Auditory Processing in Musicians: History
Please note this is an old version of this entry, which may differ significantly from the current revision.

Μusicians are reported to have enhanced auditory processing. Auditory processing elements evaluated were speech recognition in babble, rhythmic advantage in speech recognition, short-term working memory, temporal resolution, and frequency discrimination threshold detection.

  • hearing
  • auditory processing
  • cognition
  • music

1. Background

Current research provides evidence of enhanced auditory processing in musicians, compared to non-musicians. Capitalizing on this neuroplasticity-based improvement may lead to more focused auditory training for individuals with Auditory Processing Disorder (APD) with the aim of better results and faster rehabilitation. Neuroplasticity, in this case, is the nervous system adaptation resulting from an active response to auditory stimuli. It involves connectivity changes for better performance, especially in related tasks [1]. Hearing is a prerequisite for communication, work, and learning for the average person as well as an essential sense for every musician. Hearing being evaluated by the gold standard pure-tone audiometry may be missing aspects of hearing that are important for everyday life [2]. An audiological evaluation may include speech audiometry as well as tympanometry, stapedial reflexes, otoacoustic emissions, and auditory brainstem responses depending on symptoms and the medical history of a given patient. Communication through the auditory modality needs intact temporal processing, speech in noise perception, working memory, and frequency discrimination [3][4]. Auditory processing happens at the level of the central auditory nervous system. Hearing (i.e., hearing sensitivity and auditory processing) contributes to the formation of cognition, and cognition contributes to hearing [4][5]. The superior auditory processing performance in musicians vs. non-musicians is explained by the enhanced usage and training of their hearing sense, emotion, and listening skills [6]. Musical training goes beyond auditory training to reading and comprehending complex symbols into motor activity [7]. Of interest, recent research shows that frequency precision is more correlated with musical sophistication than cognition [8].
The perception of music and speech is thought to be distinct, although sharing many acoustic and cognitive characteristics [9]. Pitch, timing, and timbre cues may be considered commonalities for auditory information transfer [10]. Memory and attention are required cognitive skills for both music and speech processing. Pitch is the psychoacoustic analogous of the frequency of the sound. Timing refers to specific turning points in the sound (for example, the beginning and the negation of the sound), and timbre is multidimensional and includes spectral and temporal features. Musicians’ superior auditory processing is attributed to enhanced accuracy of neural sound encoding [9][11][12][13] as well as better cognitive function [14][15]. The musical practice embraces the experience of specific sound ingredients as well as joint integration during the performance. Extracting meaning from a complex auditory scene may be a transferable skill to tracking a talker’s voice in a noisy environment [16].
Musicians are in an advantageous position in processing the pitch, timing, and timbre of music compared to non-musicians [17]. They demonstrate strengthened neural encoding of the timbre of their own instrument [18][19][20], but also show enhancements in processing speech [9][21][22][23][24][25] and non-verbal communication sounds [26]. Musical experience promotes a more accurate perception of meaningful sounds in communication contexts other than musical ones [9][12][23][27]. Music training is reported to change brain areas in a specific way that may be predicted by the performance requirements of the specific training instrument [28]. Musicians’ perceptual skills are influenced by the style of music played by them [29][30].
Auditory processing [31] consists of mechanisms that analyze, preserve, organize, modify, refine, and interpret information from the auditory signal. Skills that support these mechanisms are auditory discrimination, temporal and binaural processing, which are known as auditory processing elements. Temporal processing refers to auditory pattern recognition and temporal aspects of audition, divided into four subcomponents: temporal integration, temporal resolution/discrimination (e.g., gap detection), temporal ordering and temporal masking [32]. Sound localization and lateralization and auditory performance with challenging or degraded acoustic signals (including dichotic listening) [33] are included in binaural processing. Auditory discrimination involves the perception of acoustic stimuli in very rapid succession requiring the accuracy of information that is carried to the brain [34][35]. These processes may affect phoneme discrimination, speech in noise comprehension, duration discrimination, rhythm perception, and prosodic distinction [36][37]. Temporal resolution, defined as the shortest period over which the ear can discriminate two signals [38] may be linked to language acquisition and cognition in both children [39][40][41][42] and adults [43][44][45][46].
American Speech Language Hearing Association (ASHA) uses the term Central Auditory Processing Disorder (CAPD) to refer to deficits in neural processing, including bottom–up and top–down neural connectivity [47] of auditory information in the Central Auditory Nervous System (CANS) not as a consequence of cognition or higher order language [33]. Deficits in auditory information processing in the central nervous system (CNS) are demonstrated by poor performance in one or more elements of auditory processing [48]. (C)APD may coexist with, but is not derived from, dysfunction in other modalities. Despite the absence of any substantial audiometric findings, poor hearing and auditory comprehension are expressed in some cases in CAPD. Moreover, (C)APD can be associated with, co-exist or lead to difficulties in speech, language, attention, social, learning (e.g., spelling, reading), learning, and developmental functions [33][49]. In the international statistical classification of diseases and related health problems, 11th edition (ICD-11), auditory processing disorder (APD) is classified as AB5Y as a hearing impairment. (C)APD affects both children and adults, including the elderly [50], and it is linked to functional disorders beyond the cochlea [51][52]. According to WHO [49] prevalence estimates of APD in children range from 2–10% and can affect psychosocial development, academic achievement, social participation, and career opportunities.

2. Speech Perception in Noise

Speech perception in noise is at the core of auditory processing as the most easily explainable test with a real-life depiction. Temporal elements required to perceive speech may be similar to those needed for music with rhythm thought to stand as a bridge between speech and music [52]. Highly trained musicians have been reported in some studies to have superior performance on different measures of speech in noise [22][52][53][54] with this advantage not always being present [55][56][57].
The consolidating of the possible improved speech in noise perception of musicians may have rehabilitation implications for individuals with hearing impairment [55]. Research outcomes reveal that rhythm perception benefits are present at different levels of speech from words to sentences [58][59]. Percussionists were found to perform relatively better at the sentence in noise level compared to the words in noise one contrasted with vocalists while significantly outperforming non-musicians [52]. There is limited research evaluating speech perception in noise among musicians from different musical styles.

3. Temporal Resolution

Auditory temporal processing is the alteration of elements of duration within a specific time interval [50]. The ability of the auditory system to respond to rapid changes over time is a component of temporal processing called temporal resolution, linked to stopping consonants perception during a running speech [37][60].
Temporal processes are necessary for auditory processing and the perception of rhythm, pitch, duration, and separating foreground to background [3][36]. Chermak and Musiek [37] highlighted the role of temporal processing across a range of language processing skills, from phonemic to prosodic distinctions and ambiguity resolution. Temporal resolution underlies the discrimination of voiced from unvoiced stop consonants [61] and is clinically evaluated using Gaps-In-Noise [GIN] or Random Gap Detection Test [RGDT] [62]. Evaluating an individual’s ability to perceive a msec gap in noise or between two pure tones provides information on possible deficits in temporal resolution and can lead to a better shaping of rehabilitation [50]. Older adults generally are found to have poorer (longer) gap thresholds than younger adults [5].
Early exposure to frequent music training for years improves timing ability across sensory modalities [63]. Musicians present with better temporal resolution [64][65][66][67][68]. Musicians of different instruments and styles were found to have superior timing abilities compared to non-musicians [65][69]. Longer daily training in music leads to a better gap detection threshold [70]. Neuroplasticity as a result of music training results in enhanced temporal resolution in children that are comparable to adults [66]. No research publications exist evaluating possible differences in temporal resolution across musicians from different musical styles.

4. Working Memory

Auditory and visual memory skills are enhanced in musicians and linked with early, frequent, and formal musical training [4][22][71][72][73][74][75][76][77][78][79][80][81][82][83][84][85][86]. In rare cases, no difference is documented [55] between musicians and non-musicians. A meta-analysis reported a medium effect on short-term working memory with musicians being better. The advantage was large with tonal stimuli, moderate with verbal stimuli, and small or null with visuospatial stimuli [82]. This points to an auditory-specific working memory advantage rather than a more general one. Working memory improves due to auditory processing being enhanced through music education; hearing improves cognition.

5. Frequency Discrimination

During speech processing, the pitch has hyper-linguistic characteristics that provide information on emotion and intent [87] as well as linguistic characteristics. Musicians outperform non-musicians [13][22][65][69][84][88][89][90][91][92][93][94]. This advantage was hypothesized to be a contributing factor in better speech-in-noise perception found in musicians [22]. Classical musicians were reported to have superior frequency discrimination abilities when compared to those with contemporary music (e.g., jazz, modern) background [95]. There is no study researching possible differences across different musical styles that include Byzantine music.

6. Different Music Styles and Instruments

The musicians’ groups selected for the present study differ in styles and music training. Byzantine music (BM), or Byzantine chant (BC), is the traditional ecclesiastical music of the Orthodox church. It is vocal music sung by one or more chanters [96] always having a monophonic character based on eight modes (“echos”) [97]. The chanters are usually male and there is no musical instrument involved apart from the human voice [98][99]. This is in contrast with Western classical music that is polyphonic, frequently including male and female voices in the presence of instruments. Percussionists are vastly trained in rhythmic skills and timing physical flexibility and in this research are experienced in both tuned and untuned percussions.
The ordinary tuning system for Western music is the 12 equal temperament tuning system which subdivides the octave interval into 12 tones (semitones) [99]. By contrast, the BC tuning system divides the octave into 72 equal subdivisions or “moria”, according to the Patriarchal Music Committee (PMC) [100]. In comparison to Western music, where the octave is based on 12 equal units (semitones), BM has each semitone corresponding to 6 moria [96]. The elementary tone (a minor second) consists of 100 logarithmically equal micro-intervals called cents; thus, the octave consists of (12 semitones × 100 cents) 1200 cents [101]. PMC’s musician experts indicate [100] that the less audible music interval is considered to be 1 m or 16.7 c, a critically smaller interval relevant to classical music. Likewise, Sunberg [102] argues that an interval of 20 cents (1.2 moria) is hardly heard by a listener. In BM, each micro-interval differs from its neighbors by at least 2 moria [99] and the frequency steps made in Byzantine music, compared to Western music, may vary from even 1 Hz in the bass voice range.

This entry is adapted from the peer-reviewed paper 10.3390/healthcare11142027


  1. Chatterjee, D.; Hegde, S.; Thaut, M. Neural Plasticity: The Substratum of Music-Based Interventions in Neurorehabilitation. NeuroRehabilitation 2021, 48, 155–166.
  2. Bamiou, D.-E. Aetiology and Clinical Presentations of Auditory Processing Disorders—A Review. Arch. Dis. Child. 2001, 85, 361–365.
  3. Chermak, G.D.; Lee, J. Comparison of Children’s Performance on Four Tests of Temporal Resolution. J. Am. Acad. Audiol. 2005, 16, 554–563.
  4. Rudner, M.; Rönnberg, J.; Lunner, T. Working Memory Supports Listening in Noise for Persons with Hearing Impairment. J. Am. Acad. Audiol. 2011, 22, 156–167.
  5. Iliadou, V.; Bamiou, D.E.; Sidiras, C.; Moschopoulos, N.P.; Tsolaki, M.; Nimatoudis, I.; Chermak, G.D. The Use of the Gaps-in-Noise Test as an Index of the Enhanced Left Temporal Cortical Thinning Associated with the Transition between Mild Cognitive Impairment and Alzheimer’s Disease. J. Am. Acad. Audiol. 2017, 28, 463–471.
  6. Quinto, L.; Thompson, W.F.; Keating, F.L. Emotional Communication in Speech and Music: The Role of Melodic and Rhythmic Contrasts. Front. Psychol. 2013, 4, 184.
  7. Schlaug, G.; Norton, A.; Overy, K.; Winner, E. Effects of Music Training on the Child’s Brain and Cognitive Development. Ann. N. Y. Acad. Sci. 2005, 1060, 219–230.
  8. Lad, M.; Billig, A.J.; Kumar, S.; Griffiths, T.D. A Specific Relationship between Musical Sophistication and Auditory Working Memory. Sci. Rep. 2022, 12, 3517.
  9. Kraus, N.; Chandrasekaran, B. Music Training for the Development of Auditory Skills. Nat. Rev. Neurosci. 2010, 11, 599–605.
  10. Kraus, N.; Skoe, E.; Parbery-Clark, A.; Ashley, R. Experience-Induced Malleability in Neural Encoding of Pitch, Timbre, and Timing: Implications for Language and Music. In Annals of the New York Academy of Sciences; Blackwell Publishing Inc.: Hoboken, NJ, USA, 2009; Volume 1169, pp. 543–557.
  11. Koelsch, S.; Schröger, E.; Tervaniemi, M. Superior Pre-Attentive Auditory Processing in Musicians. Neuroreport 1999, 10, 1309–1313.
  12. Strait, D.L.; Kraus, N. Biological Impact of Auditory Expertise across the Life Span: Musicians as a Model of Auditory Learning. Hear. Res. 2014, 308, 109–121.
  13. Tervaniemi, M.; Just, V.; Koelsch, S.; Widmann, A.; Schroger, E. Pitch Discrimination Accuracy in Musicians vs Non-musicians: An Event-Related Potential and Behavioral Study. Exp. Brain Res. 2005, 161, 1–10.
  14. Forgeard, M.; Winner, E.; Norton, A.; Schlaug, G. Practicing a Musical Instrument in Childhood Is Associated with Enhanced Verbal Ability and Nonverbal Reasoning. PLoS ONE 2008, 3, e3566.
  15. Kraus, N.; Strait, D.L.; Parbery-Clark, A. Cognitive Factors Shape Brain Networks for Auditory Skills: Spotlight on Auditory Working Memory. Ann. N. Y. Acad. Sci. 2012, 1252, 100–107.
  16. Slater, J.; Skoe, E.; Strait, D.L.; O’Connell, S.; Thompson, E.; Kraus, N. Music Training Improves Speech-in-Noise Perception: Longitudinal Evidence from a Community-Based Music Program. Behav. Brain Res. 2015, 291, 244–252.
  17. Tzounopoulos, T.; Kraus, N. Learning to Encode Timing: Mechanisms of Plasticity in the Auditory Brainstem. Neuron 2009, 62, 463–469.
  18. Margulis, E.H.; Mlsna, L.M.; Uppunda, A.K.; Parrish, T.B.; Wong, P.C.M. Selective Neurophysiologic Responses to Music in Instrumentalists with Different Listening Biographies. Hum. Brain Mapp. 2009, 30, 267–275.
  19. Pantev, C.; Roberts, L.E.; Schulz, M.; Engelien, A.; Ross, B. Timbre-Specific Enhancement of Auditory Cortical Representations in Musicians. Neuroreport 2001, 12, 169–174.
  20. Strait, D.L.; Chan, K.; Ashley, R.; Kraus, N. Specialization among the Specialized: Auditory Brainstem Function Is Tuned in to Timbre. Cortex 2012, 48, 360–362.
  21. Besson, M.; Chobert, J.; Marie, C. Transfer of Training between Music and Speech: Common Processing, Attention, and Memory. Front. Psychol. 2011, 2, 94.
  22. Parbery-Clark, A.; Skoe, E.; Lam, C.; Kraus, N. Musician Enhancement for Speech-In-Noise. Ear Hear. 2009, 30, 653–661.
  23. Patel, A.D. Why Would Musical Training Benefit the Neural Encoding of Speech? The OPERA Hypothesis. Front. Psychol. 2011, 2, 142.
  24. Patel, A.D.; Iversen, J.R. The Linguistic Benefits of Musical Abilities. Trends Cogn. Sci. 2007, 11, 369–372.
  25. Strait, D.L.; Parbery-Clark, A.; Hittner, E.; Kraus, N. Musical Training during Early Childhood Enhances the Neural Encoding of Speech in Noise. Brain Lang. 2012, 123, 191–201.
  26. Strait, D.L.; Kraus, N.; Skoe, E.; Ashley, R. Musical Experience and Neural Efficiency—Effects of Training on Subcortical Processing of Vocal Expressions of Emotion. Eur. J. Neurosci. 2009, 29, 661–668.
  27. Patel, A.D. Can Nonlinguistic Musical Training Change the Way the Brain Processes Speech? The Expanded OPERA Hypothesis. Hear. Res. 2014, 308, 98–108.
  28. Elbert, T.; Pantev, C.; Wienbruch, C.; Rockstroh, B.; Taub, E. Increased Cortical Representation of the Fingers of the Left Hand in String Players. Science 1995, 270, 305–307.
  29. Vuust, P.; Brattico, E.; Seppänen, M.; Näätänen, R.; Tervaniemi, M. Practiced Musical Style Shapes Auditory Skills. Ann. N. Y. Acad. Sci. 2012, 1252, 139–146.
  30. Vuust, P.; Brattico, E.; Seppänen, M.; Näätänen, R.; Tervaniemi, M. The Sound of Music: Differentiating Musicians Using a Fast, Musical Multi-Feature Mismatch Negativity Paradigm. Neuropsychologia 2012, 50, 1432–1443.
  31. Medwetsky, L. Spoken Language Processing Model: Bridging Auditory and Language Processing to Guide Assessment and Intervention. Lang. Speech Hear. Serv. Sch. 2011, 42, 286–296.
  32. American Speech-Language-Hearing Association. Central auditory processing: Current status of research and implications for clinical practice. Am. J. Audiol. 1996, 5, 41–54.
  33. American Speech-Language-Hearing Association. (Central) Auditory Processing Disorders—The Role of the Audiologist; American Speech-Language-Hearing Association: Rockville, MD, USA, 2005.
  34. Monteiro, A.R.M.; Nascimento, M.F.; Soares, D.C.; Ferreira, I.M.D.D.C. Temporal Resolution Abilities in Musicians and No Musicians Violinists Habilidades de Resolução Temporal Em Músicos Violinistas e Não Músicos. Int. Arch. Otorhinolaryngol. 2010, 14, 302–308.
  35. Samelli, A.G.; Schochat, E. The Gaps-in-Noise Test: Gap Detection Thresholds in Normal-Hearing Young Adults. Int. J. Audiol. 2008, 47, 238–245.
  36. Phillips, D.P. Central Auditory System and Central Auditory Processing Disorders: Some Conceptual Issues; Thieme Medical Publishers, Inc.: New York, NY, USA, 2002; Volume 23.
  37. Chermak, G.D.; Musiek, F.E. Central Auditory Processing Disorders: New Perspectives; Singular Pub Group: San Diego, CA, USA, 1997.
  38. Gelfand, S.A. Hearing: An Introduction to Psychological and Physiological Acoustics; Informa Healthcare: London, UK, 2010.
  39. Griffiths, T.D.; Warren, J.D. The Planum Temporale as a Computational Hub. Trends Neurosci. 2002, 25, 348–353.
  40. Hautus, M.J.; Setchell, G.J.; Waldie, K.E.; Kirk, I.J. Age-Related Improvements in Auditory Temporal Resolution in Reading-Impaired Children. Dyslexia 2003, 9, 37–45.
  41. Walker, M.M.; Shinn, J.B.; Cranford, J.L.; Givens, G.D.; Holbert, D. Auditory Temporal Processing Performance of Young Adults with Reading Disorders. J. Speech Lang. Hear. Res. 2002, 45, 598–605.
  42. Rance, G.; McKay, C.; Grayden, D. Perceptual Characterization of Children with Auditory Neuropathy. Ear Hear. 2004, 25, 34–46.
  43. Fingelkurts, A.A.; Fingelkurts, A.A. Timing in Cognition and EEG Brain Dynamics: Discreteness versus Continuity. Cogn. Process. 2006, 7, 135–162.
  44. Bao, Y.; Szymaszek, A.; Wang, X.; Oron, A.; Pöppel, E.; Szelag, E. Temporal Order Perception of Auditory Stimuli Is Selectively Modified by Tonal and Non-Tonal Language Environments. Cognition 2013, 129, 579–585.
  45. Grube, M.; Kumar, S.; Cooper, F.E.; Turton, S.; Griffiths, T.D. Auditory Sequence Analysis and Phonological Skill. Proc. R. Soc. B Biol. Sci. 2012, 279, 4496–4504.
  46. Grube, M.; Cooper, F.E.; Griffiths, T.D. Auditory Temporal-Regularity Processing Correlates with Language and Literacy Skill in Early Adulthood. Cogn. Neurosci. 2013, 4, 225–230.
  47. Iliadou, V.; Ptok, M.; Grech, H.; Pedersen, E.R.; Brechmann, A.; Deggouj, N.; Kiese-Himmel, C.; Sliwinska-Kowalska, M.; Nickisch, A.; Demanez, L.; et al. A European Perspective on Auditory Processing Disorder-Current Knowledge and Future Research Focus. Front. Neurol. 2017, 8, 622.
  48. Musiek, F.E.; Shinn, J.; Chermak, G.D.; Bamiou, D.-E. Perspectives on the Pure-Tone Audiogram. J. Am. Acad. Audiol. 2017, 28, 655–671.
  49. Musiek, F.E.; Baran, J.A.; James Bellis, T.; Chermak, G.D.; Hall, J.W., III; Professor, C.; Keith, R.W.; Medwetsky, L.; Loftus West, K.; Young, M.; et al. American Academy of Audiology Clinical Practice Guidelines Guidelines for the Diagnosis, Treatment and Management of Children and Adults with Central Auditory Processing Disorder; American Academy of Audiology: Reston, VA, USA, 2010.
  50. Musiek, F.E.; Shinn, J.B.; Jirsa, R.; Bamiou, D.-E.; Baran, J.A.; Zaidan, E. GIN (Gaps-In-Noise) Test Performance in Subjects with Confirmed Central Auditory Nervous System Involvement. Ear Hear. 2005, 26, 608–618.
  51. Gilley, P.M.; Sharma, M.; Purdy, S.C. Oscillatory Decoupling Differentiates Auditory Encoding Deficits in Children with Listening Problems. Clin. Neurophysiol. 2016, 127, 1618–1628.
  52. Slater, J.; Kraus, N. The Role of Rhythm in Perceiving Speech in Noise: A Comparison of Percussionists, Vocalists and Non-Musicians. Cogn. Process. 2016, 17, 79–87.
  53. Coffey, E.B.J.; Mogilever, N.B.; Zatorre, R.J. Speech-in-Noise Perception in Musicians: A Review. Hear. Res. 2017, 352, 49–69.
  54. Hennessy, S.; Mack, W.J.; Habibi, A. Speech-in-noise Perception in Musicians and Non-musicians: A Multi-level Meta-Analysis. Hear. Res. 2022, 416, 108442.
  55. Boebinger, D.; Evans, S.; Rosen, S.; Lima, C.F.; Manly, T.; Scott, S.K. Musicians and Non-Musicians Are Equally Adept at Perceiving Masked Speech. J. Acoust. Soc. Am. 2015, 137, 378–387.
  56. Fuller, C.D.; Galvin, J.J.; Maat, B.; Free, R.H.; Başkent, D. The Musician Effect: Does It Persist under Degraded Pitch Conditions of Cochlear Implant Simulations? Front. Neurosci. 2014, 8, 179.
  57. Ruggles, D.R.; Freyman, R.L.; Oxenham, A.J. Influence of Musical Training on Understanding Voiced and Whispered Speech in Noise. PLoS ONE 2014, 9, e86980.
  58. Sidiras, C.; Iliadou, V.; Nimatoudis, I.; Reichenbach, T.; Bamiou, D.E. Spoken Word Recognition Enhancement Due to Preceding Synchronized Beats Compared to Unsynchronized or Unrhythmic Beats. Front. Neurosci. 2017, 11, 415.
  59. Sidiras, C.; Iliadou, V.V.; Nimatoudis, I.; Bamiou, D.E. Absence of Rhythm Benefit on Speech in Noise Recognition in Children Diagnosed with Auditory Processing Disorder. Front. Neurosci. 2020, 14, 418.
  60. Iliadou, V.; Bamiou, D.E.; Chermak, G.D.; Nimatoudis, I. Comparison of Two Tests of Auditory Temporal Resolution in Children with Central Auditory Processing Disorder, Adults with Psychosis, and Adult Professional Musicians. Int. J. Audiol. 2014, 53, 507–513.
  61. Elangovan, S.; Stuart, A. Natural Boundaries in Gap Detection Are Related to Categorical Perception of Stop Consonants. Ear Hear. 2008, 29, 761–774.
  62. Keith, R. Random Gap Detection Test; Auditec: St. Louis, MO, USA, 2000.
  63. Rammsayer, T.H.; Buttkus, F.; Altenmüller, E. Musicians Do Better than Non-musicians in Both Auditory and Visual Timing Tasks. Music Percept. 2012, 30, 85–96.
  64. Donai, J.J.; Jennings, M.B. Gaps-in-Noise Detection and Gender Identification from Noise-Vocoded Vowel Segments: Comparing Performance of Active Musicians to Non-Musicians. J. Acoust. Soc. Am. 2016, 139, EL128–EL134.
  65. Kumar, P.; Sanju, H.; Nikhil, J. Temporal Resolution and Active Auditory Discrimination Skill in Vocal Musicians. Int. Arch. Otorhinolaryngol. 2015, 20, 310–314.
  66. Rammsayer, T.; Altenmüller, E. Temporal Information Processing in Musicians and Non-musicians. Music Percept. 2006, 24, 37–48.
  67. Van Ryn, F., Jr.; Lüders, D.; Casali, R.L.; Amaral, M.I.R.D. Temporal Auditory Processing in People Exposed to Musical Instrument Practice. Codas 2022, 34, e20210256.
  68. Sangamanatha, V.A.; Bhat, J.; Srivastava, M. Temporal Resolution in Individuals with and without Musical Training Perception of Spectral Ripples and Speech Perception in Noise by Older Adults View Project. 2012. Available online: (accessed on 22 February 2023).
  69. Tervaniemi, M.; Janhunen, L.; Kruck, S.; Putkinen, V.; Huotilainen, M. Auditory Profiles of Classical, Jazz, and Rock Musicians: Genre-Specific Sensitivity to Musical Sound Features. Front. Psychol. 2016, 6, 713.
  70. Nascimento, F.; Monteiro, R.; Soares, C.; Ferreira, M. Temporal Sequencing Abilities in Musicians Violinists and Non-Musicians. Arq. Int. Otorrinolaringol. 2014, 14, 217–224.
  71. Brandler, S.; Rammsayer, T.H. Differences in Mental Abilities between Musicians and Non-Musicians. Psychol. Music 2003, 31, 123–138.
  72. Chan, A.S.; Ho, Y.-C.; Cheung, M.-C. Music Training Improves Verbal Memory. Nature 1998, 396, 128.
  73. Franklin, M.S.; Sledge Moore, K.; Yip, C.-Y.; Jonides, J.; Rattray, K.; Moher, J. The Effects of Musical Training on Verbal Memory. Psychol. Music 2008, 36, 353–365.
  74. George, E.M.; Coch, D. Music Training and Working Memory: An ERP Study. Neuropsychologia 2011, 49, 1083–1094.
  75. Hallam, S.; Himonides, E. The Power of Music; Open Book Publishers: Cambridge, UK, 2022.
  76. Hansen, M.; Wallentin, M.; Vuust, P. Working Memory and Musical Competence of Musicians and Non-Musicians. Psychol. Music 2013, 41, 779–793.
  77. Jakobson, L.S.; Lewycky, S.T.; Kilgour, A.R.; Stoesz, B.M. Memory for Verbal and Visual Material in Highly Trained Musicians. Music Percept. 2008, 26, 41–55.
  78. Lee, Y.; Lu, M.; Ko, H. Effects of Skill Training on Working Memory Capacity. Learn. Instr. 2007, 17, 336–344.
  79. Pallesen, K.J.; Brattico, E.; Bailey, C.J.; Korvenoja, A.; Koivisto, J.; Gjedde, A.; Carlson, S. Cognitive Control in Auditory Working Memory Is Enhanced in Musicians. PLoS ONE 2010, 5, e11120.
  80. Parbery-Clark, A.; Strait, D.L.; Anderson, S.; Hittner, E.; Kraus, N. Musical Experience and the Aging Auditory System: Implications for Cognitive Abilities and Hearing Speech in Noise. PLoS ONE 2011, 6, e18082.
  81. Talamini, F.; Carretti, B.; Grassi, M. The Working Memory of Musicians and Non-musicians. Music. Percept. 2016, 34, 183–191.
  82. Talamini, F.; Altoè, G.; Carretti, B.; Grassi, M. Musicians Have Better Memory than Non-musicians: A Meta-Analysis. PLoS ONE 2017, 12, e0186773.
  83. Taylor, A.C.; Dewhurst, S.A. Investigating the Influence of Music Training on Verbal Memory. Psychol. Music 2017, 45, 814–820.
  84. Vasuki, P.R.M.; Sharma, M.; Demuth, K.; Arciuli, J. Musicians’ Edge: A Comparison of Auditory Processing, Cognitive Abilities and Statistical Learning. Hear. Res. 2016, 342, 112–123.
  85. Wallentin, M.; Nielsen, A.H.; Friis-Olivarius, M.; Vuust, C.; Vuust, P. The Musical Ear Test, a New Reliable Test for Measuring Musical Competence. Learn. Individ. Differ. 2010, 20, 188–196.
  86. Zuk, J.; Benjamin, C.; Kenyon, A.; Gaab, N. Behavioral and Neural Correlates of Executive Functioning in Musicians and Non-Musicians. PLoS ONE 2014, 9, e99868.
  87. Belin, P. Voice Processing in Human and Non-Human Primates. Philos. Trans. R. Soc. B Biol. Sci. 2006, 361, 2091–2107.
  88. Bianchi, F.; Santurette, S.; Wendt, D.; Dau, T. Pitch Discrimination in Musicians and Non-Musicians: Effects of Harmonic Resolvability and Processing Effort. J. Assoc. Res. Otolaryngol. 2016, 17, 69–79.
  89. Inabinet, D.; De La Cruz, J.; Cha, J.; Ng, K.; Musacchia, G. Diotic and Dichotic Mechanisms of Discrimination Threshold in Musicians and Non-Musicians. Brain Sci. 2021, 11, 1592.
  90. Magne, C.; Schön, D.; Besson, M. Musician Children Detect Pitch Violations in Both Music and Language Better than Nonmusician Children: Behavioral and Electrophysiological Approaches. J. Cogn. Neurosci. 2006, 18, 199–211.
  91. Micheyl, C.; Delhommeau, K.; Perrot, X.; Oxenham, A.J. Influence of Musical and Psychoacoustical Training on Pitch Discrimination. Hear. Res. 2006, 219, 36–47.
  92. Musacchia, G.; Sams, M.; Skoe, E.; Kraus, N. Musicians Have Enhanced Subcortical Auditory and Audiovisual Processing of Speech and Music. Proc. Natl. Acad. Sci. USA 2007, 104, 15894–15898.
  93. Toh, X.R.; Tan, S.H.; Wong, G.; Lau, F.; Wong, F.C.K. Enduring Musician Advantage among Former Musicians in Prosodic Pitch Perception. Sci. Rep. 2023, 13, 2657.
  94. Tervaniemi, M.; Huotilainen, M.; Brattico, E. Melodic Multi-Feature Paradigm Reveals Auditory Profiles in Music-Sound Encoding. Front. Hum. Neurosci. 2014, 8, 496.
  95. Kishon-Rabin, L.; Amir, O.; Vexler, Y.; Zaltz, Y. Pitch Discrimination: Are Professional Musicians Better than Non-Musicians? J. Basic Clin. Physiol. Pharmacol. 2001, 12, 125–143.
  96. Delviniotis, D.; Kouroupetroglou, G.; Theodoridis, S. Acoustic Analysis of Musical Intervals in Modern Byzantine Chant Scales. J. Acoust. Soc. Am. 2008, 124, EL262–EL269.
  97. Wellesz, E. A History of Byzantine Music and Hymnography; Clarendon Press: Oxford, UK, 1961.
  98. Baloyianis, S. Psaltic art and the brain: The philosophy of the Byzantine music from the perspectives of the neurosciences. In Proceedings of the 1st International Interdisciplinary Musicological Conference, The Psaltic Art as an Autonomous Science: Scientific Branches—Related Scientific Fields—Interdisciplinary Collaborations and Interaction, Volos, Greece, 29 June–3 July 2014; Available online: (accessed on 3 February 2023).
  99. Delviniotis, D.S. New Method of Byzantine Music (BM) Intervals’ Measuring and Its Application in the Fourth Mode. A New Approach of the Music Intervals’ Definition. In Proceedings of the MODUS-MODI_MODALITY International Musicological Conference, Nicosia, Cyprus, 6–10 September 2017; Volume 1.
  100. Patriarchal Music Committee. Elementary Teaching of Ecclesiastical Music—Elaborated on the Base of the Psalter; Patriarchal Music Committee: Constantinople, Türkiye, 1881.
  101. Kypourgos, N. Some Observations on the Intervals of Greek and Eastern Music. Musicology 1985, 2, 83–93.
  102. Sundberg, J. The Acoustics of the Singing Voice. Sci. Am. 1977, 236, 82–91.
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