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Verbal working memory and its relationship to sentence-level reading andlistening comprehension in persons with aphasiaJee Eun Sunga; Malcolm R. McNeila; Sheila R. Pratta; Michael Walsh Dickeya; William D. Hulaa; Neil J.Szuminskya; Patrick J. Doylea

a University of Pittsburgh and VA Pittsburgh Healthcare System, Pittsburgh, PA, USA

First published on: 03 December 2010

To cite this Article Sung, Jee Eun , McNeil, Malcolm R. , Pratt, Sheila R. , Dickey, Michael Walsh , Hula, William D. ,Szuminsky, Neil J. and Doyle, Patrick J.(2009) 'Verbal working memory and its relationship to sentence-level reading andlistening comprehension in persons with aphasia', Aphasiology, 23: 7, 1040 — 1052, First published on: 03 December 2010(iFirst)To link to this Article: DOI: 10.1080/02687030802592884URL: http://dx.doi.org/10.1080/02687030802592884

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http://www.psypress.com/aphasiology DOI: 10.1080/02687030802592884

Verbal working memory and its relationship to sentence-level

reading and listening comprehension in persons with aphasia

Jee Eun Sung, Malcolm R. McNeil, Sheila R. Pratt, Michael WalshDickey, William D. Hula, Neil J. Szuminsky, and Patrick J. Doyle

University of Pittsburgh and VA Pittsburgh Healthcare System, Pittsburgh, PA, USA

Background: Working memory (WM) has gained recent attention as a cognitiveconstruct that may account for language comprehension deficits in persons with aphasia(PWA) (Caspari, Parkinson, LaPointe, & Katz, 1998; Martin, Kohen, & Kalinyak-Fliszar, 2008; Wright, Downey, Gravier, Love, & Shapiro, 2007). However, few studieshave investigated individual differences in performance on sentence comprehensiontasks as a function of WM capacity in PWA when WM demands are manipulated.Aims: The purposes of the current study were: (1) to examine the relationships amongverbal WM, sentence comprehension, and severity of impairment in PWA and (2) toinvestigate the differential performance of high versus low verbal WM groups onsentence comprehension tasks in which task demands were manipulated by the length ofthe sentence stimuli, complexity of syntactic structure, and by presentation methodwhich varied the time over which the linguistic material was available for computation.Methods & Procedures: A total of 20 PWA were divided into high and low WM groupsbased on a listening version of a WM sentence span task. Each participant completed alistening version (CRTT) and three reading versions (CRTT-R) of the ComputerisedRevised Token Test as the sentence comprehension tasks.Outcomes & Results: The WM task significantly predicted performance on the CRTTconditions in which information was only temporarily available, thereby imposinggreater WM demands on sentence comprehension. The verbal WM task wassignificantly correlated with aphasia severity and a principal components analysisrevealed that the WM task, overall aphasia severity, and overall reading impairmentlevel loaded on a single factor with 76% of shared variance. The low WM group’sperformance was significantly lower than the high WM group on the CRTT subtestswith syntactically more complex structures and on the CRTT conditions withtemporally restricted presentation methods.Conclusions: This verbal WM task was significantly and moderately correlated with theoverall severity of aphasia as well as with both listening and reading sentencecomprehension. The WM group differences emerged only in sentence comprehensiontasks with greater WM demands. These results are consistent with the notion that WMeffects are most evident when WM capacity is sufficiently taxed by the task demands(e.g., Caplan & Waters, 1999; Just & Carpenter, 1992).

Keywords: Working memory; Aphasia; Sentence comprehension; Aphasia severity.

Address correspondence to: Jee Eun Sung, 4033 Forbes Tower, Communication Science & Disorders,

University of Pittsburgh, PA 15260, USA. E-mail: jee311@gmail.com

This research was supported by the VA Research & Development Grant C4074X and in part by VA

Research & Development Grant C3318R. The authors are grateful to the audience at the 38th annual

Clinical Aphasiology Conference, to all of the participants in the study, and to Aelee Kim, MaryBeth

Ventura, Tepanta Fossett, and Wiltrud Fassbinder for their help with various phases of the study.

APHASIOLOGY, 2009, 23 (7–8), 1040–1052

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The concept of working memory (WM) has gained acceptance as a cognitive

mechanism relevant for sentence comprehension. The concept was proposed with the

incorporation of a computational working component in short-term storage

(Baddeley, 1986; Baddeley & Hitch, 1974). Given that persons with aphasia

(PWA) have sentence comprehension impairments, it is reasonable to explore the

construct of WM to account for these language-processing impairments. A number

of studies have suggested that verbal WM tasks such as sentence span tasks (Caspari

et al., 1998; Tompkins, Bloise, Timko, & Baumgaertner, 1994) or n-back types ofWM tasks (Martin et al., 2008; Wright et al., 2007) are related to sentence

comprehension measures in PWA. One research group proposed that syntactic

comprehension deficits in aphasia are, in part, attributed to limited WM capacity

(Miyake, Carpenter, & Just, 1994). This argument was based on findings that when

WM capacity is sufficiently taxed, normal individuals’ performance on sentence

comprehension is diminished as a function of syntactic complexity. These patterns of

degradation, especially in individuals with lower WM capacity, were claimed to be

similar to that of PWA. However such findings, and their significance for therelationship between the WM capacity and sentence comprehension, have been

controversial for both normal and clinical populations. Some researchers have claimed

that there is a single WM capacity engaged in all types of language processing (Just &

Carpenter, 1992; King & Just 1991; Miyake et al., 1994), while others have argued that

there are different verbal WM or short-term memory (STM) systems depending on the

type of linguistic information, such as phonological, semantic, and syntactic structure

(Caplan & Waters, 1999; Friedmann & Gvion, 2003; Martin et al., 2008; Waters &

Caplan, 1996; Wright et al., 2007). Regardless of the hypotheses about single versusmultiple WM systems, there is a common underlying assumption that the effects of

WM capacity on language processing manifest themselves most evidently when the task

demands are high enough to exceed WM capacity.

Although there are increasing numbers of studies investigating the relationship

between WM and sentence comprehension in PWA, there are few studies that have

investigated whether there are individual differences in performance on sentence

comprehension tasks as a function of WM capacity when WM demands are

manipulated. The WM demands have been manipulated in several ways in previousstudies, such as by adding a concurrent memory load to sentence processing or by

manipulating syntactic complexity (Caplan & Waters, 1996; Fedorenko, Gibson, &

Rohde; 2006; King & Just, 1991; Waters, Caplan, & Yampolsky, 2003). Adding

extra linguistic material such as padding adjectives, prepositional phrases, or

adverbial clauses has also been used to manipulate processing difficulty with a

presumed effect on WM. This type of approach was used in the construction of the

Revised Token Test (RTT) (McNeil & Prescott, 1978), which systematically varies

the number of linguistic units and syntactic structures across its 10 subtests.The RTT was designed to minimise top-down language processing by carrying

relatively decontextualised linguistic elements such as shapes, colours, and sizes but

with the syntactic requirement to integrate each lexical item into the identification of

a single, identifiable target. Because context and lexical-semantics are highly

constrained in the RTT, thereby reducing the processing burden at these cognitive/

linguistic levels, this task is a good candidate for studying memory-related effects on

sentence comprehension. The RTT has been recently computerised (Computerised

Revised Token Test, CRTT) (McNeil et al., 2008b) and the CRTT makes it easy tomanipulate the presentation methods that impose differential WM demands on the

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task. These methodological properties make the CRTT an especially good task for

investigating issues of WM and sentence comprehension among persons with

aphasia. Furthermore, the CRTT has been demonstrated to have good construct and

concurrent validity, and high test–retest reliability as a measure of sentence

comprehension deficits in PWA (McNeil et al., 2008a, 2008c).

The first purpose of the current study was to examine the relationship between

WM capacity and sentence comprehension in PWA. More specifically, the study

investigated which of the following factors best predicted performance on listening(CRTT-auditory) and reading comprehension (CRTT-R) tasks in PWA: (a) verbal

WM, as assessed by a listening WM span task (Tompkins et al., 1994), (b) overall

aphasia severity, as measured by Porch Index of Communicative Ability (PICA)

(Porch, 2001), and (c) overall severity of reading impairment, as measured by

Reading Comprehension Battery for Aphasia (RCBA-2; 2nd edition) (LaPointe &

Horner, 1998). It was hypothesised that the verbal WM measure would significantly

predict performance on the CRTT conditions in which sentences were syntactically

more complex or long, and/or information was only temporarily available.The second purpose of the study investigated WM group differences for the PWA

as a function of syntactic complexity, sentence length, and task demands for

maintaining the linguistic information over time. It was hypothesised that the effects

of WM capacity on sentence comprehension would differentially challenge the low

WM group on CRTT subtests that have more syntactically complex constructions,

more lexical items to be comprehended, and under task conditions that make

linguistic information available for processing over a shorter period of time.

METHOD AND PROCEDURE

Participants

A total of 20 persons with aphasia with a history of left-hemisphere cerebrovascular

accident completed the following screening procedures: (a) the Picture Identification

Task (Wilson & Antablin, 1980) with a score of 50% or better, (b) vision screeningwith the reduced Snellen chart with 20/40 or better visual acuity (with correction if

necessary), and (c) performance on the language recall task of the Assessment

Battery of Communication in Dementia (ABCD) (Bayles & Tomoeda, 1993) yielding

a ratio (the delayed recall/immediate recall 6 100) greater than 0.70 on the delayed

recall compared to the immediate recall. The participants demonstrated language

performance consistent with the McNeil and Pratt (2001) definition of aphasia as

determined by performance on the PICA, (M %ile 5 75, SD 5 10, Range 5 57–89).

Of the 20 PWA, 1 presented with a mild severity apraxia of speech. This participantwas included in the study because it was judged that his speech production disorder

would not affect performance on the verbal WM measure. Additional language

performance and other descriptive information for the RCBA-2, hearing threshold,

age, education, months post-onset, and gender for each participant for each WM

group is summarised in Table 1.

Stimuli and tasks

WM capacity measure. A listening version of the sentence span task, modified byTompkins et al. (1994), was employed to estimate each participant’s verbal WM

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TABLE 1Descriptive information for individuals with aphasia

Low WM group WM PICA (%ile) RCBA-2 (OA) Age (yrs) Ed. (yrs) PTA MPO Gender

1 6 69 166 40 18 18.33 12 M

1 11 57 166 76 12 10.01 564 F

1 15 66 181 72 14 18.33 444 F

1 15 72 178 60 16 17.5 24 M

1 15 70 157 70 12 29.17 29 F

1 17 73 178 63 14 17.5 456 F

1 17 76 172 66 12 20 192 M

1 18 59 184 63 18 21.67 46 M

1 19 84 184 49 16 15.84 71 F

1 19 76 179 82 16 12.48 106 M

Mean (SD) 15 (4) 70 (8) 175 (9) 64 (12) 15 (2) 18.08 (5.18) 194 (211) F55, M55

High WM group WM PICA (%ile) RCBA-2 (OA) Age (yrs) Ed. (yrs) PTA MPO Gender

2 20 66 186 61 16 58.75 15 F

2 20 71 176 69 10 15.82 453 F

2 22 86 185 66 13 32.5 25 F

2 25 69 174 62 16 19.15 60 M

2 25 83 189 90 12 20.82 58 M

2 26 76 179 65 12 12.5 201 M

2 28 88 182 56 18 47.5 31 M

2 30 89 190 53 18 31.67 88 F

2 36 88 187 43 14 26.6 91 M

2 36 89 190 51 18 17.25 139 F

Mean (SD) 27 (6) 81 (9) 184 (6) 62 (13) 15 (3) 28.25 (14.89) 116 (131) F55, M55

Total Group Mean (SD) 21 (8) 75 (10) 179 (9) 63 (12) 15 (3) 23.17 (12.04) 155 (176) F510, M510

WM group: Participants were divided into low and high WM groups based on a median split measure (Group 15Low WM group; Group 25High WM group). WM: A total

number of words recalled from a listening version of sentence span task (Tompkins et al., 1994). One-way ANOVA revealed that WM scores were significantly higher in the high

WM group than the low WM group, F(1, 18)526.96, p,.001. PICA: Porch Index of Communicative Ability (Porch, 2001). One-way ANOVA revealed that PICA scores were

significantly higher in the high WM group than the low WM group, F(1, 18)57.16, p,.05. RCBA-2 (OA): Overall scores of the Reading Comprehension Battery for Aphasia

(LaPointe & Horner, 1998). One-way ANOVA revealed that RCBA-2 scores were significantly higher in the high WM group than the low WM group, F(1, 18)57.57, p,.05. Ed.:

Education. There were no significant differences between the two WM groups, F(1, 18)5.007, p..05. PTA: Pure Tone Average. There were no significant differences between the

two WM groups, F(1, 18)54.16, p..05. MPO: Months-post-onset. There were no significant differences between the two WM groups, F(1, 18)5.99, p..05.

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capacity. This task assesses the ability to process and simultaneously maintain

language information over a systematic increase in the number of sentences over

which the information has to be maintained. The WM stimuli consisted of 42 simple

active declarative sentences that had three words including a transitive verb and its

corresponding two arguments. These sentences were grouped into the four levels

from level 2 (two sentences per set) to level 5 (five sentences per set), in which three

sets of sentences are presented per level. The participants were required to listen to

each sentence and decide whether the sentence was true or false. After each set of

sentences was presented, the participants were asked to recall the last words from

each sentence. The total number of words recalled served as the dependent measure

of the participants’ WM capacity. Individual WM scores are provided in Table 1.

Sentence comprehension tasks. The CRTT was employed as listening and reading

sentence comprehension tasks. The test consists of 10 subtests with 10 items per

subtest. The command lengths vary from three, four, five, six, and eight critical

lexical items, each of which is individually scored. For example, in Subtest I there are

three linguistic elements in each of the 10 commands (e.g., touch the red circle) that

receive an individual score based on a 15-point multidimensional scoring system. In

contrast, there are a total of eight critical linguistic elements in Subtest IV (e.g.,

touch the little red circle and [touch] the big blue square). The basic syntactic

structures of the RTT consist of either simple (Subtests I and II) or compound

imperatives (Subtests III and IV), prepositional phrases (Subtest V through VIII) or

adverbial clauses or phrases (Subtest XI and X) that each vary in sentence length.

Specific examples for each subtest are provided in Table 2.

Experimental procedures

All participants completed the four different versions of the CRTT with

presentation order randomised across participant. The versions consisted of the

TABLE 2Syntactic structures of the Computerised Revised Token Test per subtest with specific examples

Syntactic

structures

aNumber of linguistic

elements (words) Examples

Subtest_1 SI 3 (4) Touch the black circle.

Subtest_2 SI 4 (5) Touch the big green circle.

Subtest_3 CI 6 (8) Touch the green square and the black square.

Subtest_4 CI 8 (10) Touch the big green square and the little black square.

Subtest_5 SI-GSP 6 (8) Put the black square by the red circle.

Subtest_6 SI-GSP 8 (10) Put the big red square before the big white circle.

Subtest_7 SI-DP 6 (11) Put the black circle to the right of the white square.

Subtest_8 SI-DP 8 (13) Put the little green circle to the left of the big red square.

Subtest_9 SI-AC/P 4 (9 – 12) Instead of the green square, touch the black square.

Subtest_10 SI-AC/P 5 (11–14) Touch the big black square unless you have touched the

little red circle.

a: Number of linguistic elements is presented based on the units which will receive individual scores.

SI: Simple Imperative. CI: Compound Imperative. SI-GSP: Simple Imperative with General Spatial

Prepositions. SI-DP: Simple Imperative with Directional Prepositions. SI-AC/P: Simple Imperative with

Adverbial Clause/Phrase.

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auditory version (CRTT) with commands presented acoustically, and three reading

versions (CRTT-reading; CRTT-R), with the commands presented visually. In the

auditory condition commands were pre-recorded and presented via loudspeakers at

75dB SPL as measured with a sound-level meter at the ear, approximately 24 inches

away from the loudspeaker. In the reading conditions commands were presented in

a textbox at the bottom of a 15-inch touchscreen in Arial 36-point font size under

three different stimulus presentation conditions: (1) complete command presenta-

tion (full-sentence; CRTT-R-FS), (2) self-paced word-by-word with each word

remaining on the screen (word constant, CRTT-R-WC), and (3) self-paced word-

by-word presentation, with each previous word disappearing with the onset of the

following word (word-fade; CRTT-R-WF). In the CRTT-R-WC and CRTT-R-WF

conditions the words appeared in their natural left to right position on the screen

without cues as to the length or position of the upcoming words. These stimulus

presentation methods were employed based on the assumption that the CRTT-

auditory and CRTT-R-WF conditions employ different modalities (auditory vs

visual) but are similar in making the linguistic information temporarily available.

The CRTT-R-FS, considered to be most analogous to natural reading, and

the CRTT-R-WC were assumed to be less memory demanding compared to the

auditory and CRTT-R-WF conditions, because the participants have the

opportunity re-read previous material as needed in the CRTT-R-FS and CRTT-

R-WC conditions.

RESULTS

Multiple stepwise regressions and correlations

In order to investigate which factors predicted CRTT-auditory and CRTT-R

performance among the WM, PICA (overall aphasic severity), and RCBA-2 (overall

reading impairment) measures, multiple stepwise regression analyses with forward

selection were performed. Overall scores for the three measures were entered as

predictors. The WM measure was a significant predictor (p (.05) and the largest

contributor to the CRTT-auditory, (R2 5 .36, p , .01) and CRTT-R-WF (R2 5 .36,

p , .01) overall scores. Overall reading ability, as assessed by the RCBA-2, best

predicted performance in the CRTT-R-FS condition (R2 5 .33, p , .05). PICA

performance was the best predictor of CRTT-R-WC performance (R2 5 .41, p ,

.005).

In order to examine whether the predicted relationship between the WM measure

and the two more WM-demanding CRTT conditions (CRTT-auditory and CRTT-

R-WF) would remain significant after controlling language severity as measured by

the PICA and RCBA-2, partial correlations between WM and each of the two

CRTT condition were computed. The relationship between WM and the CRTT-

auditory condition remained significant when the PICA score was partialled out, r 5

.53. However, the relationship decreased substantively when the RCBA-2 was

removed, r 5 .36, or when both the PICA and RCBA-2 were removed together, r 5

.39. The correlations between WM and the CRTT-R-WF condition were reduced

from r 5 .60 to r 5 .39 with the PICA partialled out and to r 5 .38 with the RCBA-2

removed. When both language factors were removed the correlation was reduced to

r 5 .27. The results for all of the partial correlations in the CRTT-auditory and

CRTT-R-WF are provided in Table 3.

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Given that the results of the partial correlations suggested the WM task and two

language measures (PICA and RCBA-2) may have shared the majority of the

variance that they contributed, a principal component analysis (PCA) was

performed to examine whether the WM task and the two language measures loaded

on the same factor. The results revealed a single factor solution that accounted for

76% of the total variance and that all three tasks highly loaded onto the first

component. Factor loadings were .92 for the WM task, .85 for the RCBA-2, and .85

for the PICA.

In order to investigate the relationships among the CRTT-auditory and CRTT-R

conditions, and the measures of aphasia severity and working memory, Pearson

correlation coefficients were computed among the working memory (WM) measure,

the measure of overall severity of aphasia (PICA), and the overall measure of

reading impairment (RCBA-2). Several of these three measures were positively and

significantly correlated with the CRTT-auditory and the CRTT-R conditions. The

WM and RCBA-2 were significantly correlated with the CRTT-Auditory (r 5 .60, p

, .01 and r 5 .55, p , .05, respectively) and CRTT-R-FS (r 5 .45, p , .05 and r 5

.57, p , .05, respectively) measures. All three measures (WM, PICA, and RCBA-2)

were significantly correlated with the CRTT-R-WC (r 5 .58, p , .01, r 5 .64, p ,

.005, and r 5 .51, p , .05, respectively) and CRTT-R-WF (r 5 .60, p , .01, r 5 .53,

p , .05, and r 5 .52, p , .05, respectively) conditions. These measures were also

correlated among each other, with WM significantly correlated with PICA and

RCBA-2 overall scores (r 5 .70, p , .005, and r 5 .69, p , .005, respectively) and the

PICA significantly correlated with the RCBA-2, r 5 .54, p , .05. The correlation

coefficients among these variables and each CRTT condition are summarised in

Table 4.

Analyses of variance

A series of analyses examined whether PWA group differences in WM capacity

could account for differential performance depending on the task complexity as

reflected by the subtest demands in the CRTT and CRTT-R tasks. A bimodal

distribution of WM scores (a total number of items recalled) justified the division of

the 20 PWA into low (n 5 10) and high (n 5 10) WM groups based on a median split

of their WM performance. The mean WM score from 20 PWA was 21 (out of 42)

with SD 5 7.69 and range from 6 to 36. The high WM group had a mean of 27 (SD

TABLE 3Summary of results from partial correlations

Controlled Variables

CRTT conditions

CRTT-Auditory CRTT-R-WF

None 0.60** (R25.36) 0.60** (R25.36)

PICA 0.53* (R25.28) 0.39 (R25.15)

RCBA-2 0.36 (R25.13) 0.38 (R25.14)

PICA & RCBA-2 0.39 (R25.15) 0.27 (R25.07)

Summary of the results from partial correlations between WM and the two CRTT conditions

significantly predicted by the WM task when the language severity factors such as PICA and RCBA-2

were partialled out of the correlation. *significant at p5.05, **significant at p5.01.

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5 5.8) and the low WM group had a mean of 15 (SD 5 4.0). The descriptive data for

the WM, PICA, RCBA-2, and the CRTT scores for each WM group are presented in

Table 5. Removing the middle WM group around the median was not possible due

to the relatively small sample size available for this investigation. Additionally,

removing participants with WM scores close to the median would likely increase the

significant differences reported below. Adopting an alternative splitting procedure

was therefore judged to be unlikely to add to the interpretation of the results.

A two-way mixed ANOVA, with the WM group (high vs low) as a between-

participant factor and the CRTT subtest (I through X) as a within-participant factor,

was performed for each of the four CRTT conditions. There were significant main

effects for the CRTT subtest in all of the four CRTT conditions for the CRTT-

auditory, F(9, 135) 5 10.69, MSE 5 .39, p , .001, partial eta-squared (g2) 5 .43, the

CRTT-R-FS, F(9, 135) 5 9.99, MSE 5 .35, p , .001, partial g2 5 .40, the CRTT-R-

WC, F(9, 135) 5 4.22, MSE 5 .29, p , .001, partial g2 5 .22, and the CRTT-R-WF,

F(9, 135) 5 4.11, MSE 5 .39, p , .001, partial g2 5 .22, exhibiting a common

pattern of poorer performance on the subtests with prepositional phrases (Subtest V,

VI, VII, and VIII) than the other six subtests. The results indicated that the four

subtests with prepositional phrases were significantly more difficult from the others.

There were significant main effects of the WM group only for the two CRTT

conditions hypothesised to be more WM demanding—the CRTT-auditory F(1, 15)

5 8.85, MSE 5 4.14, p , .05, partial g2 5 .39, and the CRTT-R-WF, F(1, 15) 5

5.16, MSE 5 8.03, p , .05, partial g2 5 .27—indicating that the high WM group

TABLE 4Correlation coefficients among the predictors and CRTT conditions

WM PICA_OA RCBA-2

CRTT-

Auditory

CRTT-R-

FS

CRTT-R-

WC

CRTT-R-

WF

WM 1.00

PICA_OA .70** 1.00

RCBA-2 .69** .54* 1.00

CRTT-Auditory .60** .35 .55* 1.00

CRTT-R-FS .45* .36 .57** .65** 1.00

CRTT-R-WC .58** .64** .51** .67** .65** 1.00

CRTT-R-WF .60** .53* .52* .66** .70** .88** 1.00

OA: overall scores. *significant at p5.05. **significant at p5.01.

TABLE 5Descriptive data

CRTT-Auditory CRTT-R-FS CRTT-R-WC CRTT-R-WF

Low WM group 13.22 (0.63) 12.62 (0.80) 12.67 (0.62) 12.56 (1.05)

High WM group 14.06 (0.64) 13.39 (0.71) 13.47 (0.82) 13.74 (0.77)

Group difference 0.84 0.77 0.79 1.8

Total 13.64 (0.75) 13.03 (0.83) 13.07 (0.81) 13.15 (1.08)

Descriptive data with means and standard deviations of the CRTT scores for each WM group in the

listening and reading CRTT conditions. OA5overall scores. Numbers in parenthesis are standard

deviations.

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performed better than the low WM group. There were significant interactions

between WM group and subtest only for the CRTT-auditory, F(9, 135) 5 2.70, MSE

5 .39, p , .01, partial g2 5 .16, and the CRTT-R-WF, F(9, 135) 5 3.07, MSE 5 .39,

p , .005, partial g2 5 .17, conditions. In contrast, the main effects of WM group

were not significant for the remaining two CRTT conditions that were hypothesised

to be less memory demanding, CRTT-R-FS, F(1, 15) 5 2.03, MSE 5 3.95, p . .10,

partial g2 5 .12, and the CRTT-R-WC, F(1, 15) 5 3.32, MSE 5 6.10, p . .05,

partial g2 5 .18. The two-way interactions were not significant for either the CRTT-

R-FS, F(9, 135) 5 0.41, MSE 5 .35, p , .10, partial g2 5 .03, or the CRTT-R-WC,

F(9, 135) 5 1.04, MSE 5 .29, p , .10, partial g2 5 .07, conditions.

In order to identify whether WM group differences emerged in more complex

subtests with either prepositional phrases or adverbial clauses, planned comparisons

were performed at an alpha level of .01 for the two CRTT conditions that generated

significant interactions between WM group and subtest. These analyses revealed that

there were significant differences between low and high WM groups in Subtests V,

F(1, 18) 5 15.52, p , .005, and VI, F(1, 17) 5 23.80, p , .001, of the CRTT-auditory

condition, and in subtests V, F(1, 18) 5 8.73, p , .01, VI, F(1, 18) 5 9.35, p , .01,

IX, F(1, 17) 5 14.46, p , .005, and X, F(1, 18) 5 8.66, p , .01, of the CRTT-R-WF

condition. These differences indicated that WM group differences were most evident

on more complex subtests that contained either prepositional phrases or adverbial

clauses (Figure 1 and 2) than on subtests containing simpler constructions.

DISCUSSION

The current study investigated the relationships among WM, aphasia severity, and

sentence comprehension in PWA by varying the modalities and presentation

Figure 1. Mean subtest scores on the auditory version of the CRTT for the low and high working memory

groups. The error bars represent ¡ 1 SD and * indicates a significant difference at p ( 01. Subtests V

through VIII with a prepositional phrase and Subtest IX and X with an adverbial phrase/clause in a box

are assumed to be more WM demanding than the other subtests.

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methods of the CRTT, and by assessing aphasia severity independently of these

tasks. A listening WM task significantly predicted overall performance on both the

listening CRTT and the reading version of the CRTT presented in a self-paced,

word-by-word reading format (CRTT-R-WF). Despite using different modalities,

both of these conditions limit the time course over which information is available

and were therefore hypothesised to exert greater demands on the temporal

component of WM. In contrast, the RCBA-2 (overall reading impairment) and

PICA (overall severity of aphasia) better predicted performance on the reading

versions of the CRTT presented with a full-sentence method (CRTT-R-FS) and with

a cumulative self-paced presentation method (CRTT-R-WC) than the WM measure.

The latter two conditions were hypothesised to be closer to naturalistic reading and

less memory demanding than the CRTT-R-WF or CRTT-auditory, given the

availability of the sentence stimuli throughout the task and the ability to re-read

sentences as needed. These findings are consistent with arguments that the WM

construct underlies the ability to maintain and process temporarily available

linguistic information, and that the effects of WM are clearest in the conditions in

which memory demands are higher among both unimpaired adults (Gibson, 1998;

Just & Carpenter, 1992; King & Just, 1991; Miyake et al., 1994) and PWA (Caspari

et al., 1998; Martin et al., 2008; Tompkins et al., 1994; Wright et al., 2007).

Beyond examining the simple associations between WM and the CRTT

conditions, this study also investigated how the WM group differences in sentence

comprehension emerged as a function of task and stimulus complexity for

individuals with aphasia. The levels of the subtests in the CRTT served as a

complexity manipulation based on the assumption that sentences with more

linguistically complex syntactic structures (such as prepositional phrases or adverbial

clauses) and more linguistic elements to process are more memory demanding.

Consistent with a WM account, only the low WM group showed greater difficulties

Figure 2. Mean subtest scores the CRTT-R-WF for the low and high working memory groups. The error

bars represent ¡ 1 SD and * indicates a significant difference at p ( 01. Subtests V through VIII with a

prepositional phrase and Subtest IX and X with an adverbial phrase/clause in a box are assumed to be

more WM demanding than the other subtests.

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than the high WM group in the more complex subtests such as V and VI with

prepositional phrases and/or IX and X with adverbial phrases, and only for the two

CRTT conditions that make greater demands on the temporal component of WM

(CRTT-auditory and CRTT-R-WF). Consistent with the results from the regression

analyses, WM group effects were not evident in the ANOVA analyses for the less

memory-demanding conditions such as CRTT-R-FS and CRTT-R-WC.

These results are consistent with the predictions that WM effects are most evident

when WM capacity is sufficiently taxed to be challenged or exceeded (e.g., Caplan &Waters, 1999; Just & Carpenter, 1992). The results from the CRTT-R-WF condition

presented with self-paced reading are comparable to those from the studies with

young normal adults such as King and Just (1991), who used a self-paced reading

method, and Waters and Caplan (2004), who used a self-paced auditory moving

window. Both studies found that the low WM group demonstrated lower accuracy in

sentence comprehension than the high WM group, especially for more syntactically

complex sentences.

The findings of a positive relationship between the WM measure and sentencecomprehension in aphasia require cautious interpretation, given that the WM

contribution to sentence comprehension substantially decreased when independently

derived language severity performance was removed from this relationship. The WM

task used in this study accounted for only 15% of the variance in the CRTT-auditory

and about 10% of the variance in the CRTT-R-WF condition, once the PICA and

RCBA-2 scores were partialled out of the correlations between WM and the CRTT

conditions. Furthermore, the WM task, PICA, and RCBA-2 scores loaded on the

same factor, which accounted for 76% of the variance.These findings suggest that the verbal WM measure shares substantially the same

cognitive mechanisms that are shared with the language severity measures. Based

only on the current results it is difficult to disambiguate whether the verbal WM task

used in this investigation is another language-related severity measure or if this WM

task reflects a cognitive substrate that can account for sentence comprehension

deficits beyond aphasia severity. The WM task was related to aphasia severity but it

might carry unique variance, which accounts for memory-sensitive language

performance that was not reliably identified by the overall severity measures.However, it is also difficult to disambiguate whether the WM task is a measure of

language performance with temporal demands on processing linguistic information,

or whether the sentence comprehension tasks with similar temporal constraints on

sentence processing are another measure of WM. The measure of WM used in this

study had limitations given that it required spoken recall responses for individuals

with aphasia. As Tompkins et al. (1994) pointed out, the WM task would be difficult

and inappropriate to be administered to persons with severe language and/or motor

speech disorders. Further studies with larger samples of individuals with aphasia,including other measures of verbal WM without spoken responses such as

recognition (Caspari et al., 1998) or n-back type (Wright et al., 2007) tasks, might

help to determine whether the residual variance of WM can account for other

comprehension tasks than the CRTT and other cognitive processing tasks after

partialling out language severity factors.

In sum, the results demonstrated that persons with aphasia who perform more

poorly on verbal WM tasks demonstrated differentially greater difficulties than

those with high WM performance in processing CRTT sentences with greaterlinguistic demands and selectively in conditions that limit the duration over which

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information is available for processing. These results are consistent with the notion

that WM effects are most evident when WM capacity is sufficiently taxed by the

linguistic computational demands, by the amount of information to be processed,

and/or the time over which it is available for processing (e.g., Caplan & Waters,

1999; Just & Carpenter, 1992).

Manuscript received 22 July 2008

Manuscript accepted 30 October 2008

First published online 16 March 2009

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