both concreteness and age-of-acquisition affect reading accuracy but only concreteness affects...

Both concreteness and age-of-acquisitionaffect reading accuracy but only

concreteness affects comprehension in adeep dyslexic patient

Christopher Barrya,* and Simon Gerhandb

a Department of Psychology, University of Kent at Canterbury, Canterbury, Kent CT2 7NP,

United Kingdomb School of Psychology, Cardiff University, United Kingdom

Accepted 8 October 2001

Abstract

As concreteness correlates very highly with the age-of-acquisition (AoA) of words, we

attempted to disentangle the effects of these two variables in the oral reading and compre-

hension performance of the deep dyslexic patient LW. The results of a multiple regression

analysis of LW�s reading of 217 words showed that both AoA and concreteness affect readingaccuracy, with the AoA effect being most apparent for her reading of concrete words. How-

ever, concreteness and not AoA affected LW�s performance in matching spoken definitions toprinted words, both when the distractors were semantically unrelated and when they were

related. These data are interpreted in terms of a model of reading in deep dyslexia in which

concreteness affects the ease with which semantics are accessed and can activate lexical rep-

resentations, and AoA affects the ease with which lexical phonology becomes available for

spoken word production.

� 2002 Elsevier Science (USA). All rights reserved.

1. Introduction

The oral reading of the acquired reading disorder of deep dyslexia has the followingmajor characteristics (see Coltheart, 1980a, for a review). First, when attempting to

read aloud individually presented words, deep dyslexic patients make a variety of

paralexic reading errors, chief among which are semantic errors (e.g., sun! ‘‘moon’’,

lorry ! ‘‘car’’, hair ! ‘‘comb’’, cigarette ! ‘‘fag’’1), although they also make visual

errors (e.g., chain ! ‘‘chair’’, watch ! ‘‘water’’, rate ! ‘‘rat’’), morphological errors

(e.g., dirt ! ‘‘dirty’’, drug ! ‘‘drugs’’), visual and/or semantic errors (e.g., evil !

Brain and Language 84 (2003) 84–104

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*Corresponding author. Fax: +44-1227-82703.

E-mail address: [email protected] (C. Barry).1 All examples of reading errors are from LW.

0093-934X/02/$ - see front matter � 2002 Elsevier Science (USA). All rights reserved.

PII: S0093 -934X(02)00522 -9

mail to: [email protected]

‘‘devil’’), visual-then-semantic errors (e.g., abyss ! ‘‘counting’’, presumably via aba-

cus), and functionword substitution errors (e.g., and! ‘‘the’’). Deep dyslexics are also

unable to read aloud many words (reading omissions). Second, deep dyslexics show a

powerful effect of concreteness on reading accuracy: they are able to read aloud con-

crete (or imageable) words, such as chair, house, or even chrysanthemum, more accu-

rately than abstract words, like idea and love. An effect of syntactic class on reading

accuracy (whereby nouns are read more accurately than adjectives, which are, in turn,read more accurately than verbs) has also been claimed for deep dyslexic reading.

However, this putative effect is likely to be due to confounded effects of concreteness

and frequency (Allport & Funnell, 1981; Barry & Richardson, 1988). Third, perfor-

mance on explicit tests of assembled phonological recoding, such as reading aloud

nonwords, is extremely poor, although whether the process of assembled phonological

recoding itself has been completely abolished in deep dyslexia has been questioned by

the work of Buchanan, Hildebrandt, and MacKinnon (1994, 1995) and Katz and

Lanzoni (1992, 1997).Concreteness is implicated in three aspects of deep dyslexic reading performance.

The first, and certainly the most apparent, concerns reading accuracy. Comparisons of

words read correctly with those omitted reveal that deep dyslexics show a substantial

effect of concreteness. For example, Barry andRichardson (1988) conducted amultiple

regression analysis on the words the deep dyslexic patient GR read correctly compared

to those he omitted (from his reading attempts to 643 words fromBrown&Ure, 1969).

They found that concreteness, associative difficulty, and frequency had independent

significant effects, with concreteness accounting for the largest proportion of the var-iance. The second effect of concreteness in deep dyslexic reading concerns the strong

tendency for thewords towhich the patients produce semantic errors to be less concrete

than those they are able to read aloud correctly. This has been observed by a number of

authors (Barry & Richardson, 1988; Gerhand & Barry, 2000; Newton & Barry, 1997;

Nolan & Caramazza, 1982; Shallice & Warrington, 1975), and we suspect that it may

also be true for many of the patients for whom the contrast has not been reported. The

third effect of concreteness concerns visual errors (e.g., stool! ‘‘school’’). There exist

strong tendencies for these to be made to more abstract words and to involve theproduction of words that are more concrete than the stimulus (Barry & Richardson,

1988; Coltheart, 1980b; Nolan & Caramazza, 1982; Shallice & Warrington, 1975).

Morton and Patterson (1980) interpret this concreteness effect in visual errors as re-

flecting a ‘‘second attempt’’ for a recognized word to negotiate a successful pathway

through the entire oral reading process.

1.1. The relationship between concreteness and other variables

It is clear that accounts of deep dyslexic reading must explain the effects of

concreteness. However, before considering such accounts, it is necessary to be

confident that concreteness is indeed the ‘‘correct’’ variable. Stimulus word con-

creteness, or the extent to which a word�s referent ‘‘can be experienced by the senses’’(Paivio, Yuille, & Madigan, 1968), correlates highly with a number of other psy-

cholinguistic characteristics of words, particularly imageability (the ‘‘capacity to

arouse mental images of things or events,’’ Paivio et al., 1968), associative difficulty

(how readily it is possible to think of a large number of other related words or ideas,Brown & Ure, 1969), and ease-of-predication (how easy it is to think of factual

statements, or predicates, describing a word, Jones, 1985). Concreteness and im-

ageability correlate very highly; the correlation coefficients between the two variables

are .83 for the ratings of 925 words provided by Paivio et al. (1968) and .78 for the

ratings of 1944 words provided by Gilhooly and Logie (1980). The correlation be-

C. Barry, S. Gerhand / Brain and Language 84 (2003) 84–104 85

tween concreteness and associative difficulty is ).28 for the ratings of 650 wordsprovided by Brown and Ure (1969), and the correlation between imageability and

ease-of-predication is .88 in the ratings of 125 words provided by Jones (1985). Given

such correlations, it has been natural that there has been debate as to which variable

has the major effect on the reading performance of deep dyslexic patients.

It is useful to separate what might be called empirical from theoretical accounts of

the effects of intercorrelated variables. If a particular variable captures a greaterproportion of the variance than a correlated variable, then it provides a better

‘‘empirical’’ account of performance (i.e., it gives a more complete or accurate de-

scription). However, in our view, it is more productive theoretically to concentrate

on the nature of the explanatory mechanisms proposed to account for the effects of

each variable in question (and, indeed, this should motivate attempts to discover the

most appropriate description of performance). Thus, if two intercorrelated variables

are both assumed to operate in similar ways (i.e., they are both assumed to be indices

of a common underlying process), then knowing which provides the better empiricalaccount of performance cannot, in itself, necessarily help illuminate the precise na-

ture of the process assumed to determine that performance. However, if two inter-

correlated variables are assumed to be indices of qualitatively different underlying

processes, then it is very important to evaluate which permits a better ‘‘theoretical’’

or explanatory account of performance (i.e., which provides the more coherent

support for hypotheses concerning the mechanisms generating the performance).

Theoretical accounts of concreteness (e.g., Newton & Barry, 1997; Plaut &

Shallice, 1993) have invoked similar explanatory mechanisms to those advanced forthe effects of ease-of-predication (Jones, 1985) and, by extension, may also be applied

to any account constructed of the effects of associative difficulty. Such accounts

contain the common feature that the variable has its locus at the process of lexi-

calization, that is, it affects how semantic representations are used to activate lexical

representations for spoken word production. Therefore, these variables may be as-

sumed to affect (or to be measures of) similar underlying mechanisms. However,

qualitatively different theoretical accounts have been proposed for the effects of

concreteness and imageability. Whereas concreteness has been generally interpretedas a feature of lexical organization (e.g., Richardson, 1975, 1980), imageability has

been interpreted as an index of the process of creating and maintaining mental

images (Paivio, 1991; Richardson, 1980). Concreteness and imageability ratings of

words correlate very highly; concrete words are also imageable, whereas abstract

words are less imageable, if their referents can be imaged at all. However, there are

good grounds for believing that the process of imagery is not involved in deep

dyslexic reading accuracy (Barry & Richardson, 1988; Coltheart, 1980c); for ex-

ample, many semantic errors are more plausibly regarded as being conceptually orassociatively based rather than as reflecting paraphasic misnamings of generated

pictorial images. Therefore, we believe that concreteness rather than imageability

provides a better theoretical account of the cognitive processes that determine

reading performance in deep dyslexia.

Concreteness also correlates very highly with a word�s rated age-of-acquisition

(henceforth, AoA). There is a correlation of ).503 between concreteness and AoAratings of the 1944 words in the norms provided by Gilhooly and Logie (1980) (and a

correlation of ).713 between imageability and AoA); words acquired earlier in life(with lower AoA ratings) tend to be more concrete (and imageable) than those ac-

quired later in life. Quite different explanations have been advanced for the effects of

concreteness and AoA. Explanations of the concreteness effect in reading accuracy in

deep dyslexia have focused on assumed problems with either accessing semantic

representations of abstract words (e.g., Plaut & Shallice, 1993) or with the process of

86 C. Barry, S. Gerhand / Brain and Language 84 (2003) 84–104

lexicalization for abstract words (Newton & Barry, 1997). In contrast, explanations

of AoA effects in word and picture naming in normal participants have been in-

terpreted in terms of the ease with which phonological representations of words

become available for spoken production (Brown and Watson, 1988; Gerhand &

Barry, 1998). To date, little systematic work has been reported that contrasts the

effects of concreteness and AoA in deep dyslexia (but see Gerhand & Barry, 2000).

The purpose of the present paper is to investigate the effects of these two variables inthe deep dyslexic patient LW�s reading accuracy and her performance in a com-prehension task. As different theoretical accounts have been offered for the effects of

concreteness and AoA, it is very important to determine which of the two inter-

correlated variables is the effective one in deep dyslexic reading (or, indeed, whether

both have an effect). Furthermore, the study of AoA in deep dyslexia will also

provide important information concerning the locus at which AoA operates. Before

specifying these issues further, we shall provide a brief review of the effects of AoA in

reading and naming.

1.2. AoA effects in lexical processing tasks

Traditionally, word frequency has been considered to be the most important

variable in many lexical processing tasks (see Monsell, 1991, for a review). However,

many of the effects formally ascribed to frequency may be due to its relationship with

the age at which words are first learned. AoA has been shown to be a predictor of

naming accuracy in some aphasic patients. Rochford and Williams (1962) found thatthe age at which an item was named correctly by 80% of children aged 2–11 years old

predicted the proportion of aphasic patients who could name that item. Feyereisen,

Van der Borght, and Seron (1988) found that AoA (as well as frequency) predicted

picture naming accuracy in a group of 18 aphasic patients, and Hirsh and Ellis (1994)

and Hirsh and Funnell (1995) have reported patients for whom AoA was the main

predictor of picture naming accuracy.

Clear effects of AoA have been demonstrated in picture and word naming speed in

normal speakers and readers. AoA effects in picture naming latencies have beenfound both for rated estimates of AoA (e.g., Carroll & White, 1973) and for ob-

jective measures of when children can name pictures (Morrison, Chappell, & Ellis,

1997). Some studies have found no effect of the frequency of the objects� names onpicture naming latency once the effect of the AoA of the names has been taken into

account (Carroll & White, 1973), whereas others have reported significant inde-

pendent effects of both AoA and frequency; Lachman (1973) and Lachman, Shaffer,

and Hennrikus (1974) found an independent effect of subjective ratings of word

frequency. Oldfield and Wingfield (1965) reported a linear relationship between logfrequency and picture naming latency, however, when Morrison, Ellis, and Quinlan

(1992) reanalyzed their data including AoA ratings of the objects� names, they foundan effect of AoA but no effect of frequency. Furthermore, in their own study of

picture naming latencies, Morrison et al. (1992) found that only AoA and the

number of phonemes in the item�s name had significant effects on naming time; theword frequency of the item�s name had no independent effect. Barry, Morrison, andEllis (1997) reported a study of the naming latencies to 195 items from the Snodgrass

and Vanderwart (1980) picture set. They found that the determinants of naminglatency were the frequency of the name, the AoA of the name, name agreement, and

the rated image agreement of the picture. They also found a significant effect of the

multiplicative term of AoA�frequency, which shows that there is an interactionbetween AoA and frequency, such that the frequency effect was found mainly for

items with later-acquired names. In semi-factorial studies, Barry, Hirsh, Johnston,


and Williams (2001) found that participants were faster to name pictures with ear-

lier-acquired names than those with later-acquired names when these were matched

for word frequency, but that there was no effect of the frequency of picture names

when these were matched for AoA. Similar effects have been reported by Bonin,

Fayol, and Chalard (2001) for both oral and written naming latencies.

The vast majority of the very many studies that have reported an effect of fre-

quency in picture naming have failed to control for AoA (e.g., Humphreys, Riddoch,& Quinlan, 1988; Jescheniak & Levelt, 1994; Oldfield & Wingfield, 1965), whereas

every study that has included AoA in the analysis has found it to have a significant

effect. However, studies that have included AoA in their analysis have varied in their

results concerning a frequency effect: some have found no effect (e.g., Barry et al.,

2001; Bonin et al., 2001; Morrison et al., 1992), some have found an additional effect

of frequency (e.g., Lachman, 1973), and Barry et al. (1997) found that frequency

only affected the naming of pictures with late-acquired names. Nevertheless, the

point we wish to reinforce here is that all studies of AoA in picture naming latencieshave found it to have an effect.

Effects of AoA have also been reported for word naming latencies (e.g., Brown &

Watson, 1987; Coltheart, Laxon, & Keating, 1988; Gilhooly & Logie, 1981). There

have been very many studies reporting effects of word frequency on word naming

(e.g., Forster & Chambers, 1973; Frederiksen & Kroll, 1976; McRae, Jared, & Se-

idenberg, 1990; Monsell, Doyle, & Haggard, 1989), but these have typically not

controlled for AoA and so the possibility exists that apparent frequency effects may

actually be due to the confounding effect of AoA. Morrison and Ellis (1995) found aclear effect of AoA on the time to read words that were matched carefully for fre-

quency, but no effect whatsoever of frequency for reading words matched for AoA.

The studies that have found effects of AoA on naming time have either analyzed

their data using multiple regression techniques (Brown & Watson, 1987; Gilhooly &

Logie, 1981) or have used a partial factorial design in which AoA and frequency

were not manipulated orthogonally (Coltheart et al., 1988; Morrison & Ellis, 1995).

Gerhand and Barry (1998) investigated the joint effects of AoA and word frequency

using a fully factorial design in which both variables were manipulated orthogonally(and in which other variables, such as concreteness, length, and orthographic factors,

were matched). They found that both AoA and frequency had independent, and

noninteracting, effects upon naming time: early acquired words were read aloud

faster than later-acquired words, and high-frequency words were read aloud faster

than low-frequency words. Furthermore, Gerhand and Barry also found reliable

effects of both AoA and frequency for the stimuli used by Morrison and Ellis in two

replications of their study. These results show that there are effects of both AoA and

word frequency in oral reading times to words, which suggests that theories of wordnaming must account for the effects of both variables.

1.3. Is AoA or concreteness the critical variable in deep dyslexic reading?

Much of the impetus for the recent work on the effects of AoA in picture and

word naming has been to contrast its effects with those claimed for word frequency.

Indeed, the motivation of many studies was to examine the possibility that previ-

ously reported effects of word frequency in lexical tasks might actually result fromconfounded effects of AoA (Morrison et al., 1992; Morrison & Ellis, 1995). AoA

ratings correlate moderately with word frequency counts. We have calculated that

the correlation between the AoA ratings of 1903 words in the Gilhooly and Logie

(1980) norms and the Kucera and Francis (1967) frequency counts of those words is

).271 (and the correlation between AoA and log(1 + frequency) is ).445); words that


are learned earlier in life tend to be those that occur frequently in the language,

whereas later-acquired words tend to be less common. However, the correlation

between AoA and frequency is markedly less than the correlation between AoA and

concreteness ().503). Given this, the possibility exists that the concreteness effectspreviously reported in deep dyslexic reading may actually be due to a confounded

effect of AoA. Alternatively, it is possible that both concreteness and AoA may have

independent effects on deep dyslexic reading.The aim of the present study is to attempt to disentangle the effects of con-

creteness and AoA in the deep dyslexic patient LW. In a previous study of this

patient, Newton and Barry (1997) reported that she showed no reliable difference

between her comprehension of concrete and abstract high-frequency words (as tested

in tasks of synonym matching and spoken definition to printed word matching). This

suggested that, in this patient at least, the concreteness effect on oral reading accu-

racy was not due to any major semantic impairment of common abstract words.

Newton and Barry argued that concreteness affects the lexicalization process (wheresemantic representations activate words in the speech production system). The

present study will test the hypothesis that concreteness affects lexicalization whereas

AoA affects the accessibility of lexical phonological representations.

We shall report multivariate studies of LW�s word naming accuracy (with re-peated presentations of each word) and comprehension performance (under two

conditions) to examine for effects of both AoA and concreteness, and to determine

whether there is any interaction between them. The study of the relative importance

of the effects of concreteness and AoA in deep dyslexia will provide important in-formation for theories of the mechanisms of deep dyslexic reading and compre-

hension. In addition, the study of AoA in deep dyslexia will provide important

additional information concerning the locus or loci at which the variable operates.

Ellis and Lambon Ralph (2000) have recently shown that connectionist models can

simulate age (or rather order) of acquisition effects. They trained distributed net-

works using back-propagation with interleaved presentation whereby after first en-

tered patterns had been learned, later patterns were added but the early patterns also

continued to be presented. Ellis and Lambon Ralph argued that such cumulativepresentation reflects normal vocabulary acquisition, as the occurrence of early items

does not cease when later ones are encountered. Ellis and Lambon Ralph�s simu-lations always showed effects of both AoA and frequency, although the AoA effects

tended to be larger in magnitude. They argued that AoA effects are a natural and

probably inescapable property of these networks. On this account, AoA effects

should be found in all lexical tasks, and not just those that require or involve spoken

word production. If their account is correct, then we would expect to see AoA effects

on both reading accuracy and word comprehension in deep dyslexia.

2. Case history

LW�s case history and her reading performance have been reported by bothNewton and Barry (1997) and Gerhand and Barry (2000). To summarize briefly, LW

is a 52-year-old, right-handed woman who worked as a clerical officer. Twenty-two

years before the start of this study, she had surgery to clip a left hemisphere aneu-rysm at the junction of the internal carotid and middle cerebral arteries. She remains

severely aphasic: her spontaneous speech is limited to eight utterances (and she

frequently repeats ‘‘lovely, lovely’’ and ‘‘thank-you, thank-you’’), although her

comprehension within informal social interaction appears to be preserved. LW is

unambiguously deep dyslexic. She is unable to read aloud nonwords but she is able


to orally repeat spoken nonwords. In reading aloud, LW makes many semantic

errors (e.g., fireplace! ‘‘hearth’’, occupation ! ‘‘job’’), and also makes visual errors

(e.g., waste ! ‘‘water’’), visual-then-semantic errors (e.g., gallery ! ‘‘ships’’, pre-

sumably via galley) and morphological errors (e.g., dirt ! ‘‘dirty’’), many of which

are ‘‘pluralizations’’ (e.g., horse ! ‘‘horses’’). LW is able to read aloud concrete

words more accurately than abstract words (e.g., she read 19/40 concrete and 4/40

abstract words matched for frequency and length). In a test of lexical decision toprinted words, LW showed no difference in accuracy for concrete and abstract

words, when summed over frequency (85 vs 80%), but she was significantly more

accurate for high- than for low-frequency words, when summed over concreteness

(92.5 vs 72.5%). LW�s advantage for high-frequency words was no greater for con-crete than for abstract words. Newton and Barry also report a series of tests of LW�scomprehension of concrete and abstract words, including a synonym judgment task

on printed words, and a spoken definition to printed word matching task. LW

showed no significant impairment of her comprehension of abstract high-frequencywords in these tasks, despite being unable to read most of the words aloud; she was,

however, impaired in her comprehension of low-frequency abstract words.

3. AoA vs concreteness in reading aloud

Due to the high correlation between AoA and concreteness, it is difficult to in-

vestigate the effects of the two variables using factorial designs in which both aremanipulated orthogonally (while controlling for other pertinent factors). Therefore,

we decided to perform a multiple regression analysis of LW�s reading of 217 wordswhich were presented for oral reading on three separate testing occasions.

The 217 words were selected fromGilhooly and Logie�s (1980) norms and are listedin the Appendix A (along with some characteristics of the words). The words were

selected so as to sample over a wide range of AoA and concreteness ratings (from

Gilhooly & Logie, 1980) and word frequency (from Kucera & Francis, 1967) and to

ensure that the intercorrelations between the variables were not markedly differentfrom those for the entire Gilhooly and Logie corpus (which have been cited earlier).

The words were presented in blocks of about 110 words in weekly testing sessions

lasting 30–45 minutes. (Thus, repeated presentation of the words were separated by

at least two weeks.) Prior to each testing session, she was asked to read 10 highly

concrete words (as a ‘‘warm-up’’ to encourage her in what she finds the difficult task

of reading aloud.) Words were classified as �correct� if she produced the target wordeither immediately (which she did on the majority of occasions) or after some other

reading attempt (e.g., ship! ‘‘boat, sea, ship’’). All errors, including semantic errorsand omissions (when no response was offered within 20 s) were classified as �incor-rect.� Table 1 presents the mean characteristics of the stimulus words as a function ofher reading accuracy.

As can be seen from Table 1, the words that LW consistently read aloud correctly

(3/3) were more frequent, more concrete, earlier-acquired and shorter than those she

was unable to read on any occasion (0/3). As these variables tend to be intercorre-

lated, a multiple regression analysis was performed. This analysis contained, for each

word, LW�s reading accuracy (the number correct out of three reading attempts) asthe dependent variable and the following five independent variables: (1) the Kucera

and Francis (1967) frequency of the word, transformed to log (1 + frequency); (2) the

concreteness rating of the word (from Gilhooly & Logie, 1980); (3) the AoA rating of

the word (from Gilhooly & Logie, 1980); (4) the number of letters in the word; (5) the

multiplicative term of AoA�concreteness. All independent variables were first


converted to standard scores, which is particularly important when considering ef-

fects of any multiplicative term (Aiken & West, 1991). If the multiplicative term of

AoA�concreteness were to have a significant effect over and above any separateeffects of concreteness and AoA, then this would be evidence for the existence of an

interaction between the two variables.

Table 2 shows the results of the multiple regression analysis. The overall equationfor the regression was significant [R ¼ :688; F ð5; 211Þ ¼ 38:01; p < :0001] and thevariables that had a significant effect were frequency, concreteness, AoA, and the

multiplicative term of AoA�concreteness; there was no major effect of word length.The interaction resulted from the fact that there was a clear effect of AoA on LW�sreading of concrete words, but not for her reading of abstract words. This interac-

tion was explored, using ‘‘simple slope analyses’’ (Aiken & West, 1991, pp. 9–27), in

order to examine the significance of the AoA effect for concrete and abstract words

separately. To examine the effect of AoA for concrete words, the multiple regressionanalysis was repeated substituting concreteness minus 1 SD for concreteness, and

AoA�(concreteness ) 1 SD) for the multiplicative term. The effect of AoA was

significant (b ¼ �:771; t ¼ 7:52; p < :0001). When the regression was repeated

containing concreteness plus 1 SD and AoA�(concreteness + 1 SD), in order to

examine the effect of AoA for abstract words, the effect of AoA was not significant

(b ¼ :03; t ¼ 0:27). These analyses show that there is a significant effect of AoA onLW�s reading of concrete words, but not for her reading of abstract words (where sheshowed almost a floor effect).

4. AoA vs concreteness in word comprehension

Our examination of LW�s oral word reading demonstrated that both concretenessand AoA affected her reading accuracy. It is possible that the reason why LW was

unable to read some of the words presented was that she could not understand them.

Many accounts of deep dyslexia assume that oral reading is semantically mediated

Table 2

Results of the multiple regression analysis on LW�s word reading accuracy (number correct out of threetesting presentations)

Variable b coefficient SE t value p (2-tailed)

Log (1 + frequency) .128 .061 2.10 .037

Concreteness .424 .088 4.84 .0001

AoA ).370 .086 4.29 .0001

No. of letters ).116 .063 1.85 .066

AoA� concreteness ).400 .064 6.26 .0001

Note. (All independent variable were included in the regression as standard scores.)

Table 1

The characteristics of the stimulus words as a function of LW�s oral reading accuracy over three pre-sentations of each word

Number correct

(over 3 tests)

(%) Mean

frequency

Mean

concreteness

Mean

AoA

Mean

length

0 68.8 61.7 4.65 4.03 6.3

1 9.7 47.8 5.68 2.69 5.5

2 11.5 65.0 5.86 2.50 4.8

3 12.0 132.8 6.00 2.43 4.4


(but see Buchanan, Hildebrandt, & MacKinnon, 1999). In their investigation of

LW�s comprehension of words, Newton and Barry (1997) used a task in which aspoken definition was presented along with two printed words, where LW had to

point to the word to which the definition referred. LW was 87% correct for both

highly concrete and moderately concrete words, and showed no effect of frequency

for these items. For highly abstract words, she was 81% correct for high-frequency

words but at chance for low-frequency words. Thus, LW�s comprehension appearedto be impaired markedly only for abstract low-frequency words.

In the following tests, we assessed LW�s comprehension in a spoken definition toword matching task with the same 217 words we presented to her for oral reading.

The aim was to determine whether AoA or concreteness (or both) affected LW�scomprehension under two conditions, one in which the foils were unrelated to the

target and one with semantically related foils. Morrison et al. (1992) found that, for

normal speakers, AoA affected picture naming times but had no effect on time to

make man-made vs living-thing categorizations for the same sample of pictures. Thissuggested that AoA does not affect the recognition or comprehension of pictures,

and that the AoA effect in naming is post-semantic.

Two versions of the comprehension test were administered, each on two separate

testing occasions. In each version, LW was given a spoken definition of a word taken

from the Collins English Dictionary (Collins, 1994), for example, ‘‘a collection of

articles gathered together in one place’’ (for heap), and was required to point to one

of four words (printed as a vertical list on a sheet of paper) to which she thought the

definition referred. The spoken definitions were repeated to LW up to a maximum ofthree times and the position of the target word in the list of four words was random.

In the unrelated version, the four words were selected randomly from the 217

words, each of which was tested by a definition once only for each trial (e.g., heap,

sink, boot, and drug). In the related version, each target word was presented with

three related distractors chosen to be as similar in meaning to the target word as

possible but without being either alternative matches to the definition or words

mentioned in the definitions (e.g., heap, crop, supply, and mass). Other examples

from the related condition include ‘‘a shoe that extends above the ankle’’ (boot, sock,sandal, and foot) and ‘‘a thin fog caused by condensation in the air’’ (mist, smoke,

rain, and breeze).

Table 3 shows the characteristics of the words as a function of LW�s performancein the spoken definition to printed word matching task under the two conditions. In

the unrelated condition, LW performed rather well and was correct on 73% of all

trials. Her performance was worse in the related condition, where she was correct on

54% of all trials, but was above chance (as guessing would result in only 25% cor-

Table 3

The characteristics of words as a function of LW�s performance in the spoken definition to printed wordmatching task, with both Unrelated distractors and semantically Related distractors

Number correct

(over 2 tests)

(%) Mean

frequency

Mean

concreteness

Mean

AoA

Mean

length

Unrelated distractors

0 16.1 72.3 4.44 3.84 5.9

1 21.2 59.0 4.47 3.96 6.4

2 62.7 71.9 5.41 3.30 5.6

Related distractors

0 30.0 61.3 4.55 4.04 6.5

1 32.7 70.9 5.04 3.49 5.7

2 37.3 74.1 5.47 3.16 5.4


rect). In both the unrelated and related conditions, the items on which LW per-

formed correctly on both occasions were more concrete than those on which she

selected the incorrect word, but there were only smaller differences in the AoA and

length of the words and no substantial differences in the frequency of the words.

Separate multiple regression analyses were performed on LW�s accuracy (numbercorrect out of 2) in the unrelated and related conditions. These analyses contained five

independent variables (all of which were first converted to standard scores): log (1 +frequency), concreteness, AoA, word length, and AoA�concreteness. Table 4 showsthe results of these analyses. When tested with unrelated distractors, the overall

equation for the multiple regression was significant [R ¼ :422; F ð5; 211Þ ¼9:14; p < :001], but the only variable that had a significant effect was concreteness.When tested with semantically related distractors, the overall equation for themultiple

regression was also significant [R ¼ :372; F ð5; 211Þ ¼ 6:79; p < :001], and again theonly variable that had a significant effect was concreteness. In both the unrelated and

related conditions, the main effects of frequency, AoA and word length were not sig-nificant, and there was no significant AoA�concreteness interaction.LW�s generally good performance in the unrelated condition confirms the studies

of Newton and Barry (1997) who also showed that LW was substantially better on

comprehension tests than in the task of reading words aloud. However, LW�s per-formance was worse when the foils were semantically related. Furthermore, the

present data are in disagreement with Newton and Barry�s general conclusion withregard to the effect of concreteness on comprehension: Newton and Barry found no

effect of concreteness for high-frequency words, whereas the present study found asignificant effect of concreteness in both the unrelated and related conditions. In

order to investigate whether the concreteness effect observed in the present study was

limited to, or was more pronounced for, low-frequency words, additional multiple

regressions were performed that included the multiplicative term of concrete-

ness�frequency. If this additional term were to have a significant effect, it would

suggest that the concreteness effect on LW�s comprehension performance variedaccording to word frequency. The multiplicative term was not significant for the

unrelated condition (b ¼ :087; t ¼ 1:61; p ¼ :11), which suggests that, as regardsher performance in this condition, LW showed an effect of concreteness for both

high- and low-frequency words. The multiplicative term was significant for the re-

lated condition (b ¼ �:142; t ¼ 2:41; p < :05), which reflected the fact that theconcreteness effect was larger for low-frequency words than for high-frequency

Table 4

Results of the multiple regression analysis on LW�s performance in each condition of the comprehensiontask

Variable b coefficient SE t value p (2-tailed)

Unrelated distractors

Log (1+ frequency) .071 .053 1.34 .18

Concreteness .424 .077 5.53 .0001

AoA .100 .076 1.32 .19

No. of letters .041 .055 0.75 .46


Related distractors

Log (1+ frequency) .041 .059 0.70 .49

Concreteness .233 .085 2.74 .007

AoA ).079 .084 0.95 .35

No. of letters ).034 .061 0.56 .58



words, but subsequent simple slopes analyses showed that the concreteness effect was

significant both for high-frequency words (b ¼ :462; t ¼ 3:64; p < :001) and low-frequency words (b ¼ :178; t ¼ 2:05; p < :05).It is, of course, entirely possible that LW�s failure on any trial of the spoken

definition to printed word matching task could be due to a number of different

reasons: she might not have been able to access fully the semantics corresponding to

the target word, or she might not have understood completely the definition (and itmust be stressed that some of the definitions were indeed rather difficult and argu-

ably opaque, e.g., ‘‘a band or margin around the edge of something’’ for border). It is

also possible that the particular relationships between the four printed words on the

page—and/or with the definition (e.g., ‘‘to show or make visible’’ for display for

which the related foils were hide, parade and flourish)—contributed to making the

task difficult, and so might have underestimated LW�s single-word comprehensionability. However, the main point we wish to make here is that AoA had no effect on

LW�s performance in either the unrelated or the harder related conditions of ourcomprehension task.

As the same 217 words were administered to LW for oral reading and compre-

hension under two conditions, it is possible to examine the relationship between her

reading and comprehension accuracy. Table 5 shows that LW�s comprehensionperformance was better for words she was more able to read aloud, although the

contingency between her performance on the these tasks is confounded by the fact

that concreteness affects both tasks. However, we wish to point out that LW�s per-formance on the comprehension tasks is above chance and that she is substantiallybetter at understanding the words than she is at reading them aloud.

5. General discussion

We have shown that both concreteness and AoA affect word reading accuracy in

the deep dyslexic patient LW. LW read concrete words more successfully than ab-

stract words, and was more accurate reading aloud early-acquired than late-acquiredconcrete words. However, she was unable to read aloud most abstract words, irre-

spective of their AoA. When matching a spoken definition to one of four printed

words, she was more accurate for concrete than for abstract words, but showed no

effect of AoA. This was true both when the foils were semantically unrelated and

when they were closely related (where her performance deteriorated), which shows

that the absence of any effect of AoA could not have been due to a lack of sensitivity

of the comprehension task to detect an effect. These results suggest that previously

reported effects of concreteness in deep dyslexic reading cannot be due entirely to thelikely confound with AoA, although there is an additional effect of AoA on reading

Table 5

The relationship between LW�s reading and comprehension accuracy

Reading

Number correct (over 3 tests) % correct in comprehension tests

Unrelated distractors Related distractors

0 65.3 43.1

1 85.7 69.1

2 88.0 72.0

3 94.3 82.7


accuracy (but not comprehension) that exists over and above the effect of con-

creteness.

Many accounts of deep dyslexia presuppose that word reading is semantically

mediated (but see Buchanan et al., 1999). The processes that underpin oral reading in

deep dyslexia are often assumed to reflect the following sequence: After graphemic

analysis of the stimulus, a word�s input orthographic representation is activated; arecognized word will then activate its corresponding semantic representation; finally,semantic information then activates the word�s output phonological representation,in the lexicalization process. Two major theories of lexicalization may be distin-

guished. In one, semantic information is used to directly activate representations of

the phonological forms of words (e.g., Morton, 1985), stored in a phonological

output lexicon. Once an entry in this lexicon has been activated, the phonology of

the word is then encoded for production in speech. Alternatively, in two-stage

models (e.g., Jescheniak & Levelt, 1994; Levelt, 1989; Levelt, Roelofs, & Meyer,

1999), lexicalization is assumed to reflect two major steps: first, conceptual, semanticand syntactic information is used to select a lemma, which is an abstract represen-

tation of a word; and second, the activated lemma will activate a lexeme, which is the

phonological representation of the word (which, once activated, is encoded for ar-

ticulation). Although the distinction between lemmas and lexemes has been ques-

tioned by Caramazza (1997), it is possible to phrase the account we shall offer of the

data reported here within either framework.

5.1. Concreteness

Many theories of the concreteness effect in deep dyslexia propose that it is located

entirely within the semantic system. This may be seen in three varieties of accounts of

deep dyslexia that presuppose some form of semantic ‘‘deficit’’ for abstract words.

First, Coltheart (1980b), in his right hemisphere hypothesis, claimed that abstract

words ‘‘are dealt with much better by the left hemisphere than by the right’’ (p. 347),

which is an implicit acknowledgement of a deficit for abstract words in the right

hemisphere system proposed to underlie word reading in deep dyslexia. Second,within their modular model, Morton and Patterson (1980) claim quite explicitly that

the ‘‘semantics for some words (particularly abstract ones) are probably impaired’’

(p. 114). Third, in Plaut and Shallice�s (1993) connectionist model, abstract words areactually implemented as having substantially fewer semantic features than concrete

words; indeed, in one of Plaut and Shallice�s simulations, concrete words were as-cribed a mean of 18.2 features and abstract words a mean of only 4.7.

In contrast to these views, Caramazza and Hillis (1990) proposed that deep

dyslexic reading arises from damage to the phonological output lexicon (which issimilar to Morton and Patterson�s account of semantic errors in terms of the outputlogogens for some words having heightened thresholds). Similarly, Buchanan et al.

(1999) have proposed that deep dyslexia results when the phonological output

lexicon is compromised by an impaired selection mechanism. Newton and Barry

(1997) argued that such accounts are unappealing as there are no convincing rea-

sons to suppose that the speech production system should be structured according

to concreteness or any semantic variable. (Buchanan et al.�s more recent account,however, has suggested that semantic neighborhood size, as determined by thenumber of different associates produced to words—which is likely to be correlated

with concreteness—is a variable that affects the number of activated candidates in

the phonological output lexicon.) Newton and Barry proposed that concreteness

affects the lexicalization process whereby phonological word forms are activated by

semantic representations. They argued that the concreteness effect in deep dyslexic


oral reading cannot be at the level of accessing orthographic lexical representations,

as they found no reliable concreteness effect in LW�s performance in the lexicaldecision task with printed words, and is not due solely to a semantic deficit for

abstract words, as they found no systematic concreteness effect in LW�s perfor-mance in various tests of comprehension, at least not for high-frequency words.

Newton and Barry advanced their NICE (‘‘normal isolated centrally expressed’’)

model of semantically mediated reading in deep dyslexia, in which concreteness wasproposed to be an important dimension of normal lexicalization. They suggested

that deep dyslexia reflects the ability of qualitatively normal semantic representa-

tions to activate entries in a phonological output lexicon (subject to a pathologi-

cally increased aphasic ‘‘threshold’’ for any lexicalization to be achieved), when this

system is isolated from other reading routes. The claim that LW�s impairment is inthe lexicalization process is similar to Morton and Patterson�s (1980) proposal thatdeep dyslexic reading results from a problem of transmission from semantic

codes to lexical phonology; indeed, Morton and Patterson suggest that it is ‘‘onlyfor some words that the semantic code uniquely identifies one output logogen’’

(p. 114).

On the basis of the results from the spoken definition to word matching tasks

presented in the present paper, where LW showed a significant effect of concreteness

(and for both high- and low-frequency words), we have chosen to position the

concreteness effect in deep dyslexic reading accuracy at both the semantic level and

the lexicalization process. It would appear that there are some abstract words that

LW is unable to read aloud because she cannot fully activate their complete semanticrepresentations. However, it appears also to be the case that there are other words,

including many abstract words, that LW can understand reasonably well (i.e., at

least to the level required by the fairly difficult task in the related condition), but is

unable to read aloud. We have been impressed by the fact that LW�s performance inour comprehension tasks was substantially better than her oral reading accuracy. We

accept that there are intrinsic difficulties in making direct comparisons between

performance levels in any forced-choice comprehension task and oral reading. The

chance rate is obviously 25% in the four-alternative forced-choice tasks we used, butthe baseline ‘‘chance’’ rate for reading aloud accurately is substantially lower (and

may be close to 0%). LW�s performance in our tests of comprehension was alwaysabove chance and, as we have noted earlier, the definition to word matching task we

used may actually underestimate her ability to access and process semantic infor-

mation of words because incorrect selections may result from problems with un-

derstanding aspects of the spoken definition (in addition to any difficulties in

accessing the meaning of the printed words).

We propose that the major effect of concreteness in deep dyslexic reading accuracyis to be attributed to the lexicalization process. Newton and Barry�s NICE modelproposes that the semantic representations of very concrete words have a high degree

of specificity in the lexicalization process and so are able to efficiently and uniquely

access entries in the speech production system (which have generally increased

thresholds for any spoken word production in aphasic deep dyslexic patients).

However, the semantic representations of very abstract concepts have little specificity

in the lexicalization process and will produce a more diffuse activation of many

loosely related entries in the speech production system, each with a weaker degree ofactivation than for those activated by concrete concepts. For such items, deep

dyslexic patients will be unable to activate any phonological entry sufficiently to

produce as a word reading response. The semantic representations of moderately

concrete words will activate a number of related entries in the speech production

system, and infortuitous selection from these will result in semantic errors. This


account is therefore able to explain why deep dyslexics tend to make semantic errors

to words with concreteness values intermediate between those words that are read

correctly and those that are omitted (Barry & Richardson, 1988; Nolan & Caram-

azza, 1982; Shallice & Warrington, 1975).

5.2. Age-of-acquisition

There was a clear and reliable AoA effect on LW�s oral reading accuracy, but noeffect of AoA on her comprehension performance with the same printed words. This

pattern of results poses some problems for the generality of Ellis and Lambon

Ralph�s (2000) account of AoA effects in terms of their being a ubiquitous feature ofconnectionist models trained with cumulative and interleaved presentation. The fact

that an AoA effect was found when spoken word production is required (as in the

case of oral reading), but not when lexical phonology is not involved (as is pre-

sumably the case when matching printed words to spoken definitions), suggests thatAoA has its major locus at the speech production system. One theory of the

mechanism by which AoA has its effect is the ‘‘phonological completeness’’ hy-

pothesis advanced by Brown and Watson (1987) to account for AoA effects in oral

reading latencies in normal readers. Brown and Watson proposed that early-learned

words have ‘‘more complete’’ representations in the speech production system than

later-acquired words. They suggested that the ‘‘phonological output representations

are stored in a relatively complete form during the early stages of vocabulary ac-

quisition’’ (p. 214) and that, for later-acquired words, ‘‘only minimal information isstored explicitly’’ (p. 215). Early-acquired words therefore have the advantage of

more rapid and efficient phonological assembly than later-acquired words when

required to be produced as a naming response. If we assume that a variable that

affects naming latencies in normals will also affect naming accuracy in deep dyslexics

(and in aphasic patients in general)—and by the operation of the same underlying

mechanism—then we suggest that the AoA effect in LW arises because the phono-

logical forms of late-acquired words are harder to retrieve and produce than those of

early-acquired words.Although the phonological completeness hypothesis has not been elaborated in

specific detail concerning the nature of lexical phonological representations, the

notion that greater phonological assembly is required for late-acquired words is

supported by the finding that normal speakers are able to articulate early-acquired

words faster than late-acquired words (Gerhand & Barry, 1998; Roodenrys, Hulme,

Alban, Ellis, & Brown, 1994). However, the phonological completeness hypothesis is

not in accord with Levelt et al.�s (1999) model of speech production; indeed, Leveltet al. claim that ‘‘word forms are retrieved from the mental lexicon not as unanalyzedwholes but rather as sublexical and subsyllabic units, which are to be positioned in

structures (such as word and syllable skeletons) that are independently available’’ (p.

19, our emphasis). As Levelt et al. claim that the stored phonological representation

of every word must to be segmented (and then recombined with their stored frame)

each time it is produced, words that are more assumed to be ‘‘complete’’ (and so

harder to segment) should not enjoy any processing advantage; on the contrary, they

would be harder (or take longer) to produce. As it is not clear at present precisely

how phonological forms of words are represented and processed in speech pro-duction, we cannot resolve the discrepancy between these hypotheses. However, the

pattern of results we have observed with the deep dyslexic patient LW strongly

suggests that AoA has its major locus at the stage of the retrieval of lexical pho-

nology (contrary to the expectation from Ellis and Lambon Ralph�s connectionistaccount), and general models of speech production will need to accommodate this


result. It appears that the stored lexical phonological representations that support

spoken word production are easier to retrieve for early-acquired words than for late-

acquired words.

5.3. Frequency

LW showed a small but significant effect of word frequency in addition to those ofconcreteness and AoA in her word reading accuracy. However, she showed no effect

of frequency in her accuracy in the definition to word matching tasks. A number of

authors have proposed that word frequency affects the process of visual word rec-

ognition in reading tasks (e.g., McClelland & Rumelhart, 1981), and frequency will

affect all connections between distributed representations within connectionist

models of reading. Borowsky and Besner (1993) proposed a multistage activation

model of visual word recognition, in which frequency ‘‘affects pathways that map

representations in the orthographic input lexicon onto their corresponding repre-sentations in the semantic system and the phonological output lexicon rather than

directly affecting either of these subsystems themselves’’ (p. 834). It is possible to

interpret our finding that LW showed a frequency effect in reading accuracy but not

in word comprehension within Borowsky and Besner�s model by assuming thatfrequency affects connections to speech production rather than connections to se-

mantics. However, we have noted that correct performance in the comprehension

test we have used requires the appreciation of the meaning of combinations of words

(in understanding the dictionary definitions), and so we would wish to examinepossible effects of word frequency more exhaustively in tests of LW�s single wordrecognition, comprehension and spoken production before being able to localize the

frequency effect in deep dyslexic reading with greater confidence.

6. Conclusion

The deep dyslexic patient LW showed a clear effect of concreteness on both wordreading and word comprehension accuracy. We have argued that concreteness has

some effect on LW�s ability to activate semantic representations but has a more sub-stantial effect within her lexicalization process, such that semantics activate lexical

phonology more successfully for concrete than for abstract items. LW also showed

clear effects of AoA in her word reading accuracy but not in her accuracy in the word

comprehension tasks with either unrelated and related foils. We have interpreted the

AoA effect in LW�s oral reading accuracy by appeal to the proposal that AoA has itsmajor effect at the stage of spoken word production (contrary to Ellis & LambonRalph�s (2000) claim that AoA effects are a ubiquitous feature of connectionist modelstrained by back-propagation with cumulative and interleaved training), and that the

phonological forms of late-acquired words are harder to retrieve and produce than

those of early-acquired words. In terms of the two-stage model of lexicalization (e.g.,

Levelt et al., 1999), we would say that concreteness affects the process of lemma se-

lection, whereas AoA affects the ability to retrieve and execute lexemes.

Appendix A

Table 6 presents the 217 words used. For each word, we give its concreteness andAoA ratings (from Gilhooly & Logie, 1980), its word length (in terms of number of

letters), and its frequency (from Kucera & Francis, 1967). READ¼ the number of


Table 6

Concreteness AoA No. letters Frequency READ UNREL REL

abyss 4.50 5.97 5 4 0 2 1

acre 4.62 4.11 4 9 0 2 2

addition 3.39 3.14 8 142 0 2 0

adjournment 3.11 6.06 11 4 0 0 0

alkali 4.37 6.33 6 4 0 2 1

amateur 3.88 5.22 7 25 0 2 0

ankle 6.08 2.64 5 8 1 2 1

apple 6.20 2.11 5 9 3 2 2

approach 3.23 4.44 8 123 0 0 0

area 3.84 3.92 4 323 0 2 2

arrangement 3.08 4.89 11 34 0 0 1

aunt 5.64 2.33 4 22 0 2 2

babe 5.62 3.03 4 8 0 0 0

ball 6.15 1.50 4 110 3 2 2

base 4.41 3.69 4 91 0 1 1

bath 6.00 1.72 4 26 3 2 2

bay 5.80 3.36 3 57 0 0 1

beast 5.64 3.19 5 7 1 2 1

bed 6.35 1.69 3 127 3 2 2

bill 5.28 4.06 4 143 0 2 1

blood 6.13 2.53 5 121 1 2 2

bloom 5.20 4.03 5 12 0 2 1

bolt 5.56 3.69 4 10 0 1 1

boot 5.95 2.51 4 13 0 2 0

border 4.44 4.17 6 20 0 0 0

bowl 5.75 2.56 4 23 1 2 0

box 5.97 1.92 3 70 2 2 2

breakfast 5.76 2.33 9 53 1 1 2

breath 4.79 3.31 6 53 0 1 2

brim 5.09 3.94 4 4 0 2 2

brother 5.85 2.19 7 73 1 2 1

cage 5.93 3.00 4 9 0 0 1

cake 6.24 2.14 4 13 3 2 2

car 6.22 1.97 3 274 3 2 1

cause 2.87 4.08 5 130 0 0 0

cellar 5.72 3.61 6 26 2 2 2

character 3.65 4.64 9 118 0 0 1

cheek 5.65 2.67 5 20 0 0 1

chicken 6.14 2.50 7 37 0 2 2

claim 3.31 4.17 5 98 0 1 0

clearance 3.28 5.47 9 4 0 1 0

cliff 5.91 3.22 5 11 0 2 2

coach 5.61 3.14 5 24 0 2 2

coal 5.84 2.78 4 32 2 2 2

coffee 6.13 2.92 6 78 3 2 1

cologne 5.76 4.94 6 9 0 2 2

combination 3.26 4.75 11 57 0 2 0

communication 3.99 5.03 13 67 0 2 0

company 4.24 4.36 7 290 0 2 1

condition 3.03 4.61 9 91 0 0 1

consummation 3.18 6.58 11 4 0 1 0

copper 5.47 4.28 6 13 0 0 1

costume 5.44 3.92 7 10 0 2 2

deer 6.31 2.81 4 13 3 2 2

delta 4.94 5.54 5 7 0 2 1

deposit 4.17 4.83 7 9 0 2 2

display 4.62 4.00 7 41 0 1 0

ditch 5.55 2.92 5 10 0 2 1

door 6.06 2.14 4 312 0 2 0


Table 6 (continued)


dress 5.95 2.22 5 67 3 2 2

drink 5.49 2.11 5 82 1 2 2

drug 5.55 4.64 4 24 0 1 2

earth 5.80 3.17 5 150 0 2 1

elbow 6.07 2.37 5 10 2 2 2

entrance 4.84 3.72 8 57 0 1 1

establishment 3.91 5.26 13 52 0 1 1

excuse 3.16 3.56 6 27 0 1 2

fee 4.41 4.44 3 16 0 2 0

fencing 5.25 4.97 7 4 0 2 0

flag 6.06 2.58 4 16 1 2 2

fork 5.92 2.25 4 14 2 2 1

fountain 5.93 3.89 8 18 0 0 0

fox 6.05 2.83 3 13 3 2 2

gallery 5.69 4.42 7 31 0 2 0

grandfather 5.65 2.14 11 12 0 2 0

gun 6.12 2.28 3 118 3 2 2

hall 5.65 2.83 4 152 2 2 2

head 6.03 1.81 4 424 2 2 0

heap 4.85 3.19 4 14 0 0 0

highway 5.75 4.36 7 40 0 2 0

hold 4.16 2.67 4 169 0 0 1

honey 6.11 2.86 5 25 1 2 2

hotel 5.91 3.08 5 126 0 2 2

impetus 2.78 6.44 7 6 0 1 0

improvement 3.26 4.42 11 40 0 2 1

incident 3.40 4.58 8 49 0 2 1

influence 2.80 5.42 9 132 0 1 2

insect 5.93 2.83 6 14 0 0 0

institution 4.42 5.53 11 41 0 2 0

intention 2.85 4.81 9 36 0 1 0

interior 4.34 4.81 8 74 0 2 0

island 5.96 2.89 6 167 0 2 1

jolt 4.24 4.31 4 4 0 1 0

juice 5.99 2.50 5 11 0 2 0

junior 3.84 3.56 6 75 0 1 2

kitten 6.12 2.19 6 5 3 2 2

knee 5.93 2.31 4 35 0 2 1

knitting 5.83 2.86 8 1 2 2 2

lady 5.64 2.31 4 80 2 1 2

lane 5.37 2.61 4 30 2 2 0

lap 5.40 2.63 3 19 0 1 0

lion 6.27 2.44 4 17 3 2 1

magazine 5.88 3.53 8 39 0 1 1

marble 6.11 2.94 6 21 0 1 1

men 5.86 2.36 3 763 3 2 2

method 3.03 4.81 6 142 0 1 2

mist 4.97 3.67 4 14 0 1 0

mistress 5.30 5.17 8 5 0 2 0

mortal 4.06 5.08 6 10 0 2 1

mother 5.79 1.44 6 216 2 2 1

mouse 6.24 2.42 5 10 0 2 1

nail 5.98 2.72 4 6 2 0 1

nerve 4.88 4.80 5 12 0 2 0

oak 5.88 3.11 3 15 0 2 2

occupation 3.81 4.89 10 24 0 2 0

oil 5.81 3.03 3 93 2 2 2

opening 4.55 3.36 7 83 0 1 0

order 3.44 3.44 5 376 0 1 2


Table 6 (continued)


oven 5.93 2.36 4 7 2 2 2

pact 3.72 5.31 4 5 0 0 0

paper 5.99 2.29 5 157 3 2 1

park 5.79 2.19 4 94 1 2 2

part 3.39 3.14 4 500 0 0 1

pasture 5.62 3.86 8 14 0 2 1

peasant 5.50 4.19 7 7 0 1 2

pencil 6.17 2.25 6 34 2 2 2

penny 6.06 1.86 6 25 0 2 2

people 5.40 2.81 6 847 3 2 2

pepper 5.91 2.69 6 13 3 1 2

physician 5.73 5.61 9 14 0 2 2

picture 5.79 2.19 7 162 2 1 1

pit 5.93 3.14 3 14 0 0 1

pool 5.73 2.39 4 111 0 2 1

porch 5.96 3.19 5 43 1 2 2

position 3.51 3.75 8 241 0 2 0

prairie 5.75 4.33 7 21 0 2 2

priest 5.61 4.11 6 16 2 1 2

professional 3.79 4.94 12 105 0 2 0

property 4.60 4.47 8 156 0 1 0

pump 5.56 3.44 4 11 0 2 1

purpose 2.80 4.28 7 149 0 0 1

quantity 3.40 4.19 8 33 0 2 1

radio 6.15 3.17 5 120 3 2 2

range 4.17 4.36 5 160 0 0 0

rate 3.08 4.56 4 209 0 0 0

rattle 5.49 2.61 6 5 1 2 1

refuse 4.26 3.94 6 16 0 2 1

remedy 3.68 4.92 6 13 0 2 0

report 4.17 3.86 6 174 0 2 1

result 3.18 4.06 6 244 0 2 1

resumption 2.62 6.03 10 9 0 1 0

ridge 5.47 4.33 5 18 0 0 1

ring 5.93 2.08 4 47 3 2 2

route 4.40 4.47 5 43 0 0 0

rubber 5.96 2.89 6 15 2 2 1

rust 5.53 3.80 4 10 0 1 0

salary 4.56 5.58 6 43 0 2 0

sauce 5.76 2.58 5 20 0 2 0

saw 5.32 2.69 4 352 3 2 2

scheme 3.28 4.75 6 33 0 1 0

segment 4.85 4.28 7 10 0 1 0

self 4.59 3.28 4 40 0 0 1

servant 5.15 4.06 7 19 0 2 2

shed 6.11 2.31 4 11 0 0 1

shepherd 5.98 2.75 8 3 0 2 2

ship 6.15 2.49 4 83 3 2 2

shirt 6.16 2.69 5 27 1 1 2

sink 5.90 2.19 4 23 2 1 1

situation 3.11 4.57 9 196 0 0 0

snake 6.21 2.89 5 44 3 2 1

soap 5.98 2.22 4 22 2 2 2

soldier 5.78 2.75 7 39 1 2 1

solution 3.88 5.06 8 59 0 0 2

sound 5.02 3.00 5 204 1 2 0

spare 3.13 3.64 5 23 0 1 1

speech 4.53 3.69 6 61 0 2 2

spot 5.12 2.61 4 57 1 1 2


times LW read each word correctly (over three testing presentations); UNREL¼ thenumber of LW�s correct responses with unrelated distractors in the definition toword matching task (over two testing presentations); REL¼ the number of LW�scorrect responses with related distractors (over two testing presentations).

References

Aiken, L. A., &West, S. G. (1991).Multiple regression: Testing and interpreting interactions. London: Sage.

Allport, D. A., & Funnell, E. (1981). Components of the mental lexicon. Philosophical Transactions of the

Royal Society (London) B, 295, 397–410.

Barry, C., Hirsh, K. W., Johnston, R. A., & Williams, C. L. (2001). Age of acquisition, word frequency

and the locus of repetition priming of picture naming. Journal of Memory and Language, 44, 350–375.

Table 6 (continued)


stain 5.35 3.11 5 6 0 2 0

standard 3.24 4.72 8 110 0 0 2

statement 3.79 4.81 9 141 0 1 1

steak 6.46 3.29 5 10 0 2 2

steeple 5.61 3.61 7 9 0 2 1

stool 5.92 2.03 5 8 2 2 1

stove 5.91 2.97 5 15 1 2 2

submarine 5.83 3.81 9 27 0 2 2

sun 6.17 1.81 3 112 3 2 0

sunlight 5.15 2.89 8 17 0 0 2

sunshine 5.27 2.06 8 8 1 1 2

surface 4.47 3.78 7 200 0 1 0

suspect 3.79 4.72 7 30 0 1 0

swallow 5.47 3.08 7 10 1 0 0

swell 4.11 4.28 5 7 0 1 1

tap 5.38 2.22 3 18 3 0 0

tape 5.64 4.06 4 35 0 2 0

task 4.09 3.92 4 60 0 2 2

tax 4.45 4.69 3 197 0 2 2

teacher 5.69 2.47 7 80 1 2 1

thief 5.19 3.22 5 8 3 2 2

thinker 4.03 4.08 7 6 0 1 0

tobacco 6.09 3.66 7 19 3 2 2

ton 4.73 3.86 3 13 1 2 1

topic 3.66 4.83 5 9 0 2 1

toy 5.67 1.64 3 4 2 2 2

trim 3.88 3.67 4 20 0 2 0

trout 6.17 3.94 5 4 2 2 2

typewriter 6.11 3.89 10 10 0 2 2

uncle 5.80 1.92 5 57 2 2 0

usual 2.35 3.53 5 96 0 0 1

vegetable 6.02 2.69 9 10 0 2 2

veto 3.26 6.36 4 10 0 1 2

village 5.76 3.17 7 72 0 2 2

voice 4.85 2.75 5 226 0 1 1

whip 5.70 3.97 4 19 0 2 1

window 6.09 2.31 6 119 2 2 1

wine 6.21 4.03 4 72 0 2 1

witness 4.59 4.72 7 28 0 0 1

wound 5.61 3.72 5 28 0 2 0

Note. Concreteness AoA No. letters Frequency

Mean: 5.05 3.53 5.82 69.2

SD: 1.06 1.12 2.11 107.8


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both concreteness and age-of-acquisition affect reading accuracy but only concreteness affects...

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