Influence of Music Therapy in the Understanding of Spoken Language in Users of Cochlear Implant

The cochlear implant is one of the most important recent technological advances in healthcare. The possibility of rehabilitating an individual with hearing loss not only provides him/her with auditory sensory input, but also makes it possible for his/her integration in the educational, social and emotional spheres. Prescribed for severe and profound hearing loss where the participant does not experience satisfactory gain with hearing aids, cochlear implant sends electrical impulses to the auditory nerve to be encoded by the auditory system. (Bilger et al., 1977; Loizou, 1999)

The coding system of sound in the cochlear implant is complex and involves several steps. The greatest concern is related to more accurate translation of the aspects of timing and frequency of sound. Therefore, devices have a strategy of signal encoding, responsible for maintaining the characteristics of the auditory input. Over the years, the cochlear implant has undergone great technological advancement: the sound has better resolution; and in certain devices, there is an option of algorithms capable of, for instance, minimizing noise, wind effects, and strengthening fine temporal aspects in music. However, users still have complaints, primarily related to situations in which it is difficult to listen, such as conversations in the presence of noise or competitive sounds; certain users have a low performance of speech understanding. (McDermott, 2004; Tanamati, 2011)

In the process of prescription and use of cochlear implant, auditory training provides increased performance of the individual’s hearing abilities (Scaranello, 2005). One approach in auditory training is music therapy. Although musical perception in cochlear implant users is reduced due to technical limitations, including processing of acoustic signals, special specificity from individual electrodes and the amount of current spread in the cochlea; music remains a powerful tool in terms of neuronal plasticity and learning capacity of the auditory system through training (Looi et al., 2012). The use of music therapy is described in the literature as a way of stimulating auditory processing in various conditions (Gutgsell et al., 2013; Raglio et al., 2012). Due to music’s complexity, it can activate various brain areas with a simple melody. Studies conducted in aphasic participants and those with brain damage reveal that other functions can be normal when musical perception is altered, and the same happens when there is impairment in language and musical perception remains intact. This finding demonstrates the principle of decoupling, implying functional and anatomical specificity in music. (Thaut & McIntosh, 2010; Thaut et al., 2014)

In a cognitive-neuropsychological approach, the researchers (Peretz et al., 2003) proposed a model showing the distribution of the auditory input in diverse processing areas. According to the authors, music triggers the language processing system (speech) and the musical processing system in parallel. Therefore, the lyrics of a song would be processed in the language system, and the musical input would be parsed in two parallel and independent systems: one for the melodic dimension and the other for the temporal dimension. Thus, melody and rhythm send analyses to the repertoire which, in turn, activate representations from other systems, such as lexical representations, associative memories and feelings of acquaintance, even if the musical excerpt is not named.

Hence, a hypothesis was proposed: music therapy could be a useful tool for stimulating and promoting the improvement of auditory skills in individuals with implants, thereby aiding their understanding of spoken language. The objective of the current research was to verify the influence of music therapy on spoken language comprehension in participants who are post-lingual users of cochlear implants.

This research complies with the rules of the ethics committee and was approved by the Ethics committee of the institution where it was carried out. Participants in the study were participants with post-lingual bilateral sensorineural hearing loss of severe or profound degree. The participants made use of unilateral cochlear implant for at least one year. The participants had not previously studied music in a formal way, and they had a hearing threshold with a CI of at least 30 dBNA in the sound-field in the frequencies of 0.5 kHz, 1 kHz, 2 kHz, 3 kHz and 4 kHz. Functional gain was achieved only with the use of cochlear implant in those participants who used contralateral hearing aids. Participants were not in speech therapy when the study was conducted.

Participants underwent an initial interview, pure tone and vocal audiometry and audiometry with functional gain. For the evaluation of speech comprehension, a list of phonetically-balanced sentences was used (Valente, 1998) presented in sound field (with no visual clue), 0-degree azimuth, with the participant at a distance of 60 cm from loudspeakers. The presentation was performed at the intensity of 40 dBNS above the speech reception threshold or speech detection threshold researched during the functional gain. As all the participants had hearing threshold with the cochlear implant of up to 30 dBNA; therefore, the presentation of the sound field phrases did not exceed 70 dBNA. The set of lists of phrases used was formed by 10 lists, each of which had 10 phonetically-balanced sentences. Each list contained 50 words, scored and doubled for each hit. Participants were evaluated with the phrases at three different moments: Evaluation 1, before any intervention, conducted after history taking; Evaluation 2, conducted after the home activity period, before the music therapy; and Evaluation 3, the final evaluation, after music therapy. For each evaluation was randomly chosen a list of phrases from the set of options of the 10 lists available.

Participants who presented a percentage over 80% of comprehension of sentences underwent evaluation of sentence in noise comprehension (speech noise), in a S/N ratio of +10 dB.

All participants underwent a home activity period. The purpose of this step was to assess the test-retest effect, providing the study with more transparency. This period involved requesting the participant to watch/listen to some TV or radio news reports twice a week for four weeks. At the end of each week, the evaluator asked questions regarding the news reports to confirm the completion of the task. This evaluation was conducted via phone or cell phone message and was directly with the participant, and when this was not possible, it was performed by any relative/caregiver. Participants who did not have sufficient auditory comprehension to understand the news they listened to, described information based on visual images, in the case of TV. This period was shorter than the therapy period because of participant adherence. The current study included adult participants and all participants had daily life activities. The drop-out rate during the long process could be greater.

After the daily activity phase, within one week, the participants underwent Evaluation 2 followed by musical training. This training consisted of activities prepared by the researcher, as well as software use and home work.

For auditory training, all participants underwent sessions held once a week, lasting 40 minutes for 10 weeks in a quiet environment and always monitored by the speech therapist. There was no closed protocol training because the performance of each participant was different and the activities were performed according to each participant’s needs. The exercises used involved auditory training software, a keyboard used for the execution of well-known children's songs and use of songs brought by the participants that suited their musical tastes (the types varied between gospel, Brazilian popular music and samba).

The activities that involved the use of software mainly worked bottom-up skills, since the exercises involved, for example, discrimination exercises and ordering of frequency and tone length, perception of rhythm and meter, melodic contour recognition, timbre recognition and temporal resolution training. The musical activities (with lyrics or even using a keyboard) involved top-down abilities, since often the presented songs had already been listened to by the participants in the past, prior to hearing loss. Therefore, there were visual clues with lyrics of songs and word gaps, for example. In every session, activities on the keyboard were carried out. The chosen songs were children’s songs, such as "I threw the stick on the cat." Children songs were chosen because they are well-known, and they have short sequences.

The difficulty level was progressive, and it was changed when the participant achieved more than 70% correct responses in a given activity. This percentage was chosen such that the exercises were challenging, that is, not very easy but not very difficult, with the latter being liable to cause frustration to the participant. In addition, active training was always prioritized, in which the participant was involved and participated in the activities because this type of condition improves and accelerates the auditory learning more than does passive training (Looi et al., 2012). Those who used contralateral hearing aids during therapy only used CI.

Regarding home training, the plan was for the participant to carry out the activities at least 3 times a week, 20 minutes a day. The decision not to carry out very extensive training was due to the fact that the participants had other activities of personal life; therefore, excess activities could cause the participant to give up the training. Home activities were recorded on a memory card, and the participant had to resolve the exercises and record their answers on handouts that were checked by the therapist before the start of each therapy session. The activities were always related to what had been proposed in face-to-face therapy. In addition, participants were encouraged to listen to music of any style. This time of activity varied greatly among the participants because it depended on each participant’s availability.

Finally, all participants underwent reassessment after the training (Evaluation 3).

There were 9 individuals (4 males and 5 females) aged between 34 and 68 years with a mean age of 52 ± 11.2 years. All participants had previously performed auditory therapy, since this therapy is part of the CI protocol. All participants had finished this training in at least six months.

The individual characteristics of the participants in this study (n = 9) are shown in Table 1.

Subject	Age	Gender	Processor/ strategy	Aetiology	Deafness time (years)	Time of CI Use (years)
1	67	M	opus2/fs4	idiopathic	47	3
2	55	F	n6/ace	otosclerosis	40	11
3	34	M	n6/ace	ototoxic	29	5
4	52	M	opus2/fs4	meningitis	40	2
5	54	F	harmony/HiRes120	idiopathic	30	6
6	51	F	harmony/HiRes120	meningitis	42	17
7	51	F	n5/ace	familiar	39	11
8	38	F	naida/HiRes Optima	idiopathic	30	1
9	68	M	naida/HiRes Optima	idiopathic	28	3
Average (SD)	52 (± 11.2)	N/A	N/A	N/A	39 (± 6.9)	5 (± 5.3)

As can be seen in Table 1, the characteristics of the participants were heterogeneous, including the external processor model and speech coding strategy. We observed that 4 of the 9 participants used MEDEL brand, 3 used Cochlear and only 2 used Advanced Bionics. All participants were adults and had a long time of sensory deprivation.

During the initial interview, all participants reported that they used daily CI, removing them only for bathing and sleeping (daily average use of 17 hours).

Table 2 shows the performance of each participant in the test of speech comprehension with sentences in the three parts of the evaluation.

Table 2. Test performance for each participant in all the evaluations carried out

Subject	Evaluation1 (%)	Evaluation 2 (%)	Evaluation 3 (%)
1	64	82	72
2	84	92	98
3	0	0	14
4	0	0	26
5	44	46	64
6	8	10	16
7	76	94	98
8	36	30	82
9	14	10	14

According to Table 2, only 1 of the 9 participants did not improve their performance in the speech test after the musical training (participant 9). In addition, 3 of the 9 individuals showed improvement between the evaluation 1 and 2, that is, before the auditory training. This finding may be explained by intrinsic factors, including motivation and attention, since it is a behavioural test. Finally, 6 of the 9 participants showed improvement after the auditory training. We also observed that the performance among the participants varied considerably, and was not associated with any type of specific characteristic (implant brand, participant age, deafness time).

Table 3 shows the results of the test of speech-in-noise understanding for each participant, in 1, 2 and 3 scored 80% or over on the speech test in silence.

Table 3. Description of the performance of the five individuals who took the test of speech-in-noise in Evaluations 1, 2 and 3

	SIN (1) %	SIN (2) %	SIN (3) %
Subject 1	-	64	-
Subject 2	80	82	80
Subject 7	-	86	74
Subject 8	-	-	56

SIN = speech-in-noise; SIN (1) = evaluation 1; SIN (2) = evaluation 2, SIN (3) = evaluation 3.

All participants who performed the speech test with noise performed worse than they did in the context of silence. This type of performance was expected, since situations of difficult listening, such as the presence of noise, is one of the limitations of hearing aids. Only 1/9 were able to perform this test in evaluation 1, 3 in evaluation 2, and 3 in evaluation 3.

The sample of this study was small and it was not possible to use parametric tests, so non-parametric statistical tests were used in all of the analyses. For the comparison between the three evaluation periods, we used analysis of variance of Friedman's repeated measures. The test of the posts with signs of Wilcoxon was conducted for pair-wise comparisons and effect size were calculated (r). The analysis were conducted using Statistical Package for the Social Sciences (SSPS, version 20). The level of significance (P) adopted was 0.05 (5%).

Table 4 presents the descriptive statistics of the tests used in evaluations 1, 2 and 3 and the comparisons between them.

Table 4. Descriptive statistics of the performance of the individuals in the tests used during the three study evaluation moments

	Speech test %
Periods	1	2	3
Average	36.22	40.44	53.78
Medium	36.00	30.00	64.00
Standard deviation	32.81	39.56	36.24
Minimum	0.00	0.00	14.00
Maximum	84.00	94.00	98.00

Friedman's repeated measures of variance analysis showed that there was a statistically significant difference between the conducted assessments (χ2 (2) = 10.97, P = 0.004).

Wilcoxon signal testing was used for multiple comparisons. A Bonferroni correction was applied and all effects were tested with a significance level of 0.0167. The results appeared to show that there was a statistically significant difference between moments 2 and 3 (T = 40, r = -0.69) and 1 and 3 (T = 36, r = -0.84).

This study evaluated the test results of comprehension of sentences in post-lingual adult participants using cochlear implants. We observed heterogeneous patterns in the study participants (Table 1), each with his/her specific characteristics. This pattern could also be observed in each participant’s results in terms of their speech understanding test results (Table 2). This variability is described in other studies and is explained by numerous factors that can affect the results among the implanted participants. Researchers reported about the anatomical characteristics, including remaining neuronal fibers, and theirs relevance for cochlear implantation (Nadol, 1997; Rask-Andersen et al., 2015). Hanekom and Shannon (1998) in their study about electrodes interactions, indicated the possibility of deterioration of speech recognition ability in function of the number of neural population active in electrical stimulus that may cause an overlapping of neurons active. Other authors explained about cortical function and plasticity in CI outcomes. There is a consensus of the importance of the deprivation sensory time. In infants were observed that more satisfactory performance in children has been obtained in those submitted to implantation until the time closer to typical speech development (Leigh et al., 2016). In adults the long time of deprivation can result in poorly outcomes (Francis et al., 2015). Also, the pathology can contribute in performance in CI users. In case of meningitis, for example, it can show some implications due to a soft tissue neoformation in cochlea (cochlear obliteration) or intracochlear osteoneogenesis (cochlear ossification), and even the presence of additional central nervous system disorders post-meningitis. (Bayazit et al., 2016)

We observed that only participants 1, 2, 7 and 8 performed the speech-in-noise test (Table 3) and that there was a diminished understanding by these individuals in the presence of noise, because of the difficulties implanted participants experienced in this situation. This occurs due to the loss of hearing standards that control background noise and emphasize speech signals in normal hearing. Although the external processors of cochlear implant tend to improve over time, participants have a lower performance than do normal listeners (Glasberg et al., 1987; Johannesen et al., 2016). The cochlear implants cannot provide more refined features of acoustic stimuli that are essential for situations of difficult listening such as speech-in-noise, for example, and in musical perception, although there was considerable variability in the performance of implanted individuals. (Limb & Roy, 2014; Gfeller et al., 2015)

In this study, no statistically significant differences were observed between Evaluations 1 and 2 on the speech test. This suggests that activities requested by the therapist in the home activity period (watching TV news or listening to the radio) did not affect the auditory performance of the participants throughout the study, and that the performance of the participants did not change in the reapplication of the test, before the intervention.

However, we observed that participants 1 and 7, who did not reach the top 80% in the speech test (here proposed) in Evaluation 1, did reach it in Evaluation 2. A possible explanation for this finding is the influence of factors such as attention and motivation, and even the evaluator-participant relationship in behavioural tests. The speech test used is scored by each word in the phrase, i.e., if the participant becomes distracted or nervous over a short time, it may be sufficient for his/her score to decrease.

After music therapy, a statistically significant difference was observed in the test results of sentence comprehension (Table 4). We observed after the analysis that there was a difference between periods 2 and 3 and between 1 and 3. Specifically, Table 2 shows individual scores: all participants improved speech understanding, except participant 1, including those who had scores of zero in previous evaluations. Table 3 shows score improvements, even in speech-in-noise situations. Music is an instrument of rehabilitation with great potential. It simultaneously activates diverse brain areas, including peripheral auditory pathways, primary cortex, insula, anterior and lateral temporal lobe, parietal lobe, frontal lobe and even occipital lobe (Griffiths & Warren, 2002; Patterson et al., 2002; Warren et al., 2003; Satoh et al., 2006). Regarding language processing, there is a parallel operation to the system of musical processing (Breitling et al., 1987; Polk & Kertesz, 1993; Peretz et al., 2003). In training involving music, there is expected to be a generalization for the neural coding of speech, thereby promoting an improvement of listening comprehension in implanted participants (Kraus et al., 2009). In addition, when there is therapeutic work with active participation of the individual, music promotes sustained attention, excitement, sense of reward and positive mood. (Gfeller et al., 2000; Herholz & Zatorre, 2012)

In this study, two approaches to auditory training were used. The first was the analytical approach that emphasizes bottom-up perceptual processes. In this approach, participants carried out activities involving the analysis of elements with musical characteristics, e.g. judging and distinguishing various timbres, pitches, rhythms, and identification of gaps and even of musical excerpt contours. The aim of using these resources was to increase the efficiency in processing along auditory pathways (Moore & Amitay, 2007; Strait et al., 2009).

The second approach was related to synthetic characteristics, or top-down features. This work aimed to promote more efficiency in central processing such as using contextual clues. For these activities, we used the following: lyrics of known songs and of songs unknown to the participant in order to complete sentences and paragraphs; attention directed to the singer’s voice with a background musical instrument; and keyboards for practising children songs, thereby promoting the integration of visual, motor and auditory systems. Specifically involving the test used in the evaluations of the present study, this approach helped the participants to realize that even though he/she does not understand all of the words of a sentence, by deduction, the participant can judge the word that would fit the sentence better, making sense. This tool can be used in daily prosthesis users.

Mitani et al. (2007), found higher scores of words recognition in implanted children with early home music exposure. In another study (Yucel et al., 2009), the researchers found improvement of implanted children in music auditory skills who had been treated with music therapy, but they did not observe a significant difference regarding speech perception in closed, semi-open and open sets. In the present study, we observed improvement in speech understanding after music therapy, accomplished through evaluation of a wordlist.

Although we observed significant differences after auditory training, we observed a high value of standard deviation. Studies involving cochlear implant are often influenced by many variables. It is impossible to fully measure all factors that result in the performance of individual device users and to separate them by group. The same pathology, for example, may present different results, or even the time of deprivation can be difficult to measure, since many participants become aware of hearing loss after the thresholds were below the sounds of a conversation. Although there are all these factors, it was possible to verify that music can serve as a working tool in cochlear implant users. In addition to improved speech comprehension, participants in this study reported an increased habit of listening to music. Music is present in all cultures and has a great social role in people's lives. Music can be used not only in isolation, as in the present study, but also in conjunction with other therapeutic approaches.

The findings of this study revealed a positive effect of music therapy on the speech understanding ability of post-lingual implanted adult participants, as there was a clear improvement in speech comprehension after music therapy. The music therapy that was developed could reveal the benefits of this type of stimulation in cochlear implant users, showing that music education can be presented even for those with hearing loss. This finding indicated that the proposed training was effective for the studied group.

Bayazit, Y., Kosaner, J., Celenk, F., Somdas, M., Yilmaz, I., Altin, G. et al. (2016). Auditory brainstem implant in postlingual post meningitic patients. Laryngoscope, 126,1889-1892. https://doi: 10.1002/lary.25731

Bilger, R.C., Black, F.O., Hopkinson, N.T. (1977). Research plan for evaluating participants presently fitted with implanted auditory prostheses. Annals of Otology, Rhinology & Laryngology, 86, 21-24. https://doi.org/10.1177/00034894770860S303

Breitling, D., Guenther, W., Rondot, P. (1987). Auditory perception of music measured by brain electrical activity mapping. Neuropsychologia, 25(5), 765-774. https://doi: 10.1016/0028-3932(87)90114-x.

Francis, H.W., Yeagle, J.A., Thompson, C.B. (2015). Clinical and psychosocial risk factors of hearing outcome in older adults with cochlear implants. Laryngoscope, 125, 695-702. https://doi.org/10.1002/lary.24921

Gfeller, K., Chris, A., Knust, J.F., Witt, S.A., Murray, K.T. (2000). Musical back-grounds, listening habits, and aesthetic enjoyment of adult cochlear implant recipients. Journal of the American Academy of Audiology, 11(7),390-406.

Gfeller, K., Guthe, E., Driscoll, V., Brown, C.J. (2015). A preliminary report of music-based training for adult cochlear implant users: rationales and development. Cochlear Implants, 16 (3), S22-31. https://doi:10.1179/1467010015Z.000000000269.

Glasberg, B.R., Moore, B.C.J., Bacon, S.P. (1987). Gap detection and masking in hearing-impaired and normal-hearing participants. Journal of the Acoustical Society of America, 81(5), 1546-56.

Griffiths, T.D., Warren, J.D. (2002). The planum temporale as a computational hub. Trends Neuroscience, 25(7), 348-53. https://doi: 10.1016/S0166-2236(02)02191-4.

Gutgsell, K.J., Schluchter, M., Margevicius, S., Degolia, P., McLaughlin, B., Harris, M. et al. (2013). Music therapy reduces pain in palliative care participants: a randomized controlled trial. Journal of Pain and Symptom Management, 45(5),822-831. https://doi: 10.106/j.jpainsymman.2012.05.008

Hanekom, J.J., Shannon, R.V. (1998). Gap detection as a measure of electrode interaction in cochlear implants. Journal of the Acoustical Society of America, 104(4), 2372-2384.

Herholz, S.C., Zatorre, R.J. (2012). Musical training as a framework for brain plasticity: behavior, function, and structure. Neuron,76(3),486-502. https://doi: 10.106/j.neuron.2012.10.011

Johannesen, P.T., Pérez-Gozález, P., Kalluri, S., Blanco, J.L., Lopes-Poveda, E.A. (2016). The influence of cochlear mechanical dysfunction, temporal processing deficits, and age on the intelligibility of audible speech in noise for hearing-impaired listeners. Trends in Hearing, 7,20. https://doi: 10.1177/2331216516641055

Kraus, N., Skoe, E., Parbery-Clark, A., Ashley, R. (2009). Experience-induced malleability in neural encoding of pitch, timbre, and timing-implications for language and music. Annals of the New York Academy of Sciences, 1169,543-57. https://doi: 10.1111/j.1749-6632.2009.04549.x

Leigh, J.R., Dettman, S.J., Dowell, R.C. (2016). Evidence based guidelines for recommending cochlear implantation for young children: audiological criteria and optimizing age at implantation. International Journal of Audiology, 55(2),S9-S18.

Limb, C.J., Roy, A.T. (2014). Technological, biological, and acoustical constraints to music perception in cochlear implant users. Hearing Research,308:13-26. https://doi: 10.1016/j.heares.2013.04.009.

Loizou, P.C. (1999). Introduction to cochlear implants. IEEE Engineering in Medicine and Biology Magazine, 18(1),32-42. https://doi: 10.1109/51.740962.

Looi, V., Gfeller, K., Driscoll, V. (2012). Music appreciation and training for cochlear implant recipients: a review. Seminars in Hearing, 33(4), 307-34. https://doi: 10.1055/s-0032-1329222.

McDermott, H.J. (2004). Music perception with cochlear implants: a review. Trends in Amplification, 8(2), 49-82. https://doi: 10.1177/108471380400800203.

Mitani, C., Nakata, T., Trehub, S.E., Kanda, Y., Kumagami, H., Takasaki, K., Miyamoto, I., Takahashi, H. (2007). Music recognition, music listening, and word recognition by deaf children with cochlear implants. Ear and Hearing, 28 (2),29S-33S. https://doi:10.1097/AUD.0b013e318031547a.

Moore, D.R., Amitay, S. (2007). Auditory training: rules and applications. Seminars in Hearing, 28(2),99-109. https://doi: 10.1055/s-2007-973436.

Nadol, J.B. (1997). Patterns of neural degeneration in the human cochlea and auditory nerve: Implications for cochlear implantation. Otolaryngology Head Neck Surgery, 117,220-8.

Patterson, R.D., Uppenkamp, S., Johnsrude, I.S., Griffiths, T.D. (2002). The processing of temporal pitch and melody information in auditory cortex. Neuron, 36(4),767-76. https://doi: 10.1016/S0896-6273(02)01060-7.

Peretz, I., Champod, A.S., Hyde, K. (2003). Varieties of musical disorders. The Montreal Battery of Evaluation of Amusia. Annals of the New York Academy of Sciences, 999, 58-75. https://doi: 10.1196/annals.1284.006.

Polk, M., Kertesz, A. (1993). Music and language in degenerative disease of the brain. Brain and Cognition, 22(1), 98-117. https://doi: 10.1006/brcg.1993.1027.

Raglio, A., Bellelli, G., Mazzola, P., Bellandi, D., Giovagnoli, A.R., Farina, E. et al. (2012). Music, music therapy and dementia: a review of literature and recommendations of the Italian Psychogeriatric Association. Maturitas, 72(4),305-10. https://doi:10.1016/j.maturitas.2012.05.016

Rask-Andersen, H., Liu, M. (2015). Auditory nerve preservation and regeneration in man: Relevance for cochlear implant. Neural Regeneration Research, 10, 710. https://doi:10.4103/1673-5374.156963

Satoh, M., Takeda, K., Nagata, K., Shimosegawa, E., Kuzuhara, S. (2006). Positron-emission tomography of brain regions activated by recognition of familiar music. American Journal Neuroadiology, 27(5), 1101-6.

Scaranello, C.A. (2005). Reabilitação auditiva pós implante coclear. Medicina (Ribeirão Preto), 38(3/4),273-8. https://doi: 10.11606/issn.2176-7262.v38i3/4p273-278.

Strait, D.L., Kraus, N., Skoe, E., Ashley, R. (2009). Musical experience promotes subcortical efficiency in processing emotional vocal sounds. Annals of the New York Academy of Sciences, 1169,209-13. https://doi: 10.1111/j.1749-6632.2009.04864.x.

Tanamati, L.F. (2011). Audição e inteligibilidade da fala de crianças após 10 anos da cirurgia de implante coclear [tese]. São Paulo: Universidade de São Paulo. https://doi:10.11606/T.5.2012.tde-11052012-133542.

Thaut, M.H., McIntosh, G.C. (2010). How music helps to heal the injured brain: therapeutic use crescendos thanks to advances in brain science. Cerebrum. Retrieved on February 02, 2020 from https://dana.org/article/how-music-helps-to-heal-the-injured-brain/

Thaut, M.H., Trimarchi, P.D., Parsons, L.M. (2014). Human brain basis of musical rhythm perception: common and distinct neural substrates for meter, tempo and pattern. Brain Sciences, 4(2),428-52. https://doi: 10.3390/brainsci4020428.

Valente S.L.O. (1998). Elaboração de listas de sentenças construídas na língua portuguesa [dissertação]. São Paulo: Pontifícia Universidade Católica.

Warren, J.D., Uppenkamp, S., Patterson, R.D., Griffiths, T.D. (2003). Separating pitch chroma and pitch height in the human brain. Proceedings of the National Academy of Sciences of the United States of America, 100(17), 10038-42. https://doi: 10.1073/pnas.1730682100.

Yucel, E., Sennaroglu, G., Belgin, E. (2009). The family oriented musical training for children with cochlear implants: speech and musical perception results of two years follow-up. International Journal of Pediatric Otorhinolaryngology, 73(7),1043-52. https://doi: 10.1016/j.ijporl.2009.04.009.