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Published in final edited form as: NeuroRehabilitation. 2021 Jan 1;48(2):187–193. doi: 10.3233/NRE-208013

Deficits in musical rhythm perception in children with specific learning disabilities

Vasudha Hande a, Shantala Hegde b,*
PMCID: PMC7613144  EMSID: EMS150883  PMID: 33664156

Abstract

Background

A specific learning disability comes with a cluster of deficits in the neurocognitive domain. Phonological processing deficits have been the core of different types of specific learning disabilities. In addition to difficulties in phonological processing and cognitive deficits, children with specific learning disability (SLD) are known to have deficits in more innate non-language-based skills like musical rhythm processing.

Objectives

This paper reviews studies in the area of musical rhythm perception in children with SLD. An attempt was made to throw light on beneficial effects of music and rhythm-based intervention and their underlying mechanism.

Methods

A hypothesis-driven review of research in the domain of rhythm deficits and rhythm-based intervention in children with SLD was carried out.

Results

A summary of the reviewed literature highlights that music and language processing have shared neural underpinnings. Children with SLD in addition to difficulties in language processing and other neurocognitive deficits are known to have deficits in music and rhythm perception. This is explained in the background of deficits in auditory skills, perceptuo-motor skills and timing skills. Attempt has been made in the field to understand the effect of music training on the children’s auditory processing and language development. Music and rhythm-based intervention emerges as a powerful intervention method to target language processing and other neurocognitive functions. Future studies in this direction are highly underscored.

Conclusions

Suggestions for future research on music-based interventions have been discussed.

Keywords: Rhythm perception, specific learning disability, dyslexia, language

1. Dyslexia − Difficulties in phonological processing

Children with dyslexia despite having normal, average or above average levels of intelligence, motivation and schooling, face difficulties with reading and language processing. At the core of this neurobiological developmental condition lies deficit in phonological processing. Phonological awareness comprises of knowledge of sounds as revealed by ability to identify rhymes, identifying the sound of individual syllable and their combination, blending and deleting phonemes (Frith, Landerl, & Frith, 1995) and phonemic discrimination (Démonet, Taylor, & Chaix, 2004; Thomson & Goswami, 2008). These difficulties emerge from general deficit in processing dynamic, rapidly changing auditory information (rapid temporal processing) (Overy, Nicolson, Fawcett, & Clarke, 2003). In addition, there is a lack of well timed, automated motor skills which in turn inhibits the normal development of articulatory gestures, phonological awareness and literacy skills in children with dyslexia (Overy et al., 2003). They have difficulties with time estimation, rhythm tapping, detecting complex timing patterns and rapid temporal processing. Interestingly, the rapid temporal processing is an essential skill required for processing non-speech sounds like music and rhythm perception.

2. Musical rhythm and language: Shared and unique neural underpinnings

Music and language are two of the most complex cognitive processes considered to be unique to human. Music perception is an ability to perceive temporally ordered sound sequences in rapid succession. It involves a complicated interaction among cognitive, perceptual, affective and motor processes. Contrary to popular belief on hemispheric specialization of music and language, they share neural correlates and have similarities in the way they are processed and produced. Both music and auditory language processing comprises of inferior frontolateral and anterior as well as posterior temporal lobe structures in both hemispheres (Koelsch et al., 2002). Musical events activate language processing areas such as the Broca’s and Wernicke’s areas, superior temporal sulcus, Heschl’s gyrus, planum polare and planum temporale as well as the anterior superior insular cortices (Koelsch, 2011; Peretz, Vuvan, Lagrois, & Armony, 2015). Music and language perception begin with a processing of auditory signals. Both require a precise representation of several sound features, such as timbre, pitch, duration, and their interactions. They both involve a sequencing of syllables and use a complex set of cognitive and motor processes. Prosody, periodicity and syntactical structure are common components in both music and language. Rhythm is another important feature overlapping between music and language (Patel & Daniele, 2003a).

Rhythm refers to the organization of events in time. Meter involves hearing the beat of a rhythm, the regular pulse that serves as a temporal anchor around which other events are organized. Perception of rhythm is crucial to find structure and meaning in speech and music (Iversen, Patel, & Ohgushi, 2008). In perceiving rhythm, we naturally perceive events as grouped into higher level patterns. Such grouping is an essential step in the interpretation of complex sound sequences. In music, rhythm orders movement of musical patterns in time (Thaut, Trimarchi, & Parsons, 2014). Linguistic rhythm refers to the way languages are organized in time (Patel & Daniele, 2003b). In language, listeners must segment words and phrases from the ongoing speech stream in order to make sense of the incoming signal. A louder sound tends to mark the beginning of a group. A lengthened sound tends to mark the end of a group. Three ways in which a language can divide time are postulated: syllable timed, mora timed and stress timed. In syllable timed languages, the duration of every syllable is equal. In mora timed languages, the duration of every mora is equal and in stress timed languages, the interval between the two stressed syllables is equal (Patel & Daniele, 2003b). Rhythmic grouping preferences are acquired sometime between six to eight months of age. This is an age during which many language skills also emerge. This suggests that learning of linguistic factors and rhythmic grouping interact. In typically developing children, ability to synchronise with the beat is associated with competencies underlying reading acquisition such as phonological awareness, verbal short-term memory and rapid naming (Gervain, Macagno, Cogoi, Peña, & Mehler, 2008).

Music training is associated with enhanced auditory processing. As compared to non-musicians, musicians are observed to have an increased activation of left superior, middle and inferior temporal cortex (Thaut et al., 2014). The regularity of musical primes is beneficial for language development. According to dynamic attending theory (Jones & Boltz, 1989) attention aligns with external regularities. Due to this, listeners will develop expectations about when future events will occur. Entrainment to regular musical prime benefits language processing by aiding sequencing and structural integration (Canette et al., 2020). Hence it is evident that rhythm and language processing overlap and influence each other.

Music and rhythm perception deficits in children with dyslexia can be explained in the background of deficits in auditory skills, perceptuo-motor skills and timing skills. Rhythm perception is a complex sensory representation of the auditory input, the sense of motion from sound which is mediated by the vestibular system, a motor representation of the body (McAngus Todd, O’Boyle & Lee, 1999). Children with reading impairments were found to be significantly poorer in their ability to discriminate auditory patterns on the rhythm discrimination tasks compared to controls (Lee, Sie, Chen, & Cheng, 2015; McGivern, Berka, Languis, & Chapman, 1991; Overy et al., 2003). These results indicate a neurological unpreparedness to learn to read in a normal classroom setting. There is a correlation between spelling ability and the skill of tapping out the rhythm of a song, both of which rely to some extent on phonological segmentation skills. This suggests that children who are able to extract the rhythm of a song may have a phonological advantage when approaching spelling.

Rhythm perception is strongly associated with reading outcome measures and phonological awareness (Flaugnacco et al., 2014). A strong relationship was found between auditory musical discrimination abilities and language related skills in children (Forgeard et al., 2008). This relationship was stronger in children with music training. Studies on children with dyslexia suggest that these children have rhythm processing and production deficits that are also correlated with their reading accuracy and fluency. There is a significant difference in beat detection between English speaking dyslexic children and their chronological age matched healthy control (Goswami et al., 2002). Furthermore, tapping tasks are correlated with some aspects of language and rise time is correlated with text reading. They found that meter perception task was a good predictor of text reading accuracy and word reading speed, while rhythm reproduction was the best predictor of pseudo-word reading accuracy (phonological processing). Adults with dyslexia showed abnormal rhythmic entrainment to syllable patterns in speech when multi-timescale analysis method was used during a study of rhythm perception and rhythm production. Deficit in rhythm perception in children with dyslexia is found to be universal in nature (Muneaux, Ziegler, Truc, Thomson, & Goswami, 2004). Rhythm production and rhythm discrimination tasks were correlated with musical pitch tasks and reading in children as young as four years (Anvari, Trainor, Woodside, & Levy, 2002). Skill in music perception is related to auditory or cognitive mechanisms beyond those tapped by phonological awareness. Children with dyslexia have difficulty synchronizing taps to a changing tempo as compared to ‘typical school’ group (Gyarmathy, Kertesz, & Forstner, 2017). They have difficulty in rhythm copying, rhythm perception and discrimination and tempo copying and discrimination.

Most of the studies on rhythm deficits have focused on dyslexia or specific reading disability. However, children suffering from learning disability are usually found to have mixed difficulties in reading, writing and arithmetic as these skills interact and influence each other. Children diagnosed to have pure dys-graphia or dyscalculia are also found to have deficits in rhythm processing.

3. Rhythm-based intervention: Future directions

Music and rhythm have evolutionary importance, present across cultures and are found to be more innate compared to language. Music related activities have been associated with improved cognitive and academic skills. Music training consists of singing, playing musical instruments, rhythm-based games and also involving any art form that uses rhythm. In children with dyslexia, the important question is whether music training and/or music and rhythm-based intervention has benefit on language development.

Several successful attempts have been made to understand the effect of music training on the children’s auditory processing and language development. Most of the studies have compared children already trained in music with those who are not. Rhythm-based activities can be used to enhance general cognitive abilities in typically developing children as well. A few studies have developed a specific rhythm-based intervention module to understand its benefits on reading development (Cancer et al., 2020; Fujioka, Ross, Kakigi, Pantev, & Trainor, 2006; Stievano, Pace, Colombo, & Antonietti, 2019).

Music training and music education is found to be associated with general cognitive abilities and specific language skills (Gerry, Unrau, & Trainor, 2012; Hille, Gust, Bitz, & Kammer, 2011). An association is found between music education and general IQ, verbal, auditory and motor abilities, mathematical and spatial abilities as well as neural changes such as white matter microstructural properties in the corpus callosum and the left superior longitudinal fasciculus. Musical training and hours of practice and intellectual ability seem to be related to the maturation of white matter pathways in the auditory-motor system (Loui, Raine, Chaddock-Heyman, Kramer, & Hillman, 2019; Paul, Sharda, & Singh, 2012). Rhythm-based intervention can be beneficial in preventing future reading deficits. Music training also enhances ability to detect tonal changes and accelerates auditory processing (Habibi, Cahn, Damasio, & Damasio, 2016). Musicians are able to better detect pitch variations in both music and language (Schön, Magne, & Besson, 2004). Studies have shown long lasting brain changes related to fine motor skills and melodic discrimination in children trained in music (Habibi et al., 2018; Schlaug, Norton, Overy, & Winner, 2005). Functional magnetic resonance imaging (fMRI) studies on musicians and non-musicians have found statistically significant differences in neural correlates of math processing (Schmithorst & Holland 2004).

Music and rhythm-based intervention has also been found to benefit children having predominantly dyscalculia (Esteki, 2013; Ribeiro & Santos, 2019). Table 1 summarises the research studies on music and rhythm-based interventions in children with dyslexia and other learning disabilities. In their study, (Rodriguez, do Nascimento, Voigt, & Dos Santos, 2019) authors came up with numeracy musical training which includes certain rhythm-based techniques to train children on cardinal system, numerical verbal system, visual numerical system and ordinal system. Music training is known to enhance spatial sense and working memory which are important components of mathematical ability. Greater activation was found in left fusiform gyrus and left prefrontal cortex for musicians. It is hypothesized that greater activation in left fusiform gyrus is associated with enhanced processing of shape information and visuo-perceptual semantic information and that in left prefrontal cortex with semantic working memory (Schmithorst & Holland, 2004). Rhythm-based activities include orienting children to the concept of pulse, mimicking clapping, identifying sound duration, discriminating between long and short sounds, rhymes, tongue twisters and body games among others (Ribeiro & Santos, 2019).

Table 1. Summary of studies on music-based intervention in specific learning disabilities.

Study Duration of intervention Methods Outcome
(Esteki, 2013) 16 sessions of music training. Students aged between 7−9 years are selected on whom K-Math Test, Wechsler Intelligence Test and brain mapping were performed. Then, subjects were divided into two groups and musical training was presented in a group for 16 sessions. Tests were repeated after the training sessions. Music training is found to increase attention rate, learning process, visual-motor−spatial perceived ability, concentration and visual speed as well as verbal memory.
(Ribeiro & Santos, 2019) 60 minutes music training once a week for a duration of 14 weeks. Follow up assessment after 10 months. Longitudinal and double-blind research with a mixed design. Twenty-two children with Developmental Dyscalculia (DD) and 29 typical development (TD) children underwent Musical training (MT). MT included melodic and rhythmic activities. MT was grounded on active musical learning methodologies such as Willems, Suzuki, Dalcroze Eurhythmics, and Suzuki methods, which combine music, movement, and speech into lessons to make it analogous to a setting where children play. The groups’ baseline was compared with the three-time points: mid-test, post-test and at follow-up after 10 months. The DD group showed slight improvements in numerical cognition throughout 14 sessions of a brief MT, especially for number production, number comprehension, and calculation. Scores for calculation remained better for the DD group compared with their baseline, but lower compared to the TD group performance throughout the training, which shows that the calculation deficits seem to be longer-lasting in the DD group. On the other hand, the follow up indicated that the MT benefits in numerical cognition remained at least 10 months after training.
(Rodriguez et al., 2019) Eight weekly sessions lasting 40 minutes each carried out over 2 months. Double blind prospective case control study investigating the effects of numeracy music training (NMT) on cognitive skills of 42 children aged 8−12 years grouped into low achievement n math and average achievement in math. Assessments were done pre and post NMT. Each NMT training session was divided into three types of techniques: rhythmic stimulation, melodic stimulation and tone stimulation. The eight days of NMT included training on cardinal system, numerical verbal system, visual numerical system, ordinal system, cardinal system, verbal numerical system, visual numerical system and ordinal system. Decrease in mathematics anxiety and improvements in counting backwards, reading and dictation of numbers, arithmetic as well as word problem solving, and in verbal working memory. In conclusion, NMT provided beneficial effects in the performance of numerical cognition tasks for children with DD.
(Stievano et al., 2019) 20 individual sessions of RRT over a 10-week period. Nineteen Italian students aged 8−14 years diagnosed with dyslexia participated in the study. A rhythm-based computerized training program to improve the reading abilities of Italian individuals with reading problems was designed, Rhythmic Reading Training (RRT). it consists of reading exercises designed to target specific reading subprocesses, namely, syllabic recognition, phonological awareness, grapheme-to-phoneme mapping, and lexical recognition. Trainees have to adjust their reading to synchronize it to the acoustic rhythm. The tempo of the rhythm and the complexity of the verbal stimuli are increased gradually during each training session. Rhythm discrimination ability was found to be strongly related to baseline reading ability and the improvements made during the intervention. RRT has the potential to improve reading speed, verbal working memory, rhythm discrimination and visual and auditory attention. Impact of RRT is proportional to reading impairment.
(Cancer et al., 2020) Two 45 minutes training sessions per day for 9 days. Rhythmic reading training (Traditional remediation approach combined with rhythm processing) was compared with VHSS (Visual Hemisphere-specific stimulation) and AVG (Action video game training). Children in the rhythmic reading training group improved in pseudoword reading speed.

Attempts have been made to understand the underlying mechanisms of rhythm-based interventions. Dynamic attending theory and neural resonance theories highlight about the attentional resources that are involved in rhythm perception. According to neural resonance theory (E. Large & Snyder, 2009; E. W. Large, 2008) built on the dynamic attending theory (Jones & Boltz, 1989) beat perception occurs when the nonlinear oscillations in the nervous system entrain to external rhythmic stimuli. The rhythm in music is not periodic. Yet people are able to perceive a periodicity using beats or pulse. This skill of perceiving rhythm can be transferred to perceiving linguistic rhythm and thus better language perception. Beat perception is predictive. We tend to nod our head and tap our hands a few milliseconds before the actual beat happens. Beat perception engages motor system even when there are no visible motor actions. Action Simulation for Auditory Prediction (ASAP) hypothesis (Patel & Iversen, 2014) argues that the motor system influences auditory processing and auditory perception.

Music training leads to enhanced neural encoding of speech sounds and subcortical speech processing. These brain changes were also correlated with amount of music training. Longitudinal studies have shown that music training causes changes in auditory cortical structure and function. To answer how these changes possibly occur the OPERA hypothesis (Patel, 2011) sums up five components that lead to music-driven adaptive plasticity in speech processing networks. First, there is an overlap (O) in the brain network for acoustic processing in both speech and music. Second, music places higher demand than speech in terms of precision (P) of processing. The musical activities that engage this network elicit positive emotion (E). Positive emotions can play a role in enhancing learning processes. The musical activities that engage this network are frequently repeated (R) thus strengthening the neural connections. Finally, the musical activities that engage this network are associated with focused attention (A).

4. Conclusion

Musical training is found to enhance the functioning of multiple senses: aural, visual, oral and kinaesthetic. Music-based interventions improve language skills in two ways. First, it enhances cognitive processes like attention, working memory and longterm memory which in turn enhances language skills. Second, the underlying overlapping features of musical and linguistic rhythm help to enhance language skills. To sum them up, first, they share several neural substrates. Second, they both have similar components like rhythm, syntax, prosody etc. Also, music-based interventions can be enjoyable to the children and can prove to be a less stressful intervention for children with dyslexia.

It seems important and beneficial to evaluate rhythm perception skills in children with dyslexia. This evaluation would be beneficial in more than one way: First, rhythm perception can be tested much before child starts attending formal school. This is important as it helps in an early detection of deficits as a diagnosis of dyslexia requires certain number of years of schooling. Second, music and rhythm perception tasks are mostly perceived enjoyable and one can expect an optimal level of performance by the child. Third, once the association between rhythm perception and language development is established, we can assess the predictive ability of different rhythmic aspects on the reading skills. Fourth, this would also help to use rhythm tasks in training children with specific learning disability.

Acknowledgement

Author SH acknowledges the support by the Wellcome Trust DBT India Alliance Intermediate Clinical Fellowship (IA/CPHI/17/1/503348).

Footnotes

Conflict of interest

None to report.

References

  1. Anvari SH, Trainor LJ, Woodside J, Levy BA. Relations among musical skills, phonological processing, and early reading ability in preschool children. Journal of Experimental Child Psychology. 2002;83(2):111–130. doi: 10.1016/s0022-0965(02)00124-8. [DOI] [PubMed] [Google Scholar]
  2. Cancer A, Bonacina S, Antonietti A, Salandi A, Molteni M, Lorusso ML. The effectiveness of interventions for developmental dyslexia: Rhythmic reading training compared with hemisphere-specific stimulation and action video games. Frontiers in Psychology. 2020;11 doi: 10.3389/fpsyg.2020.01158. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Canette L-H, Fiveash A, Krzonowski J, Corneyllie A, Lalitte P, Thompson D, Tillmann B. Regular rhythmic primes boost P600 in grammatical error processing in dyslexic adults and matched controls. Neuropsychologia. 2020;138:107324. doi: 10.1016/j.neuropsychologia.2019.107324. [DOI] [PubMed] [Google Scholar]
  4. Démonet J-F, Taylor MJ, Chaix Y. Developmental dyslexia. The Lancet. 2004;363(9419):1451–1460. doi: 10.1016/S0140-6736(04)16106-0. [DOI] [PubMed] [Google Scholar]
  5. Esteki M. Effectiveness of “Music Training” on reorganization of brain and poor intellectual abilities in female students with dyscalculia (7-9 years old) Global Journal of Arts Education. 2013;3(2) [Google Scholar]
  6. Flaugnacco E, Lopez L, Terribili C, Zoia S, Buda S, Tilli S, Ronfani L. Rhythm perception and production predict reading abilities in developmental dyslexia. Frontiers in Human Neuroscience. 2014;8:392. doi: 10.3389/fnhum.2014.00392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Forgeard M, Schlaug G, Norton A, Rosam C, Iyengar U, Winner E. The relation between music and phonological processing in normal-reading children and children with dyslexia. Music Perception. 2008;25(4):383–390. [Google Scholar]
  8. Frith U, Landerl K, Frith C. Verbal fluency in dyslexia: Further evidence for a phonological deficit. Dyslexia. 1995;1:2–11. [Google Scholar]
  9. Fujioka T, Ross B, Kakigi R, Pantev C, Trainor LJ. One year of musical training affects development of auditory cortical-evoked fields in young children. Brain. 2006;129(10):2593–2608. doi: 10.1093/brain/awl247. [DOI] [PubMed] [Google Scholar]
  10. Gerry D, Unrau A, Trainor LJ. Active music classes in infancy enhance musical, communicative and social development. Developmental Science. 2012;15(3):398–407. doi: 10.1111/j.1467-7687.2012.01142.x. [DOI] [PubMed] [Google Scholar]
  11. Gervain J, Macagno F, Cogoi S, Peña M, Mehler J. The neonate brain detects speech structure. Proceedings of the National Academy of Sciences. 2008;105(37):14222–14227. doi: 10.1073/pnas.0806530105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Goswami U, Thomson J, Richardson U, Stainthorp R, Hughes D, Rosen S, Scott SK. Amplitude envelope onsets and developmental dyslexia: A new hypothesis. Proceedings of the National Academy of Sciences. 2002;99(16):10911–10916. doi: 10.1073/pnas.122368599. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Gyarmathy E, Kertesz C, Forstner B. Keeping the Beat as a Measure Of Specific Learning Difficulties Using Midi Controller. 2017 [Google Scholar]
  14. Habibi A, Cahn BR, Damasio A, Damasio H. Neural correlates of accelerated auditory processing in children engaged in music training. Developmental Cognitive Neuroscience. 2016;21:1–14. doi: 10.1016/j.dcn.2016.04.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Habibi A, Damasio A, Ilari B, Veiga R, Joshi AA, Leahy RM, Damasio H. Childhood music training induces change in micro and macroscopic brain structure: results from a longitudinal study. Cerebral Cortex. 2018;28(12):4336–4347. doi: 10.1093/cercor/bhx286. [DOI] [PubMed] [Google Scholar]
  16. Hille K, Gust K, Bitz U, Kammer T. Associations between music education, intelligence, and spelling ability in elementary school. Advances in Cognitive Psychology. 2011;7:1. doi: 10.2478/v10053-008-0082-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Iversen JR, Patel AD, Ohgushi K. Perception of rhythmic grouping depends on auditory experience. The Journal of the Acoustical Society of America. 2008;124(4):2263–2271. doi: 10.1121/1.2973189. [DOI] [PubMed] [Google Scholar]
  18. Jones MR, Boltz M. Dynamic attending and responses to time. Psychological review. 1989;96(3):459. doi: 10.1037/0033-295x.96.3.459. [DOI] [PubMed] [Google Scholar]
  19. Koelsch S. Toward a neural basis of music perception–a review and updated model. Frontiers in Psychology. 2011;2:110. doi: 10.3389/fpsyg.2011.00110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Koelsch S, Gunter TC, von Cramon DY, Zysset S, Lohmann G, Friederici AD. Bach speaks: A cortical” language-network” serves the processing of music. Neuroimage. 2002;17(2):956–966. [PubMed] [Google Scholar]
  21. Large E, Snyder J. Pulse and meter as neural resonance. Annals of the New York Academy of Sciences. 2009;1169(1):46–57. doi: 10.1111/j.1749-6632.2009.04550.x. [DOI] [PubMed] [Google Scholar]
  22. Large EW. Resonating to musical rhythm: theory and experiment. The Psychology of time. 2008:189–232. [Google Scholar]
  23. Lee H-Y, Sie Y-S, Chen S-C, Cheng M-C. The music perception performance of children with and without dyslexia in Taiwan. Psychological Reports. 2015;116(1):13–22. doi: 10.2466/15.28.PR0.116k15w8. [DOI] [PubMed] [Google Scholar]
  24. Loui P, Raine LB, Chaddock-Heyman L, Kramer AF, Hillman CH. Musical instrument practice predicts white matter microstructure and cognitive abilities in childhood. Frontiers in Psychology. 2019;10:1198. doi: 10.3389/fpsyg.2019.01198. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. McAngus Todd NP, O’Boyle DJ, Lee CS. A sensory-motor theory of rhythm, time perception and beat induction. Journal of New Music Research. 1999;28(1):5–28. [Google Scholar]
  26. McGivern RF, Berka C, Languis ML, Chapman S. Detection of deficits in temporal pattern discrimination using the seashore rhythm test in young children with reading impairments. Journal of Learning Disabilities. 1991;24(1):58–62. doi: 10.1177/002221949102400110. [DOI] [PubMed] [Google Scholar]
  27. Muneaux M, Ziegler JC, Truc C, Thomson J, Goswami U. Deficits in beat perception and dyslexia: Evidence from French. NeuroReport. 2004;15(8):1255–1259. doi: 10.1097/01.wnr.0000127459.31232.c4. [DOI] [PubMed] [Google Scholar]
  28. Overy K, Nicolson RI, Fawcett AJ, Clarke EF. Dyslexia and music: measuring musical timing skills. Dyslexia. 2003;9(1):18–36. doi: 10.1002/dys.233. [DOI] [PubMed] [Google Scholar]
  29. Patel AD. Why would musical training benefit the neural encoding of speech? The OPERA hypothesis. Frontiers in Psychology. 2011;2:142. doi: 10.3389/fpsyg.2011.00142. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Patel AD, Daniele JR. An empirical comparison of rhythm in language and music. Cognition. 2003a;87(1):B35–B45. doi: 10.1016/s0010-0277(02)00187-7. [DOI] [PubMed] [Google Scholar]
  31. Patel AD, Daniele JR. Stress-timed vs. syllable-timed music? A comment on Huron and Ollen (2003) Music Perception. 2003b;21(2):273–276. [Google Scholar]
  32. Patel AD, Iversen JR. The evolutionary neuroscience of musical beat perception: the Action Simulation for Auditory Prediction (ASAP) hypothesis. Frontiers in Systems Neuroscience. 2014;8:57. doi: 10.3389/fnsys.2014.00057. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Paul A, Sharda M, Singh NC. Effect of music instruction on cognitive development: a review. Journal of the Indian Institute of Science. 2012;92(4):441–446. [Google Scholar]
  34. Peretz I, Vuvan D, Lagrois M-E, Armony JL. Neural overlap in processing music and speech. Philosophical Transactions of the Royal Society B: Biological Sciences. 2015;570(1664):20140090. doi: 10.1098/rstb.2014.0090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Ribeiro FS, Santos FH. Persistent Effects of Musical Training on Mathematical Skills of Children With Developmental Dyscalculia. Frontiers in Psychology. 2019;10 doi: 10.3389/fpsyg.2019.02888. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Rodriguez IA, do Nascimento JM, Voigt MF, Dos Santos FH. Numeracy musical training for school children with low achievement in mathematics. Anales De Psicología/Annals of Psychology. 2019;55(3):405–416. [Google Scholar]
  37. Schlaug G, Norton A, Overy K, Winner E. Effects of music training on the child’s brain and cognitive development. Annals-New York Academy of Sciences. 2005;1060:219. doi: 10.1196/annals.1360.015. [DOI] [PubMed] [Google Scholar]
  38. Schmithorst VJ, Holland SK. The effect of musical training on the neural correlates of math processing: a functional magnetic resonance imaging study in humans. Neuroscience Letters. 2004;554(3):193–196. doi: 10.1016/j.neulet.2003.10.037. [DOI] [PubMed] [Google Scholar]
  39. Schön D, Magne C, Besson M. The music of speech: Music training facilitates pitch processing in both music and language. Psychophysiology. 2004;41(3):341–349. doi: 10.1111/1469-8986.00172.x. [DOI] [PubMed] [Google Scholar]
  40. Stievano G, Pace G, Colombo A, Antonietti A. Cognitive Processes Underlying Reading Improvement during a Rhythm-Based Intervention. A Small-Scale Investigation of Italian Children with Dyslexia. Children. 2019;6(8):91. doi: 10.3390/children6080091. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Thaut MH, Trimarchi PD, Parsons LM. Human brain basis of musical rhythm perception: common and distinct neural substrates for meter, tempo, and pattern. Brain Sciences. 2014;4(2):428–452. doi: 10.3390/brainsci4020428. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Thomson JM, Goswami U. Rhythmic processing in children with developmental dyslexia: auditory and motor rhythms link to reading and spelling. Journal of Physiology-Paris. 2008;102(1–3):120–129. doi: 10.1016/j.jphysparis.2008.03.007. [DOI] [PubMed] [Google Scholar]

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