Analogical transfer is effective in a serial reaction time task in Parkinson's disease: Evidence for a dissociable form of sequence learning

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Pergamon

PII] S9917Ð2821"85#99949Ð3

Neuropsycholo`ia\ Vol[ 24\ No[ 0\ pp[ 0Ð8\ 0886 Copyright Þ 0885 Elsevier Science Ltd[ All rights reserved Printed in Great Britain 9917Ð2821:86 ,06[99¦9[99

Analogical transfer is effective in a serial reaction time task in Parkinson|s disease] Evidence for a dissociable form of sequence learning PETER F[ DOMINEY\$%& JOCELYNE VENTRE!DOMINEY\ EMANNUEL BROUSSOLLE% and MARC JEANNEROD$ Vision et Motricite\ Unite 83 INSERM\ 58499 Bron\ France^ $Institut des Sciences Cognitives EP!099!CNRS\ 58997 Lyon\ France^ %Service de Neurologie\ Ho¼pital Neurologique\ 58992 Lyon\ France "Received 1 November 0884^ accepted 1 May 0885#

Abstract*Several studies of procedural learning in Parkinson|s disease "PD# have demonstrated that these patients are impaired with respect to age!matched control subjects[ In order to examine more closely the speci_c impairment\ we considered three dimensions along which a procedural learning task could vary[ These are] "0# implicit vs explicit learning\ "1# instance vs rule learning\ and "2# learning with internal vs external error correction[ We consider two hypotheses that could explain the impairments observed in PD for di}erent types of explicit motor learning] "H0# an impairment related to the acquisition of rules vs speci_c instances\ and "H1# an impairment in learning when no explicit error feedback is provided[ In order to examine the condition of rule learning with external error feedback\ we developed a modi_ed version of the serial reaction time "SRT# protocol that tests analogical transfer in sequence learning "ATSL#[ Reaction times are measured for responses to visual stimuli that appear in several di}erent repeating sequences[ While these isomorphic sequences are di}erent\ they share a common rule[ Verbatim learning of a sequence would result in negative transfer from one sequence to a di}erent one\ while rule learning would result in positive transfer[ Parkinson|s patients and age!matched controls demonstrate signi_cant acquisition and positive transfer of the rule between sequences[ Our results demonstrate that PD patients are capable of learning and transferring rule or schema!based representations in an explicit learning format\ and that this form of learning may be functionally distinct from learning mechanisms that rely on representations of the verbatim or statistical structure of sequences[ Copyright Þ 0885 Elsevier Science Ltd[ Key Words] Parkinson|s disease^ serial reaction time^ analogical transfer^ sequence learning[

order to clarify the speci_c impairment"s# we consider three dimensions along which a procedural learning task can vary[ These three dimensions are "0# implicit vs explicit learning\ "1# speci_c instance vs rule learning ð34Ł\ and "2# learning with internal vs external error correction[ Implicit learning has been extensively studied with the serial reaction time "SRT# task\ developed by Nissen and Bullemer ð21Ł[ In their SRT task\ subjects respond to the presentation of visual stimuli in one of four locations on a video monitor by pressing one of four associated keys[ If the stimuli are presented in a repeating sequence\ the reaction times "RTs# are reduced\ re~ecting a form of learning that was not seen when random stimuli were used[ The learning can be quanti_ed as the di}erence between mean RTs for the random vs the sequential stimuli[ In the implicit condition\ subjects are simply told to respond as quickly as possible\ yet they display sig! ni_cant learning\ and are often not aware that such learn! ing has occurred ð5\ 6\ 21Ł[ If subjects are warned that a

Introduction While the contribution of Parkinson|s disease "PD# to de_cits in initiating and executing familiar movements and movement sequences is fairly well established ð0\ 1\ 2\ 00\ 11\ 29\ 27Ł\ the contribution of PD to de_cits in the procedural learning of new movement sequences appears to be present but less clear[ In several tasks that test di}erent aspects of procedural learning\ Parkinson|s pat! ients are signi_cantly impaired with respect to controls ð04\ 12\ 15\ 25\ 32\ 33Ł[ However\ modi_cations of these tasks that change the mode of learning from implicit to explicit can produce striking improvements in per! formance ð25Ł\ indicating that it is not general motor learning\ but something more speci_c that is impaired[ In

& Address for correspondence] Vision et Motricite\ Unite 83 INSERM\ 58499 Bron\ France^ fax] 2261258659[

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P[ F[ Dominey et al[:Analogical transfer in PD

sequence may be present\ the task becomes explicit\ often with signi_cantly greater learning taking place "e[g[ Cur! ran and Keele ð6Ł#[ In several recent studies with implicit SRT learning tasks\ PD patients displayed signi_cant learning impair! ments with respect to their age!matched controls ð04\ 15\ 25Ł[ When the task is made more explicit\ however\ PD patients| performance improves to that of control sub! jects ð25Ł[ In one explicit form\ patients were informed that a sequence would be presented\ and they were asked to concentrate on the sequence without making any motor responses\ and to be prepared to reproduce the sequence at the end of the test[ PD patients| learning in this explicit task\ as measured by the declarative knowl! edge of the sequence\ was equal to that of the control subjects ð25Ł[ Pascuale!Leone et al[ ð25Ł considered that the PD patients| improvement is due to the explicit instructions\ though the e}ects of the eliminated motor e}ort cannot be ignored[ In a related test of the e}ect of explicit declarative knowledge on SRT performance\ PD subjects demonstrated learning equal to that of control subjects after 29 repetitions of the sequence[ These results indicate that the procedural learning impairment in PD can be reduced or eliminated if tasks are made explicit ð25Ł[ This does not appear to be the whole story\ however\ when we consider procedural learning experiments of Saint!Cyr et al[ ð32Ł[ In their Tower of Toronto "ToT# task\ subjects are faced with a set of colored discs stacked on one of three vertical pegs\ with the discs progressing from light on top to dark on the bottom of the stack[ Subjects are instructed to displace the entire stack from one peg "initial state# to a di}erent one "_nal state# fol! lowing two rules] "0# only one disc can be moved at a time\ and "1# a darker disc can never be placed on a lighter disc[ Large color photographs of the initial and _nal state are constantly in view[ Solving the problem optimally is based on an inherent rule that\ once learned\ applies in all cases[ Despite the fact that this is an explicit task\ PD patients require signi_cantly more moves to solve the four!disc problem than do age matched controls[ This suggests that the impairment may be in learning a general procedural rule vs a speci_c repetitive procedure as in the SRT task[ There is\ however\ another characteristic of the ToT task that distinguishes it from tasks such as SRT with respect to the presence or absence of error feedback[ In the SRT task\ even if the subject has a tendency to gen! erate an incorrect response\ the correct response is always provided\ i[e[ the SRT task has external error feedback[ In the ToT task\ however\ there is no such external feedback\ and incorrect moves may pass undetected[ The import! ance of such error feedback has been clearly dem! onstrated by Vriezen and Moscovitch ð38Ł\ who studied the number of errors for PD patients and controls to learn a set of stimulusÐresponse associations between numbers and visual stimuli "line drawings\ abstract designs and spatial locations#[ Subjects were presented

with the visual stimulus and had to respond with the associated number[ For the {correction| procedure\ on error trials\ the correct response was given as feedback\ and PD patients made no more errors than control subjects[ For the {trial and error| procedure\ on error trials\ subjects had to continue to guess until they made the correct response\ with only one error scored[ In this case\ PD subjects made signi_cantly more errors than controls[ This observation coincides with the conclusion of Taylor et al[ ð37Ł that PD patients are speci_cally impaired in conditions that require the ability to spon! taneously generate e.cient\ self!directed response stra! tegies and with several observations that PD patients are disadvantaged in the absence of external cues ð3\ 07\ 08\ 16\ 17\ 20\ 36Ł[ This leaves two open hypotheses consistent with the observed PD impairments in explicit learning] H0] Rule learning is impaired in PD while speci_c instance learning is retained[ H1] Self!directed learning is impaired in PD while error feedback learning is not[ Table 0 displays a categorization of several explicit learning tasks along these axes of internal vs external correction\ and rule vs instance learning[ These data indicate that instance learning is intact provided that external correction is available\ but they do not allow a similar conclusion regarding rule learning\ i[e[ can rules be learned with external correction< In order to respond to this question\ one should develop a protocol that requires a rule or rules to be learned\ and provides external error correction[ We have recently developed such a protocol that is based on an explicit SRT task\ with the modi_cation that\ in each successive block of sequence trials\ instead of using the same repeating sequence\ di}erent isomorphic sequences are used[ Thus\ while the sequences have di}erent serial or verbatim structure ð35Ł in terms of the spatial locations of the stimuli\ they all share a common rule that describes a repetitive structure[ Examples of two such isomorphic sequences are] "0# FÐCÐJÐFÐCÐJ and "1# QÐLÐPÐQÐLÐP[ In both cases\ the fourth to sixth elements are fully predicted by the _rst to third elements[ Analogical transfer is the process of forming and exploit! ing such a rule or analogical schema\ based on a familiar problem in order to solve a new one ð4\ 19\ 14\ 22\ 31Ł[ We thus refer to our task as a test of analogical transfer in sequence learning "ATSL#\ since it tests the ability to acquire and transfer knowledge of an analogical schema or rule from one problem to another in the domain of sequence learning[ We now compare PD and control subjects in the ATSL task in order to determine if PD patients can acquire a procedural rule in an explicit\ exter! nally guided task[ Material and methods Patients and normal control subjects Seven non!demented\ non!depressed\ right!handed patients\ with early! or mid!stage "duration range 0Ð09 years# idiopathic\

P[ F[ Dominey et al[:Analogical transfer in PD

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Table 0[ Explicit learning of rules and instances with internal and external error correction Rule

Instance

Internal correction

Tower of Toronto "PD group impaired#

Association!trial and error "PD group impaired#

External correction

Analogical transfer in sequence learning*ATSL "<<<<#

Association*correction SRT!explicit\ declarative "PD group unimpaired#

Rule and single instance based learning have been studied using procedures that require internal correction\ and single instance!based learning has been studied using procedures that provide external correction[ The current study addresses explicit rule learning using a procedure that provides external correction[

levodopa!responsive Parkinson|s disease\ were tested[ The mean age "2S[D[# was 40[8200[5 years[ Chronic anti!par! kinsonian treatment consisted of levodopa "049Ð899 mg:day\ with peripheral levodopa!decarboxylase inhibitor# in all but one case\ dopamine agonists in four cases\ deprenyl in one patient\ and anticholinergic drugs in two cases[ One patient "P0# was drug!free[ The clinical evaluation of the motor state of the patients was quanti_ed on the Hoehn and Yahr scale ð13Ł\ and the Uni_ed Parkinson|s Disease Rating Scale "UPDRS# ð03Ł[ Individual patient data are summarized in Table 1[ All patients consented to participate in the experiment\ and had normal or corrected!to!normal vision[ A group of six healthy age matched volunteers was tested as a control under the same experimental conditions for subsequent comparison with the patients[ The control subjects were all right!handed[ Their mean age "2S[D[# was 44[225[8 years[

"from target onset until subject|s contact with the screen# was recorded[ The eight sequence targets used ðlabeled AÐH in Fig[ 0"A#Ł were each 1[4 cm1 squares\ and were illuminated one at a time[ The letters AÐH were never presented to the subjects and are only used here for describing the sequences[ After a target was touched\ it was extinguished\ the reaction time was recorded and the next target was immediately displayed[ It is important

Analogical transfer protocol The primary task was based on the SRT protocol ð21Ł and involved pointing to single illuminated square targets on a touch!sensitive screen as quickly and accurately as possible[ Subjects sat in front of the touch sensitive computer screen on which the sequence targets were displayed\ and response time Table 1[ Details of the individual patients with Parkinson|s disease Age Patients Sex "years#

Duration of illness Hoehn and "years# Yahr stage

P0 P1

F M

27 51

0 09

P2

F

47

8

P3

M

34

7

P4

F

27

3

P5 P6

F M

44 56

1 7

0[9 "o}# 1[9 "on# 1[4 "o}# 1[9 "on# 2[9 "o}# 0[4 "on# 1[4 "o}# 0[4 "on# 0[4 "on# 1[9 "on# 1[4 "o}#

Treatment None 149 mg l!d\ d!a\ D 899 mg l!d\ d!a\ a 199 mg l!d\ a 049 mg l!d\ d!a 199 mg l!d 649 mg l!d\ d!a

Medication abbreviations] l!d\ levodopa:day^ d!a\ dopamine agonist^ a\ anticholinergic^ D\ deprenyl[ The Hoehn and Yahrð04Ł stage of disease is indicated in all patients while chron! ically treated "{on|#\ and for the ~uctuating patients in the {on| and in the {o}| medication motor state[

Fig[ 0[ Analogical transfer in sequence learning protocol[ Above!13 element sequence[ "A# One mapping of letters AÐH to target locations on the touch!sensitive screen[ Targets are presented one at a time[ Note that the letters themselves are never displayed[ "B# Breakdown of sequence AÐBÐCÐBÐCÐDÐ CÐDÐE into three!element chunks[ Note that each shaded element is predictable from the element two positions behind\ labeled {n−1|[ For example\ the _rst two elements {BÐC| in {BÐCÐD| are predicted by the last two elements {BÐC| in the preceding chunk {AÐBÐC|[ "C# Analogical Schema[ The _rst two elements are predicted from the previous two elements "{n−1|#\ and the third element is unpredictable "{u|#[ These elements are referred to\ respectively\ by their position in the analogical schema\ P0\ P1 and P2[ P0 and P1 are predictable and P2 is unpredictable[ This analogical schema is the unit that describes the isomorphism between SEQ0\ SEQ1 and SEQ2 "see text#[ "D# An alternative mapping of AÐH to the eight target locations used to generate an isomorphic sequence[

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to recall that\ since the correct response is always presented\ this task provides explicit external correction of errors[ Targets could appear in blocks of two types*random and sequence[ In random blocks\ 019 targets were successively pre! sented in random order[ In sequence blocks\ 019 targets were successively presented in _ve repetitions of 13 element sequences of the form AÐBÐCÐBÐCÐDÐCÐDÐEÐDÐEÐFÐEÐFÐGÐFÐGÐ HÐGÐHÐAÐHÐAÐB "Fig[ 0#[ To appreciate the overall com! plexity of this sequence\ note that each of the eight "AÐH# elements repeats three times\ with two di}erent successors\ thus yielding a complex\ or ambiguous\ sequence "see C\ for exam! ple#[ A form of repetitive\ internal organization becomes evident if it is noted\ for example\ that G and H are repeats of the elements two places behind them "n−1#\ while A is unpre! dictable "u#[ As shown in Fig[ 0"B#\ this pattern {n−1\n−1\u| repeats throughout the sequence\ forming the basis of the ana! logical schema displayed in Fig[ 0"C#[ In this notation\ G and H are said to be in positions 0 and 1 "both predictable# and A in position 2 "unpredictable# of the analogical schema {n−1\n−1\u|[ We can observe that\ in its _rst appearance\ C is in position 2 "unpredictable#[ It then appears in position 1 and _nally again in position 0 "both predictable#[ Finally\ we see that the sequence {wraps around| so the repeating pattern is never interrupted as the sequence repeats[ Since our goal is to study the transfer of knowledge between di}erent\ isomorphic sequences\ we must construct several sequences that meet these requirements[ Three such sequences were generated by using the 13!element pattern described above with three di}erent mappings of AÐH to the eight locations on the touch sensitive screen ðe[g[ Figure 0"A and D#Ł[ Thus\ the three resulting 13!element sequences di}er completely in their serial or verbatim ordering of the spatial targets[ However\ they are isomorphic in that they all share the analogical schema {n−1\n−1\u| that describes their di}erent speci_c serial order! ings in a common abstract form[ To summarize\ in each of three sequence blocks\ one of these sequences was repeated _ve times for a total of 019 targets[ Each individual target presentation and touch is referred to as a trial[ An experimental session started with 19 random trials to familiarize the subject with the touch!screen[ The data recording started with a random block of 019 trials "RAND0#\ followed by the three sequence blocks of 019 trials each "SEQ0\ SEQ1\ SEQ2#\ and a _nal random block of 019 trials "RAND1#[ Subjects were shown a diagram visually depicting the ana! logical schema {n−1\ n−1\ u|\ and told before and once during the examination that such a rule!like structure might be found in the subsequent testing and that searching for and _nding such a structure could aid their performances[ In this sense\ ATSL is an explicit learning task[

improvement "RTi# by subtracting the mean RT for RAND1 from the mean RT for each sequence block "RTimean SEQ RT−mean RAND1 RT#[ This provided a quanti_cation of the sequence!learnin` speci_c RT improvement[ Data were analysed using multifactor ANOVA and Sche}e|s post!hoc comparisons[ For a more speci_c analysis\ we used a Student|s t!test[ All statistical analyses were performed by the STATISTICA software package[ For ANOVA\ the within!sub! ject factors were {block| "SEQ0\ SEQ1\ SEQ2#\ and {position| "{predictable|\ {unpredictable|#[ P0 and P1 were collapsed to form the predictable case\ and P2 formed the unpredictable case[ {Group| "Parkinson\ control# was the between!subjects factor[ The dependent variable was the RT improvement "RTi# measure as described above[ Note that an increasingly negative RTi value corresponds to a greater learning e}ect[

Results Overall learnin` Figure 1 shows the mean RTi values for the PD and control groups[ The three!way ANOVA revealed a sig! ni_cant main e}ect for group ðF"0\094#07[5\ P³9[9990Ł\ with the mean RTi values of −001 msec for the control group and −27 msec for the PD group[ There was also a signi_cant main e}ect for block ðF"1\094#02[65\ P³9[9990Ł\ with RTi values of −03 msec\ −098 msec\ and −83 msec for SEQ0\ SEQ1 and SEQ2\ respectively[ There was no group×block interaction ðF"1\094#9[41\ P9[48Ł[ We veri_ed that the accumulated learning dem! onstrated in SEQ2 di}ered signi_cantly from the random responses in RAND1 by comparing absolute RT values for SEQ2 and RAND1 in paired t!tests[ The control group showed a signi_cant di}erence between SEQ2 and RAND1 ð040 msec\ t2[5\ P³9[90Ł\ as did the PD group ð37 msec\ t3[8\ P³9[994Ł[ This learning e}ect was veri! _ed by performing the same analysis on each individual

Data analysis For each subject\ mean RTs were calculated for each block of trials "RAND0\ SEQ0\ SEQ1\ SEQ2\ RAND1#[ Mean RT values for two groups are presented in Table 2[ RTs in RAND1 were used as a reference for simple sensoryÐmotor coordination improvement\ independent of sequence!related learning\ that could occur during the _ve blocks[ We thus calculated RT

Table 2[ Mean RT values for the PD and control groups "in milliseconds#

Control PD

RAND0

SEQ0

SEQ1

SEQ2

RAND1

491 532

333 478

225 494

239 420

380 468

Fig[ 1[ Mean reaction time improvement "RTi# values by block for the control and Parkinson groups[ RTi values are calculated by subtracting the mean RT for RAND1 block from the other SEQ and RAND blocks[ Negative values indicate improvement over Rand1 performance[ First\ the signi_cant di}erence in RT between SEQ2 and RAND1 indicates signi_cant overall learning for both groups "see text#[ Second\ a cumulative reduction in RTi for SEQ2 vs SEQ0 is seen in the control and in Parkinson groups[ This re~ects analogical transfer since SEQ0ÐSEQ2 are all di}erent isomorphic sequences[

P[ F[ Dominey et al[:Analogical transfer in PD

which revealed signi_cant SEQ2 RAND1 di}erences ðP³9[90Ł for all control subjects and for six of the seven PD subjects[ All of the control subjects reported an awareness of a repeating structure in the three sequence blocks\ and _ve of the six were able to sketch a directed graph _gure that re~ected the {n−1\ n−1\ u| structure[ Likewise\ all of the PD subjects reported an awareness of a repeating structure in the three sequence blocks\ and _ve of the seven were able to sketch a pattern that re~ected the {n−1\ n−1\ u| structure[ The sketches were considered to re~ect reasonable awareness if they included a directed graph representing the pattern AÐBÐAÐBÐC[ In addition\ the PD group showed an overall motor facilitation\ independent of their sequence!related learn! ing\ as revealed by a signi_cant RT improvement for Rand1 over Rand0 ð52 msec\ t1[2\ P³9[94Ł[ The con! trol group similarly displayed a small but non!signi_cant Rand1 vs Rand0 improvement ð00 msec\ t0[47\ P×9[0Ł[

Acquisition of analogical schema The analogical schema is characterized by the proper! ties that sequence elements in positions P0 and P1 are predictable\ whereas elements in position P2 are not pre! dictable by the anological schema ðFig[ 0"C#Ł^ thus\ the degree of schema acquisition can be quanti_ed by this "non!predictable−predictable# di}erence[ Figure 2 dis! plays the mean RTi values for the three sequences by element position "predictable and non!predictable#[ The three!way ANOVA revealed a signi_cant main e}ect for position ðF"0\094#52[0\ P³9[9990Ł\ with mean RTi

Fig[ 2[ Mean RT improvement "RTi# by position[ Solid lines] non!predictable elements "position 2#\ Dashed lines] predictable elements "position 0 and 1#[ "Right# Control subjects[ Pre! dictable elements show a progressive signi_cant RT reduction in the three sequence blocks SEQ0Ð2 when compared to non! predictable elements[ This indicates that it is the analogical schema\ and not the sequences themselves\ that is being learned[ Note in SEQ1\ the slight reduction in RTs for non!predictable elements\ due to an increase in the number of spatially adjacent target pairs in SEQ1\ that yields a non!transferable RT reduction for that sequence[ "Left# Parkinson subjects display a similar predictable vs non!predictable pro_le[ See the text for analysis[

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values of −096 msec for predictable and −1 msec for unpredictable positions[ There was a signi_cant inter! action between group and position ðF"0\094#09[8\ P³9[994Ł[ Post!hoc analysis by Sche}e|s test revealed\ in the control group\ a signi_cant di}erence between pre! dictable "−052 msec# and non!predictable RTis "−8 msec# ðP³9[9990Ł[ The same e}ect was observed for the PD group with a signi_cant di}erence between predictable "−59 msec# and non!predictable RTis "3 msec# ðP³9[91Ł[

Transfer of the analogical schema If positive transfer occurs between the three sequences\ then the di}erence between non!predictable vs pre! dictable responses should become increasingly signi_cant across the three sequence blocks as a result of that trans! fer[ In the three!way ANOVA\ the signi_cant interaction between position and block ðF"1\094#4[12\ P³9[90Ł indicates a change in the relation between non!pre! dictable and predictable positions during the course of the three sequences\ i[e[ transfer of the analogical schema[ There was no signi_cant group di}erence in this transfer as revealed by the non!signi_cant three!way interaction ðF"1\094#9[70\ P9[34Ł[ We analysed this transfer e}ect more closely by two!way block "SEQ0\ SEQ1\ SEQ2#×position "predictable\ non!predictable# ANOVAs for the PD and control groups independently "Fig[ 3#[ The control group displayed signi_cant main e}ects for block ðF"1\37#4[3\ P³9[90Ł\ and for position ðF"0\37#25[4\ P³9[9990Ł[ The interaction between block and position ðF"1\37#1[7\ P9[956Ł was not sig! ni_cant[ However\ post!hoc analysis by Sche}e|s test showed that the non!predictable−predictable "N−P#

Fig[ 3[ Analogical schema transfer[ The level of analogical schema transfer is displayed as the progressive change during the three sequence blocks of the level of analogical schema acqui! sition\ as indexed by di}erence between predictable minus non! predictable RTis[ For both the control and PD groups\ this measure becomes increasingly signi_cant in the progression from SEQ0 to SEQ2\ indicating a signi_cant level of analogical transfer in both groups[

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di}erence is non!signi_cant in SEQ0 ðN−P64 msec\ P9[60Ł\ more signi_cant in SEQ1 ðN−P051 msec\ P³9[94Ł\ and highly signi_cant in SEQ2 ðN−P 119 msec\ P³9[990Ł[ Likewise\ the PD group displayed signi_cant main e}ects for block ðF"1\46#00[0\ P³9[9990Ł\ and for pos! ition ðF"0\46#12[8\ P³9[9990Ł\ and as in the control group\ the interaction between block and position was not signi_cant ðF"0\46#1[3\ P9[09Ł[ Furthermore\ as seen in the control group\ post!hoc analysis by Sche}e|s test showed that the non!predictable predictable di}er! ence is non!signi_cant in SEQ0 ðN−P13 msec\ P9[84Ł\ and then signi_cant in SEQ1 ðN−P79 msec\ P³9[91Ł\ and in SEQ2 ðN−P77 msec\ P³9[91Ł[ Thus\ for both groups\ there was a signi_cant positive transfer between the successive sequences\ with no group inter! action in this measure of transfer[

Rule vs speci_c sequence learning If subjects are learning speci_c sequences\ then any given sequence must be presented at least once in its entirety before the e}ects of learning can be observed[ Thus\ if learning is already evident in a new 13!element sequence before that sequence has been completely pre! sented for the _rst time\ the learning can only be due to a rule acquired and transferred from previous training[ To address directly whether a transferable rule or indi! vidual sequences were being learned\ we performed a two! way ANOVA on group "PD and control# and position "predictable\ non!predictable# for the _rst 13 elements of sequence block SEQ2\ i[e[ the _rst presentation of the previously unseen sequence of block SEQ2[ The depen! dent variable was the mean of the RTis for the predictable and non!predictable elements\ respectively\ of the _rst repetition "i[e[ the _rst 13 elements# of the sequence in SEQ2\ calculated for each subject[ The signi_cant main e}ect for position ðF"0\11#22[5\ P³9[9990#Ł indicates that\ even during the very _rst presentation of this sequence\ its predictable structure was already being exploited\ with RTi values of 24 and −097 msec for the non!predictable and predictable elements\ respectively[ The lack of signi_cant group or group×position inter! action e}ects ðF"0\11#2[6\ P9[96#^ and F"0\11#1[5\ P9[01#\ respectivelyŁ indicates that there is no sig! ni_cant di}erence in PD vs control groups in the use of the learned rule during this _rst repetition of the 13! element sequence in SEQ2[

Discussion These results demonstrate that\ under conditions of explicit learning with external error feedback\ patients with Parkinson|s disease are capable of a simple form of analogical transfer that involves learning a generalized rule that can apply in di}erent but isomorphic situations[

This allows us to reject our Hypothesis H0 which stated that {{Rule learning is impaired in PD while speci_c instance learning is retained||[ In contrast\ these results support Hypothesis H1] {{Self!directed learning is im! paired in PD while error feedback learning is not||\ in agreement with the conclusions of Taylor et al[ ð37Ł and Vriezen and Moscovitch ð38Ł and the general observation that these patients rely heavily on external cues ð3\ 07\ 08\ 16\ 17\ 20\ 36Ł[ In addition\ these results help to clarify the distinction between rule and instance learning advocated by Shanks and St[ John ð34Ł\ demonstrating how\ from several per! spectives\ the explicit rule learning in ATSL is func! tionally dissociable from that of speci_c sequence! learning\ either implicit or explicit[ Particular di}erences can be seen for both PD and control groups in terms of "0# the distribution of reaction times for elements within sequence blocks\ "1# the dependence of learning on sequence length\ and "2# characteristics of performance transfer to new sequences[ "0# Distribution of reaction times within the sequence blocks[ If a sequence is learned {{verbatim|| ð35Ł\ the RT reductions should be observed for all sequence elements with a relatively uniform distribution[ In the ATSL task\ reduced RTs are seen for predictable but not for non!predictable elements\ even though both are contained in sequence blocks[ This supports the view that a rule\ that is not speci_c to any one of these sequences\ is being learned\ and not the sequences themselves[ Curran and Keele ð6Ł performed a similar analysis of RT distribution in an SRT task using a repeating sequence of the form CÐAÐBÐCÐBÐD[ They compared RTs for three types of positions] unique "A and D#\ after unique "B following A and C following D#\ and ambiguous "C following B\ and B following C#[ The ambiguous elements "underlined# are in fact repetitions of the elements three and two places behind them and thus resemble our predictable elements\ while the unique elements resemble our non!predictable elements[ Curran and Keele|s analy! sis con_rmed\ in fact\ that RTs for all three of these position types are signi_cantly reduced with respect to those for random elements\ supporting their con! tention that the entire structure of the sequence was being learned[ We can consider that\ in general\ if a single given sequence is successively repeated then the sequence itself can be learned\ whereas if a number of isomorphic sequences are presented then only the rule common to all can be learned[ "1# The lack of dependence on sequence len`th[ Motor sequence performance is dependent upon several par! ameters of the sequence\ including its length ð0\ 1\ 04\ 15\ 25Ł[ Length dependence in the SRT task was demonstrated by Pascuale!Leone et al[ in both nor! mal controls and PD subjects\ using repeating sequences of length 7\ 09 and 01 elements ð25Ł[ RT reduction was inversely related to sequence length in

P[ F[ Dominey et al[:Analogical transfer in PD

control and PD subjects\ and for the longer sequences\ PD patients were particularly impaired[ For the 01!element sequence\ the RT improvements "RAND − SEQ# were 034 msec for controls and 34 msec for PD patients[ Ferraro et al[ ð04Ł observed RT improvements of 77 and 40 msec for control and PD patients\ respectively\ using a 09!element sequence\ and for sequences of length 00\ Jackson et al[ ð15Ł found RT improvements of 63 msec for con! trol and 6 msec for PD patients[ In contrast\ in the last of three di}erent 13!element sequences\ we observed RT improvements of 040 msec and 37 msec for control and PD subjects\ respectively\ a notable deviation from the length dependencies observed in non!rule!based SRT tasks in PD ð04\ 15\ 25Ł[ "2# Transfer to isomorphic sequences[ The most profound di}erence between the rule learning mechanisms that we observe vs speci_c sequence learning is the sig! ni_cant positive transfer to di}erent but isomorphic sequences for both PD and control groups[ This is in contrast to the negative transfer results of Robertson and Flowers ð30Ł who demonstrated that\ while PD subjects were able to demonstrate explicit sequence learning\ when asked to change from one sequence to the next\ these patients displayed signi_cantly more negative transfer than that observed in controls[ That is\ after instructions to shift to a di}erent sequence\ PD subjects tended to continue with the old sequence[ A related form of negative transfer was observed by Benecke et al[ ð2Ł in making the transition from one movement to another in a sequence\ and is related to the more general impairment in set!shifting observed in PD ð05\ 23\ 24Ł[ In contrast\ our observation of no negative transfer likely results from the fact that it was not a set of di}erent sequences that was learned\ but instead\ a single rule that is common to all of these sequences[ The observed transfer was\ in fact\ positive\ since\ from the perspective of the rule in question\ all three sequences are the same[ Carrying this line of reason! ing to its logical end\ we considered that\ if subjects are learning a verbatim representation\ then there can be no performance improvement during the _rst exposure to the new sequence[ Learning can only be seen on the second and subsequent repetitions of the sequence[ We observed\ however\ for both PD and control subjects\ signi_cant learning e}ects during the _rst presentation of the new 13!element sequence in block SEQ2\ with no group interaction[ In terms of the learned rule\ SEQ2 is equivalent to the previous sequences SEQ0 and SEQ1 and thus it is not sur! prising that learning e}ects are seen immediately\ via transfer of the rule[ Sequential structure and forms of learning Stadler ð35Ł pointed out that performance improve! ments can result from learning a verbatim representation

6

of the sequence\ event by event\ or from learning an aggregate representation of the sequence in terms of probabilities of elements\ or element transitions\ etc[ ð15\ 18\ 39\ 35Ł[ Here\ we consider a third representation that is rule!based[ In a rule\ the unit of representation is not the set of speci_c sequence elements nor statistical relations between pairs or groups of elements[ Instead\ it is in terms of the relative positions of repeating elements[ For example\ two sequences like AÐBÐAÐBÐC and GÐ DÐGÐDÐH can be represented in a common by the rule {u\ u\ n−1\ n−1\ u| that describes the relations between repeating elements[ This type of rule!based rep! resentation has been demonstrated in tests of judging the grammaticality of letter strings ð10\ 26\ 28Ł[ Subjects learned a set of grammatical rules by studying strings or letter pairs generated with one set of letters\ and were then able to correctly judge the grammaticality of new strings generated with the same letter set[ In tests of transfer of this rule!based knowledge to a set of strings generated with new set of letters\ only subjects trained on strings were capable of this transfer ð10Ł[ This suggests a dissociation between one system that learns element! speci_c associations avaiable in the pairs training data\ vs another that learns more abstract relations between repeated elements available in the strings training data[ In conclusion\ we have demonstrated that\ in an explicit procedural learning context\ PD subjects\ like normal controls subjects\ are capable of developing a rule!based representation of sequential knowledge that serves as the basis for analogical transfer to new\ iso! morphic sequences[ This suggests that PD patients are not intrinsically impaired in learning procedural rules\ as required in the Tower of Toronto task ð32Ł\ but rather\ that they are impaired in the ability to generate internally an appropriate evaluation or response in error conditions ð37\ 38Ł[ At the same time\ based on the di}erences in ATSL and SRT learning characteristics\ including di}erences in the distribution of RT reductions\ length dependencies and transfer\ these results suggest that the rule!based representation that supports ATSL is functionally dis! tinct from that involved in SRT learning[ In support of this idea\ our recent simulation results have demonstrated that\ while a recurrent neural network can learn verbatim and aggregate structures in SRT task\ it failed in the ATSL task which requires an additional capacity to rep! resent positional relations between repeating elements ð7Ð 09\ 01\ 02Ł\ see also ð06Ł for comments on fronto!cortical hierarchical dissociationsŁ[

Acknowled`ements*The authors acknowledge the constructive comments of two anonymous reviewers and the Editor[ We also gratefully acknowledge discussions with Keith Holyoak and Jean Saint!Cyr regarding aspects of analogical transfer and learning[ PFD was supported by a Post!Doctoral Fellowship from the Fyssen Foundation "Paris#[

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P[ F[ Dominey et al[:Analogical transfer in PD

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