Working Memory and Dyslexia

Roderick I. Nicolson*, Angela J. Fawcett*and Alan D. Baddeley†

*Department of Psychology †MRC Applied Psychology Unit

University of Sheffield Cambridge

Abstract

Recent research has demonstrated that dyslexic children suffer impairments in

both phonological skills and in working memory performance. In principle

either a phonological deficit or a working memory deficit could underlie both

sets of symptoms. This issue was addressed via a series of experiments

designed to explore the relationships between dyslexia, age, phonological

performance and working memory. Two groups of dyslexic children

participated, with mean ages 15 and 11 years respectively, together with three

groups of non-dyslexic children (mean ages 15, 11 and 8 years) matched for IQ

with the dyslexic children and selected so as to provide both chronological and

reading age controls for the two dyslexic groups. The performance of the older

dyslexics across the range of tasks was slightly but not significantly worse than

their chronological age controls and indistinguishable from that of their reading

age controls. By contrast, the performance of the younger dyslexics was

significantly worse than that of their chronological age controls on phonological

discrimination, articulation rate, and nonword repetition, and was significantly

worse even that of their reading age controls on repetition of longer nonwords.

On tests of memory span, all five groups showed the normal phonological

similarity effect and the normal word length effect. When memory span was

regressed as a function of articulation rate, there was no evidence of impaired

slope or intercept for the dyslexic children. It is concluded that the 11 year old

dyslexic children show residual problems on phonological processing,

especially for tasks involving unfamiliar stimuli, but that by their mid-teens

dyslexic children have overcome these problems. The major remaining problem

for the dyslexic children appears to be a continuing lack of fluency in

articulation, a factor which is sufficient to account for the slight deficits on

memory span. Furthermore, it is argued that the articulation rate deficit

provides a parsimonious explanation of the range of deficits shown by the

younger dyslexic children. It is concluded that neither impaired phonological

skills nor impaired working memory is sufficient in itself to explain the deficits,

but that some deeper explanation must be sought.

Acknowledgements

The research reported in this chapter was supported by a grant from the Leverhulme Trust to the

first author. We acknowledge gratefully the support of the participants in this study, and of the

staff and pupils at Ecclesall Junior School and High Storrs and Silverdale Secondary schools,

Sheffield.

1 . Introduction

Developmental dyslexia is conventionally defined as “a disorder in children who, despite

conventional classroom experience, fail to attain the language skills of reading, writing and

spelling commensurate with their intellectual abilities” (World Federation of Neurology, 1968). A

typical estimate of the prevalence of dyslexia in the British school population is 5% (Miles &

Haslum, 1986), with roughly four times as many boys as girls being diagnosed. It has been

assumed that the problems of dyslexic children derive from impairment of some skill or cognitive

component largely specific to the reading process, and the consensus view (eg. Stanovich, 1988)

is still that the deficits are attributable to some disorder of phonological processing. It is also well-

established, however, that dyslexic children have pervasive problems in working memory (Jorm,

1983), and it is logically possible that these problems underlie the phonological deficits rather than

vice versa. Furthermore, recent research (Nicolson & Fawcett, 1990) has demonstrated that there

are also pervasive problems in motor skill. Given the established link between articulation rate and

memory span (Baddeley, Thomson & Buchanan, 1975), there is an intriguing possibility that the

cognitive deficits in children are attributable to a deficit in working memory which is itself

attributable to motor deficit in articulation speed. The research reported here investigates this

hypothesis by means of a series of investigations of working memory. First, however, we

summarise the evidence linking phonological deficit and working memory deficit with dyslexia.

There is considerable evidence that dyslexic children suffer from deficits in phonological skill

(Vellutino, 1979), and indeed some form of ‘phonological deficit hypothesis’ (eg. Miles & Miles,

1990; Stanovich, 1988) is arguably the consensus belief of most dyslexia researchers. Particularly

striking were longitudinal studies (eg. Bradley & Bryant, 1983; Lundberg & Høien, 1989) which

demonstrated that those children who showed deficits at the age of 3 or 4 years in phonemic

segmentation or simple rhyming tasks were likely to develop reading problems subsequently.

Furthermore, Bradley (1988) and Olson, Wise and Rack (1989) have demonstrated that

prophylactic phonological support for the ‘at risk’ younger children led to normal subsequent

acquisition of reading.

However, dyslexic children often show equally severe problems in immediate memory — for

instance, Miles (1983) has shown that a deficit on digit span is one of the most common

symptoms of dyslexia, with particular deficits often shown on backwards span. In a

comprehensive review of working memory, Jorm (1983), having noted that much of the evidence

was confusing owing to problems of definition of dyslexia and inadequate experimental control,

concluded that “… there is fairly consistent evidence that [specific] reading retardation1 can be

associated with a deficit in the long-term storage of phonological information. This deficit may

affect retarded readers’ ability to utilize the articulatory loop, a short-term store which appears to

play an important role in certain aspects of normal reading acquisition.” (1983, p311). In other

words, Jorm attributed the working memory deficits of dyslexic children to the established

phonological deficits. Further evidence of impaired phonological working memory was provided

by Snowling and her colleagues, who discovered that dyslexic children show a deficit compared

even with reading age controls on nonword repetition, that is, accurately repeating a spoken

nonsense word (Snowling, 1981, Snowling,Goulandris, Bowlby & Howell, 1986).

A systematic investigation of the relationship between working memory and phonological skill

was reported in Gathercole and Baddeley (1990) in which they investigated several of the skills

potentially underlying phonemic segmentation. The participants in the study were five ‘language

disordered’ children with ages in the range from 7:2 to 8:10, with symptoms largely consistent

with a diagnosis of dyslexia. Their performance was compared with two sets of individually

selected control children, with one set matched for nonverbal performance, and another set of

younger children matched for verbal performance. The distinction corresponds fairly closely to

the chronological age match and reading match groups advocated by Backman, Mamen and

Ferguson (1984).

Gathercole and Baddeley assessed five separate competences: phonological discrimination (the

ability to detect whether two stimuli, differing in at most one phoneme, were different);

1 Jorm was using ‘specific reading retardation’ as a more precisely defined synonym of dyslexia (see Rutter and

Yule, 1975). We prefer to use the word dyslexia to avoid premature commitment as to the underlying cause.

articulation rate (the time taken to repeat a word 10 times), a test of vocal sequencing and control;

and voice onset latency (the time taken to start saying a given word), a test of vocal response

initiation time. In addition to these straightforward performance tests, three theoretically motivated

tests were performed. The first was a non-word repetition (NWR) test which measured the ability

to repeat accurately a nonsense word spoken by the experimenter. Performance typically declines

as the nonsense words get longer, and thus it is taken to be a valuable early test of working

memory performance. The NWR test is thought to be a useful indicator of a child’s ability to

acquire new vocabulary, since any word will appear to be a nonword the first time it is heard by

the child. The two remaining experiments tested memory span for words, an analogue of the digit

span test on which dyslexic children have well-documented problems. Two experiments were

performed, in one the acoustic confusability of the words was manipulated, and in the other the

length of words was manipulated.

Gathercole and Baddeley established that: all three groups were equivalent on the phonological

discrimination and on voice onset latency tasks; the language disordered group were equivalent to

the verbal controls but non-significantly worse than the nonverbal controls on articulation rate;

and, most notably, that they were significantly worse even than the verbal controls on NWR and

on memory span. Furthermore, all three groups showed the same qualitative effects of acoustic

confusability and word length on memory span. Consequently Gathercole and Baddeley

concluded that the language disordered children were showing a specific deficit in the capacity of

the phonological store component of the working memory system (Baddeley, 1986), whereas their

articulatory rehearsal processes appeared to be normal. The authors went on to speculate that this

deficit might underlie problems in acquiring reading skills and vocabulary knowledge.

Interestingly, taking the stronger form of the above argument, it is logically possible that this

working memory deficit might be the factor underlying all the established phonological deficits of

dyslexic children. Consider first the early problems of phonemic segmentation and rhyming

awareness that have often been associated with reading impairment. To segment a word into

phonemes requires that one holds it in temporary store while attempting to analyse it — a

significant working memory load. If one cannot hold an unfamiliar word long enough to repeat it,

how could one hope to segment it? Telling whether two words rhyme is arguably an even more

demanding task for working memory, in that two words must be stored concurrently and

analysed. It is also important to note that Gathercole and Baddeley’s results were eliminative

rather than prescriptive. They demonstrated that the working memory deficit was probably not

attributable to a qualitative difference in utilizing the phonological loop, but it is possible that the

deficit might lie either in reduced phonological storage capacity or in some working memory

component other than the phonological store.

2 . The Experimental Programme

It is unsatisfactory from a theoretical viewpoint to have two alternative factors underlying the

problems of dyslexia, and the experiments reported here were designed to explore the issue as

directly as possible.

Overall Design of the Study

It is clearly valuable to identify whether dyslexic children perform significantly worse than their

age-matched controls, but one of the key discriminants between theories is a test of performance of

dyslexic children against reading age controls, since a significant impairment compared with

reading age controls is indicative of developmental disorder rather than just a developmental lag

(cf. Bryant & Goswami, 1986). Since the specific nature of dyslexic children’s deficits may also

change with age, it is important to examine the effects of age separately. These considerations

suggest an experiment with at least six groups of subjects: two groups of dyslexic children of

different mean ages; two groups of non-dyslexic children matched to the dyslexic children on

chronological age; and two groups of non-dyslexic children matched to the dyslexic children on

reading age.

Three separate issues are of interest in the statistical analyses for each experiment. First, whether

there are any between-group differences at all. This involves a design which treats all the six

groups within one factor, irrespective of age and presence/absence of dyslexia. We refer to this as

the ‘Overall Analysis’. A lack of a significant effect here would suggest that the variable under

investigation was unaffected by either age or dyslexia. Second, it is important to identify whether

dyslexic children perform worse than their age-matched controls. This design has the two level

factor age and the two level factor presence/absence of dyslexia. We refer to this as ‘CA &

Dyslexia’. A main effect of age would indicate a developmental trend in the variable in question,

while a main effect of dyslexia would suggest a reliable difference between dyslexic and control

subjects of equivalent age. Such a difference may, however, be attributable either to a

fundamental difference, or to a developmental lag. Deciding between these requires a third

analysis, one involving a comparison with reading age controls; this also has two factors, namely

a two level factor reading age, and a two level factor presence/absence of dyslexia. We refer to

this as ‘RA & Dyslexia’. A negative effect of dyslexia on this analysis would indicate that

dyslexic subjects are performing more poorly than younger children of equivalent reading age, and

would argue against a developmental lag interpretation.

Note that the latter two analyses are based on only four of the experimental groups. Fortunately,

as described in the next section we were able to select two groups of dyslexic children who were

sufficiently similar in IQ to allow a single control group to be used both as RA control for the older

dyslexics and CA control for the younger dyslexics, thus leading to a total of only five groups.

2 . 2 . The subject panel

Five groups of subjects participated. The groups were; 12 dyslexic children around 15 years old;

11 dyslexic children around 11 years old; a group of 12 non-dyslexic children matched to the older

dyslexics for age and full IQ; a group of 11 non-dyslexic children of similar IQ to the two dyslexic

groups, matched for chronological age with the younger dyslexics and for reading age with the

older dyslexics; and a fifth group of 10 non-dyslexic children around 8 years old matched for

reading age and full IQ with the younger dyslexics. All the dyslexic children had been diagnosed

as dyslexic between the ages of 7 and 10, based on discrepancies of at least 18 months between

chronological and reading age. Their IQ levels fell in the normal to superior range on the Wechsler

Intelligence Scale for Children (Wechsler, 1976) and they had no known neurological deficit or

primary emotional difficulty. For several dyslexic children IQ and/or reading age deficit had

changed since diagnosis, and a criterion of at least one year deficit in reading age compared with

chronological age at the time of the experiment was adopted (this led to the exclusion of 5 children

from a larger original pool). The dyslexic children were recruited via the local British Dyslexia

Association and the Dyslexia Institute2, and the non-dyslexic controls were recruited from local

schools. Summary data for chronological age, reading age and IQ are presented in Table 1, and

full individual data are presented in Appendix 1.

**Insert table 1 here**

3 . The Experiments

Our experiments were a straightforward replication of the Gathercole and Baddeley experiments,

with the further addition that we included a more detailed investigation of the children’s

articulatory rate for words of different length. The experiments were all re-implemented within an

automatic computerised hypermedia format, in order to facilitate subsequent replication. Explicit

comparison of experimental results using both hypermedia and traditional presentation confirmed

that comparable results should be obtained, with the hypermedia implementation adding greater

experimental control, consistency and recording accuracy (see Nicolson, note 1 for a detailed

discussion of the issues involved). We will report the procedure and results briefly for each

experiment in turn before providing an overall discussion

3 . 1 . Experiment 1. Phonological Discrimination.

The experimental design was based directly on stimuli constructed by Bishop (1985) comprising

36 pairs of single syllable words and 36 pairs of single syllable nonwords. One third of the pairs

in each set were identical, one third differed by one fricative/affricative feature (eg. fuse vs views),

and the remaining third differed in a nasal/plosive feature (eg. cub vs cup). The results for the five

groups are shown in figure 1. The error markers represent the standard error for that

group/condition. It is clear that all subjects found the fricative decisions the most difficult,

especially in the nonword condition, and that performance was close to ceiling on the nasal/plosive

difference conditions.

2 We are grateful to Dr. Harry Chasty and to Mrs Jean Walker of the Dyslexia Institute for allowing us to approach

the parents of the children involved and for permitting access (with parental consent) to the original diagnostic data.

**Insert Figure 1 here**

Overall Analysis. An analysis of variance was undertaken with group (5 levels) and difference

condition (6 levels) as the two factors. Significant main effects were found for group and

difference condition [F(4,52)=3.3, p<.05; F(5,260)=68.8, p<.0001 respectively]. The interaction

between group and difference condition was also significant [F(20,260)=2.1, p<.01]. Tukey

pairwise comparisons indicated that the younger dyslexics performed significantly worse overall

than the oldest controls (p<.05). Analysis of the simple effects of group in the individual

conditions revealed that the younger dyslexics performed significantly worse than the oldest

controls on the ‘Fricative Difference’ condition for Words, and the ‘Same’ condition for

Nonwords [F(4,52)=3.83 p<.01; F(4,52)=2.57, p<.05 respectively]. No other difference was

significant.

Comparisons with CA Controls. A second analysis of variance was then undertaken limited to the

four older groups, taking age and presence/absence of dyslexia as two factors and difference

condition as the third. The main effect of dyslexia was significant at the .05 level [F(1,43)=5.1,

p<.05], whereas the effect of age did not reach significance [F(1,43)=3.0, NS]. There was a

significant interaction between age and dyslexia, and a significant interaction between dyslexia and

condition [F(1,43)=4.9, p<.05; F(5,215)=3.6, p<.01 respectively]. Difference condition again

had a highly significant main effect, and no other effects were significant.

Comparisons with RA Controls. A third analysis of variance was conducted, omitting the oldest

controls and comparing the two dyslexic groups with their reading age controls. The main effect

of dyslexia was not significant, whereas that of reading age was significant [F(1,41)=1.7, NS;

F(1,41)=8.1, p<.01 respectively]. Difference condition again had a highly significant main effect,

and no other effects were significant.

These results suggest that dyslexic children are discriminating at the same level as reading age

controls, as would be predicted by a developmental lag hypothesis.

3 . 2 . Experiment 2. Voice Onset Latency

In this test the subject was primed with a common word, and told to say that word as soon as

possible on seeing the light flash on a computer screen. The initial energy in saying the word

triggered the computer via a microphone, leading to the automatic recording of the latency between

the flash and the voice onset. A range of words were used of varying lengths and complexities.

The one syllable words were: tap, cat, pig, lamb, bed and egg and the three syllable words were:

pineapple, elephant, ladybird, catapult, banana and telephone. The results are shown in Figure 2.

The data presented are the mean times (averaged over five repetitions excluding outliers of more

than 1.0 second latency).

**Insert Figure 2 here**

Overall Analyses. A 5 group analysis of variance indicated that there was no difference in latency

between short and long words for any group, [F(1,53)=1.9, NS] but that there were significant

differences between groups [F(4,53)=6.1, p<.001]. Tukey hsd post-hoc analyses indicated that

the group effect was attributable to slower performance by the younger dyslexics and the youngest

controls than the oldest controls (p<.01) and the older dyslexics (p<.05).

Comparisons with CA controls. A second analysis of variance of the four older groups by age

and presence/absence of dyslexia revealed that the overall effect of age was significant whereas

that of dyslexia was not [F(1,44)=13.1, p=<.001; F(1,44)=2.7, NS respectively]. No other

effect approached significance.

Comparisons with RA controls. A third analysis of variance by reading age and presence/absence

of dyslexia, excluding the oldest controls, revealed that the overall effect of reading age was

significant whereas that of dyslexia was not [F(1,41)=8.9, p=<.01; F(1,41)=1.4, NS

respectively]. No other effect approached significance.

The results suggest therefore that voice onset latency is a simple function of age, and shows no

reliable effect of dyslexia.

3 . 3 . Experiment 2a. Articulation Rate

Articulation rate was measured by asking the subjects to say a given word five times speaking as

rapidly as possible. The speech was recorded onto the computer and the duration of the five

repetitions was measured to the nearest centisecond from the digitised signal. The same words

were used as for the voice onset latency tests. The mean articulation times per word are shown in

figure 3.

**Insert Figure 3 here**

Overall analyses. As one would expect, articulation rate was significantly slower for the longer

words [F(1,53)=591.7, p<.0001]. There was also a significant group effect [F(4,53)=4.0,

p<.01]. Tukey hsd analysis indicated that the group effect was attributable to a significant

difference (p<.01) between the oldest controls and the younger dyslexics.

Comparisons with CA controls. When the four older groups were split into the age factor and the

presence/absence of dyslexia factor, dyslexia had a significant main effect [F(1,44)=10.0, p<.01]

whereas the main effect of age was not significant [F (1,44)=4.0, p>.05]. The effect of syllables

was of course highly significant.

Comparisons with RA controls. A third analysis of variance by reading age and presence/absence

of dyslexia, excluding the oldest controls, revealed that neither the main effect of reading age nor

that of dyslexia was significant [F(1,41)=2.5, NS; F(1,41)=2.0, NS respectively]. The effect of

syllables was highly significant and no other effect approached significance.

This pattern of results suggests that dyslexic subjects do articulate more slowly, but that this could

be most easily interpreted as reflecting a developmental lag rather than as a developmental

disorder.

3 . 4 . Experiment 3. Nonword Repetition

The set of 40 nonwords constructed by Gathercole and Baddeley (1990) was used. The stimuli

were recorded as digitised speech, and re-recorded until a panel of adult subjects made no errors

when repeating them, in order to ensure that the test was one of memory rather than

discrimination3. Nonwords varied both in terms of number of syllables (2, 3, 4 or 5) and

complexity (presence of absence of consonant clusters). Each nonword was presented in turn by

the computer program, and the subject’s task was to repeat it correctly. Each response was scored

either as correct or error, and if an error was made the experimenter recorded the response.

**Insert Figure 4 here**

The data, pooled across consonant complexity for visual clarity, are shown in figure 4. Full

means and standard deviations are presented in Appendix 2. It may be seen that the younger

dyslexics performed worse than the other groups for longer stimuli.

Overall Analyses. A five group analysis of variance was undertaken with three factors: group,

number of syllables and consonant complexity. All three factors had significant main effects

[F(4,53)=14.3, p<.0001; F(3,159)=6.5 p<.001; F(1,53)=4.1, p<.05 for group, syllables and

complexity respectively]. The interaction between group and syllables was also significant, as

was that between complexity and syllables [F(12,159)=2.5, p<.01; F(3,159)=2.7, p<.05

respectively]. A Tukey hsd analysis of the group effect showed a number of significant

differences: the younger dyslexics recalled significantly less than all other groups except the

youngest controls (p<.01); the youngest controls recalled significantly less than the oldest controls

(p<.01) and the older dyslexics (p<.05); and the 11 year old controls recalled significantly less

than the oldest controls (p<.05). Analysis of the simple effects in the interaction between group

and syllables indicated that the younger dyslexics were the only group for whom syllables had a

significant effect (p<.05). Pairwise comparisons of the terms in the interaction between syllables

and complexity indicated that performance was significantly worse for the complex 5 syllable

stimuli than for the simple or complex stimuli with 2 3, or 4 syllables, except for complex stimuli

of 3 syllables.

Since the effect of increasing the number of syllables was of theoretical interest, a further 5 group

analysis of variance was undertaken excluding the data for the shortest (2 syllable) stimuli. The

3 We were unable to reach this perfect criterion with the word ‘brasterer’, for which we had to be satisfied with a

10% error rate.

results were, of course, very similar to the full analysis, with the additional finding that the

younger dyslexics performed significantly worse even than the youngest controls (p<.05).

Comparison with CA controls. The analysis of the four older groups in terms of age and

presence/absence of dyslexia indicated that both age and dyslexia had significant main effects

[F(1,43)=39.1, p<.0001; F(1,43)=9.7, p<.01 respectively], whereas the interaction between age

and dyslexia was not significant [F(1,43)=3.7, p>.05].

Comparisons with RA controls. A third analysis of variance by reading age and presence/absence

of dyslexia, excluding the oldest controls, revealed that the the main effect of reading age was

highly significant, whereas that of dyslexia was not [F(1,41)=21.5, p<.0001; F(1,41)=0.1, NS

respectively]. The interaction between RA and dyslexia was also significant [F(1,41)=11.3,

p<.01]. The effect of syllables was highly significant (p<.001), and there was a significant

interaction between reading age and number of syllables (p<.01). No other effect was significant.

This rather complex pattern of results suggests that nonword repetition is influenced by both age

and dyslexia. However, the interaction in the RA controls comparison, with poorer performance

by the young dyslexics than that shown by the even younger RA controls, is consistent with the

view that this test may be tapping a causal factor underlying dyslexia, and not simply reflecting a

developmental lag. The fact that there is no such discrepancy between dyslexic subjects and RA

controls for the older group suggests that this handicap may diminish as the child develops.

3 . 5 . Experiment 4. Memory Span and Phonological Similarity

The traditional technique for measuring span is to present two words, asking the subject to recall

them in order, then a list of 3 words, then 4 and so on, until two consecutive failures are made. In

this experiment, following Gathercole and Baddeley, two pools of six single syllable words were

constructed, with one pool comprising phonologically similar words (bat, cap, cat, pan, pram,

tap) and the other pool comprising six phonologically dissimilar words (bus, clock, hand, horse,

girl , spoon). Stimuli were stored as digitised speech on the computer. Lists for recall were

generated in a pre-specified sequence, with four cycles in each of which a two word list was

followed by a three word list, then a four word list, then a five word list, and then a six word list

(with the next cycle starting again at a two word list). The procedure for a single trial was as

follows: the experimenter checked that the subject was ready, then clicked the ‘start’ button. The

appropriate number of stimuli were then presented auditorily by the computer at the rate of one per

second. Immediately after the final stimulus, the subject was required to point to the stimuli in the

correct order, with the eight year olds pointing by hand, and the other groups using the mouse.

Data analysis and storage were performed automatically. Memory span was calculated following

the standard formula, in effect by adding 0.5 to the longest sequence of stimuli for which the

subject responded correctly4 . Thus, if a child consistently recalled all the stimuli for lists up to

and including four words, but made one or more errors on five word lists, the memory span

calculated would be 4.5. The results are shown in Figure 5.

**Insert Figure 5 here**

Overall analyses. A five group analysis of variance indicated significant main effects for group

and phonological similarity [F(4,50)=5.5, p<.001; F(1,50)=306.9, p<.0001 respectively]. The

interaction between group and similarity did not approach significance [F(4,50)=1.1, NS]. Tukey

hsd analysis indicated that the group effect was attributable to the oldest controls outperforming the

younger dyslexics and the youngest controls (p<.01).

Comparisons with CA controls. An analysis of the effects of age and of presence/absence of

dyslexia for the four older groups indicated that both factors had significant main effects

[F(1,41)=8.6, p<.01; F(1,41)= 7.8, p<.01 respectively] but the interaction between them was not

significant [F(1,46)=1.2, NS].

Comparisons with RA controls. A third analysis of variance by reading age and presence/absence

of dyslexia, excluding the oldest controls, revealed that neither the main effect of reading age nor

that of dyslexia was significant [F(1,39)=3.4, p>.05; F(1,39)=0.0, NS respectively]. The effect

of similarity was of course highly significant, and no other effect was significant.

4 In fact the formula used was ‘span = 0.5 + mean number of correct trials per cycle + 1’, which is a slightly more

general form of that cited above, and allows credit to be given where, say, the child errs on lists of length 3 but gets

some right at length 4.

This pattern of results therefore suggests that phonological similarity has a comparable effect on all

the groups tested.

3 . 6 . Experiment 5. Memory Span, Word Length and Articulation Rate

Baddeley, Thomson and Buchanan (1975) demonstrated that adults have a higher memory span

for short words than for long words. They showed further that the span was directly related to the

rate at which the subjects could articulate the words involved and interpreted their results in terms

of an auxiliary storage system that they termed the ‘articulatory loop’. Nicolson (1981)

demonstrated that this effect was sufficient to account for the increase in children’s memory span

with age, in that the increase in memory span directly paralleled the increase in reading rate. This

finding has been replicated and extended by Hitch and by Hulme and their co-workers (eg. Hitch,

Halliday & Littler, 1983; Hulme, Thomson, Muir & Lawrence, 1984). The power of the

technique for analysis of dyslexia is that it provides a method of determining whether the

established immediate memory problems of dyslexic children should be thought of as

developmental lag or developmental disorder. The lag hypothesis would suggest that the span

would be exactly as predicted from the articulation rate, whereas the disorder hypothesis would

require that the deficit in span should be more extreme than predicted from articulation rate.

3 . 6 . 1 . Experiment 5a. Memory Span and Word Length

In order to be able to test this hypothesis, we extended the word length experiment reported in

Gathercole and Baddeley (1990) by using three word lengths and by measuring the articulation

rate for words in each of the three word length pools. The procedure used was adapted from those

used recently by Hitch, Halliday, Dodd and Littler (1989) and Hulme and Tordoff (1989) in

investigating the development of memory span as children get older. The stimuli used were taken

from a pool of one-syllable words (pig, bus, car, fish, leaf, spoon, bed, and egg); a pool of two-

syllable words (monkey, rocket, tiger, apple, pencil, scissors, hammer, and flower); and a pool

of three-syllable words (helicopter, elephant, banana, butterfly, umbrella, christmas tree,

kangaroo, and fire engine). The memory span data were collected as in the previous experiment,

with four cycles of presentation of lists of 2, 3, 4, 5 and then 6 words for each of the three word

pools. Stimuli were presented auditorily at the rate of one per second, and subjects attempted

spoken recall of the list in order directly following each presentation. Results were recorded

online and memory span determined automatically. The results for memory span are shown in

figure 6.

**Insert Figure 6 here**

It may be seen that all four groups showed the usual effect of word length, in that the memory

span decreased as the word length increased.

Overall Analysis. A five group analysis of variance was undertaken. Both group and length had

significant main effects [F(4,51)=4.9, p<.01; F(2,102)=71.1, p<.0001 respectively], whereas

their interaction did not approach significance (F<1). Tukey hsd analysis indicated that the group

effect was attributable to the oldest controls outperforming the younger dyslexics (p<.05) and the

youngest controls (p<.01).

Comparison with CA controls. Analysis by age and dyslexia for the four older groups indicated

that both had significant main effects [F(1,42)= 5.9, p<.05; F(1,42)=4.1, p<.05 respectively]

with the interaction non-significant (F<1).

Comparisons with RA controls. A third analysis of variance by reading age and presence/absence

of dyslexia, excluding the oldest controls, revealed that the main effect of reading age was

significant whereas that of dyslexia was not [F(1,38)=7.1, p<.05; F(1,38)=0.9, NS respectively].

The effect of syllables was of course highly significant and no other effect approached

significance.

This pattern of results is consistent with the assumption that the effects of word length on recall by

the dyslexic subjects are the result of a developmental lag.

3 . 6 . 2 . Experiment 5b. Articulation Rate and Word Length

Articulation rate for 1 syllable, 2 syllable and 3 syllable words was tested by timing the subjects

repeating each word in each list five times, following the procedure outlined in experiment 2b

above. For each child the mean articulation time for a given syllable length was then obtained by

averaging the times for the words in that list. The results are shown in figure 7. Overall, as one

would expect, the data follow a similar pattern to that of Experiment 2b.

**Insert Figure 7 here**

Overall analysis. A five group analysis of variance indicated that both group and syllables had

significant main effects [F(4,49)=11.5, p<.0001; F(2,98)=5050.8, p<.0001 respectively]. The

interaction between group and word length was also significant [F(8,98)=2.7, p<.05]. Tukey hsd

analysis indicated that the group effect was attributable to the younger dyslexics and the youngest

controls performing significantly slower than the oldest controls and the 11 year old controls

(p<.01) together with the younger dyslexics also performing significantly slower than the older

dyslexics (p<.05).

Comparison with CA controls. Analysis in terms of age and presence/absence of dyslexia for the

four older groups indicated that both had a significant main effect [F(1,41)=10.0, p<.01;

F(1,41)=23.9, p<.0001 for age, dyslexia respectively], thus replicating the results of Experiment

2a. The interaction between age and dyslexia was not significant [F(1,42)=3.7, p>.05], and the

only significant interaction was between group and word length [F(2,82)=4.6, p<.05].

Comparison with RA controls. The analysis by reading age and presence/absence of dyslexia,

excluding the oldest controls, revealed that the main effect of reading age was significant whereas

that of dyslexia was not [F(1,38)=20.9, p<.001; F(1,38)=2.5, NS respectively]. The effect of

syllables was of course highly significant, and the only significant interaction was that between

reading age and word length [F(2,76)=5.5, p<.01].

This pattern of results is therefore broadly consistent with a developmental lag interpretation of the

deficit in articulation rate by the dyslexic subjects.

3.6.3. Analysis 5c. Memory Span and Articulation Rate

As noted earlier, however, a key theoretical question is whether the memory span differences

between the groups parallel the differences in articulatory rate. The data are replotted in figure 8 in

terms of memory span as a function of articulation rate. Each group contributes three points to the

graph (one for each list length). The regression line through the five sets of three points gives an

estimate of the relationship between memory span and articulation rate. The value of r2 represents

the square of the correlation between span and articulation rate for the groups, with 1.0 reflecting

perfect collinearity.

**Insert Figure 8 here**

The mean group data show a reasonably linear relationship between memory span and articulation

rate, though the scatter in the individual results was marked. The population mean slope was

0.54, with an intercept of 3.31, and an overall correlation given by r2=0.83. It may be seen that

all the points (except that for the longest words for the youngest controls) fall close to the overall

line, and there is no obvious discrepancy between the groups on the basis of the presence or

absence of dyslexia. The normal interpretation of the intercept and slope following Baddeley’s

(1986) working memory framework would be that the intercept reflects the contribution of the

phonological input store, whereas the slope of the line reflects the efficiency of the phonological

rehearsal process. Given this interpretation it is possible to test directly the possibility that there is

some deficit in one or other phonological component of the working memory system. The

regression technique does not yield inferential statistics, and so we performed regressions for

slope and intercept on all the individual sets of three data point pairs. A 5 group analysis of

variance was then undertaken separately for intercept and for slope and no significant differences

were found in either analysis. Unfortunately the data thus obtained are somewhat unreliable,

depending critically on how closely the individual data correspond to a straight line. Furthermore,

the intercept correlates negatively with the slope, since it represents the back-projection of the

regression line to the zero articulation rate axis. Consequently little reliance can be placed on the

null results obtained.

In an attempt to control for these problems, for each individual the ‘centroid’ of their three data

points was calculated (ie. their mean span and their mean articulation rate). The centroid is the

most reliable summary statistic for the overall data, and the regression line will always travel

through it. Two separate analyses were then undertaken, first calculating the intercept by

projecting backwards a line from the individual’s centroid with slope equal to the population mean

(0.54), and second calculating the slope of the line from the individual’s centroid to the population

mean intercept (3.31). These represent the most robust, unbiased estimates possible for the

intercept and slope respectively. The mean data are shown in Table 2. Separate analyses of

variance performed on the adjusted slopes and intercepts indicated there was no significant

difference between groups [F(4,47)=1.1, NS; F(4,47)=1.06, NS for slope, intercept

respectively].

4 . Overall Discussion of Phonological Processing and Working Memory

The results follow a similar general pattern to that found by Gathercole and Baddeley (1990),

though there are also notable differences. For voice onset latency there was no evidence of any

effect related to dyslexia, findings also obtained by Gathercole and Baddeley. For articulation rate

Gathercole and Baddeley found a non-significant trend towards slower articulation for the dyslexic

children, whereas our results were more clear-cut, indicating a significant effect of dyslexia,

whereas that of age was not significant. For memory span, the qualitative effects of word length

and of phonological similarity were equivalent for all groups, as was found by Gathercole and

Baddeley. On the other hand, the degree of overall impairment was less marked than found by

Gathercole and Baddeley, with neither dyslexic group performing significantly worse even than

their age-matched controls. For phonological discrimination there was an effect of dyslexia but

not age, with the younger dyslexics showing significant impairments in two conditions.

Gathercole and Baddeley found no such impairment, though the language-disordered children

showed a tendency to impairment on nonword discriminations. For nonword repetition there was

a clear effect both of age and dyslexia (deriving from the younger dyslexic subjects) and

furthermore the younger dyslexics were even out-performed by their reading age controls on the

longer stimuli, as found by Gathercole and Baddeley.

The group effects are summarised in Table 3. Note that the second column gives the mean

performance of each group (collapsed over the other experimental variables).

**Insert table 3 here**

In summary, it would appear that the fifteen year old dyslexic children have effectively overcome

any earlier handicaps in phonological discrimination, nonword repetition and memory span,

performing at levels close to those of non-dyslexic children of similar age. By contrast, the eleven

year old dyslexic children still show evidence of deficits in phonological skills such as nonword

repetition which are known to be particularly marked in younger dyslexic children. In this

connection it should be noted that the language-disordered subjects tested by Gathercole and

Baddeley averaged eight years of age, as compared to the 11 and 15 year old groups in the present

study. Our subjects are therefore likely to have had both more remedial teaching and more time for

any developmental lag to catch up. The fact that the 15 year old dyslexics were not significantly

inferior to age-matched controls on any of our tests contrasts with the performance of the 11 year

old dyslexics, who broadly speaking performed at the level of the younger reading-matched

controls. This, together with Gathercole and Baddeley’s finding that 8 year old language

disordered children performed phonological memory tasks at a level below that of reading-matched

controls, suggests a process of gross initial impairment followed by gradual recovery. Any

attempt to draw strong conclusions of a causal nature thus runs into problems — it is quite

possible that whatever deficit was initially responsible for poor reading may well have recovered in

our 15 year old group. The good performance of our group of older dyslexic children is

underlined by the fact that these 12 dyslexic children were the lower performers in a group of over

20 dyslexic children whom we had been monitoring since the age of 11. Six of the remainder had

achieved normal reading levels and were thus no longer technically ‘dyslexic’.

Before considering the possible reasons for the deficit of the 11 year old dyslexics, it is therefore

important to make the applied point that the full recovery of the older dyslexics is particularly

encouraging for long-term alleviation of their problems. It suggests that many of their long-term

reading-related problems are probably attributable entirely to the cumulative impairments caused by

lack of reading skill (termed by Stanovich, 1986, the ‘Matthew Effect’, a biblical reference to the

poor getting poorer). In particular, it would suggest that if the early problems are diagnosed and

remedied quickly, this should prevent any subsequent ‘recurrence’ of reading problems.

Let us now consider the implications of the findings for our original research issue — which is the

primary deficit, phonological skill or working memory? This is a difficult issue to tackle owing to

the close relationship between the two, not least because of their co-variation with fluency of

articulation. Insofar as the issue can be addressed, one would expect a phonological anomaly to

show up either as a phonological discrimination deficit, or as an abnormal phonological

confusability effect, or as an impairment of the phonological input store. For working memory

(WM) it is useful to distinguish between the architecture and the performance of the WM system,

with the performance reflecting not only the architecture but also the efficiency of the control

processes involved. The improvement of a child’s WM with age indicates a performance

improvement, but with the same architecture. With this analysis, a WM architecture disorder

should show up either as an anomalous slope or intercept for the memory span vs articulation rate

regression. Although the latter regression data are noisy, there is no evidence whatever of an

abnormality in either slope or intercept, and the slight deficit in overall span is accounted for

completely by an equivalent deficit in articulation rate. One might conclude therefore that,

although there is a slight impairment in working memory performance, this reflects impairment of

the control processes (as reflected by articulation rate) rather than an underlying disorder of the

WM architecture.

On the other hand, the evidence for a causal role of phonological skill deficits is barely more

convincing. The deficit in phonological discrimination is difficult to interpret, owing to difficulties

with the test used and also discrepancies between the results of the different components of the

test. There was no evidence of any abnormality in the phonological confusability effect, and no

evidence of impairment for repeating short nonwords. Even the deficit in articulation rate is

problematic for a pure phonological deficit hypothesis. Since the children were merely repeating a

given word, little or no perceptual processing is required, and only a single access to the motor

articulation codes for the word, an access which occurs before timing starts. The most natural

interpretations of an articulation rate deficit are either motor skill deficit or perhaps inefficiencies in

the stored articulatory codes, neither being directly related to phonological skill.

It would appear, therefore, that any adequate explanation of the deficits of dyslexic children would

need to confront the issues of why there was an articulation rate deficit, why there was a nonword

repetition deficit for the younger dyslexics. Neither of our original hypotheses provides a

convincing account of both deficits.

In an attempt to investigate further the cause of the deficit on repeating nonwords, the errors made

were inspected. The errors for the younger dyslexics and the youngest controls are reproduced in

Appendix 3. It may be seen that for both groups the errors were relatively minor, almost always

preserving the overall ‘auditory shape’ of the stimulus, and generally involving the substitution or

addition of a single phoneme. Interestingly, the ‘error phoneme’ is usually phonologically

plausible and often occurs elsewhere in the stimulus (cf. empliforvent-emplifLorvent;

perplisteronk-pLerplisteronk; stopograttic-stRopograttic; vultularity-vultuRarity; detraterpilic-

detraPerpilic; confrantually-confLantually). This pattern of errors suggests that the subjects are

able to make use of two sources of information: first, the fading echoic trace of the original

stimulus, which presumably retains prosodic cues, giving an ‘auditory blueprint’ which constrains

the possible matches for each phoneme; and, second, the activation energies of the individual

‘phoneme detectors’ which are activated by the auditory input. As the blueprint fades, it will

constrain the possible matches less, thus allowing intrusions or substitutions of phonemes which

were highly activated because of a match elsewhere in the stimulus. Deficits in this process might

be caused in several ways. One possibility would be that the phoneme activation process was

slower, which would mean that by the time all the phonemes had been processed the blueprint

would be more degraded. A related possibility would be that the phoneme activation process was

more noisy, leading to activation not only of the correct phoneme but also several related

phonemes. Subsequent input of a related phoneme might well lead to ‘swamping’ of the correct

phoneme by the related one.

Our data do not discriminate between these hypotheses, which should prove a valuable target for

subsequent research. However, regardless of the underlying cause, let us consider the likely

effect of the observed articulation rate deficit on nonword repetition (NWR). There is a clear

analogy between NWR and memory span. It is well established that the ‘stimuli’ in a memory

experiment depend upon the notion of a ‘cognitive unit’ or chunk (Miller, 1956). Presumably, a

cognitive unit is the largest component that is explicitly represented. In a span experiment the

stimuli are words as are the cognitive units, and the task is to repeat back the words in the right

order. In the NWR task the stimuli are nonwords, but the units are word fragments (phonemes,

phoneme clusters, or syllables), and the subject’s task is to repeat back the units in the right order.

There is no doubt a high correlation between the rate of phoneme or syllable articulation and the

rate of articulation of words, and so there is every reason to believe that nonword repetition should

co-vary with articulation rate in much the same way as does memory span, and hence that the

reduced nonword repetition ‘span’ is also attributable to the reduced articulation rate. This

interpretation would therefore allow a parsimonious account of the data in terms only of the

articulation rate deficit. Whether articulation rate deficits can provide a complete account of the

data remains questionable, however. A slight problem for this interpretation derives from our own

data, in that the younger dyslexic children had a slightly better memory span than their age-

matched controls despite a slightly slower articulation rate. More worrying, however, is

Gathercole and Baddeley’s finding (1990) of significantly reduced memory span in their 8 year old

children, despite no significant difference in articulation rate.

The reason for an articulation rate deficit remains unclear. One possibility, which receives support

from experiments on gross motor skill in dyslexic children, is that it reflects a deficit in skill

automatisation (Nicolson & Fawcett, 1990). However, the experiments reported here were not

designed to investigate this possibility, and the relationship between articulation rate, working

memory and automatisation would again make a valuable focus for further research.

5 . Conclusions

The issue that initially motivated this research was an attempt to discriminate between two possible

theoretical explanations of the impairments of dyslexic children, namely the phonological deficit

hypothesis and the working memory deficit hypothesis. The most parsimonious account of the

data is that the 11 year old dyslexic children suffered from a deficit in articulation rate, and that the

articulation rate deficit mediates the performance deficits across the range of tasks reported.

Unfortunately, neither working memory nor phonological deficits provide a natural explanation of

the significantly slower articulation rate of the dyslexic children. The automatisation deficit

hypothesis (Nicolson & Fawcett, 1990) provides a natural account of the articulation rate deficits

but provides no insight into the linkage between articulation rate and working memory. We

propose that all three theories are best seen as symptoms, each providing a different perspective on

some underlying deficit.

In terms of the theoretical interpretation of the results, discovery of the articulation rate deficit is a

potentially significant breakthrough in dyslexia research. The finding has not previously been

reported in the literature, but it is clear that subsequent research on working memory and on

phonological processing must monitor this variable. The reasons for the deficit in articulation rate

remain unclear, and should prove a valuable target for subsequent research. It is also worth

emphasising the need to consider longitudinal effects, in that the developmental pattern of working

memory performance is one of fairly severe initial deficit (as established by Gathercole &

Baddeley, 1990, with 8 year old children), through mild deficit at 11 years to little or no deficit at

15 years.

The applied implications of the research seem clear. The established links between phonological

deficits and problems in learning to read (eg. Bradley & Bryant, 1983) suggest that dyslexic

children are not ‘phonologically ready’ to read at the normal age of around six years. Related

work (eg. Bradley, 1988) has shown that pre-school phonological training for ‘at risk’ children

can allow an apparently normal acquisition of reading, but there has been uncertainty as to how

completely the problems have been remedied, and whether in the absence of continuing support

the children might start to lose ground again. Our research leads to the positive conclusion that

there is a good chance of an essentially complete recovery, and it therefore further strengthens the

case for very early diagnosis of dyslexia backed up by a remediation programme which provides

extensive, carefully designed support for phonological skills and other skills upon which reading

is based.

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Appendix 1. Psychometric Details on the Subject Panel

ActualAge (yrs)

FullIQ

ReadingAge (yrs)

ActualAge (yrs)

FullIQ

ReadingAge (yrs)

Cont 15 Dys 15AJ 15.5 130 15.0 DK 15.8 118 11.4AV 15.1 105 14.6 GF 15.8 102 11.1DB 15.6 95 14.5 JN 14.2 100 12.2JE 15.0 115 15.0 JB 15.8 124 13.9KT 15.2 101 15.0 JA 16.0 126 14.4MG 15.0 117 15.0 JH 16.2 91 11.3NM 16.0 112 15.0 MH 16.1 117 13.9NS 15.4 104 14.4 NL 14.9 114 13.1PB 15.6 92 15.0 PS 14.4 102 8.1PC 15.9 118 15.0 RF 15.8 115 12.8SW 15.2 101 14.8 SP 15.5 92 11.2TB 15.2 91 15.0 SG 15.0 92 10.8

Cont 11 Dys 11AJ 12.1 117 12.6 AB 12.4 101 10.8BD 10.8 96 9.8 CJ 11.3 119 8.9CA 12.2 111 12.1 CE 9.7 109 7.0DG 10.8 121 11.4 DP 10.8 109 7.3JM 10.8 103 10.2 IT 12.0 112 9.5JD 11.0 96 11.0 MC 11.3 114 8.3KH 11.7 100 10.6 MC 12.9 109 9.8KG 11.7 126 11.6 RH 12.5 105 8.0LL 12.1 107 12.0 SA 11.3 128 9.6RM 11.7 105 12.7 TA 10.5 109 8.3SE 11.8 114 12.2 TF 9.7 109 6.9SW 11.7 119 12.0

Cont 8AM 7.9 102 8.2CE 8.2 133 8.0DT 8.5 121 9.5KN 7.0 129 7.7MC 8.8 105 8.1MCh 8.0 112 10.6PT 8.2 105 7.7SS 8.6 101 9.6TW 8.1 112 9.5VS 8.1 117 8.2

Appendix 2. Mean Scores for Nonword Repetition

Maximun score is 5; standard deviations are in parentheses.

2 syllables 3 syllables 4 syllables 5 syllables

Simple Complex Simple Complex Simple Complex Simple Complex

Cont 15 4.92 (0.29) 4.75 (0.45) 4.92 (0.29) 4.83 (0.39) 4.33 (0.78) 4.67 (0.65) 4.67 (0.89) 4.75 (0.45)

Dys 15 4.92 (0.28) 4.85 (0.38) 4.85 (0.38) 4.38 (0.77) 4.62 (0.65) 4.62 (0.65) 4.46 (0.66) 4.31 (0.85)

Cont 11 3.83 (1.03) 4.25 (0.63) 4.42 (0.79) 4.17 (0.72) 4.83 (0.39) 4.67 (0.49) 4.58 (0.51) 3.75 (0.87)

Dys 11 4.64 (0.67) 4.18 (0.75)4.00 (1.26) 3.55 (0.69) 3.64 (1.03) 4.00 (1.18) 3.36 (1.03) 3.27 (1.56)

Cont 8 4.30 (1.06) 4.30 (0.67) 4.40 (0.97) 3.90 (0.74) 4.30 (0.48) 4.30 (0.82) 3.80 (0.63) 3.60 (0.84)

Appendix 3. Nonword Repetition Errors

** this is in a separate file since it needs printing out as landscape page setup

Table 1. Summary Psychometric Data for the 5 groups of subjects

Group Number MeanChron.Age (CA)

MeanIQ

MeanReadingAge (RA)

CA Range IQ Range RA Range

Dys 15 12 15.3 107.7 11.9 14.2 to 16.2 91 to 126 8.1 to 14.4

Cont 15 12 15.4 106.8 14.9 15.1 to 15.9 91 to 130 14.4 to 15.0*

Dys 11 11 11.5 111.5 8.6 9.7 to 12.9 101 to 128 6.9 to 10.8

Cont 11 12 11.5 109.6 11.5 10.8 to 12.1 96 to 126 9.8 to 12.7

Cont 8 10 8.1 113.7 8.7 7.0 to 8.8 101 to 133 7.7 to 10.6

* 15.0 represents ceiling on the Schonell test of reading age used. Most of this group werereading at this level.

Table 2. Mean data for slope and Intercept (standard deviations in parentheses)

†Slope3.31* Intercept0.54

Cont 15 0.61 (0.18) 3.54 (0.49)

Dys 15 0.56 (0.18) 3.34 (0.46)

Cont 11 0.53 (0.23) 3.26 (0.54)

Dys 11 0.62 (0.24) 3.39 (0.42)

Cont 8 0.47 (0.25) 3.16 (0.49)

† Slope3.31 is the mean of the individual slopes per group, with the regressionconstrained to pass through the population mean intercept of 3.31 items.

* Intercept0.54 is the mean of the individual intercepts per group, with theregression constrained to have the population mean slope of 0.54 items/sec..

Table 3. Summary of the Between-Group Effects in the Six Experiments

MeanScores

Overall 5 groupanalyses

Comparisonwith CAControls

Comparisonwith RAControls

C15vs

D15

D15vs

C11

C11vs

D11

D11vsC8

AgeCA DysCA AgeRA DysRA

PhonologicalDiscrimination(% correct)

C15 85D15 84C11 85D11 80C8 83

NS NS * NS NS * * NS

Voice OnsetLatency(sec.)

C15 .36D15 .38C11 .42D11 .45C8 .46

NS NS NS NS *** NS * NS

Articulation TimeI(sec / word)

C15 .35D15 .44C11 .41D11 .50C8 .45

NS NS NS NS NS ** NS NS

Articulation TimeII(sec / word)

C15 .34D15 .37C11 .35D11 .48C8 .46

NS NS ** NS ** *** *** NS

NonwordRepetition(% correct)

C15 95D15 92C11 86D11 77C8 84

NS NS ** NS* *** ** *** NS*

Memory Span &PhonologicalSimilarity(words)

C15 4.9D15 4.2C11 4.1D11 3.8C8 3.8

NS NS NS NS ** ** NS NS

Memory Span &Word Length(words)

C15 5.1D15 4.7C11 4.7D11 4.4C8 4.2

NS NS NS NS * NS * NS

Intercept(words)

C15 3.5D15 3.3C11 3.3D11 3.4C8 3.1

NS NS NS NS NS NS NS NS

Slope(sec)

C15 .61D15 .58C11 .55D11 .62C8 .44

NS NS NS NS NS NS NS NS

KeyC15 Controls age 15 *** difference significant at the .001 levelD15 Dyslexics age 15 ** difference significant at the .01 levelC11 Controls age 11 * difference significant at the .05 levelD11 Dyslexics age 11 NS difference not significant at the .05 levelC8 Controls age 8 NS* main effect NS, but interaction sig. at .05 level

Figures

Figure 1. Results for Phonological Discrimination

Figure 2. Voice Onset Latency Results

Figure 3. Articulation Times

Figure 4. Nonword Repetition Performance

Figure 5. The Effects of Phonological Similarity on Memory Span

Figure 6. Memory Span and Word Length

Figure 7. Articulation Rate and Word Length

Figure 8. Memory Span as a function of Articulation Rate

Figure 1. Results for Phonological Discrimination

50

60

70

80

90

100Cont 15Dys 15Cont 11Dys 11Cont 8

% C

orre

ct

WordsSame

NonwordsSame

WordsFric

NonwordsFric

WordsPlosive

NonwordsPlosive

Figure 2. Voice Onset Latency Results

1 syll 3 syll0

0.1

0.2

0.3

0.4

0.5Cont 15Dys 15Cont 11Dys 11Cont 8

Vo

ice

On

set

La

ten

cy (

sec)

Figure 3. Articulation Times

1 syll 3 syll0

0.2

0.4

0.6

0.8

Cont 15Dys 15Cont 11Dys 11Cont 8

Art

icu

latio

n

Tim

e

(se

c)

Figure 4. Nonword Repetition Performance

5432

50

60

70

80

90

100

Cont 15Dys 15Cont 11Dys 11Cont 8

Syllables

Per

cent

Cor

rect

Figure 5. The Effects of Phonological Similarity on Memory Span

Normal Confusable0

1.0

2.0

3.0

4.0

5.0

6.0

Cont 15Dys 15Cont 11Dys 11Cont 8

Me

mo

ry S

pa

n

Figure 6. Memory Span and Word Length

1 syll 2 syll 3 syll0

1.0

2.0

3.0

4.0

5.0

6.0Cont 15Dys 15Cont 11Dys 11Cont 8

Mem

ory

Spa

n

Figure 7. Articulation Rate and Word Length

1 syll 2 syll 3 syll

0

0.2

0.4

0.6

0.8

1.0

Cont 15Dys 15Cont 11Dys 11Cont 8

Art

icul

atio

n T

ime

(sec

)

Figure 8. Memory Span as a function of Articulation Rate

543210

3

4

5

6

Dys 15Cont 15

Cont 8

Cont 11Dys 11

Articulation Rate (Words / sec)

Mem

ory

Sp

an (

wo

rds)

MS = 3.31 + 0.54 AR (

R = 0.83)

2