+1(978)310-4246 credencewriters@gmail.com
  

article Summary

the summary should focus on methods, results, and  discussion of the article, and what you took away from it of relevance to the aging population. You can choose either one of the following articles.

Journal of Gerontology: MEDICAL SCIENCES
2006, Vol. 61A, No. 11, 1166–1170
Copyright 2006 by The Gerontological Society of America
Exercise: An Active Route to Healthy Aging
Aerobic Exercise Training Increases
Brain Volume in Aging Humans
1
Beckman Institute & Department of Psychology and 2Department of Kinesiology,
University of Illinois, Urbana.
Background. The present study examined whether aerobic fitness training of older humans can increase brain volume
in regions associated with age-related decline in both brain structure and cognition.
Methods. Fifty-nine healthy but sedentary community-dwelling volunteers, aged 60–79 years, participated in the 6month randomized clinical trial. Half of the older adults served in the aerobic training group, the other half of the older
adults participated in the toning and stretching control group. Twenty young adults served as controls for the magnetic
resonance imaging (MRI), and did not participate in the exercise intervention. High spatial resolution estimates of gray
and white matter volume, derived from 3D spoiled gradient recalled acquisition MRI images, were collected before and
after the 6-month fitness intervention. Estimates of maximal oxygen uptake (VO2) were also obtained.
Results. Significant increases in brain volume, in both gray and white matter regions, were found as a function of
fitness training for the older adults who participated in the aerobic fitness training but not for the older adults who
participated in the stretching and toning (nonaerobic) control group. As predicted, no significant changes in either gray or
white matter volume were detected for our younger participants.
Conclusions. These results suggest that cardiovascular fitness is associated with the sparing of brain tissue in aging
humans. Furthermore, these results suggest a strong biological basis for the role of aerobic fitness in maintaining and
enhancing central nervous system health and cognitive functioning in older adults.
B
EGINNING in the third decade of life the human brain
shows structural decline, which is disproportionately
large in the frontal, parietal, and temporal lobes of the brain
(1). This decline is contemporaneously associated with
deterioration in a broad array of cognitive processes (2).
Given the projected increase in the number of adults surviving to advanced age, and the staggering costs of caring
for older individuals who suffer from neurological decline,
identifying mechanisms to offset or reverse these declines
has become increasingly important.
Cardiovascular exercise has been associated with improved cognitive functioning in aging humans (3,4). These
effects have been shown to be the greatest in higher order
cognitive processes, such as working memory, switching
between tasks, and inhibiting irrelevant information, all of
which are thought to be subserved, in part, by the frontal
lobes of the brain (3). However, very little is known about
the structural brain changes, if any, which underlie these
benefits in humans. Previous research with nonhuman
animals has shown that chronic aerobic exercise can lead
to the growth of new capillaries in the brain (5,6), increase
the length and number of the dendritic interconnections
between neurons (7), and even increase cell production in
the hippocampus (8). These effects likely result from
increases in growth factors such as brain-derived neurotrophic factor (7,9) and insulin-like growth factor (10,11),
1166
among others (12). The end result of these structural
changes is a better interconnected brain that is more plastic
and adaptive to change (8,13). Given that cardiovascular
exercise has similar effects on human cognitive function that
might be predicted from the structural changes in nonhuman
animals, it seems likely that similar structural changes
would be engendered in human brain tissue following
chronic exercise, but research examining the impact of
exercise on brain structure has overwhelmingly relied upon
nonhuman animals, due to the highly invasive methods
typically required to assess changes in brain structure.
With the advent of noninvasive in vivo brain imaging
technologies such as structural and functional magnetic
resonance imaging (MRI), it is possible to address questions
about changes in the underlying brain structure of humans.
In one such study (14), we found that older adults with a
lifelong history of cardiovascular exercise had better preserved brains than did age-matched sedentary counterparts.
Interestingly, the structural preservation was greatest in the
frontal and parietal regions of the brain, which are thought
to subserve aspects of higher order cognition, such as working
memory, task switching, and the inhibition of irrelevant
information. However, owing to the cross-sectional nature
of that study, it is conceivable that a number of factors
influence both brain volume and aerobic fitness. It is even
possible that the relationship is reversed. That is, those older
Downloaded from http://biomedgerontology.oxfordjournals.org/ at Georgia Southwestern State University on June 2, 2015
Stanley J. Colcombe,1 Kirk I. Erickson,1 Paige E. Scalf,1 Jenny S. Kim,1 Ruchika Prakash,1
Edward McAuley,2 Steriani Elavsky,2 David X. Marquez,2 Liang Hu,2 and Arthur F. Kramer1
FITNESS AND BRAIN HEALTH
Table 1. Demographic Information on Aerobic Exercising and
Nonaerobic Exercising Control Older Adults
Measured Variable
Exercise
Control
t Test
Initial VO2
Change in VO2
Age
Sex
Education
MMSE
Hypertensive
HRT (women)
23.3 (2.4)
16.1% (1.9)
65.5 y
53% women
13.5 y
29 (1.2)
30%
43.3%
23.6 (2.7)
5.3% (1.3)
66.9 y
57% women
14 y
29.4 (1.4)
26.7%
53.3%
t(58) , 1, NS
t(58) ¼ 2.05, p , .025
t(58) , 1, NS
t(58) , 1, NS
t(58) , 1, NS
t(58) , 1, NS
t(58) , 1, NS
t(58) , 1, NS
adults who have relatively well preserved brains may be
differentially able to maintain participation in a physically
active lifestyle, through better preserved cognitive abilities
or some other set of genetic or environmental variables that
affect both somatic and brain health.
To address this issue, we randomly assigned 59 older
adults to participate in either a cardiovascular exercise group
or a nonaerobic exercise control group for a 6-month period.
We scanned these participants in a high-resolution structural
MRI protocol immediately before and after participation
in the exercise program. We then compared changes in
regional brain volume from preintervention to postintervention for aerobic exercisers and nonaerobic exercise control
participants using an optimized voxel-based morphometric
technique which can assess tissue volume in a point-bypoint fashion throughout the brain (see Methods). We
additionally analyzed high-resolution brain scans of 20
younger adults; these scans were collected at the same
intervals as those from the older adults. The younger adults
did not participate in an exercise intervention, and served
largely as methodological controls as we did not expect to
see any appreciable change in the volume of younger adult
brains within the 6-month time frame of the study.
METHODS
Participants
Fifty-nine older (60–79 years) and 20 younger (18–30
years) right-handed, neurologically intact adults took part in
the 6-month study. All participants were screened for
neurological defect (e.g., possible dementia, self-report of
neurological disease such as multiple sclerosis, brain tumor,
and Parkinson’s disease) and appropriateness for testing in
an MRI environment (e.g., no metallic implants that could
interfere with testing, no claustrophobia). Older adults were
additionally required to obtain physician approval for
participation in an exercise program before beginning any
phase of the study. Older participants were randomly assigned by the project coordinator during recruitment to
participate in either an aerobic exercise program or a nonaerobic stretching and toning exercise program.
Participant characteristics are documented in Table 1. The
only significant difference between the aerobic and nonaerobic training group participants was in the maximal oxygen uptake (VO2) change measure (i.e., the cardiovascular
improvement from pre- to post-training). The Institutional
Review Board at the University of Illinois approved this
research. Written informed consent was obtained from all
participants.
Exercise Intervention Protocols
The aerobic exercise intervention was designed to
improve cardiorespiratory fitness with an exercise intensity
prescription derived from peak heart rate (HR) responses to
baseline graded exercise testing. Intensity levels began at
40%–50% HR reserve increasing (15) to 60%–70% HR
reserve over the course of the trial. Intensity levels and
exertion were recorded in daily exercise logs and monitored
by trained exercise leaders. Participants in the older
nonaerobic exercise control group followed the same
activity schedule and format as the aerobic exercise group
did, but engaged in a program of whole-body stretching and
toning designed for individuals 60 years old or older. As the
individual’s level of flexibility increased, stretches with
increasing levels of difficulty were incorporated into the
program. Participants in both the aerobic and control
exercise groups attended three 1-hour exercise training
sessions per week for the 6-month period of the intervention. Compliance in the exercise sessions was excellent,
exceeding 85% for all participants. Each group participated
in their sessions at separate geographical locations around
campus to reduce the probability of any crossover effects
occurring between the groups.
Assessment of Cardiorespiratory Fitness
Participants completed a graded exercise test on a motordriven treadmill. Peak oxygen uptake (VO2peak) was measured from expired air samples taken at 30-second intervals
until the highest VO2peak was attained at the point of volitional exhaustion. The aerobic fitness training group showed
a significant 16.1% in increase in VO2peak, whereas the older
control participants showed a nonsignificant 5.3% change in
VO2peak across the 6-month intervention.
Imaging Protocols and Analyses
We acquired a high-resolution T1 weighted structural
image for each participant, 1 week prior to the intervention
and within 1 week after cessation of the exercise program.
Twenty-two of the older adults and eight of the younger
adults were scanned in a 1.5 Tesla GE Signa MRI scanner
(1 3 1 3 1.3 mm; Niskayuna, NY) at both times 1 and 2 and
the remaining older and younger adults were scanned in a
3 Tesla Siemens Allegra MRI scanner (1 3 1 3 1.3 mm;
Malvern, PA) at both times 1 and 2. None of the results
reported in this study were significantly impacted by the
scanner type used to acquire the MRI images.
Our voxel-based morphometry analyses largely followed
those methods described elsewhere (16), with the exception
that we adapted our protocol to include a highly optimized
Downloaded from http://biomedgerontology.oxfordjournals.org/ at Georgia Southwestern State University on June 2, 2015
Notes: All values except the change in VO2 outcome represent participant
characteristics at the onset of study participation.
HRT includes participant’s self-report of either opposed or unopposed
estrogen therapy, and participants included in the hypertensive category were
those who were diagnosed as hypertensive prior to their participation in the
study.
Standard errors are in parentheses.
MMSE ¼ Mini-Mental State Examination score; NS ¼ not significant;
HRT ¼ hormone replacement therapy.
1167
1168
COLCOMBE ET AL.
and robust longitudinal registration approach to perform the
initial coregistration between participants’ time 1 and time 2
images (17). The registration constrained spatial scaling by
the skull to minimize any potential differences in scanner
geometry or misregistration due to soft-tissue changes.
First, each participant’s images were skull-stripped and
segmented into 3D maps of gray matter, white matter, and
cerebrospinal fluid, using a semi-automated algorithm that
takes into account voxel intensity distributions as well as
hidden Markov random fields to estimate tissue volume at
each voxel (18). Then, the 3D maps of gray and white
matters for each participant were registered to a common
space (MNI) using a 12-parameter affine transformation.
These segmented images were then used as a priori
templates for a second-level segmentation. In addition,
a mean image was calculated from all participants, spatially
smoothed with a 12 mm full-width at half max kernel, and
subsequently used as a study-specific template. The use of
study-specific templates has been shown to reduce error
associated with misregistration and, therefore, to provide a
better estimate of brain volume differences between groups.
The second-level analysis then consisted of a resegmentation
based on the a priori gray and white matter maps from stage
1 and a realignment to the study-specific template image.
These images provide a voxel-by-voxel estimation of the
volume of gray matter, white matter, and cerebrospinal fluid
contained within the particular voxel. These images were
then multiplied by the Jacobian determinant for each
participant to preserve original volume and to control for
differences in the extent of registration and possible
interpolation error. Finally, the percent change in volume
was computed at each voxel for each participant. All of
these processes were conducted by an experimenter who
was blind to the group assignment of each individual.
The maps representing the percent volume change in gray
and white matter for each participant were then forwarded to
a group analysis, where we compared the changes in volume
for aerobic exercising and nonaerobic control older adults in
a set of unpaired t tests at each voxel. We initially subjected
the younger adult data to a simple t test against zero to
evaluate whether any changes occurred during the 6-month
period for younger adults. These analyses yielded three
statistical parametric maps for gray and white mater, which
described where (a) aerobic exercisers showed a greater
increase in volume than stretching and toning controls, (b)
nonaerobic controls showed a greater increase in volume
than aerobic exercisers, and (c) any change in volume,
positive or negative, was present in younger adults. We
performed a second set of analyses to examine whether the
results of our initial analysis interacted with the two
different MRI scanners used in the study. In none of the
regions presented in Figure 1 did the scanner used to collect
the MRI data interact with the effects of interest. The
resulting statistical parametric maps presented in Table 2
were statistically corrected for multiple comparisons at a
p , .05 level for each cluster (19).
RESULTS
Descriptive information on the participants is presented
in Table 1. Participant ages ranged from 60 to 79 years, with
a mean of 66.5 years. Overall, the sample was 55% female,
and tended to be well educated, with an average 13.8 years
of education. The estimated VO2 scores ranged from 12.6 to
Table 2. Cluster Size, Peak Location, and Statistical Value for
Each of the Four Regions Where Aerobically Exercising
Older Adults Showed a Significant Increase in Brain Volume
Region
Peak Z
Cluster Size
X (mm)
Y (mm)
Z (mm)
ACC/SMA
rIFG
lSTL
AWM
5.17
4.01
3.94
4.66
1459
604
308
1085
2
54
58
4
20
14
6
26
38
30
8
2
Note: ACC/SMA ¼ anterior cingulate cortex, supplementary motor cortex;
rIFG ¼ right inferior frontal gyrus; lSTL ¼ left superior temporal gyrus; AWM ¼
anterior white matter.
Downloaded from http://biomedgerontology.oxfordjournals.org/ at Georgia Southwestern State University on June 2, 2015
Figure 1. Regions showing a significant increase in volume for older adults who participated in an aerobic fitness training program, compared to nonaerobic
(stretching and toning) control older adults. A and B, Neurologically oriented axial slices through the brain, at þ2 and þ34 mm, respectively, in stereotaxic space. C,
Sagittal slice 2 mm to the right of the midline of the brain. Blue regions: Gray matter volume was increased for aerobic exercisers, relative to nonaerobic controls.
Yellow regions: White matter volume was increased for aerobic exercisers, relative to controls. (See also Table 2.)
FITNESS AND BRAIN HEALTH
DISCUSSION
In this study, we randomly assigned older adult participants to either an aerobic exercise group or a nonaerobic
exercise control group for 6 months and then examined
whether participation in an aerobic exercise regimen would
alter brain volume in an aged cohort. In short, we found that
participation in an aerobic exercise program increased
volume in both gray and white matter primarily located in
prefrontal and temporal cortices—those same regions that are
often reported to show substantial age-related deterioration.
The current findings are the first, to our knowledge, to
confirm benefits of exercise training on brain volume in aging
humans. These findings both compliment and extend extant
human and nonhuman research on the benefits of exercise on
cognition and brain structure such as neuron proliferation and
survival, growth of capillary beds, and increased dendritic
spines (5–13,25). These findings also highlight the potential
importance of aerobic exercise in not only staving off neural
decline in aging humans, but also suggest promise as an
effective mechanism to roll back some of the normal agerelated losses in brain structure (1,23).
These results also directly bear on issues of public policy
and clinical recommendations in that they suggest a rather
simple and inexpensive mechanism to ward off the effects of
senescence on human brain tissue. Most importantly, the
regions of cortex and white matter that show the greatest
sparing with aerobic fitness play central roles in successful
everyday functioning, and declines in these regions are
associated with a broad array of clinical syndromes. For
example, the prefrontal cortex has been associated with
critical cognitive processes ranging from inhibitory functioning (22) to measures of general intelligence (26). Losses
in this area have been associated with devastating clinical
syndromes such as schizophrenia. The temporal lobes are
associated with effective long-term memory function, and
losses in these areas of cortex have been associated with
Alzheimer’s dementia in aging populations. Importantly,
these are the same locations that we report brain volume
increases with exercise.
These findings, as provocative as they are promising,
must be viewed with some caution. For example, the older
adults in our sample were all very healthy and cognitively
intact. It is not clear whether similar benefits will accrue in
pathologically aging individuals. Furthermore, a detailed
neuropsychological battery was not collected on these
participants at each time point; therefore, we do not have
the data to assess how these volumetric changes relate to
changes in cognitive scores [but see Erickson and colleagues
(27) for a cross-sectional examination of the relationship of
fitness-related brain volume differences and cognition]. Our
relatively small sample size is also a limiting factor. Our
exclusionary criteria limit the interpretation of our results
to a select group of individuals. Additionally, data from
nonhuman models suggest that the changes in brain volume
seen in our study are likely due to changes in synaptic
interconnections, axonal integrity, and capillary bed growth,
but very little is known about the relationship between the
voxel-based morphometry methodology used in this study,
and the underlying cellular changes that might occur.
Downloaded from http://biomedgerontology.oxfordjournals.org/ at Georgia Southwestern State University on June 2, 2015
49.9. As shown in greater detail in Table 1, groups did not
differ at program onset with respect to average VO2 score,
age, sex, years of education, hormone replacement therapy
usage, hypertension, or Mini-Mental State Examination
score. However, after the intervention the aerobically exercising older adults showed a significant increase in VO2.
As predicted, no significant changes in either gray or
white matter volume were detected for our younger participants. However, when directly comparing the changes in
gray matter volume for older exercise and control participants, we found that the previously sedentary aerobic
exercising group showed a benefit in brain volume in several
regions after participation in an exercise training protocol.
The blue regions in Figure 1 show areas of gray matter in
which older adults who participated in the 6-month aerobic
exercise program showed a significant increase in regional
brain volume, compared to older adult controls. As might be
expected from the human behavioral research on aerobic
training effects on cognition (3,4), the largest changes in
volume were present in the frontal lobes of the brain, and
included regions of cortex that are implicated in a broad array
of higher order attentional control and memory processes
(20–22). The largest region subsumed portions of the dorsal
anterior cingulate cortex, supplementary motor area, and
middle frontal gyrus bilaterally within the medial walls of the
brain (ACC/SMA). The second region subsumed a moderately large portion of the dorsolateral region of the right
inferior frontal gyrus, but also part of the posterior aspect of
the middle frontal gyrus (rIFG), and a third region included
the dorsal aspect of the left superior temporal lobe (lSTL).
The yellow region in Figure 1 shows the area in which
aerobically exercising participants showed a significant
increase in white matter volume after the 6-month intervention, compared to control participants. This region was
in the anterior white matter tracts (AWM), subtending
roughly the anterior third of the corpus callosum. These
white matter tracts allow the left and right hemispheres of the
brain to communicate, and deterioration in these regions has
been implicated in age-related cognitive decline (23,24). See
Table 2 for peak locations, z scores, and cluster sizes.
Considering the detrimental impact of age-related brain
volume loss on a broad spectrum of outcomes, it would be
interesting to investigate the potential for fitness to reduce
the risk of brain tissue loss during the intervention. To
address this issue, we computed a binary outcome measure
of volume change, in which volume loss was coded as
a negative outcome. From this we computed, within each
cluster reported in Table 2, the relative reduction in risk for
brain volume loss associated with participation in the
aerobic fitness training protocol. Older adults who participated in the aerobic fitness training protocol showed
average reductions in risk, relative to participants in the
stretching and toning control group, for brain volume loss of
42.1%, 33.7%, 27.2%, and 27.3%, in the anterior cingulate
cortex (ACC/SMA), right superior temporal gyrus (rtSTG),
right middle frontal gyrus (rtMFG), and anterior white
matter (AWM) clusters, respectively. We should note that
our sample is somewhat smaller than the recommended
minimum for risk-reduction estimates, and as such, the risk
reduction estimates should be viewed with some caution.
1169
1170
COLCOMBE ET AL.
ACKNOWLEDGMENTS
We thank the National Institute on Aging (RO1 AG25667 and RO1
AG25032) and the Institute for the Study of Aging for supporting this
research.
Address correspondence to Arthur F. Kramer, PhD, Beckman Institute,
University of Illinois, 405 N. Mathews Ave., Urbana, IL 61801. E-mail:
akramer@s.psych.uiuc.edu
REFERENCES
1. Raz N. Aging of the brain and its impact on cognitive performance:
integration of structural and functional findings. In Craik F, Salthouse
T, eds. Handbook of Aging and Cognition. Hillsdale, NJ; Erlbaum:
2000;1–90.
2. Park DC, Polk T, Mikels JA, Taylor SF, Marshuetz C. Cerebral aging:
integration of brain and behavioral models of cognitive function.
Dialogues Clin Neurosci. 2001;3:151–164.
3. Colcombe S, Kramer AF. Fitness effects on the cognitive function of
older adults: a meta-analytic study. Psychol Sci. 2003;14:125–130.
4. Kramer AF, Hahn S, Cohen N, et al. Aging, fitness, and neurocognitive
function. Nature. 1999;400:418–419.
5. Black JE, Isaacs KR, Anderson BJ, Alcantara AA, Greenough WT.
Learning causes synaptogenesis, whereas motor activity causes angiogenesis in cerebellar cortex of adult rats. Proc Natl Acad Sci U S A.
1990;87:5568–5572.
6. Rhyu IJ, Boklewski J, Ferguson B, et al. Exercise training associated
with increased cortical vascularization in adult female cynomologus
monkeys. Abstr Soc Neurosci. 2003;920.
7. Cotman CW, Berchtold NC. Exercise: a behavioral intervention to
enhance brain health and plasticity. Trends Neurosci. 2002;25:
295–301.
8. van Praag H, Christie BR, Sejnowski TJ, Gage FH. Running enhances
neurogenesis, learning, and long-term potentiation in mice. Proc Natl
Acad Sci U S A. 1999;96:13427–13431.
9. Neeper S, Gomez-Pinilla F, Choi J, Cottman C. Exercise and brain
neurotrophins. Nature. 1995;373:109.
10. Carro E, Trejo LJ, Busiguina S, Torres-Aleman I. Circulating insulinlike growth factor 1 mediates the protective effects of physical exercise
against brain insults of different etiology and anatomy. J Neurosci.
2001;21:5678–5684.
11. Niblock MM, Brunso-Berchtold JK, Riddle DR. Insulin-like growth
factor I stimulates dendritic growth in primary somatosensory cortex.
J Neurosci. 2000;20:4165–4176.
12. Churchill JD, Galvez R, Colcombe S, Swain RA, Kramer AF,
Greenough WT. Exercise, experience and the aging brain. Neurobiol
Aging. 2002;23:941–955.
13. Anderson BJ, Rapp DN, Baek DH, McCloskey DP, Coburn-Litvak PS,
Robinson JK. Exercise influences spatial learning in the radial arm
maze. Physiol Behav. 2000;70:425–429.
14. Colcombe SJ, Erickson KI, Raz N, et al. Aerobic fitness reduces brain
tissue loss in aging humans. J Gerontol A Biol Sci Med Sci. 2003;
58A:176–180.
15. Karvonen M, Kentala K, Mustala O. The effects of training on heart
rate: a longitudinal study. Annales Medicinae Experimentalis et
Biologiae Fenniae. 1957;35:307–315.
16. Good CD, Johnsrude IS, Ashburner J, Henson RN, Friston KJ,
Frackowiak RSJ. A voxel-based morphometric study of ageing in 465
normal adult human brains. Neuroimage. 2001;14:21–36.
17. Smith SM, Zhang Y, Jenkinson M, et al. Accurate, robust, and
automated longitudinal and cross-sectional brain change analysis.
Neuroimage. 2002;17:479–489.
18. Zhang Y, Brady M, Smith S. Segmentation of brain MR images
through a hidden Markov random field model and the expectation
maximization algorithm. IEEE Trans Med Imag. 2001;20:45–57.
19. Friston KJ, Worsley KJ, Frakowiak RSJ, Mazziotta JC, Evans AC.
Assessing the significance of focal activations using their spatial extent.
Hum Brain Map. 1994;1:214–220.
20. Duncan J, Owen AM. Common regions of the human frontal lobe
recruited by diverse cognitive demands. Trends Neurosci. 2000;
23:475–483.
21. Gunning-Dixon FM, Raz N. Neuroanatomical correlates of selected
executive functions in middle-aged and older adults: a prospective
MRI study. Neuropsychologia. 2003;41:1929–1941.
22. West R. An application of prefrontal cortex function theory to cognitive
aging. Psychol Bull. 1995;120:272–292.
23. O’Sullivan M, Jones DK, Summers PE, Morris RG, Williams SCR,
Markus HS. Evidence for cortical ‘‘disconnection’’ as a mechanism of
age-related cognitive decline. Neurology. 2001;57:632–638.
24. Colcombe SJ, Kramer AF, Erickson KI, Scalf P. The implications of
cortical recruitment and brain morphology for individual differences
in cognitive performance in aging humans. Psychol Aging. 2005;20:
363–375.
25. Trejo JL, Carro E, Torres-Aleman I. Circulating insulin-like growth
factor mediates exercise-induced increases in the number of new
neurons in the adult hippocampus. J Neurosci. 2001;21:1628–1634.
26. Duncan J, Emslie H, Williams P, Johnson R, Freer C. Intelligence and
the frontal lobe: the organization of goal-directed behavior. Cognit
Psychol. 1996;30:257–270.
27. Erickson KI, Colcombe SJ, Elavsky S, et al. Interactive effects of
fitness and hormone treatment on brain health in elderly women.
Neurobiol Aging. In press.
Received July 8, 2006
Accepted September 21, 2006
Decision Editor: Luigi Ferrucci, MD, PhD
Downloaded from http://biomedgerontology.oxfordjournals.org/ at Georgia Southwestern State University on June 2, 2015
Conclusion
We report the novel and intriguing finding that only 6
months of regular aerobic exercise not only spares brain
volume but also increases brain volume in an aged cohort.
These effects cannot be driven by methodological limitations because neither of the control groups (the older
nonaerobic exercise participants or the younger control
group) showed significant changes in brain volume over 6
months. Our results suggest that brain volume loss is not an
inevitable effect of advancing age and that relatively minor
interventions can go a long way in offsetting and minimizing brain volume loss. Future studies should replicate
these effects using a larger sample size and a more extensive
neuropsychological battery to examine the relationship
between brain volume changes and cognitive changes.

Purchase answer to see full
attachment

  
error: Content is protected !!