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Rhythm and Syntax Processing in School-Age Children
Yune S. Lee, Sanghoon Ahn,
and Rachael Frush Holt
The Ohio State University
E. Glenn Schellenberg
University of Toronto Mississauga
Scholars debate whether musical and linguistic abilities are associated or independent. In the present
study, we examined whether musical rhythm skills predict receptive grammar proficiency in childhood.
In Experiment 1, 7- to 17-year-old children (N!68) were tested on their grammar and rhythm abilities.
In the grammar-comprehension task, children heard short sentences with subject-relative (e.g., “Boys that
help girls are nice”) or object-relative (e.g., “Boys that girls help are nice”) clauses, and determined the
gender of the individual performing the action. In the rhythm-discrimination test, children heard two
short rhythmic sequences on each trial and decided if they were the same or different. Children with
better performance on the rhythm task exhibited higher scores on the grammar test, even after holding
constant age, gender, music training, and maternal education. In Experiment 2, we replicated this finding
with another group of same-age children (N!96) while further controlling for working memory. Our
data reveal, for the first time, an association between receptive grammar and rhythm perception in
typically developing children. This finding is consistent with the view that music and language share
neural resources for rule-based temporal processing.
Keywords: rhythm, syntax, music, language, children
Behavioral studies often report associations between music and
speech. In childhood, music aptitude is correlated with phonolog-
ical (Anvari, Trainor, Woodside, & Levy, 2002; Moritz, Yampol-
sky, Papadelis, Thomson, & Wolf, 2013) and pronunciation (Mi-
lovanov et al., 2009) skills. Although one study reported that pitch
perception was correlated positively with phonological awareness
(Anvari et al., 2002), musical rhythm skills (e.g., rhythm discrim-
ination or reproduction) are more often predictive of speech per-
ception (Carr, White-Schwoch, Tierney, Strait, & Kraus, 2014;
Moritz et al., 2013; Ozernov-Palchik, Wolf, & Patel, 2018; Poli-
timou, Dalla Bella, Farrugia, & Franco, 2019; Swaminathan &
Schellenberg, 2017, 2019). For example, a recent study found that
rhythm perception and production best accounted for phonological
awareness in 4-year-olds (Politimou et al., 2019). By contrast,
impaired rhythm abilities are associated with deficits in phonolog-
ical awareness. For example, children with SLI (specific language
impairment) or developmental dyslexia exhibit poor performance
on tasks that require them to detect rhythmic timing or amplitude
rise— cues that are essential to speech perception (Corriveau,
Pasquini, & Goswami, 2007; Corriveau & Goswami, 2009; Gos-
wami, Gerson, & Astruc, 2010; Huss, Verney, Fosker, Mead, &
Goswami, 2011).
In some instances, children assigned randomly to music lessons
exhibit enhanced performance on auditory tasks that require dis-
crimination and detection of subtle phonetic features in speech
(Degé & Schwarzer, 2011; Flaugnacco et al., 2015; François,
Grau-Sánchez, Duarte, & Rodriguez-Fornells, 2015; Moreno et al.,
2009). For example, children who received two years of music
classes performed better on a test of speech-segmentation ability
than other children who received two years of painting class
(François, Chobert, Besson, & Schön, 2013). Similarly, children
with dyslexia who received seven months of music training out-
performed their counterparts who received painting training on
phonemic blending (i.e., hearing /c/-/a/-/t/ and producing “cat”) or
rhythm reproduction tasks (Flaugnacco et al., 2015). These find-
ings raise the possibility that music training causes improvements
in speech processing, as some scholars have theorized (Kraus &
Chandrasekaran, 2010; Patel, 2011). According to Patel (2011),
the particular characteristics of the music-learning process are
demanding but enjoyable, leading to enhanced listening skills that
transfer to speech perception. The perspective of Kraus is similar
but focused on encoding sound in the brainstem, which becomes
more faithful and accurate with music training, such that it en-
hances the perception of speech (Kraus & Chandrasekaran, 2010).
XYune S. Lee, Department of Speech and Hearing Science and
Chronic Brain Injury Program, The Ohio State University; XSanghoon
Ahn, Department of Neuroscience, The Ohio State University; XRachael
Frush Holt, Department of Speech and Hearing Science, The Ohio State
University; XE. Glenn Schellenberg, Department of Psychology, Uni-
versity of Toronto Mississauga.
We thank Jessica Grahn and Reyna Gordon for sharing materials for the
rhythm test. We also thank Ian Goldthwaite, Allison Byrer, Kate Corbeil,
Katherine Miller, Korrin Perry, Aiesha Polakampalli, Christina Roup,
Laura Wagner, Cynthia Clopper, and Kathryn Campbell-Kibler for their
support. Special thanks to the parents and children who participated in our
study. Data are available upon request.
Correspondence concerning this article should be addressed to Yune S.
Lee, who is now at School of Behavioral and Brain Sciences, The Uni-
versity of Texas at Dallas, 800 West Campbell Road, Richardson, TX
75080. E-mail: yunesang.lee@gmail.com
This document is copyrighted by the American Psychological Association or one of its allied publishers.
This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.
Developmental Psychology
© 2020 American Psychological Association 2020, Vol. 2, No. 999, 000
ISSN: 0012-1649 http://dx.doi.org/10.1037/dev0000969
1
Although both scholars focus on transfer from music to speech,
they also believe that enhanced speech perception has cascading
effects that positively influence language use more broadly (e.g.,
reading).
Despite numerous reports of associations between music and
speech perception (for review, see Schellenberg & Weiss, 2013),
only recently have scholars turned their attention to plausible
connections between musical ability and language skills beyond
simple listening (or acoustic) processes in childhood (Gordon,
Jacobs, Schuele, & McAuley, 2015; Gordon, Shivers, et al., 2015;
Politimou et al., 2019). For example, Gordon, Shivers, et al. (2015)
tested 6-year-old children and reported a positive association be-
tween rhythm-discrimination ability and expressive grammar (i.e.,
producing morpho-syntactically well-formed words/phrases). No-
tably, the association remained evident even after controlling for
IQ, musical experiences, and socioeconomic status, which sug-
gests that similar underlying mechanisms influence both rhythm
and expressive grammar.
For adults, some evidence points to interactions between rhythm
and syntactic processing when these processes operate in parallel
during language comprehension. For example, words that unfold
metrically over time (i.e., with a beat) facilitate comprehension of
sentences that are syntactically complex or ambiguous (Roncaglia-
Denissen, Schmidt-Kassow, & Kotz, 2013; Schmidt-Kassow &
Kotz, 2008). By contrast, processing of word sequences with
irregular rhythmic patterns is more effortful (Bohn, Knaus, Wiese,
& Domahs, 2013). Priming with external rhythmic cues (e.g.,
march music) also leads to enhanced performance on tests of
syntax (Bedoin, Brisseau, Molinier, Roch, & Tillmann, 2016;
Canette et al., 2020; Chern, Tillmann, Vaughan, & Gordon, 2018;
Kotz & Gunter, 2015; Przybylski et al., 2013).
In the present study, we tested school-age children. Our goal
was to examine the possibility of a connection between proficiency
on a task that measured receptive grammar, and the ability to
perceive, remember, and discriminate musical rhythms. Basic syn-
tactic abilities are acquired early in life (Corrêa, 1995; Kidd &
Bavin, 2002; Labelle, 1990), such that older, school-age children
tend to be fluent in commanding multiclausal sentences (Nippold,
2009). Nevertheless, syntactic skills continue to improve through-
out the adolescent period (Frizelle, Thompson, McDonald, &
Bishop, 2018; Hartshorne, Tenenbaum, & Pinker, 2018; Loban,
1976). Notably, in a recent study based on a large amount of data
(N"600,000), Hartshorne et al. (2018) estimated that grammar-
learning abilities improved until approximately 17 years of age.
Although syntactic competency is thought to remain stable
throughout adulthood (Chomsky, 2014; Herschensohn, 2009;
Nowak, Komarova, & Niyogi, 2001), there are individual differ-
ences in syntactic ability among adults (Da˛browska, 2012a, 2012b,
2018, 2019; Da˛browska & Street, 2006). In a recent study,
Da˛browska (2018) demonstrated that grammar competency among
adults depended on differences in IQ, education, and exposure to
print. There are similarly marked individual differences in chil-
dren’s syntactic ability (Nippold, 2009; Nippold, Mansfield, &
Billow, 2007; Spencer, Clegg, & Stackhouse, 2012). In the present
study, we held constant extraneous individual differences (i.e.,
confounding variables) to ensure that any observed associations
between rhythm and grammar were not artifacts. We hypothesized
that this association would emerge because central auditory pro-
cessing is required for rapid and efficient temporal analysis of
musical and linguistic structures.
To test this hypothesis, we administered short tests of rhythm
and grammar, which were tailored for testing outside of the labo-
ratory (i.e., in a children’s museum). In the rhythm test, children
compared pairs of rhythm sequences that required same/different
judgments. In the grammar test, children were asked to indicate the
gender of a noun that was linked to an “action” verb in a sentence
with either a subject- or object-relative embedded clause. For
example, consider the following two sentences, which comprise
the same six words:
“Kings that help queens are nice”
“Kings that queens help are nice”
Whereas the first sentence has an embedded clause that relates
to the subject of the action, the second sentence has an embedded
clause that relates to the object of the action (Kings in both
instances). Such object-relative (OR) clauses are syntactically
more complex than subject-relative (SR) clauses, a consequence of
the order (or temporal) rearrangement of the same words presented
serially. Half of these SR and OR sentences were further manip-
ulated in acoustic clarity by applying a vocoding-filter (Experi-
ment 1) or by adding multitalker babble (Experiment 2). The
clarity manipulation would allow us to explore a potential inter-
action between sensory (acoustic) and linguistic (syntactic) chal-
lenges (Wingfield, McCoy, Peelle, Tun, & Cox, 2006). Although
all of the degraded sentences were intelligible, such acoustic
manipulations could still render difficulty in syntactic access.
Experiment 1
The study protocol used here and in Experiment 2 was approved
by the Institutional Review Board at the Ohio State University
(IRB #: 2012B0213; Language studies in the labs in Life POD at
the Center of Science and Industry).
Method
A priori power analysis conducted with G
!
Power 3.1 (Faul,
Erdfelder, Buchner, & Lang, 2009) indicated that a sample of 63
participants was required to reach 85% certainty of detecting a
medium-sized association (f
2
!.15;Cohen, 1988) between rhythm
and grammar with six other variables held constant, #!.05. Our
goal was to ensure that the sample was at least this large, and our
arrangement with the museum did not allow for turning away
children after this goal was reached.
Participants. Ninety-eight native English-speaking children,
with reported normal speech, language, and hearing, were re-
cruited from the visitor population at a local museum. Only five
children were bilingual, and one was trilingual. The children
ranged in age from 7 to 17 years, which ensured marked individual
differences in grammar and rhythm skills. Parental consent and
child assent were obtained prior to the beginning of the experi-
ment. Some children (N!26) were subsequently excluded from
the sample for significantly below-chance (i.e., worse than guess-
ing) levels of performance on the grammar test (i.e., in any of 4
conditions), which likely arose due to misunderstanding directions
or swapping button responses. Another three children did not want
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2LEE, AHN, HOLT, AND SCHELLENBERG
to complete the task, and one child was excluded for concurrently
receiving speech therapy. Thus, the final sample comprised 68
children (35 girls), whose mean age was 11.3 years (SD !2.7).
We also measured demographic variables, including age, gen-
der, music training, and maternal education (as a proxy for socio-
economic status, or SES). Because these demographic variables
are known to be associated with children’s language skills (Barbu
et al., 2015; Hoff, 2003; Tabri, Chacra, & Pring, 2011), they served
as covariates when we examined whether musical-rhythm sensi-
tivity predicts receptive-grammar proficiency. Duration of music
training was calculated as the square root of total period of training
(i.e., total years), which was summed for children who had learned
more than one musical instrument, as in previous research (e.g.,
Swaminathan & Schellenberg, 2017). Lastly, maternal education
was measured on a 5-point scale (1 !high school diploma or less,
2!associate’s degree, 3 !bachelor’s degree, 4 !master’s
degree, and 5 !doctorate).
Stimuli. In the grammar test, stimuli comprised sentences
uttered by a native American-English speaking female. Ten “base”
sentences varied in syntax and acoustic clarity (Figure 1A). For the
syntactic manipulation, each of the sentences was center-
embedded with an SR clause or an OR clause. Sentences with SR
and OR clauses consisted of identical words, the only difference
being the position of two words in each sentence. Each sentence
also contained a male and a female noun, but only one of them
performed the action of the sentence (e.g., “hug,” Figure 1A). The
gender of the characters was counterbalanced, as was the presence
of SR and OR clauses. For the acoustic manipulation, sentences
were processed by a 15-channel vocoder that reduced spectral
details, hampering acoustic clarity. Although sound quality was
substantially degraded, sentences were still intelligible, as would
be expected (Eisenberg, Shannon, Martinez, Wygonski, &
Boothroyd, 2000; Fishman, Shannon, & Slattery, 1997; Lee, Min,
Wingfield, Grossman, & Peelle, 2016). The stimuli comprised 40
sentences in total, 10 in each of four conditions: SR and OR in
clear and vocoded formats. A second set of 40 sentences was
created to counterbalance gender fully with the syntactic and
acoustic manipulations. The two sets were alternated from one
child to the next. The sentence stimuli were equalized in mean
RMS (root-mean-square) intensity.
In the rhythm test, 20 rhythm sequences were chosen from
Grahn and Brett (2009), with the original pure tones (sine waves)
replaced by woodblock sounds. The new rhythm stimuli (.wav
files; 44.100 kHz; stereo) were obtained from the instrument
source in Ableton Live music production software (www.ableton
.com). Sound intensity was equalized based upon mean RMS. Half
of the rhythms consisted of seven sounds; the other half had eight
(Figure 1B). All sequences were structured so that the woodblock
sounds’ onsets were aligned with four beats (i.e., not syncopated),
in order to provide a strong sense of meter. The standard and
comparison rhythms varied on “different” trials, but even then they
had the same number of woodblock sounds.
Procedure. All children were administered the grammar and
rhythm tests, which were programmed on Open Sesame 3.1.6 and
run on desktop computers (Dell OptiPlex 7040). Both tests took
approximately 10 min. Sound stimuli were presented binaurally
through Bose Quiet Comfort 15 Acoustic Noise Canceling head-
phones. A parent completed a background questionnaire regarding
the child’s age, gender, language/music background, maternal
education, and any history of speech or language deficits and/or
therapy. The grammar test was always administered before the
rhythm test to avoid the potential influence of musical-rhythm
activity on subsequent grammar performance. For both tasks,
accuracy and response times (RTs) were recorded.
Children were first familiarized with the grammar task by un-
dergoing 14 practice trials. On each trial, they were instructed to
indicate the gender of the actor by pressing either the “male” (left
arrow) or “female” (right arrow) key as quickly and accurately as
possible (Figure 1A). During sentence presentation, children were
instructed to view the fixation cross on the monitor (Dell Profes-
sional P2417H 23.8” Screen LED-Lit) located approximately 50
cm in front of the child, and to hover their right-hand fingers over
the left and right arrows on the keyboard. During practice, there
was no restriction on response time, and children received feed-
back after each response. During the actual test session that fol-
lowed, children were encouraged to respond within 3 s and in-
structed to proceed to the next trial if no response was made during
this window. No feedback was given, but noncontingent verbal
encouragement was provided.
After a short break, children took the rhythm test (Figure 1C),
which had 20 trials. On each trial, children heard a pair of rhythm
sequences (Grahn & Brett, 2009) presented concurrently with
visual images of cartoon characters adapted from Gordon, Shivers,
et al. (2015). Five practice trials with feedback were administered
first to familiarize children with the test. On each trial, children
heard a rhythmic “standard” sequence while viewing a single
cartoon character playing drums. After a short delay (1500 ms), a
C
A
Syntax Acoustic Sentence Response
SR Clear Brothers that hug sisters are good Male
SR Noisy Sisters that hug brothers are good Female
OR Clear Brothers that sisters hug are good Female
OR Noisy Sisters that brothers hug are good Male
Listen
?
Sandy Same
Left Right
Delay
Beat 1
Delay
Beat 2
Response
300 ms
1500 ms
4000 ms
4000 ms
3000 ms
B4
4
4
4
7-sound
8-sound
Figure 1. (A) Examples of sentence conditions from the grammar test.
(B) Examples of a 7-sound and 8-sound rhythm in the rhythm test. (C)
Schematic illustration of the rhythm test. See the online article for the color
version of this figure.
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3
RHYTHM AND SYNTAX PROCESSING IN CHILDHOOD
comparison rhythm sequence was presented with side-by-side pic-
tures of two cartoon characters, one being the same as the character
who had just appeared, the other being new. In other words, the
cartoon characters provided a visual analogue for children’s
“same” or “different” responses. During familiarization, there was
no restriction on response time, and feedback was given following
each response. For the test session, children were encouraged to
answer within 3 s and no feedback was provided except for
noncontingent verbal encouragement. Trials were fully random-
ized across participants.
Results and Discussion
Scores measuring performance accuracy on the grammar and
rhythm tasks were converted to d=scores for statistical analyses.
Because perfect performance leads to an indeterminate d=, hit and
false-alarm rates were modified slightly by adding 0.5 to the
numerator and 1.0 to the denominator. This transformation has no
effect on the rank order of scores (Thorpe, Trehub, Morrongiello,
& Bull, 1988).
Figures 2A and 2B illustrate descriptive statistics for the gram-
mar task, separately for accuracy and RTs. Mean levels of perfor-
mance accuracy were significantly above chance levels (d=!0) in
each of the four conditions (Bonferroni-Holm corrected for four
tests), ps$.05. A two-way analysis of variance (ANOVA) was
used to analyze effects of syntax (SR or OR) and acoustic clarity
(clear or vocoded) as repeated measures. For accuracy, a main
effect of syntax, F(1, 67) !132.11, p$.001, %p
2!.664,
confirmed that children were more accurate with SR than OR
sentences. Similarly, a main effect of acoustic clarity, F(1, 67) !
13.02, p!.001, %p
2!.163, indicated higher accuracy for clear
than for vocoded speech. There was no two-way interaction, F$
1. For RTs, there was a main effect of syntax, F(1, 67) !50.21,
p$.001, %p
2!.428, with performance on SR trials being faster
than it was on OR trials. There was no main effect of acoustic
clarity and no two-way interaction, ps".1. Further analyses were
restricted to performance accuracy.
Figures 2C and 2D illustrate descriptive statistics for the rhythm
test. Accuracy was similar for sequences that had seven- or eight-
sound rhythm, p".1, correlated across conditions, r!.464, N!
68, p$.001, and substantially better than chance in both condi-
tions, ps$.001. Similarly, RTs did not differ reliably across
conditions, p".1, but they were correlated across conditions, r!
.377, N!68, p!.002. Further analyses considered performance
accuracy collapsed across the two conditions.
A linear mixed-effects regression (using the LMER framework
via lme4 package in R, Version 3.4) was used to predict d=scores
in the four sentence conditions as a function of performance
accuracy (d=) on the rhythm test. Covariates (fixed effects) in-
cluded syntax (SR/OR), clarity (clear/vocoded), age (M!11.13
years, SD !2.7), duration of music training (M!1.9 years, SD !
2.8), maternal education (M!2.7, SD !1.0), and gender (Male/
Female). Intercepts for subjects were included as random effects.
Syntax and clarity were included as random slopes. The results
revealed that age was the most significant predictor of grammatical
ability, as one would expect, with rhythm being the second-best
predictor, in line with the expected pattern of higher levels pre-
dicting better grammar performance (see Table 1).
In sum, as children improved on the rhythm task, they also
improved on the grammar task. Although this finding was evident
when maternal education, age, duration of music training, and
gender were held constant, one potentially important though miss-
ing covariate was a measure of short-term or working memory. In
Experiment 2, we attempted to replicate and extend the findings of
Experiment 1 by adding a brief test of working memory.
Experiment 2
Time constraints of testing in a museum setting precluded the
possibility of administering a comprehensive measure of general
cognitive ability, such as IQ. We therefore opted to measure one
aspect of general cognition that might best account for perfor-
mance on the grammar and rhythm tests: auditory working mem-
ory. On same-different tasks of musical ability, performance tends
to be associated with scores on nonmusical tests of auditory
memory (Hausen, Torppa, Salmela, Vainio, & Särkämö, 2013).
Method
Our inclusion of a measure of working memory as a covariate
could decrease the size of the partial association between rhythm
and grammar. Thus, we used G
!
Power 3.1 (Faul et al., 2009) to
determine that a sample of 92 participants was required to be 85%
certain of detecting a small- to medium-sized association (f
2
!.10,
Cohen, 1988), with seven other variables held constant, #!.05.
Participants. Children were recruited as in Experiment 1.
Although we tested 136 children, 40 were excluded for the fol-
Time (ms)
AB
CD
1000
1200
1400
1600
1800
2000
Time (ms)
1000
1200
1400
1600
1800
2000
7 sounds 8 sounds
OR SR
0.5
1.0
1.5
2.0
OR
clear voc. clear
SR
voc.
d prime
7 sounds 8 sounds
d prime
clear voc. clear voc.
0.5
1.0
1.5
2.0
Figure 2. Descriptive statistics for Experiment 1: (A) Mean d=in the four
conditions of the grammar test (voc. !vocoded; OR !object-relative;
SR !subject-relative); (B) Mean response times in the four conditions of
the grammar test; (C) Mean d=in the two conditions of the rhythm test; (D)
Mean response times in the two conditions of the rhythm test. Error bars
are standard errors calculated using method from Loftus and Masson
(1994).
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4LEE, AHN, HOLT, AND SCHELLENBERG
lowing reasons: 32 performed significantly below chance levels in
at least one condition of the grammar test, 4 did not complete the
task, and 4 had speech problems or language delays. Thus, the final
sample comprised 96 children (56 females), whose mean age was
11.1 years (SD !2.7). Only two children were bilingual. Two of
the 96 caregivers did not provide information about maternal
education. These missing values were replaced by the mean.
Stimuli and measures. The stimuli were the same as in Ex-
periment 1 with one exception. For the grammar test, instead of
degrading the speech signal itself (via vocoding), the original
sentences were presented in a background of multitalker babble
that consisted of three male and three female talkers (adapted from
Sperry, Wiley, & Chial, 1997). MATLAB code was used to
combine the babble with each sentence at a signal-to-noise ratio
(SNR) of 2 dB. In pilot testing, this SNR manipulation rendered a
degree of difficulty comparable to the vocoding manipulation of
Experiment 1. An additional buffer of 0.5 s babble was included
before and after each sentence. The intensity (mean RMS) of all
stimuli was equated.
For our test of auditory working memory, we adapted Stern-
berg’s (1966) paradigm. On each trial, a group of three or four
novel synthetic sounds was presented followed by a probe sound.
Participants indicated whether the probe sound was old (i.e., pre-
sented in the group) or new. An example is provided at the
following link: https://www.youtube.com/watch?v!9TwDVn
5n8Zw.
Results and Discussion
As in Experiment 1, performance accuracy was indexed with d=
scores, including performance on the test of working memory.
Figures 3A and 3B show descriptive statistics across the four
different conditions of the grammar test. As in Experiment 1,
performance was above chance levels in all four conditions, ps$
.005. A two-way ANOVA revealed a main effect of syntax, F(1,
95) !102.85, p$.001, %p
2!.520, with higher accuracy for SR
than for OR sentences. Neither acoustic clarity, F$1, nor the
interaction between syntax and clarity, p".1, was significant. For
the ANOVA on RTs, there was again a main effect of syntax, F(1,
95) !69.25, p$.001, %p
2!.422, with faster RTs for SR than for
OR sentences, as well as a main effect of clarity, F(1, 95) !11.88,
p!.001, %p
2!.111, with faster RTs for sentences presented in
quiet than in babble. There was no interaction between syntax and
clarity, F$1. In other words, background babble slowed down
responding, but it did not make the children less accurate.
Figures 3C and 3D provide descriptive statistics for perfor-
mance on the rhythm test. For accuracy, performance was much
higher than chance levels in both conditions, ps$.001. Perfor-
mance was correlated across the two conditions, r!.263, N!96,
p!.010, but better for 8-sound than for 7-sound rhythms, t(95) !
3.50, p!.001, %p
2!.114. RTs were also faster for 8-sound
rhythms, t(95) !3.51, p!.001, %p
2!.115, which were never-
theless correlated with 7-sound rhythms, r!.394, N!96, p$
.001.
For the test of auditory working memory, the children responded
correctly on an average of 75.4% (SD !14.0) of the trials, such
that the mean d=score was substantially better than chance, p$
.001. Scores were correlated with mean performance on the gram-
mar test, r!.296, N!96, p!.003, but not with performance on
the rhythm test, p".4. When age was held constant, the associ-
ation between working memory and grammar disappeared, p".4.
As in Experiment 1, the linear mixed-effects regression was
conducted to predict d=in the four sentence conditions as a
function of accuracy (d=) on the rhythm test. Other variables for
fixed effects were syntax (SR/OR), clarity (clear/vocoded), age,
rhythm, auditory working memory (M!1.38, SD !0.38), dura-
tion of music training (M!1.2 years, SD !2.1), maternal
education (M!2.7, SD !1.1), and gender (Male/Female).
Intercepts for subjects were included as random effects, as were
the slopes of the syntax and clarity manipulations. Results are
summarized in Table 2. After controlling for all other variables,
performance on the grammar test improved dramatically with age,
and significantly with rhythm scores. In short, the findings repli-
Table 1
Results From the Linear Mixed-Effects Model Predicting
Performance on the Grammar Test in Experiment 1
Variable Estimate Std. Error tscore pvalue
Syntax (SR) 1.287 0.111 11.580 $.001
Acoustic clarity (voc.) &0.273 0.077 &3.530 $.001
Age 0.147 0.03 4.987 $.001
Gender (M) 0.052 0.154 0.337 .737
Maternal education 0.102 0.083 1.231 .222
Music training 0.047 0.035 1.357 .179
Rhythm discrimination 0.272 0.097 2.793 .007
Note. SR !subject-relative; voc. !vocoded; M !male.
Time (ms)
AB
CD
1000
1200
1400
1600
1800
2000
Time (ms)
OR
clear bab. clear
SR
bab.
1000
1200
1400
1600
1800
2000
7 sounds 8 sounds
0.5
1.0
1.5
2.0
OR
clear bab. clear
SR
bab.
d prime
7 sounds 8 sounds
d prime
0.5
1.0
1.5
2.0
Figure 3. Descriptive statistics for Experiment 2: (A) Mean d=in the four
conditions of the grammar test (bab. !babble; OR !object-relative; SR !
subject-relative); (B) Mean response times in the four conditions of the
grammar test; (C) Mean d=in the two conditions of the rhythm test; (D)
Mean response times in the two conditions of the rhythm test. Error bars
are standard errors calculated using method from Loftus and Masson
(1994).
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5
RHYTHM AND SYNTAX PROCESSING IN CHILDHOOD
cated the association between rhythm and grammar found in
Experiment 1, but with auditory working memory held constant as
well.
In a final analysis, we collapsed the data sets from Experiments
1 and 2 in order to look at developmental trends more closely. Of
particular interest was whether the association between rhythm and
grammar would become weaker or stronger with age. We used
multiple regression to predict performance on the grammar task
(aggregated across the four conditions) as a function of age,
rhythm, and the interaction between age and rhythm (variables
centered). Additional control variables included gender (dummy
coded), maternal education, music training, and a dummy variable
that accounted for differences between the two experiments. The
model explained 40.3% of the variance in grammar performance,
R!.637, F(7, 156) !15.05, p$.001 (adjusted R
2
!.376).
Significant contributions were made by age, '!.532, t(156) !
8.24, p$.001, rhythm, '!.239, t(156) !3.62, p$.001, and the
interaction between age and rhythm, '!.148, t(156) !2.35, p!
.020. All control variables were nonsignificant, ps".1. In short,
performance on the grammar task was better among older children
and among children with better performance on the rhythm task.
The positive slope for the interaction term indicated that the
association between rhythm and grammar became stronger as age
increased.
To test for possible interactions between age and variance in
performance due to the syntactic manipulation, we correlated age
with the difference between performance in the subject- and
object-relative conditions. The association was negative but very
weak, r!&.143, N!164, p!.034 (one-tailed; a positive
association would be uninterpretable). In other words, we found
weak evidence that the performance advantage for subject- over
object-relative sentences decreased as children became older and
more masterful with English grammar.
General Discussion
In two experiments, we explored the possibility of an asso-
ciation between musical rhythm skills and receptive grammar in
school-age children. In Experiment 1, rhythm discrimination
predicted the comprehension of syntactically complex sen-
tences (i.e., with embedded clauses), and this positive associa-
tion remained significant after accounting for individual differ-
ences in age, gender, music experience, and maternal education.
This finding was replicated in Experiment 2 while further
controlling for individual differences in working memory. After
collapsing both data sets, we found that the rhythm– grammar
link became stronger as children grew older. These data further
corroborate the association between rhythm and grammar in
typically developing children, and provide support for the pre-
vailing notion that shared neural resources are involved in some
aspects of music and language processing (Heard & Lee, 2020).
Despite ample documentation of a positive association be-
tween musical expertise and speech perception (see Schellen-
berg & Weiss, 2013, for review), it is less common to find links
between music and higher-order language processes, such as
grammar or reading. In one previous study, cited earlier, the
6-year-olds’ rhythm discrimination ability predicted their use of
expressive syntax (Gordon, Shivers, et al., 2015). Our results
extend this finding by documenting an association between
rhythm abilities and receptive grammar among children who
varied substantially in age. In both studies, there was no asso-
ciation between music training and grammar proficiency when
rhythm abilities were held constant, which raises the possibility
that the link may be mediated by preexisting neural traits. This
interpretation is inconsistent with proposals that music training
benefits speech and language skills (Kraus & Chandrasekaran,
2010; Patel, 2011), but consistent with other studies that failed
to find a positive influence of music training on speech percep-
tion (Boebinger et al., 2015; Ruggles, Freyman, & Oxenham,
2014; Swaminathan & Schellenberg, 2017, 2019) and reading
comprehension (Swaminathan & Schellenberg, 2019; Swami-
nathan, Schellenberg, & Venkatesan, 2018). One possibility is
that the discrepancy may be due to the differences in the way
that music training was measured, although Swaminathan and
her colleagues reported the same finding when they coded
music training in four different ways (Swaminathan & Schel-
lenberg, 2017, 2019; Swaminathan et al., 2018). Indeed, links
between music training and language abilities may be epiphe-
nomenal (Schellenberg, 2015), such that they disappear when
individual differences in musical aptitude or general cognitive
ability are held constant.
Although our findings are consistent with those of Gordon,
Shivers, et al. (2015), there are notable differences between the
two studies. The earlier study measured the use of morpho-
syntactic operations in expressive grammar, whereas we used a
receptive grammar test that required listeners to cope rapidly
with syntactic complexities while listening to a series of short
sentences. Although SR and OR sentences involved temporal
interruption due to the center-embedded clause, OR sentences
were more challenging than SR sentences due to the noncanoni-
cal ordering of the words, as evidenced by less accurate and
slower performance. Although most children use sentences with
relative clauses well before they enter school (Brown, 1971;
Corrêa, 1995; de Villiers, Tager Flusberg, Hakuta, & Cohen,
1979; Kidd & Bavin, 2002; Labelle, 1990; Sheldon, 1976,
1977), our data confirm that full mastery of these types of
sentences develops throughout the school-age period. With such
large developmental differences between 7 and 17 years of age,
however, it would be ideal to replicate the present results with even
larger samples of children. Nevertheless, our findings are in line
with those from a large and multinational online sample, which
documented that grammar development continued throughout
Table 2
Results From the Linear Mixed-Effects Model Predicting
Performance on the Grammar Test in Experiment 2
Variable Estimate Std. Error tscore pvalue
Syntax (SR) 1.334 0.131 10.195 $.001
Acoustic clarity (babble) &0.033 0.066 &0.495 .622
Age 0.162 0.027 5.978 $.001
Gender (M) 0.145 0.136 1.065 .737
Maternal education &0.011 0.061 &0.182 .856
Music training &0.026 0.033 &0.782 .436
Rhythm discrimination 0.211 0.097 2.168 .033
Working memory 0.039 0.086 0.450 .654
Note. SR !subject-relative; M !male.
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6LEE, AHN, HOLT, AND SCHELLENBERG
most of adolescence, plateauing at approximately 17 years of age
(Hartshorne et al., 2018).
In a recent study of 6- to 9-year-old children (Swaminathan &
Schellenberg, 2019), performance on a test of receptive grammar
was correlated positively with performance on a test of rhythm
discrimination, a finding that corroborates the present results.
Moreover, as in the present study, the association remained evident
after holding constant SES and general cognitive ability. Claims of
a special link between rhythm and grammar require evidence of
discriminant validity, however, which their data only partly sup-
ported. On the one hand, rhythm discrimination was better than
melody discrimination at predicting receptive grammar and speech
perception. On the other hand, scores on a test of memory for
music matched rhythm abilities in predictive power. These results
raise the possibility that the “special” status of rhythm in predict-
ing language abilities may emerge primarily when it is compared
directly with melody perception, a result that is now common in
studies of adults (Bhatara, Yeung, & Nazzi, 2015; Hausen et al.,
2013; Swaminathan & Schellenberg, 2017). Among children, how-
ever, things may be less clear-cut. Indeed, studies of very young
children have reported that melody is better than rhythm at pre-
dicting grammar (Politimou et al., 2019), and that training in
melody is superior to training in rhythm at improving phonological
awareness (Patscheke, Degé, & Schwarzer, 2019). In short, a
complete developmental account of associations between music
and language will require researchers to include multiple measures
in both domains.
One particularly positive aspect of the present study was its
relatively large samples of children compared to previous re-
search. In the study by Gordon, Jacobs, et al. (2015), only 25
children were tested, whereas we had a total of 164 children
across two experiments. A notable limitation of the present
study was that we did not include full-scale IQ to measure
general cognitive ability, due to the time constraint imposed by
testing in the museum (i.e., $25–30 min). Rather, in Experi-
ment 2, we administered a brief test of auditory working mem-
ory. Another potential limitation was that the experiment was
conducted in an open laboratory space where other experiments
were sometimes conducted simultaneously. Although our audi-
tory stimuli were delivered via noise-canceling headphones, the
children may still have been distracted periodically in the open
environment. Such distraction may have led to a higher exclu-
sion rate than anticipated due to misunderstanding of the task,
and/or loss of interest in both auditory experiments. In any
event, the cross-experiment replication and large samples pro-
vide clear evidence of a link between rhythm and receptive
grammar among school-age children, thereby extending evi-
dence of a link with expressive grammar in 6-year-olds (Gor-
don, Shivers, et al., 2015).
In addition to varying the degree of syntactic complexity, we
varied the acoustic clarity of the speech stimuli using two
strategies. In Experiment 1, we removed some of the spectral
details using a 15-channel vocoder, whereas in Experiment 2,
we added multitalker babble as background noise to mask the
speech energetically. The vocoded speech was challenging for
our child listeners, who were less accurate with vocoded than
with clear speech. By contrast, the multitalker babble had no
effect on accuracy, but it led to slower responding. Although we
attempted to equate the perceptual difficulty between the two
types of manipulation, we failed to do so in the sense that they
had differential effects on accuracy, but succeeded in the sense
that both manipulations affected the processing time required to
complete the task. As noted in the introduction, our rationale for
including acoustic clarity in the stimuli design was to explore
children’s language comprehension when both syntactic com-
plexity and acoustic clarity varied simultaneously. Indeed,
noise is detrimental to the comprehension of syntactically com-
plex sentences, such as those with object-relative clauses for
older adults (Wingfield et al., 2006). For our children, vocoded
object-relative sentences were the most difficult to comprehend
in Experiment 1, but the effects of syntax and clarity were
additive rather than interactive.
Tierney and Kraus (2015) suggest that different tests of
rhythm involve different aspects of cognitive and sensory pro-
cesses (e.g., working memory, sensory-motor integration, etc.).
The rhythm-discrimination test that we used allowed us to
measure children’s auditory sensitivity to moment-by-moment
temporal dynamics in musical sequences. Why would such
sensitivity predict children’s ability to comprehend syntacti-
cally and sequentially complex sentences? One likely possibil-
ity is that the neural mechanism responsible for analyzing
temporal structures extends to both musical and linguistic
events. That is, certain aspects of music and language pro-
cesses, such as the rhythm and syntactic tasks explored here, are
mediated by common temporal-processing mechanisms.
Emerging evidence demonstrates that temporal structures of
sentences affect syntactic analysis. As noted, individuals per-
form better on a syntactic task when constituent words of
a sentence are presented metrically with a regular beat
(Roncaglia-Denissen et al., 2013). They also display a concom-
itantly reduced P600 EEG amplitude, a hallmark of syntactic
processing in response to metrical sentences, which suggests
that the established meter made syntactic processing less effort-
ful. Syntactic processing is also influenced by external rhythms
that are independent of the intrinsic temporal structure of given
sentences. Specifically, Przybylski et al. (2013) demonstrated
that children are better at detecting morphosyntactic violations
after listening to 32 s of rhythmically regular rather than irreg-
ular musical sequences. This finding was subsequently ex-
tended to a design that compared priming with regular beats to
arrhythmic environmental sounds (Bedoin et al., 2016). Evi-
dence of discriminant validity comes from results showing that
regular-beat priming improves grammar performance but not
mathematical ability (Chern et al., 2018).
According to dynamic attending theory (Jones, 1976; Jones &
Boltz, 1989), neural oscillations for syntactic operations become
more efficient when a regular rhythm serves as a prime. The
observed phenomena could nonetheless be independent of atten-
tional modulation; rather, temporal processing could be enhanced
via the sensorimotor network. Future research is warranted to
elucidate further the detailed neurofunctional and neuroanatomical
mechanisms that explain the link between rhythm and grammar. In
any case, our data provide behavioral support for the prevailing
notion that similar or identical neural mechanisms are used for
rule-based temporal processing in language and music (Heard &
Lee, 2020).
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7
RHYTHM AND SYNTAX PROCESSING IN CHILDHOOD
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Received October 22, 2019
Revision received April 16, 2020
Accepted April 17, 2020 !
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10 LEE, AHN, HOLT, AND SCHELLENBERG
