The heterogeneity of picture-supported narratives in Alzheimer’s disease

The heterogeneity of picture-supported narrativesin Alzheimer�s disease

Anh Duonga,b,*, Francine Girouxb, Andreanne Tardifa,b, Bernadette Skaa,b

a Centre de recherche, Institut universitaire de geriatrie de Montreal, Canadab Ecole d�orthophonie et audiologie, Faculte de Medecine, Universite de Montreal, Canada

Accepted 18 October 2004Available online 8 December 2004

Abstract

This study describes discourse patterns produced by 46 Alzheimer disease (AD) patients and 53 normal elderly subjects in twopicture-supported narratives. Nine measures derived from a cognitive model of discourse processing were obtained and submitted tocluster analysis. Results indicate that discourse patterns elicited from both stimuli were heterogeneous. Further, they fail to clearlydifferentiate between normal aging and AD in half of the AD patients. Discourse patterns are examined in light of various sources ofheterogeneity including severity of cognitive impairment, subject characteristics, and task demands. The usefulness of discourse as adiagnostic and therapeutic tool is discussed.� 2004 Elsevier Inc. All rights reserved.

Keywords: Alzheimer; Aging; Language; Discourse; Communication; Cognition; Heterogeneity

1. Introduction

Alzheimer�s disease (AD) is an age-associated degen-erative disorder characterized by progressive deteriora-tions in major cognitive functions such as memory andexecutive functions, as well as gnosis, praxis, and lan-guage (DSM-IV-TR, 2000). Within the language func-tion, word-finding difficulties have long beenrecognized (Appell, Kertesz, & Fisman, 1982; Bayles,Kaszniak, & Tomoeda, 1987). More recently, a numberof discourse alterations across different discourse typeshave also been described (for a review, see Caramelli,Mansur, & Nitrini, 1998; Ehrlich, 1994). This interesthas been fueled in part by the recognition that discourseis a natural form of communication that can providevaluable information about the integration of cogni-tive–linguistic abilities, such as naming, and cognitive–

non-linguistic abilities, such as selection, organization,and planning. Because all of these abilities can be im-paired to some degree in AD, several authors have sug-gested that discourse be included in a diagnostic battery(Ehrlich, 1994; Orange & Kertesz, 2000).Although the integrative and connected nature of dis-

course is well recognized, its analysis remains largelyinfluenced by the traditional linguistic approach derivedfrom the aphasia literature. Indeed, the emptiness ofAD patient�s discourse (Nicholas, Obler, Albert, &Helm-Estabrooks, 1985), the reduction in informationcontent (Bschor, Kuhl, & Reischies, 2001; Giles, Patter-son, & Hodges, 1996; Glosser & Deser, 1990; Tomoeda& Bayles, 1993; Tomoeda, Bayles, Trosset, Azuma, &McGeagh, 1996), the overuse of pronouns without refer-ents (Almor, Kempler, MacDonald, Andersen, & Tyler,1999), and the simplified syntax (Altmann, Kempler, &Andersen, 2001; Bates, Harris, Marchman, Wulfeck, &Kritchevsky, 1999; Croisile et al., 1996; Glosser & Deser,1990) can all be conceived as lexico-linguistic impair-ments, or impairments of individual lexical entries that

0093-934X/$ - see front matter � 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.bandl.2004.10.007

* Corresponding author. Present address: Lady Davis Institute forMedical Research, Room 8, 3999 Chemin de la Cote Ste-Catherine,Montreal, Que., Canada H3T 1E2. Fax: +1 514 340 8295.

E-mail address: [email protected] (A. Duong).

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Brain and Language 93 (2005) 173–184

can either affect the meaning of a word, or the meaning ofa string of words in the case of a sentence. Strikingly fewerstudies (Chenery & Murdoch, 1994; Ehrlich, Obler, &Clark, 1997) have investigated the ability to link theseindependent lexical entries to form a connected unit ofmeaning, and to organize them according to a canonicalstructure (Kintsch & van Dijk, 1975). Analysis of dis-course production must therefore extend beyond simplelexico-semanticmeasures to incorporatemeasures reflect-ing cognitive–linguistic and cognitive–non-linguistic abil-ities within an integrative discourse model (Orange &Kertesz, 2000).While the use of integrative models could permit the

detailed descriptions of discourse patterns (impaired rel-ative to retained abilities) and provide information as tothe underlying levels of dysfunction, the usefulness of dis-course as a diagnostic tool still faces other concerns. Oneof them pertains to the specificity of discourse patterns.Indeed, the same impaired language/discourse measuresreported in AD are often qualitatively similar, if notquantitatively similar, to those described in normal aging(Au, Joung, Nicholas, & Obler, 1995; Glosser & Deser,1992; LeDorze & Bedard, 1998; Mackenzie, 2000; Nor-man, Kemper, & Kynette, 1992; Shadden, 1997). In addi-tion, inter-subject variability in normal aging has beenobserved across a variety of cognitive domains (Valdois,Joanette, Poissant, Ska, & Dehaut, 1990). Variability isnot only inherent to aging, but also appears to increasewith advancing age (Obler et al., 1994). Finally, the clin-ical manifestations of AD are also heterogeneous, as ADpatients do not necessarily show the same degree ofimpairments across cognitive functions (Fisher et al.,1996; Joanette, Ska, Poissant, & Beland, 1992; Joanetteet al., 1995a, 1995b; Martin et al., 1986) or betweensubtests of the same cognitive function (Joanette et al.,1992; Ska, Joanette, Poissant, Beland, & Lecours,1990). Since performance on basic language and othercognitive subtests can reveal a level of functioning ade-quate for discourse processing, heterogeneity in ADand heterogeneity in normal aging could very well leadto heterogeneity in discourse production. This would re-sult in the observation of overlapping discourse patterns.The present study addressed three objectives. The first

objective was to provide a detailed description of AD pa-tient�s discourse. This was done using a cognitivemodel ofdiscourse processing originally proposed by Kintsch(Kintsch & van Dijk, 1975, 1978, 1988) and later adaptedto account for discourse dysfunctions in neurologicallyimpaired populations by Frederikssen (Frederiksen,Bracewell, Breuleux, & Renaud, 1989). This approachallowed for the description of a number of discourse mea-sures that reflect various levels of discourse representa-tions. To evaluate the organizational demands of thetask, discourse was elicited from two types of picturedstimuli that differ in terms of degree of organization. Con-trasts between levels of representation would provide an

accurate description not only of impairments, but alsopreservations in discourse abilities, while contrastsbetween production stimuli would provide an indicationas to the organizational skills elicited by each of thepictured stimuli. The second objective was to determinethe specificity of AD discourse patterns with respect tothat of normal elderly (NE) subjects. This was done usingcluster analysis. If AD patients and NE subjects producequalitatively and quantitatively distinct discourse pat-terns, then they should be classified in different clusterson the basis of their discourse performance. If theirdiscourse patterns overlap, then both NE subjects andAD patients should be found in the same clusters. The fi-nal objective was to characterize the various discoursepatterns using basic cognitive variables. If the heterogene-ity of discourse patterns reflects the heterogeneity of basiccognitive abilities, then a relationship between cognitiveperformance and discourse performance should beobserved.

2. Method

2.1. Subjects

Subjects in the present study were drawn from a co-hort of subjects who took part in a larger study on nor-mal and pathological aging (Joanette et al., 1995a,1995b). Ninety-nine subjects were selected on the basisof age (65–84 years) and education (4–18 years). Ofthe total number of subjects, 46 French-speaking sub-jects had received a clinical diagnosis of probable ADaccording to NINCDS-ADRDA criteria (McKhann etal., 1984) and were considered mild to moderate(GDS = 3 and 4) according to the Reisberg scale (Reis-berg, Ferris, de Leon, & Crook, 1982). The remaining 53French-speaking subjects presented no neurological,psychiatric, or medical problems at the time of testing.Table 1 summarizes subject�s characteristics.

2.2. Tasks

All subjects had undergone a complete neuropsy-chological assessment with the PENO (protocole

Table 1Subject characteristics

Subjects n Gender Age Education DGS

NE 53 40 F 73.8 10.2 DGS 113 M (6.3) (3.2)

65–84 4–17AD 46 39 F 74.3 8.3 DGS 3 = 12

7 M (5.5) (2.8) DGS 4 = 3465–83 4–16

Total 99 79 F 74.1 9.320 M (5.9) (3.2)

65–84 4–17

Age and education are given in mean, standard deviation, and range.

174 A. Duong et al. / Brain and Language 93 (2005) 173–184

d�evaluation neuropsychologique optimal; Joanette et al.,1995a, 1995b), which comprised 17 subtests aimed atassessing the main cognitive domains of language, mem-ory, gnosis, and praxis. For the purpose of the presentstudy, two discourse production tasks were selected fromthe language subtests of the PENO. In the first task, sub-jects were presented with a single picture (P1) depicting abank robbery (Nespoulous et al., 1992) andwere asked to:‘‘look at this picture and tell me the story that you see.’’ Inthe second task, subjects were presented with a sequenceof 7 pictures (P7) placed in the appropriate order anddepicting a car accident, andwere asked to: ‘‘look at thesepictures, and tell me the story that you see.’’ Subjects wereallowed as much time as was necessary for them to com-plete their stories. To elicit more verbal output in subjectswhose stories were felt to be incomplete, prompts that didnot reveal the content of the stories such as ‘‘do you haveanything else to add?’’ were offered. All 198 discoursesamples obtained from the 99 subjects were audiotapedand subsequently transcribed verbatim for discourseanalyses.Nine other subtests in the cognitive domains of mem-

ory, language, and visual gnosis that were considered tohave a potential influence on picture-supported discourseproductions were also selected to further characterize thesubjects� discourse performance. The nine subtests whichwere either French translations of existing tests or part ofthe PENOwere: for memory—text recall/immediate, textrecall/delayed (Weschler, 1969), and verbal span; forlanguage—naming, verbal fluency/formal criteria, andverbal fluency/semantic criteria, and for visual gnosis—visual discrimination (Agniel, Joanette, Doyon, & Duch-ein, 1993), the bells test (Gauthier, Dehaut, & Joanette,1989), and line orientation judgments (Benton, Varney,& Hamscher, 1978).

2.3. Scoring

Discourse samples were analyzed within the frame-work of a multilayered cognitive model of discourse pro-cessing (Frederiksen et al., 1989; Kintsch & van Dijk,1975, 1978, 1988). This model was adapted to accountfor the expressive aspect of discourse production and,as such, three levels of representation (lexical-semantic,conceptual-semantic, and organizational-semantic) wereretained for analysis. Nine measures that were thoughtto reflect processing at these three levels of representa-tion and that were compatible with measures obtainedin the Alzheimer literature were derived.

2.3.1. Lexical-semantic level

1. The lexical index (LI) provided a measure of the lex-ical conciseness of discourse production. It wasobtained by dividing the number of expected infor-mation units (IU) by the total number of words pro-

duced. An IU was defined as a word or a group ofwords that expressed an unrepeated piece of informa-tion found in the storyline. The LI was therefore pro-portional to the lexical conciseness of a story.

2. The syntactic index (SI) provided a measure of thesyntactic complexity of discourse production. It wasobtained by dividing the number of complex clauses(subordinate, coordinate, and infinitive) by the totalnumber of clauses (simple and complex). The SIwas therefore proportional to the syntactic complex-ity of a story.

3. The referential index (RI) provided a measure of pro-noun use. It was obtained by dividing the number ofpronouns with a specified referent by the total num-ber of pronouns used. The RI was therefore propor-tional to the use of pronouns with specified referents.

2.3.2. Conceptual-semantic level

1. Micropropositions (m) correspond to the smallest unitof meaning in connected speech (Kintsch & van Dijk,1978) and comprise a predicate that qualifies an argu-ment or a predicate that connects two arguments. Inthe example below, predicates (outside the parenthe-ses) and arguments (inside the parentheses) are writ-ten in capital letters to convey the general meaningof the utterance as opposed to its exact wording.

‘‘It is, there are bandits who come into a bank for ahold-up.’’ (Subject 10444, translated from French)m1: BANDITSm2: ENTER (BANDITS, BANK)m3: COMMIT (BANDITS, HOLD-UP)m4: IN ORDER (m2, m3)

The number of micropropositions was defined as thetotal number of all micropropositions produced,regardless of their level of importance. In the exampleabove, the total number of micropropositions corre-sponding to the verbatim sentence ‘‘It is, there arebandits who come into a bank for a hold-up’’ wouldbe four.

2. The number of right-shifts (RS) provided an index ofthe semantic complexity of the discourse. The micro-propositional analysis resulted in the description of asemantic hierarchy (based on argument overlap orlocal coherence) such that the first level of micropro-positions could be considered semantically moreimportant than the second, and so on. This hierarchywas annotated as shifts to the right from the firstmicroproposition. The number of right-shifts wasdefined as the number of different levels within agiven micropropositional hierarchy. In the exampleprovided above, the small network of four micropro-positions derived from the verbatim sentence could be

A. Duong et al. / Brain and Language 93 (2005) 173–184 175

displayed on two levels, thus corresponding to tworight-shifts. The number of right-shifts was thereforeproportional to the semantic complexity of the micro-propositional network.

3. Macropropositions (M) may be defined as the mainideas in a story. Macropropositions correspond tothe core propositions that can be derived from micro-propositions according to the three macro-rules ofreduction, construction, and generalization (Kintsch& van Dijk, 1975). The lists of expected macropropo-sitions for P1 and P7 were taken from Laliberte (1993)and can be found in Appendices A and B, respectively.

2.3.3. Organizational-semantic level

1. The number of elements of the narrative schema (E)provided a measure of the completeness of the narra-tive schema and was obtained by counting all elementswith at least one macroproposition. The narrativeschema corresponds to a canonical structure in whichevents are told in the same temporal and sequentialorder for all narratives, although the main contentof each element depends on the storyline. In the pres-ent study, five elements of the narrative schema (set-ting, complication, resolution, evaluation, andmorals) were used (Kintsch & van Dijk, 1978).

2. The mean number of macropropositions per element

(M/E) provided a measure of the completeness of eachelement and was obtained by summing the percentageof expected macropropositions produced in each ele-ment of the narrative schema and by dividing by thetotal number of elements. Thismeasurewas performedto account for the unevenness of macropropositionsacross the five elements and across the two stories.

3. Transitional markers (TM) provided a measure of theconnections between elements and were defined asany production that was used to link ideas fromtwo different elements. In a narrative schema,expected transitional markers were sequential, tem-poral, or spatial. The number of transitional markerscorresponded to the total number of transitionalmarkers, regardless of their nature.

2.4. Reliability of scoring

A reliability test was performed on the microproposi-tional analysis. This validation was deemed importantbecause most other measures were derived from themicropropositional base. It was performed on every fifthanalysis for both NE and AD samples by the fourthauthor (BS). Reliability measures were defined as thenumber of discrepant micropropositions divided by thetotal number of micropropositions derived by the firstauthor (AD). Agreement between the two authors was95.7%. All remaining discrepancies were subsequentlyresolved by consensus on which results are reported.

2.5. Statistical analysis

To classify subjects into ‘‘naturally’’ occurring sub-groups with similar overall scores, discourse measures(converted into z-scores) were submitted to cluster anal-ysis (Aldenderfer & Blashfield, 1985) using the Clustanprogram (Wishart, 2001). For each production stimulus,a matrix of nine measures (converted to z-scores) by 99subjects was generated. Cluster analysis was then per-formed on each matrix using the Ward�s method, whichuses the smallest variance between any two overall dis-tance measures (in this case, the squared Euclidian dis-tance). Subjects within a cluster thus consisted ofsubjects whose overall distance measure were the mostsimilar and whose overall distance measure differedfrom subjects in all other clusters. The number of clus-ters accepted, and their subject composition, was a vi-sual trade-off between the relative difficulties (seedendograms, Figs. 1A and B) in connecting subjectswithin and between clusters. The number of clusterswas then held constant and the initial cluster composi-tions were internally validated using three relocationprocedures simultaneously (tree partitioned, exemplars,and random assignment). These relocation procedureswere necessary to account for the order of data compar-ison in the Ward�s method that could have influencedthe initial cluster composition. Each of these procedureswas run through 500 iterations for a total of 1500 reiter-ations. Initial cluster solutions were judged internallyvalid if less than 10% of subjects had relocated relativeto the cluster solution that recurred most frequently.

3. Results

3.1. Number of clusters and composition of clusters

Figs. 1A and B depict the number of clusters ob-tained through the Ward�s method for the picture se-quence (P7) and the single picture (P1), respectively.This method identified five different clusters for the pic-ture sequence, and four for the single picture. Validationof these initial clustering solutions using the combinedrelocation procedures revealed very similar clusteringsolutions in which only 9 of the 99 subjects had relo-cated for the picture sequence, and 8 of the 99 subjects,for the single picture.Table 2 depicts the cluster compositions for both pic-

ture stimuli. For the picture sequence, only two of thefive clusters identified were composed (almost) purelyof AD patients; cluster 1/P7 (25 AD, 2 NE) and cluster2/P7 (3 AD). Further, these two ‘‘pure’’ AD clustersonly accounted for 28 of the 46 AD patients (60.8%)suggesting that even a detailed discourse analysis canonly clearly differentiate a little over half the subjectsin an AD sample. The remaining 18 AD patients were


distributed across the remaining three clusters (cluster 3/P7, cluster 4/P7, and cluster 5/P7) composed of NE sub-jects in 1:5, 2:5, and 3:5 ratios, respectively. Contrary tothe picture sequence, cluster compositions for the singlepicture (P1) revealed two pure clusters, one pure ADcluster (cluster 1/P1; 20 AD, 1 NE) and one pure NE

cluster (cluster 3/P1; 1 AD, 10 NE). The pure AD cluster(cluster 1/P1) accounted for even less AD patients (20out of 46 patients or 43.4%) than the pure clusters inthe picture sequence. The remaining AD patients weredistributed across two other clusters (cluster 2/P1 andcluster 4/P1) in 1:1 and 1: 3 ratios, respectively.

Fig. 1. (A) Dendogram for the picture sequence (P7) stimulus using the Ward�s method. Individual vertical lines on the abscissa represent the 99subjects. The five clusters retained are identified in light color. (B) Dendogram for the single picture (P1) stimulus using the Ward�s method.Individual vertical lines on the abscissa represent the 99 subjects. The four clusters retained are identified in light color. (For interpretation of thereferences to colour in this figure legend, the reader is referred to the web version of this article.)

Table 2Cluster compositions for the picture sequence (P7) and the single picture (P1)

Cluster n AD:NE Age Education F:M

Picture sequence

1/P7 27 25:2 76 7.59 25:22/P7 3 3:0 70.7 7 3:03/P7 37 11:27 73.5 9.97 26:114/P7 24 5:19 73.4 9.75 19:55/P7 8 3:5 73.4 11.4 6:2

Single picture

1/P1 21 20:1 76.7 7.24 19:22/P1 41 19:22 74.1 9.17 33:83/P1 11 1:10 75.5 10.8 10:14/P1 26 6:20 71.3 10.5 17:9— — — — — —


4. Discourse patterns

Figs. 2A and B depict discourse patterns produced bysubjects classified through cluster analysis for the picturesequence and the single picture, respectively. Tocompare between production stimuli, results are givenin percent of expected number (measures M, E, andM/E). Measures for which expected numbers were notavailable (measures LI, SI, RI, m, RS, and TM) are gi-ven in percent of highest number produced by any givensubject.Comparisons of the five discourse patterns obtained

in the picture sequence revealed that subjects in the pureAD clusters either performed poorly (cluster 1/P7) ormost poorly (cluster 2/P7) on all nine discourse mea-sures. For each of these two patterns, performancewas slightly lower on the M, E, M/E, and TM measurescompared to the remaining measures. Thus level of per-formance in pure AD clusters resulted in slight contrastsbetween lexical-semantic and organizational-semanticlevel measures, as well as within conceptual-semantic le-vel measures. Subjects in the remaining three mixed clus-ters (cluster 3/P7, cluster 4/P7, and cluster 5/P7)performed clearly better on all nine discourse measures.For these three patterns, performance was more variableon lexical-semantic (SI and RI) and conceptual-semantic

(m and RS) level measures than on conceptual-semantic(M) and organizational-semantic level measures (E,M/E, and TM). Again, contrasts between and withinthe same levels were observed although in the mixedclusters, it is the stability of performance that resultedin these contrasts.While discourse performance may be related to

pathology as above, it may also be related to other fac-tors such as age and education. For example, the lowestperforming cluster in the picture sequence (cluster 1/P7)was composed of the youngest subjects with the leastnumber of years of education. The highest performingcluster in the picture sequence, on the other hand, wascomposed of subjects with the highest number of yearsof education. Because clusters were composed of unevenand sometimes small numbers of subjects, correlationscould not be performed to examine the strength of theobserved association.Contrary to the picture sequence, the single picture

produced discourse patterns that were more quantita-tively and qualitatively distinct. As expected, subjectsin the pure AD cluster (cluster 1/P1) performed the mostpoorly on all nine measures. However, marked impair-ments on conceptual-semantic and organizational-se-mantic measures (approaching 0% of expected values)were observed, thus producing a clear contrast betweenand within these levels. Subjects in the remaining mixedcluster (cluster 2/P1, cluster 3/P1, and cluster 4/P1) per-formed differently on all nine measures. However, thesedifferences were more quantitative in nature as all ninemeasures tended to differ equally from one pattern tothe other. The observed quantitative difference couldbe due a less marked difference in performance betweenlevels of representation. Indeed, it is interesting to notethat while performance in the mixed clusters was morestable on organizational-level measures for the picturesequence, it was less stable with the single picture. Thissuggests that the lack of visual organization inherentin the single picture brought about an increased hetero-geneity on measures reflecting organizational-semanticrepresentations. In the single picture, age seems to beassociated with performance as the cluster that per-formed best on the majority of the nine measures (clus-ter 4/P1) was composed of the youngest subjects.Finally, a comparison between the two picture stimuli

revealed that overall, subjects performed better with thepicture sequence than the single picture. For example,discourse patterns obtained with the picture sequence(especially, cluster 3/P7, cluster 4/P7, and cluster 5/P7)contained higher scores on the M and E measures thandiscourse patterns obtained with the single picture. Be-cause the organization of the story is available visuallythrough the sequence of pictures, it is conceivable thatsome subjects, mostly NE subjects, could have takenadvantage of this facilitating effect, leading to the pro-duction of a higher number of M and E.

Fig. 2. (A) Discourse patterns produced by subjects in the five clustersidentified through the Ward�s method for the picture sequence (P7).Results are given in percent of expected production or percent ofmaximum production. LI, lexical index; SI, syntactic index; RI,referential index; m, micropropositions; RS, right-shifts; M, macro-propositions; E, elements; M/E, mean percent of macropropositionsper element; and TM, transitional markers. (B) Discourse patternsproduced by subjects in the four clusters identified through the Ward�smethod for the single picture (P1). Results are given in percent ofexpected production or percent of maximum production. LI, lexicalindex; SI, syntactic index; RI, referential index; m, micropropositions;RS, right-shifts; M, macropropositions; E, elements; M/E, meanpercent of macropropositions per element; and TM, transitionalmarkers.


4.1. Factor analysis

To confirm the combinations of discourse variablesthat account for subjects� distribution across clusters,principal components factor analyses were performedon each of the picture stimuli using SPSS for Windows(1997). For the picture sequence, a principal componentsfactor analysis with varimax rotations revealed three fac-tors with eigenvalues greater than 1, accounting for74.4.5% of the total variance. Factor 1 accounted for44.4% of the total variance. Loadings on LI, M, E,M/E, and TM suggest that this factor captured the lexi-cal-macro-organizational measures. Factor 2 with load-ings on LI, SI, and m, which accounted for anadditional 18.1% of the total variance, suggest that thisfactor captured the lexical-micropropositional measures.Finally, factor 3 with loading on RS accounted for anadditional 11.9%. The same analysis performed on thesingle picture is less satisfactory at explaining subject� dis-tribution across clusters. Two factors with eigenvaluesgreater than 1 were extracted, which only accounted for64.1% of the total variance. Factor 1 accounted for46.1% of the total variance. Again, with loadings on LI,M, E, M/E, and TM, this factor captured the lexical-macro-organizational measures. Factor 2, which ac-counted for an additional 17.7% loaded on IL, m, andRS, suggesting that it captured the lexical-microproposi-tional measures. In both picture stimuli, low correlationsbetween measures accounted for the observed residualvariance and suggested that each measure carried animportant weight.Tables 3A and 3B summarize the results of principal

components analysis for the picture sequence and thesingle picture, respectively.

4.2. Performance of basic cognitive measures

Figs. 3A and B depict the average performance onbasic cognitive measures obtained by AD subjects dis-

tributed across clusters, for the picture sequence andthe single picture, respectively. Because these measureswere not rated on the same scale, comparisons will onlybe carried out between clusters and not betweenmeasures.For both picture stimuli, a relationship between per-

formance on discourse measures and performance onbasic cognitive measures could be observed. Overall, dis-

Table 3ARotated components matrix for the picture sequence

Measures Component

1 2 3

LI 0.626 �0.665 �0.005SI 0.242 0.609 �0.307RI 0.543 �0.133 0.341m 0.102 0.843 0.311RS 0.113 0.009 0.905M 0.952 0.129 0.054E 0.905 0.111 �0.052M/E 0.95 0.132 0.044TM 0.742 0.0004 0.127

LI, lexical index; SI, syntactic index; RI, referential index; m, micro-propositions; RS, right-shifts; M, macropropositions; E, elements;M/E, mean percent of macropropositions per element; and TM,transitional markers.

Table 3BRotated components matrix for the single picture

Measures Component

1 2

LI 0.624 �0.59SI 0.501 0.286RI 0.565 �0.0088m 0.233 0.863RS 0.109 0.644M 0.927 0.137E 0.913 0.074M/E 0.945 0.123TM 0.643 0.293

LI, lexical index; SI, syntactic index; RI, referential index; m, micro-propositions; RS, right-shifts; M, macropropositions; E, elements;M/E, mean percent of macropropositions per element; and TM,transitional markers.

Fig. 3. (A) Performance on basic cognitive tests obtained by fiveclusters previously identified in the Ward�s method for the picturesequence (P7). Results are given in raw scores for AD subjects withineach cluster. LM-I, logical memory—immediate; LM-D, logicalmemory—delayed; VF-F, verbal fluency—formal criteria; VF-S, ver-bal fluency—semantic criteria; VD, visual discrimination; and LOJ,line orientation judgments. (B) Performance on basic cognitive testsobtained by four clusters previously identified in the Ward�s methodfor the single picture (P1). Results are given in raw scores for ADsubjects within each cluster. LM-I, logical memory—immediate; LM-D, logical memory—delayed; VF-F, verbal fluency—formal criteria;VF-S, verbal fluency—semantic criteria; VD, visual discrimination;and LOJ, line orientation judgments.


course performance and basic cognitive performancefollowed the same ordering for both stimuli suggestingthat the heterogeneity of discourse performance couldbe related to a heterogeneity in the performance on basiccognitive tests. For both stimuli, the most discriminativebasic cognitive subtests were the memory subtests (logi-cal memory—immediate and delayed), the languagesubtests (naming and formal and semantic verbal flu-ency), and the visuo–spatial subtest (line orientation).Most of these variables, however, only discriminated be-tween clusters in which subjects displayed the highestand the lowest performing discourse patterns. This sug-gests that discourse tasks engender more heterogeneitythan basic cognitive tasks.

5. Discussion

The present study addressed three objectives: (1) todescribe discourse patterns in two picture-supportednarratives within the framework of cognitive model ofdiscourse processing, (2) to determine the specificity ofthese discourse patterns with respect to normal andpathological aging, and (3) to examine the relationshipbetween performance on discourse measures and perfor-mance on basic cognitive tests thought to have an im-pact on discourse production. Results indicated thatthe picture sequence stimulus elicited the production offive different discourse patterns while the single picturestimulus led to the production of four different discoursepatterns. However, these observed discourse patternscould not readily distinguish between normal agingand AD, as cluster analysis revealed a number of mixedclusters containing both AD patients and NE subjects.Finally, subjects� performance on discourse measurescould partially be explained by their performance onmemory, language, and visuo–spatial tests.

5.1. The heterogeneity of discourse patterns

The simultaneous description of nine discourse mea-sures reflecting three levels of representation, combinedwith cluster analysis, has led to the identification of dif-ferent discourse patterns for both pictured stimuli.When the composition of these clusters was examined,it was found that for the picture sequence, only 61%of AD patients were classified in relatively pure AD clus-ters. The remaining 39% of AD patients could not bedistinguished from NE subjects on the basis of discourseperformance alone because they were distributed acrossmixed clusters in which NE subjects were also found.The specificity of discourse was even lower in the singlepicture stimulus as only 41% of AD patients were classi-fied in pure AD clusters while the remaining 59% of ADpatients were distributed across a number of mixed clus-ters. Further, the overall discourse performance in these

pure AD clusters was always lower than discourse per-formance in the mixed clusters, suggesting that in thelatter, AD patients tended to behave more like NE sub-jects as reflected in their higher performance on basiccognitive tests.Alternatively, it could be argued that in those mixed

clusters, it is the NE subjects who behaved more like ADpatients. This scenario would be a distinct possibility be-cause the criteria for mild cognitive impairment (MCI),a gray zone between normal aging and AD (Blanchet,McCormick, Belleville, Gely-Nargeot, & Joanette,2002; Chertkow, 2002), had not been specified at thetime this databank was constituted. As a result, NE sub-jects had not been screened specifically for MCI. Theclaim, however, that MCI subjects would produce inter-mediate discourse patterns between those of NE subjectsand AD patients, just as they do for basic cognitive tests(Petersen, 2000) remains a hypothesis that needs to beaddressed specifically. Less hypothetical is that descrip-tions of single discourse measures as opposed to a com-bination of discourse measures, and in conventionalgroup studies as opposed to cluster analytic studies,would likely fail to identify up to half of the AD pa-tients. The heterogeneity of discourse patterns thereforeis not only present, it is also important.

5.2. Sources of heterogeneity

The first candidate to account for discourse heteroge-neity would be severity of cognitive impairment. The rela-tionship between performance on basic cognitive testsand performance on discoursemeasures suggests that dis-course heterogeneity is associated with cognitive hetero-geneity. However, because cognitive performance didnot discriminate between all discourse patterns and be-cause subjects tended to redistribute across clusters fromone discourse production task to the other, cognitive het-erogeneity cannot account entirely for discourseheterogeneity.Another possible source of heterogeneity is subject

characteristics such as age, education, and gender. Forexample, of the five clusters obtained in the picture se-quence, the lowest performing cluster (cluster 2/P7) wascomposed of ADpatients whowere also the youngest. In-versely, of the four clusters obtained in the single picture,the highest performing cluster (cluster 4/P7) was com-posed mostly of NE patients who were also the youngestand the most educated. These results would agree withprevious research in which early age at onset was corre-lated with severity of language impairments in AD(Bayles, 1991; Imamura et al., 1998; but see Selnes, Car-son, Rovner, &Gordon, 1988). The opposite associationswere reported for normal aging in which younger-oldadults or younger-old adults with high levels of educationperformed better than older-old adults on language (Auet al., 1995; Goulet, Ska, & Kahn, 1994) and discourse


tasks (Cooper, 1990; Duong & Ska, 2001). While gendermay also explain some discourse heterogeneity, it is moredifficult to interpret in the present study because of theskewed distribution of men to women. Further, resultsin the literature have been inconsistent with some studiesciting an advantage for men on some language tests (Rip-ich, Petrill, Whitehouse, & Ziol, 1995) while others havereported no sex differences (Hebert et al., 2000).Finally, the picture format may constitute yet another

source of heterogeneity. Examination of discourse pat-terns revealed that differences between patterns obtainedin the picture sequence were more quantitative thanqualitative in nature. Indeed, they differed similarly onthe nine measures without striking contrasts betweenlevels of representation. This could be tied to the lesserorganizational demands of the picture sequence stimu-lus. Because the organization of the story was visuallyprovided by the sequence of pictures, there was no needto organize ideas before expressing them. Subjects there-fore conveyed more or less macropropositions withinthat sequence, a tendency that was confirmed in theprincipal components analysis. When differences in per-formance between the two picture stimuli were consid-ered, the overall number of macropropositionsproduced in response to the picture sequence stimuluswas lower than that produced in response to the singlepicture. While it may be that the picture sequence facil-itates the organization of the story, as attested by a high-er performance on organizational relative to lexicalmeasures, it may be more difficult from a visuo–spatialpoint of view, as attested by a lower performance onmacropropositions overall. This observation was furthercorroborated by the poorer performance on visuo–spa-tial tasks exhibited by subjects who produced the leastnumber of macropropositions.The single picture stimulus, on the other hand,

elicited quantitatively but also qualitatively differentpatterns. In this case, contrasts between the lexical-micropropositional and the macro-organizational mea-sures could be observed, especially for cluster 1/P1(mostly AD) for whom the organizational demands ofthe single picture may have been more difficult. For sub-jects who could meet these organizational demands,however (mostly NE subjects in cluster 3/P1 and cluster4/P1), the single picture actually brings out abilities atthe lexico-micropropositional levels (LI, m, and RS) asconfirmed by the principal components analysis. In lightof a more challenging discourse production task, thesesubjects were able to be lexically more concise while atthe same time managing to convey more microproposi-tions within a semantically richer network.

5.3. Implications for the discourse model

In this study, discourse production was describedwithin the framework of a cognitive model of discourse

processing. The contrasts observed between levels ofrepresentation indicated that these levels might be inde-pendent to some extent. A clear contrast within the con-ceptual-semantic level could be observed for bothpicture stimuli such that micropropositions and numberof right-shifts were often clearly different from macro-propositions. This suggests that within a propositionalanalysis (Kintsch & van Dijk, 1975, 1978) reflecting con-ceptual-semantic units of discourse production, a dis-tinction between micropropositions (or connectedideas) and macropropositions (or connected main ideas)is an important one. Contrasts between discourse pat-terns were confirmed by the principal components anal-ysis although, for the population under study, measuresreflecting the theoretical levels of representation did nottend to correlate as neatly as expected. For example, LI,M, E, and M/E always correlated together to form onefactor capturing lexical-macro-organizational measureswhile LI, m always correlated to form another factor,capturing lexical-micropropositional measures. Further,an important residual variance was left unexplained dueto the low correlations between measures, especially inthe case of the SI and RI measures that did not correlatewith any other measure. This suggests that within theconstraints of the present discourse tasks, each of thesenine measures carried its own weight so as to convey dif-ferent information about the discourse abilities of thepresent subjects. From the point of view of the discoursemodel, all of these measures were necessary to capturethe complexity of the different levels of representation.Description of discourse abilities in different neurologi-cal populations such as traumatic-injury or right-hemi-sphere damage patients might further contribute to thevalidation of the present discourse model.

5.4. Normal vs pathological discourse patterns

Discourse descriptions within a cognitive model haverevealed the heterogeneous nature of discourse produc-tion but have also revealed a gray zone between normaland pathological aging, as attested by the mixed clus-ters. In conventional group studies, normality is as-sumed to be homogeneous and often definedstatistically. Abnormality is then defined with referenceto this statistical norm. In the present cluster analysisstudy, results indicated that in both NE subjects inAD patients, performance on individual measures didnot vary to the same degree in the same individual. Fur-ther, difficulty on one measure was often balanced by abetter performance on another measure such that over-all, discourse and communication might appear func-tional. This raises the question as to what constitutes aprototypical AD discourse pattern or even if one exists.How much impairment on any given measure or howmany levels of representation must be impaired to con-stitute a clear AD discourse pattern? Again, answers to


these questions may come about with a better under-standing of the discourse patterns produced by otherneurological populations. This will not only clarify dis-tinctions between normal and AD discourse patternsbut also distinctions between AD and other age-associ-ated neurological pathologies.Clearly the relevance of including discourse in a diag-

nostic battery is premature. For the moment, discoursealone may not be so useful in providing a differentialdiagnosis. This practice would be more suitable for con-trived and decontextualized tasks (such as picture nam-ing) that are more sensitive to the early breakdown ofthe semantic system (Chertkow & Bub, 1990). Rather,the relevance of discourse may reside in assessing thefunctional communication of AD patients as well asits follow-up. For example, identification of a particulardiscourse pattern for a given individual may proveimportant in understanding how that individual, in lightof his/her cognitive impairments, can make use of theredundancy of information present in discourse to com-municate. Further, consideration of retained relative toimpaired abilities may prove useful in tracking changesbrought about by the progression of the disease for thatsame individual. Discourse therefore constitutes a moresophisticated therapeutic tool than the simple learningof word lists. Eventually, the use of retained discourseabilities and discourse strategies in combination with apharmacological treatment may constitute a startingpoint in a comprehensive intervention program in AD.

Acknowledgments

This research was supported by grants from theFonds de la recherche en sante du Quebec (FRSQ),the Reseau de Sante Mentale du Quebec (RSMQ), andthe Universite de Montreal awarded to the first author.

Appendix A. Single picture (P1) Bank robbery story

(Nespoulous et al., 1992)

Elements of thenarrative schema(Kintsch andvan Dijk, 1975)

List of macropropositions(Laliberte, 1993) translatedfrom French

Setting (1) IN (PEOPLE, BANK)Complication (2) ATTACK (ROBBERS, BANK)

(3) ARMED (ROBBERS)(4) WAIT (ROBBER, ROBBERS)(5) IN (ROBBER, CAR)(6) STEAL (ROBBERS, MONEY)(7) HELD UP (PEOPLE)

Resolution (8) IN (MAN, OFFICE)(9)TELEPHONE(MAN,POLICE)(10) WITNESS (PASSERBY,

CRIME)

Appendix A (continued)

(11) CALL (PASSERBY,POLICEMAN)

Evaluation (12a) LEFT (VOLEURS)2 possibilities (12b) CATCH (POLICE, ROBBERS)Morals Any value judgment in

reaction to events associatedwith a bank robbery

Appendix B. Picture sequence (P7) Car accident story

Elements of the narrativeschema (Kintsch andvan Dijk, 1975)

List of macropropositions(Laliberte, 1993) translatedfrom French

Setting (1) MOTHER(2) CHILDREN(3) IN (CHILDREN, CAR)(4) GO (MOTHER,

GROCERIES STORE)(5) WAVE GOODBYE

(MOTHER, CHILDREN)Complication (6) GO (CHILD, FRONT)

(7) PLAY (CHILD, BREAK)(8) ROLL (CAR)(9) DOWN ((8), HILL)

Resolution (10) HIT (CAR, LAMPOST)(11) SMASHED (CAR)(12) SMASHED (LAMPOST)

Evaluation (13) BACK (MOTHER,GROCERIES STORE)

2 possibilities (14) ANGRY (MOTHER)(15) ADMONISH (MOTHER,

CHILDREN)(16) SHEEPISH (CHILDREN)(17) DRIVE AWAY (MOTHER)

Morals (18) STAY (CHILDREN,ALONE, CAR)

(19) UNSAFE (18)

References

Agniel, A., Joanette, Y., Doyon, B., Duchein, C., et al. (1993).Protocole devaluation des gnosies visuelles Montreal-Toulouse—

PEGV. France: L�ortho-Edition, Isbergues.Aldenderfer, M. S., & Blashfield, R. K. (1985). Cluster analysis.

Beverly Hills, CA: Sage Publications.Almor, A., Kempler, D., MacDonald, M. C., Andersen, E. S., & Tyler,

L. K. (1999). Why do Alzheimer patients have difficulty withpronouns? Working memory, semantics, and reference in compre-hension and production in Alzheimer�s disease. Brain and Lan-

guage, 67, 202–227.Altmann, L. J. P., Kempler, D., & Andersen, E. S. (2001). Speech

errors in Alzheimer�s disease: Reevaluating morphosyntactic pres-ervation. Journal of Speech Language and Hearing Research, 44,1069–1082.

American Psychiatric Association (2000). DSM-IV-TR: Diagnostic and

statistical manual of mental disorders (4th ed). Text Revision,Washington, DC.


Appell, J., Kertesz, A., & Fisman (1982). A study of languagefunctioning in Alzheimer patients. Brain and Language, 17, 73–91.

Au, R., Joung, P., Nicholas, M., & Obler, L. K. (1995). Naming abilityacross the adult life span. Aging and Cognition, 2, 300–311.

Bates, E., Harris, C.,MarchmanWulfeck, B., &Kritchevsky,M. (1999).Production of complex syntax in normal ageing and Alzheimer�sdisease. Language and Cognitive Processes, 10, 487–539.

Bayles, K. A. (1991). Age at onset of Alzheimer�s disease. Relation tolanguage dysfunction. Archives of Neurology, 48, 155–159.

Bayles, K. A., Kaszniak, A. W., & Tomoeda, C. K. (1987).Communication and cognition in normal aging and dementia. Boston,MA: College-Hill Press.

Benton, A. L., Varney, N. R., & Hamscher, K. (1978). Visuospatialjudgements: A clinical test. Archives of Neurology, 35, 364–367.

Blanchet, S., McCormick, L., Belleville, S., Gely-Nargeot, M.-C., &Joanette, Y. (2002). Mild cognitive impairment in the elderly: Acritical review. Revue Neurologique, 158, 29–39.

Bschor, T., Kuhl, K. P., & Reischies, F. M. (2001). Spontaneousspeech of patients with dementia of the Alzheimer type and mildcognitive impairment. International Psychogeriatrics, 13, 289–298.

Caramelli, P., Mansur, L. L., & Nitrini, R. (1998). Language andcommunication disorders in dementia of the Alzheimer type. In B.Stemmer & H. A. Whitaker (Eds.), Handbook of neurolinguistics

(pp. 463–473). San Diego, CA: Academic Press.Chenery, H. J., & Murdoch, B. E. (1994). The production of narrative

discourse in response to animations in persons with dementia of theAlzheimer�s type: Preliminary findings. Aphasiology, 8, 159–171.

Chertkow, H. (2002). Mild cognitive impairment. Current Opinions in

Neurology, 15, 401–407.Chertkow, H., & Bub, D. (1990). Semantic memory loss in dementia of

Alzheimer�s type. What do various measures measure?. Brain, 113,397–417.

Cooper, P. V. (1990). Discourse production and normal aging:Performance on oral picture description tasks. Journals of Geron-tology, 45, 210–214.

Croisile, B., Ska, B., Brabant, M. J., Duchene, A., Lepage, Y., Aimard,G., et al. (1996). Comparative study of oral and written picturedescription in patients with Alzheimer�s disease. Brain and Lan-

guage, 53, 1–19.Duong, A., & Ska, B. (2001). Production of narratives: Picture

sequence facilitates organizational but not conceptual processing inless educated subjects. Brain and Cognition, 46, 121–124.

Ehrlich, J. S. (1994). Studies of discourse production in adults withAlzheimer�s disease. In R. L. Bloom, L. K. Obler, S. DeSanti, & J.S. Ehrlich (Eds.), Discourse analysis and applications: Studies in

adult clinical populations (pp. 149–160). Hillsdale, NJ: LawrenceErlbaum Associates.

Ehrlich, J. S., Obler, L. K., & Clark, L. (1997). Ideational and semanticcontributions to narrative production in adults with dementia ofthe Alzheimer�s type. Journal of Communication Disorders, 30,79–99.

Fisher, N. J., Rourke, B. P., Bieliauskas, L., Giordani, B., Berent, S., &Foster, N. L. (1996). Neuropsychological subgroups of patientswith Alzheimer�s disease. Journal of Clinical and Experimental

Neuropsychology, 18, 349–370.Frederiksen, C. H., Bracewell, R. J., Breuleux, A., & Renaud, A.

(1989). The cognitive representation and processing of discoursefunction and dysfunction. In Y. Joanette & H. H. Brownell (Eds.),Discourse ability and brain damage: Theoretical and empirical

perspectives (pp. 19–44). New York, NY: Springer Verlag.Gauthier, L., Dehaut, F., & Joanette, Y. (1989). The Bells test: A

quantitative and qualitative test for visual neglect. InternationalJournal of Clinical Neuropsychology, 11, 49–54.

Giles, E., Patterson, K., & Hodges, J. R. (1996). Performance on theBoston Cookie Theft picture description task in patients with earlydementia of the Alzheimer�s type: Missing information. Aphasiol-ogy, 10, 395–408.

Glosser, G., & Deser, T. (1990). Patterns of discourse productionamong neurological patients with fluent language disorders. Brainand Language, 40, 67–88.

Glosser, G., & Deser, T. (1992). A comparison of changes inmacrolinguistic and microlinguistic aspects of discourse productionin normal aging. Journal of Gerontology, 47, 266–272.

Goulet, P., Ska, B., & Kahn, H. J. (1994). Is there a decline in picturenaming with advancing age?. Journal of Speech and Hearing

Research, 37, 629–644.Hebert, L. E., Wilson, R. S., Gilley, D. W., Beckett, L. A., Scherr,

P. A., Bennett, D. A., et al. (2000). Decline of language amongwomen and men with Alzheimer�s disease. Journals of Geron-

tology Series B-Psychological Sciences and Social Sciences, 55,354–360.

Imamura, T., Takatsuki, Y., Fujimori, M., Hirono, N., Ikejiri, Y.,Shimomura, T., et al. (1998). Age at onset and language distur-bances in Alzheimer�s disease. Neuropsychologia, 36, 945–949.

Joanette, Y., Ska, B., Poissant, A., & Beland, R. (1992). Neuro-psychological aspects of Alzheimer�s disease: Evidence for inter-and intra-function heterogeneity. In F. Boller, F. Forette, Z.Khachaturian, M. Poncet, & Y. Christen (Eds.), Heterogeneity

of Alzheimer�s disease (pp. 33–42). New York, NY: Springer-Verlag.

Joanette, Y., Ska, B., Poissant, A., Belleville, S., Bellavance, A.,Gauthier, S., et al. (1995a). Evaluation neuropsychologiqe etprofils cognitifs des demences de type Alzheimer: Dissociationstransversales et longitudinales. In F. Eustache & A. Agniel (Eds.),Neuropsychologie clinique des demences: evaluations et prises en

charge (pp. 91–106). Solal: Marseilles.Joanette, Y., Ska, B., Poissant, A., Belleville, S., Lecours, A. R., &

Peretz, I. (1995b). Evaluation neuropsychologique dans la demencede type Alzheimer: Un compromis optimal. Annee gerontologique

(suppl Maladie d�Alzheimer), 2, 69–83.Kintsch, W., & van Dijk, T. A. (1975). Comment on se rappelle et on

se resume des histoires. Languages, 40, 98–116.Kintsch, W., & van Dijk, T. A. (1978). Towards a model of text

comprehension and production. Psychological Review, 85, 363–395.Kintsch, W. (1988). The role of knowledge in discourse comprehen-

sion: A construction-integration model. Psychological Review, 95,163–182.

Laliberte, H., 1993. Schema narratif dans la production discursive desdements de type Alzheimer. Unpublished Master�s thesis, Univer-site de Montrel.

LeDorze, D. G., & Bedard, C. (1998). Effects of age and education onthe lexico-semantic content of connected speech in adults. Journalof Communication Disorders, 31, 53–70.

Mackenzie, C. (2000). Adult spoken discourse: The influences of ageand education. International Journal of Language and Communica-

tion Disorders, 35, 269–285.Martin, A., Brouwers, P., Lalonde, F., Cox, C., Teleska, P., Fedio, P.,

et al. (1986). Towards a behavioral typology of Alzheimer�spatients. Journal of Clinical and Experimental Neuropsychology, 8,594–610.

McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., &Stadlan, E. M. (1984). Clinical diagnosis of Alzheimer�s disease:report of the NINCDS-ADRDA Work Group under the auspicesof Department of Health and Human Services Task Force onAlzheimer�s Disease. Neurology, 34, 939–944.

Nespoulous, J. L., Lecours, A. R., Lafond, D., Lemay, A., Puel, M., &Joanette, Y., et al. (1992). Protocole Montr eal-Toulouse. Examende l�aphasie. Version Beta modifiee, Editions Ortho.

Nicholas, M., Obler, L. K., Albert, M. L., & Helm-Estabrooks, N.(1985). Empty speech in Alzheimer�s disease and fluent aphasia.Journal of Speech and Hearing Research, 28, 405–410.

Norman, S., Kemper, S., & Kynette (1992). Adults� reading compre-hension: Effects of syntactic complexity and working memory.Journals of Gerontology, 47, P258–P265.


Obler, L. K., Au, R., Kugler Melvold, J., Tocco, M., & Albert, M.L. (1994). Intersubject variability in adult normal discourse. InR. L. Bloom, L. K. Obler, S. De Santi, & S. Ehrlich Jonathan(Eds.), Discourse analysis and applications: Studies in adult

clinical populations (pp. 15–27). Hillsdale, NJ: Lawrence ErlbaumAssociates.

Orange, J. B., & Kertesz, A. (2000). Discourse analyses and dementia.Brain and Language, 71, 172–174.

Petersen, R. C. (2000). Aging, mild cognitive impairment, andAlzheimer�s disease. Neurological Clinics, 18, 789–806.

Reisberg, B., Ferris, S. H., de Leon, M. J., & Crook, T. (1982). TheGlobal Deterioration Scale for assessment of primary degenerativedementia. American Journal of Psychiatry, 139, 1136–1139.

Ripich, D. N., Petrill, S. A., Whitehouse, P. J., & Ziol, E. W. (1995).Gender differences in language of AD patients: A longitudinalstudy. Neurology, 45, 299–302.

Selnes, O. A., Carson, K., Rovner, B., & Gordon, B. (1988). Languagedysfunction in early- and late-onset possible Alzheimer�s disease.Neurology, 38, 1053–1056.

Shadden, B. B. (1997). Discourse behaviors in older adults. Seminars in

Speech and Language, 18, 143–156.Ska, B., Joanette, Y., Poissant, A., Beland, R., & Lecours, A. R.

(1990). Language disorders in dementia of the Alzheimer type:Contrastive patterns from a multiple single case study. Abstract ofthe Academy of aphasia, 28th Annual Meeting.

Tomoeda, C. K., & Bayles, K. A. (1993). Longitudinal effects ofAlzheimer disease on discourse production. Alzheimer Disease and

Associated Disorders, 7, 223–236.Tomoeda, C. K., Bayles, K. A., Trosset, M. W., Azuma, T., &

McGeagh, A. (1996). Cross-sectional analysis of Alzheimer diseaseeffects on oral discourse in a picture description task. Alzheimer

Disease and Associated Disorders, 10, 204–215.Valdois, S., Joanette, Y., Poissant, A., Ska, B., & Dehaut, F. (1990).

Heterogeneity in the cognitive profile of normal elderly. Journal ofClinical and Experimental Neuropsychology, 12, 587–596.

Weschler, D. (1969). Manuel de l�echelle clinique de memoire de D.

Weschler. Paris: Les editions du centre de psychologie appliquee.Wishart, D. (2001). ClustanGraphics5�. Edinburgh: Clustan Limited.


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The heterogeneity of picture-supported narratives in Alzheimer’s disease