  • Duman, R.S. (2005). Neurotrophic factors and regulation of mood: Role of exercise, diet and metabolism. Neurobiology of Aging , 26(Suppl 1), 88–93. [CrossRef] [PubMed] [Google Scholar]
  • Dupuy, O., Gauthier, C.J., Fraser, S.A., Desjardins-Crepeau, L., Desjardins, M., Mekary, S., Lesage, F., Hoge, R.D., Pouliot, P., & Bherer, L. (2015). Higher levels of cardiovascular fitness are associated with better executive function and prefrontal oxygenation in younger and older women. Frontiers in Human Neuroscience , 9, 66. [CrossRef] [PubMed] [Google Scholar]
  • Dupuy, O., Bosquet, L., Fraser, S.A., Labelle, V., & Bherer, L. (2018). Higher cardiovascular fitness level is associated to better cognitive dual-task performance in Master Athletes: Mediation by cardiac autonomic control. Brain and Cognition , 125, 127–134. [CrossRef] [PubMed] [Google Scholar]
  • E, L., Lu, J., Selfridge, J.E., Burns, J.M., & Swerdlow, R.H. (2013). Lactate administration reproduces specific brain and liver exercise-related changes. Journal of Neurochemistry , 127, 91–100. [PubMed] [Google Scholar]
  • El Hayek, L., Khalifeh, M., Zibara, V., Abi Assaad, R., Emmanuel, N., Karnib, N., El-Ghandour, R., Nasrallah, P., Bilen, M., Ibrahim, P., Younes, J., Abou Haidar, E., Barmo, N., Jabre, V., Stephan, J.S., & Sleiman, S.F. (2019). Lactate mediates the effects of exercise on learning and memory through SIRT1-dependent activation of hippocampal Brain-Derived Neurotrophic Factor (BDNF). The Journal of Neuroscience , 39, 2369–2382. [Google Scholar]
  • Engeroff, T., Vogt, L., Fleckenstein, J., Fuzeki, E., Matura, S., Pilatus, U., Schwarz, S., Deichmann, R., Hellweg, R., Pantel, J., & Banzer, W. (2018). Lifespan leisure physical activity profile, brain plasticity and cognitive function in old age. Aging and Mental Health , 23(57), 811–818. [CrossRef] [Google Scholar]
  • Erickson, K.I., Colcombe, S.J., Elavsky, S., McAuley, E., Korol, D.L., Scalf, P.E., & Kramer, A.F. (2007). Interactive effects of fitness and hormone treatment on brain health in postmenopausal women. Neurobiology of Aging , 28, 179–185. [CrossRef] [PubMed] [Google Scholar]
  • Erickson, K.I., Prakash, R.S., Voss, M.W., Chaddock, L., Hu, L., Morris, K.S., White, S.M., Wojcicki, T.R., McAuley, E., & Kramer, A.F. (2009). Aerobic fitness is associated with hippocampal volume in elderly humans. Hippocampus , 19, 1030–1039. [CrossRef] [PubMed] [Google Scholar]
  • Erickson KI, Raji CA, Lopez OL, Becker JT, Rosano C, Newman AB, Gach HM, Thompson PM, Ho AJ, & Kuller LH. (2010). Physical activity predicts gray matter volume in late adulthood: The Cardiovascular Health Study. Neurology , 75(16), 1415–1422. [Google Scholar]
  • Erickson, K.I., Voss, M.W., Prakash, R.S., Basak, C., Szabo, A., Chaddock, L., Kim, J.S., Heo, S., Alves, H., White, S.M., Wojcicki, T.R., Mailey, E., Vieira, V.J., Martin, S.A., Pence, B.D., Woods, J.A., McAuley, E., & Kramer, A.F. (2011). Exercise training increases size of hippocampus and improves memory. Proceedings of the National Academy of Sciences of the United States of America , 108, 3017–3022. [CrossRef] [PubMed] [Google Scholar]
  • Erickson, K.I., Miller, D.L., & Roecklein, K.A. (2012a). The aging hippocampus: Interactions between exercise, depression, and BDNF. Neuroscientist , 18, 82–97. [CrossRef] [PubMed] [Google Scholar]
  • Erickson, K.I., Weinstein, A.M., Sutton, B.P., Prakash, R.S., Voss, M.W., Chaddock, L., Szabo, A.N., Mailey, E.L., White, S.M., Wojcicki, T.R., McAuley, E., & Kramer, A.F. (2012b). Beyond vascularization: Aerobic fitness is associated with N-acetylaspartate and working memory. Brain and Behavior , 2, 32–41. [CrossRef] [PubMed] [Google Scholar]
  • Ferris, L.T., Williams, J.S., & Shen, C.L. (2007). The effect of acute exercise on serum brain-derived neurotrophic factor levels and cognitive function. Medicine & Science in Sport & Exercise 39, 728–734. [CrossRef] [Google Scholar]
  • Fleischman, D.A., Yang, J., Arfanakis, K., Arvanitakis, Z., Leurgans, S.E., Turner, A.D., Barnes, L.L., Bennett, D.A., & Buchman, A.S. (2015). Physical activity, motor function, and white matter hyperintensity burden in healthy older adults. Neurology , 84(13), 1294–1300. [Google Scholar]
  • Forstermann, U., & Munzel, T. (2006). Endothelial nitric oxide synthase in vascular disease: From marvel to menace. Circulation , 113, 1708–1714. [CrossRef] [PubMed] [Google Scholar]
  • Gauthier, C.J., Lefort, M., Mekary, S., Desjardins-Crepeau, L., Skimminge, A., Iversen, P., Madjar, C., Desjardins, M., Lesage, F., Garde, E., Frouin, F., Bherer, L., & Hoge, R.D. (2015). Hearts and minds: Linking vascular rigidity and aerobic fitness with cognitive aging. Neurobiology of Aging , 36, 304–314. [CrossRef] [PubMed] [Google Scholar]
  • Gayda, M., Gremeaux, V., Bherer, L., Juneau, M., Drigny, J., Dupuy, O., Lapierre, G., Labelle, V., Fortier, A., & Nigam, A. (2017). Cognitive function in patients with stable coronary heart disease: Related cerebrovascular and cardiovascular responses. PloS One , 12, e0183791. [CrossRef] [PubMed] [Google Scholar]
  • Geard, D., Reaburn, P., Rebar, A., & Dionigi, R. (2017). Masters athletes: Exemplars of successful aging? Journal of Aging and Physical Activity , 25, 490–500. [CrossRef] [PubMed] [Google Scholar]
  • Gertz, K., Priller, J., Kronenberg, G., Fink, K.B., Winter, B., Schrock, H., Ji, S., Milosevic, M., Harms, C., Bohm, M., Dirnagl, U., Laufs, U., & Endres, M. (2006). Physical activity improves long-term stroke outcome via endothelial nitric oxide synthase-dependent augmentation of neovascularization and cerebral blood flow. Circulation Research , 99, 1132–1140. [CrossRef] [PubMed] [Google Scholar]
  • Gonzales, M.M., Tarumi, T., Kaur, S., Nualnim, N., Fallow, B.A., Pyron, M., Tanaka, H., & Haley, A.P. (2013). Aerobic fitness and the brain: Increased N-acetyl-aspartate and choline concentrations in endurance-trained middle-aged adults. Brain Topography , 26, 126–134. [CrossRef] [PubMed] [Google Scholar]
  • Gordon, B.A., Rykhlevskaia, E.I., Brumback, C.R., Lee, Y., Elavsky, S., Konopack, J.F., McAuley, E., Kramer, A.F., Colcombe, S., Gratton, G., & Fabiani, M. (2008). Neuroanatomical correlates of aging, cardiopulmonary fitness level, and education. Psychophysiology , 45, 825–838. [PubMed] [Google Scholar]
  • Gow, A.J., Bastin, M.E., Muñoz Maniega, S., Valdés Hernández, M.C., Morris, Z., Murray, C., Royle, N.A., Starr, J.M., Deary, I.J., & Wardlaw, J.M. (2012). Neuroprotective lifestyles and the aging brain: Activity, atrophy, and white matter integrity. Neurology , 79(17 PG-1802-8), 1802–1808. [Google Scholar]
  • Grolimund, P., & Seiler, R.W. (1988). Age dependence of the flow velocity in the basal cerebral arteries– a transcranial Doppler ultrasound study. Ultrasound in Medicine & Biology , 14, 191–198. [CrossRef] [PubMed] [Google Scholar]
  • Hajjar, I., Quach, L., Yang, F., Chaves, P.H., Newman, A.B., Mukamal, K., Longstreth, W., Jr., Inzitari, M., & Lipsitz, L.A. (2011). Hypertension, white matter hyperintensities, and concurrent impairments in mobility, cognition, and mood: The Cardiovascular Health Study. Circulation , 123, 858–865. [CrossRef] [PubMed] [Google Scholar]
  • Hakansson, K., Ledreux, A., Daffner, K., Terjestam, Y., Bergman, P., Carlsson, R., Kivipelto, M., Winblad, B., Granholm, A.C., & Mohammed, A.K. (2017). BDNF responses in healthy older persons to 35 minutes of physical exercise, cognitive training, and mindfulness: Associations with working memory function. Journal of Alzheimer’s Disease , 55, 645–657. [CrossRef] [Google Scholar]
  • Hillman, C.H., Erickson, K.I., & Kramer, A.F. (2008). Be smart, exercise your heart: Exercise effects on brain and cognition. Nature Reviews Neuroscience , 9, 58–65. [CrossRef] [PubMed] [Google Scholar]
  • Iadecola, C., Yaffe, K., Biller, J., Bratzke, L.C., Faraci, F.M., Gorelick, P.B., Gulati, M., Kamel, H., Knopman, D.S., Launer, L.J., Saczynski, J.S., Seshadri, S., & Zeki Al Hazzouri, A., American Heart Association Council on H, Council on Clinical C, Council on Cardiovascular Disease in the Y, Council on C, Stroke N, Council on Quality of C, Outcomes R and Stroke C. (2016). Impact of hypertension on cognitive function: A scientific statement from the American Heart Association. Hypertension , 68, e67–e94. [CrossRef] [PubMed] [Google Scholar]
  • Ivey, F.M., Ryan, A.S., Hafer-Macko, C.E., & Macko, R.F. (2011). Improved cerebral vasomotor reactivity after exercise training in hemiparetic stroke survivors. Stroke , 42(7), 1994–2000. [CrossRef] [PubMed] [Google Scholar]
  • Johnson, N.F., Kim, C., Clasey, J.L., Bailey, A., & Gold, B.T. (2012). Cardiorespiratory fitness is positively correlated with cerebral white matter integrity in healthy seniors. Neuroimage , 59(2), 1514–1523. [CrossRef] [PubMed] [Google Scholar]
  • Koziris, L.P., Hickson, R.C., Chatterton, R.T., Jr., Groseth, R.T., Christie, J.M., Goldflies, D.G., & Unterman, T.G. (1999). Serum levels of total and free IGF-I and IGFBP-3 are increased and maintained in long-term training. Journal of Applied Physiology , 86, 1436–1442. [CrossRef] [PubMed] [Google Scholar]
  • Kramer, A.F., & Colcombe, S. (2018). Fitness effects on the cognitive function of older adults: A Meta-Analytic Study-Revisited. Perspectives on Psychological Science , 13, 213–217. [CrossRef] [Google Scholar]
  • Krejza, J., Mariak, Z., Walecki, J., Szydlik, P., Lewko, J., & Ustymowicz, A. (1999). Transcranial color Doppler sonography of basal cerebral arteries in 182 healthy subjects: Age and sex variability and normal reference values for blood flow parameters. AJR. American Journal of Roentgenology , 172, 213–218. [CrossRef] [PubMed] [Google Scholar]
  • Leckie, R.L., Oberlin, L.E., Voss, M.W., Prakash, R.S., Szabo-Reed, A., Chaddock-Heyman, L., Phillips, S.M., Gothe, N.P., Mailey, E., Vieira-Potter, V.J., Martin, S.A., Pence, B.D., Lin, M., Parasuraman, R., Greenwood, P.M., Fryxell, K.J., Woods, J.A., McAuley, E., Kramer, A.F., & Erickson, K.I. (2014). BDNF mediates improvements in executive function following a 1-year exercise intervention. Frontiers in Human Neuroscience , 8, 985. [CrossRef] [PubMed] [Google Scholar]
  • Lee, S., Kim, E.Y., & Shin, C. (2019). Longitudinal association between brain volume change and gait speed in a general population. Experimental Gerontology , 118, 26–30. [CrossRef] [PubMed] [Google Scholar]
  • Lucas, S.J., Ainslie, P.N., Murrell, C.J., Thomas, K.N., Franz, E.A., & Cotter, J.D. (2012). Effect of age on exercise-induced alterations in cognitive executive function: Relationship to cerebral perfusion. Experimental Gerontology , 47(8), 541–551. [CrossRef] [PubMed] [Google Scholar]
  • Marie, C., Pedard, M., Quirie, A., Tessier, A., Garnier, P., Totoson, P., & Demougeot, C. (2018). Brain-derived neurotrophic factor secreted by the cerebral endothelium: A new actor of brain function? Journal of Cerebral Blood Flow and Metabolism , 38, 935–949. [CrossRef] [Google Scholar]
  • Marijon, E., Tafflet, M., Antero-Jacquemin, J., El Helou, N., Berthelot, G., Celermajer, D.S., Bougouin, W., Combes, N., Hermine, O., Empana, J.P., Rey, G., Toussaint, J.F., & Jouven, X. (2013). Mortality of French participants in the Tour de France (1947–2012). European Heart Journal , 34, 3145–3150. [CrossRef] [PubMed] [Google Scholar]
  • Markus, H., & Cullinane, M. (2001). Severely impaired cerebrovascular reactivity predicts stroke and TIA risk in patients with carotid artery stenosis and occlusion. Brain , 124, 457–467. [CrossRef] [PubMed] [Google Scholar]
  • Markus, H.S. (2004). Cerebral perfusion and stroke. Journal of Neurology, Neurosurgery, and Psychiatry , 75, 353–361. [CrossRef] [PubMed] [Google Scholar]
  • Masouleh, S., Beyer, F., Lampe, L., Loeffler, M., Luck, T., Riedel-Heller, S.G., Schroeter, M.L., Stumvoll, M., Villringer, A., & Witte, A.V. (2018). Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults. Journal of Cerebral Blood Flow & Metabolism , 8(2), 360–372. [CrossRef] [Google Scholar]
  • Matura, S., Fleckenstein, J., Deichmann, R., Engeroff, T., Füzéki, E., Hattingen, E., Hellweg, R., Lienerth, B., Pilatus, U., Schwarz, S., Tesky, V.A., Vogt, L., Banzer, W., & Pantel, J. (2017). Effects of aerobic exercise on brain metabolism and grey matter volume in older adults: Results of the randomised controlled SMART trial. Translational Psychiatry , 7(7), e1172. [CrossRef] [PubMed] [Google Scholar]
  • Miyake, A., Friedman, N.P., Emerson, M.J., Witzki, A.H., Howerter, A., & Wager, T.D. (2000). The unity and diversity of executive functions and their contributions to complex “Frontal Lobe” tasks: A latent variable analysis. Cognitive Psychology , 41, 49–100. [CrossRef] [PubMed] [Google Scholar]
  • Moffett, J.R., Ross, B., Arun, P., Madhavarao, C.N., & Namboodiri, A.M. (2007). N-Acetylaspartate in the CNS: From neurodiagnostics to neurobiology. Progress in Neurobiology , 81: 89–131. [CrossRef] [PubMed] [Google Scholar]
  • Murrell, C.J., Cotter, J.D., George, K., Shave, R., Wilson, L., Thomas, K., Williams, M.J., & Ainslie, P.N. (2011a). Cardiorespiratory and cerebrovascular responses to head-up tilt I: Influence of age and training status. Experimental Gerontology , 46, 9–17. [CrossRef] [PubMed] [Google Scholar]
  • Murrell, C.J., Cotter, J.D., George, K., Shave, R., Wilson, L., Thomas, K., Williams, M.J., & Ainslie, P.N. (2011b). Cardiorespiratory and cerebrovascular responses to head-up tilt II: Influence of age, training status and acute exercise. Experimental Gerontology , 46, 1–8. [CrossRef] [PubMed] [Google Scholar]
  • Murrell, C.J., Cotter, J.D., Thomas, K.N., Lucas, S.J., Williams, M.J., & Ainslie, PN. (2013). Cerebral blood flow and cerebrovascular reactivity at rest and during sub-maximal exercise: Effect of age and 12-week exercise training. Age (Dordrecht, Netherlands) , 35, 905–920. [CrossRef] [PubMed] [Google Scholar]
  • Novak, V., & Hajjar, I. (2010). The relationship between blood pressure and cognitive function. Nature Reviews. Cardiology , 7, 686–698. [CrossRef] [PubMed] [Google Scholar]
  • Oberlin, L.E., Verstynen, T.D., Burzynska, A.Z., Voss, M.W., Prakash, R.S., Chaddock-Heyman, L., Wong, C., Fanning, J., Awick, E., Gothe, N., Phillips, S.M., Mailey, E., Ehlers, D., Olson, E., Wojcicki, T., McAuley, E., Kramer, A.F., & Erickson, K.I. (2016). White matter microstructure mediates the relationship between cardiorespiratory fitness and spatial working memory in older adults. Neuroimage , 131, 91–101. [CrossRef] [PubMed] [Google Scholar]
  • Pajonk, F.G., Wobrock, T., Gruber, O., Scherk, H., Berner, D., Kaizl, I., Kierer, A., Muller, S., Oest, M., Meyer, T., Backens, M., Schneider-Axmann, T., Thornton, A.E., Honer, W.G., & Falkai, P. (2010). Hippocampal plasticity in response to exercise in schizophrenia. Archives of General Psychiatry , 67, 133–143. [CrossRef] [PubMed] [Google Scholar]
  • Pereira, A.C., Huddleston, D.E., Brickman, A.M., Sosunov, A.A., Hen, R., McKhann, G.M., Sloan, R., Gage, F.H., Brown, T.R., & Small, SA. (2007). An in vivo correlate of exercise-induced neurogenesis in the adult dentate gyrus. Proceedings of the National Academy of Sciences of the United States of America , 104, 5638–5643. [CrossRef] [PubMed] [Google Scholar]
  • Ploughman, M. (2008). Exercise is brain food: The effects of physical activity on cognitive function. Developmental Neurorehabilitation , 11, 236–240. [CrossRef] [PubMed] [Google Scholar]
  • Prehn, K., Lesemann, A., Krey, G., Witte, A.V., Köbe, T., Grittner, U., & Flöel, A. (2019). Using resting-state fMRI to assess the effect of aerobic exercise on functional connectivity of the DLPFC in older overweight adults. Brain and Cognition , 131, 34–44. [CrossRef] [PubMed] [Google Scholar]
  • Raji, C.A., Merrill, D.A., Eyre, H., Mallam, S., Torosyan, N., Erickson, K.I., Lopez, O.L., Becker, J.T., Carmichael, O.T., Gach, H.M., Thompson, P.M., Longstreth, W.T., & Kuller, L.H. (2016). Longitudinal relationships between caloric expenditure and gray matter in the cardiovascular health study. Journal of Alzheimer’s Disease , 52(2), 719–729. [CrossRef] [Google Scholar]
  • Rooks, C.R., Thom, N.J., McCully, K.K., & Dishman, R.K. (2010). Effects of incremental exercise on cerebral oxygenation measured by near-infrared spectroscopy: A systematic review. Progress in Neurobiology , 92, 134–150. [CrossRef] [PubMed] [Google Scholar]
  • Ruscheweyh, R., Deppe, M., Lohmann, H., Wersching, H., Korsukewitz, C., Duning, T., Bluhm, S., Stehling, C., Keller, S.S., & Knecht, S. (2013). Executive performance is related to regional gray matter volume in healthy older individuals. Human Brain Mapping , 34, 3333–3346. [CrossRef] [PubMed] [Google Scholar]
  • Salthouse, T.A. (2010). Selective review of cognitive aging. Journal of the International Neuropsychological Society , 16, 754–760. [CrossRef] [Google Scholar]
  • Saunders, T.J., Chaput, J.P., & Tremblay, M.S. 2014. Sedentary behaviour as an emerging risk factor for cardiometabolic diseases in children and youth. Canadian Journal of Diabetes , 38(1), 53–61. [CrossRef] [PubMed] [Google Scholar]
  • Schiffer, T., Schulte, S., Sperlich, B., Achtzehn, S., Fricke, H., & Struder, H.K. (2011). Lactate infusion at rest increases BDNF blood concentration in humans. Neuroscience Letters , 488, 234–237. [CrossRef] [PubMed] [Google Scholar]
  • Schmolesky, M.T., Webb, D.L., & Hansen, R.A. (2013). The effects of aerobic exercise intensity and duration on levels of brain-derived neurotrophic factor in healthy men. Journal of Sports Science & Medicine , 12, 502–511. [PubMed] [Google Scholar]
  • Schott, N., & Krull, K. (2019). Stability of Lifestyle Behavior – The answer to successful cognitive aging? A comparison of Nuns, Monks, Master Athletes and non-active older adults. Frontiers in Psychology , 10, 1347. [CrossRef] [PubMed] [Google Scholar]
  • Schwarz, A.J., Brasel, J.A., Hintz, R.L., Mohan, S., & Cooper, D.M. (1996). Acute effect of brief low- and high-intensity exercise on circulating insulin-like growth factor (IGF) I, II, and IGF-binding protein-3 and its proteolysis in young healthy men. The Journal of Clinical Endocrinology and Metabolism , 81, 3492–3497. [PubMed] [Google Scholar]
  • Seider, T.R., Fieo, R.A., O’Shea, A., Porges, E.C., Woods, A.J., & Cohen, R.A. (2016). Cognitively engaging activity is associated with greater cortical and subcortical volumes. Frontiers in Aging Neuroscience , 8(MAY), 1–10. [CrossRef] [PubMed] [Google Scholar]
  • Seifert, T., Brassard, P., Wissenberg, M., Rasmussen, P., Nordby, P., Stallknecht, B., Adser, H., Jakobsen, A.H., Pilegaard, H., Nielsen, H.B., & Secher, N.H. (2010). Endurance training enhances BDNF release from the human brain. American Journal of Physiology. Regulatory, Integrative and Comparative Physiology , 298, R372–377. [CrossRef] [PubMed] [Google Scholar]
  • Sexton, C.E., Betts, J.F., Demnitz, N., Dawes, H., Ebmeier, K.P., & Johansen-Berg, H. (2016). A systematic review of MRI studies examining the relationship between physical fitness and activity and the white matter of the ageing brain. Neuroimage , 131, 81–90. [CrossRef] [PubMed] [Google Scholar]
  • Smith, J.C., Nielson, K.A., Woodard, J.L., Seidenberg, M., Durgerian, S., Hazlett, K.E., Figueroa, C.M., Kandah, C.C., Kay, C.D., Matthews, M.A., & Rao, S.M. (2014). Physical activity reduces hippocampal atrophy in elders at genetic risk for Alzheimer’s disease. Frontiers in Aging Neuroscience , 6(APR), 1–7. [CrossRef] [PubMed] [Google Scholar]
  • Smith, J.C., Lancaster, M.A., Nielson, K.A., Woodard, J.L., Seidenberg, M., Durgerian, S., Sakaie, K., & Rao, S.M. (2016). Interactive effects of physical activity and APOE-ε4 on white matter tract diffusivity in healthy elders. Neuroimage , 131, 102–112. [CrossRef] [PubMed] [Google Scholar]
  • Stein, A.M., Silva, T.M.V., Coelho, F.G.M., Arantes, F.J., Costa, J.L.R., Teodoro, E., & Santos-Galduroz, R.F. (2018). Physical exercise, IGF-1 and cognition A systematic review of experimental studies in the elderly. Dementia & Neuropsychologia , 12, 114–122. [CrossRef] [PubMed] [Google Scholar]
  • Stillman, C.M., & Erickson, K.I. (2018). Physical activity as a model for health neuroscience. Annals of the New York Academy of Sciences , 1428, 103–111. [CrossRef] [PubMed] [Google Scholar]
  • Szabo, A.N., McAuley, E., Erickson, K.I., Voss, M., Prakash, R.S., Mailey, E.L., Wojcicki, T.R., White, S.M., Gothe, N., Olson, E.A., & Kramer, A.F. (2011). Cardiorespiratory fitness, hippocampal volume, and frequency of forgetting in older adults. Neuropsychology , 25, 545–553. [CrossRef] [PubMed] [Google Scholar]
  • Szuhany, K.L., Bugatti, M., & Otto, M.W. (2015). A meta-analytic review of the effects of exercise on brain-derived neurotrophic factor. Journal of Psychiatric Research , 60, 56–64. [CrossRef] [PubMed] [Google Scholar]
  • Taki, Y., Kinomura, S., Sato, K., Goto, R., Wu, K., Kawashima, R., & Fukuda, H. (2011). Correlation between gray/white matter volume and cognition in healthy elderly people. Brain and Cognition , 75, 170–176. [CrossRef] [PubMed] [Google Scholar]
  • Tamura, M., Nemoto, K., Kawaguchi, A., Kato, M., Arai, T., Kakuma, T., Mizukami, K., Matsuda, H., Soya, H., & Asada, T. (2015). Long-term mild-intensity exercise regimen preserves prefrontal cortical volume against aging. International Journal of Geriatric Psychiatry , 30(7), 686–694. [CrossRef] [PubMed] [Google Scholar]
  • Tang, K., Xia, F.C., Wagner, P.D., & Breen, EC. (2010). Exercise-induced VEGF transcriptional activation in brain, lung and skeletal muscle. Respiratory Physiology & Neurobiology , 170, 16–22. [CrossRef] [PubMed] [Google Scholar]
  • Tao, J., Liu, J., Liu, W., Huang, J., Xue, X., Chen, X., Wu, J., Zheng, G., Chen, B., Li, M., Sun, S., Jorgenson, K., Lang, C., Hu, K., Chen, S., Chen, L., & Kong, J. (2017). Tai Chi Chuan and Baduanjin increase grey matter volume in older adults: A brain imaging study. Journal of Alzheimer’s Disease , 60(2), 389–400. [CrossRef] [Google Scholar]
  • Taran, S., Taivassalo, T., & Sabiston, C.M. (2013). The neuroprotective effects of long-term exercise training in older adults: A look at world-ranking elite Masters athletes. Journal of Exercise, Movement, and Sport , 45, 192. [Google Scholar]
  • Tarumi, T., Gonzales, M.M., Fallow, B., Nualnim, N., Pyron, M., Tanaka, H., & Haley, A.P. (2013). Central artery stiffness, neuropsychological function, and cerebral perfusion in sedentary and endurance-trained middle-aged adults. Journal of Hypertension , 31, 2400–2409. [CrossRef] [PubMed] [Google Scholar]
  • Tarumi, T., Gonzales, M.M., Fallow, B., Nualnim, N., Lee, J., Pyron, M., Tanaka, H., & Haley, A.P. (2015). Cerebral/peripheral vascular reactivity and neurocognition in middle-age athletes. Medicine and Science in Sports and Exercise , 47, 2595–2603. [CrossRef] [PubMed] [Google Scholar]
  • Thomas, B.P., Yezhuvath, U.S., Tseng, B.Y., Liu, P., Levine, B.D., Zhang, R., & Lu, H. (2013). Life-long aerobic exercise preserved baseline cerebral blood flow but reduced vascular reactivity to CO2. Journal of Magnetic Resonance Imaging , 38, 1177–1183. [CrossRef] [Google Scholar]
  • Tseng, B.Y., Uh, J., Rossetti, H.C., Cullum, C.M., Diaz-Arrastia, R.F., Levine, B.D., Lu, H.Z., & Zhang, R. (2013a). Masters Athletes exhibit larger regional brain volume and better cognitive performance than sedentary older adults. Journal of Magnetic Resonance Imaging , 38, 1169–1176. [CrossRef] [Google Scholar]
  • Tseng, B.Y., Gundapuneedi, T., Khan, M.A., Diaz-Arrastia, R., Levine, B.D., Lu, H., Huang, H., & Zhang, R. (2013b). White matter integrity in physically fit older adults. Neuroimage , 82, 510–516. [CrossRef] [PubMed] [Google Scholar]
  • Tsivgoulis, G., Alexandrov, A.V., Wadley, V.G., Unverzagt, F.W., Go, R.C., Moy, C.S., Kissela, B., & Howard, G. (2009). Association of higher diastolic blood pressure levels with cognitive impairment. Neurology , 73, 589–595. [Google Scholar]
  • Tyndall, A.V., Davenport, M.H., Wilson, B.J., Burek, G.M., Arsenault-Lapierre, G., Haley, E., Eskes, G.A., Friedenreich, C.M., Hill, M.D., Hogan, D.B., Longman, R.S., Anderson, T.J., Leigh, R., Smith, E.E., & Poulin, M.J. (2013). The brain-in-motion study: Effect of a 6-month aerobic exercise intervention on cerebrovascular regulation and cognitive function in older adults. BMC Geriatrics , 13, 21. [CrossRef] [PubMed] [Google Scholar]
  • Verstynen, T.D., Lynch, B., Miller, D.L., Voss, M.W., Prakash, R.S., Chaddock, L., Basak, C., Szabo, A., Olson, E.A., Wojcicki, T.R., Fanning, J., Gothe, N.P., McAuley, E., Kramer, A.F., & Erickson, K.I. (2012). Caudate nucleus volume mediates the link between cardiorespiratory fitness and cognitive flexibility in older adults. Journal of Aging Research , 2012, 939285. [CrossRef] [PubMed] [Google Scholar]
  • Vesperman, C.J., Pozorski, V., Dougherty, R.J., Law, L.L., Boots, E., Oh, J.M., Gallagher, C.L., Carlsson, C.M., Rowley, H.A., Ma, Y., Bendlin, B.B., Asthana, S., Sager, M.A., Hermann, B.P., Johnson, S.C., Cook, D.B., & Okonkwo, O.C. (2018). Cardiorespiratory fitness attenuates age-associated aggregation of white matter hyperintensities in an at-risk cohort. Alzheimer’s Research & Therapy , 10(97), 1–7. [CrossRef] [Google Scholar]
  • Voelcker-Rehage, C., & Niemann, C. (2013). Structural and functional brain changes related to different types of physical activity across the life span. Neuroscience and Biobehavioral Reviews , 37, 2268–2295. [CrossRef] [PubMed] [Google Scholar]
  • Voss, M.W., Heo, S., Prakash, R.S., Erickson, K.I., Alves, H., Chaddock, L., Szabo, A.N., Mailey, E.L., Wójcicki, T.R., White, S.M., Gothe, N., McAuley, E., Sutton, B.P., & Kramer, A.F. (2013). The influence of aerobic fitness on cerebral white matter integrity and cognitive function in older adults: Results of a one-year exercise intervention. Human Brain Mapping , 34(11), 2972–2985. [CrossRef] [PubMed] [Google Scholar]
  • Wan, Y., Hu, W., Gan, J., Song, L., Wu, N., Chen, Y., & Liu, Z. (2019). Exploring the association between cerebral small-vessel diseases and motor symptoms in Parkinson’s disease. Brain and Behavior , 9(4), e01219. [CrossRef] [PubMed] [Google Scholar]
  • Weinstein, A.M., Voss, M.W., Prakash, R.S., Chaddock, L., Szabo, A., White, S.M., Wojcicki, T.R., Mailey, E., McAuley, E., Kramer, A.F., & Erickson, K.I. (2012). The association between aerobic fitness and executive function is mediated by prefrontal cortex volume. Brain, Behavior, and Immunity , 26, 811–819. [CrossRef] [PubMed] [Google Scholar]
  • Williams, V.J., Hayes, J.P., Forman, D.E., Salat, D.H., Sperling, R.A., Verfaellie, M., & Hayes, S.M. (2017). Cardiorespiratory fitness is differentially associated with cortical thickness in young and older adults. Neuroimage , 146, 1084–1092. [CrossRef] [PubMed] [Google Scholar]
  • Winter, B., Breitenstein, C., Mooren, F.C., Voelker, K., Fobker, M., Lechtermann, A., Krueger, K., Fromme, A., Korsukewitz, C., Floel, A., & Knecht, S. (2007). High impact running improves learning. Neurobiology of Learning and Memory , 87, 597–609. [CrossRef] [PubMed] [Google Scholar]
  • Wood, K.N., Nikolov, R., & Shoemaker, J.K. (2016). Impact of long-term endurance training vs. guideline-based physical activity on brain structure in healthy aging. Frontiers in Aging Neuroscience , 8(JUN), 1–15. [CrossRef] [PubMed] [Google Scholar]
  • Yuki, A., Lee, S., Kim, H., Kozakai, R., Ando, F., & Shimokata, H. (2012). Relationship between physical activity and brain atrophy progression. Medicine and Science in Sports and Exercise , 44, 2362–2368. [CrossRef] [PubMed] [Google Scholar]
  • Zhao, E., Tranovich, M.J., DeAngelo, R., Kontos, A.P., & Wright, V.J. (2016). Chronic exercise preserves brain function in master athletes when compared to sedentary counterparts. The Physician and Sportsmedicine , 44, 8–13. [CrossRef] [PubMed] [Google Scholar]

Cite this article as: Dupuy O, Goenarjo R, Fraser SA, Bherer L, & Bosquet L (2019) Master Athletes and cognitive performance: What are the potential explanatory neurophysiological mechanisms? Mov Sport Sci/Sci Mot, 104, 55–67

All Figures

thumbnail Fig. 1

Summary of the possible neurophysiological mechanisms underlines cognitive improvement after long life intense training.

In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.