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Component Processes of Memory -- 7/29/97 --

Component Processes Of Memory: Changes Across The Adult Lifespan Peter Graf & Bob Uttl Department of Psychology University of British Columbia

Running Head: Component Processes of Memory

Address: Peter Graf Department of Psychology University of British Columbia 2136 West Mall Vancouver, B.C. V6T 1Z4

Phone: (604) 822-6635 Fax: (604) 822-6923 Email: [email protected]

1

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Abstract What abilities or skills need to be recruited for free recall of a list of words, to what extent do they influence performance, and does their influence remain constant across the lifespan? These and related questions were addressed in an investigation with 163 community dwelling healthy adults. In a session that lasted about 2.5 hours, each participant received a battery of tests, including the Rey Auditory Verbal Learning Test (RAVLT), and the North American Adult Reading Test (NAART). We also assessed age-changes in motor-speed -- by means of a finger tapping test, processing-rate -- by means of the speed of reactions to a simple stimulus, and processingcapacity -- by means of a card sorting task. The results show age-declines in the scores on all tests, except for on the NAART. More detailed analysis of RAVLT performance showed agerelated declines only on the primacy and middle portion of recall, but not on the recency portion. Structural equation modeling showed that aging was associated with a decline on all three components of speed, and more importantly, that processing-rate and -capacity make distinct contributions to episodic memory test performance. The latter finding underscores the fact that speed is made-up of dissociable components.

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Component Processes Of Memory: Changes Across The Adult Lifespan Memory is a collection of interdependent cognitive abilities or functions, each with its own developmental trajectory across the life span. Previous research has targeted a few of these functions: semantic memory, also called reference or generic memory or the repository of knowledge and facts, procedural memory or the sum of our habits or skills, and episodic memory or the ability to consciously recollect specific recent events and experiences (for overviews see Kausler, 1994; Poon, 1986; Craik & Salthouse, 1992; Squire & Butters, 1992; Schacter & Tulving, 1994; Tulving, 1983). An individual’s repository of knowledge and facts grows rapidly throughout childhood and the teenage years, with growth leveling off typically around the middle of life, and from then on the knowledge pool shows either a small, steady increase or it remains constant until late adulthood (e.g., Albert & Heller, 1988; Baltes & Baltes, 1990; Bowles, 1994; Kausler, 1991; Schneider & Pressley, 1989; Wingfield, Aberdeen & Stine, 1991). Memory for habits and procedures seems to follow the same basic pattern, but it becomes functional earlier in life, even before children have the ability to talk about habits and skills and long before they acquire the metacognitive abilities for controlling habits and skills in a conscious or purposive manner (DiGuilio & Seidenberg, 1994; Graf, 1990; Howard & Howard, 1989; Schacter & Moscovitch, 1984; Schneider & Pressley, 1989). Much contemporary research has focused on direct or repetition priming, which is the change in habits and skills produced by specific prior events and experiences, and the findings suggest that priming is fully functional even in early childhood (age 2 or 3) and it remains intact well into old age (for reviews see Graf, 1990; Mitchell, 1993; Light & La Voie, 1993; Parkin, 1993; Naito & Komatsu, 1993). Finally, episodic memory or the ability to consciously recollect specific recent events and experiences shows a steep increase in childhood and through the teenage years (or even until the mid 20s), remains stable across adulthood, but then declines in old age (Craik & Salthouse, 1992; Kausler, 1994; Poon, 1986; Salthouse, 1982). For this article, we concentrated on semantic and episodic memory, and the overall goal was to gain further insights into the processing components that mediate memory performance and how they change across the adult lifespan. What abilities or skills need to be recruited for free recall of a list of words, to what extent do they (i.e., abilities or skills) influence performance, and does their influence remain constant across the lifespan? What abilities or skills must be recruited

Component Processes of Memory -- 7/29/97 --

4

for one particular semantic memory task, the North American Adult Reading Test (NAART) (Nelson, 1982; Nelson & O’Connell, 1978; Spreen & Strauss, 1991), an instrument that measures correct pronunciation of irregular rare words? These and related questions motivated the present investigation. A complex episodic memory task like free recall involves a variety of system abilities or skills and these have been described in many different ways. One widespread portrait of what is required for such tasks is provided by contemporary resource accounts of human cognition (Greenwood & Parasuraman, 1991; Hasher & Zacks, 1979; Kubanis & Zornetzer, 1981; Navon, 1984; Salthouse, 1980, 1985). Cognitive resource has been conceptualized as “any internal input essential for processing (e.g., locations in storage, communication channels) that is available in quantities that are limited at any point in time” (Navon, 1984, p. 217). More relevant to the present article, Salthouse, Kausler, and Saults (1988) explained that age differences in cognitive tasks may be at least “partially attributable to an age-related reduction in the quantity of some type of general-purpose processing resources considered necessary for efficient functioning in a broad assortment of cognitive tasks” (p. 158). Salthouse (1985, 1988, 1991, 1993) and others (Cerella, 1985; Cerella, Poon, & Williams, 1980) have translated cognitive resource to mean processing speed, and they used this operationalization as an anchor for the general slowing hypothesis, the notion that “the central nervous system is functioning at a slower rate in older adults, [and therefore] mental operation time may be the principal mechanism behind age differences in nearly all aspects of cognitive functioning” (Salthouse, 1980, p. 61). According to an alternative operationalization, cognitive resource has been equated with working memory capacity (Baddeley, 1986; Baddeley & Hitch, 1974; Daneman & Carpenter, 1980; Hasher & Zacks, 1979; Kausler, 1994; Welford, 1958), where working memory is defined as a system for holding information and for operating on it, and greater capacity means that more operations can be coordinated with each other. By this view, age-changes in cognition are assumed to reflect a decline in the system’s capacity for how much information it can hold and operate on simultaneously. One specific objective of the present investigation was to map-out the link between ageneral slowing account and a capacity account for age-changes in memory test performance. Instead of regarding speed and capacity accounts as competitors, however, we consider them to be

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complementary descriptions of the cognitive operations that mediate age-declines in episodic memory. By analogy with a micro computer, the speed of a system -- defined in terms of the amount of work performed per time unit -- turns out to be a consequence of many factors, most importantly for the present, the system’s clock-rate or the number of operation-cycles that it can run per time unit (usually measured in MHz) and its register-width or the size of the information chunks on which it operates (usually measured in bits). For this article, we will use the term processing-capacity to refer to the system’s register-width -- that which reflects the breadth of operations that it can coordinate, and we reserve the term processing-rate for referring to the system’s clock-rate. A decade ago, most desk-top computers were slow with clock-rates of .05. Figure 3

Component Processes of Memory -- 7/29/97 --

AGE

-.25*

-.40*

-.28*

MOTOR SPEED

.28*

-.67*

PROCES. RATE

PROCES. CAPACITY

.26* .84*

.18*

.54*

.80* .36*

EPISODIC MEMORY

SEMANTIC MEMORY

(RAVLT)

(NAART)

.72*

.62* .18*

.32* .13* EDUCATION

Hierarchical Regression Analysis

.51*

20

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In this final section we used hierarchical regression analyses to ferret out how much variance in episodic memory was explained by each latent variable that entered into SM7. The results from these analyses are summarized in Table 6. An initial regression analysis showed that age alone explained 29% of the variance in episodic memory, and the influence due to age2 was not significant. We also probed episodic memory with a series of hierarchical regression analyses and found significant influences due to motor-speed, processing-rate, and processing-capacity (see Table 6 for statistics). In combination, these three factors explained 35% of the variance in episodic memory, and only an additional 3% of the remaining variability could be explained by age (there was no effect due to age2). This outcome that about 90% of age-related variance in memory can be explained in terms of differences in motor-speed, processing-rate and processingcapacity replicates results reported by Salthouse (1993), thereby generalizing this finding to RAVLT performance in healthy adults. -----------------insert Table 6 ------------------

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Concluding Comments In this article, we examined age-changes in episodic and semantic memory from two different perspectives. The first perspective, which we offer as a caricatures of main-stream contemporary memory research, focuses on selective changes that occur with age, more particularly, it highlights the finding that age had different effects across tests and that it influenced the primacy and middle portion but not the recency portion of recall on the RAVLT (findings in Table 2 and in Figure 2). The other perspective, the more quantitative approach of Salthouse, Cerella, and their colleagues, builds on the general slowing account for age-related changes in cognition. We postulated three distinct components of speed -- motor-speed, processing-rate and -capacity, and the findings summarized in Figure 3 show that while aging has a negative influence on each of these components, the latter two made separate and different contributions to memory performance. To our knowledge, the findings in Figure 3 constitute the first evidence that age-changes in memory are mediated by distinct components of speed, thereby extending previous efforts by Salthouse and his colleagues (Salthouse, 1993, 1994; Salthouse & Babcock, 1991). More important, both sets of findings underscore the selective nature of the cognitive changes that accompany aging, thereby indicating that aging is not the unitary phenomenon that might be inferred from the general slowing hypothesis, that aging should not be conceptualized as being akin to computers from yesteryear (i.e., slow systems with narrow registers). The particular paths and coefficients shown in Figure 3 were, of course, influenced by the specific instruments used to index the different components of speed in our study. In previous investigations that concerned the general slowing hypotheses, speed was indexed by means of a variety of different instruments. One of the most often used indexes, the one that seems to have the most predictive power (Salthouse, 1985), is performance on the digit symbol subtest from the Wechsler Adult Intelligence Scale. We also administered the digit symbol subtest in the present investigation, but only to about 2/3 of the participants. Structural equation modeling showed that the addition of the scores from this test did not change the pattern of paths in the model. Consistent with how processing-capacity was operationalized for the present investigations, the digit-symbol test is similar to the card sorting task, and for this reason, we also investigated models in which digit-symbol test performance was used to index processing-capacity (i.e., instead of card sorting test performance) and this also did not change the findings. In light of this

Component Processes of Memory -- 7/29/97 --

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outcome, the digit-symbol test might easily have been substituted for card sorting in the present investigation (note: r = .76 between digit symbol and card sorting scores), especially because it has the advantage of being a paper and pencil instrument which is highly portable. Nevertheless, we opted for the card sorting test, a less-well established instrument that requires a computer (at least our version of this test) for two main reasons: first, in order to minimize the motor component associated with test performance (the digit-symbol test has a larger motor component), and second, so as to equate the motor actions required for each of our indexes of speed. The general slowing hypothesis offers a particular quantitative description of age changes in the processing system, and one objective of the present investigation was to show that this description is different but commensurate with those provided by contemporary memory investigations, for example. Most contemporary memory investigations emphasize dissociations or selective influences due to aging, or selective influences due to other factors such as special populations and a wide range of study and test trial manipulations (Graf & Masson, 1993). The present investigation established that speed, defined in terms of the quantity of work that a system performs per unit time, is also made-up of dissociable components. We had three different indicators for speed (e.g., finger tapping, simple reactions, card sorting), and while performance on each declined with age, the different components did not decline at the same rate, and they made different contributions to memory test performance. In future research, we will investigate more closely the link between these different components of speed, how they are influenced by various experimental manipulations (e.g., divided attention tasks), and how they operate in special populations (e.g., patients with Huntington’s Disease).

Component Processes of Memory -- 7/29/97 --

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Author notes This research was supported by operating grants from the British Columbia Health Research Foundation and by the Natural Sciences and Engineering Research Council of Canada to P. Graf, and by a Natural Sciences and Engineering Research Council of Canada graduate scholarship to B. Uttl. We thank Jennifer Shapka for assisting with the preparation of this manuscript, and Nadine Bruce for assisting with data collection. Special thanks also go to the staff of the Kerrisdale Community Centre whose cooperation benefited many aspects of the study. Correspondence about this article should be addressed to Peter Graf, Department of Psychology, University of British Columbia, 2136 West Mall, Vancouver, B.C., V6T 1Z4. Email: [email protected].

Component Processes of Memory -- 7/29/97 -Table 1 Demographics, Education, Employment, and Health of Research Participants. Age group 16-29 30-39 40-49 50-59

60-69

70+

n

19

23

30

31

29

31

Sex Men Women

7 12

11 12

6 24

4 27

8 21

12 19

English first language Yes No

14 5

19 4

25 5

25 6

23 6

27 4

Education 0-8 years High school College/University Post-graduate

0 3 16 0

0 2 18 3

0 5 24 1

1 6 20 4

0 6 17 6

2 8 14 7

14.3

15.7

14.7

14.4

14.8

14.3

1 13 3 4 2 0

1 19 4 1 4 1

0 12 8 1 5 5

0 2 5 1 1 20

0 0 1 0 0 30

21.7 91.3 4.0 2.3 8.7 1.2 3.4

26.7 80.0 3.1 2.5 23.3 1.5 3.0

32.3 74.2 3.8 4.3 25.8 1.6 2.9

34.5 89.7 4.6 3.3 27.6 1.4 3.3

3.0 14.0 3.1 26.8

3.1 13.2 3.3 23.6

3.1 14.2 3.4 24.4

Overall years of education Employment Student Employed/full-time Employed/part-time Unemployed/Seeking work Unemployed/Not seeking work Retired Health status Physical/emotional problems (%) Sports participation (%) Sports frequency (times/week) Doctor visits (times/year) Medication (%) Health trouble Overall health ratings

5 4 3 7 0 0

5.3 73.7 3.7 2.1 10.5 1.1 3.4

Vision ratings 3.3 3.6 CVSI 1 14.1 13.1 Hearing ratings 3.4 3.7 HSI2 22.2 22.1 ♣Age effects were computed by regression analysis. 1 Color Vision Screening Inventory (Coren & Hakstian, 1988) 2 Hearing Screening Inventory (Coren & Hakstian, 1992) *p < .05, +p < .10

Age♣ F(1,162)

32 Age2♣ F(1,161)

.67

.30

38.7 83.9 4.0 3.2 22.6 1.4 3.2

7.52* .51 1.61 1.22 3.40+ 3.16+ .39

1.01 .04 .05 2.62 .85 3.56+ 6.36*

3.2 13.7 2.8 27.2

2.35 .03 15.51* 7.17*

1.51 .18 .83 .48

Component Processes of Memory -- 7/29/97 -Table 2 Means, Standard Deviations (in parentheses), and Regression Analyses Results, for Various Measures of Cognitive Ability. Age group Age♣ Age2♣ 16-29 30-39 40-49 50-59 60-69 70+ F(1,162) F(1,161) NAART1

38.68 (6.70)

40.07 (9.46)

43.13 (8.79)

43.78 (8.17)

43.06 (10.78)

45.81 (8.42)

9.63*

.41

9.17 (2.44)

8.44 (2.34)

7.77 (1.78)

7.79 (1.88)

7.00 (1.79)

6.05 (1.98)

38.87*

.06

Trial 2

12.05 (1.90)

10.87 (2.03)

10.96 (2.12)

10.19 (2.14)

9.79 (2.21)

8.62 (2.28)

36.69*

.02

Trial 3

13.22 (1.59)

12.96 (1.30)

12.11 (1.59)

12.26 (2.05)

11.11 (1.90)

9.85 (2.27)

56.76*

3.11+

53.61 (6.21)

54.15 (5.99)

52.74 (6.72)

51.32 (5.50)

48.49 (5.80)

47.39 (5.86)

29.39*

1.82

47.11 (6.11)

48.77 (6.18)

46.13 (5.48)

45.51 (4.36)

44.15 (6.18)

42.88 (4.75)

17.70*

1.28

275.93 (29.24)

285.62 (38.56)

295.69 (41.94)

300.26 (40.28)

308.45 (48.87)

330.33 (52.84)

26.14*

1.18

Trial 2

275.96 (38.45)

283.44 (35.59)

297.46 (40.93)

293.90 (37.32)

294.38 (46.42)

317.77 (42.21)

14.78*

.43

Trial 3

272.89 (29.62)

276.61 (30.76)

296.46 (43.16)

301.36 (41.34)

290.76 (44.50)

315.82 (41.91)

15.33*

.00

Trial 4

270.94 (32.87)

282.46 (33.72)

294.54 (38.01)

298.36 (42.66)

296.51 (44.36)

315.27 (46.17)

17.68*

.23

614.50 (85.85)

621.09 (79.27)

659.01 (94.18)

684.69 (72.00)

752.56 (87.93)

792.80 (125.27)

77.98*

1.53

744.05 (99.42)

768.71 (115.98)

818.17 (108.49)

885.33 (117.26)

959.87 (138.48)

1004.01 (144.76)

100.95*

.09

885.37 953.82 1039.75 1146.47 1229.79 (172.61) (178.96) (186.55) (207.49) (204.91) ♣Age effects were computed by regression analysis. 1 North American Adult Reading Test (Blair & Spreen, 1989; Spreen & Strauss, 1991) 2 Rey Auditory Verbal Learning Test (Spreen & Strauss, 1991) *p < .05, +p = .08

1366.17 (257.19)

103.45*

.22

RAVLT2 List A Trial 1

Finger Tapping Dominant Hand Other Hand

Simple Reaction (ms) Trial 1

Card Sorting (ms) 0 Distractors 4 Distractors 8 Distractors

33

Component Processes of Memory -- 7/29/97 --

34

Table 3 Test-Retest Reliabilities, Block-Averaged Estimated Reliabilities, and Published Reliabilities for Indicators of Latent Factors. Test-retest Estimated Ri♣ Ri♦ NAART1

.94♠

RAVLT2

.77, .78

Finger Tapping Dominant Hand Other Hand

.91, .91, .87, .92 .88, .86, 92, .86

Simple Reaction

.72, .76, .81

.98 .97

Card Sorting 4 Distractors .90 .95 8 Distractors .87 .93 ♣Values were computed between successive trials or blocks. ♠Published reliability estimate (Spreen & Strauss, 1991) ♦Values are estimated reliabilities of the scores averaged across several blocks of trials, which were used as indicators of the latent factors in structural equation modeling. 1 North American Adult Reading Test (Blair & Spreen, 1989; Spreen & Strauss, 1991) 2 Rey Auditory Verbal Learning Test (Spreen & Strauss, 1991)

Component Processes of Memory -- 7/29/97 -Table 4 Summary of Model-Fitting Approach. Model Commentary df p χ² Measurement models (MM) 75.23 67 .23 MM1 Free correlations among linear age, age², education, motor speed, reaction speed, search speed, RAVLT, and NAART. MM2 Same as MM1 but age² paths set to 77.64 73 .33 zero. MM3 Same as MM2 but with age² removed 68.21 59 .19 from the model. 68.89 60 .20 MM4 Same as MM3 but with correlation between age and education set to zero. Structural models (SM) SM1 The component processing model: 126.32 65