&
Auditory Processing Skills and
Phonological Representation
in Dyslexic Children
Ulla Richardson1, Jennifer M. Thomson2, Sophie K. Scott3 and
Usha Goswami1,*
1
Faculty of Education, University of Cambridge, UK
Institute of Child Health, University College London, UK
3
Department of Psychology, University College London, UK
2
It is now well-established that there is a causal connection between
children’s phonological skills and their acquisition of reading and
spelling. Here we study low-level auditory processes that may
underpin the development of phonological representations in
children. Dyslexic and control children were given a battery of
phonological tasks, reading and spelling tasks and auditory
processing tasks. Potential relations between deficits in dyslexic
performance in the auditory processing tasks and phonological
awareness were explored. It was found that individual differences
in auditory tasks requiring amplitude envelope rise time processing
explained significant variance in phonological processing. It is
argued that developmentally, amplitude envelope cues may be
primary in establishing well-specified phonological representations,
as these cues should yield important rhythmic and syllable-level
information about speech. Copyright # 2004 John Wiley & Sons,
Ltd.
E
vidence from both typically developing and atypically developing
children demonstrates that the quality of a child’s phonological
representations is important for their subsequent progress in literacy.
This relationship has been found across all languages so far studied, for both
normal readers (e.g. Bradley & Bryant, 1983; Hoien et al., 1995; Siok & Fletcher,
2001), and dyslexic children (e.g. Bradley & Bryant, 1983; Bruck, 1992; Landerl,
Wimmer, & Frith, 1997; Porpodas, 1999). It is thus generally accepted that
dyslexia is characterized by developmental weaknesses in establishing phonological representations of speech. The ‘phonological core deficit’ theory
(Stanovich, 1988) argues that dyslexic children find it difficult to represent
mentally the sound patterns of the words in their language in a detailed and
*Correspondence to: Professor Usha Goswami, Faculty of Education, Shaftesbury Rd,
Cambridge CB2 2BX, UK. Tel.: +44-1223-369631; fax: +44-1223-324421, e-mail: ucg10@
cam.ac.uk
Copyright # 2004 John Wiley & Sons, Ltd.
DYSLEXIA 10: 215–233 (2004)
Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/dys.276
216
U. Richardson et al.
specific way. However, possible developmental causes of individual differences
in the quality of children’s phonological representations are not well-understood.
In this paper, we re-examine the hypothesis that auditory perceptual
difficulties impair the development of high-quality phonological representations
by children. This theory has lost favour recently, despite its logical appeal (see
Goswami, 2003a). Common criticisms are that positive findings are difficult to
replicate, that only sub-groups of dyslexics are affected, that when positive
relationships are found they are more robust in control groups, and that when
auditory deficits are found they tend to be small and cannot easily explain the
large phonological deficits observed (see Ramus, 2003; Rosen, 2003; for examples
of critiques, note however that both authors focus mainly on studies of adult
(remediated) dyslexics). The dominant auditory perceptual theory has been that
proposed by Tallal and her colleagues (Tallal, 1980; Tallal, Miller, & Fitch, 1993).
They have argued that dyslexic children have particular difficulties in processing
rapidly changing or transient acoustic events, and that the ability to process rapid
successive information is fundamental to setting up the phonological system. The
‘rapid processing deficit’ theory stemmed from data suggesting that dysphasic
(SLI) children had difficulties in making rapid temporal judgements when
stimuli were presented closely spaced in time. The children showed deficits in
comparison to controls when one stimulus rapidly followed another in both a
temporal order judgement paradigm (TOJ) and a same-different discrimination
paradigm. Children were not impaired when the ISIs were long (Tallal & Piercy,
1973; Tallal & Piercy, 1974). Similar deficits were then observed in 8 out of 20
dyslexic children (Tallal, 1980). Theoretically, it was argued that a rapid
processing deficit could affect literacy because transient information is critical
for phoneme perception, and phoneme awareness is necessary for reading. In
order to establish whether one is hearing phonemes such as /b/ or /d/ without
context, auditory information within temporal windows of approximately 40 ms
must be distinguished. This ‘rapid processing deficit’ theory has become so
dominant that a remediation package based on the elongation of brief perceptual
cues has been developed and is administered to thousands of children
(Merzenich et al., 1996; Tallal et al., 1996).
Nevertheless, the notion that dyslexic children suffer from a rapid auditory
processing deficit has been increasingly criticised (McArthur & Bishop, 2001;
Mody, 2003; Rosen, 2003, for recent reviews). Tallal’s initial findings have been
difficult to replicate, and studies that have found differences in either TOJ or the
alternative same-different judgement (repetitiony) task have suffered from
experimental designs employing non-adaptive procedures. Accordingly, the
number of trials administered around critical threshold regions have typically
been small (De Weirdt, 1988; Reed, 1989; Heiervang, Stevenson, & Hugdahl,
2002). An associated problem has been ceiling effects in control groups (Reed,
1989; De Martino, Espesser, Rey, & Habib, 2001). Studdert-Kennedy and Mody
(1995), see also Studdert-Kennedy (2002), have focused particularly on tasky
The same-different judgement or repetition task uses the same frequency-differing
stimuli as the TOJ task, however rather than making a judgement about stimulus order, the
listener hears a pair of tones and must decide whether they are the same or different (e.g.
‘high-high’, same; ‘high-low’, different). Following evidence of success at a long tone pair
ISI, the ISI then varies between 8 and 4062 ms (original 1973/4 papers).
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Auditory Processing Skills in Dyslexia
217
related problems in interpreting existing data for a rapid auditory processing
deficit, and have concluded that evidence for non-speech auditory processing
deficits is extremely weak. Other authors have noted that when non-speech
difficulties are found in dyslexic children, they extend to stimuli presented at
long ISIs (e.g. Share, Jorm, MacLean, & Matthews, 2002). Further, group
differences that are found in non-speech tasks frequently fail to account for
independent variance in reading and spelling (Farmer & Klein, 1993; Heiervang
et al., 2002).
An alternative research strategy for those interested in potential auditory
processing deficits is to work from the developmental nature of the phonological
deficits displayed by dyslexic children across languages. These deficits are very
consistent, even though the stimuli employed in phonological awareness tasks
are vastly supra-threshold. Developmental research has shown that awareness of
syllables in children precedes awareness of onsets and rimes, which in turn
precedes awareness of phonemes (see Ziegler & Goswami, in press, for a recent
cross-language review). Dyslexic children show developmental difficulties at
each linguistic level, depending on the age at which they are tested. Note
that the development of phonemic awareness can reach high levels in dyslexic
children learning to read languages other than English (Goswami, 2003b for
review). Goswami et al. (2002) proposed that as syllable-level information is
primary in early language acquisition, a difficulty in perceiving aspects of speech
rhythm (which is driven by syllable-level phonological structure) could be
impaired in developmental dyslexia. An early deficiency in extracting syllablelevel information from the speech stream would impair the development of the
entire phonological system, necessarily including the representation of
onset-rime level and phoneme-level information. Thus phonological processing
would remain effortful and slow, even in transparent languages where
orthographic consistency can ‘bootstrap’ the development of well-specified
phonological representations (see Ziegler & Goswami, in press). In dyslexic
children learning to read transparent orthographies, highly accurate performance
in phonological awareness tasks is eventually achieved, but processing is always
extremely slow.
To test their proposal, Goswami et al. (2002) developed a non-speech task
requiring children to judge whether an amplitude-modulated sound was
comprised of one element fluctuating in loudness, or of two different elements,
a distinct beat and a background sound. The sharper the rise time of the
modulation, the more likely it is that two sounds are perceived (the ‘beat’ is
perceived overlaying the carrier sound at the same rate as the modulation; see
Bregman, 1993). Dyslexic children were significantly impaired at this ‘beat
detection’ task compared to normally developing control children. Meanwhile,
precocious readers were superior at ‘beat detection’ compared to normally
developing controls. Behaviourally, the dyslexic children lost the perception of
the ‘beat’ when the rise times were extended (they perceived beats easily when
the rise times were rapid, e.g. 15 ms). Control children still perceived beats with
extended rise times. Precocious readers could detect a ‘beat’ when rise times were
extended so that normally developing control children lost beat perception.
These patterns suggest that an enhanced ability to integrate temporal information
over (relatively) long time windows is associated with better reading (rise times
used varied from 15 to 300 ms).
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U. Richardson et al.
Goswami et al. (2002) argued that deficits in the perception of amplitude
envelope cues or in the use of such envelope cues to construct auditory
objects may compromise the development of well-specified phonological
representations in dyslexic children. In particular, rise time perception
appeared to be impaired, which should lead to problems in representing the
syllable in terms of the sub-syllabic units of onset and rime (the rise time of
mid-band spectral energy is a strong cue to vowel onset). Information
about amplitude envelope onsets is also important for speech intelligibility
(Drullman, Festen, & Plomp, 1994; Shannon, Zeng, Kamath, Wygonski, & Ekelid,
1995) and hence phonological representation. Perceptually, the onset of the
envelope seems to be more important than what follows (Heil, 2003). Rise time
can also cue phonetic contrasts (as between /ch/ and /sh/, Cutting &
Rosner, 1974). There is also evidence that the perception of amplitude modulation
is impaired in dyslexia (Witton et al., 1998; Lorenzi, Dumont, & Fullgrabe, 2000).
For example, Witton, Stein, Stoodley, Rosner, and Talcott (1998) showed that
dyslexic children needed deeper modulations for detection, and as rise time covaried with modulation depth in this study, this is consistent with our
demonstration that dyslexics need sharper rise times to perceive AM-driven
‘beats’ in the signal.
Goswami et al. (2002) also reported that beat detection predicted large amounts
of variance in reading and spelling in the 73 dyslexic and control children
studied. Beat detection predicted 25% of the variance in standardized tests of
reading and spelling, even after controlling for age, non-verbal I.Q. and
vocabulary, and 14% of the variance in nonword reading (p’s50.001). These
are relatively large amounts of variance for simple auditory tasks (in prior
studies, auditory processing measures have typically accounted for 1–4% of the
variance in literacy measures after controlling for I.Q.). However, the potential
explanatory significance of these relationships was criticised by Rosen (2003)
in a re-analysis of Goswami et al.’s (2002) data. Rosen (2003) argued that as 3
groups of children had been studied (i.e. dyslexics, chronological age controls,
reading level controls), each group should be considered in isolation. He
then reported that AM beat detection did not correlate with nonword
reading when the dyslexic group were considered alone ðr ¼ 0:12Þ. His
conclusion was that significant relationships between auditory processing skills
and literacy were only characteristic of control children. Surprisingly, he did not
report that beat detection did correlate with both reading and spelling
development in the dyslexic group considered alone (reading; r ¼ 0:38,
p50.065; spelling, r ¼ 0:43, p50.05). Further, when seeking developmental
relationships, it is standard to analyse samples of children with varying levels of
development of the target skills (see Goswami, 2003a; Karmiloff-Smith, 1998, for
papers on stringent developmental research paradigms). The critical methodological point is to seek to control other variables, such as age or I.Q., that may covary with the target skills when carrying out such analyses. Within-group
analyses are of course important, but may not be informative when sample sizes
are small.
In the study reported here, we investigate the beat detection hypothesis further
using new auditory processing tasks designed to yield quantitative information
about the potential amplitude rise time deficit in dyslexia. One difficulty with the
original beat detection task was that it employed a categorization procedure,
Copyright # 2004 John Wiley & Sons, Ltd.
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Auditory Processing Skills in Dyslexia
219
even though the perception of a beat does not depend on a categorical distinction.
We therefore sought converging evidence for a rise time deficit via two new
measures of rise time perception based on a child-friendly threshold estimation
procedure involving cartoon dinosaurs. As a control measure, we also used
the dinosaur procedure to measure intensity (loudness) judgements. A second
goal was to explore in more detail potential relationships between rise
time perception and phonological awareness. Theoretically, Goswami et al.’s
causal hypothesis requires a connection between beat detection and the
development of well-specified phonological representations. A wide variety of
measures of phonological awareness was therefore employed in the current
study, incorporating both perception and production tasks at different linguistic
levels (oddity onset, oddity rhyme, onset same-different judgement, coda samedifferent judgement, onset production, rime production, coda production).
Phonological short-term memory and rapid automatised naming skills were
also measured.
A third goal of the study reported here was to explore rise time processing in
the context of other aspects of auditory processing in the same children.
These additional aspects comprised duration processing and rapid auditory
processing, following prior work by other investigators. Recent work in
Finnish has shown that the categorization of speech stimuli with durational
differences is poorer in infants at risk for dyslexia (Richardson, Leppanen,
Leiwo, & Lyytinen, 2003). In Finnish, duration is a phonemic cue, as sound
duration alone determines the quantity of a phoneme. The word ‘palo’ (short
duration of /l/) means ‘fire’, whereas the word ‘pallo’ (long duration of /l/)
means ‘ball’. Richardson et al. (2003) varied the phonological import of physical
duration in a categorical perception task based on the pseudowords ‘ata’/’atta’.
Here we used the same stimuli with English children. As ‘ata’ and ‘atta’ are
nonwords in English, we asked children to judge the duration of the entire
(bisyllabic) utterance (they effectively judged whether ‘atta’ was longer than
‘ata’).
The children’s rapid temporal processing abilities were investigated with nonspeech stimuli. Both TOJ and rapid frequency detection (same/different
judgement) tasks were administered, as in Goswami et al. (2002). Goswami et al.
reported a significant group difference between dyslexic children and controls in
the dog/car TOJ task (in which children had to decide whether they heard a dog
bark first or a car horn sound). However, TOJ performance accounted for only 6%
of unique variance in reading and explained no significant variance in nonword
reading or spelling. Dyslexic children and controls also differed significantly in
the rapid frequency detection (RFD) task, however here the deficit extended
across all ISIs, both long and short (Tallal’s theory requires differences at rapid
ISIs only). Interpretation of the findings for the RFD task were further
complicated by the fact that the performance levels of control children were
close to ceiling (mean performance across ISIs=89% correct). In the study
reported here, we therefore improved the sensitivity of the RFD task by
presenting it in an adaptive format. As the task can also be described as a pitch
discrimination task, we refer to it by that label in this paper. The TOJ task format
was unchanged, because the dog/car task proved the most predictive of
phonological skills in a study of adult developmental dyslexics reported by
Ramus et al. (2003).
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U. Richardson et al.
Table 1. Participant characteristics on the standardized tests
Group
Dyslexic
CA match
RL match
N
Age in years and months
Reading level (age)a
Reading standard scorea
Spelling level (age)a
Spelling standard scorea
Nonword reading/20b
IQc
Vocabulary stand scored
Mathematics stand scorea
24
8,9 (9)
7,6 (9)
89.5 (5.4)
7,9 (9)
90.5 (6)
8.9 (4.7)
110.6 (11.3)
107.5 (14.2)
106.8 (13.4)
24
8,10 (10)
11,0 (23)
118.8 (9.7)
11,3 (27)
119.4 (13)
18.6 (1.7)
111.6 (15.4)
106.9 (10.6)
112.5 (14.1)
17
7,3 (6)
7,8 (12)
110.4 (10.8)
8,5 (17)
116.1 (12)
10.5 (5.1)
110.8 (12.3)
103.0 (10.6)
109.9 (12.5)
Standard deviations are shown in parentheses.
British ability scales.
b
Graded test of non-word reading.
c
WISC short form.
d
British picture vocabulary score.
a
METHOD
Subjects
Sixty-five children participated in the study. Twenty-four of the children had a
statement of dyslexia from their local education authority, and were drawn from
special dyslexic schools and support units. None of these children had dysphasia
or suffered from another neurological or psychiatric disorder. Of the 41 control
children from a local school, 24 were chronological age-matched controls (CA
group) and 17 were reading level-matched controls (RL group). All control
children whose parents returned a consent form and who met our inclusion
criteria of normal reading and spelling, no other educational difficulties and a
WISC I.Q. above 85 were included in the study. Participant characteristics are
shown in Table 1.z
Tasks
a. Auditory processing tasks
Most of the auditory processing tasks were administered using a child friendly
‘Dinosaur’ program (created by Dorothy Bishop, Oxford University) that
presents auditory stimuli in a forced choice paradigm, adaptively selecting
stimulus values to enable efficient threshold measuring. Two Dinosaur
paradigms were utilized here. In the two-interval forced-choice paradigm
(2IFC), two sounds are presented consecutively as the sounds made by two
distinctive cartoon dinosaurs (500 ms IOI), and the child is required to choose the
dinosaur making the target sound. In the AXB paradigm, three sounds are
z
As can be seen, the British Ability Scales (re-standardized in 1997, just before the advent
of the National Literacy Strategy) are now producing consistently elevated literacy
standard scores for the different age groups.
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221
presented consecutively as the sounds made by three distinctive cartoon
dinosaurs (500 ms IOI). The middle stimulus (X) is always the standard stimulus
and either the first (A) or the last (B) stimulus is different from the standard. The
more virulent PEST (Parameter Estimation by Sequential Testing, Finlay, 1978)
method was used adaptively to control which stimulus was presented according
to the subject’s previous performance.
i. Rise time of amplitude envelope onset (AXB) task. A continuum of 40 stimuli was
created from a 500 Hz sinusoid with 0.7 Hz amplitude-modulation (depth of
50%), varying the linear rise time envelope logarithmically from 15 to 300 ms. The
steady state of the stimuli had a fixed duration of 700 ms. The linear fall time
envelope was fixed to 50 ms (thus the overall duration of the stimuli varied from
765 to 1050 ms). The stimulus with the shortest rise time (15 ms) was used as the
standard. The child was required to choose the dinosaur that sounded different at
the beginning (which in this case corresponded to the ramps with the longer rise
times).
ii. Rise time of amplitude envelope onset (2IFC) task. A 3573 ms sinusoid carrier at
500 Hz amplitude-modulated at the rate of 0.7 Hz (depth of 50%), was used as a
starting point in creating a continuum of 40 stimuli. The underlying modulation
envelope was based on a square wave. The rise time was varied from 15 to 300 ms
(logarithmically spaced) and the fall time was fixed at 350 ms. The stimulus with
the longest rise time (300 ms) was used as the standard. The child was required to
choose the dinosaur with a clearer beat (which in this case corresponded to the
ramps with the shorter rise times).
iii. Duration discrimination (2IFC) task. A continuum of 100 stimuli was
constructed of the naturally produced nonword ata in which the duration of
the silent closure of the word medial stop (varying from 65 to 265 ms) was
augmented in stepwise fashion with increments of 2 ms. The stimulus with a
65 ms closure duration was used as a standard stimulus. The child listened to two
nonwords and was required to decide which of them was longer.
iv. Intensity detection (AXB) task. The dinosaur paradigm was used. A 500 Hz
sinusoid with linear onset and offset envelopes (50 ms) and fixed steady
state duration of 700 ms was used as a starting point for creating a
stimulus continuum for the intensity detection task. A continuum of 40 stimuli
was constructed by varying the intensity of the steady state logarithmically,
values ranging from 0 to 29.25 dB. The stimulus with 29.25 dB steady state was
used as a standard, and the child’s task was to choose the stimulus that was
different from the other two (which in this case was the quietest of the three
sounds).
v. Rapid pitch discrimination (previously RFD) task. This adaptive task was
modelled on Tallal and Piercy (1973). The stimuli were pairs of 30 ms complex
periodic (sawtooth) waves using harmonics up to the Nyquist frequency of
11.025 kHz with 4 ms rise and fall times. Two sounds were used, low and high,
with fundamental frequencies of 260 and 320 Hz. Every trial consisted of two
stimuli presented sequentially with an interstimulus interval ranging from 5 to
500 ms. All four possible stimulus orders were presented (low–low, low–high,
high–low, high–high). The children’s task was to tell whether the stimuli were the
same or different. Psychometric functions were obtained using special-purpose
software designed by Stuart Rosen (University College London) based on a
modification of Levitt’s adaptive procedure (Speech Pattern Audiometer or SPA).
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U. Richardson et al.
Two independent adaptive tracks were used, a continuum with the low
frequency sawtooth first (100 stimuli) and another with the high frequency
sawtooth first (100 stimuli). The categorisation function was derived from all
trials, and summary statistics for slope and category boundary estimated by
Probit analysis (Finney, 1971).
vi. Temporal order judgement (TOJ) task. Two sounds readily identifiable as a dog
bark (aperiodic) and a car horn (periodic) with a fundamental frequency of
about 400 Hz were used as stimuli. The sounds were 115 ms in duration (5 ms rise
and fall times) and the two stimuli were normalised to have the same rms level.
Two TOJ continua were constructed from these two pairs of sounds and
delivered using SPA. Each continuum consisted of 204 stimuli (stimulus onset
asynchrony, SOA, varied from þ405:0794 ms to 2405:0794 in 3.9909 ms steps).
Stimuli were allowed to overlap to the degree necessary to create the specified
SOAs. The children’s task was to tell which sound (dog or car horn) was
presented first.
Schematic depictions of the stimuli used in the different auditory processing
tasks are provided in Figure 1.
b. Phonological processing tasks
All phonological tasks except for the rapid naming task were presented
using digitised speech created from a native female speaker of standard
Southern British English. The children listened to the words through
headphones (AKG K141) and their responses were recorded using a DAT
recorder (Tascam DA-P1). Three different orders of trial presentation were
used in each task, counterbalanced across children. Practice trials were always
given.
i. Oddity task. The child listened to sets of 3 words, and had to select the odd
word out in terms of onset (20 trials, e.g. cap, cat, tab) or rhyme (20 trials, e.g. coal,
pole, tone).
ii. Segmentation and production task. The child listened to a spoken word and
either had to produce the onset (20 trials, e.g. ‘mud’ - /m/), the rime (20 trials,
e.g. ‘rhyme’}’I’m’) or the coda (20 trials, e.g. ‘coat’ - /t/).
iii. Same/different judgement task. The child had to decide whether pairs of
words shared the same or a different sound at the beginning (e.g. rule-room, millring; onset task) or at the end (e.g. tan-pan, tug-pub; coda task). There were 40
word pairs in each task (20 same pairs, 20 different pairs).
iv. Phonological short-term memory (PSTM). The child listened to sets of 4
monosyllabic CVC words and had to repeat them in the correct order (e.g. hat,
weak, jug, shop). There were 16 trials. No phoneme occurred more than once in
each trial.
v. Rapid automatised naming task (RAN). The child had to name two sets of 50
pictures of familiar objects (cat, shell, knob, zip, thumb; web, fish, book, dog, cup)
as fast as possible. Total naming time was recorded for each set and the mean
naming time for the two lists was used in the analyses.
c. Standardized psychometric tests
The children completed four subscales of the Wechsler Intelligence Scale for
Children (WISC): blocks, picture arrangement, similarities, vocabulary (these
four scales yield a short-form I.Q.). The British Ability Scales reading, spelling
Copyright # 2004 John Wiley & Sons, Ltd.
DYSLEXIA 10: 215–233 (2004)
Auditory Processing Skills in Dyslexia
223
and mathematics standardized tests were also administered, along with the
Graded Test of Nonword Reading. Finally, a measure of receptive vocabulary, the
British Picture Vocabulary Scales, was also administered.
Figure 1. Schematic depiction of the stimulus wave forms for the different auditory
processing tasks (note that the time scales used differ for different stimuli). (a) Rise time
AXB task: 15 ms rise time (standard) at left, 300 ms rise time at right. The duration of the
stimulus ranged from 765 to1050 ms in total. (b) Rise time 2IFC task: 300 ms rise time
(standard) at left, 15 ms rise time at right. The duration of the stimulus was 3570 ms in
total. (c) Duration 2IFC task: Ata with 65 ms occlusion (standard) at left, atta with 245 ms
occlusion at right. Total duration of a stimulus varied from 270 to 450 ms. (d) Intensity AXB
task: 29.25 at left (standard) and 0 dB at right. The total duration of the stimulus
was 800 ms. (e) Pitch discrimination task: The lower frequency sound (260 Hz) and
higher frequency sound (320 Hz) with 5 ms ISI at left, and with 500 ms ISI at right.
The total duration of the stimuli pair varied from 65 to 560 ms. (f) TOJ task: Dog bark
and car horn with 0 ms ISI at left and with 405 ms ISI at right. The total duration of
the stimuli pair varied from 230 to 635 ms.
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U. Richardson et al.
Figure 1. Continued.
RESULTS
The mean scores obtained by the children in each experimental group are shown
in Table 2. As predicted, a significant difference was found between the group of
dyslexic children and their CA controls in the two amplitude envelope onset
tasks. The dyslexics showed elevated thresholds for discrimination of rise time in
both the AXB and 2IFC tasks. The RL match controls had intermediate thresholds
in both tasks. The higher dyslexic threshold in the AXB task meant that with a
short rise time standard (15 ms) and comparison sounds with longer rise times,
dyslexics needed a difference in rise time of at least 104 ms in order to perform
the task with 75% accuracy. Thus they were reliably able to detect rise times of
119 ms and above as differing from 15 ms. In comparison, CA controls could
reliably detect a 60 ms difference in rise times (75 ms onset ramp versus 15 ms
standard). The higher dyslexic threshold in the 2IFC task meant that dyslexics
found it difficult to identify the dinosaur with a sharper beat once rise times
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Table 2. Mean performance for the dyslexics, CA and RL controls on the experimental
tasks
Amplitude envelope rise time 2IFC
threshold (max ¼ 40, 300 ms std)
Rangea in ms
Amplitude envelope rise time AXB
threshold (max ¼ 40, 15 ms std)
Rangea in ms
Duration 2IFC threshold
(max ¼ 100, 65 ms std)
Durations distinguished as ‘long’
Pitch discrimination task: slope SPA
Dog/car TOJ: slope SPA
Intensity threshold AXB (29.25 dB std)
dB range where all sounds ‘loud’
Short-term memory task (% correct)
RAN (s)
Oddity onset task (% correct)
Oddity rhyme task (% correct)
Same/diff onset task (% correct)
Same/diff coda task (% correct)
Onset production task (% correct)
Coda production task (% correct)
Rime production task (% correct)
Dyslexics
ðN ¼ 24Þ
CA Match
ðN ¼ 24Þ
RL Match
ðN ¼ 17Þ
21.5 (11.3)
13.9** (9.9)
16.8 (9.7)
15–58 ms
27.3 (9.9)
15–102 ms
21.1* (6.1)
15–82 ms
25.0 (9.6)
119–300 ms
41.9 (36.3)
75–300 ms
22.6* (22.1)
102–300 ms
46.4 (36.3)
149–265 ms
0.01 (0.02)
0.03 (0.02)
4.0 (2.6)
26.25–29.25 dB
68.4 (10.4)
45.8 (7.3)
68.5 (15.0)
61.0 (15.2)
84.4 (13.2)
87.0 (10.6)
69.4 (27.1)
67.9 (25.0)
94.2 (8.5)
110–265 ms
0.03 (0.04)
0.06* (0.07)
3.3 (1.7)
26.50–29.25 dB
78.7** (12.5)
42.3 (6.4)
90.6*** (11.5)
88.5*** (7.3)
95.6*** (3.6)
94.9** (4.9)
95.4*** (9.4)
94.0*** (7.1)
98.5* (3.5)
157–265 ms
0.03 (0.07)
0.03 (0.02)
4.5 (3.6)
26.00–29.25 dB
66.7 (10.6)
49.1 (7.0)
79.1* (11.2)
75.6** (14.5)
94.6** (6.6)
90.7 (7.7)
95.3*** (7.2)
89.1** (6.4)
97.4 (6.4)
a
Range of rise times reliably distinguished from the standard (on 75% of occasions). Standard deviations in
parentheses.
*p50.05.
**p50.01.
***p50.001.
differed from the 300 ms standard by less than 242 ms. Dyslexics could reliably
detect that pairs of ramps with 58 ms rise times had a sharper beat than the
300 ms standard pairs, whereas CA controls could differentiate sharper beats
when rise times differed by as little as 198 ms (distinguishing 102 ms onset ramps
from the 300 ms standard). Relating this back to the beat detection task, this
suggests that dyslexic children lose the perception of a beat once rise times are
longer than approximately 60 ms, whereas normally reading controls retain the
perception of a beat for rise times as long as 102 ms. The dyslexics also had
significantly higher thresholds than CA controls in the duration detection task
(2IFC dinosaur format). This task required the child to discriminate which of two
2-syllable nonwords was longer.} Importantly, however, thresholds in the
}
As well as responding on the basis of the duration of the entire stimulus, as instructed, it
is possible that children were responding on the basis of the length of the period of silent
closure of the medial stop (gap size). In the original Finnish data, dyslexic children needed
a longer gap (180 ms) than controls (140 ms) to detect the change from one pseudoword
(ata) to the other (atta). It should be noted that in the Finnish language, the quantity (short
vs long) of the intervocalic t-sound is syllabic (supra-segmental): a long consonant
includes a syllable boundary, whereas a short consonant does not.
Copyright # 2004 John Wiley & Sons, Ltd.
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U. Richardson et al.
intensity detection task (AXB dinosaur format) did not differ significantly
between the groups. Thus, dyslexic children are not simply worse at detecting
any auditory parameter in the Dinosaur paradigm. Further, dyslexic children did
not show a deficit in the rapid pitch discrimination task employing the more
sensitive adaptive procedure. They did show significantly flatter psychometric
slopes than CA controls in the temporal order judgement (TOJ) task.
To explore relations with phonological representation, a series of fixed order
multiple regression equations were computed, using the whole group of children
in order to characterise developmental relationships. For each regression,
unusual or influential data-points according to the Cook’s Distance metric were
eliminated. The dependent variables used were respectively onset oddity, rime
oddity, onset production, rime production, coda production, onset samedifferent, coda same-different, RAN and PSTM. The independent variables were
(in a fixed order) 1. age, 2. WISC short-form I.Q. (verbal and nonverbal), 3.
vocabulary (BPVS), 4. an auditory processing measure. Figures from the resulting
equations are shown in Table 3.
Inspection of Table 3 shows that the two measures of amplitude envelope onset
processing accounted for up to an additional 22% of the variance in phonological
processing in these stringent analyses. Relations with phonological skills were
stronger for the perception tasks (oddity and same-different judgement) than the
production tasks (segment production, PSTM and RAN). The rapid processing
measures, intensity detection and the duration processing tasks made no
independent contributions to phonological processing, with the exception of
significant relationships between intensity detection and PSTM, and pitch
discrimination and performance in the rhyme oddity task.
To explore relations between auditory processing, reading and spelling, a
further series of fixed order multiple regression equations were computed, again
using the whole group of children. The dependent variables were respectively
reading (standard score), spelling (standard score) and non-word reading
(number correct). The independent variables were again (in a fixed order) 1.
age, 2. WISC short-form I.Q., 3. vocabulary (BPVS), 4. an auditory processing
measure. The results of all equations computed are shown in Table 4. The two
measures of rise time processing accounted for significant additional variance in
reading and non-word reading (8–13%), with the rise time 2IFC task also
accounting for significant additional variance in spelling (11%). The duration
measure also accounted for significant additional variance in reading, spelling
and nonword reading (8–12%). The pitch discrimination measure made a
significant contribution to reading, but not to non-word reading or spelling. The
TOJ and intensity detection tasks made no independent contributions to reading
and spelling.
The group analyses clearly suggest that individual differences in auditory
processing skills are related to individual differences in the quality of
phonological representations, reading and spelling. Further, relations found
between the rise time measures, phonological representation and literacy are the
most consistent. However, patterns of performance within the dyslexic group are
also of interest. For example, it has been suggested that auditory processing
deficits may only characterise a sub-group of dyslexic children. In order to
investigate this possibility, the performance of the CA controls was used to
determine processing deficits in the dyslexics employing a stringent deviance
Copyright # 2004 John Wiley & Sons, Ltd.
DYSLEXIA 10: 215–233 (2004)
Copyright # 2004 John Wiley & Sons, Ltd.
*P50.05.
**P50.01.
***P50.001.
Step 4: 2IFC
Risetime
Step 4: AXB Risetime
Step 4: Duration
Step 4: Pitch
Step 4: Dog/car TOJ
Step 4: AXB
Intensity
Step 1: Age
Step 2: IQ
Step 3: BPVS
0.07*
0.04
0.01
0.01
0.01
0.00
0.01
0.00
0.02
0.00
0.06*
R2 change
0.12**
0.02
0.01
R2 change
0.11**
0.11**
0.00
0.08*
RAN
PSTM
0.08*
0.04
0.04
0.04
0.04
0.22***
R2 change
0.03
0.00
0.01
Oddity
Onset
0.09*
0.04
0.11*
0.05
0.02
0.13**
R2 change
0.00
0.01
0.00
Oddity
Rhyme
0.16**
0.02
0.03
0.02
0.02
0.17**
R2 change
0.00
0.03
0.01
Onset
Same/diff
0.08*
0.01
0.03
0.01
0.04
0.19***
R2 change
0.05
0.05
0.00
Coda
Same/diff
0.08*
0.01
0.03
0.05
0.03
0.09*
R2 change
0.01
0.01
0.04
Onset
Productn
0.06
0.03
0.02
0.05
0.01
0.08*
R2 change
0.00
0.01
0.00
Coda
Productn
0.03
0.02
0.03
0.00
0.01
0.08**
R2 change
0.02
0.07*
0.03
Rime
Productn
Table 3. Stepwise regressions exploring the unique variance accounted for by the auditory processing measures in the phonological tasks
Auditory Processing Skills in Dyslexia
227
DYSLEXIA 10: 215–233 (2004)
228
U. Richardson et al.
Table 4. Stepwise regressions exploring the unique variance accounted for by the auditory
processing measures in the literacy tasks
Step 1: Age
Step 2: IQ
Step 3: BPVS
Step 4: 2IFC
Rise time
Step 4: AXB
Rise time
Step 4: Duration
Step 4: Pitch
Step 4: Dog/car TOJ
Step 4: AXB intensity
Reading std score
Spelling std score
Nonword reading
R2 change
0.03
0.02
0.00
R2 change
0.06
0.01
0.00
R2 change
0.14**
0.02
0.00
0.08*
0.11**
0.09*
0.08**
0.03
0.13**
0.10**
0.11**
0.04
0.05
0.08*
0.04
0.06
0.01
0.12**
0.05
0.04
0.05
*P50.05.
**P50.01.
***P50.001.
criterion suggested by Ramus (see Ramus, 2003),} which identifies performance
levels below the 5th percentile. Application of the criterion to the dyslexic
children yielded 62.5% of dyslexics deviant for the AXB risetime measure, 41.7%
for the 2IFC risetime measure, 41.7% for the duration measure, 33% for the pitch
discrimination measure, and 13% for the TOJ measure. Regarding consistency of
these auditory deficits in individual dyslexic children, 15 dyslexic children were
below the 5th percentile for the rise time AXB measure, 10 of these same 15
children were also those deviant for the 2IFC measure of rise time discrimination,
and 9 of these same 15 dyslexic children were those deviant for the duration
measure. In contrast, only three dyslexic children were deviant for the pitch task
but not for the risetime AXB task, possibly suggesting an independent specific
deficit in rapid processing for these three children. However, TOJ, the other rapid
processing measure, was not deviant in these same three dyslexic children.
DISCUSSION
Dyslexic children as a group showed significant deficits in four measures of
auditory processing, comprising rise time AXB, rise time 2IFC, duration detection
and temporal order judgement. For the rise time tasks, individual differences
strongly predicted phonological skills, even after controlling for age, verbal and
nonverbal IQ and vocabulary. Individual differences in rise time processing were
}
Ramus (2003) used a stringent criterion to determine deviance for auditory processing
studies, whereby the control mean and s.d. was first used to determine the 5th percentile
for the normally developing controls (using the formula x+1.65 s.d.). Any controls outside
this cut-off were excluded. The control mean and s.d. was then recalculated, and the
criterion reapplied. Dyslexic individuals scoring above this latter criterion were then
assumed to be deviant.
Copyright # 2004 John Wiley & Sons, Ltd.
DYSLEXIA 10: 215–233 (2004)
Auditory Processing Skills in Dyslexia
229
also significant predictors of progress in reading and spelling, although
the relationships found were not as strong as those reported by Goswami et al.
(2002). However, the current study controlled for verbal as well as non-verbal I.Q.
The amounts of unique variance in phonological skills accounted for by the rise
time tasks was particularly impressive given that our groups were matched for
verbal I.Q. and vocabulary. The duration detection measure showed similar
predictive patterns to the rise time tasks for literacy, but not for phonological
awareness. The group difference found in TOJ did not predict progress in
phonological skills or literacy. The rise time findings support our earlier report of
a dyslexic deficit in AM-driven beat detection using a categorisation task
(Goswami et al., 2002).
The consistent relationships found for processing amplitude envelope rise
times may suggest that the accurate detection of supra-segmental cues are more
important for the development of phonological representations and consequently
literacy than the detection of rapid or transient cues (see also Foxton et al., 2003;
Rocheron, Lorenzi, Fullgrabe, & Dumont, 2002; Talcott et al., 2000; note also that
recent evidence suggests that dyslexic children may be more sensitive to withincategory phoneme distinctions than controls, see Serniclaes, van Heghe, Mousty,
Carre, & Sprenger-Charolles, 2004). This may seem counter-intuitive given the
documented importance of phonemic awareness skills and learning grapheme–
phoneme correspondences for progress in reading and spelling. However, this
view becomes less counter-intuitive when considered within a developmental
framework. In the development of phonological awareness, awareness of ‘large’
units (syllables, onsets, rimes) develops before awareness of segmental units such
as phonemes. If the lexical system is set up initially on the basis of information
about prosody, onsets, duration and vocalic nuclei (as implied by studies of
language acquisition in infancy, e.g. Juszcyck, Goodman, & Bowman, 1999;
Trehub, Thorpe, & Morrongiello, 1987; Plunkett & Schafer, 2001), then
impairments in children’s integration of information across longer temporal
windows becomes theoretically important for understanding linguistic disorders
such as dyslexia. Heil (2003) has suggested that each onset envelope is
represented by a unique spatio-temporal pattern of neuronal responses. It
follows that such neuronal responses may be immature or even impaired in
dyslexia.
Another potential link between amplitude envelope onsets and phonological
representation is also of interest. Rise time detection may be critical for
identifying ‘perceptual centres’ (P-centres) in acoustic signals. P-centres are the
experienced moments in time at which different speech (Morton, Marcus, &
Frankish, 1976) and musical (Gordon, 1987) sounds occur. They are determined
by the onsets of signals. P-centres in speech are associated with rapid increases of
mid band spectral energy, typically occurring around the onset of a vowel
(Marcus, 1981). If required to speak to a regular rhythm, speakers align the onsets
of their vowels, creating rhythmic patterns (e.g. if saying ‘street, eat’ aloud to a
rhythm, the vowel in ‘eat’ is timed with the vowel in ‘street’, even though the
vowel is at the beginning of the word ‘eat’ and near to the end of the word
‘street’). This means that speakers align vowel onsets rather than the physical
onset of articulation for each word (Marcus, 1981). This phenomena is also seen
with musical instruments: The beat of a plucked note comes earlier than that of a
bowed note (Vos & Rasch, 1981), and this affects timing when the instruments are
Copyright # 2004 John Wiley & Sons, Ltd.
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U. Richardson et al.
played (Rasch, 1979). P-centres may thus provide a non-speech-specific
mechanism for perceptually segmenting syllable onsets and rhymes.
If this were the case, then the accurate detection of P-centres would be
important for the quality of phonological representations developed by children
prior to the acquisition of reading. Phonological awareness develops in the
sequence syllable}onset/rime}phoneme across all languages so far studied,
with phoneme awareness largely dependent on literacy tuition (Goswami, 2003b,
for overview). Theoretically, therefore, deficits in the accurate perception of rise
time could affect the development of onset-rime representation, the most finegrained level of sub-syllabic representation attained prior to literacy. P-centres
have been shown to be important for speech rhythm in languages as diverse as
English, Spanish and Japanese (Hoequist, 1983). Deficits in rise time perception
should thus affect the development of high-quality phonological representations
across languages. We have recently shown that French dyslexic children, too,
exhibit a deficit in rise time processing (Muneaux, Ziegler, Truc, Thomson, &
Goswami, 2004). We are currently exploring the P-centres hypothesis in dyslexic
children learning to read Dutch, Greek and Finnish.
ACKNOWLEDGEMENTS
We would like to thank the head teacher, teachers and children of Fairley House
School, London, Panshanger Primary School and Applecroft Primary School,
Welwyn Garden City, England, for taking part in this study. We also thank Andy
Faulkner and Jill House for their help in preparing the digitised speech stimuli.
Support for this research was provided by an ESRC grant (RN 000 239084) to
Usha Goswami and by an Academy of Finland grant to Ulla Richardson.
Requests for reprints should be addressed to Usha Goswami, Faculty of
Education, Shaftesbury Rd, Cambridge CB2 2BX, UK.
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