Análisis interno

This chapter reviews possible explanations for age differences in memory. Firstly, cognitive explanations are considered, including the possibility of reduced processing resources, speed of processing, and reduced efficiency of working memory being implicated in age-related decline in memory. Secondly, the changes in the neural substrates of memory are discussed. The effects of brain changes on working memory and episodic encoding and retrieval are addressed. The focus then turns to

demyelination and neurochemical changes as possible explanations for age differences in memory.

Despite the paucity of memory research for the oldest-old, basic cognitive abilities such as verbal ability and working memory have been investigated. Several major theories attempting to account for the observed age-related changes in memory have been suggested: reduced processing resources, speed of processing, reduced efficiency of working memory, and changes in the neural substrates of memory, for example. It is clear from aging research studies that statistical control of processing speed and working memory variables can attenuate the extent of age-related variation in memory performance. For example, Lindenberger, Mayr, and Kliegl (1993) examined the relationship between speed and intelligence in 76 old (M = 77.2, SD = 4.6) and 73 oldest-old (M = 92.3, SD = 4.7) adults to investigate whether speed continues as a main determinant of age-related variability after the age of 70 years. Participants completed 14 tests to measure speed, reasoning, memory, knowledge, and fluency. Age trends in all abilities tested were well described by a negative linear function. The data were consistent with the hypothesis that age-related decrements are a result of age differences in speed, although the researchers caution against the conclusion “that speed is all there is to cognitive aging” (p. 218). Further investigation is necessary to

establish the contribution of such variables as health status, education, and social involvement. Bäckman, Small, and Wahlin (2001) concur, suggesting future research combining biological aspects with health-related factors would increase our knowledge of memory functioning in old age.

Cognitive Explanations

Reduced processing resources

Craik and Byrd (1982), proposed that “reduced attentional resources lead to an attenuation or shrinkage in the richness, extensiveness, and depth of processing operations at both encoding and retrieval” (p. 208). Attentional resources are those required to focus on, and react to, the auditory, visual, and tactile stimuli (Spence, Kettenmann, Kobal, & McGlone, 2001). While the role of such resources in encoding has been well investigated (e.g., Craik & Byrd, 1982; Perlmutter & Mitchell, 1982) the role of processing resources in retrieval have received less attention (Fastenau, Denburg, & Abeles, 1996).

Fastenau et al. (1996) suggest that age differences in processing resources are particularly salient to age-related decline in the formation of new memories and in recent long-term memory. They investigated this assertion in a cross-sectional study utilising 47 younger (M = 43.5, SD = 7.4) and 43 older (M = 67.5, SD = 7.4) adults, who completed four memory tests and four measures of processing resources designed to assess memory span, attention span, speed, and accuracy. The hypotheses that retrieval would be less efficient in older adults was fully supported, whilst the prediction that these age effects would be reduced when controlling for differences in processing resources was largely evident. These results support those of Corgiat, Templer, and Newell (1989) who compared young (18 - 30 years) and older (60 - 88 years) adults to determine the relationship between memory and processing resources, finding the older adults recalled less than their younger counterparts under the most effortful condition. Thus, Fastenau et al. concluded both their own results and those of Corgiat et al., provide support for explanations of aging memory such as that proposed by Salthouse (1988). Both of these studies, however, fail to provide comprehensive evidence for Salthouse’s resource-reduction explanation. The oldest group included in the Fastenau et al. study had a mean age of only 67.5 years, while the Corgiat et al.

study utilised an older group with a 28 year age range. Clearly, it could be expected that individuals who are 85+ years are going to perform very differently to 60 year old people, and studies which exclude the oldest-old or even the young-old cannot provide a complete picture of memory performance during aging.

Arguably, the reduced processing resource theory which has received the most attention is that of a reduced processing speed in the elderly.

Speed of Processing

The speed with which information can be processed reflects the efficiency of the cognitive system. The processing speed hypothesis argues that the speed with which elementary cognitive operations are carried out places fundamental limits on all aspects of cognitive functioning, including remembering (Luszcz & Bryan, 1999). Hartley, Harker, and Walsh (1980) note that by the early 1980s the hypothesis had emerged that neurophysiologically-based change could account for much of age- related changes in memory. Waugh and Barr (1980) and Salthouse (1980) suggested older people employ the same types of processing strategies as younger people, but the limiting factor in memory performance is the rate at which these operations can be accomplished by the central nervous system (CNS). Salthouse (1991, 1996a) suggests the speed at which the CNS processes information influences both the quantity and quality of memory. Salthouse (1996a) further suggests that age-related differences may be a function of slower processing speed with advancing age, because memory traces for previous operations may decay before later information is received,

weakening linkages between representations.

A decline in processing speed appears to provide a parsimonious account of some of the memory losses encountered in normal aging. The slowing has been hypothesised to be a reflection of greater interference or noise in the nervous system (Salthouse & Lichty, 1985), damaged neural connections (Cerella, 1990), weakened linkages

between connections (MacKay & Burke, 1990), or an accumulation of loss at each step of processing – encoding, storage, and retrieval (Salthouse, 1985). Salthouse (1996b) suggests two mechanisms underpinning the relationship between speed and cognition. The limited time mechanism is assumed to result from cognitive operations being executed too slowly to be successfully completed in the available time, whilst the simultaneity mechanism is hypothesised to operate because slow processing reduces

the amount of simultaneously available information needed for higher level processing. For most memory tasks there is a limited window of time in which a specific operation must be completed to avoid compromising the end result (Luszcz & Bryan, 1999).

The speed hypothesis has impressive support. In 1991, Salthouse and Babcock partitioned the components of working memory into storage, processing efficiency, and coordination components. Evidence was found that processing efficiency, measured by ability to answer simple numerical and verbal comprehension questions, mediated most age-related variance in measures of working memory. However, Salthouse and Babcock also reported that the age-related deficiencies in processing efficiency were mediated by speed. Salthouse (1991) recruited between 220 and 230 adults from 20 - 84 years in each of three studies in which tasks were designed to measure perceptual comparison speed and working memory. The results suggested that many of the differences in measures of cognitive functioning with increased age may be mediated by reductions in the speed of executing relatively simple processing operations. Salthouse reported that whilst working memory appeared responsible for some of the age-related declines, many of the working memory differences may also be mediated by reductions in the speed of carrying out elementary operations.

Salthouse (1993), in a later cross-sectional study using a large number of adults from students to adults in their 70s, measured processing speed (measured by pattern and letter comparison tasks and number and letter transformation tasks) and motor speed (marking and copying tasks), as well as long-term memory. He found that between 80% and 100% of the age-related influences on memory were eliminated after

statistical procedures to equate participants on an index of speed. For example, 18.4% of the variance in the memory composite was associated with age prior to statistical control of the speed variable, whereas after statistical control of processing speed the age-associated variance was 3.2% for memory. Reviewing this, and numerous other similar studies, Salthouse (1994) concudes that “it is apparent that the results were similar in every study in that the age-related variance in the measure of working memory was greatly attenuated after control of the measure of speed” (p. 539). Many other studies, however, demonstrate nowhere near such a large amount of the variation accounted for by processing speed (e.g., Hultsch et al., 1990; Rabbitt, 1993; Schaie, Maitland, Willis, & Intrieri, 1998).

A plethora of studies, typically correlational studies using hierarchical multiple

regression, have found that speed of processing is an important factor in age-related memory decline (e.g., Bryan & Luszcz, 1996; Hultsch et al., 1990; Park et al., 1996; Salthouse, 1996a). This robust effect persists across a wide range of age groups utilising differing memory tests and statistical analysis procedures, as well as in population-based samples of the very old (Lindenberger et al., 1993), and across studies of a wide range of predictors of memory variance both cross-sectionally and longitudinally (Luszcz et al., 1997). Schaie et al. (1998), discussing the invariance of adult psychometric ability over 7 years, caution that although processing speed is an important factor in cognitive abilities, when adults over 75 years are included, only longitudinal data gives an accurate picture, and cross-sectional studies including adults over 75 years would require specific demonstrations of invariance before the age- difference findings can be accepted.

Zimprich (2002) constructed a test of processing speed balancing the cross-sectional age range and the time period covered longitudinally to test the findings that cross- sectional studies have provided impressive support for the processing speed theory although longitudinal studies provide much weaker support. Data were collected from the Bonn Longitudinal Study on Aging. At first measure in 1965, the average age of the 221 participants was 67.7 years (SD = 4.9). The fifth and final measure was in 1976, at which time 38% of the original 221 participants completed the last of five assessments. Participants completed a German version of the WAIS (Wechsler, 1981). At Time 1 testing speed differences, on average across all subtests, explained 85% of the age- related intellectual ability. However, the covariance between the amount of change in processing speed and the amount of change in intellectual abilities over 9 years was only about 4%. Zimprich and Martin (2002) tested the hypothesis that if speed of information processing is at the core of cognitive aging, the correlation between changes in processing speed and fluid intelligence should be substantial. In a 4-year longitudinal study (two test waves), a sample of 417 individuals (M = 62.96 years, SD = 0.92) completed a range of speed and fluid intelligence measures. Compared to cross- sectional data, in which processing speed and fluid intelligence share up to 79% common variance (Verhaeghen & Salthouse, 1997), Zimprich and Martin report that age-related changes in processing speed and fluid intelligence shared only 28% common variance.

This is comparable to the findings of Sliwinski and Buschke (1999) who juxtaposed cross-sectional age-difference effects and longitudinal age-change effects in a sample of 302 people (M = 77.2 years, SD = 5.0) in a 4-year longitudinal study. Utilising

hierarchical linear models, Sliwinski and Buschke reported that cross-sectionally speed of processing accounts for 70% (verbal fluency) up to 100% (verbal comprehension) of age differences. In contrast, longitudinal analysis showed that processing speed accounts for only 6% (verbal comprehension) to 29% (memory span) of age changes. Schaie (1989) also points out that a single-effects model of processing speed must be questioned as, in the 1977 cross-sectional data from the Seattle Longitudinal Study, it is clear that substantial age effects remain even when speed is accounted for. Taken together, the results of these studies suggest that the explanatory power of speed of processing theory appears to be reduced when age changes, rather than age differences, are taken into account.

Lindenberger et al. (1993), in a large sample of adults from 60 - 90 years, also found that even in very advanced age, speed mediated performance on all measures of cognitive abilities. However, it remained unclear whether working memory was a separate key mediating construct, in conjunction with speed, a matter addressed in studies by Mayr and Kliegl (1993) and Kliegl, Mayr, and Krampe (1994). These latter two studies suggest speed and working memory might independently contribute to age- related declines in memory. Hultsch et al. (1990) and Rabbitt (1993) also propose that discrepant research findings suggest that speed is not sufficient to explain age-related declines in memory, and suggest that there is at least one, if not more, other factors operating in age-related decrements.

Light (1991) warns that strong testimonials for general slowing hypotheses such as that of Cerella (1990) who asserts that it replaces “the myriad task-specific explanations of age effects that have proliferated in the literature” (p. 217), must be tempered as it is by no means clear that a single slowing parameter suffices to describe age-related

differences.Salthouse (1994) concurs that the mechanism for the robust and large influence of speed on the relationship between age and working memory is not yet well understood, but points out in a review of studies designed to explore the relationship demonstrated that between 71% and 96% of the age-related variance in measures of working memory is shared with measures of processing speed. Salthouse further suggests there is support for the interpretation that advancing age is associated with a reduction in the speed of encoding or activating information, as the preservation of

information over very short intervals is relatively unaffected by aging. However, it must be noted that many studies have found nowhere near this percentage of working memory shared with processing speed (e.g., Hultsch et al., 1990; Rabbitt, 1993).

Furthermore, Hartley et al. (1980) caution against viewing the speed of processing as the prime mediator between aging and memory on three counts:

(a) Walsh, Williams, and Hertzog (1979) found that older adults require some 30% more processing time than younger people when constructing a sensory memory representation of visual output, whilst Walsh and Prasse (1980) found that older adults need as much as 80% longer than their younger counterparts to extract information from sensory memory and recode it into primary memory. Hartley et al. (1980) contend that this does not provide evidence for large amounts of slowing being in memory-related mechanisms, as such research would suggest difference between young and older adults on primary memory tasks, and such differences are not supported by research. If there was validity to the speed of processing explanation, then brief tachistoscopic presentations should produce age differences in primary memory span for digits, even though the same individuals, using standard presentation rates may show no age differences in memory span.

(b) For processing speed to have validity, Hartley et al. (1980) assert it is

necessary to supply detailed specifications on how affected memory systems might result in less information stored or retrieved from secondary memory. This can be clarified by the Hartley et al. computer metaphor: Two computers may differ by almost 100% in the speed at which they execute hardware

instructions, though each will store and retrieve identical amounts of information when executing the same programme. Slower processing does not in itself mean that less information is stored or retrieved. A longer time to remember does not always mean slower processing – rather than proposing that older people remember less because they process more slowly, it may be that they divert their processing resources to concurrent processing demands, thus never completing the operations necessary for efficient encoding and retrieval from secondary memory.

(c) The pattern of age differences in memory is the reverse of the pattern predicted by processing speed explanations. There is strong evidence of age differences in processing speed at early stages of information output where memory performance does not differ greatly with advancing age. Conversely, there is little evidence of substantial slowing where greatest differences in memory are demonstrated. i.e., There is no change with advancing age in speed of retrieval from semantic memory (Eysenck, 1975), or naming latencies (Waugh & Barr, 1980). These are paradoxes as yet unexplained.

In sum, processing speed needs to be incorporated into any explanation of age-related decrements in memory, and further research is needed to define and refine both what it should stand for and the degree to which it impacts on memory. While impressive results have claimed between 80% and 100% of the age-related influences on memory was eliminated after statistical procedures to equate participants on an index of speed (Salthouse, 1993), in other studies speed of processing influences declines much less spectacularly. For example, Lindenberger and Baltes (1997) found just 38% of the variance was reliably associated with processing speed.

It is clear that processing speed impacts on age-related declines in memory, but much remains to be explained. Myerson, Hale, Wagstaff, Poon, and Smith (1990) assert that speed of processing is not yet well explained, suggesting that slowing may be a

consequence of neurobiological changes that lead to an increase in the proportion of information lost at each processing step in a way not yet fully understood. A powerful connection between sensory functions and speed was found by Baltes and

Lindenberger (1997) with a comparison of younger individuals (M = 48.2 years, SD = 14.7) and older adults (M = 84.9, SD = 8.66) showing a high degree of age-relatedness of the link between sensory and intellectual functioning, including speed of processing. Lindenberger et al. (1993) also suggest there is a need for further research on the reasons underlying age differences in measures of speed. Additionally, it is essential to ensure the measures of processing speed under investigation accurately represent the hypothesised construct.

A further avenue of investigation into reduced capacity has centred on the role of working memory resources in observed age changes in memory, particularly in the functioning of the central executive.

Working Memory and the Role of the Central Executive

A mounting body of research has investigated a decrease in the efficiency of central executive functioning with increasing age (Fisk & Warr, 1996; Salthouse, Atkinson, & Berish, 2003; Salthouse & Babcock, 1991).

Broadly defined, central executive functioning consists of “control processes

responsible for planning, assembling, coordinating, sequencing, and monitoring other cognitive operations” (Salthouse et al., 2003, p. 566). The authors propose executive functioning encompasses tasks such as inhibition, updating, and attentional capacity, suggesting that whilst these functions have largely been viewed as independent, it is possible they represent different aspects of a single function. Furthermore, such

executive functioning is associated with the frontal lobes and is relevant to theories that propose that age-related deficits are associated with a deterioration of the frontal lobes of the brain (Crawford, Bryan, Luszcz, Obonsawin, & Stewart, 2000; Moscovitch & Winocur, 1995; Raz, 2000; Shimamura, 1984; West, 1996). This view of central

executive processes provides a neuropsychological model of aging and memory rather than a purely cognitive explanation (Luszcz & Bryan, 1999).

Troyer, Graves, and Cullum (1994) tested the extent to which measures of executive function contributed to age-related declines in episodic memory performance in a sample of 51 adults 60 - 91 years of age. They found that age predicted memory performance before, but not after, measures of executive function were partialled out, suggesting executive function does play a mediating role. Troyer et al. found that executive functioning accounted for 36% of the variance in recall performance. However, the Troyer et al. study did not include measures of general cognitive ability and it is not clear whether the demonstrated declines were mediated by decrements in