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Introduction
t is well-documented by scientists and well-
recognized by the public that, as people age, they expe-
rience some diminishment of cognitive abilities. At some
point, for many older adults, the decline becomes suffi-
ciently serious that they are no longer able to live inde-
pendently and manage their lives. Of course, when indi-
viduals decline cognitively to the point of inability to
manage, they are experiencing significant neuropathol-
ogy in the form of some type of dementia or other neu-
rological disorder. The loss of the ability to live inde-
pendently is one of the greatest fears adults express
when considering old age.1Based on the public’s recog-
nition and fear of pathological age-related cognitive
decline, the issue of whether one can combat this decline
has become a highly salient issue. A casual perusal of
print, electronic, and broadcasting media would seem to
give reason for optimism. Pills and elixirs are guaranteed
to keep the brain healthy and sharp. Brain-training pro-
grams promise even more—these programs are pur-
ported to enhance and “rewire” the brain to make it bet-
ter than ever. There are popular books with amazing
titles that promise to reveal the simple secrets of improv-
Treatment research
I
The aging mind: neuroplasticity in response
to cognitive training
Denise C. Park, PhD; Gérard N. Bischof, DiplPsy
Keywords:
neuroplasticity; scaffolding; cognitive training; cognitive reserve;
engagement
Author affiliations: The Center for Vital Longevity, School of Brain and
Behavioral Sciences, University of Texas at Dallas, Texas, USA
Address for correspondence: Denise C. Park, PhD, Center for Vital Longevity,
1600 Viceroy Drive Suite 800, University of Texas at Dallas, Dallas, TX 75235,
USA
(e-mail: denise@utdallas.edu)
Is it possible to enhance neural and cognitive function with
cognitive training techniques? Can we delay age-related
decline in cognitive function with interventions and stave
off Alzheimer’s disease? Does an aged brain really have the
capacity to change in response to stimulation? In the pre-
sent paper, we consider the neuroplasticity of the aging
brain, that is, the brain’s ability to increase capacity in
response to sustained experience. We argue that, although
there is some neural deterioration that occurs with age,
the brain has the capacity to increase neural activity and
develop neural scaffolding to regulate cognitive function.
We suggest that increase in neural volume in response to
cognitive training or experience is a clear indicator of
change, but that changes in activation in response to cog-
nitive training may be evidence of strategy change rather
than indicative of neural plasticity. We note that the effect
of cognitive training is surprisingly durable over time, but
that the evidence that training effects transfer to other
cognitive domains is relatively limited. We review evidence
which suggests that engagement in an environment that
requires sustained cognitive effort may facilitate cognitive
function.
© 2013, LLS SAS
Dialogues Clin Neurosci.
2013;15:109-119.
109
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Treatment research
ing the mind and preventing dementias, including
Alzheimer’s disease. Nearly all of these claims are, at
best, overly optimistic, and, at worst, blatant charla-
tanism. Nevertheless, the public’s keen interest in this
topic is matched by that of scientists, who have become
deeply engaged in understanding how to improve the
aging mind, or at least prevent its decline into demen-
tia.2,3 In order to improve cognitive function, the aging
brain must have plasticity—that is, the ability to change
structure or function in a sustained manner in response
to some type of external stimulation. In the present
paper, we will consider what we mean by plasticity, and
whether behavioral interventions designed to improve
function of the aging brain have been successful.
Most studies that have conducted interventions on older
adults have focused on training some type of cognitive
skill through practice, and, at the end of a training
period, measuring improvement. The improvement is
typically behavioral (eg, improved working memory
capacity4-6) but there are some studies that focus on actu-
ally changing neural activity or increasing neural tissue
with training.5,7 Most studies also consider whether the
observed improvement “transfers” to other tasks.5,8
Finally, some studies consider how long adults are able
to maintain the trained improvement over time. In this
paper, we will first discuss some basic issues associated
with the topic of neuroplasticity in older adulthood, and
what must be considered when evaluating the likelihood
that a training intervention is actually helpful. Then we
will review studies that have shown some evidence for
improving both cognitive function and provide evidence
for the neural substrate underlying the improvement. We
will finally consider the impact of lifestyle factors (exer-
cise and/or engagement) in maintaining and facilitating
cognitive function in older adults. Finally, we will close
with recommendations for future research.
Improving function versus minimizing loss
One issue that we feel does not get enough attention is
the role that cognitive training and interventions play
over the short and long term. Most studies are focused
on showing an improvement in cognitive function imme-
diately or a few weeks after training, relative to some
appropriate control group. However, it is important to
recognize that the normal course of aging is one of
decline in many core cognitive abilities (commonly
referred to as fluid intelligence), including speed of pro-
cessing, working memory, long-term memory, and rea-
soning.9Figure 1 presents evidence that all of these core
abilities show age-related decline, even in a highly edu-
cated lifespan sample, while knowledge (crystallized
intelligence) remains invariant, or even increases with
age. Given the data presented in Figure 1, we suggest
that the focus of cognitive training and other interven-
tions should be on slowing cognitive aging. The
Alzheimer’s Association estimates that if the onset of
Alzheimer’s disease could be delayed by 5 years due to
successful interventions, this would result in a 50%
decrease in Alzheimer’s diagnoses.10 Moreover, many
older adults are interested in staying in the work force
past traditional retirement age. Participation in the work
force for most adults would require that they maintain
cognitive ability. Thus, slowing decline for this group
could be very meaningful, as it would allow them to con-
tinue to work. There are few studies that have examined
the effects of interventions over a period of years.
Nevertheless, the ability to find effective techniques that
will slow the process of aging is almost certainly more
important than the demonstration of short-term
improvements in cognitive function. Slowing decline of
the aging mind is both an economic and quality of life
issue that is central to controlling spiraling health costs
as well as providing for the emotional well-being of both
older adults and their families.
How can the brain protect itself from decline?
The concept of some type of neural or cognitive pool of
resources that protects against age-related cognitive
decline has been an important idea in both the cognitive
and neural aging literature. The basic notion emerged
from evidence that there are substantial individual dif-
ferences in the rate that people evidence cognitive aging,
and there must be some mechanism that accounts for
these differences. To address this issue, Baltes and
Baltes11 proposed the construct of “reserve capacity,”
suggesting that older adults were able to maintain cog-
nitive function by drawing on a pool of resources that
mitigated aging effects. Interestingly, the earliest neu-
roimaging research on older adults provided clear evi-
dence that older adults showed increased contralateral
hemispheric recruitment in right frontal regions for both
working memory12 and episodic encoding,13 supporting
the notion of compensation and neural reserve. This
increased bilateral recruitment in frontal cortex that
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occurred across multiple cognitive tasks was interpreted
to indicate that the enhanced neural activity of old
adults operated to maintain cognitive function.
The scaffolding theory of aging and cognition (STAC)14
provides a theoretical model for the causes and conse-
quences of age-related compensatory neural activity.
STAC posits that cognitive function in older adults can
be understood in terms of the magnitude of neural
insults that the brain has sustained (both structural and
functional) as well as the compensatory neural activities
(“scaffolding”) that operate to maintain cognitive
behavior. According to this model, scaffolding is con-
ceptualized as the recruitment of additional circuitry
that shores up declining brain function that has become
noisy, inefficient, or both. The pervasive finding of
increased prefrontal activation in older adults across
many different cognitive tasks reflects the engagement
of compensatory scaffolding. The scaffolding is a direct
response to the neural insults of aging which include vol-
umetric shrinkage of brain structures,15 white matter
degradation,16 and amyloid deposition,17 as well as func-
tional decline in neural activities associated with dedif-
ferentiation of ventral visual cortex,18,19 poor modulation
of default network activity,20 and declining activity in the
hippocampus.21,22 Effective compensatory activation in
response to this degradation mitigates age-related
decline in cognition. Importantly, STAC also provides for
the possibility that cognitive training or sustained
engagement in a novel task or environment, as well as
exercise, can enhance the development of compensatory
scaffolding, so that the ability to increase scaffolding as
a result of cognitive training confers protection on cog-
nitive function.
A related view that has emerged from the imaging liter-
ature is that of cognitive reserve.23 The cognitive reserve
model suggests that there are specific experiences and
behaviors that confer protection from age-related
decline. Examples of behaviors that may create reserve
111
Cognitive training and neuroplasticity - Park and Bischof Dialogues in Clinical Neuroscience - Vol 15 .No. 1 .2013
Figure 1. Cross-sectional aging data adapted from ref 9 showing behavioral performance on measures of speed of processing (ie, Digit Symbol,
Letter Comparison, Pattern Comparison), working memory (ie, Letter rotation, Line span, Computation Span, Reading Span), Long-Term
Memory (ie, Benton, Rey, Cued Recall, Free Recall), and world knowledge (ie, Shipley Vocabulary, Antonym Vocabulary, Synonym
Vocabulary). Almost all measures of cognitive function (fluid intelligence) show decline with age, except world knowledge (crystallized
intelligence), which may even show some improvement.
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Treatment research
include education, high literacy, engaging work, and
maintenance of an active, engaged lifestyle in late adult-
hood.24,25 All of these experiences appear to delay pro-
gression towards Alzheimer’s disease, although, without
experimental studies, the causal component is unclear
(eg, do people high in reserve stay in the workforce or
does workforce participation create reserve?). Stern26
distinguishes between neural reserve and neural com-
pensation. Reserve is essentially an increased supply of
neural resources created as a result of experiences,
whereas neural compensation is the ability to draw more
effectively and efficiently on networks.
Can the brain actually improve
as a result of experience?
Although the findings in the literature are sparse, there
is a range of evidence suggesting that the older brain has
considerable plasticity. Probably the most compelling
data comes from stroke patients who have sustained per-
manent damage to their brain in specific areas as a result
of neural bleed or blood clot. Despite very significant
damage that has led to loss of behavioral function,
stroke patients show dramatic recovery with sustained
therapy.27 This change in function can only be due to
plastic changes in brain function, where new parts of the
brain take over functions performed by areas that have
been damaged. The plasticity evidenced in stroke
patients is quite amazing, and indicates that the aging
brain is very capable of neural reorganization. One
important thing to note about stroke patients are that
they undergo many hours of intense therapy to regain
function, and that this training is in domains that greatly
facilitate function in everyday life. Thus, the environment
maintains and supports gains in improvement after
stroke, as patients must have communication and mobil-
ity skills if they are to maintain independence in every-
day life. It is also important to recognize that a part of
the stroke patient’s brain has literally shut down, and
this extreme condition forces the brain to manifest any
plasticity that is available to restore function, when it
may not do so under normal conditions.
Healthy adults, on the other hand, may not have the abil-
ity to consciously draw upon unused parts of the brain
to enhance cognitive function. Much remains to be
understood as to how much cognitive training or other
cognitive interventions can enhance function, but it does
seem clear, based on stroke patients, as well as data from
animal studies,28 that the potential of brain reorganiza-
tion does occur even in late adulthood. Nevertheless, the
conditions under which healthy older brains reorganize
in an adaptive matter to enhance cognitive function are
poorly understood.
In line with the notion that contextual press or demand
is an important element of accessing and utilizing any
neural plasticity that exists in the aging brain, is the con-
cept of a sustained mismatch between a person’s desired
cognitive state or goal and the demands of the environ-
ment.29 It is only when an individual experiences sub-
stantial and sustained demands on their cognitive system
that plasticity will manifest itself. An older adult who, for
example, must learn a demanding new route to visit his
or her grandchildren in a new city might need to draw
maximally upon attentional, task-switching, and work-
ing memory resources to complete this demanding drive
on a complex highway system in traffic. This initial task
requires flexibility; that is, deployment of the existing
supply of resources to perform the novel task at hand.
Plasticity would be manifested if this trip was successful,
and the older adult began driving to many new places
and ultimately developed significantly enhanced driving
skills over a sustained period. This sustained novel activ-
ity might result in neural reorganization or even growth
of neural structures associated with way-finding (much
like the famed London cab driver study30), in which case
plasticity would be manifested. Finally, we note that
many of the cognitive demands associated with a
demanding new drive could be diminished by using a
navigational system, in which case, neither flexibility nor
plasticity would be required, as the environmental sup-
port provided by the navigational system would result in
a match between existing abilities and task demands. In
a similar vein, Park et al31 suggest that cognitive change
can only occur when a task or environment consistently
makes demands on core cognitive processes like speed,
working memory, episodic memory, and reasoning.
Finally, it is important to recognize that there can be sub-
stantial individual differences in what comprises a
demanding task or a challenging environment, and Park
et al31 explicitly note the importance of novelty in effect-
ing change. An older adult who was an accountant might
not find it very demanding to learn how to manage a
stock portfolio, but would be very challenged by learn-
ing to play a musical instrument. Past experiences, exper-
tise, and cognitive status will all play important roles in
understanding tasks that provide optimal challenge to
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Cognitive training and neuroplasticity - Park and Bischof Dialogues in Clinical Neuroscience - Vol 15 .No. 1 .2013
an individual and have the potential to effect change in
neural structure or function.
What constitutes change?
Increases in neural volume
There is tremendous debate about what constitutes evi-
dence for neural plasticity. Perhaps the most unambigu-
ous evidence is when training increases the thickness or
volume of neural structure. It has been demonstrated
that sedentary older adults who engage in aerobic exer-
cise can delay shrinkage in prefrontal cortex, an area
maximally sensitive to age-related volumetric shrink-
age.32 In terms of cognitive interventions, actual gains in
neural volume relative to a control group were demon-
strated by Boyke et al33 in the mid temporal regions, hip-
pocampus and nucleus accumbens, when older adults
were trained to juggle for 90 days. These regions are
associated with complex motor behaviors, so this finding
was an important demonstration of plasticity in older
adults. Importantly, however, the gains were not main-
tained after a 90-day period of non-juggling, providing
important evidence that there are many constraints on
plasticity, and that the familiar “use or lose it” adage was
disappointingly relevant in this particular study. Other
evidence shows that older men who played a demand-
ing spatial navigational game every other day for 4
months exhibited stability of hippocampal volume over
a 4-month period, whereas control subjects declined.34
Additionally, these trained subjects showed an increase
in structural integrity of the hippocampus which was
maintained when training ceased. Overall, however, the
evidence that one can improve volume of neural struc-
tures through training is relatively sparse. The limited
data available suggest that gains that are realized from
a sustained training program most likely need to be
maintained with continued performance. An important
question is whether continuous improvement and chal-
lenge on a task is required to maintain gains, or whether
mere maintenance of a high level of improved but
asymptotic performance would be sufficient to preserve
gains. It seems likely that it will be important for indi-
viduals to enjoy the tasks they are performing over the
very long term so that the behavior can be sustained and
gains maintained. This may be the greatest challenge
associated with training the aging human brain. From a
clinical perspective, daily “brain training” could become
a boring and effortful task, such that gains realized might
be offset by the negative consequences of performing a
task that over time could become a dreaded obligation
rather than a pleasurable and stimulating activity.
Changes in neural activity
A more common finding than volumetric increase is a
change in neural activity with training. The change can
be in the form of activation of new regions, or decreases
or increases in neural activity in task related structures
that were activated before the training. The neural dif-
ferences between pretest and post-test can be quite hard
to interpret, and may or may not reflect a fundamental
change in brain function or organization. Noack et al35
argue that many changes in activation as a result of
training reflect flexibility in deployment of resources due
to strategy change rather than a manifestation of plas-
ticity resulting in an increase in intrinsic neural or cog-
nitive capacity. They argue that the rich knowledge base
that accrues as we age provides an excellent mechanism
for utilizing wisdom and knowledge to facilitate perfor-
mance, rather than a true change in the neurocognitive
system. They suggest that younger adults have more
neural plasticity than old, and that the young are most
likely to show an increase in intrinsic neural capacity
with training, whereas the old are more likely to recog-
nize gains due to flexibility in strategy use.
The expectation behind training is that it will improve
cognitive capacity and thus increase neural efficiency by
decreasing the demands a task makes on the neural sys-
tem. If this is the case, one might expect that training
would decrease neural activation on the trained task.
Such a finding was reported by Brehmer et al.36 They
trained older adults on a working memory task for 5
weeks and found that subjects who trained on the most
demanding tasks (adaptive training) showed a decrease
in activation in frontal, parietal, and occipital regions,
which the authors suggested reflected improved neural
efficiency and decreased resource utilization as a result
of training.
On the other hand, there is a considerable body of liter-
ature suggesting that enhanced neural activity is facili-
tative for old adults, so it is also easy to imagine findings
where training enhances neural activation and behav-
ioral function in older adults. In line with this hypothe-
sis, Nyberg et al7reported that mnemonic training in
older adults resulted in an increase in activations in
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114
occipito-parietal regions, but only for those who showed
a training-related behavioral improvement. Young adults
showed improvement in these regions as well, but also
evidenced increases in frontal regions. Similarly, Carlson
et al37 reported that older adults who were highly
engaged in the Experience Corps intervention (a pro-
gram where older adults engage in support and literacy
activities for elementary teachers) showed an increase
in prefrontal activity as well as an increase in executive
function. Using a different approach, Mozolic et al38
examined changes in cerebral blood flow as a result of
training. They reported that 6 weeks of attentional train-
ing in older adults resulted in an increase in cerebral
blood flow to the prefrontal cortex during rest, com-
bined with a decrease in distractibility.
The neurological literature on cognitive training is at an
early stage, and results are varied and actually quite lim-
ited. It is difficult to predict whether training will
increase or decrease neural activity, and how it might
interact with age, as well as how durable effects are over
time. It also is surprisingly difficult to assess whether any
observed brain changes reflect a fundamental increase
in neural capacity or merely a change in strategy. Lövdén
et al39 suggest that specific strategy instructions operate
to reduce performance differences between subjects
because, in a sense, such instructions level the playing
field so that old and young participants are more likely
to use similar and optimal strategies. At the same time,
Lövdén et al39 observed that sustained cognitive training
that followed the strategy instructions operated to mag-
nify differences between individuals, because there was
considerable heterogeneity in the ability of participants
to profit from the training—that is, there were significant
plasticity differences between subjects. These joint
manipulations of instruction and training provided an
elegant demonstration of how one might begin to sep-
arate strategy effects from changes in actual neural
capacity.
This brief discussion of the relationship between train-
ing effects and neural change highlights the complexity
of the issues associated with training and neural func-
tion. Given the plethora of possibilities in findings, as
well as the interpretations of those findings, associated
with training, it would be wise for training studies that
utilize neural measures to use training tasks that have
been highly researched so that neural circuitry engaged
by old and young is well understood. Moreover, a focus
on studies with large participant pools, inclusion of a
group that could replicate previous findings, and inclu-
sion of long-term follow-up intervals will all enhance the
quality of work and our understanding of the relation-
ship among training, neural function, and behavioral
improvement.
Near versus far transfer
One important aspect of training studies is whether the
training results in broad changes in processing abilities
that transfer to other unrelated tasks (so-called “far
transfer”) or whether it is only the trained ability that
improves.40,41 This is in fact an age-old issue in the cogni-
tive aging literature, dating back to early work done by
Willis et al41 on the Seattle Longitudinal Study of Aging.
It is clear from a raft of studies that older adults improve
significantly on a trained task42 and that the training
improvements in some cases are manifested for pro-
longed periods of time, even years later.43 Despite these
encouraging findings, there is relatively little evidence
that training induces a fundamental change in processes
that transfer to everyday life. We do note that Willis et
al43 reported that participants who were trained in rea-
soning in the ACTIVE trial42 reported less difficulty in
instrumental activities of daily living 5 years later,43 a
finding which is indicative of both far transfer and
improvement in everyday function, but this is an uncom-
mon finding. Furthermore, in the same study, training in
speed of processing and episodic memory did not yield
significant improvements, and thus the mediating mech-
anism for the improvement in daily activities resulting
from reasoning training is not clear. Nevertheless, the
results are encouraging.
The concept of far transfer as a result of “brain training”
is highly appealing and is absolutely fundamental to
claims that for-profit enterprises make about their
neural facilitation products. The basic premise of these
products is that their use (that typically involves
extended training on tasks that train core cognitive
processes) will literally make a person smarter and that
the training will lead to broad improvement in many
mental activities. Until recently, there was not strong evi-
dence that this far transfer occurred, typically because
appropriate control groups were not employed, or claims
by purveyors of products were not rigorously evaluated.
Recent work on working memory training, however, has
yielded provocative evidence for far transfer from train-
ing on a working memory task to improvement in gen-
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115
eral intelligence.8Findings indicate that young adults
who are consistently challenged to increase their work-
ing memory span in an n-back paradigm are able to do
so with training. More importantly, those participants
who improve on the n-back training task show a signifi-
cant increase in general measures of fluid intelligence.
Thus far, the effects have been limited to young adults
and, more recently, to children who showed an improve-
ment in working memory from the original training.44
The only neural study of “far transfer” of which we are
aware was conducted by Dahlin et al.45 In this study, the
researchers trained young and old on an updating task,
a critical component of working memory function
involving the ability to rapidly delete irrelevant infor-
mation and integrate relevant information in working
memory. When subjects were tested on a 3-back task, a
related but different working memory task, they found
young but not old showed transfer. Importantly, when
the neural underpinnings of this effect were investigated,
Dahlin et al5reported that the trained updating task
improved striatal function in young and that the striatal
activation was shared by the 3-back transfer task.
Importantly, older adults did not show striatal activity
during training or during the transfer task. Thus, it
appeared that striatal function was trained in young
adults and the training transferred to other striatum-
based tasks. This important result suggests that a neural
process, rather than a task, was trained and that this is an
effective mechanism for future training.1We note as well
that whether the transfer was “far” is arguable. Both
trained and transfer task relied on the same neural cir-
cuitry and, although the tasks were different, both were
tasks that tapped into working memory. Finally, the fact
that the training was unsuccessful in older adults is a
caveat regarding the difficulties that will be encountered
in neural training in later adulthood. There is at present
little evidence that cognitive training on a task will
improve general cognitive ability in old adults, despite a
plethora of claims in the media. Nevertheless, extant
data for young suggest that it is not implausible that such
findings could emerge as we learn more about the basis
for transfer effects.
Maintenance of gains
There are a range of studies that have demonstrated that
cognitive training in older adults has resulted in gains
over time for periods ranging from 3 months to 5 years.
Mahncke et al46 trained participants extensively (1 hour
per day for 8 to 10 weeks) on a series of computerized
tasks designed to improve representational fidelity of
language systems. Following training, subjects received
a battery of neuropsychological tests and there was evi-
dence that, despite no training specifically on memory,
the training improved verbal memory on the Repeatable
Battery for the Assessment of Neuropsychological
Status (RBANS).47 Three months later, the participants
showed an improvement in digit span forward scores rel-
ative to controls. These findings are interesting and pro-
vide some evidence for far transfer. It is unfortunate that
the design of the study did not permit a second test of
memory improvement at 3 months, and that a number
of participants were initially at ceiling performance on
the memory task, possibly limiting the impact of the
intervention. A critical design feature of intervention
studies is that the training and transfer tasks have suffi-
cient range to accommodate the scores of both young
and older adults. The tasks must have sufficient difficulty
to challenge adults and avoid ceiling effects, but not be
so difficult that floor is observed in the frailest adults or
months after task performance. In a related study,
Zelinski et al48 reported on a much larger sample (n
=487) of older adults who received auditory language
training similar to that of Mahncke et al46 or participated
in control conditions. At 3-month follow-up after the lan-
guage training, there was a significant improvement in
tasks that were directly trained as well as in a memory
composite score, but not in the RBANS memory task, as
reported earlier by Mahncke et al.46 Overall, the results
do provide some evidence for far transfer from auditory
language training to a memory task as a result of train-
ing, but the findings are somewhat inconsistent across
studies. As the authors note, it is both desirable and
important to show some improvement in functional out-
comes, and over longer periods of time. We also note
that the Dahlin et al45 study discussed earlier reported
that, although old adults did not show cognitive or
neural facilitation on a transfer task after updating train-
ing, both young and old showed gains on the trained
updating task. Of particular interest was the finding that
older adults, when tested 18 months later, maintained
gains that they demonstrated on the originally trained
updating task.
Overall, there is a growing body of evidence suggesting
that training gains can be maintained for long periods on
the originally trained task, but that transfer effects are
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not easily demonstrated, particularly in older adults.
Given these findings, perhaps the focus of training stud-
ies should be mainly on training skills and abilities that
have pragmatic value and would be useful in everyday
life. Cognitive training is time-consuming for the partic-
ipant. If the primary gain to the trainee is that he or she
becomes more efficient at the training task for a pro-
longed interval, the gain to the participant is slight. With
more practical tasks, the time investments of both par-
ticipants and staff are likely to lead to gains for the par-
ticipant in their everyday life, even if they do not realize
far transfer.
Engagement as a cognitive intervention
There are a number of studies that suggest that older
adults who maintain an active lifestyle or who engage in
a range of intellectual pursuits are diagnosed at later
ages with Alzheimer’s disease.49 In fact, there is com-
pelling evidence that a high level of education confers
protection against neurocognitive aging and decline26
and is a type of cognitive reserve. The problem with
these large epidemiological studies is that the data are
primarily correlational, and it is not entirely clear if
maintaining an active mind and lifestyle offers protec-
tion against cognitive aging, or whether those who are
protected tend to maintain an active lifestyle.
Nevertheless, the notion that staying mentally active
confers protection against cognitive decline is pervasive
and best represented by the frequently invoked adage
of “use it or lose it.” It is surprising that there is relatively
little research that provides a careful test of this state-
ment, and that is largely because it is quite difficult to
study experimentally the effects of an engaged lifestyle.
There are a few studies that have addressed this issue
and all have shown positive but relatively limited effects.
The Experience Corps Project37 examined the cognitive
benefits of older adults working with teachers in pro-
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116
Figure 2. A conceptual model of the scaffolding theory of aging and cognition (STAC).
• Amyloid
• Shrinkage
• White matter changes
• Cortical thinning
• Dopamine depletion
• Dedifferentiation of
ventral visual area
• Decreased medial
temporal recruitment
• Increased default
activity
• New learning
• Engagement
• Exercise
• Cognitive training
• Frontal recruitment
• Neurogenesis
• Distributed processing
• Bilaterality
Neural
challenges
Aging
Functional
deterioration
Compensatory
scaffolding
Level of
cognitive
function
Scaffolding
enhancement
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grams to train literacy and provide educational assis-
tance to young children. The program has shown that
participation yielded cognitive, social, and health bene-
fits to older adults, while at the same time giving back to
the community.50 In addition, there is some evidence that
participation increased neural activation in prefrontal
cortex along with behavioral performance on executive
function tasks. Another project that examines the role of
sustained engagement on cognition is the Odyssey of the
Mind Project.51 In this study, participants regularly par-
ticipated in group problem-solving activities for several
months with a culminating event that required elaborate
team-based performance to present solutions to com-
plex, ill-defined problems. In an initial study, Odyssey
participants realized gains in fluid ability from pretest to
post-test,53 and, in a later study, showed an enhancement
in the personality trait of openness to experience.54 In
recent work in our own laboratory, the Synapse project55
required that older adults participate in a demanding
new learning task 15 hours a week for 3 months.
Participants were immersed in what Park et al31
described as “productive engagement”—new learning
that requires consistent engagement of working mem-
ory, motor skills, reasoning, and social challenge.
Participants in productive engagement conditions
learned quilting, digital photography, or both. Other par-
ticipants were randomly assigned to “receptive engage-
ment” conditions—situations that involved stimulating
social activities or use of existing knowledge but rela-
tively little new learning. Results indicated that partici-
pants in the productive but not receptive engagement
conditions showed improved episodic memory perfor-
mance, a finding similar to the results from the
Experience Corps Project.37 Although much more exper-
imental work is needed on the issue of engagement,
there is a small but promising body of literature which
suggests that modest amount of cognitive gains can be
realized by engagement in tasks that demand sustained
cognitive effort. The engagement issue is an important
one because engaging activities are intrinsically satisfy-
ing and can be sustained indefinitely with considerable
pleasure. Unlike cognitive training that relies on com-
puter training and may deprive individuals of social
engagement and pursuit of satisfying activities, immer-
sion in a social learning environment has the potential
to confer cognitive protection while meeting basic psy-
chological needs for social interactions and purpose in
life.
Summary and conclusions
There is some evidence that the aging brain is malleable
and that cognitive function can be facilitated through cog-
nitive training or engagement in demanding tasks that pro-
vide a sustained cognitive challenge. Unfortunately, the
most durable effects observed in old adults are gains on
the trained task, with only limited evidence that “far trans-
fer” (ie, improvement on an array of tasks that share sim-
ilarity in processes but not content to the trained task) is
possible. Nevertheless, the persistence of training effects
over a period of years is both impressive and somewhat
unexpected. Despite remarkable tools to examine neural
structure and function in the aging brain, a great deal of
work needs to be done to understand whether changes in
neural function are indicative of neural plasticity or merely
represent shifts in strategy. Evidence suggests that older
adults show less neuroplasticity than younger subjects, and
we argue that interventions that successfully delay age-
related cognitive decline will yield greater benefits than
short-term facilitation of cognition. An important aspect
of cognitive enhancement techniques that is not consid-
ered sufficiently is how enjoyable the activities to be per-
formed are. We argue that engagement in challenging
leisure activities that activate core cognitive processes such
as working memory, episodic memory, and reasoning may
ultimately prove to be more effective than computer-based
training techniques due to the ability to of older adults to
sustain interesting leisure activities indefinitely. One of the
greatest research challenges facing this domain of research
is to demonstrate that cognitive training results in mean-
ingful gains in everyday life or delays onset of Alzheimer’s
disease or other neurological disorders. Another area of
particular importance is understanding the meaning of
neural change and what type of neural change represents
enhancement (eg, decreased activity could represent
enhanced neural efficiency or insufficient neural engage-
ment). The field would greatly profit from evidence for
replicability of important findings. Claims that older adults
can greatly improve their intellectual capacity or prevent
Alzheimer’s disease through “brain training” appear, at
this time, to be overstated. Nevertheless, there is sufficient
promise in results that continued investigation and the
hope for a clearer understanding of mechanisms underly-
ing observed effects is warranted. ❏
Acknowledgments: This work was supported by the National Institute
on Aging at the National Institutes of Health (5R37AG-006265-25 and
(NIA grant 5R01AG026589-05).
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117
13_AG_1004_BA_INTERIEUR.qxd:DCNS#55 1/03/13 17:13 Page 117
Treatment research
118
El envejecimiento de la mente:
la neuroplasticidad en respuesta al
entrenamiento cognitivo
¿Es posible mejorar la función neuronal y cognitiva
con las técnicas de entrenamiento cognitivo?
¿Podemos retrasar con intervenciones la disminu-
ción de la función cognitiva relacionada con la edad
y evitar la Enfermedad de Alzheimer? ¿Tiene real-
mente un cerebro envejecido la capacidad de cam-
biar en respuesta a la estimulación? En este artículo
se revisa la neuroplasticidad del cerebro que enve-
jece, es decir, la posibilidad de este órgano de
aumentar su capacidad en respuesta a la experien-
cia mantenida. Se argumenta que, aunque existe
un cierto deterioro neuronal que ocurre con la
edad, el cerebro tiene la capacidad de aumentar la
actividad neuronal y desarrollar una estructura neu-
ronal para regular la función cognitiva. Se sugiere
que los aumentos del volumen neuronal en res-
puesta al entrenamiento o la experiencia cognitiva
constituyen un claro indicador de cambio, pero que
los cambios en la activación en respuesta al entre-
namiento cognitivo pueden ser una evidencia de
cambio de estrategia más que un indicador de plas-
ticidad neuronal. Se menciona que el efecto del
entrenamiento cognitivo sorprendentemente per-
dura a lo largo del tiempo, pero es relativamente
limitada la evidencia que existe respecto a que los
efectos del entrenamiento se puedan trasladar a
otros dominios cognitivos. Se revisa la evidencia que
sugiere que la participación en un ambiente que
requiere de un esfuerzo cognitivo sostenido puede
facilitar el funcionamiento cognitivo.
L’intellect du sujet âgé :
la neuroplasticité en réponse à
l’entraînement cognitif
Les techniques d’entraînement cognitif peuvent-
elles améliorer les fonction neurales et cognitives ?
Pouvons-nous retarder le déclin des fonctions
cognitives lié à l’âge et éviter la maladie
d’Alzheimer ? Un cerveau âgé peut-il vraiment
changer en réponse à une stimulation ? Nous étu-
dions dans cet article la neuroplasticité du cerveau
vieillissant, c’est-à-dire le potentiel du cerveau
d'augmenter sa capacité de réponse à une expé-
rience prolongée. Nous pensons que le cerveau, en
dépit d’une certaine détérioration liée à l’âge, peut
augmenter son activité neurale et développer un
échafaudage neural pour réguler la fonction cogni-
tive. L’augmentation du volume neural en réponse
à l’expérience ou à l’entraînement cognitif nous
semble être un bon indicateur de modification ;
cependant, les changements dans l’activation de la
réponse à l’entraînement cognitif seraient plus une
preuve de changement de stratégie qu’un indica-
teur de plasticité neurale. Nous observons que l’ef-
fet de l’entraînement cognitif est, de façon sur-
prenante, durable dans le temps, mais que les
arguments en faveur du transfert de ces effets sur
d’autres domaines cognitifs sont assez limités. Nous
passons en revue les preuves suggérant qu’une
implication dans un environnement demandant un
effort cognitif prolongé pourrait faciliter la fonc-
tion cognitive.
REFERENCES
1. Lustig C, Shah P, Seidle R, Reuter-Lorenz, P. Aging, training, and the
brain and future directions. Neuropsychol Rev. 2009;19:504-522.
2. Park DC, Bischof, GN. Neuroplasticity, aging, and cognitive function. In:
Schaie KW, Willis SL, eds. Handbook of the Psychology of Aging. San Diego,
CA: Academic Press; 2011:109-117.
3. Clarity Web site. Aging in place in America. Available at: http://www.clar-
ityproducts.com/. Published August 20, 2007. Accessed December 3, 2008.
4. Buschkuehl M, Jaeggi SM, Hutchison S, et al. Impact of working mem-
ory training on memory performance in old-old adults. Psychol Aging.
2008;23:743-753.
5. Dahlin E, Neely AS, Larsson A, Bäckman L, Nyberg L. Transfer of learn-
ing after updating training mediated by the striatum. Science.
2008;320:1510-1512.
6. Li SC, Schmiedek F, Huxhold O, Röcke C, Smith J, Lindenberger U.
Working memory plasticity in old age: transfer and maintenance. Psychol
Aging. 2008;23:731-742.
7. Nyberg L, Sandblom J, Jones S, et al. Neural correlates of training-
related memory improvement in adulthood and aging. Proc Natl Acad Sci.
2003;100:13728-13733.
8. Jaeggi SM, Buschkuehl M, Jonides J, Perrig WJ. Improving fluid intelligence
with training on working memory. Proc Natl Acad Sci. 2008;105:6829–6833.
9. Park DC, Lautenschlager G, Hedden T, Davidson NS, Smith AD, Smith
PK. Models of visuospatial and verbal memory across the adult life span.
Psychol Aging. 2002;17:299-320.
10. Alzheimer’s Association Web site. Available at:
http://www.alz.org/alzheimers_disease_trajectory. Published May 2010.
Accessed November 25, 2012.
11. Baltes P, Baltes M. Psychological perspectives on successful aging: The
model of selective optimization with compensation. In: Baltes P, Baltes M.
Successful Aging: Perspectives from the Behavioral Sciences. Cambridge, UK: Press
Syndicate of the University of Cambridge;1990:1-35.
12. Reuter-Lorenz PA, Jonides J, Smith EE, et al. Age differences in the
frontal lateralization of verbal and spatial working memory revealed by
PET. J Cogn Neurosci. 2000;12:174-187.
13_AG_1004_BA_INTERIEUR.qxd:DCNS#55 1/03/13 17:13 Page 118
Cognitive training and neuroplasticity - Park and Bischof Dialogues in Clinical Neuroscience - Vol 15 .No. 1 .2013
119
13. Cabeza R, Anderson ND, Locantore JK, McIntosh AR. Aging gracefully:
compensatory brain activity in high-performing older adults. NeuroImage.
2002;17:1394–1402.
14. Park DC, Reuter-Lorenz PA. The adaptive brain: aging and neurocog-
nitive scaffolding. Annu Rev Psychol. 2009;2:173–196.
15. Raz N, Lindenberger U, Rodrigue KM, et al. Regional brain changes in
aging healthy adults: General trends, individual differences and modifiers.
Cereb Cortex. 2005;15:1679–1689.
16. Raz N, Rodrigue KM. Differential aging of the brain: patterns, cogni-
tive correlates and modifiers. Neurosci Biobehav Rev. 2006;30:730-748.
17. Rodrigue KM, Kennedy KM, Devous MD Sr, et al. β-Amyloid burden in
healthy aging: regional distribution and cognitive consequences. Neurology.
2012;78:387-395.
18. Park DC, Polk TA, Park R, Minear M, Savage A, Smith MR. Aging reduces
neural specialization in ventral visual cortex. Proc Natl Acad Sci.
2004;101:13091-13095.
19. Carp J, Park J, Polk TA, Park DC. Age differences in neural distinctive-
ness revealed by multi-voxel pattern analysis. NeuroImage. 2010;15;56:736-
743.
20. Andrews-Hanna JR, Snyder AZ, Vincent JL, et al. Disruption of large-
scale brain systems in advanced aging. Neuron. 2007; 56:924–935.
21. Gutchess AH, Welsh RC, Hedden T, et al. Aging and the neural corre-
lates of successful picture encoding: frontal activations compensate for
decreased medial-temporal activity. J Cogn Neurosci. 2005;17:84-96.
22. Park DC, Gutchess AH. The cognitive neuroscience of long term mem-
ory and aging. In: Cabeza R, Nyberg L, Park D, eds. A Handbook of Cognitive
Neuroscience of Aging. New York, NY: Oxford University Press; 2000.
23. Stern Y. What is cognitive reserve? Theory and research application of
the reserve concept. J Int Neuropsychol Soc. 2000;8:448–460.
24. Meng X, D'Arcy C. Education and dementia in the context of the cog-
nitive reserve hypothesis: a systematic review with meta-analyses and qual-
itative analyses. PLoS One. 2012;7:e38268.
25. Tucker AM, Stern Y. Cognitive reserve in aging. Curr Alzheimer Res.
2011;8:354-360.
26. Stern Y. Cognitive reserve in ageing and Alzheimer's disease. Lancet
Neurol. 2012;11:1006-1012.
27. Ramanathan D, Conner JM, Tuszynski MH. A form of motor cortical
plasticity that correlates with recovery of function after brain injury. Proc
Natl Acad Sci U S A. 2006;103:11370–11375.
28. Murphy TH, Corbett D. Plasticity during stroke recovery: from synapse
to behaviour. Nat Rev Neurosci. 2009;10:861-872.
29. Lövdén M, Bäckman L, Lindenberger U, Schaefer S, Schmiedek F. A the-
oretical framework for the study of adult cognitive plasticity. Psychol Bull.
2010;136:659-676.
30. Maguire EA, Gadian DG, Johnsrude IS, et al. Navigation-related struc-
tural change in the hippocampi of taxi drivers. Proc Natl Acad Sci.
2000;97:4398-4403.
31. Park DC, Gutchess AH, Meade ML, Stine-Morrow, EA. Improving cog-
nitive function in older adults: nontraditional approaches. J Gerontol B
Psychol Sci Soc Sci. 2007;62:45-52.
32. Colcombe SJ, Erickson KI, Scalf PE, et al. Aerobic exercise training
increases brain volume in aging humans. J Gerontol A Biol Sci Med Sci.
2006;61:1166-1170.
33. Boyke J, Driemeyer J, Gaser C, Büchel C , May A. Training-induced brain
structure changes in the elderly. J Neurosci. 2009;28:7031-7035.
34. Lövdén M, Schaefer S, Noack H, et al. Spatial navigation training pro-
tects the hippocampus against age-related changes during early and late
adulthood. Neurobiol Aging. 2012;33:620.e9-620.e22.
35. Noack H, Lövdén M, Schmiedek F, Lindenberger U. Cognitive plastic-
ity in adulthood and old age: gauging the generality of cognitive inter-
vention effects. Restor Neurol Neurosci. 2009; 27:435-453.
36. Brehmer Y, Rieckmann A, Bellander M, Westerberg H, Fischer H,
Bäckman L. Neural correlates of training-related working-memory gains in
old age. NeuroImage. 2011;58:1110-1120.
37. Carlson MC, Erickson KI, Kramer AF, et al. Evidence for neurocognitive
plasticity in at risk older adults: the experience corps program. J Gerontol
A Biol Sci Med Sci. 2009;64:1275-1282.
38. Mozolic JL, Hayasaka S, Laurienti PJ. A cognitive training intervention
increases resting cerebral blood flow in healthy older adults. Front Hum
Neurosci. 2010;12;4-16.
39. Lövdén M, Brehmer Y, Li S, Lindenberger U. Training-induced compen-
sation versus magnification of individual differences in memory perfor-
mance. Front Hum Neurosci. 2012;6:141.
40. Jones S, Nyberg L, Sandblom J, et al. Cognitive and neural plasticity in
aging: general and task-specific limitations. Neurosci Biobehav Rev.
2006;30:864–871.
41. Willis SL, Nesselroade CS. Long-term effects of fluid ability training in
old-old age. Dev Psychol. 1990;26:905–910.
42. Ball K, Berch DB, Helmers KF, et al. Advanced Cognitive Training for
Independent and Vital Elderly Study Group. Effects of cognitive training
interventions with older adults: a randomized controlled trial. JAMA.
2002;288:2271-2281.
43. Willis SL, Tennstedt SL, Marsiske M, et al. Long-term effects of cogni-
tive training on everyday functional outcomes in older adults. JAMA.
2006;296:2805-2814.
44. Loosli SV, Buschkuehl M, Perrig WJ, Jaeggi SM. Working memory train-
ing improves reading processes in typically developing children. Child
Neuropsychol. 2012;18:62-78.
45. Dahlin E, Nyberg L, Bäckman L, Neely, AS. Plasticity of executive func-
tioning in young and older adults: immediate training gains, transfer and
long-term maintenance. Psychol Aging. 2008;23:720-730.
46. Mahnke HW, Connor BB, Appelman J, et al. Memory enhancement in
healthy older adults using a brain plasticity-based training program: a ran-
domized, controlled study. Proc Natl Acad Sci. 2006;103:12523-12528.
47. Randolph C, Tierney MC, Mohr E, Chase TN. The Repeatable Battery for
the Assessment of Neuropsychological Status (RBANS): preliminary clinical
validity. J Clin Exp Neuropsychol. 1998;20:310-319.
48. Zelinski EM, Spina LM, Yaffe K, et al. Improvement in memory with
plasticity-based adaptive cognitive training: results of the 3-month follow-
up. J Am Geriatr Soc. 2011;59:258-265.
49. NIH State-of-the-Science Conference Preventing Alzheiner ’s Disease
and Cognitive Decline. Available at: http://consensus.nih. gov/2010/docs/
alz/ALZ_Final_Statement.pdf (1-19). Accessed November 22, 2012.
50. Martinez IL, Frick K, Glass TA, et al. Engaging older adults in high
impact volunteering that enhances health: recruitment and retention in The
Experience Corps Baltimore. J Urban Health. 2006;83:941-953.
51. Stine-Morrow EA, Parisi JM, Morrow DG, Greene J, Park DC. An
engagement model of cognitive optimization through adulthood. J Gerontol
B Psychol Sci Soc Sci. 2007;62:62-69.
52. Stine-Morrow EA, Parisi JM, Morrow DG, Park, DC. The effects of an
engaged lifestyle on cognitive vitality: a field experiment. Psychol Aging.
2008;23:778-786.
53. Stine-Morrow EA, Basak C. Cognitive interventions. In: Schaie KW, Willis
SL, eds. Handbook of the Psychology of Aging. 7th ed. 2011;153-165.
54. Jackson JJ, Hill PL, Payne BR, Roberts BW, Stine-Morrow EA. Can an old
dog learn (and want to experience) new tricks? Cognitive training increases
openness to experience in older adults. Psychol Aging. 2012;27:286-
292.
55. Lodi-Smith J, Park DC. Synapse: A clinical trial examining the impact of
actively engaging the aging mind. In: Hartman-Stein PE, LaRue A, eds.
Enhancing Cognitive Fitness in Adults: A Guide to the Use and Development of
Community-Based Programs. New York, NY: Springer; 2011.
13_AG_1004_BA_INTERIEUR.qxd:DCNS#55 1/03/13 17:13 Page 119
