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APPLIED SCIENCES: Psychobiology and Behavioral Strategies

The Unique Relation of Physical Activity to Executive Function in Older Men and Women

BIXBY, WALTER R.1; SPALDING, THOMAS W.2; HAUFLER, AMY J.1; DEENY, SEAN P.3; MAHLOW, PAMELA T.4; ZIMMERMAN, JO B.1; HATFIELD, BRADLEY D.1,5

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Medicine & Science in Sports & Exercise: August 2007 - Volume 39 - Issue 8 - p 1408-1416
doi: 10.1249/mss.0b013e31806ad708
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Abstract

Many changes occur in the brain with advanced aging that result in neurocognitive decline (28,30,32). These alterations include atrophy of cortical gyri, decreased brain vascularization, and reductions in central nervous system neurotransmitters. On a behavioral level, the deficits are expressed as slower reaction time as well as a degradation of long-term episodic memory, working memory, and other areas of cognitive performance (28). However, the frontal and prefrontal regions of the brain, which mediate executive processes (i.e., inhibition, selection, scheduling, planning, and coordination of perception, working memory, and action) are especially at risk for age-related decline (33). In contrast, other regions of the brain, such as the occipital lobe and motor cortex, which underlie visual and motor processes, respectively, are relatively immune to the aging process (16). Therefore, from a public health perspective, the preservation of executive function is a primary concern for older men and women because of the accelerated decline of frontal structures and the pivotal role of executive functioning in cognitive operations.

According to epidemiological, correlational, and experimental evidence, physical activity participation yields robust positive effects on a number of cognitive processes associated with normal aging (6) as well as a reduction in the prevalence of dementia (23). However, it seems that the apparent influence of physical activity and fitness on cognition is related to the nature of the cognitive challenge. In this regard, Chodzko-Zajko and Moore (3) reviewed the literature on fitness, cognition, and aging and differentiated cognitive tasks into two categories: those requiring effortful processing, and those requiring relatively little effort that could be performed somewhat automatically. In support of the principle of specificity, they concluded that the greatest benefit of physical fitness extended to tasks requiring effortful processing. More recently, Colcombe and Kramer (6) have refined this taxonomy by further partitioning tasks into 1) speed (i.e., reaction time), 2) spatial, 3) controlled or effortful, and 4) executive functioning. They reported that each of these domains of cognitive function derived benefit from aerobic training, but the magnitude of effect was greatest for executive functions, which may be attributable to the accelerated decline of the frontal lobes (33). In this manner, the angiogenic (enhancing cerebral blood flow) and neurotrophic (enhancing neuronal integrity) effects of physical activity that have been demonstrated in both animal and human brain (9,24) would likely exert the greatest or most apparent influence on those regions experiencing the fastest rate of decline (i.e., the frontal lobes).

In addition to the positive effects of exercise on neurocognitive function in the elderly, Compton, Bachman, and Logan (8) report that education also has an ameliorative effect on age-related cognitive decline, whereas Schmand, Smit, Geerlings, and Lindeboom (26) have observed an even stronger effect of IQ on both cognitive decline and the emergence of incident dementia. Occupational level, which may be considered a proxy for cognitive stimulation, also has shown a protective effect against cognitive decline in older men and women (26). More recently, Fritsch et al. (14), in a retrospective epidemiological study, have reported that IQ, assessed during the high school years, was negatively related to the incidence of dementia in an older cohort. Collectively, these results may be explained by the concept of cognitive reserve (29), which refers to the capacity to withstand structural and functional neurodegenerative processes such that a viable level of cognitive function is maintained for responding to mental challenge. In this regard, native intelligence and a high level of cognitive stimulation, likely attributable to the experiences associated with educational level, promote increased density of dendritic connections between neurons, resulting in greater thickness of the cerebral cortex. Such an adaptation would likely result in greater tolerance of age-related neurodegenerative processes and delay the onset of cognitive deficits relative to those with lower intelligence, education, and cognitive stimulation. As such, a rigorous test of the linkage between physical activity participation and cognitive function in the elderly requires explicit consideration of IQ and education level in study participants, because these factors are known to exert a significant effect of their own.

Furthermore, the magnitude of age-related cognitive deficit likely varies across specific age groups within the older population: the young-old (55-74 yr of age) and the old (75 yr and older) (19). In addition, the National Institute on Aging (NIA) has subdivided the latter group (i.e., the old) into the elderly (75-84 yr) and the oldest old (85 yr and over). Attention to the prevention of frontal decline in the older age groups (over 75 yr) is critical because these individuals would likely exhibit the greatest magnitude of age-related decline in cognitive processes. In this regard Cohn, Dustman, and Bradford (4) examined various age groups (21-30, 41-50, 61-70, and 71-90 yr) to determine the effect of age on a specific aspect of executive processing: cognitive inhibition. Their results reveal that the oldest study participants (71-90 yr) did exhibit a deficit relative to those aged 61-70 as well as both of the younger age groups (21-30 and 41-50 yr), who did not differ from one another. Therefore, it follows that there is a need to examine the impact of physical activity on executive function in older adults, particularly in individuals at the upper boundary of the lifespan.

There are a number of age-appropriate tests of executive function. The Stroop Color and Word Test provides a specific means of assessing inhibitory executive processes (4). This task is highly sensitive to age-related cognitive decline in light of frontal lobe engagement enabling definitive conclusions about frontal integrity. In this regard, a recent fMRI study clearly revealed frontal lobe engagement during Stroop test performance (22). Other tasks that challenge executive function such as the Wisconsin Card Sort Test (WCST) rely on distributed mental processes mediated by the frontal region as well as other brain regions (i.e., temporal-parietal), making it difficult to determine whether behavioral performance is related solely to frontal integrity (25). As such, the Stroop test seems to rely more specifically on frontally mediated processes than many other tests of executive function.

The present study assessed a range of physical activity as it related to performance on a targeted test of executive functioning with a more inclusive age range than that typically employed in other investigations. Specifically, men and women ranging in age from 65 to 92 yr reported their physical activity participation, completed an intelligence test, and reported the number of years of education, which served as a proxy variable for cognitive stimulation. Cognitive performance was evaluated with tests of executive and nonexecutive function. The purpose of this investigation was to examine the association between physical activity and performance on executive and nonexecutive tasks in these older men and women after statistically controlling for the effects of age, cognitive stimulation, and intelligence. Beyond any age-related decrement to cognitive performance or any benefits of cognitive stimulation, we predicted that physical activity participation would account for additional, unique variability in executive performance. In light of the neurobiological benefits of physical activity, we predicted that any activity-induced benefit would be more pronounced with advancing age. In contrast, we expected that the relationship between physical activity and performance on the nonexecutive tasks would be diminished or absent.

METHODS

Participants

Participants were recruited by posted flyers, closed-circuit television announcements, and investigator presentations at a retirement community located in the mid-Atlantic region (Catonsville, MD) of the United States. The participants were 38 men and 84 women aged 65-92 yr (mean = 78.6, SD = 5.7 and mean = 79.1, SD = 5.9, respectively). To assess general health and medication use, participants completed a health history questionnaire. For screening purposes the Beck Depression Inventory (BDI) (2) and the Mini-Mental State Exam (MMSE) (13) were administered to assess depression and dementia, respectively. These inventories revealed that none of the participants were taking psychotropic medications, and none evidenced depression (BDI mean = 5.7, SD = 4.7) or dementia (MMSE mean = 28.7, SD = 1.5). The Kaufman Brief Intelligence Test (K-BIT) (20) also was administered, and all participants exhibited above-average intelligence (K-BIT mean = 118.1, SD = 9.4). Physical activity participation was assessed with the Yale Physical Activity Survey (YPAS) (10). The weekly energy expenditure (i.e., beyond basal metabolic rate) was estimated for all physical activities including those of daily living and those involving light, moderate, and intense exercise. Additionally, the health history questionnaire revealed that physical activity levels were stable for all participants during the past 3-5 yr immediately preceding the study. An examination of the distribution of the physical activity profiles revealed the presence of two women who reported remarkable activity levels. Conversion of their physical activity estimates to z-scores indicated that they were outliers (z1 = 3.47, z2 = 5.75). Hence, these cases were excluded from subsequent analyses, resulting in a sample size of 120 participants for data analysis. Participant characteristics for the final sample are summarized in Table 1 and further classified by gender. All participants provided written informed consent.

TABLE 1
TABLE 1:
Mean (SD) participant characteristics by gender and overall.

Measures

K-BIT.

The K-BIT was created to test individuals aged 4-90 yr and has been scaled and normalized for easy comparison with several other more comprehensive batteries such as the Wechsler Adult Intelligence Scale-Revised (WAIS-R) (20). Reliability testing, using the split-half technique, has revealed correlation coefficients ranging from 0.74 to 0.98, and coefficients for individuals aged 55-90 yr have been quite high (vocabulary: r = 0.98, matrices: r = 0.95, composite: r = 0.98). Estimates of construct validity in adult groups range from r = 0.61 to 0.75 when compared with the WAIS-R, and estimates of concurrent validity in adult groups have ranged from r = 0.37 to 0.50 when compared with the Slosson Intelligence Test (20).

YPAS.

The YPAS was used to assess the participants' physical activity levels (10). The YPAS considers a wide range of physical activities including those involved in household chores, recreation, and structured exercise. It is particularly useful in the assessment of physical activity in those over age 60 because of the inclusion of low-intensity activities. Participants reported how much time that they spent on a comprehensive list of activities as well as the frequency and duration of physical activity in five categories or dimensions (i.e., vigorous activity, leisurely walking, moving, standing, and sitting) during a typical week. An index score for each category was computed as a product of frequency, duration, and a weighting factor that was related to the intensity of physical activity for that category (10). A summary score, referred to subsequently as the Yale index, was calculated as the sum of index scores across the five activity categories (10). As such, the Yale index characterized the total physical activity that an individual completed during a typical 7-d period, with consideration of intensity achieved by weighting the activities in the various categories. The YPAS also yields an estimate of the weekly volume of physical activity expressed in kilocalories, without additional categorical weighting given to the intensity of the activities.

The Stoop Color and Word Test.

The Stroop test (15) was selected as a measure of inhibition, a key executive function. The Stroop test requires suppression of one's response to a dominant stimulus pattern (printed words) while attending and responding to a secondary stimulus characteristic (i.e., ink color). There are three phases of the test, each 45 s in duration. The first phase assesses the number of words that can be read (i.e., names of colors-red, green, and blue appearing in black-colored ink), and the second phase assesses the number of colored stimuli (i.e., a string of X's printed in one of the three respective colors) that can be correctly identified during the 45-s interval. The third phase assesses the participant's ability to identify the color of ink while suppressing the response to identify text, which appears in an incongruent color (e.g., the word "RED" printed in blue ink). The Stroop test yields four scores: one each for the word and color tests, a color-word score, and the interference score, which is derived from performance on the three phases described above (15). The raw word, color, and color-word scores simply represent the total number of correct responses during each of the respective tasks. An age-based correction factor was applied to each of the word (w), color (c), and color-word (cw) scores. A predicted color-word score (cw′), which served to adjust for individual differences in the speed of naming words and colors, was then computed by dividing the product of the word and color scores by the sum of the word and color scores: (cw′ = w × c/w + c). Finally, the interference (I) score was calculated by subtracting the predicted color-word score from the obtained color-word score (I = cwcw′) to assess resistance to cognitive interference (i.e., cognitive inhibition). It served as the primary index of executive function (15). A higher score represents more resistance to cognitive interference and, therefore, better executive function (15).

Procedures

Participants were tested individually in a single session that was conducted in a quiet classroom on the campus of the retirement community in which the participants lived. On arrival the participant was given an overview of the study and a description of the requirements, after which they provided written consent on a form approved by the institutional human research review board. The participant then completed the health history screening questionnaire and the BDI. A trained research assistant administered the MMSE, the K-BIT, the Stroop test, and the YPAS. On completing the protocol, participants were allowed to ask questions about the nature of the investigation and thanked for their time.

Statistical Analysis

A series of hierarchical regression analyses, which specifically accounted for age and the role of cognitive stimulation (as represented by years of education and IQ), was planned, to isolate the link between cognitive performance and physical activity. Justification for inclusion of the variables entered into the regression equations applied to the scores for the executive challenge (i.e., color-word and the derived interference score) was empirically based on the attainment of significant correlations between the dependent measures of interest and each of the predictor variables. An interaction term, calculated as the product of age and the Yale index, was also included in the model to test whether the relationship between physical activity and executive task performance was dependent on age. To test the notion of specificity in the relationship between cognitive performance and physical activity, these same regression models were also applied to the nonexecutive challenges (i.e., word and color). The significant correlations required for inclusion of the predictor variables identified above were not consistently obtained and, therefore, precluded empirical justification. However, all four of the Stroop test variables were subjected to the same model sequence, to achieve consistency in the statistical treatment of the dependent measures. The correlation matrix is presented in Table 2. Although the Yale index was significantly correlated with the executive variables, the weekly kilocalorie estimates were not associated with any of the cognitive performance measures. Figure 1 illustrates the coefficients obtained for the correlation of the Yale index and weekly kilocalories with each of the measures of cognitive performance.

TABLE 2
TABLE 2:
Mean (SD) cognitive performance scores by gender and overall.
FIGURE 1
FIGURE 1:
Pearson coefficients for correlation of the Yale index (A) and weekly kilocalories (B) with Stroop word, color, color-word (C-W), and interference (inter) scores. The only significant correlations observed were between the Yale index and the measures of executive function (i.e., Stroop color-word and interference scores). *Significant correlation coefficient, P < 0.05.

Thus, the word, color, color-word, and interference scores were regressed separately on age, education, IQ, Yale index, and the age × Yale index interaction term. Age was entered at the first step of the analysis to account for variability in cognitive performance attributable to individual differences in age (age ranged from 65 to 92 yr). Education was entered at the second step to account for variability in cognitive performance attributable to individual differences in the years of education completed by the participants (education ranged from 10 to 26 yr). K-BIT composite scores (IQ) were entered into the regression model at the third step of these analyses in order to account for variance in Stroop test performance attributable to individual differences in intelligence. The Yale index was then entered into the model at the fourth step in order to assess the unique variance in Stroop test performance accounted for by physical activity after accounting for the influence of age, education, and IQ. Finally, the age × Yale index interaction term was entered into the model at the last step. The increment in explained variance (ΔR2) was tested for significance at each step of the analysis. A criterion alpha of 0.05 was adopted for all tests.

RESULTS

Mean performance on the cognitive tests is reported by gender and for the sample overall in Table 3. Summaries of the hierarchical regression analyses for Stroop test performance are presented in Table 4. The analyses of the executive measures revealed that age, education, and IQ were significant predictors of performance for both color-word and interference (Table 4). After accounting for the influence of these variables, the Yale index was positively related to executive task performance and explained a small but significant amount of variance in both color-word (ΔR2 = 0.02, P = 0.04) and interference (ΔR2 = 0.04, P = 0.01) scores. Further, the relationship between physical activity and Stroop test performance did not vary across the age range examined in this study, as indicated by the nonsignificant age × Yale index interaction term. Collectively, these results indicate that chronic physical activity explained a small but significant amount of variance in Stroop executive task performance beyond that explained by age and cognitive stimulation, and that the unique relationship of physical activity and Stroop executive performance was stable across the age range (65-92 yr) examined in this study. The Yale index was unrelated to nonexecutive performance (i.e., word and color scores). Bivariate scatterplots of the Yale index with the Stroop word, color, color-word, and interference scores, residualized on age, education, and K-BIT composite IQ, are shown in Figure 2.

TABLE 3
TABLE 3:
Intercorrelations between intelligence, education, Yale index, and cognitive performance scores.
TABLE 4
TABLE 4:
Summary of hierarchical regression analyses for Stroop Color-Word test.
FIGURE 2
FIGURE 2:
Bivariate scatterplots of Yale index scores with Stroop word, color, color-word and interference residuals. Stroop test scores were residualized by removing the influence of age, years of education, and the K-BIT composite IQ. The regression equations represent the regression of the Stroop residuals on the Yale index. Slopes were significant for Stroop color-word and interference residuals (executive function) but not for word or color residuals (nonexecutive function).

DISCUSSION

The relationship between physical activity participation and cognitive function was investigated in older men and women who represented a broad age range (65-92 yr). The primary purpose of the study was to examine the specificity of this relationship on the basis of the work of Kramer et al. (21), who have observed that the magnitude of the benefits derived from aerobic exercise were strongly related to the specific nature of the cognitive challenge. More specifically, Colcombe et al. (6) have noted that reaction time, spatial, controlled or effortful, and executive functioning all benefit from exercise participation, but the greatest effects were revealed for tasks that are executive in nature. The present findings also support the notion of specificity in the physical activity-cognition relationship and extend the principle to a broader definition of motor behavior by examining overall physical activity, including activities of daily living in addition to vigorous exercise. The independently dwelling sample examined in this study was healthy, nondepressed, and high in formal education; as such, this sample provided a conservative test of the relationship between physical activity and cognitive function. Accordingly, this high level of function provided only a small margin for accruing any benefit from physical activity. However, despite this constraint, we were able to account for significant variation in executive function, albeit modest, in this population on the basis of physical activity. Furthermore, we attempted to control for cognitive stimulation via assessment of IQ and years of education to determine whether physical activity was uniquely associated with cognitive performance. The results imply an independent benefit beyond that resulting from mental activity.

Initially, we examined the overall pattern of correlations among the variables to gauge the logical structure of the data set and evaluated the results of the regression analyses to determine concurrence with findings reported in previous investigations of age, physical activity, and cognition (3,11,17). As expected, age was, indeed, negatively correlated with both executive and non-executive function, and accounted for as much as 13% of the variability in performance. Also, as predicted, cognitive stimulation was related to cognitive performance. More specifically, IQ was positively correlated with all categories of cognitive performance and specifically accounted for as much as 17% of executive task performance. Furthermore, years of education was related only to executive performance and explained approximately 4% of the variance. The findings were mixed for the nonexecutive tests of speeded response (word and color), because a negative correlation was found between age and color naming speed, whereas no such relationship was found with word naming. Also, as predicted, physical activity was positively correlated with executive task performance and explained a modest, but unique, 2-4% of the variance. The finding implies opportunity for neurobiological benefit from physical activity participation even with advancing age. Although the magnitude of the explained variance was relatively modest it is remarkable that any such effect was observed in light of the high functioning of the present sample. That is, they were characterized by high IQ and educational attainment, absence of depression, and robust health and vitality, so little opportunity for activity-induced benefit would be expected. No relationship was found between physical activity and the nonexecutive performance measures of word and color. Collectively, these findings underscore a selective or specific relationship between physical activity and cognitive function (21).

In light of the magnitude of the age range of the study participants, it was important to determine whether the relationship between physical activity and cognition varied or was modified with age. The age range of the sample in the present study was wider than that typically studied (e.g., 65-92 yr in the present study vs 60-75 yr in that conducted by Kramer et al. (21)), and this study included individuals who were less likely or unable to engage in vigorous cardiovascular training regimens. The regression analyses revealed that physical activity was positively related to executive function across the age range examined and the findings suggest that activity-induced benefit is constant for this age, as indicated by the absence of a significant interaction between age and the Yale index. Such a finding suggests a consistent influence of physical activity on the older brain. However, the relationship between physical activity and executive task performance may not be constant across such a wide age range in older men and women in the population at large. That is, the potential benefit available to the older individuals in the present sample may not have been fully realized. More specifically, executive task performance was negatively correlated with age (r = −0.36 and −0.31 for color-word and interference, respectively) in this study sample, indicating that cognitive performance worsened with advancing age and implying that the older participants in the study had a greater opportunity to benefit from regular physical activity. Accordingly, if physical activity levels were uniform across the age range, the older individuals in the sample may have exhibited greater benefit and the age × Yale index interaction term might have been significant. However, the lack of a significant interaction may have been attributable to the fact that physical activity levels declined with age as the Yale index was negatively correlated with age (r = −0.23). Hence, the older individuals may not have capitalized on the potential benefit attributable to a decline in physical activity.

On the basis of the present findings, the intensity dimension of physical activity seems to be a critical aspect of its relationship with cognition. The Yale index, which is particularly sensitive to the intensity of physical activity, was significantly associated with executive function, whereas overall energy expenditure (kcal) was not. Total caloric expenditure is inclusive of activities of daily living and other low-intensity behaviors, as well as higher-intensity activities, but the results of the present study, which only reveal a positive slope for the Yale index, suggest that some degree of cardiovascular demand is essential to achieve cognitive benefit. That is, those who reported higher intensity (i.e., higher index) exhibited higher executive performance. Perhaps this is attributable to a need to challenge the cardiovascular system before activity-induced central nervous system adaptations are triggered. However, the link between cognition and cardiovascular function (i.e., fitness) is not a direct one. On the basis of a recent meta-analytic review, Etnier et al. (12) did not find a significant relationship between cognition and aerobic capacity, although there was a clear relationship with participation in physical activity. As such, there are many alternative ways that physical activity may influence mental function, such as angiogenic and neurotrophic processes on various brain regions or structures, as well as social stimulation. The present study suggests that both volume and intensity of the work stimulus (i.e., physical activity) are important considerations for deriving cognitive benefit.

To isolate the role of physical activity, we accounted for the influence of age and cognitive stimulation on executive performance in the initial steps of the regression analyses. In agreement with earlier investigations (8), education was positively related to cognitive function. It is noteworthy that both cognitive stimulation (i.e., as indexed by IQ and education) and physical activity were positively related to performance on the tests of executive function. This was not unexpected, given the findings of Fritsch et al. (14)-who observed a negative relationship between IQ, as measured during the high school years and incident dementia, in a retrospective study of older men and women-as well as those of Compton et al. (8), who found an ameliorative effect of education on age-related cognitive decline. A strong case for the powerful influence of cognitive ability on neurocognitive decline can also be made from the studies of cognitive status of older members of religious orders (i.e., the studies of Catholic nuns) (27). This work has revealed that language facility during young adulthood, in this population who lived a remarkably controlled lifestyle, was inversely related to mental decline in the later years. Collectively, these investigations strongly demonstrate the need to control for the influence of intellectual variables when assessing the role of physical activity on cognitive performance, because mental activity is known to impact cognitive reserve. In this regard, Allen et al. (1) distinguished between passive and active dimensions of cognitive reserve; passive reserve refers to the biological integrity of the brain (i.e., volume of neuropil and connectivity allowing one to tolerate age-related atrophy), and active reserve refers to strategic flexibility and compensation during problem solving. One would logically assume that both mental and physical activity contribute to cognitive reserve, but the essential finding in the present study is that there seems to be a unique influence of physical activity on cognition that is likely attributable to additive neurobiological benefit, beyond that attributable to cognitive stimulation.

In fact, a number of investigators have reported neurobiological benefits in animal studies suggesting mechanisms that may also be operating in the brains of older men and women. Cotman and Berchtold reported that exercise maintains brain function and promotes brain plasticity (9). They reported an upregulation of certain neurotrophic factors in rats as a result of exercise. Specifically, exercise increases brain derived neurotrophic factor (BDNF), which helps to protect neurons against insult and is necessary for long-term potentiation and synaptic growth (9). Although the earliest and most sustained increases in BDNF after exercise have been shown in the hippocampus, the frontal cortex, which mediates executive function, has also exhibited increases in BDNF (C. W. Cotman, personal communication, 2003). Although this research was based on an animal model, Colcombe et al. (5) recently reported a study in which structural MRI scans of brain tissue in middle-aged men and women revealed that those regions of the brain exhibiting the greatest age-related neural degeneration were the regions most spared by increased aerobic fitness, including the anterior white-matter tracts, and the gray matter of the prefrontal cortex. Aerobic capacity was positively related to tissue density in cortical association regions at greatest risk for age-related decline with particular impact in the prefrontal. The neurotrophic influences reported by the Cotman group in animals may well explain the structural MRI findings reported by Colcombe et al. (5) in humans. Thus, it seems that it is biologically plausible for physical activity to exert a positive effect on brain structures that are associated with executive function.

In a related paper, Colcombe et al. (7) examined hemodynamic response in the brain to the Ericksen flanker task using fMRI with both an extreme-groups contrast (fit vs sedentary) and an intervention study; the latter was employed to detect brain changes causally related to aerobic training. The results of the studies were convergent and revealed increased activation in midfrontal and temporal-parietal regions (indicative of enhanced processing) in aerobically trained individuals, whereas other regions of the brain (anterior cingulate cortex (ACC)) revealed a decrease in activation in these groups that may be attributable to a reduced need for conflict resolution. That is, the ACC is activated during unintended responses so as to correct future action but heightened attentional processing in the fit individuals may have reduced the load on this region. Such a coordinated change in brain activation implies a clear and logical outcome on the basis of the link between exercise and neurocognitive function. In this manner, the intervention clearly reveals that physical activity participation causally affects executive function in the form of improved inhibition and focused attention. Beyond the neurotrophic effect, Isaacs et al. (18) have provided evidence that physical activity has an angiogenic effect on the cerebellum in rat brains. Such a finding implies that physical activity may also influence cerebral blood flow and oxygenation in human brains. In fact, Rogers, Meyer, and Mortel (24) report that physical activity is associated with maintenance of blood flow in the human cerebral cortex as the brain ages. Collectively, these findings suggest that aerobic exercise may exert profound changes on the central nervous system independently of the effects of cognitive stimulation and, specifically, on areas of the brain where executive functions are processed.

In summary, the results of this investigation reveal that a physically active lifestyle is uniquely associated with specific cognitive benefits in older men and women. The present results suggest benefits from physical activity beyond those attained through cognitive stimulation and extend the findings of Kramer et al. (21) to the oldest old regarding the relationship between physical activity and executive function, controlling for important sources of variability (education and IQ). This is logical, given the accelerated decline of the frontal lobe, which would be expected to show greater benefit from physical activity relative to other brain regions. Although the explained variance in executive function is modest, it is important to remember that the participants in this investigation were already functioning at a high level. Thus, there was little room for alteration, and the study provides for a conservative test of the benefits of physical activity on the aging brain. Furthermore, in light of the modest levels of physical activity reported by the participants this study also extends the position of the 1996 report of the Surgeon General (31), such that moderate, accumulated physical activity benefits cognitive function as well as physical health. Therefore, a physically active lifestyle seems to maintain and enhance specific aspects of cognitive function in older men and women, and the benefits seem to increase with more vigorous activity participation.

This research was funded by a grant from the Erickson Foundation, 701 Maiden Choice Lane, Catonsville, MD 21228.

REFERENCES

1. Allen, J. S., J. Bruss, C. K. Brown, and H. Damasio. Normal neuroanatomical variation due to age: the major lobes and a parcellation of the temporal region. Neurobiol. Aging 26:1245-1260, 2005.
2. Beck, A. T., C. H. Ward, M. Mendelson, J. Mock, and J.Erbaugh. An inventory for measuring depression. Arch. Gen. Psychiatry 4:561-571, 1961.
3. Chodzko-Zajko, W. J., and K. A. Moore. Physical fitness and cognitive functioning in aging. Exerc. Sport Sci. Rev. 22:195-220, 1994.
4. Cohn, N. B., R. E. Dustman, and D. C. Bradford. Age-related decrements in Stroop color test performance. J. Clin. Psychol. 40:1244-1250, 1984.
5. Colcombe, S. J., K. I. Erickson, N. Raz, et al. Aerobic fitness reduces brain tissue loss in aging humans. J. Gerontol. A Biol. Sci. Med. Sci. 58:176-180, 2003.
6. Colcombe, S. J., and A. F. Kramer. Fitness effects on the cognitive function of older adults: a meta-analytic study. Psychol. Sci. 14:125-130, 2003.
7. Colcombe, S. J., A. F. Kramer, K. I. Erickson, et al. Cardiovascular fitness, cortical plasticity, and aging. Proc. Natl. Acad. Sci. U. S. A. 101:3316-3321, 2004.
8. Compton, D. M., L. D. Bachman, and J. A. Logan. Aging and intellectual ability in young, middle-aged, and older educated adults: preliminary results from a sample of college faculty. Psychol. Rep. 81:79-90, 1997.
9. Cotman, C. W., and N. C. Berchtold. Exercise: a behavioral intervention to enhance brain health and plasticity. Trends Neurosci. 25:295-301, 2002.
10. Di Pietro, L., C. J. Caspersen, A. M. Ostfeld, and E. R. Nadel. A survey for assessing physical activity among older adults. Med. Sci. Sports Exerc. 25:628-642, 1993.
11. Dustman, R. E., R. O. Ruhling, E. M. Russell, et al. Aerobic exercise training and improved neuropsychological function in older individuals. Neurobiol. Aging 5:35-42, 1994.
12. Etnier, J. L., P. M. Nowell, D. M. Landers, and B. A. Sibley. A meta-regression to examine the relationship between aerobic fitness and cognitive performance. Brain Res. Rev. 52:119-130, 2006.
13. Folstein, M. F., S. E. Folstein, and P. R. McHugh. "Mini-mental state." A practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 12:189-198, 1975.
14. Fritsch, T., K. A. Smyth, M. J. McClendon, et al. Associations between dementia/mild cognitive impairment and cognitive performance and activity levels in youth. J. Am. Geriatr. Soc. 53:1191-1196, 2005.
15. Golden, C. J. Stroop Color and Word Test: A Manual for Clinical and Experimental Uses. Los Angeles, CA: Western Psychological Services, 1978.
16. Hatfield, B. D., T. W. Spalding, R. J. Apparies, A. J. Haufler, and D. L. Santa Maria. The relationship of physical activity to pattern-reversal evoked-potential components in young and older men and women. J. Aging Phys. Act. 11:167-188, 2003.
17. Hendrie, H. C., M. S. Albert, M. A. Butters, et al. The NIH Cognitive and Emotional Health Project: Report of the Critical Evaluation Study Committee. Alzheimers Dement. 2:12-32, 2006.
18. Isaacs, K. R., B. J. Anderson, A. A. Alcantara, J. E. Black, and W. T. Greenough. Exercise and the brain: angiogenesis in the adult rat cerebellum after vigorous physical activity and motor skill learning. J. Cereb. Blood Flow Metab. 12:110-119, 1992.
19. Kart, C. S., and J. M. Kinney. The Realities of Aging: An Introduction to Gerontology, 6th ed. Boston, MA: Allyn and Bacon, 2001.
20. Kaufman, A. S., and N. L. Kaufman. Kaufman Brief Intelligence Test Manual. Circle Pines, MN: American Guidance Services, 1990.
21. Kramer, A. F., S. Hahn, N. J. Cohen, et al. Aging, fitness and neurocognitive function. Nature 400:418-419, 1999.
22. Langenecker, S. A., K. A. Nielson, and S. M. Rao. fMRI of healthy older adults during Stroop interference. Neuroimage 21:192-200, 2004.
23. Laurin, D., R. Verreault, J. Lindsay, K. MacPherson, and K. Rockwood. Physical activity and risk of cognitive impairment and dementia in elderly persons. Arch. Neurol. 58:498-5004, 2001.
24. Rogers, R. L., J. S. Meyer, and K. F. Mortel. After reaching retirement age physical activity sustains cerebral perfusion and cognition. J. Am. Geriatr. Soc. 38:123-128, 1990.
25. Royall, D. R., E. C. Lauterbach, J. L. Cummings, et al. Executive control function: a review of its promise and challenges for clinical research. A report from the Committee on Research of the American Neuropsychiatric Association. J. Neuropsychiatry Clin. Neurosci. 14:377-405, 2002.
26. Schmand, B., J. H. Smit, M. I. Geerlings, and J. Lindenboom. The effects of intelligence and education o the development of dementia. A test of the brain reserve hypothesis. Psychol. Med. 27:1334-1337, 1997.
27. Snowdon, D. A., L. H. Greiner, and W. R. Markesbury. Linguistic ability in early life and the neuropathology of Alzheimer's disease and cerebrovascular disease. Ann. N. Y. Acad. Sci. 903:34-38, 2000.
28. Spirduso, W. W. Health, exercise, cognitive function. In: Physical Dimensions of Aging. Champaign, IL: Human Kinetics, 1995.
29. Stern, Y. What is cognitive reserve? Theory and research application of the reserve concept. J. Int. Neuropsychol. Soc. 8:448-460, 2002.
30. Tomporowski, P. D., and B. D. Hatfield. Effects of exercise on neurocognitive functions. Int. J. Sport Exerc. Psychol. 3:263-279, 2005.
31. U.S. Department of Health and Human Services. Physical Activity and Health: A Report of the Surgeon General, Executive Summary. Atlanta, GA: U.S. Department of Health and Human Services, 1996. Publication HE 20.7602:P 56.
32. Van Petten, C., E. Plante, P. S. R. Davidson, T. Y. Kuo, L. Bajuscak, and E. L. Glisky. Memory and executive function in older adults: Relationships with temporal and prefrontal gray matter volumes and white matter hyperintensities. Neuropsychologia 42:1313-1335, 2004.
33. West, R. An application of prefrontal cortex function theory to cognitive aging. Psychol. Bull. 120:272-292, 1996.
Keywords:

AGING; COGNITION; EXERCISE; STROOP TEST

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