Preparation Lecture 4
Salthouse (2010). Selective review of cognitive aging.
Goal review -> to describe some of the major questions and findings in the field of cognitive aging.
What cognitive variables and abilities are affected?
There is consensus on the general pattern of cross-sectional age-cognition relations.
- There is an increase, at least until people are in their 60’s, for measures representing products of
processing carried out in the past, such as vocabulary or general information in which the relevant
acquisition occurred earlier in one’s life.
- There is a nearly linear decline from early adulthood on measures representing efficiency or
effectiveness of processing carried out at the time of assessment, usually involving manipulations
or transformations of abstract or familiar material.
Similar age trends are apparent with other types of variables, such as measures of performance in
various neuropsychological tests. A possible implication is that because the age relations in many
cognitive and neuropsychological variables are so well-established, they might be considered the
baseline against which age relations in other variables should be evaluated.
How many distinct age-related influences are operating?
There are two approaches to find out how many different mechanisms are contributing to the age
differences in measures of cognitive and neuropsychological functioning:
1. The most direct approach consists of examining correlations among longitudinal changes in
different cognitive variables. Several studies have found significant correlations among the
changes in different cognitive abilities.
2. The most common indirect method involves using statistical procedures to control the variance in
one variable when examining the relations of age with other variables. Many studies with different
types of cognitive and neuropsychological variables have reported substantial attenuation of cross-
sectional age relations with these types of methods.
It seems clear that a number of distinct influences contributing to both age differences and age changes
in cognitive functioning is considerably smaller than the number of variables exhibiting age relations.
Researchers should be cautious about interpreting age differences observed in a particular variable in
terms of task-specific processes or mechanisms until more general influences have been considered.
Are age-related declines in mean level of performance associated with increases in between-person
variability?
It is often assumed that the differences between people increase with age, and that only some people
experience cognitive declines, while many either remain stable or improve throughout most of their
lives. Cross-sectional data indicate that mean declines occur without accompanying increases in
between-person variability. An implication of these findings for researchers interested in age-related
cognitive declines is that mechanisms need to be identified which contribute to a shift in the entire
distribution, in addition to those which affect people differentially and result in an increase in the
breadth of the distribution.
1
, What is responsible for the discrepancy between cross-sectional and longitudinal age trends?
Within-person longitudinal comparisons sometimes reveal stability or an increase in cognitive
performance, whereas between-person cross-sectional comparisons typically reveal nearly monotonic
declines from early adulthood. One factor that clearly seems to be involved in the discrepancy is an
influence of practice associated with prior test experience in longitudinal comparisons. These results
not only suggest that longitudinal data are influenced by practice effects and thus do not provide pure
measures of maturational change, but in addition they suggest that some of the discrepancy between
cross-sectional and longitudinal age trends in cognitive functioning is likely attributable to prior
practice inflating the second scores in longitudinal assessments.
How can causes of age-cognition relations be investigated?
The ideal method to investigate cause and effect relations involves random assignment and
experimental manipulation of the relevant factor, and when the interest is on effects on rate of aging,
the research participants must be monitored over a long enough time to examine effects on rates of
cognitive change. However, because experimental methods with long-term follow-up are seldom
feasible with humans, correlation-based procedures have been used to investigate causal relations.
Because causation does imply correlation, correlation-based procedures can be used to examine the
implications of causal hypotheses.
Meditation analyses can be conducted to examine whether the results are consistent a particular set
of relations among the variables. Two limitations of mediation analyses are often not recognized:
1. Results of mediation analyses are only consistent with the hypothesized model, and the results
could be equally consistent with alternative models of the relations among the variables.
2. Mediation results might not be interpretable if there is evidence of moderation, in which the
mediator-target relations are different at different ages, because this would suggest that the
meaning of the mediator varies as a function of age.
Stern (2012) Cognitive reserve in ageing and Alzheimer’s disease
It has been suggested that we must remain open to the view that “educational level and/or
socioeconomic behavior correlated with it may be a genuine risk factor for senile dementia and are
worthy of scientific exploration. Authors published a report of lower education being associated with
higher prevalence of Alzheimer’s disease and dementia in Shanghai.
Cognitive and brain reserve
Reserve can act as a moderator between pathology and clinical outcome. One differential classification
of reserve is brain reserve versus cognitive reserve (CR).
- Brain reserve -> quantitative, for example more neurons or synapses to lose. This idea is
supported by studies that suggest that prevalence or incidence of dementia is lower in individuals
with larger brains.
o Passive model -> it suggests that the brain can simply tolerate more pathology before it
reaches a critical threshold for clinical symptoms to appear.
- Cognitive reserve -> the brain actively attempts to cope with brain damage by using pre-existing
cognitive processing approaches or by enlisting compensatory approaches. An individual with
high CR would cope better with the brain damage than an individual with lower CR. Brain
function is more relevant than brain size.
2
Salthouse (2010). Selective review of cognitive aging.
Goal review -> to describe some of the major questions and findings in the field of cognitive aging.
What cognitive variables and abilities are affected?
There is consensus on the general pattern of cross-sectional age-cognition relations.
- There is an increase, at least until people are in their 60’s, for measures representing products of
processing carried out in the past, such as vocabulary or general information in which the relevant
acquisition occurred earlier in one’s life.
- There is a nearly linear decline from early adulthood on measures representing efficiency or
effectiveness of processing carried out at the time of assessment, usually involving manipulations
or transformations of abstract or familiar material.
Similar age trends are apparent with other types of variables, such as measures of performance in
various neuropsychological tests. A possible implication is that because the age relations in many
cognitive and neuropsychological variables are so well-established, they might be considered the
baseline against which age relations in other variables should be evaluated.
How many distinct age-related influences are operating?
There are two approaches to find out how many different mechanisms are contributing to the age
differences in measures of cognitive and neuropsychological functioning:
1. The most direct approach consists of examining correlations among longitudinal changes in
different cognitive variables. Several studies have found significant correlations among the
changes in different cognitive abilities.
2. The most common indirect method involves using statistical procedures to control the variance in
one variable when examining the relations of age with other variables. Many studies with different
types of cognitive and neuropsychological variables have reported substantial attenuation of cross-
sectional age relations with these types of methods.
It seems clear that a number of distinct influences contributing to both age differences and age changes
in cognitive functioning is considerably smaller than the number of variables exhibiting age relations.
Researchers should be cautious about interpreting age differences observed in a particular variable in
terms of task-specific processes or mechanisms until more general influences have been considered.
Are age-related declines in mean level of performance associated with increases in between-person
variability?
It is often assumed that the differences between people increase with age, and that only some people
experience cognitive declines, while many either remain stable or improve throughout most of their
lives. Cross-sectional data indicate that mean declines occur without accompanying increases in
between-person variability. An implication of these findings for researchers interested in age-related
cognitive declines is that mechanisms need to be identified which contribute to a shift in the entire
distribution, in addition to those which affect people differentially and result in an increase in the
breadth of the distribution.
1
, What is responsible for the discrepancy between cross-sectional and longitudinal age trends?
Within-person longitudinal comparisons sometimes reveal stability or an increase in cognitive
performance, whereas between-person cross-sectional comparisons typically reveal nearly monotonic
declines from early adulthood. One factor that clearly seems to be involved in the discrepancy is an
influence of practice associated with prior test experience in longitudinal comparisons. These results
not only suggest that longitudinal data are influenced by practice effects and thus do not provide pure
measures of maturational change, but in addition they suggest that some of the discrepancy between
cross-sectional and longitudinal age trends in cognitive functioning is likely attributable to prior
practice inflating the second scores in longitudinal assessments.
How can causes of age-cognition relations be investigated?
The ideal method to investigate cause and effect relations involves random assignment and
experimental manipulation of the relevant factor, and when the interest is on effects on rate of aging,
the research participants must be monitored over a long enough time to examine effects on rates of
cognitive change. However, because experimental methods with long-term follow-up are seldom
feasible with humans, correlation-based procedures have been used to investigate causal relations.
Because causation does imply correlation, correlation-based procedures can be used to examine the
implications of causal hypotheses.
Meditation analyses can be conducted to examine whether the results are consistent a particular set
of relations among the variables. Two limitations of mediation analyses are often not recognized:
1. Results of mediation analyses are only consistent with the hypothesized model, and the results
could be equally consistent with alternative models of the relations among the variables.
2. Mediation results might not be interpretable if there is evidence of moderation, in which the
mediator-target relations are different at different ages, because this would suggest that the
meaning of the mediator varies as a function of age.
Stern (2012) Cognitive reserve in ageing and Alzheimer’s disease
It has been suggested that we must remain open to the view that “educational level and/or
socioeconomic behavior correlated with it may be a genuine risk factor for senile dementia and are
worthy of scientific exploration. Authors published a report of lower education being associated with
higher prevalence of Alzheimer’s disease and dementia in Shanghai.
Cognitive and brain reserve
Reserve can act as a moderator between pathology and clinical outcome. One differential classification
of reserve is brain reserve versus cognitive reserve (CR).
- Brain reserve -> quantitative, for example more neurons or synapses to lose. This idea is
supported by studies that suggest that prevalence or incidence of dementia is lower in individuals
with larger brains.
o Passive model -> it suggests that the brain can simply tolerate more pathology before it
reaches a critical threshold for clinical symptoms to appear.
- Cognitive reserve -> the brain actively attempts to cope with brain damage by using pre-existing
cognitive processing approaches or by enlisting compensatory approaches. An individual with
high CR would cope better with the brain damage than an individual with lower CR. Brain
function is more relevant than brain size.
2
