Journal of Research in Reading, ISSN 0141-0423
Volume 29, Issue 3, 2006, pp 334–348
DOI: 10.1111/j.1467-9817.2006.00312.x
Auditory and motor rhythm awareness
in adults with dyslexia
Jennifer M. Thomson, Ben Fryer, James Maltby and
Usha Goswami
University of Cambridge
Children with developmental dyslexia appear to be insensitive to basic auditory cues
to speech rhythm and stress. For example, they experience difficulties in processing
duration and amplitude envelope onset cues. Here we explored the sensitivity of
adults with developmental dyslexia to the same cues. In addition, relations with
expressive and receptive rhythm tasks, such as tempi recognition and manual tapping
to a metronome, were explored. Our goal was to investigate whether the auditory
deficits seen in dyslexia are specific to cues to speech rhythm and stress, or are part
of a wider rhythmic awareness problem. A group of 19 undergraduate students with
dyslexia were compared with 20 age- and ability-matched controls. The findings
confirmed a relationship between auditory rhythm sensitivity and literacy in adults,
as well as showing an association with metronome inter-tap-interval variability.
Keywords: developmental dyslexia, motor skills, auditory processing, rhythm
Individuals with developmental dyslexia have a specific difficulty in the acquisition of
reading and spelling which cannot be accounted for by lack of educational opportunity,
additional learning difficulties or obvious sensory impairment. These specific learning
difficulties usually persist into adulthood. The difficulty in acquiring orthography–
phonology relations characteristic of dyslexia is usually thought to stem from the
presence of pervasive deficits in phonological awareness across languages. These deficits
are thought to be caused by impairments in establishing fully specified phonological
representations (Snowling, 2000). The underlying neural factors leading to these
characteristic difficulties in representing phonology are still under debate.
One logical precursor of these difficulties with phonology is a deficit in basic auditory
processing. Much research has looked at aspects of auditory processing thought to be
relevant to phonological specificity, for example temporal order judgement (Tallal,
1980), frequency discrimination (Amitay, Ahissar & Nelken, 2002), categorical
perception of phonemes and non-speech analogues (Brier et al., 2001; Serniclaes,
Sprenger-Charolles, Carre & Demonet, 2001) and backward masking (Rosen &
Manganari, 2001). Although group deficits are commonly found, the developmental
route to reading difficulty is unclear.
When initially forming phonological representations infants use prosodic cues and
statistical patterns (Kuhl, 2004) to help them segment the continuous stream of speech
they are exposed to. Sensitivity to speech rhythm will thus be of key importance in
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establishing phonological representations, and indeed the exaggerated prosody of
Motherese, or Infant-directed-speech emphasises these rhythms across languages
(Fernald, Taeschner, Dunn & Papoušek, 1989). Syllables are the most fundamental unit
of speech rhythm across languages and sensitivity to the syllabic properties of speech will
provide access to the segmental information within syllables.
Auditory perception is thus important to the establishment of phonological
representations; however evidence also points to the intimate relationship between
infants’ motor skills and phonological development. One example of motoric influence is
the mandibular oscillations during rhythmic babbling in infancy, which govern the basic
syllabic time frame of speech (MacNeilage & Davis, 1990). Kuhl and Meltzoff (1982)
have also shown how infants use articulatory knowledge when interpreting the auditory–
visual information presented in face-to-face interactions. Motor rhythm influences
language acquisition across modality; for example, Petitto, Holowka, Sergio, Levy and
Ostry (2004) have shown distinct rhythmic frequencies for babble-like hand activities in
signing babies. Petitto et al. (2004) argue for both a motoric and a linguistic element to
these movements.
Data such as this suggest a synergistic role for auditory and motor development as
young children establish phonological representations. Yet this interaction and its
implications for phonological and later literacy development has been relatively ignored
in dyslexia research. The most researched and also most controversial framework within
which motor deficits have been linked to dyslexia is the automaticity/cerebellar
hypothesis of Nicolson and Fawcett (Nicolson & Fawcett, 1990; Nicolson, Fawcett &
Dean, 2001). In this hypothesis dysfunction at the level of the cerebellum leads to
difficulties in skill automatisation. This is hypothesised to have direct effects on the
process of writing and spelling and indirectly to affect phonological awareness and
decoding (via effects on articulation). Evidence for this theory depends on group studies
in which dyslexic students show deficits in dual tasking and balance activities. However,
the hypothesis has been criticised at both theoretical and empirical levels. Theoretically,
the relevance of such a broad concept of ‘automaticity’ for a specific learning deficit like
dyslexia has been questioned. Empirically, subsequent studies have struggled to replicate
Nicolson et al.’s findings (Ramus, Pidgeon & Frith, 2003; van Daal & van der Leij, 1999;
Wimmer, Mayringer & Raberger, 1999), with Wimmer et al. attributing the failure to
replicate to a possible confound of dyslexia and ADHD in the Nicolson et al. studies.
Nevertheless, there is a long history of studies reporting high comorbidity between
reading difficulties and mild motor difficulties such as ‘clumsiness’. Motor difficulties
can, however, cover a wide range of skills, which to date have not been investigated in
any systematic way in relationship to phonological processing. Some motor skills are also
likely to be more important for literacy than others. In this paper, we explore a possible
common link via rhythm.
The most extensive investigations to date of motoric rhythm skills in individuals with
dyslexia are those by Wolff et al. (Wolff, 2002; Wolff, Michel & Ovrut, 1990a; Wolff,
Michel, Ovrut & Drake, 1990b). In the most recent of these studies Wolff (2002)
examined adolescents’ abilities (age range 10–16) to finger tap in time to an isochronic
pacing metronome. It is well observed that when synchronising to a beat there is a
systematic tendency for tap responses to precede the signal by 20–80 ms (Aschersleben &
Prinz, 1995). Wolff reported anticipation times for dyslexic individuals two to three times
greater than for the control groups. They also had difficulties reproducing patterned
rhythms of tones separated by a sequence of long or short inter-tap-intervals (ITI). Wolff
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concluded that the study could not address the relevance of these findings for the ‘core
deficit’ of phonological processing in dyslexia, but suggested that one link might involve
the temporal organisation of speech prosody.
Rhythmic periodicity in speech is a crucial element of prosody, and is related to the
onsets of the vowels in stressed syllables. When deliberately speaking to a rhythm, a
crucial cue for timing speech output is the rate of change (rise time) of the amplitude
envelope onset (AEO) of the vowel. This cue, also called a ‘P-centre’ (perceptual centre),
essentially yields the perceptual ‘moment of occurrence’ of the syllable (Scott, 1998). It
is these moments of occurrence, rather than the onsets of the syllables per se, which need
to be timed in order for speech perception and production to be experienced as rhythmic.
Long onsets before the vowel (e.g. ‘skate’) move the P-centre temporally to the left; long
codas (e.g. ‘banks’) can move it to the right. In 2002 Goswami et al. demonstrated that
dyslexic children show a deficit in AEO rise time sensitivity. The children were given a
categorisation task in which amplitude modulating tones had to be categorised as either
having a ‘beat’ (i.e. short rise times) or ‘no beat’ (a long rise time). Dyslexic children
performed significantly more poorly on this task than their age-matched peers whilst
performance on this task predicted up to 25% of the variance in reading ability, even after
controlling for age and non-verbal intelligence quotient (IQ, n 5 73).
Goswami et al.’s finding has subsequently been replicated with another group of
English good and poor school-age readers (Richardson, Thomson, Scott & Goswami,
2004) as well as in a group of French good and poor school-age readers (Muneaux,
Ziegler, Truc, Thomson & Goswami, 2004). Because the perception of a beat does not
depend on a categorical distinction, the Richardson et al. study measured AEO sensitivity
using two new discrimination tasks. An AXB task was used to measure single rise time
ramp discrimination whilst a two-interval forced choice (2IFC) task used two-ramp
amplitude modulating strings. Both tasks revealed group differences between dyslexic
and control readers, with the single ramp task predicting up to 13% of unique variance in
reading (in this case, non-word reading). The study also extended its focus to other
speech rhythm parameters, finding that not all parameters were equally affected. For a
2IFC task requiring duration discrimination of the silent closure of a pseudo-word medial
stop, group differences and predictive relationships with literacy were found. In contrast,
an AXB tone intensity detection task yielded neither group differences nor predictive
relations.
All three of these studies (Goswami et al., 2002; Muneaux et al., 2004; Richardson
et al., 2004) found that dyslexics experience specific difficulties with rise time perception.
This finding suggests that a broader difficulty with P-centre timing may contribute to the
problems with motor and musical timing noted in some studies of dyslexic individuals. In
the study reported here our aim was to investigate auditory and motor rhythm
performance alongside phonological processing and literacy measures within the same
group of individuals, in order to test this P-centre hypothesis. Here a group of university
students with dyslexia were investigated. A prior study of university students (Pasquini,
Corriveau & Goswami, 2005) using a subset of the current tasks suggested that the
auditory AEO deficits seen in children with dyslexia persist into adulthood. The current
study allowed us to test the robustness of that finding and compare the relative predictive
power of AEO sensitivity with other parameters of auditory rhythm: duration and
intensity. Rather than use the pseudo-words of the Richardson et al. duration task, tone
stimuli were used here to provide greater equivalence to the AEO tasks. The 2IFC
intensity discrimination task was also made more sensitive, through a stimuli continuum
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containing smaller dB increments. The current study was also designed to examine the
motor skills of dyslexic adults. A parallel motor-rhythm study is in progress with a
school-age population in order to observe potential developmental differences (Thomson
& Goswami, 2005).
The key research questions explored in the current study are as follows:
1. Will the auditory rhythmic deficits characteristic of children with developmental
dyslexia be found in remediated adults?
2. How specific is the rhythm deficit in dyslexia? Will a deficit also be observed in
expressive and receptive rhythm tasks?
3. If rhythmic motor deficits are present for the dyslexic group, how closely (if at all) will
these be associated with AEO sensitivity and with literacy?
Methods
Participants
Nineteen dyslexic adults between the ages of 18 and 31 and twenty control participants
between the ages of 18 and 31, with no history of dyslexia, were recruited from four UK
universities. All individuals with developmental dyslexia, had been diagnosed by a
registered Educational Psychologist (EP) and were recruited via university learning
disability centres. Both groups contained six males.
A preliminary questionnaire was given to all participants assessing criteria for inclusion.
Participants were required to speak English as their first language and had to pass a short
hearing test using an audiometer. Individuals with additional learning disabilities, a history
of mental illness, epilepsy or any other neurological disorder were excluded.
Participant characteristics are shown in Table 1. Independent sample t-tests confirmed
that there was no difference in age, verbal IQ or performance IQ. Verbal and performance
IQ were measured using the Wechsler Abbreviated Scale of Intelligence (WASI;
Wechsler, 1999).1 Four subtests of the WASI were used to assess verbal (Vocabulary and
Similarities) and non-verbal (Block Design and Matrix Reasoning) intelligence. Untimed
single word reading and spelling were measured using the Wide Range Achievement Test
(WRAT-III; Wilkinson, 1993).
Tasks
Participants received a battery of psychometric, phonological, psychoacoustic and motor
tests lasting approximately 3 hours, with breaks as required.
Table 1. Mean participant characteristics.
N
Age (SD)
WRAT reading standard score (SD)
WRAT spelling standard score (SD)
Verbal IQ standard score (SD)
Non-verbal IQ standard score (SD)
Dyslexic
Control
19
22;3 (3;3)
96.95 (11.31)
101.11 (10.43)
123.79 (10.23)
117.00 (9.83)
20
22;3 (2;11)
110.10 (7.66)
117.55 (4.33)
128.80 (8.30)
121.70 (8.30)
t(1, 37)
0.00
4.27***
6.48***
1.67
1.62
Notes: IQ, intelligence quotient; ***po.001.
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Experimental phonological processing tasks.
Phoneme deletion: This was an abbreviated version of a similar deletion task designed by
McDougall, Hulme, Ellis and Monk (1994). The experimenter orally presented eighteen
pseudo-words (including three practice words), followed by a target phoneme contained
in the pseudo-word. Participants were asked to produce the pseudo-word omitting the
target phoneme (e.g. Say ‘bice’ without the ‘b’; Say ‘splow’ without the ‘p’). Scores on
this task were out of a possible 15 points.
Rapid automatised naming: The rapid automatised naming (RAN) measure was drawn
from the Phonological Assessment Battery (Frederickson, 1996). Participants were
presented with an array of fifty pictures of five common objects (door, chair, hat, ball,
table) and were asked to name the objects from left to right as quickly as possible. This
was followed by a second trial in which participants named a different fifty-item array of
the same five pictures. The final score on this measure was the mean of the two trial times
(in seconds), disregarding accuracy.
Digit span: the Wechsler Adult Intelligence Scale (WAIS-IIIUK; Wechsler, 1998)
forward digit span task was used to assess auditory short-term memory. Raw scores on
this measure were the mean of the number of correct answers, out of a possible 14.
Auditory processing tasks. With the exception of the audiometer screening, all auditory
tasks were presented on a laptop with headphones. The tasks were presented using the
Dinosaur program created by Dorothy Bishop at Oxford University. The computer
presented pairs of sounds in an adaptive 2IFC format, with a 500 ms interstimulus
interval. A maximum of 40 trials was presented and all trials were accompanied by online
feedback. The point at which the subject gave correct responses 75% of the time was
adaptively determined by the more virulent form of PEST (Parameter Settings by
Sequential Estimation; Findlay, 1978). Scores on these measures represent the 75%
correct threshold over the last four reversals.
Audiometer screening: All participants were required to pass an audiometer-hearing
test given at the 20 dB HL. Tones were presented by the audiometer in either the right or
left ear at five frequencies (0.25, 0.50, 1, 2, 4 and 8 kHz).
Intensity discrimination: In the intensity discrimination task, the dinosaur program
presented pairs of 50 ms, 1 kHz pure tones. Each pair of tones included a 73 dB standard
tone and a second tone that was drawn adaptively from a stimulus set of 31 pure tones
that ranged in loudness from 73 to 81.1 dB, with 0.27 dB between each step. Participants
were asked to identify which of the dinosaurs made a louder sound. This measure and the
duration discrimination task below were modelled upon the perception tasks used by Ivry
and Keele (1989).
Duration discrimination: A continuum of 31 stimuli was created using pure tones. The
stimuli ranged in duration from 400 to 640 ms, with 8 ms between each step. Each pure
tone was presented at 1000 Hz and the duration of the standard tone was 400 ms.
Participants were presented with pairs of tones and were asked to identify the dinosaur
that made the longest sound.
AEO rise time (2-ramp task): In this task, 40 stimuli were created from 500 Hz
sinusoidal carriers, which were amplitude-modulated at 0.7 Hz and had a depth of 50%.
Each stimuli was 2.5 cycles long (3570 ms). The amplitude modulation envelope was a
modified square wave, with a fixed 350 ms fall time, and a rise time that varied
logarithmically from 15 to 300 ms. The 300 ms rise time tone was the standard sound,
which was included in every pair of stimuli. Participants were instructed to identify the
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dinosaur that made the sound with a sharper beat. This task is also described in
Richardson et al. (2004).
AEO rise time (1-ramp task): In order to also investigate rise time discrimination at an
even simpler level, a task with single-modulation stimuli was administered. In this task,
participants heard pairs of modulated 500 Hz pure tones. One of the tones in each pair
was always the standard tone, which had a 300 ms linear rise time envelope, 450 ms
steady state and 50 ms linear fall time (total duration 5 800 ms). The 40 stimuli from
which the comparison tones were drawn had a constant total duration of 800 ms and
linear fall time of 50 ms, but were preceded by linear rise time envelopes that varied
logarithmically from 15 to 300 ms. Participants were instructed to identify the dinosaur
that made the sound that was sharpest at the beginning.
Rhythm tasks.
Receptive rhythm: Tempi discrimination: Using the dinosaur program interface this task
required a decision from participants as to which string of regular tempo sounds had a
larger inter-stimulus-interval (ISI), and thus sounded slower. A continuum of thirty sound
strings was created and each string contained nine 40 ms sine tones. The standard tone
string had ISIs of 210 ms and successive stimuli had ISIs increasing at 1 ms intervals
(range 210–240 ms).
Expressive rhythm: Metronome: This task was modelled on work by Wolff and
colleagues (Wolff, 2002; Wolff et al., 1990b) and assesses rhythmic motor ability in
paced (where the metronome beat is audible) and unpaced (no audible beat) conditions.
Presentations software (Version 0.92, www.neuro-bs.com) was used to present 10 ms
pure tone beats at rates of 1.5, 2 and 2.5 Hz. Participants were instructed to tap along to
the rhythm they heard with the left hand mouse button and to continue tapping through
the silence at the rate of the last rhythm they heard. There was a 30-second practice block
at the beginning of the task with 10 seconds each of 2 Hz paced, 2 Hz unpaced and 1.5 Hz
paced rhythm. Each metronome speed was then presented for 20 seconds (paced
condition) followed by 20 seconds of silence (unpaced condition) in the following order:
2 Hz paced, 2 Hz unpaced, 2.5 Hz paced, 2.5 Hz unpaced, 1.5 Hz paced 1.5 Hz unpaced.
The response count, inter-tap interval and time between expected and actual tap were
recorded at 1 ms resolution.
Motor task.
Pegboard: The Purdue Pegboard Battery (Tiffin, 1999) was used to measure motor skill
in both hands. This task does not require a rhythmic component, thus enabling a
distinction between basic motor co-ordination and rhythmic motor activity in the
metronome task. The pegboard has two rows of 30 holes. Participants were asked to place
pegs of 1 mm diameter and 25 mm length from a bowl at the top of the pegboard and
place them in the row of holes indicated by the tester. Following a series of practice trials
participants were given 30 seconds to place as many pegs as possible, firstly with their
dominant hand, then non-dominant hand and finally both hands together. The score
reported was the number of pegs placed for each respective condition.
Procedure
Testing was administered one-to-one, in quiet rooms by the authors B.F. and J.M. Tasks
were administered in a fixed order, which was reversed for half the dyslexics and half the
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Table 2. Mean performances on phonological tasks.
Phoneme deletion, maximum 5 15 (SD)
Phab RAN, seconds (SD)
Digit span, maximum 5 14 (SD)
Dyslexic
Control
10.47 (2.27)
33.79 (5.43)
6.17 (1.38)
13.15 (1.66)
30.30 (5.14)
7.75 (1.25)
t(1, 37)
4.22***
2.06*
3.71**
Note: *po.05, **po.01, ***po.001.
non-dyslexics in order to control for order effects. Dyslexics and controls were also
alternated to control for changes in administration style and both testers assessed equal
numbers of dyslexic and control participants.
Results
Phonological tasks
The means and standard deviations for performance on the phonological measures are
shown in Table 2. Independent sample t-tests to look at group effects were carried out
taking each of the phonological measures as a dependent variable. Significant group
differences were found for all measures, the dyslexic group showing poorer performance
(for t- and significance values, see Table 2).
Auditory processing tasks
The means and standard deviations for performance on the auditory processing measures
are shown in Table 3. Independent sample t-tests were used to explore group differences.
Significant effects were found across all auditory processing measures (for t- and
significance values see Table 3). The threshold measures for these tasks represent the
smallest interval at which an individual can distinguish the standard stimulus from
another on the continuum with 75% accuracy. The significantly higher mean threshold
values for the dyslexic individuals thus indicate that a greater difference is required
between sounds in order for the distinction to be reliably heard.
Rhythm tasks
Tempi discrimination: Group threshold means for this task are shown in Table 4. There
were no significant group differences in performance on this task.
Table 3. Mean performances on auditory tasks.
Rise time 1 ramp threshold, standard 5 300 ms (SD)
Range of noticeable difference (ms)
Rise time 2 ramp threshold, standard 5 300 ms (SD)
Range of noticeable difference (ms)
Intensity threshold, standard 5 73 dB SPL (SD)
Range of noticeable difference (dB)
Duration threshold, standard 5 400 ms (SD)
Range of noticeable difference (ms)
Dyslexic
Control
t(1, 37)
117.54 (70.22)
40.7–277.8
119.30 (81.79)
32.3–257.3
76.02 (1.21)
73.81–78.4
446.40 (14.8)
424–472
173.91 (43.73)
94.8–277.8
189.20 (47.87)
110.5–277.8
75.32 (0.86)
73.81–76.78
430.40 (16.16)
408–456
2.55*
2.77**
2.06*
3.10**
Note: *po.05, **po.01.
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Table 4. Mean performances on rhythm tasks: tempi and metronome anticipation time.
Tempi threshold, standard ISI 5 210 ms (SD)
Range of noticeable ISI difference (ms)
Metronome, mean anticipation time (ms)
1.5 Hz (SD)
2 Hz (SD)
2.5 Hz (SD)
Dyslexic
Control
216.6 (3.54)
211–224
215.9 (3.22)
211–225
102.13 (61.69)
14.79 (46.16)
4.41 (66.87)
123.51 (92.88)
2.58 (81.29)
20.77 (84.69)
Note: ISI, inter-stimulus-interval.
Metronome: For the metronome analysis, three measures were investigated.
Mean difference scores for actual versus expected ITIs. For both the paced and
unpaced conditions, in order to determine whether the time interval between the subject’s
responses was similar to the time interval between the metronome beeps, the ITI was
calculated for all three rhythm speeds (1.5, 2, 2.5 Hz). For each individual the middle 15
ITIs were analysed and outlying values removed. From raw ITIs, the absolute difference
between the target ITI and the individual’s mean ITI was calculated (e.g. for 2 Hz a mean
ITI of 450 would yield an ITI difference score of |500 450 ms| 5 50 ms). Mean
performances are displayed in Table 5. A 2 (Group: dyslexic, control) 2 (paced,
unpaced) 3 (tapping rate: 1.5, 2 and 5 Hz) repeated measures analysis of variance
(ANOVA) was carried out which yielded a main effect of rate, F(2, 60) 5 17.39, po.001,
a main effect of pace, F(1, 30) 5 87.33, po.001, with no main effect of group, F(1, 30)
5 0.62, p 5 .44. Across both groups, a slower metronome pace resulted in greater ITI
difference scores. ITI difference scores were greater for the unpaced condition compared
with the paced condition. There was an interaction between rate and pace,
F(2, 60) 5 13.29, po.001, but no interactions between pace and group or rate and
group. Post-hoc Newman–Keuls tests showed that the rate–pace interaction arose because
the effect of rate was significant for the unpaced condition only (po.05).
Inter-subject ITI variability. This variable characterised an individual’s internal
consistency of tapping rate, independent of whether or not this was actually the right rate
per se. ITI inter-subject variability was measured by calculating the standard deviation of
each participant’s paced and unpaced ITI scores. As with the difference scores, only the
Table 5. Mean performances on rhythm tasks: metronome ITI scores.
Dyslexic
Paced
Control
Unpaced
Paced
Unpaced
Metronome, ITI difference scores (ms)
1.5 Hz (SD)
4.30 (3.98)
2 Hz (SD)
3.81 (3.89)
2.5 Hz (SD)
2.94 (3.92)
45.99 (35.49)
32.79 (23.99)
20.65 (19.41)
3.47 (1.81)
2.82 (1.96)
2.27 (1.69)
47.77 (32.10)
20.05 (19.99)
14.76 (11.57)
Metronome, ITI variability (ms)
1.5 Hz (SD)
44.07 (20.72)
2 Hz (SD)
28.89 (16.92)
2.5 Hz (SD)
23.69 (7.52)
40.77 (20.12)
43.13 (40.65)
31.62 (18.19)
33.71 (13.19)
22.54 (6.25)
22.40 (6.80)
35.22 (12.17)
24.19 (6.91)
23.40 (7.28)
Note: ITI, inter-tap-interval.
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Table 6. Mean number of rows completed inserted in 30 seconds for pegboard.
Dominant hand (SD)
Non-dominant hand (SD)
Both hands (SD)
Dyslexic
Control
14.21 (1.55)
13.89 (1.85)
11.47 (1.71)
15.6 (2.16)
13.55 (1.85)
12.1 (1.55)
middle 15 beats were analysed. Mean performances are shown in Table 5. A 2 (Group:
dyslexic, control) 2 (paced, unpaced) 3 (tapping rate: 1.5, 2 and 2.5 Hz) repeated
measures ANOVA yielded a significant main effect of rate, F(2, 60) 5 22.42, po.001, no
main effect of pace, F(1, 30) 5 2.19, p 5 .15 and an effect of group significant at the .05
level, F(1, 30) 5 4.07, p 5 .05. No interactions were statistically significant. Across both
groups, a slower metronome pace resulted in greater ITI variability scores. Post-hoc
Newman–Keuls tests to investigate the group effect found that significant differences
between groups were present for the 1.5 and 2 Hz paced conditions, as well as the 2 Hz
unpaced condition (po.05), the dyslexic group exhibiting more ITI variability.
Anticipation time. The extent to which each individual anticipated the metronome beat
was also measured for the paced condition. Mean anticipation time scores (standard
deviations) for each tapping rate are displayed in Table 4. A repeated measure ANOVA
with group (dyslexic, control) as between-subjects factor and rate (1.5, 2 and 2.5 Hz) as
the repeated measure found a main effect of rate, F(2, 34) 5 67.53, po.001 but no
significant main effect of group, F(1, 35) 5 0.14, p 5 .71 and no interaction.
Motor task
Mean scores for the pegboard task are shown in Table 6. A 2 (Group: dyslexic,
control) 3 (Hand: dominant, non-dominant, both) ANOVA was conducted with
number of rows completed as the dependent variable. A main effect of hand was found,
(F(2, 36) 5 66.59, po.001), with most rows of pegs completed for the dominant hand and
least in the both-hand condition. There was no main effect of group, F(1, 37) 5 1.59,
p 5 .22. The interaction between hand and group approached significance,
F(2, 36) 5 3.01, p 5 .06. Post-hoc Newman–Keuls tests looking at group effects for
each hand condition, respectively, showed that the difference between groups was
significant for the dominant hand condition (po.05), although not for the other two
conditions.
Relationships between auditory, motor and literacy skills
Partial correlations controlling for IQ were calculated to examine relationships between
measures of literacy, phonology, auditory and motor skills across all participants (see
Table 7, zero order correlations also shown). Given the large number of metronome
variables calculated, only those yielding significant group differences were included in
the matrices (paced and unpaced ITI variability).
Controlling for IQ, some significant correlations were observed between the auditory
and motor measures of rhythm. Metronome ITI variability in the unpaced 2 Hz condition
was related to the AEO 2-ramp task as well as digit span (a phonological measure).
Metronome ITI variability in the paced 2 Hz condition was correlated with reading. As
expected, auditory rhythmic measures were related to literacy. The AEO 1-ramp task and
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Spell
PhonDel
RAN
DigitSp
AEO 1 ramp
AEO 2 ramps
Duration
Intensity
Tempi
Met-p 2
Met-p 1.5
Met-up 2
Pegd
.62
.43**
.10
.18
.54**
.26
.39*
.04
.21
.53**
.26
.6
.03
***
.60***
.20
.40*
.44**
.16
.34*
.07
.18
.33p 5 .05
.34*
.05
.14
.55
***
2. Spell
.43**
.60***
.38*
.09
.02
.24
.14
.24
.33*
.23
.17
.30
.53**
.48**
.23
.35*
.03
.41*
.23
.19
.04
.22
.09
.02
.10
.35*
.24
.39*
.00
.29
.05
.03
.13
.50**
.36*
.10
.35*
.57***
.44**
.44**
.02
.01
.07
.28
.18
.30
.11
.42
.34*
.22
.11
.16
*
3. PhonDel 4. RAN 5. DigitSp 6. AEO 1
.28
.15
.02
.34
.34*
.64***
.20
34*
.33*
.13
.05
.08
.27
7. AEO 2
.15
.20
.37*
.21
.22
.15
.38*
.32
.03
.07
.03
.08
.26
.13
.07
.10
.31
.28
.04
.15
.19
.38*
.25
.08
.10
.13
.23
.04
.05
.14
.28
.24
.22
.28
.07
.15
.07
.22
.11
.46**
.43*
.02
.52**
.29
.19
.14
.01
.15
.30
.36*
.05
.25
.41*
.03
.15
.32
.23
.15
.07
.04
.26
.19
.04
.08
.44**
.23
.03
.03
.22
.21
.50**
.31
.67***
.21
.30
.06
.42*
.41*
.02
.16
.21
.11
.38*
.14
.22
.16
.29
.14
.03
.04
.24
8. Duration 9. Intensity 10. Tempi 11. Met-p 2 12. Met-p 1.5 13. Met-up 2 14. Peg
Notes: Read, WRAT reading; Spell, WRAT spelling; PhonDel, Phoneme deletion; RAN, rapid automatised naming; DigitSp, WAIS digit span; Met-p 1.5/2, Metronome ITI
variability paced 1.5/2 Hz; Met-up 2, Metronome ITI variability unpaced 2 Hz; Peg, Mean pegboard score: dominant hand.
*
po.05, **po.01, ***po.001.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
1. Read
Table 7. Partial correlations between selected motor, auditory, phonological and literacy measures (all participants), controlling for IQ (top right) and zero order correlations
(bottom left).
RHYTHM SENSITIVITY AND DYSLEXIA
343
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THOMSON, FRYER, MALTBY and GOSWAMI
Table 8. Fixed order multiple regressions with literacy measures as dependent variables and rhythm/
auditory measures as independent variables.
Step
Step
Step
Step
Step
Step
Step
Step
1:
2:
3:
4:
4:
4:
4:
4:
Age
Non-verbal IQ
Verbal IQ
AEO 1 ramp
AEO 2 ramp
Duration
Intensity
ITI var. 2 Hz paced
DV reading
DV spelling
DV phoneme deletion
R2 change
R2 change
R2 change
0.02
0.11
0.09
0.11*
0.00
0.14*
0.02
0.03
0.00
0.00
0.14*
0.20**
0.03
0.11*
0.00
0.01
0.00
0.21**
0.01
0.08
0.01
0.00
0.01
0.07
Notes: IQ, intelligence quotient; ITI, inter-tap-interval; AEO, amplitude envelope onset.
*
po.05, **po.01, ***po.001.
duration tasks correlated significantly with reading ability, whilst the former also
correlated with spelling ability. There were also significant associations between the AEO
2-ramp task and digit span, as well as intensity discrimination and RAN. When IQ was
not controlled, correlations were also present between 1.5 Hz ITI variability and spelling,
phoneme deletion and AEO 2-ramp performance.
To examine the predictive strength of the relationships between rhythm, auditory
processing and literacy a series of fixed-order multiple regressions were carried out. For
each regression, the Cook’s distance was calculated. No data points had Cook’s distance
scores above 1.0 and so no participants were excluded from the regressions (Tabachnik &
Fidell, 2001). Table 8 shows that only AEO single-ramp and duration discrimination
tasks accounted for statistically significant amounts of the variance in reading and
spelling after controlling for age, non-verbal and verbal IQ. This parallels typical results
with dyslexic children.
Discussion
This study set out to answer three main questions. The first of these was whether the
auditory rhythmic deficits characteristic of children with developmental dyslexia would
also characterise remediated adults. Significant group differences were indeed found
between the dyslexic and control groups for our two AEO rise time measures as well as
the measure of duration discrimination, replicating our previous findings with children
(Goswami et al., 2002; Muneaux et al., 2004; Richardson et al., 2004). Performance in
both the AEO 1-ramp and duration discrimination tasks predicted variance in reading and
spelling, with the AEO 1-ramp task predicting up to 20% of the variance in spelling
performance. A significant group difference was also found between groups for the
intensity task, which was not found in the Richardson et al. (2004) study. The dB range of
the task used here was smaller (current study dB range 5 8.1; Richardson et al. 5 29.25)
and so the greater difficulty of the task may have led to group differences being observed.
Rise time is essentially a change in intensity as a function of time and so similar
performance in tasks measuring rise time and intensity sensitivity is not unexpected.
However, the more dynamic nature of rise time appears to be a stronger predictor of
literacy skills than intensity discrimination per se in this study.
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Our second research question concerned the specificity of rhythm deficits in dyslexia
and whether these would be observed in both expressive and receptive motor rhythm
tasks. The findings showed that the only rhythm measure to yield group differences was
within-individual variability of ITIs on the metronome task, for both paced and unpaced
conditions. This is a novel finding. Wolff’s 2002 study featuring single finger metronome
tapping did not report ITI variability statistics. Wolff et al. (1990b) did investigate ITI
variability in a bimanual tapping task; however no group differences between dyslexic
and non-dyslexic individuals were found in the paced tapping tasks analogous to those
used here. Differences were only found with more complex asymmetric tapping
conditions. A possible procedural reason for the difference in findings could be that in the
Wolff et al. study participants had a 15-second ‘just listening’ period before motorically
pacing to the beat, which may have reduced overall variability rates and between-group
effects. Further investigation is needed to test this possibility.
Two of the three significant group differences for ITI variability were found at the 2 Hz
tapping rate, equivalent to a slow spoken syllable rate (Morgan & Fosler-Lussier, 1998).
However, as this was also the first tapping rate presented in the metronome task, it will be
important for future studies to establish whether tapping rate per se is critical to the group
differences, or whether performance factors related to the first phase of the task are
playing a role. Task phase cannot be the whole explanation however, as group differences
were also present at the last-presented rate, 1.5 Hz.
Wolff (2002) reported a greater anticipation time for adolescent dyslexics when
attempting to synchronise to a metronome beat. This finding was not replicated here, with
no significant group differences in anticipation time present at any tapping rate. These
results could suggest a developmental effect, with the increased anticipation times
reported in younger dyslexics reducing by adulthood. Referring again to Wolff’s study of
bimanual tapping (Wolff, 1990b), whilst the adult dyslexic group did not differ from
controls in alternating tapping and tapping in unison, a group of adolescent dyslexics
were significantly poorer than their peers in the alternating tapping task. Studies currently
ongoing in our lab are investigating the same metronome task with dyslexic children.
Alternatively, the absence of anticipation effects may have been due to our use of a
computer mouse to collect tapping response times, as opposed to the copper plate used
by Wolff. Although the inter-tap timing accuracy offered by the computer mouse in
concert with stimulus presentation software is very precise, use of a mouse will add a
consistent, yet moderate amount to response times (Plant, Hammond & Whitehouse,
2003). Possibly, the anticipation effects in this study were diminished by our use of the
mouse.
Group differences in tempi perception were also not found in this study. This is an
interesting finding given that group differences were present for the duration
discrimination task; altering a tone-string tempo in effect changes the perceived duration
of the string. However, as the strings consisted of only five simple tones, the task may
have been too easy for adults. Current data collection with children is exploring whether
younger individuals with dyslexia can detect the tempo of strings of tones.
The final question asked in this study was whether rhythmic motor deficits found in
the dyslexic group would be associated with AEO sensitivity and literacy. Strong
associations were found; however the overall pattern of relationships across groups was
complex. Importantly, ITI variability in the 2 Hz unpaced condition was highly correlated
with AEO 2-ramp discrimination performance. This may suggest that those adults who
have the most difficulty in generating an internally consistent rhythm are also those adults
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THOMSON, FRYER, MALTBY and GOSWAMI
who find it difficult to detect the primary cue for rhythmic timing (i.e. P-centres) in
speech. ITI variability in the paced conditions was not correlated with auditory measures,
but was strongly correlated to reading ability and digit span. While the link to literacy
was predicted theoretically, a link with phonological memory was not. This latter
relationship could reflect the need to keep track of the external rhythm in working
memory.
In terms of links between AEO sensitivity and literacy, AEO 1-ramp performance was
predictive of reading, spelling and phonological awareness, whilst the AEO 2-ramp task,
which correlated with rhythmic measures, was not. These findings suggest that sensitivity
to auditory cues to speech rhythm and prosody are still linked to reading in compensated
dyslexic individuals. However, there is no clear association between general rhythmic
ability and auditory processing, phonological processing and reading. It will be important
to use the same tasks with younger dyslexic individuals to see, for example, if interrelationships are present at earlier developmental stages.
Finally, the finding of a group difference in dominant hand pegboard performance was
unexpected. The subsequent lack of association between pegboard performance and the
metronome variables makes it unlikely that rhythmic fluency was integral to pegboard
speed. To investigate whether pegboard scores correlated with any of the other
metronome variables not included in Table 7, a further set of partial correlations
controlling for IQ was calculated. This analysis yielded no significant relationships
between any of the pegboard or metronome variables. Pegboard performance was
correlated only with digit span, a measure of phonological short-term memory (see Table
7). The reasons for this are unclear, but may reflect a working memory or executive
component to keeping track of one’s performance with the pegs.
In summary, the data here suggest that an insensitivity to AEO cues persists into
adulthood for dyslexic individuals. The ability to distinguish between more or less salient
auditory beats (i.e. sounds with shorter/longer onset rise times) is related to reading
ability even in adulthood. In speech, a syllable’s duration can also affect its salience, and
links between duration discrimination and reading and spelling were indeed found for the
adults tested here (see also Richardson et al., 2003, 2004). An insensitivity to the auditory
rhythmic cues of speech could be the result of early motor difficulties in producing
actions/sounds with differential rates of onset/degrees of salience. Alternatively, it is easy
to imagine that an auditory perceptual difficulty in processing rhythm cues could result in
associated difficulties for skills relying on this ability, e.g. tapping in time to a rhythmic
beat. Perception and production of rhythm are intimately related. There was some
evidence that rhythmic auditory and motor skills remain coupled and linked to literacy
skill, even in adulthood. Longitudinal studies beginning in infancy or early childhood are
now required to understand dynamic interactions between auditory and motor skills in
development and potential effects upon literacy acquisition. Such awareness could
greatly aid early intervention and diagnosis of developmental dyslexia.
Acknowledgements
We would like to thank the staff and students of the participating universities who gave
their time to this project, especially Sarah Slater of the Disability Resource Centre,
University of Cambridge, who was particularly helpful with volunteer recruitment.
Thanks also to Elizabeth Pasquini and Kathleen Corriveau for valuable methodological
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347
advice and comments. This study was made possible through funding from the Economic
and Social Research Council (ESRC), grant RES-000-23-0475, awarded to Usha
Goswami.
Note
1. The WASI was not administered to nine dyslexic participants who had recently been assessed by their EP or
to those who intended on being reassessed in the following months. This removed any confounding practice
effects and prevented interference with future assessment. In these cases IQ scores were taken from the most
recent dyslexia report conducted by the EP. All control participants received all four subtests of the WASI.
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Received 21 December 2005; revised version received 11 April 2006.
Address for correspondence: Jennifer M. Thomson, Centre for Neuroscience in
Education, Faculty of Education, University of Cambridge, 184 Hills Road, Cambridge
CB2 2PQ, UK. E-mail: [email protected]
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