Preface

Editors: Backman, Lars; Hill, Robert D.; Neely, Anna Stigsdotter

Title: Cognitive Rehabilitation in Old Age, 1st Edition

Copyright 2000 Oxford University Press

> Table of Contents > Part I - Theory-Driven Guidelines for Cognitive Rehabilitation Strategies in Older Adults > 1 - The Interplay of Growth and Decline: Theoretical and Empirical Aspects of Plasticity of Intellectual and Memory Performance in Normal Old Age

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The Interplay of Growth and Decline: Theoretical and Empirical Aspects of Plasticity of Intellectual and Memory Performance in Normal Old Age

Paul Verhaeghen

Research on Plasticity in Old Age: A Short History

As cognitive aging researchers, we care for our subjects. Most scientists and practitioners do, of course, but there seems to be a quite inordinate amount of sympathizing in cognitive aging circles. I usually look very much forward to testing people from our older adult research panel they are so much different from the typical undergraduate student, who breezes into the lab and seems to want nothing more than to breeze out as quickly as possible. We get acquainted over a cup of coffee, and I usually get to hear some pretty interesting stories (thanks to my research subjects, I know more about nuclear waste management than is good for my sense of security, I have an inkling of the usefulness of Bach sonatas for the beginning piano player, and I will never consider a career switch to operating high-rise cranes). It is always quite distressing to see how these interesting, highly motivated, and articulate human beings then struggle with the cognitive tasks set before them they certainly do not breeze through. This contrast between high performance in daily life and less than optimal performance in the laboratory has not been lost on most researchers in the field. Our laboratory data and our theories about basic effects of aging on cognition say one thing (decline, growing inflexibility, powerlessness); our hearts, and also our eyes, say another (accumulated experience, openness to life, potential).

In fact, a major impetus for the initiation of plasticity research in the 1970s was precisely the general theoretical scenario of gerontological work (Baltes & Lindenberger, 1988, p. 284) then prevalent: Cognitive aging was considered a process of universal, cumulative, and gradual decline. The growing dissatisfaction with this limited view on aging resulted in conceptualizations of cognitive aging as a multidimensional,

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multidirectional process with much individual variety in developmental trajectories (e.g., Baltes, Dittmann-Kohli, & Dixon, 1984). One of the cornerstones of such conceptions was the performance-potential distinction, which led researchers to look for modifiability-toward-potential as a function of the experiences accumulated by the individual rather than just to focus on scores on standard tests of cognitive performance (e.g., Baltes & Labouvie, 1973; Baltes & Schaie, 1976; Baltes & Willis, 1982; Labouvie-Vief, 1976). This modifiability within individuals was subsequently labeled plasticity, and intervention studies were started in the domain of psychometric intelligence by researchers at Penn State (the ADEPT [Adult Development and Enrichment] program), and later at the Max Planck Institute for Human Development and Education in Berlin (the PRO-ALT [Projekt Altersintelligenz, Intelligence in Old Age Project]).

Soon, the concept of plasticity became synonymous with the type of modifiability tapped by these and similar (though less ambitious) programs. Whereas Baltes and Willis (1982) defined plasticity in a generic sense as the range of functioning at the individual level, whether ontogenetic (how variable is the individual course of development?) or concurrent (how variable is the performance at a given point in ontogenetic time?) (pp. 355 356), in practice, the term has been narrowed down to mean the range of intellectual aging under conditions not normally existent in either the living ecology of older persons or in the standard assessment situation provided by classical tests of psychometric intelligence, restricted for ethical reasons, to conditions assumed to be performance enhancing (Baltes & Willis, 1982, p. 356). After first and largely unsuccessful attempts to modify performance on paper-and-pencil intelligence tests by increasing response speed (Hoyer, Hoyer, Treat, & Baltes, 1979; Hoyer, Labouvie, & Baltes, 1973; speed was indeed found to have increased after practice, but this did not have a large impact on intelligence test performance), plasticity researchers turned to the investigation of the effects of instruction and practice on performance on specific subtests of intelligence tests.

It is important to note here that these programs tapping plasticity in intellectual functioning have been developed explicitly for theoretical reasons, and not for the remediation of problems encountered in the day-to-day living ecology of the participants. The theories, moreover, were rather vague. Merely demonstrating the existence of plasticity was considered more important (at least at first) than a thorough investigation of plasticity as a phenomenon. In this, as Salthouse (1985) pointed out, 1970s accounts of plasticity often attacked a straw man position, as if any true psychologist could earnestly state that older people have no capacity to benefit from experience. Theory was not the only thing that was on researchers' minds direct links to social policy issues were involved, in a sort of vicarious emancipatory reflex, as exemplified in the following quote from Baltes and Willis (1982):

Research on plasticity is inherently aimed at providing a knowledge base apt to suggest procedures for optimization and redistribution of education resources according to a life-span perspective . In this sense, research on plasticity contributes to a foundation of social policy that is inherently preventive, corrective, and equity-oriented rather than discriminatory or defeatist. (p. 357)

Since those early days, things have changed. More recently, much emphasis has been placed on the fact that the demonstration of the existence of plasticity is not

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enough, and that plasticity in its turn needs to be explained (e.g., Baltes & Kliegl, 1986; Baltes, Kliegl, & Dittmann-Kohli, 1988; Baltes & Lindenberger, 1988; Kliegl & Baltes, 1987; Willis, 1989, 1990). Some of the controversial issues that surround plasticity as a phenomenon (rather than a concept) are the nature and directionality of the effects of treatment. With regard to the nature of training effects, there is some controversy over whether the training really attains the level of the ability trained (as was the explicit goal of the ADEPT program; Willis, 1989) or rather remains at the level of the specific skill taught (Willis called this teaching the test, 1989, p. 554). Likewise, directionality of the effects is an issue under debate. The abilities trained are known to decline with age, and it may be tempting to assume that training remediates at least part of the decline that individuals experience, by activating skills that have gone lost or rusty through disuse. However, given the large individual differences in the timing of decline and the exact abilities that show decline, Willis (1989) suggested that training effects may reflect remediation, incrementation, or compensation, depending on a given individual's prior performance history on a specific ability (p. 557).

Another interesting development is that plasticity research has moved out of the tradition of psychometric intelligence (and out of the laboratory) and into the domain of episodic memory functioning. Unlike the ADEPT or PRO-ALT studies, memory-training studies were often constructed with the explicitly pragmatic goal of boosting memory performance in the real world. Maybe because the explicit goals of these two research traditions were so diverse, the experimental design and procedures for the two types of research have been quite different, so that a direct comparison of results is difficult. For instance, research into plasticity in psychometric intelligence has used different types of control groups and control measures; control procedures are the exception rather than the rule in memory-training research. Another difference is that the psychometric intelligence tradition has not used age-comparative designs, whereas quite a number of memory-training studies exist in which the treatment gains of older adults are compared to the treatment gains of young adults. The new line of findings has led researchers to focus on other issues of interest to plasticity theory, such as (age-related) limits to plasticity (Baltes & Kliegl, 1986; Lerner, 1990) and individual differences associated with individual differences in plasticity (Willis, 1990).

In the remainder of this chapter, I will briefly summarize some key results from these two main lines of plasticity research, paying special attention to the controversies and questions mentioned above: the nature and directionality of training effects, the age-related limits of plasticity, and individual differences in training responsiveness.

Plasticity in Psychometric Test Performance

Plasticity in Psychometric Test Performance: Study Design

As stated above, the studies devised to tap plasticity in psychometric intelligence performance have been designed with the initial goal of demonstrating the existence of plasticity, rather than offering direct theoretical insights into its nature and antecedents.

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In order to demonstrate plasticity, a number of carefully planned control procedures have been included in the design of the studies. One simple control procedure is to compare treatment gain in trained subjects with the gain obtained when subjects are merely retested. This control group is used to estimate the baseline for plasticity due to testing experience alone. Some of the later studies (Baltes et al., 1988; Baltes, Sowarka, & Kliegl, 1989) also included a group receiving extensive practice; that is, participants were repeatedly retested under the standardized instructions for the test, and without receiving any feedback. This type of intervention serves as an estimate for the amount of performance gain subjects can achieve on the basis of cognitive skills already in their repertoire or by applying new but entirely self-taught skills. Two studies (Hayslip, 1989; Labouvie-Vief & Gonda, 1976) included stress inoculation treatment as a placebo group.

All of these types of control treatments are contrasted to explicit training in ability-specific problem-solving skills. The exact content of the skills trained is determined through task analysis of the marker tests for these abilities. For instance, for a training in figural relations, standard tests for this ability would be analyzed, relational rules would be identified that should be applied to the material, and these rules would then be taught in the training program. Items used for training were always similar to, but not identical to the items of the standardized test. Results obtained from such training groups yield an estimate of the amount of plasticity that can be reached when optimal strategies are applied to the task.

Another type of control procedure used in psychometric intelligence plasticity involves measuring the effects of the training on a number of transfer tests. First and foremost, tests of the ability trained are used as indicators of near-near transfer, that is, transfer from the specific items taught to the items of a test measuring the same ability. Second, tests for related abilities are used as indicators of near transfer. All training programs involve fluid abilities, and consequently tests for other fluid abilities are used as near transfer measures (in the one study on attention, memory span was used as a near transfer measure). Third, tests for abilities unrelated to the trained ability (e.g., tests for crystallized abilities) are used as indicators of far transfer. If the effect is ability-specific, as opposed to being a general reactivation effect, one should expect performance gain on near-near transfer tasks to exceed performance gain on the other transfer tasks. It might even be expected that transfer on near transfer tasks would be larger than transfer on far transfer tests.

Plasticity in Psychometric Test Performance: Some Key Findings

An overview of the results of the different training studies can be found in Table 1.1. In this table, pre-to-posttest treatment gains are expressed in terms of mean standardized differences. Thus, the numbers indicate by how many standard deviations performance was shifted from a test prior to training or the relevant control procedure to a test after the training or control treatment. A meta-analysis of these findings is presented in Table 1.2 (for an introduction to meta-analysis, see Bangert-Drowns, 1986, or Mullen, 1989; a quick tutorial can be found in Verhaeghen, Marcoen, & Goossens, 1992). Note that the subjects in Baltes, Dittmann-Kohli, and Kliegl (1986) and Baltes et al. (1988) were trained in both figural relations and inductive reasoning, so that

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effect sizes for these measures (within the control, extended-practice, and ability-training treatment groups) are not independent; also note that treatment gains could not be calculated because of design problems or insufficient data in four other relevant studies (Blackburn, Papalia-Finlay, Foye, & Serlin, 1988; Blieszner, Willis, & Baltes, 1981; Labouvie-Vief & Gonda, 1976; Willis, Blieszner, & Baltes, 1981).

Table 1.1 Studies Included in the Meta-Analysis on Pre-to-Posttest Differences in Control, Placebo, and Treatment Groups for Psychometric Intelligence Research

Study	Type	n	d	Lower	95% confidence limits for d Upper
Control groups
Baltes, Dittmann-Kohli, and Kliegl (1986)	FR	68	0.75	0.40	1.10
Baltes, Kliegl, and Dittmann-Kohli (1988)	FR	29	0.36	-0.15	0.88
Baltes, Sowarka, and Kliegl (1989)	FR	24	0.39	-0.18	0.96
Plemons, Willis, and Baltes (1978)	FR	15	1.55	0.73	2.37
Baltes et al. (1986)	IR	68	0.90	0.54	1.25
Baltes et al. (1988)	IR	29	0.23	-0.29	0.75
Hayslip (1989)	IR	88	1.21	0.89	1.54
Willis, Cornelius, Blow, and Baltes (1983)	AT	24	0.64	0.06	1.22
Extended practice
Baltes et al. (1986)	FR	29	0.88	0.34	1.42
Baltes et al. (1988)	FR	24	0.87	0.27	1.46
Baltes et al. (1988)	IR	29	0.82	0.28	1.35
Stress inoculation
Hayslip (1989)	IR	92	1.51	1.18	1.84
Ability training
Baltes et al. (1986)	FR	136	1.36	1.09	1.62
Baltes et al. (1988)	FR	29	0.67	0.15	1.20
Baltes et al. (1989)	fR	24	0.74	0.15	1.32
Plemons et al. (1978)	fR	15	2.08	1.19	2.97
Baltes et al. (1986)	IR	136	1.34	1.07	1.60
Baltes et al. (1988)	IR	29	0.80	0.27	1.34
Hayslip (1989)	IR	76	1.81	1.44	2.19
Willis and Schaie (1986)	SO	118	0.45	0.19	0.70
Willis et al. (1983)	AT	24	1.04	0.44	1.64
Near transfer
Bakes et al. (1986)	FR	136	0.66	0.42	0.90
Baltes et al. (1988)	FR	29	0.41	-0.11	0.93
Baltes et al. (1989)	FR	24	0.38	-0.19	0.95
Plemons et al. (1978)	FR	15	0.70	-0.04	1.44
Baltes et al. (1986)	IR	136	0.66	0.42	0.90
Baltes et al. (1988)	IR	29	0.41	-0.11	0.93
Willis et al. (1983)	AT	24	0.37	-0.20	0.94
Far transfer
Baltes et al. (1986)	FR	136	0.36	0.12	0.60
Baltes et al. (1988)	FR	29	0.07	-0.44	0.59
Baltes et al. (1989)	FR	24	0.25	-0.32	0.81
Baltes et al. (1986)	IR	136	0.36	0.12	0.60
Baltes et al. (1988)	IR	29	0.07	-0.44	0.59
Willis and Schaie (1986)	IR	110	0.20	-0.07	0.46
Willis et al. (1983)	SO	24	0.19	-0.06	0.45
Note. FR = figural relations; IR = inductive reasoning; SO = spatial orientation; AT = attention; d = point estimate of means standardized difference between pretest and posttest. The comparisons between Figural Relations and Inductive Reasoning by Baltes et al. (1986) and Baltes et al. (1988) are within-subject. Transfer effects versus training effects in all relevant studies are measured within-subject; effects of training versus control, extended practice or stress inoculation in all studies are measured between-subject.

Table 1.2 Summary of Effect Size Statistics (Effects of Skill Training on Intelligence Performance as Compared With the Effects of Various Control Procedures)

Measure	k	d+	95% Confidence limits for d+		Qw
			Lower	Upper
Figural relations
Ability training	4	1.21	0.99	1.41	11.30a
Near transfer	4	0.59	0.39	0.79	1.34
Far transfer	3	0.30	0.10	0.50	1.01
Control	4	0.67	0.42	0.91	6.93
Extended practice	2	0.87	0.48	1.27	0.00
Inductive reasoning
Ability training	4	1.08	0.92	1.24	35.74a
Near transfer	2	0.62	0.39	0.84	0.71
Far transfer	3	0.26	0.10	0.43	1.37
Control	3	0.92	0.71	1.14	10.12a
Extended practice	1	0.82	0.28	1.35
Stress inoculation	1	1.51	1.18	1.84
Spatial orientation
Ability training	1	0.45	0.19	0.70
Far transfer	1	0.19	-0.06	0.45
Attention
Ability training	1	1.04	0.44	1.64
Near transfer	1	0.37	-0.20	0.94
Control	1	0.64	0.06	1.22
Note, k = number of studies; d+ = mean weighted effect size (mean standardized difference); Qw = chi-square statistic for homogeneity within groups. aSignificant nonhomogeneity at p < .05, according to chi-square test.

A number of results from the meta-analysis seem noteworthy. First, training in ability-specific problem-solving skills generally results in larger performance gains than retesting. This finding indicates that the training has an effect above and beyond the effect of mere retesting. However, these differences are reliable only for the ability of figural relations (Q_B = 10.53; p < .05), and not for inductive reasoning or attention (Q_B = 1 37 and 0.86, respectively; ns). In fact, a more striking result is that for both skill training and retesting, effect sizes are fairly large. This finding indicates that retesting itself is a quite potent elicitor of plasticity in intellectual performance, improving performance by two thirds of a standard deviation or more.

Second, extended-practice groups show no reliably smaller treatment gain than skill-training groups (Q_B = 2.08 and 0.88 for figural relations and inductive reasoning, respectively; ns; and note that in the three studies that included both conditions, the effect size for extended practice was actually larger than that for skill training). This

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finding strongly suggests that the crucial factor in the difference between the outcome of retesting and skill-training treatments is not the experimenter-guided instruction. Rather, as Baltes et al (1988) formulated it, this difference seems an indication that the performance gains obtained in past cognitive training research with psychometric measures of intelligence in the elderly were possible because of the activation and practice of existing cognitive skills (p. 399). This interpretation of the data is further supported by the fact that in the Baltes et al. (1988) study, ability-trained subjects did not solve more difficult items than the subjects having received extensive practice. Further support for the skill activation/practice hypothesis comes from the result that stress inoculation treatment resulted in reliably larger treatment gain than skill training in the one study investigating both (Hayslip, 1989) maybe reducing stress helped subjects activate metacognitive operations and thus allowed them access to efficient skills. Skill reactivation appears to be a fairly rapid process, in that it already seems to operate when people are given a power assessment of the test (e.g., giving them more time and fewer items to solve; Baltes et al., 1988) rather than the usual speeded assessment.

With regard to transfer, tests for near-near transfer do indeed show a trend toward larger performance gains than either near transfer or far transfer tasks, with the latter showing the least amount of pre-to-posttest treatment gain. Inspection of the 95% confidence intervals indicates that for the abilities of figural reasoning and inductive reasoning, performance gains in ability tests are larger than those for near transfer and far transfer tests, with no reliable difference between the latter two. This finding, then, suggests that the effects of training remain largely confined to the ability trained.

Effects of cognitive skill training have also proven to be reasonably durable. Maintenance of training effects for fluid abilities have been examined over a 6-month period by Baltes et al. (1986), Willis et al. (1981), and Willis, Cornelius, Blow, and Baltes (1983), with posttest-to-follow-up-test mean standardized differences of 0.42, -0.06, and -0.14, respectively, showing either gain over this period or a decline that was relatively modest compared with the pre-to-posttest gain.

Plasticity in Psychometric Test Performance: Controversial Issues

What do these results teach us about the nature of observed plasticity in psychometric intelligence? As Willis stated in 1989: The primary concern in training research is not a change in performance on a letter-series test or the 20-questions task per se, but rather change in the latent construct the test is said to represent (p. 554). Unfortunately, the available evidence is largely inconclusive. The design of the studies, while ingenious, is not well suited for distinguishing between a change due to teaching-the-test and change at the latent construct level. For instance, in order to conclude that a change in ability has indeed occurred, one needs to demonstrate that long-term effects are present but long-term effects could also be present if one merely has learned the skills to do well on the particular test and these skills are retained over the follow-up period, as we shall see in the review of memory plasticity studies.

A finding that at first sight seems like hard evidence for ability change is the fact that in the Willis and Schaie (1986) study, where training outcome was assessed at the factorial (i.e., presumably ability) level, performance was boosted more for the

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trained than for an untrained ability. However, this again is a necessary but not a sufficient condition for demonstrating that training has reached the ability level. In this study, subjects were trained in spatial orientation, and most tests for this ability require a common skill, namely, mental rotation. If subjects master this skill well for instance, because they have learned to focus on two or more features of the figure during rotation (Willis & Schaie, 1986, p. 241) they might apply this skill to all kinds of rotation tests, including those that look quite different from the test on which they were trained.

The most stringent test for demonstrating effects at the ability level would be to assess changes in performances on tasks relying on the ability, both in a laboratory context and in the living ecology. For instance, if one claims to have raised the spatial intelligence of students and spatial intelligence is correlated with certain types of study results (say, in geometry), then one should expect an increase in study results on the specified tasks after training. To my knowledge, no explicit tests for this type of generalization of ability training to other tasks requiring the ability have been conducted. However, it is interesting to observe that training in perceptual speed through extended practice does not result in a sizable increase in fluid intelligence scores (Hoyer et al., 1979; Hoyer et al., 1973), even though perceptual speed appears to be a major determinant of fluid intelligence (Horn, 1982; Salthouse, 1996; Verhaeghen & Salthouse, 1997).

In sum, while the results are consistent with the possibility that training reached the ability level, they are equally consistent with the hypothesis that effects remained at the level of the specific skill.

Another controversial issue concerns the direction of training improvement. Does training truly provide rehabilitation, in that it installs not only levels of performance previously available, but reinstalls lost skills? Schaie and Willis (1986) investigated this question by training 229 older adults from the Seattle Longitudinal Study on either Inductive Reasoning or Spatial Orientation. These subjects had taken standardized intelligence tests 7 and 14 years prior to training, and training improvement could thus be compared to their prior level of functioning. It was found that people whose performance had declined reliably (i.e., by one standard error or more in the course of 14 years) showed larger treatment gain at the level of the test taught than stable subjects; both groups showed equal gain when performance was measured at the factorial level. For 40% of the declining subjects, performance was equal to or larger than their performance 14 years earlier. Schaie and Willis (1986) concluded that what their intervention procedures seem to accomplish is to reactivate behaviors and skills that have remained in the subjects' behavioral repertory but have not been actively employed and that at least a portion of the previously observed decline may be attributable to disuse (p. 230). Unfortunately, one can make this assertion with full confidence only if information about the 1970 skills (rather than just the 1970 performance) is available which is not the case. The question also remains: What, then, is altered in the stable subjects, who also performed better at pretest than decliners, and thus presumably deployed superior skills or used them more efficiently already at pretest? It is quite possible that the stable subjects also had the trained skills unused in their repertoire, which would imply that performance decrements of decliners over the 14-year period are not necessarily due to disuse of these skills. In fact, it remains entirely possible that young adults also have the same skills dormant in their repertoire.

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Before firm conclusions regarding the role of disuse in adult age differences in intelligence can be reached, it is absolutely necessary to include groups of young adults in the designs (Salthouse, 1991). If disuse is indeed a major determinant of adult age differences and reactivation a potent elicitor of treatment gain, young adults should show less training gain than the old (Light, 1991; Salthouse, 1991). Salthouse (1991, p. 166) reviewed seven relevant studies on extended practice in intelligence or short-term memory performance and found that in none of these studies did the young show smaller treatment gain than the old.

Plasticity in Psychometric Test Performance: Conclusions

Results from plasticity research in psychometric intelligence shows that considerable malleability of performance is indeed present in old age. The locus of these changes appears to lie largely in the older adults themselves: Given enough practice with the task, they seem perfectly able to reach the level of performance reached by their age peers who have been subjected to explicit training in the relevant skills. In fact, this research shows that a procedure for fair assessment of older adults' performance on traditional intelligence tests should include either practice with the task or power rather than speeded assessment. There seems to be no conclusive evidence yet as to the nature or directionality of the plasticity effect. Thus, it remains possible that training or self-taught improvement does not reach the ability level and is not truly reactivation, but fast learning of a new skill or increased efficiency in executing an existing skill.

Plasticity in Memory Performance

Plasticity in Memory Performance: Mnemonics, Skills, or Ability?

Interestingly, some of the controversial issues surrounding plasticity in the domain of psychometric intelligence do not apply to the domain of memory plasticity. Memory plasticity research is almost exclusively concerned with teaching particular skills or strategies that might help boost memory performance, and boosting performance is the goal the goal is not a change in memory ability. This is already evident from definitions of memory skills or strategies such as the one offered by Bellezza (1983): A memory strategy is a particular procedure that an individual can use to memorize a particular set of materials under a specific set of conditions (p. 53). One can make a loose distinction between memory skills, such as rehearsal, semantic elaboration, or the use of imagery or organization, which have broad applicability to subclasses of memory tasks, and more specific strategies, such as the method of loci or the pegword mnemonic or other formal systems for encoding and retrieving information, which can be applied to only a narrow range of tasks and materials. Memory skills are often applied spontaneously by many research subjects, because they are usually part of the behavioral repertoire of most adults, being relatively standard ways of operating on to-be-remembered materials. Formal techniques are rarely used spontaneously; they need to be learned explicitly and typically need conscious control for their initiation

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and execution (Cavanaugh, Grady, & Perlmutter, 1983; Harris, 1980; Intons-Peterson & Fournier, 1986; Park et al., 1990).

Two strategies that have been used extensively in research with older adults are the method of loci and the name-face mnemonic (for more details on these and other strategies, see Bellezza, 1983). In the method of loci, subjects learn, in a first step, a sequence of locations, such as landmarks in a city or places around their home. When a list of words has to be learned, each word is linked through interactive imagery to one of the locations. Retrieval occurs by taking a mental walk along the sequence of locations, retrieving the mental image at each location, and decoding the original word from it. In the face-name mnemonic (see Lorayne, 1976, for an extensive description), subjects select a prominent feature of the face to be learned, make a concrete, high-imagery transformation of the person's name, and then form an interactive image of the facial feature and the name transformation.

From these brief descriptions, it is clear that the effects of training in these mnemonics will probably result in highly specific effects. Training in the method of loci should be of little help to subjects learning to associate names and faces. Likewise, training in the name-face mnemonic would be of little avail when one is confronted with a list of words that have to be learned in sequence. The training effects are thus tied to performance, not to a change in an underlying ability. Kliegl and Baltes (1987) illustrated this by offering an analogy with high jumping. Trained athletes do high jumping by twisting the body after pushing off, so that they go back down, head first over the bar, a technique called the Fosbury flop after the person who used it first at the 1968 Olympic games. This technique has to be learned, and the locus of change is clearly not the trainee's intrinsic ability to high-jump, but merely her or his performance. Note that the technique can be applied only under certain circumstances; for instance, it presupposes a shock-absorbent surface at landing it's clearly not recommended for jumping the garden wall. Performance increments always occur in a specific context and make sense only within that particular context. Note that the assumed specificity of training effects also means that from a clinical point of view, it may be worthwhile to teach the metaskill of deciding what technique to use when one is faced with a particular task and a particular set of materials under specified conditions (Wong, 1989). To my knowledge, no research on the effects of training such metacognitive skills, though potentially useful, has been conducted.

Likewise, when a mnemonic strategy is taught, the directionality of effects is usually clear: Reactivation is highly improbable, because most people never had these mnemonic strategies in their behavioral repertoire (and, interestingly, even people who know these techniques and understand their effectiveness, such as professional memory researchers, do not tend to use them; Park et al., 1990). Rather, memory strategy training entails the learning and honing of a completely new skill.

Another difference between training in the use of memory skills or strategies and training in psychometric intelligence concerns individual differences. Whereas training in psychometric intelligence is always (that is, if the task analysis has been done carefully) training in the optimal technique for the test (there is only one good way to perform well on an intelligence test), this is not the case for mnemonic training. There is more than one effective way to learn, for instance, a list of words in sequence. One could apply the method of loci, the pegword mnemonic, or one could make up a story using the words in sequence or make a phrase of the first few letters of each

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word. Certain individuals may prefer one technique over the other, and this preference may have to do with particular abilities these individuals are strong in, or with their preferred cognitive style.

Plasticity in Memory Performance: Some Key Findings

The key results of plasticity in the domain of episodic memory functioning were summarized in a meta-analysis of 32 studies by Verhaeghen et al. (1992). Here, I wish to highlight four results from that analysis.

First, the effects of memory training appeared to be larger than the effects of mere retesting or placebo treatment (placebo treatment consisted of all interventions that did not consist of teaching memory skills or strategies; it included giving feedback, teaching relaxation techniques, or having group discussions of memory problems). Memory training boosted performance by 0.73 standard deviations; mere retesting enhanced performance by 0.38 standard deviations; and placebo treatment resulted in a gain of 0.37 standard deviations. Consequently, the locus of treatment effects appears to have been primarily the training itself. It can also be concluded that the effects of relaxation techniques, group discussions, and the like on memory performance probably entailed no more than a retesting effect. The reader may note that the specific effect of the instruction (0.73 - 0.38 = 0.35) was somewhat larger than the specific effect of the instruction in psychometric intelligence (which had a weighted average of 0.20, all types of abilities combined). On the other hand, the retest effect for memory tests was only about half the size of the retest effect for intelligence tests. Taken together, these results suggest that no dramatic self-initiated change in skill or strategy or optimization of skills or strategies occurred in retested subjects, but that the net effects of memory training were quite large indeed.

Second, there was indeed a differential effect of training on memory tasks tailored to measure progress after training in the specific technique (e.g., a list of words to be recalled in sequential order for training in the method of loci; Verhaeghen et al. called this a target task ) and measures that consisted of near transfer tasks (for training in the method of loci, a near transfer task could be recall for the association between faces and names). This result indicates that the effects of training in a memory technique were quite specific indeed. This is a clear indication that the locus of the training effect is the technique taught, and not reactivation of general memory skills.

Third, no differential treatment gain was observed for the different types of skills or strategies taught. This was true regardless of whether the specific skills or strategies were directly compared with each other, or whether verbal techniques were contrasted with imagery techniques, or whether skills were contrasted with strategies. Thus, when the effect is measured on target tasks, there does not seem to be any technique that is clearly superior to any other.

Fourth, a regression analysis was conducted to determine some of the characteristics of the studies that were reliably associated with treatment gain. It was found that treatment gains were largest when the subjects were younger, when pretraining (usually involving training in imagery) was provided, when training was carried out in groups, when some form of memory-related intervention (such as attention training, providing information about memory and aging, and group discussion) was included in the program, and when sessions were relatively short. Part of these effects have to

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do with optimizing the learning environment. For instance, with regard to session duration, it should be mentioned that mean session duration in these studies was 90 minutes an inordinate amount of time when one wishes to hold someone's attention. Thus, it makes sense that shorter sessions should be more fruitful. The enhancement of effect when other interventions are combined with the training proper may be due to increased motivation, or such interventions may simply provide a break in the sessions, thus reducing the need for sustained attention. The positive effects of conducting the training in a group environment may have to do with peer learning, or again, they may be due to enhanced motivation. The effect of pretraining could be explained in similar terms, or it may be a real effect of learning a new skill in the pretraining phase that can be applied to the memory technique in the training phase. Or the effect of pretraining might be artifactual, in that more testing occasions were provided in these programs, and increased familiarity with the material may have played a role. The age-relatedness of plasticity, within a group of older adults, is a finding that will be expanded upon in the next section.

Like the effects of training in psychometric intelligence, the effects of memory training appear to be reasonably durable. A small number of studies have investigated follow-up effects over either a 6-month interval (Stigsdotter Neely & B ckman, 1993a, 1993b) or a 3-year interval (Anschutz, Camp, Markley, & Kramer, 1987; Scogin & Bienias, 1988; Stigsdotter Neely & B ckman, 1993a). A meta-analysis on these studies shows that the net maintenance effect of training (i.e., pre-to-follow-up-test effect size minus pre-to-posttest effect size) was quite large. Over a 6-month interval, performance increased by 0.40 standard deviations (as compared to a 0.28 increase in retest groups); over 3 years, performance went down slightly, by 0.11 standard deviations (as compared to a 0.06 decrease in retest groups). Thus, the effects of memory training appear to be as durable as those of training in psychometric intelligence. The reader may note that since the nature of the treatment effect here is the skill or strategy rather than the ability, these results indicate that even skill or strategy training can clearly lead to durable effects.

Plasticity in Memory Performance: Testing-the-Limits and Individual Differences

A first text on the limits of plasticity in old age appeared in 1986 (Baltes & Kliegl). These authors apparently took their inspiration from theories about biopsychological adaptation in old age (Coper, J nicke, & Schulze, 1985), which state that aging brings about increased vulnerability and a reduction in system adaptability. These problems should be most easily noticeable at limits of performance. Baltes and Kliegl trained their subjects in the method of loci, using a presentation time manipulation as a way of getting at the limits of the system. It was found (and this finding has been replicated since; Kliegl, Smith, & Baltes, 1990) that at posttest, differences between subjects, including age differences, were magnified. Moreover, 20 subsequent sessions of practice and testing did not at all reduce the age difference obtained at posttest (Baltes & Kliegl, 1992). Thus, this study points at clear limits to plasticity and found these limits to be age-related. Other studies have confirmed this finding as well: When the effects of memory training in a group of young and older subjects are compared, training

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effects are usually larger for young than for older adults (for details and a metaanalysis on seven such studies, see Verhaeghen & Marcoen, 1996). In the previous section, we saw that this effect also holds within the group of older adults: On the average, studies that have younger old participants yield larger effects than studies than have examined older old participants. And it has been found that even the effects of lifelong expertise do not totally counter the negative effects of age on plasticity, as research concerning the trainability of graphic designers in the method of loci demonstrates (Lindenberger, Kliegl, & Baltes, 1992).

An obvious hypothesis might be that age is negatively associated with plasticity in memory performance because the same variables that are associated with pretest performance are also associated with posttest performance, treatment gain, or both. Consider again the high-jump analogy. While the Fosbury flop is a very effective technique if one wants to engage in high-level high jumping, it does not necessarily offer opportunities for compensation. At least some of the same abilities or strengths associated with pre- Fosbury techniques will be associated with the flop: Muscle strength, sheer speed, joint flexibility, precision of kinesthetic sensations, and motor control will probably all be important, whatever technique one uses for high jumping. To carry the analogy to the domain of memory functioning, posttest performance is still memory performance, and some of the variables associated with pretest scores will probably also affect posttest scores. Inasmuch as these variables are negatively associated with age, treatment gain may well be a negative function of adult age. Indeed, a number of variables found to be correlated with plasticity are also negatively affected by age: speed of mental operations (Kliegl et al., 1990; Kliegl & Thompson, 1991), working memory (Kliegl & Thompson, 1991), and mental status (Hill, Yesavage, Sheikh, & Friedman, 1989; Yesavage, Sheikh, Friedman, & Tanke,1990; a nonsignificant trend in the same direction was found by Stigsdotter Neely & B ckman, 1995; an overview of other variables can be found in Verhaeghen & Marcoen, 1996).

Verhaeghen and Marcoen (1996) tested this hypothesis directly by training a group of young and older adults in the method of loci and measuring a number of basic variables usually associated with age-related differences in cognition (speed, visual and auditory working memory, and associative memory), while also tapping strategy use through a questionnaire filled out immediately after the recalling of each list. One difference between the two age groups emerging from this study was that older adults were less susceptible to complying with instructions and truly applying the method of loci at posttest. All of the young adults stated that they did use the method at posttest; about one in four older adults stated they did not use the method at all at posttest. Noncomplying older adults were generally older than complying older adults, performed less well at pretest, and had lower scores on a measure of associative memory. Thus, interestingly, those subjects that presumably needed the mnemonic boost most were less willing or maybe less able to actually use it. It was also found that fewer older adults applied the method correctly: About two thirds of the older adults who did apply the method of loci at posttest mixed it with other strategies, such as making up a story and forming connections between words only 40% of the young did not apply the method correctly. It was found that incorrect application of the technique in older adults was a perseverance effect: The subjects not inclined to use the method correctly were those who, at pretest, used efficient strategies with a higher frequency

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than subjects using the method incorrectly. This finding suggests that memory training needs to be concerned not only with learning the new technique, but also with helping older people to discontinue the use of old (and usually inefficient) techniques.

With regard to individual differences in plasticity, Verhaeghen and Marcoen (1996) found that the same mechanism appears to govern plasticity in young and old adults. In both groups, speed of mental operations influences the capability of forming and retaining associations, and this capability influences pretest directly and posttest both directly and indirectly through limiting the number of times the subject can go over the list of words. For young adults, but not older adults, visual working memory appeared to be a secondary resource that correlated with pretest performance. Paradoxically, it is precisely the similarity of the mechanisms of plasticity in young and older adults that drives the magnification of age differences, because the basic variable of the plasticity system, speed of mental operations, is negatively correlated with old age. Speed of mental operations is also one of the basic variables that are associated with the age-related decline in fluid cognition (including episodic memory performance); therefore, training adults in the method of loci will result in an amplification effect: Group or individual differences that exist at pretest will be amplified at post-test.

It may be important to note here that the limiting effect of speed appears to be internal rather than external; that is, mental slowing has consequences in the efficiency of cognitive operations that go beyond a mere need for longer study times. For instance, Verhaeghen and Marcoen (1996) found that even older adults who claimed they had had the time to study all the words twice when study time was 6 minutes recalled only one word more than young adults who claimed they had had just enough time to study the list once when study time was 2 minutes (18.8 items vs. 17.8 items, out of a total of 25).

Reanalysis of the data from Baltes and Kliegl (1992) by Verhaeghen and Kliegl (1998), focusing on the relation between performance and study time, sheds additional light on the amplification of age differences. In this study, training in the method of loci was found to have mainly two immediate effects: It raised the maximum level of performance (i.e., the level that could be attained if no time pressure was present), and it slowed subjects down (i.e., at posttest, subjects needed more time to reach their maximum level of performance than at pretest). After subjects had more practice with the method, the maximum level of performance did not change much, but the speed of forming associations increased. Age differences were found at three levels: (a) Older adults needed one session more than young adults in order to reach their maximum level of performance; (b) their maximum performance was lower; and (c) they were slower at forming associations between words and places. In sum, this study showed that the effects of aging on plasticity were tied both to the maximum level of accuracy and to mental speed.

Plasticity in Memory Performance: Conclusions

As in the domain of psychometric intelligence, there appears to be sizable malleability in memory performance in old age. In contrast with plasticity in intelligence, the effects appear to be tied to teaching of the mnemonic: The effect of retesting is much smaller, and the net effect of training larger. The effects of training remain restricted

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to materials to which the specific skill or strategy taught can be applied, but they appear to be quite durable. One consistent result is that there are age-related limits to plasticity tied to basic characteristics of the aging mind: Speed goes down, as does maximum accuracy.

Plasticity Beyond the Laboratory

The research and the theoretical positions reviewed above are aimed at a better understanding of cognitive aging. Many of the research efforts aimed at uncovering plasticity do not have remediation as a primary goal. Still, some lessons that can be drawn from the literature presented here should have an impact on clinical work.

First, one way to look at the data from the ADEPT and PRO-ALT programs and the meta-analytic data gathered by Verhaeghen et al. (1992) is that training programs accomplish what they are designed to do: Programs designed to boost scores on standard intelligence tests do boost those scores, and programs teaching a particular mnemonic technique can enhance memory performance. The same was found in a meta-analysis on subjective memory functioning (Floyd & Scogin, 1997): Programs designed to improve subjective memory functioning indeed do so. However, in all these cases, the gains are restricted to those tasks that are in the focus of the program. Thus, in intelligence test training, treatment gain in scores on near transfer tests are much lower than treatment gains in tests narrowly connected to the skills taught; in memory training, treatment gain is limited to tasks to which the mnemonic can be applied; expectancy modification programs work better than actual memory training in producing treatment gain in changing scores on tests tapping subjective memory functioning. If improvement in a specific aspect of a person's functioning (regardless of that person's age) is the goal, it is important to target the intervention as closely as possible to the behavior to be changed. And it may be worthwhile to consider what precisely that target is before we rush to the training room: It seems to me that changing how older persons look at their own memory functioning may be even more important for their general well-being than their ability in recalling lists of words in the correct sequence. In that case, an intervention should probably not entail much instruction in mnemonics but should focus on a person's feelings and perceptions of memory functioning.

Second, effects of training are very much limited to specific target tasks. Most memory problems associated with old age, however, extend beyond single tasks. One then has basically two options for training. One option is to teach broader skills rather than specific techniques, at the same time focusing on the applicability of these skills in different contexts. The other option is to teach a number of different specific techniques, again paying careful attention on when and where to apply what technique. In my opinion, training for strategy selection is as important for boosting performance in the daily life ecology as training specific techniques. Memory monitoring and online control thus appear essential ingredients for any real-life cognitive training in the old.

Third, the finding of contextualization of plasticity (plasticity is always about teaching a specific person a specific technique that can be used in specific circumstances) has clear consequences for treatment. Training effectiveness will probably be

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a function of the interaction between technique, task, and individual. If a person has a visualization impairment or is not inclined to engage in imagery, teaching imagery-based mnemonics is maybe not such a good idea. Strategies and skills taught should rely on the individual's strong points, and not on the individual's weaknesses.

Fourth, the perseverance effect needs to be taken into account. Older people who have a good repertoire of effective skills tend not to trade in these skills too easily for other techniques, even if these are much more powerful. It is important to realize that such apparent lack of behavioral flexibility probably results from a lifetime of selective optimization of behavior (Baltes & Willis, 1982), resulting in self-initiated compensation (B ckman, 1989). It is quite understandable that people want to hang on to these adaptive operations. Thus, cognitive or memory trainers should make certain that they can convince older persons that the new technique is more effective than the self-taught techniques, for instance by providing extensive practice with feedback on performance, so that older persons can judge for themselves whether they want to adopt the new skills as their own.

Fifth, there is no such thing as easy and effortless remediation of age-related performance differences. Even in a laboratory setting, subjects often seem to expect a miracle worker rather than a trainer, and to strongly hope for total recall with zero effort. Both subjects and trainers should be aware that progress will be relative and that much effort is required to achieve it. This may seem self-evident, but even in the context of an experimental training (and with participants who are well aware that this is research and not therapy), people can be mightily disappointed even when their performance is boosted by 200% if they do not get everything correct.

Sixth, because general factors such as basic speed of mental operations influence treatment gain and will presumably do so in every form of training in mental skills or strategies, subjects ranking low on such basic abilities will derive little or no benefit from such training. This is most clearly the case with patients suffering from (even mild) dementia. Training demented patients appears to result in very small treatment gains (B ckman, Josephsson, Herlitz, Stigsdotter, & Viitanen, 1991; Yesavage, 1982), and sometimes even in a decrease in performance (Zarit, Zarit, & Reever, 1982), or else it demands a quite extensive training program for relatively meager results (Diesfeldt & Smits, 1991). In this case, it seems more worthwhile to resort to the principles of behavior modification, or to train external rather than internal techniques (Camp et al., 1993; Moffat, 1989; Wilson & Watson, 1996). It may also be important to restrain our therapeutic furor from time to time. There is nothing wrong with teaching older adults correct use of an agenda or helping them in the subtle art of note taking, rather than teaching them a battery of memory tricks that even schooled memory researchers refrain from using. External aids can be very powerful, and they may take away some of the daily strains of a memory that is not working perfectly: Better to go to the supermarket with a shopping list than to return home without the bathroom tissue. For those who are interested in some expert advise on how to construe one's living ecology so that the daily hassles of sensory and cognitive aging are minimized, there is the excellent Skinner and Vaughan (1983) how-to book.

By way of a final comment, I wish to stress that even though the news about plasticity has not been so good lately (we have evidence of age-related limits that seem hardwired), there are doubts about the nature of the effect (limits on growth and even shallow effects do, after all, indicate tangible growth and real effect). Some of

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the effects seem to reside within the individuals themselves, who thus prove to be more resilient that psychologists generally think: They do not really need the training; they can boost their performance all by themselves. Depending on the focal point of the viewer (growth or decline), both an optimistic and a pessimistic view on cognitive aging can be held. I propose that we try to transcend these positions dialectically and move to what I assume is a realistic view of cognitive aging. Realism, without denial of the possibilities that still lie before the older person, but certainly without fear of looking at age-related constraints on functioning, may provide a key to a richer understanding of the complex phenomenon of cognitive aging.

Acknowledgments

I would like to thank Alfons Marcoen, Paul De Boeck, and Reinhold Kliegl for helpful discussions on earlier versions of this text. This text is partly based on my dissertation, defended at the University of Leuven, Belgium, with Alfons Marcoen advising.

Address correspondence to Paul Verhaeghen, Department of Psychology, 430 Huntington Hall, Syracuse, NY 13244 2340. Electronic mail can be sent to [e-mail].

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