Transcript working memory

All highly developed nations in the world are
experiencing substantial increases in the
proportion of elderly adults in the population.
The world is experiencing a substantial increase
in the proportion of elderly adults in the
population.
Variations in
demographic
pyramids in Italy,
from 1950 to
2100:
Population by
age groups and
sex (percentage
of total
population)
source ONU,
Dipartimento
Economico e
Affari Sociali
Population aged over 65 years
Population aged over 80 years
Statistics on population aging, analyzed for countries in OECD area for the period
2010/2050
The aging of the population represents both an
opportunity and a threat for society.
The opportunity comes from the tremendous reserve of
human capital and experience represented by older
citizens;
the threat emerges from the frailties associated with
aging and from the disconcerting fact that at this time,
adults aged 85 and older have a very high dementia rate
(typically in the form of Alzheimer’s disease), with a very
high cost to affected individuals and families.
AD prevalence (UK)
40-64 years: 1 in 1400
65-69 years: 1 in 100
70-79 years: 1 in 25
80+ years: 1 in 6
At present, it is fair to say that neurocognitive
frailty is the biggest threat to successful aging in
our society.
(Denise C. Park and Patricia Reuter-Lorenz, Annual Review in
Psychology, 2009)
Adriana Fiorentini, 89
Carlo Maria Martini, 87
Rita Levi Montalcini, 103
Norberto Bobbio, 95
Cecilia Seghizzi, 108
Plasticity and the aging brain
As individuals age, many aspects of information
processing become less efficient,including speed of
processing, working memory capacity, inhibitory
function, and long-term memory.
At the same time, other aspects of cognitive function
such as knowledge storage, are protected and relatively
resistant to cognitive aging.
There is general agreement in the literature on
cognitive aging that memory performance
declines from early to late adulthood, and that
such age-related losses in performance are much
greater in relation to some tasks than to others.
Age-related declines are slight in short-term
memory span tasks, in which subjects repeat
back a short string of words, letters or numbers.
Decrements are typically considered slight also in
implicit memory tasks. However……
An example of single trial visual perceptual learning
An example of single trial visual perceptual learning
% of subjects showing the “Eureka” effect
"Eureka " effect and age
80,00%
70,00%
60,00%
50,00%
40,00%
30,00%
20,00%
10,00%
0,00%
18-50
65-69
70-74
75-79
80-84
85-89
90-95
Age (years)
Berardi et al., unpublished results
Age-related losses are substantial in
information processing speed and in
tasks of declarative memory, particularly
spatial memory, and those tasks requiring
recollection of events and of the original
context in which an event occurred (pattern
separation), all tasks involving the
hippocampus and other medial temporal
lobe structures.
Also performance in inhibitory functions
and in working memory tasks, relying on
prefrontal cortex, declines with age;
in particular, performance declines in those
tasks which have high memory load and
high demand on attention, which also
deteriorates with age (Park and Reuter
Lorenz, 2009).
Similarly, animal models of aging show a
decline in medial temporal lobe dependent
and prefrontal cortex dependent memory
(see Erickson and Barnes, 2003; Burke and
Barnes, 2006; Barnes 2011 for review).
Fin qui 26 novembre
Performance in “dual “ tasks (walking while
talking, divided attention,…).
esempio
Park and Reuter Lorenz, 2009
Digit symbol test (una cifra è associata ad un simbolo ed il soggetto deve studiare l’appaiamento e poi farlo il più rapidamente
possibile. Computational span: si dà una piccola operazione da fare, tipo 7+3= e il soggetto deve dare la risposta e ricordare la
seconda cifra. Alla fine di tutto, deve dare le seconde cifre nell’ordine in cui le ha incontrate
Because these data are cross-sectional, it is possible
that the observed differences are due to cohort effects or
some other confound.
However, data from the Victoria Longitudinal Study
(Canada) , (Small, et al. Hultsch et al 1999) show
strikingly similar findings for speed of processing,
working memory, list recall and vocabulary, suggesting
that the results are also found in longitudinal data and
are not primarily due to cohort effects.
Psychological approach
Changes in cognitive processes with age are related
to changes in the underlying mechanisms.
1) One dominant construct in the cognitive aging
literature has been that of speed of processing.
Salthouse (1991, 1996) argued that perceptual speed
(measured for instance by the rate at which individuals
can make “same/difference” judgments about simple
shapes, dot matrices, or strings of letters or digits) is a
fundamental, cognitive primitive that accounts for nearly
all of the age-related variance on a broad range of
cognitive tasks.
2) working memory, which encompasses both
the short-term maintenance and active
manipulative processing of information, figures
prominently in a view of cognitive aging that
emphasize declines in executive control
processes, namely inhibitory function
(Hasher&Zacks 1988, Hasher et al. 2007).
According to this view, age-related deficits in
cognition stem from the inefficiency of
inhibitory processes that normally control the
contents of consciousness (i.e., working
memory).
Older adults show working memory deficiencies and
slowing due to selection of irrelevant information into
the contents of working memory, along with inefficient
deletion of working memory contents that are no longer
relevant to task performance (filtering or inhibitory
action).
Inhibitory dysfunction with age is a source of general
attentional dysregulation and accounts for age-related
deficits in other cognitive domains such as task
switching, response competition, and response
suppression.
3) The effortful-automatic distinction (Braver & Barch
2002).
Cognitive control operations guide thought and
action in accord with task goals, especially when
bottom-up, automatic, or prepotent stimulusresponse associations must be overridden.
Age-related declines in cognitive control make older
adults more susceptible to the influence of
automatic, bottom-up processes.
Age-related cognitive declines might thus
be understood in terms of an age related
decline in a range of mechanisms including
speed, working memory, inhibition, and
cognitive control (Moscovitch&Winocur
1992,West 1996) that show varying degrees
of vulnerability in different individuals.
Although these mechanisms can all be
categorized as executive processes,
other sources of decline, such as
“dedifferentiation” ( but see later) of
cognitive function, have also been
considered.
Given the broad spectrum of cognitive
changes with age, it is unlikely that any
single process or unitary
mechanism can fully explain age-related
deficits across all individuals.
How to explain the decline in long term
declarative memory, including spatial memory,
with particular attention to sensitivity to context
and to pattern separation?
N.B.: A consensus holds that familiarity, a
relatively automatic feeling of knowing that can
support recognition-memory judgments, is
relatively preserved with aging.
By contrast, recollection, which requires the
effortful, strategic recovery of contextual detail,
declines as we age (Friedman, 2013).
Declarative memory depends from the
integrity of medial temporal lobe,
(hippocampus and surrounding cortical
areas), and of plasticity processes in these
areas.
Is a change in plasticity in these areas
related to age dependent decline of
declarative memory?
There are several papers which have addressed
and discussed the functional alterations that occur
during normal aging in the medial temporal lobe
and the prefrontal cortex and how these ageassociated changes might contribute to the
selective cognitive impairments that occur in
advanced age
(see for instance Berchtold et al. 2008; Burke and
Barnes, 2006, Park and Reuter Lorenz 2009;
Barnes 2011, Holden and Gilbert, 2012 for
review).
Many of these studies point out that age-related
changes in cognition cannot be accounted for by a
generalized loss of neurons:
indeed, in humans (Raz et al., 2004; Pakkenberg and
Gundersen, 1997; Pakkenberg et al., 2003; West, et al
1994), non-human primates (Merrill et al., 2004;
Peters et al., 1994; Gazzaley et al., 1997; Keukeret al.,
2003) and rodents (Merrill et al., 1996), significant cell
death in the hippocampus and neocortex is not
characteristic of normal aging.
There are instead age-related reductions in synaptic
density and neuropil, resulting in reduction in volume
of specific brain structures, but not a general
decrease in the number of neurons.
Burke and Barnes, 2006
Berchtoldt et al., 2008
On average, there is a
correlation between GM
amd WM integrity ad
cogntitive state.
However, many studies
failed to find such a
correlation
Profound loss of neurons does not significantly
contribute to age-related cognitive impairments
Significant cell death in hippocampus and neocortex is not characteristic of normal aging
and does not have a significant role in age-related cognitive decline. Less than 10% of
neurons of human brain is lost over the range 20-90 years. Rather, small, region-specific changes
in dendritic branching and spine density are more characteristic of the effects of ageing on neuronal morphology
Human
Rat
A common misconception about normal ageing is
that significant cell loss and dramatic changes in
neuronal morphology occur. a | This example
shows progressive loss of the dendritic surface in
aged human dentate gyrus granule cells. These
data do not accurately reflect the subtle and
selective morphological alterations that actually
occur in aged neurons, however. Age-associated
loss of dendritic extent in the dentate gyrus
and CA1 was exaggerated by including
healthy aged individuals and those with
dementia in the same experimental group,
and not using stereological controls. c |
Hippocampus
Representative hippocampal CA1 neurons from
young rats (2 months) and old rats (24 months).
There is no reduction in dendritic branching or
length with age in area CA1. In the subiculum of
non-human primates, however, significant
reductions in spine density with age have been
observed between the ages of 7 and 28 years.
Hippocampus
Burke and Barnes, 2006
One exception: Memory Impairment in Aged Primates Is Associated with Focal
Death of Cortical Neurons and Atrophy of Subcortical Neurons
Also cholinergic input to area 8A is reduced in aged monkeys
Smith et al., 2004
At the level of neuronal morphology, investigations on
dendritic branching and spine density suggest that
age associated alterations are also region-specific:
morphology of prefrontal cortex neurons seems to be
more vulnerable to the effects of aging than that of
hippocampal neurons (see Burke and Barnes, 2006).
Thus, normal aging is accompanied by differential and
often subtle changes in gray and white matter, with
different regions and even different subregions being
differentially affected by normal and pathological
aging; this is evident, for instance, at the level of the
hippocampus (see Small et al., 2011 for a review).
Very different is of course the situation in presence of
age associated neurodegenerative diseases leading to
dementia, such as Alzheimer’s disease (AD).
In summary, advancing age is accompanied by a
pattern of differential brain changes that are
observed in both cross-sectional and longitudinal
investigations (see Raz and Rodriguez, 2006 for
a review).
Overall, there is age related cortical thinning
and shrinkage of some neural structures and
there is loss of subcortical neurons in the
diffuse projecting systems (dopaminergic,
cholinergic).
There are disproportionate declines in the
prefrontal cortex, moderate declines in temporal
cortex and only mild declines in occipital regions.
As far as neural plasticity is concerned, normal aging
causes evident changes at multiple levels:
in addition to the reduction in synaptic density, which
by itself could affect synaptic plasticity by making it more
difficult to attain the sufficient amount of cooperatively
active synapses necessary to induce synaptic efficacy
changes, and to changes in Ca2+ conductances and
homeostasis, aging alters forms of synaptic plasticity
related to declarative memory processes such as
hippocampal LTP.
Hippocampal LTP is altered in aged animals at the level
of both induction and maintenance, with maintenance
most severely affected (see Burke and Barnes 2006 for
review).
Most basic neuronal properties remain rather constant with age both in the hippocampus
and in the PFC
Aged animals do have alterations in the mechanisms of
plasticity that contribute to cognitive functions.
LTP decline and spatial memory decline (Barnes maze) correlate
Burke and Barnes, 2006
Even in normal aging there are subtle changes in the
biological processes that underlie memory, and in the
relationship between how good an animal’s memory is
and how functional their synapses are.
But the real message in these experiments is that old
animals can and do learn.
None of the older animals exhibited what could be
considered behaviorally to be “dementia”, nor were their
biological mechanisms that allow memory traces to be
laid down completely dysfunctional.
Age-related changes in gene expression
The maintenance of LTP requires gene expression and de novo
protein synthesis; therefore, it is not surprising that aged animals
and humans also show alterations in these processes.
Following behavioural induction, the proportion
of cells expressing a gene in a specific brain
structure can be measured with fluorescence in
situ hybridization. Panel b shows confocal
images of fluorescence in situ hybridization for
Arc mRNA in the dentate gyrus of a young rat
and an old rat. Granule cells are shown in red
and Arc mRNA in yellow. After spatial
exploration, more granule cells are positively
labelled for Arc in young than old rats. No
such changes in CA3, for instance
In humans, prominent change in baseline
gene expression occurred in the sixth to
seventh decades across cortical regions,
suggesting that this period is a critical transition
point in brain aging, particularly in males.
Burke and Barnes, 2006; Berchtoldt et al., 2008
Epigenetic factors in aging
Young and old animals show differences in DNA
methylation.
In the resting old brain, granule cells, for example, had
overall higher methylation levels, meaning that it was
less likely that plasticity genes could be transcribed
from the DNA (Barnes and Sweatt, see Barnes 2001).
There may well be a number of changes that
accumulate during aging via epigenetic means, and that
dysregulation of these processes may contribute in a
fundamental way to normal age-related cognitive
change.
Peleg et al. (2010) found that during contextual fear
conditioning learning, aged mice (16 months old)
exhibited a specific deregulation of histone H4 lysine 12
(H4K12) acetylation and failed to initiate a
hippocampal gene expression program associated
with memory consolidation.
This was in very good correlation with behavioural data
showing a deficit in long-term fear memory.
Interestingly, restoration of physiological H4K12
acetylation reinstated the expression of learninginduced genes and led to recovery of cognitive
performance.
The maintenance of place maps also differs
between young and old animals.
In normal young rats, a place map for a given
environment can remain stable for months. Therefore,
when a rat is returned to the same environment, the
same place map is retrieved. A similar stability of CA1
place maps in aged rats is observed within and between
episodes of behaviour in the same environment.
Occasionally, however, if the old rat is removed from the
environment and returned later, the original place map is
not retrieved and an independent population of place
cells may be activated even in a familiar room.
Spatial maps of an environment DO NOT remain locked to context in old rats
Exploration
24h later, re-exploration
Young
Old
In the second case, the old animal DOES NOT remember
having been in this place, DOES NOT possess a spatial
map of it and may think to be in another place.
Reactivation of hippocampal neurons
during sleep is impaired in aged rats
Gerrard et al., 2008
Differential effects of aging in the hippocampus
Fin qui 11 novembre
Aging effects on hippocampal neurogenesis
Aging strongly reduces hippocampal neurogenesis
(dentate gyrus) across several species (see Amrein et
al., 2010; Kempermann et al., 1998, 2002 and 2010).
(aside note: Recent evidence by Frisen group in Sweden
(Spalding et al, 2013) found definitive evidence for DG
neurogenesis in humans. By modelling the process of
carbon 14 presence in brain cells, the team estimated
that we generate around 1400 new neurons every day in
the DG, roughly the same percentage as in rodents;
most of them die, but some are integrated into DG
circuits).
The brain, time-stamped.
Atmospheric 14C that was released during nuclear bomb tests
between 1945 and 1963 has been incorporated into the DNA of
dividing cells, providing a time-stamp. This has been used to
prove adult hippocampal neurogenesis in humans, thereby
confirming a particular type of structural and functional brain
plasticity involved in higher cognitive function.
(News and views, Kemperman et al., 2013)
Neurogenesis in the dentate gyrus of the hippocampus
is strongly reduced in aged rats
A, Total number of BrdU-positive cells per
dentate gyrus 1 d after the last injection of BrdU
to estimate ongoing proliferation (hatched bars)
and 4 weeks later to assess survival of BrdUpositive cells (open bars). B, C, Percentage of
the surviving BrdU-positive cells (compare with
B) that differentiated into either neuronal (filled
bars) or glial (hatched bars) phenotype or
showed neither differentiation (open bars).
Kemperman et al., 1998
Aging effects on hippocampal neurogenesis
In humans, indirect (doublecortin expression in
hippocampal cells from post mortem samples)
evidences for reduced neurogenesis in aged subjects
comes from the study of Knoth et al. (2010) and by
volumetric reductions in hippocampal formation found in
human aged subjects (Apostolova et al., 2011; Small et
al., 2011).
Frisen study (2013) suggests that the ability to create
new neurons declines less in aged humans than in aged
mice: instead of the nearly 10-fold decrease between
young and middle-aged mice, the Swedish team found
only a four-fold decrease in humans.
Riduzione della neurogenesi nel giro dentato con
l’età: uomo e roditore
Kheirbeck and
Hen, 2013
Ruolo della neurogenesi ippocampale nella
memoria:
Vedi lezioni sui meccanismi di plasticità
neuronale
Small et al., 2011
The human dentate gyrus plays a part in ‘pattern
separation, a cognitive operation that allows
similar stimuli flowing through the hippocampal
circuit to be represented with distinct neural codes
allowing correct storage of the spatial and
temporal contex of a memory (effects of block
of neurogenesis on pattern separation, GageBussey e vanPraag).
Impairments in these tasks have been
documented in ageing subjects (see also van
Praag) and have been interpreted as confirming
previous fMRI findings that implicated the dentate
gyrus in normal ageing.
Although the computational process underlying
pattern separation occurs within the dentate gyrus
itself, impaired performance might also be
expected with upstream lesions in the entorhinal
cortex.
A recent view of hippocampal dysfunction in
aging (Barnes, 2011).
Until recently, most neuroimaging and
neuropsychological tests have evaluated the
hippocampal formation as a singular structure,
but it is in fact a complex circuit made up of
functionally and molecularly distinct subregions.
Moreover, the complexity of the hippocampal
formation extends beyond its internal circuit
organization.
Hippocampal vulnerability to insults of
different nature is regionally specific.
Recent gene-expression studies have established
that each hippocampal subregion has a distinct
molecular profile, and this ‘molecular anatomy’
provides a partial substrate for regional
vulnerability.
The relatively high expression of certain NMDA receptors
in CA1 helps to explain its vulnerability to excitotoxicity in
the context of hypoxia and ischaemia associated with
vascular disease whereas the high levels of corticoid
receptors in the dentate gyrus confer vulnerability to the
effects of reductions in the level of circulating
corticosteroids.
Different regions of the hippocampus have different
involvements in cognition.
Although ageing is itself not a disease,
cognitive decline that occurs during ageing
has deleterious consequences, and because it
occurs without prominent cell loss it is
considered a prime example of a functional
disorder.
Nevertheless, the effect of ageing on hippocampal
function is often confounded by diseases, in particular
Alzheimer’s disease and vascular disease, which
commonly occur in older subjects and can cause
hippocampal dysfunction independent of ageing.
When attempting to isolate the hippocampal pattern
of dysfunction reflective of ageing per se, it is
therefore important to exclude the effect of
Alzheimer’s disease and vascular disease
fMRI have been applied to ageing human subjects (with
or without Alzheimer’s disease and with or without
vascular disease), ageing rhesus monkeys, ageing mice
and mice that express disease-causing mutations in the
amyloid precursor protein (FAD).
Besides confirming the differential link of Alzheimer’s
disease to the entorhinal cortex and vascular disease to
CA1, results from these cross-species studies suggested
that ageing itself differentially affects the dentate gyrus
AD
VD
AGING
Regional vulnerability and metabolic state
differentiate disorders that affect the
hippocampal formation. Although multiple
hippocampal subregions can be affected in
disorders, by comparing patterns of alterations
that are observed by functional and structural
MRI it is possible to isolate individual subregions
differentially affected by each disorder.
Furthermore, functional imaging techniques that are
sensitive to metabolic state have suggested that
some hippocampus-based disorders are
characterized by hypometabolism (shown in blue),
whereas others are abnormally hypermetabolic.
a | Alzheimer’s disease, vascular disease and ageing
all contribute to hippocampal alterations in late life. A
direct comparison suggests that the entorhinal cortex
(EC) is differentially associated with Alzheimer’s
disease and the CA1 with vascular disease, whereas
the ageing process per se seems to differentially
target the dentate gyrus (DG).
Hypometabolism has been localized to the EC in
Alzheimer’s disease, to CA1 in vascular disease
and the DG in ageing.
NB (for the next lectures):
While aging and Alzheimer’s disease may in some cases
be “superimposed”, there is not a simple linear trajectory
where we all end up with the disease.
Rather, aging has a different neural signature,
supporting the contention that aging and Alzheimer’s
disease are distinct.
Staub et al., 2006: in participants with amnestic MCI,
compared with age-matched controls, results showed a
significant decrease in white matter volume in the region
of the parahippocampal gyrus that includes the perforant
path. There was also significant atrophy in both the
entorhinal cortex and the hippocampus.
“Compensatory” plasticity in aging
In parallel to diminished neural plasticity, there
are numerous examples of what can be
considered compensatory plasticity during the
aging process.
This shows up mostly in terms of activation of a
larger and more elaborate pattern of acrivation of
brain areas, and in particular of the prefrontal
cortex, in aged with respect to young subjects
performing the same task;
interestingly, this more extensive activation
correlates with better performance in the elders
(see Park and Reuter Lorenz, 2009 for a recent
review).
Frontal bilaterality increases with age
Is this additional activity important for the better
performance of old subjects? To answer this question,
repetitive TMS (rTMS) has been used to transiently
disrupt prefrontal cortex function.
These studies have provided especially compelling
evidence in favor of contralateral activity enhancing
cognitive function in older adults.
rTMS is a technique that transiently disrupts neural
function by applying repetitive magnetic stimulation to a
specific area of the brain, creating highly focal and
temporary “lesions.”
In a seminal study conducted by Rossi et al. (2004), young and
older adults studied pictures while rTMS was applied to the
subjects’ left or right dorsolateral prefrontal cortex (DLPFC)
(encoding); the subjects then made recognition judgments while
rTMS was again applied to the left or right DLPFC (retrieval).
One of the most interesting finding from this work was that young
adults’ memory retrieval accuracy was more significantly
affected when the rTMS was applied to the right compared to
the left hemisphere during retrieval.
In contrast, older adults’ retrieval was equally affected by the
rTMS during retrieval, whether it was applied to left or right,
suggesting that the activation in both hemispheres was useful for
performing the recognition task.
Similar results to those described for memory have been
found for linguistic abilities (Wingfield and Grossman,
2006) and motor abilities Heuninckx et al., 2008);
interestingly, one of the additional brain areas recruited
by elders with good performance in the linguistic task is
an area activated in young subjects in situations of
particularly complex sentence processing, which stress
working memory demands.
Y > elderly good comprehenders
Elderly GC > Y
Wingfield and Grossman, 2006
Young adults were producing a significantly greater degree of activation than the
older adults in the posterolateral temporal-parietal cortex in the left hemisphere.
This region is thought to support a short-term auditory-phonological buffer that retains information
transiently during the course of processing (Chein and Fiez 2001; Jonides et al. 1998). This region
also includes the core left posterior sentence processing component.
The compensation hypothesis would lead one to expect to see the successful older adults recruit
other brain regions to maintain their successful performance. Indeed these successful older
adults showed significant upregulation in two areas. One of these is increased activity in
the dorsal portion of left inferior frontal cortex. This area is thought to be important for
maintaining and rehearsing stored verbal information in working memory. The other is the right
posterolateral temporal-parietal region. The young adults also showed increased
activation in this area but only for sentences that especially stressed working-memory
demands (Cooke et al. 2002). For the older adults, these areas of activation were
evident for all types of sentences.
This additional activation, which young people
use in challenging situations, would compensate
for the lower activation in the core left
hemisphere posterior language areas found in
aged people.
The result is as good a performance in elder as
in young subjects.
The aging brain can maintain a relatively high level of
performance despite the biological changes associated
with aging. The stability in performance is maintained by
engaging novel brain regions and implementing novel
(cognitive) strategies in response to a constant
(cognitive) goal.
Comment on “dedifferentiation”
This highlights the adaptive and plastic nature of the
neurobiology of brain function that supports optimizing
goal attainment with available resources even when in
older adulthood these resources may become
diminished.
Thus, the aging brain can maintain a relatively high level
of performance through neural plasticity processes,
optimizing goal attainment with the available resources.
Park and Reuter-Lorenz point out that compensatory
plasticity in the form of more elaborate patterns of
brain area activation is not unique to aging but that
it is the brain’s response to cognitive challenge:
it is more likely to find a more elaborate pattern of brain
area activation in aging brains even for simple tasks
simply because tasks which for young brains result to
have a low level of complexity bring forth significative
cognitive challenge for older brains
Neural plasticity in the form of compensatory
changes in aging
“the corpus of these data suggests that the brain is a dynamic organism seeking to
maintain homeostatic cognitive function.”
Park and Reuter-Lorenz, 2009
In contrast to the age-related declines in cognitive
function and brain structure, functional brain activity
increases with age, particularly in the frontal cortex. The
proposed scaffolding theory of aging and cognition
suggests that this increased functional activity is due to
compensatory activation—the recruitment of additional
circuitry with age that shores up declining structures
whose function has become noisy, inefficient, or both.
The Authors propose that the Prefrontal cortex, the
most flexible structure in the brain, is largely responsible
for the scaffolding processes in the aging brain.
Scaffolding is the brain’s response to cognitive challenge
and is not unique to aging.
Aging simply results in more frequent cognitive
challenges at lower levels of intensity.
The aged brain is in effect less efficient at generating
scaffolding, and significant pathology (as occurs in
advanced Alzheimer’s disease) may entirely limit
scaffolding operations.
Enhancing neural plasticity in old age, both
that underlying learning and memory and
that underlying compensatory activation,
might benefit cognitive performance in
elders through multiple mechanisms
Cognitive scaffolding is promoted by
cognitive activity.
“….. growing evidence suggests that humans
develop scaffolds as a result of stimulating
experiences. (Parl and Reuter-Lorenz, 2009”
It might be possible to enhance plasticity in
old age (that underlying learning and
memory, that underlying compensatory
activation) by being active.
Predictors of maintaining cognitive function in older adults:
The Health ABC (Aging and Body Composition) Study
Yaffe et al., Neurology, 2009
Elders who maintain cognitive function have a unique profile that
differentiates them from those with minor decline. Importantly,
some of these factors are modifiable and thus may be
implemented in prevention programs to promote successful
cognitive aging.
See you next lecture