Authors: Silvia Bonacina, Jennifer Krizman, Travis White-Schwoch, Trent Nicol, Nina Kraus
Categories: Original Article, beat, beat alignment task, rhythm, rhythmic patterns, rhythmic skills development, synchronization
Source: Global Pediatric Health
Authors: Silvia Bonacina, Jennifer Krizman, Travis White-Schwoch, Trent Nicol, Nina Kraus
Rhythmic expertise can be considered a multidimensional skill set, with clusters of distinct rhythmic abilities evident in young adults. In this article, we explore relationships in school-age children (ages 5-8 years) among 4 rhythmic tasks hypothesized to reflect different clusters of skills, namely, drumming to an isochronous beat, remembering rhythmic patterns, drumming to the beat in music, and clapping in time with feedback. We find that drumming to an isochronous beat and remembering rhythmic patterns are not related. In addition, clapping in time with feedback correlates with performance on the other 3 rhythm tasks. This study contributes to the taxonomy of rhythmic skills in school-age children. It also supports the use of clapping in time training as a way to possibly affect a broad spectrum of rhythmic abilities that are linked to language and literacy processes.
Rhythm helps organize events into predictable and coherent patterns. In music, rhythm is the primary element that creates the perception of time.^1^ In speech, rhythm helps us select and extrapolate phonemes, syllables, words, and phrases from an ongoing speech stream.^2^ Having good rhythmic skills, therefore, appears to be essential not only for music or dance but also for language and communication skills.
Rhythm abilities are not simply heritable skills; recent studies have shown that rhythm skills can be improved through training^3,4^ and that the performance of an individual may vary across different rhythm tests.^5^ This and related observations have supported a hypothesis that rhythm should be conceptualized as a multidimensional skill set, in contrast to the concept of a single “rhythmic IQ.” To date, the dissociation between sets of rhythmic abilities (drumming to the beat and discriminating/reproducing rhythm) has been reported in several case studies, including musicians and nonmusicians following a stroke,^6,7^ respectively, patients undergoing unilateral temporal cortectomy,^8^ and a patient with congenital amusia.^9^ Additionally, this dissociation has been shown in a population of healthy young adults.^5^ However, this dissociation has not been investigated in a school-age population.
Understanding the taxonomy of rhythm skills in school-age children is important not only from a theoretical standpoint but also for its clinical implications. In fact, struggling with certain rhythmic skills can reflect underlying language and/or perceptual impairments; this has led to increasingly popular rhythm-based trainings to treat literacy and auditory processing problems, especially at early stages of life.^10-14^ Therefore, a more thorough understanding of the development and interconnection of different rhythmic abilities in early childhood can crucially help in sculpting such interventions to the specific needs of each individual.
In this article, we focus on 4 rhythmic tasks that have been selected to represent multiple hypothesized rhythmic
All these tasks highlight different elements of rhythmic ability. Together, they provide a wide-ranging picture of people’s rhythmic processing. This study aims to (a) uncover the reciprocal relationships among the 4 rhythmic tasks performances in school-age children and (b) investigate changes in performances across 2 consecutive years. Given aforementioned evidence of multiple dissociable rhythmic skills in adolescents and young adults, we hypothesized distinct clusters of rhythmic interconnections also in school-age children. Thus, we predicted that we would observe steady growth in rhythmic skills from Year 1 to Year 2; but we also predicted that the rate of development would differ among the multiple rhythm skills we considered.
Sixty-eight children between 5.0 and 8.1 years of age (mean age = 6.34; SD = 0.69; 32 female) were recruited from the Chicago area. On average, maternal education level was high (mean = 17.54 years of school; SD = 2.29, range = 12-20 with 16 = all years college completed, proxy for socioeconomic status according to D’Angiulli et al^27^) and the children had relatively high IQs (assessed by the Wechsler Preschool and Primary Scale of Intelligence Information subtest, mean percentile = 72.67, SD = 27.79, and Matrix Reasoning subtest, mean percentile = 75.42, SD = 26.00). Some of the kids (N = 18) are involved in music or dance program according to the history form completed by the parents.
They were assessed with a battery of 4 different rhythmic tasks. Forty-six of these participants were retested 1 year later to monitor the development of these rhythm skills.
All of the participants passed screening tests of peripheral auditory function (normal otoscopy, tympanometry, and distortion product otoacoustic emissions at least 6 dB sound pressure level above the noise floor from 0.5 to 4 kHz).
None of the participants had a history of a neurologic condition or a diagnosis of autism spectrum disorder, learning disabilities, or attention disorder. For all participants parents or legal guardians provided informed consent and children provided verbal assent to participate. This study was approved by Northwestern University’s Institutional Review Board (#STU00016500). Participants were monetarily compensated for their participation.
The rhythmic battery includes 4 tasks. The first 3 tasks use the same system for stimulus presentation, collection, and analysis of drumming data (for data collection details refer to Tierney and Kraus^5^). For each, a conga drum, with a trigger to register drum hits, was used and practice trials were given. The clapping in time task was performed using the Interactive Metronome technology (for data collection details refer to Bonacina et al^26^).
Participants are asked to listen and drum to an isochronous pacing beat presented through in-ear headphones. Four trials are presented, 2 at 2.5 Hz (50 beats each) followed by 2 at 1.67 Hz (33 beats each). Each trial consists of a snare drum pacing sound repeated with a constant inter-onset-interval. The consistency of each participant’s drumming is averaged across all trials (both inter-onset-intervals) and is calculated using circular statistics (refer to Carr et al^25^ for complete details about data processing and analyses). Drumming consistency is defined as measure of the synchronicity of the participant’s taps averaged across both drumming rates. Throughout the article we will refer to this task as “Drumming to a beat.”
Participants are asked to listen to 3 repetitions of a rhythmic sequence without drumming and then drum out the sequence during a pause, producing the sequence exactly when it would have occurred had it repeated a fourth time. Ten trials were presented (a mix of strongly and weakly metrical sequences). No earphones are used. The performance of each participant is calculated as percentage correct, which counts the proportion of drum hits and pauses that are correctly remembered within a certain timeframe across an entire condition. Throughout the article we will refer to this task as “Remembering rhythmic patterns.”
This task is an adaptation of the beat-alignment task from Iversen and Patel.^28^
Participants are asked to listen to a musical excerpt through speakers and are instructed to tap to the perceived beat. Twelve instrumental musical excerpts from a range of genres are used and tap times are collected. Synchronization accuracy is measured as the absolute value in milliseconds of the difference between the average inter-drum interval produced by the participants and the actual beat tempo of each musical excerpt.
Participants may choose different tactus levels with which to synchronize. For example, if an excerpt is in 4/4 time, the participant might tap 4 times in every measure, or twice, on beats 1 and 3. Tapping performance is compared with the tactus level in the excerpt closest to the tapping tempo. Throughout the article we will refer to this task as “Drumming to the beat of music.”
Participants are asked to clap their hands together in a fluid circular motion against a hand trigger in time with a pacing tone delivered over headphones. A visual indicator is shown on a computer screen, reflecting the asynchrony between their last clap and the target beat (milliseconds before or behind the beat). Synchronization is performed at a rate of 0.9 Hz for 1 minute without any practice period. Synchronization variability is calculated as the standard deviation of the asynchronies in milliseconds. Throughout the article we will refer to this task as “Clapping in time.”
Table 1 contains an overview of the main measure for each rhythmic task.
The data related to each rhythmic tasks are not normally distributed, even after performing transformations (i.e. log, arcsin, square root, and inverse). This might be the result of young participants having a dispersed distribution of rhythmic skills due to different rates of development at early ages. The main descriptive statistics are reported in Table 1.
To investigate the relationships between rhythmic tasks, performances on the 4 measures of rhythmic skills were correlated using Spearman’s ρ correlations controlling for sex and participant’s age when the task was performed.
To monitor the change in performance over time, we employed repeated-measures analyses of variance for the 46 children who were assessed for 2 consecutive years. Given the not normal distribution of our data, we also ran Friedman tests to complement the results.
No significant relationship was found between drumming to a beat and remembering rhythmic patterns (ρ = .116). Participants who showed less variability in clapping in time were better at drumming to a beat (ρ = −.417**), remembering rhythmic patterns (ρ = −.271*), and drumming to a beat of music (ρ = .398**).
Children who performed better at drumming to the beat of music were better at both drumming to a beat (ρ = −.305*) and remembering rhythmic patterns (ρ = −.317*).
Figure 1 shows scatterplots comparing performance across all 4 rhythmic tasks with Spearman ρ and P values for each correlation.

The performance on each rhythmic task was compared across 2 consecutive years (Year 1; Year 2) using a repeated measures analysis of variance and percent change calculations. While drumming to a beat of music did not change, the other 3 rhythm skills improved from Year 1 to Year 2 (Table 2 and Figure 2).

This study is the first to provide evidence of the interconnections among rhythmic skills in school-age children. It provides 3 main results. First, performance on a drumming to a beat task is separate from performance on a remembering rhythmic patterns test in this age group. This finding is in line with previous evidence in adolescents^5^ and indicates that these 2 skills follow divergent maturational paths as early as childhood (ie, ages 5-8 years).
Second, despite the above-reported independence between drumming to a beat and remembering rhythmic patterns, both tasks relate to performance on a drumming to the beat of music task. It is also noteworthy that, despite these relationships, children did not improve in their performance on the drumming to music task between Years 1 and 2. This could be for several reasons, including the excessive demands of following the structure of real music, along with the development of other sensory and cognitive skills during this age range. Future studies can test drumming to music performance in older children to better understand its developmental trajectory.
Third, performance on the clapping in time task correlates with the other 3 tests considered. These relationships may reveal the complexity of the process that clapping in time with feedback requires. It is also noteworthy that this is the only task requiring the incorporation of feedback. The extensive relationships between this task and other tasks may also underlie the rehabilitative benefit of Interactive Metronome, which uses clapping in time with feedback as an intervention. Several clinical populations exhibit timing deficits that co-occur with to language deficits; for example, individuals with reading impairment often struggle to tap along to an isochronous beat. It is conceivable that clapping in time to feedback could be a viable intervention for populations with distinct rhythmic deficits (such as one group who struggles to synchronize to a beat and another who struggles to remember rhythmic patterns).
Taken together, our findings suggest a model whereby rhythm starts off early in life as a global skill across different facets of rhythm, subsequently becoming more specialized later in life. Therefore, it would be interesting to explore these relationships with a longitudinal design, using age-appropriate tests in older populations.
While this study contributes to our knowledge of the taxonomy and developmental trajectory of rhythmic skills, it has limitations that call for further investigation. Following the same population for beyond 2 years, from childhood to adulthood, would have been ideal to further understand the taxonomy of rhythmic skills from a broader developmental perspective. Previous work has shown that rhythmic tasks are more specialized in adolescents and adults^5^ than earlier in life.
Figure 3 represents current findings and schematic diagrams of hypothesized relationships for further investigations. Together with the available literature, the present study suggests that rhythmic skill is less differentiated in young children with specialization developing throughout childhood.
