Teaching an amnesic a complex cognitive skill

BRAIN AND COGNITION 8, 253-272 (1988)

Teaching an Amnesic a Complex Cognitive Skill

NEIL CHARNESS

Universi1.v of Waterloo. Waterloo, Ontario, Canada ML 3GI

WILLIAM MILBERG

GRECC. VA Medical Centrr. We.st Roxbrrry, Mas.sachrrsetts 02401

AND

MICHAEL P. ALEXANDER

Boston University School of Medicine. 85 E. Nenston Street, Boston, Massachusetts 02118

G.P., a Korsakoff’s amnesic. was able to learn an algorithm for squaring two- digit numbers mentally over a 7-day period at a rate comparable to that of age- matched controls. He failed to show normal positive transfer to specific problems or to specific numbers used in components of the task. He also exhibited slight improvement in simple naming speed, forward digit span, simple multiplication speed, but no apparent improvement for the recall of repeated supraspan digit strings. He was unable to state the algorithm he had learned to square two-digit numbers, though he could implement it successfully. The results suggest that the compilation of a skill may involve two dissociable components: composition and proceduralization, with the former, but not the latter, occurring at normal rates for Korsakoff’s amnesics. o 1~x8 Academx PES. IK.

New demonstrations ofpreserved skill learning in amnesics (e.g., Glisky, Schacter, & Tulving, 1986) have refocused attention on what amnesics can and cannot learn. Perhaps fortuitously, theories of skill acquisition have recently undergone considerable refinement (e.g., Anderson, 1982,

This work was supported by grants to N. Charness from NSERC A0790, SSHRCC 45l- 84-4284, and by grants to W. Milberg by the VA Merit Review 097443765001, and by NIA Grant ROlAG03354-03, as well as by Grant NS06209 to H. Goodglass at the Boston University School of Medicine. We thank J. 1. D. Campbell for supplying the Commodore PET programs that were subsequently modified by the first author to run on the Commodore 64. Address correspondence and reprint requests to Dr. Neil Charness. Psychology De- partment, University of Waterloo, Waterloo, Ontario, Canada N2L 3Gl.

253 0278-2626/88 $3.00

Copyright 0 1988 by Academic Press, Inc. All rights of reproduction in any form reserved.

254 CHARNESS, MILBERG, AND ALEXANDER

1987). In this paper we focus on the use of Anderson’s theory of skill acquisition (1982, 1983, 1987) to help understand the learning of a complex skill by a Korsakoff’s amnesic. The task we examine is the squaring of two-digit numbers mentally, one that is readily decomposable into component processes.

Korsakoff’s amnesia is characterized by a severely impaired ability to acquire new information. It is often accompanied by normal short-term memory, as assessed by tasks such as forward digit span and normal intelligence test performance. Such anterograde amnesia is often combined with a graded retrograde amnesia for past events (Albert, Butters, & Levin, 1979; Marslen-Wilson & Teuber, 1975). Nonetheless, it is possible for amnesics to acquire new motor skills (Cermak, Lewis, Butters, & Goodglass, 1973). The range of skills that such patients and other amnesics can acquire includes perceptual-motor skills such as mirror tracing, rotor pursuit, maze learning, jigsaw puzzle assembly, and reading inverted print (Squire & Cohen, 1984).

In some cases, more purely cognitive skills have also been acquired, such as inducing the continuation of a Fibonacci number series (Wood, Ebert, & Kinsbourne, 1982) and learning simple programming concepts (see Glisky et al., 1986). Attempts, however, to demonstrate acquisition of complex problem solving skills such as the Tower of Hanoi task, have not been successful with Korsakoff patients (Butters, Wolf, Martone, Granholm, & Cermak, 1985).

Korsakoff’s amnesics can also acquire other types of information, such as affective reactions (Johnson, Kim, & Risse, 1985). An important aspect of all these cases of successful learning is that the patient usually denies having done the tasks before, that is, fails to show memory for previous learning episodes.

Among the hypotheses that attempt to account for this pattern of findings are Kinsbourne and Wood’s use of Tulving’s Episodic/Semantic memory distinction, Squire and Cohen’s use of the Procedural/Declarative learning distinction, and Schacter’s use of the implicit/explicit memory dichotomy.

Kinsbourne and Wood (1975) argue that amnesics have relatively preserved access to semantic memory, but a profound dislocation of access to episodic memory traces, the records of specific personally experienced events. Squire and Cohen (1984) argue that amnesics can access “memory without record,” information about events in the form of the perceptual and cognitive processes that were utilized in encoding an activity, but without access to the record of having carried out these analyzing operations. The distinction between “memory with record” and “memory without record” has also been drawn by using the “procedural/declarative” distinction of computer science (Winograd, 1975).

Another argument advanced to account for the distinction between

AMNESIA AND SKILL LEARNING 255

what can and cannot be learned by amnesics originates from work on priming, e.g., Schacter (1985, 1987), Schacter and Graf (1986). Schacter argues that there is a difference between items already in the repertoire, so-called unitized or “implicit” associations, and new associations between previously unrelated items, those needing an “explicit” association. This distinction is similar to that between “vertical” and “horizontal” associations proposed by Wickelgren (1979). When amnesics are asked to learn unitized items (e.g., sour-grapes, two items with low association strength in free association), they can do so much more successfully than for nonunitized ones (e.g., sour-potatoes). Similarly, there is successful priming for unitized, but not for nonunitized items.

A serious problem with many of these distinctions is that they have been drawn a posteriori. (Another concern is that it is difficult to tease apart the cognitive and motor factors responsible for acquiring skill at overt motor tasks.) If an amnesic patient learns a task, the task has been considered to be a procedural one. If the task was not learned, it is deemed to require declarative learning. Because of this definitional problem some researchers have chosen to distinguish between what amnesics can learn and what they cannot learn based on the conditions of recall used, hence “implicit” versus “explicit” memory (Schacter, 1987).

We chose to investigate the teaching of a complex cognitive task, an algorithm used by mental calculators to square multidigit numbers mentally. Our hypothesis is that skill acquisition requires a number of distinct component processes. Some processes can be acquired at a normal rate by Korsakoff amnesics, while others cannot. We draw on two distinctions made by Anderson (1982, 1983, 1987): composition and proceduralization.

Anderson’s theory assigns special status to two systems: declarative memory and production memory. Anderson argues that early in skill acquisition actions are executed by general productions, rules of the form “IF (condition) THEN (action),” using knowledge that is represented declaratively in working memory as propositions. Initial performance is slow because the productions are general, hence many are needed for a given task, and because all the data needed by the productions must pass through a limited-capacity working memory (which holds the symbols representing a “condition”).

It is assumed that a production can be matched and executed in one unit of time no matter what its internal complexity. With practice, the productions are “composed” (automatically), such that a new complex production can apply and perform in one unit of time the actions that earlier required two or more productions.

In parallel with composition, productions are slowly specialized (proceduralized) SO that they now bypass the process of interpreting declarative knowledge via working memory. Such specialized productions “bind” local values into what were earlier “open slots” for variables in the


production rule. Another mechanism for speeding up performance is “strengthening.” Productions are selected for possible matching based on their strengths. Repetition boosts the strength of a production. Thus, even for simple tasks where little improvement could be expected through composition or proceduralization, strengthening can still speed up performance.

An example, provided by Anderson (1982), of a general production to dial a telephone number might be IF (the goal is to dial a number), THEN (dial the first digit). Another production might be IF (the goal is to dial a number and the first digit is dialed), THEN (dial the second digit). A composed version might be IF (the goal is to dial a telephone number), THEN (dial the first digit and dial the second digit), It can accomplish the task of dialing two digits in the same time that either predecessor could dial only one digit.

In the case of both the initial and the composed production, the values of the variable “digit” must still be obtained from working memory. Eventually, proceduralization might result in a highly specialized production: IF (the goal is to dial an emergency number), THEN (dial 9-1- 1). In the latter case, the specific digits become bound within the specialized production and working memory is consulted only for whether the goal is set to dial an emergency number, not for the digit values.

The algorithm we attempted to teach is based on a rearrangement of the algebraic expression (a + c) * (a - c) = a2 - c’, which yields a’ = (a + c) * (a - c) + c*. More concretely, to square 98, find a constant to add to it to get the nearest multiple of 10 (2, yields 98 + 2 = 100). Subtract the constant from the target to get the other number (98 - 2 = 96). Find the product of these two numbers (100 * 96 = 9600). Add the square of the constant (2* = 4) to the product to get the answer (9600 + 4 = 9604). This procedure can be applied recursively to obtain answers to larger squares, and has been taught successfully to young, middle-aged, and older adults (Charness & Campbell, 1988).

There appear to be two phases to skill acquisition with this task (see Campbell, 1982). At first the algorithm must be interpreted in a step by step fashion, with retrieval of the steps from long-term memory. Later the procedure appears to have become “compiled,” such that the results of one step lead directly to execution of the next step (possibly because of the collapsing of steps: composition), and the specific operations become “proceduralized” to deal with unique cases.

It is of interest to see whether these two facets, composition and proceduralization, can be dissociated. There is already evidence in the literature that proceduralization occurs abnormally slowly for amnesics. Even when amnesics are able to learn a new task at a normal rate, such as reading inverted print, they fail to show equivalent improved performance on specific repeated words (Cohen & Squire, 1980). In this study, we


attempted to teach the mental squaring algorithm to G.P., a 64-year-old Korsakoff’s amnesic, to see whether this multifaceted cognitive skill could be acquired, and if so, whether proceduralization proceeded in parallel with composition.

We also examined several other multisession tasks, digit span, and repeated supraspan digit strings, as control tasks to assess learning by simple repetition. (We also used a video game task, but since the video game was too difficult for a young control subject to learn, it will not be discussed.) There is evidence that simple repetition by itself is not sufficient for teaching new vocabulary to other amnesics (e.g., Gabrielli, Cohen, Huff, Hodgson, & Corkin, 1984).

CASE REPORT

G.P. is a 64-year-old right handed man. He was educated through high school and had been employed as a salesman until the age of 55 when chronic alcoholism led to a series of hospitalizations and loss of job. From age 55 to 59 the patient drank heavily and had multiple hospitalizations for alcoholic withdrawal seizures and alcoholic gastritis. A medical evaluation at age 57 revealed a normal mental status, neurologic examination, and electroencephalogram. CT scan demonstrated mild sulcal enlargement. He was admitted to a community hospital at age 59 for a series of tonic- clonic seizures. Diagnosis included alcohol withdrawal seizures, alcoholic hepatitis, and aspiration pneumonia. At transfer to the VA hospital 3 days after admission, he was awake and alert but disoriented and severely amnesic.

Detailed neurologic assessment 3 weeks after admission revealed only mild peripheral neuropathy. Gait was normal. There was no nystagmus or limb dysmetria. He was alert and cooperative. Digit span was eight forward and seven backward. Serial subtractions were quick and accurate. He was oriented to place but not to day, month, or year. He had no idea why or for how long he had been hospitalized. He could recall one of four words after 5 min. He named the president and immediate past president, but he had no knowledge of any prominent events over the previous several years. His knowledge of World War II and events of the 1950s was excellent.

A neuropsychological evaluation was completed 6 weeks after admission. The clinical findings were confirmed. On the WAIS, verbal IQ was 134 with little scatter on subtests; the arithmetic scale score was 17. Per- formance IQ was 108; there was some scatter. The Wechsler Memory Scale quotient was 90. Immediate recall of logical memory passages was 9/23, of paired associate learning 7/21 (with no hard pairs), and of visual reproductions 3/14. There was moderate difficulty with identifying famous faces from the 1960s and 1970s but no deficits for earlier decades. On tests of memory utilizing proactive interference there was marked im-


pairment and perseveration. EEG was normal. CT scan demonstrated diffuse sulcal enlargement and ventricular enlargement with particular increase in the width of the third ventricle. All tests of liver and metabolic functions were normal,

The patient was followed for the subsequent 4 years. He had several tonic-clonic seizures, last occurring about 6 months prior to the current assessment. He remains on dilantin and phenobarital with low therapeutic blood levels. He has had no alcohol in 4.5 years. He lives at home with his wife who believes that there has been no change in his memory, but that he has become depressed because of his inactivity. Reevaluation before this study at age 64 was basically unchanged from 4 years before. He could recall 1 of 4 words after 5 min. He recalled very scant information about recent historical events and no information about major news stories of the previous 10 years (e.g. Watergate, space shuttles, Iran crisis). His affect was consistently depressed, and he complained of his inactivity which he blamed on his memory problems.

At the time of testing, the logical memory stories from the Wechsler Memory Scale were readministered. G.P. was able to recall an average of 7/23 items immediately after hearing the story, and an average of O/23 after a lo-min delay.

METHOD

Control Subjects

A group of 16 older subjects who took part in a different study (see Charness & Campbell, in preparation) served as a control for all but the Span and Hebb-repetition tasks described below. They were community-dwelling adults living in the cities of Kitchener and Waterloo, Ontario. Their mean age was 67 (SD = 8.5) and they reported having 15 years of formal education (SD = 2.5), though in Ontario, high school lasts 13 years. Thus they were slightly older and marginally more educated than G.P. The tasks were presented via a Commodore PET 2001 microcomputer slaved to a monochrome monitor, and characters were displayed as white on black. Timing was done with a software program that had millisecond accuracy.

Materials

The format for testing the patient over the 7-day period is shown in Table 1. All tasks were administered via a Commodore 64 microcomputer attached to a Commodore

1702 color monitor. Voice response times were recorded with a hand-held microphone attached to a voice response relay connected through the Commodore’s User Port. All other responses were entered on the keyboard. Response timing was done in Commodore BASIC, via the TI function, and was accurate to approximately + 34 msec. Visual displays were presented as black characters on a light gray background.

Tasks NAME. The naming task (NAME) consisted of 60 trials (10 repetitions each) of single-

digit numbers between 0 and 9 presented randomly with the constraint that no number was repeated on consecutive trials. After a brief pause a second block of trials presented 64 three- or four-digit numbers which were a subset of the square answers for numbers


TABLE I ORDER OF PRIMARY TASKS DONE BY G.P. OVER 7 CONSECUTIVE DAYS

Day Tasks

1 (AM) Naming digits from 0 to 9. and three- or four-digit square answers (NAME).

2

3 4 5 6

7 (AM) 7 (PM)

Multiplying single digits in the range 2 x 2 to Y x Y (MULT). Doing subcomponents of the squaring procedure in isolation (COMP). Forward digit span via a staircase procedure. followed by 30 trials of

span + I digits, with every third trial repeated (SPAN-HEBB). Ten trials of a video game (VIDEO). MULT. squaring a subset of numbers between I and 99 (SQR). SPAN-

HEBB, VIDEO MULT. SQR. SPAN-HEBB, VIDEO MULT. SQR. SPAN-HEBB. VIDEO MULT. SQR, SPAN-HEBB. VIDEO MULT. SQR. SPAN-HEBB. VIDEO MULT. SQR (all numbers between I and 99). SPAN-HEBB. VIDEO NAME, MULT. COMP. SPAN-HEBB. VIDEO.

between I and 99. Instructions urged G.P. to name the numbers as quickly as possible. using the format of thousand. hundred, etc., for three- and four-digit numbers (e.g.. 2916 was to be named as “two thousand nine hundred and sixteen”). Trials occurred in a continuous sequence with a pause between blocks. A fixation point appeared for I sec. flashed twice over 1.5 set and was replaced by the digit(s) to be named. The verbal response triggered a voice key and erased the digit(s). A few seconds later the next trial commenced.

MULT. The multiplication (MULT) task consisted of two blocks of the 36 problems between 2 x 2 through 9 x 9. Each problem appeared once in each order (e.g.. 2 x 3, 3 x 2) across blocks. Order of problems was randomized within blocks with the constraint that consecutive problems could not involve either the same answer or the same operands. Instructions urged G.P. to provide the answer verbally as quickly as possible. The verbal response triggered a voice key and erased the problem. and the experimenter entered the response. Trials occurred in a continuous sequence with a few seconds between trials, and a long pause between blocks. A trial started with a flashing fixation point at the center of the screen, and the problem occurred on what would have been the third flash, with the digits separated by a multiplication sign, the latter centered where the fixation point had been.

COMP. The components of squaring task (COMP) consisted of trials that tested the individual steps of the squaring procedure in isolation. On mixed sets of trials G.P. was required to find the nearest multiple of 10 (NMT) for a target number: e.g., given 27, generate 30. Other trials required generating the other number (OTN) for a target that is as far from the target as is the nearest multiple of IO, e.g., given 27. generate 24; the product of the nearest multiple of IO and the decade digit of the other number (PI), e.g., what is 30 x 20; the product of the nearest multiple of 10 and the units digit of the other number (P2). e.g., what is 30 x 7; the sum of the latter two products (SUM), e.g., what is 600 + 210: and the sum of the two products plus the square of the constant (S + C’), e.g., what is 810 + 3’. For the NMT and OTN operations, four problems involved a difference of 1, 2, 4, or 5 and two involved a difference of 3. There were 16 PI and I6 P2 problems and 32 which involved a difference of 3. There were I6 PI and I6 P2 problems


and 32 which involved taking products which were external to the squaring procedure (EPl, EP2). There were also 16 SUM problems and 16 that involved sums external to the procedure (ESUM). Finally, there were 16 S + C’ problems, all from the squaring environment. The set of 148 total problems was ordered randomly. Trials where a misperception of the digits occurred or where the trial was terminated incorrect]y were repeated at the end. A verbal description of the desired operation was presented before the numbers to be operated on were shown on the screen. The experimenter(s) elaborated on the instructions before each trial, and prompted G.P. during trials when necessary. When GP announced the answer the experimenter pressed a button to halt the timer and entered the response. When G.P. was ready the next trial commenced. Both speed and accuracy were stressed.

SQR. Squaring (SQR) involved 66 problems between 1 and 99: the known numbers I- 12 (Class I), decade numbers: 20. 30, 40. 50, 60. 70, 80. 90 (Class 2); numbers ending in 5: 15, 25, 35, 45, 55, 65. 75. 85, 95 (Class 3): and a subset of the numbers requiring all steps of the algorithm, designated the practice set: 17. 18, 21, 24. 26, 29, 32, 33, 37, 38, 41, 44, 46, 49, 52, 53, 57. 58, 61, 64, 66, 69, 72, 73. 77, 81, 84, 86. 89, 92, 93 (Class 4). The latter were produced by dividing all class 4 problems into two sets (practice and transfer) balanced as closely as possible for the size of the constant to reach NMT, the decades digit for NMT, and OTN and size of carries in the SUM stage. (See Charness & Campbell. 1988.) On the final session of squaring the full set of problems from 1 to 99 were presented, with the second subset of the Class 4 problems designated as the transfer set. The number appeared on the screen following an instruction to square it and work through the problem by speaking out loud. The experimenter pressed a button to halt timing when the full answer was given. and then keyed in the response. The order of trials was randomized and incorrectly terminated trials were rescheduled at the end. Feedback was provided after the answer was entered. Several practice trials preceded the main sequence.

For the first three squaring sessions the algebraic equation, CI’ = (u + c.) * (a - c) + cl, was left in view on the table in front of the monitor. On trial 14 of Day 5 the formula was removed. In early sessions the experimenter(s) prompted and encouraged G.P. during the task and reminded him of the procedure before and occasionally during trials. In later sessions as G.P. acquired skill, the prompting was diminished. This support partly resembles the “method of vanishing cues” described by Glisky et al. (1986).

SPAN-HEBB. The SPAN-HEBB task was divided into two parts. Foward digit span was assessed in the first half by using staircase procedure, starting with three digits and incrementing by one digit if a trial was correct, decrementing string length by one if a trial was incorrect. The procedure was halted when six reversals of direction were obtained, and the mean of the string lengths at the last five reversals, rounded up to the nearest whole digit, served as the measure of span. In the second half 30 trials of span + 1 digit strings were presented for recall. The string given on the third trial was repeated on the 6th. 9th, 12th, etc., trial, unless it was recalled correctly, in which case it was replaced by a new string of equal length, which in turn was repeated at the same interval. Strings were randomly generated from the digits 0 through 9, with repetitions within strings permitted. Numbers were presented serially at the center of the screen at about one digit/per second. The trial began with the presentation of an asterisk accompanied by a tone and ended with an asterisk accompanied by a tone. Trials were initiated when G.P. was ready. No feedback was provided.

Procedure On each day, G.P. was taken from his ward to the experimental room, M.A.‘s office.

He was interviewed while the tasks were being prepared and following rest breaks between tasks. The interviews assessed his memory for the room, the tasks, the names of the experimenters, and other general information such as when he had last been seen, how long sessions lasted, etc. On the 7th day the Wechsler Memory Scale was also administered.


The sessions were recorded on cassettes. Sessions lasted between 1.5 and 3 hr, and breaks were arranged at the ends of tasks, including a 1% to 20-min break in the middle of the session when the patient returned to the ward recreation room to smoke and read or watch television. The order of presentation of tasks is shown in shown in Table 1. All sessions but the eighth began in the morning between 9:00 and IO:30 AM. Day I began on Tuesday, August 6, 1985. N.C. was present on all days and W.M. on Days 1, 2, and 7.

The experimenter(s) attempted to be as helpful and encouraging as possible during all the tasks and provided a great deal of prompting and modeling during the SQR and COMP tasks. All tasks were controlled and scored via the computer system.

RESULTS

Naming time. As seen in Fig. 1, G.P. was significantly slower than the controls in rapidly naming both digits in the range 0 to 9, as well as square answers, both before and after practice in squaring. All t values for comparisons of trimmed means, those with 2.5 SD outliers removed, exceeded 13. (Here and for all other such comparisons the t test assesses whether G.P.‘s mean performance differs from the mean of the age controls, using control group variability to compute the standard error term. Given the large number of potential comparisons, the rejection region was set at p < .Ol, two-tailed, requiring a t for 15 df to exceed 2.947.) G.P. did show significant improvement for both single-digit naming, t(115) = 2.2, p < .05, and for square naming, t(121) = 6.3, p < .Ol.

Simple multiplication. As seen in Fig. 2, G.P. did not show much improvement over sessions with speed of multiplying single-digit numbers

1200 T

1

M S E C

400 ANSWERS

INTEGERS

200 SQUARE ANSWERS

BEFORE PRACTlCE

FIG. 1. Mean naming time for G.P. and controls on single-digits (O-9) and three- and four-digit answers to squaring problems.


<&c, 960.

eoo-

aoo-( , 0 1 2 3 4 6 6 7 a

SESSIONS

FIG. 2. Trimmed mean correct time to multiply single-digit problems in the range 2 x

2 through 9 x 9 for G.P. and controls.

until the eighth session. All means presented are trimmed to exclude 2.5 standard deviation outliers. In contrast the group of 16 age controls showed the usual learning function. Much of the improvement across sessions for an overlearned task such as simple multiplication arises from learning specific information about the problem set (Campbell, 1985). At session 1 there is no significant difference between G.P. and his age controls for correct response time, t < 1, despite an expectation that compromised cortical functioning would slow his responses generally, as appeared to be the case for naming time. This equivalence suggests that G.P.‘s high IQ and superior performance on the WAIS arithmetic scale does not confer an advantage over the age controls. Only at the sixth session was there a significant difference between G.P. and the control group (t = 4.4), though the difference was marginal at session 4 (t = 2.795). G.P., however, committed only one error over all sessions, despite the fact that instructions stressed speed, whereas the controls averaged about two errors per session. Even taking the sudden drop in session 8 into consideration, it is obvious that G.P. does not acquire skill in this task the same way as age-matched controls.

Digit spun. The specific sequence of string lengths encountered during each session (including the starting one of 3) was entered into an ANOVA, treating each of the seven sessions as a different “group.” The slight improvement across sessions was not statistically significant, F(6, 86) =


1.88, p > .05. Digit span, defined as the mean value of the string length at the last five changes in direction, increased from six digits on the first session to eight on the seventh. The values across sessions were: 5.6, 6.4, 6.2, 7.6, 7.0, 7.2, 8.2.

Hebb repedtion. The mean number of digits reported in the correct serial position in the string was computed for both repeated (N = 8) and nonrepeated (N = 22) supraspan strings for each session. t tests were done for each session, a very liberal test of whether there was any advantage in serial recall for repeated strings. In no session was there a significant difference (p < .05) between repeated and nonrepeated strings, with means for nonrepeated and repeated strings, respectively, across sessions being (4.1, 4.0); (6.1, 6.4); (6.5, 5.0); (5.5, 7.4); (5.4, 6.75); (7.0, 6.7); (4.7, 4.2).

The lack of learning by G.P. contrasts with weak learning for amnesics reported by Baddeley and Warrington (1970). Procedural differences may mediate this discrepancy. We established digit span for the subject and defined supraspan as span plus one (as opposed to choosing eight digits arbitrarily), repeated every third string starting with the sixth trial (as opposed to every second string), and replaced correctly reported strings. Further, when Baddeley and Warrington did a t test on repeated versus nonrepeated strings for their amnesic group, they did not show significant differences. As Drachman and Arbit (1966) have shown for patients with bilateral hippocampal lesions, even when supraspan strings are repeated continuously in a trials to criterion procedure, there is little evidence of improvement. We conclude that, if there is learning by amnesics for repeated supraspan strings, it is quite weak.

Mental squaring: Practice problems. First, a test for whether G.P. and the controls differed generally across sessions was conducted as follows. The trimmed correct reaction time for each problem type (Class l-4) was entered as a “subject” in a two-factor within-subjects ANOVA (G.P./Control; Sessions l-5). Both main effects and the interaction were significant, the latter being F(4, 12) = 3.789, p < .05. The means (representing average performance over all problem types) are shown in Fig. 3. This analysis indicates that the rate of improvement across sessions was greater for G.P. than for the controls, probably because of his very slow start in session 1.

Second, more detailed contrasts were made for each problem type, using I tests. Table 2 shows that G.P. followed response time learning functions over the first five sessions that closely approximate those of his age-matched controls, though it must be remembered that in early sessions he had the benefit of prompting and a visual reminder of the algorithm that the control group did not have. It is obvious that G.P. was considerably slower at session 1 in every condition, and this is borne out by significant differences (p < .Ol) on trimmed correct response


30

1 26-

20- s1:_I_ AGE 67

04 I 0 1 2 3 4 6

SESSION

FIG. 3. Trimmed mean correct reaction time averaged across problem types for mental squaring for G.P. and controls.

times: for Class 1 problems, t(l5) = 7.6; For Class 2, t(l5) = 3.71; for Class 3 problems, t(l5) = 4.5; and for Class 4 problems, t(l5) = 4.4

By session 2, G.P. was responding as quickly as the control group in every condition but Class 2 (the decade problems) (t( 15) > 13), including the most difficult problems, those requiring the full algorithm (Class 4). This pattern of no differences in performance on Class 3 and Class 4 problems continued through the remaining sessions. Class 1 problems continued to be significantly slower on sessions 3, 4, and 5, while Class 2 problems were significantly slower on sessions 3 and 4. Note that Class 1 problems are similar to the simple multiplication problems, though they range from 1 to 12 rather than 2 to 9, and are embedded among ones requiring different operations. In summary, after the first session G.P. was squaring two-digit problems mentally as efficiently as age-matched controls.

In general, there were few differences in error rate between G.P. and the controls. G.P. committed no errors on Class 1 and Class 2 problems on any session, with the controls committing between 0 and 0.5 errors. On Class 3 problems, G.P. committed between 0 and 3 errors across sessions, with the controls making between 1 and 4 errors. On the Class 4 problems there were no significant differences in error rates at any session between G.P. and the controls: Means were 14, 13.8; 7, 10.9; 11, 10.9; 5, 8.6; and 8, 7.4 for G.P. and controls, respectively. Thus, the RT data convey an accurate picture.

TABL

E 2

TRIM

MED

M

EAN

CORR

ECT

RESF

QNSE

TI

ME

FOR

G.P.

AN

D CO

N.I.R

OLS

ON

THE

FOUR

CL

ASSE

S O

F SQ

UARI

NG

PROB

LEMS

(I-

12,

DECA

DE,

TWO-

DIGI

T EN

DING

IN

5,

O

THER

S FR

OM

13 T

O

99)

__--

____

_

G.P.

Co

ntro

ls __

___

___~

Sess

ion

Clas

s 1

Clas

s 2

Clas

s 3

Clas

s 4

Clas

s I

Clas

s 2

Clas

s 3

Clas

s 4

.__.

.~

- __

_~~_

~

I 9.

70

10.5

0 40

.82

58.7

0 4.

09

7.07

25

.57

39.2

7 (6

.36)

(4

.45)

(2

4.65

) (3

2.54

) (2

.96)

(3

.70)

(1

3.69

) (1

7.84

) 2

3.41

9.

56

17.5

5 34

.52

2.82

4.

48

18.8

2 33

.25

(I .2

0)

(5.0

4)

(9.0

4)

(17.

68)

(I .7

4)

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Mental squaring: Transfer problems. On session 6 the entire set of problems between 1 and 99 were presented, including a subset of Class 4 problems that were not practiced. Trimmed correct response times on the practice and transfer Class 4 problems are shown in Fig. 4.

There are no significant differences between G.P. and the controls on either set, both t’s < 1. Further, if anything, G.P. is nominally faster on the transfer set, though not significantly so: t(24) < 1. The control group, however, is significantly slower on the transfer set, 20.97 set vs. 19.37 set, t( 15) = - 3.16, p < .Ol. That is, the control group shows an advantage on specific problems that were practiced, whereas G.P. does not. Of course, there is considerable transfer when measured against session 1 performance. The two subsets of Class 4 problems were balanced in difficulty, with the transfer set used by G.P. nonsignificantly more easy, as shown by a comparison based on 48 subjects in Charness and Campbell (1988) for first session performance: set 1 = 32.68 set, set 2 = 28.15 set, t(46) < 1. G.P. committed fewer errors than did the controls on both sets, though not significantly so. (He made 6 errors on each. compared to 6.6 on the practice set and 7.7 on the transfer set for the controls.)

Squaring components. A test of whether G.P. and the controls differed on the components was defined as follows. The trimmed mean correct score for each component (NMT, OTN, PI, P2, SUM, S + C2) was treated as a subject with a before and after score, and formed into a G.P. group, and a control group and analyzed as a two-factor repeated- measures ANOVA. Both main effects, for G.P. versus Controls, and

25,

PRACTICE TRANSFER

FIG. 4. Trimmed mean correct reaction time for practiced and transfer Class 4 problems during session 6 for G.P. and controls.


Before versus After, were significant, as well as the interaction showing that G.P. improved more across sessions, F(1, 5) = 12.57. The mean performance for G.P. on a component improved from 3.43 to 1.95 set, versus the controls’ improvement from 2.40 to 1.67 sec.

Figure 5 shows trimmed mean correct performance on the components of the squaring task in isolation. (Error rates were roughly comparable for G.P. and the controls on components both before and after squaring practice. G.P. was significantly less error-prone on Pl and SUM before the first squaring session and significantly more error-prone on OTN, Pl, P2, and SUM after the sixth session.) Both G.P. and the controls show some improvement on every subtask, though it is evident that the magnitude of improvement cannot account for the improvement on the squaring task itself. The sum of components for G.P. before practice was 20.5 set, and after practice it became 11.7 set, a difference of less than 9 set, compared to a speed-up on mental squaring for Class 4 problems of 37 sec. Similarly, for the control group, the speed-up on components was 4.4 set, compared to a Class 4 squaring time improvement of 18.4 sec. In both cases only about 24% of the speed-up in using the squaring procedure can be attributed to speed-up on execution of the components. The rest is undoubtedly due to improvements in the control processes that retrieve the subgoals and manage working memory. Further, the sum of components is inflated since it includes six response preparation and execution times, as opposed to one response being required in the squaring task.

Figure 6 compares components which were identical to those practiced

1

0 NMT OTN Pl P2 SUM s+c2

COMPONENT

FIG. 5. Trimmed mean correct performance on the components of the squaring task in isolation for G.P. and controls, both before and after practice with squaring.


I PP BEFORE

r-l 0 OP AFTER

I 67 BEFORE

EPl P2 EP2

COMPONENT

SUM ESUM

FIG. 6. Trimmed mean correct reaction time for components of the squaring algorithm presented in isolation for G.P. and controls both before and after practice with squaring. Pl, P2, and SUM appeared in the squaring task and EPl, EP2, ESUM were external to the squaring task.

in the squaring task versus those with digit strings that were external to the squaring task, both before and after practice. Tests for G.P. of PI vs. EPI, P2 vs. EP2, and SUM vs. ESUM both before and after practice showed that there were no significant differences, with all t’s < 1. The same comparisons with the controls showed no differences before practice (all t’s < 2), but both Pl and P2 were significantly faster than EPI and EP2 after practice in squaring: t(l5) = 3.23, and 3.71, respectively. There was also a strong trend for SUM to be faster than ESUM: t(l5) = 2.71, p < .Ol, one-tailed. It should be noted that comparisons are paired for the controls, and between problems for G.P., meaning that there is less power in G.P.‘s contrasts. The mean difference scores between those problems external to the task environment and practiced components was 199 msec after practice for G.P. and 149 msec after practice for the controls. G.P. was far more variable, however.

CONCLUSIONS

The results suggest that G.P. can learn a complex algorithm for mental squaring as effectively as age-matched controls. His improvement in performance appears to be accounted for more by his ability to put together the steps of the algorithm than improvement in his ability to perform the steps themselves. To use the terminology introduced earlier, compilation occurred but not proceduralization. Practice with the mental squaring procedure yielded striking improvement despite the fact that


G.P. could not recall anything about the tasks he had performed until the last day. At that time he was able to volunteer that some tasks dealt with numbers. Even with prompting he was unable to state what the procedure was, despite being able to implement it during testing.

G.P.‘s near normal learning of the squaring algorithm did not parallel that of the controls when the microstructure of the algorithm was examined. It was evident that G.P. did not show improvement on specific problems, as evidenced by equivalent performance on old and new Class 4 problems in session 6. Normal controls performed better on the old problems. G.P. also failed to show a significant advantage for specific practiced versus unpracticed component processes (the contrast of within versus extratask components).

These findings replicate an earlier one where amnesics failed to show a normal advantage for reading repeated inverted word triads while showing normal improvement on nonrepeated items (Cohen & Squire, 1980). The results are somewhat at odds with recent data gathered by Moscovitch, Winocur, and McLachlan (1986), where patients with memory disorders did appear to learn item-specific information, as measured by reading time. As Moscovitch et al. (1986) suggest, the finding of preserved or impaired learning for amnesics seems to depend on task-specific variables.

The finding that G.P. could not describe the algorithm yet could apply it in the context of mental squaring problems, supports a contention by Glisky et al. (1986) that amnesics represent their knowledge quite spe- cifically, with little flexibility in retrieval. Nonetheless, G.P. failed to show such narrow specificity for repeated versus new Class 4 problems.

Some investigators have commented that simple repetition is not effective in improving an amnesic’s memory performance (e.g., Gabrielli et al., 1984; Schacter & Glisky, 1986). The evidence from the digit span task is generally consistent with this view, though there was a slight trend for G.P. to improve his span across days. On the basis of the results of the Hebb supraspan repetition task, there was little evidence of improvement within a session when the repetition of a digit string occurred with only two intervening trials. This paradigm results in pronounced improvement with normal subjects (e.g., Drachman & Arbit, 1966; Hebb, 1961; Schwartz & Bryden, 1971).

An important facet of this study is that response time improved on many tasks. Even multiplication of single-digit problems showed improvement by the final session, despite the fact that this is an overlearned skill in adults. Such improvement suggests that repetition results in faster retrieval from preexisting associative structures, and lends additional support to Schacter’s (1985) view that there is greater likelihood of success when training amnesics if the task depends on unitized associations. The improvement on simple naming time also buttresses this belief. Nonetheless, tasks which can be completed within a few seconds (naming, multiplication,

270 CHARNESS, MILBERG. AND ALEXANDER

Class 1 squares) do show G.P. to be significantly slowed relative to controls, despite practice-related improvement. If strengthening is the main process for improvement on such simple tasks, then this process proceeds more slowly for a Korsakoff’s amnesic.

The mental squaring algorithm is probably the most complex task that an amnesic has learned. The nearest difficult cognitive task would be the claim of successful learning to solve the Tower of Hanoi problem (Cohen, 1984). There has been one unsuccessful attempt to replicate the observation of preserved skill learning for the Tower of Hanoi task in patients with alcoholic Korsakoff’s psychosis (Butters et al., 1985). One of the reasons for the failure to demonstrate learning with a complex problem solving task such as the Tower of Hanoi may be that it can be acquired via several distinctly different strategies (Simon, 1975). Some of these may be more conducive to composition (e.g., the perceptual and goal-recursive algorithms) than proceduralization (e.g., the move- pattern strategy). Concurrent thinking-aloud data are needed to address this issue.

This failure may also have been due to the fact that patients with Korsakoff’s amnesia often have accompanying neuropsychological deficits characterized by apathy, diminished initiation (Talland, 1965), and difficulty attaining and switching task sets (Oscar-Berman, 1973; Glosser, Butters, and Samuels, 1976). These subsidiary nonamnesic deficits could have affected the asymptotic level of performance on the Tower of Hanoi problem. Mair, Warrington, and Weiskrantz (1979) argue that pathological changes restricted to the mammillary bodies and perhaps the dorsomedial nucleus of the thalamus are sufficient to produce a severe anterograde amnesia and suggest that additional cognitive decline is predicated on the occurrence of pathology outside of these periventricular structures. The exact neuropathological substrate of these additional neuropsychological deficits is uncertain.

G.P.‘s high IQ and his relatively good performance on other neuropsychological measures are commensurate with what would be expected from his premorbid educational and occupational attainment. This suggests that his neuropathology is more restricted than is often the case in patients with alcoholic Korsakoff’s disease, and perhaps accounts in part for his success in learning a rather complex cognitive procedure. Nonetheless, the finding that G.P. showed normal learning of the procedure (could compile the squaring procedure), but did not show an advantage on practiced versus transfer problems (did not specialize it), suggests that procedural learning may involve at least two dissociable components (composition, proceduralization). If this analogy is accepted, it suggests that Korsakoff amnesics suffer particular difficulties with binding local variables to procedures, but they have little difficulty streamlining procedures by eliminating unnecessary steps.


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Teaching an amnesic a complex cognitive skill