Nonmusicians Experience Early Aging on Working Memory Tasks Compared to Musicians

Authors

DOI:

https://doi.org/10.15540/nr.12.1.2

Keywords:

Music training, Age effect, Cognition, Working Memory, Backward Digit Span, Reading Span

Abstract

Background. Previous studies on musicians have revealed better working memory (WM) abilities in musicians than in nonmusicians. This study investigates whether the deterioration of WM with aging is slowed in musicians relative to nonmusicians by assessing their performances across an age continuum. Methods. A cross-sectional descriptive mixed design was used. The study involved 150 participants, 75 musicians, and 75 nonmusicians, with 15 musicians and 15 nonmusicians in each age group (10–19.11, 20–29.11, 30–39.11, 40–49.11, and 50–59.11). Simple and complex spans were measured to assess the participant's WM capacity. Backward Digit Span (BDS) maximum and Reading Span Percent Correct Score Weighted (RS PCSW) scores were calculated. Results. Two-way ANOVA revealed significant main effects of musicianship (p < .001) and age (p < .05) on BDS maximum and RS PCSW scores. A “moderate to large” effect size was noted (ηp2 = 0.062 to 0.455). Interaction effects were observed for BDS maximum (p = .022) and approached significance for RS PCSW (p = .06). Post-hoc analysis revealed that age effects were exclusively present in nonmusicians. Conclusion. Musical training can significantly reduce the cognitive decline associated with aging. It improves WM abilities, thereby minimizing the deleterious effects of aging.

References

Barrett, K. C., Ashley, R., Strait, D. L., & Kraus, N. (2013). Art and science: How musical training shapes the brain. Frontiers in Psychology, 4, Article 713. https://doi.org/10.3389/fpsyg.2013.00713

Bergman Nutley, S., Darki, F., & Klingberg, T. (2014). Music practice is associated with development of working memory during childhood and adolescence. Frontiers in Human Neuroscience, 7, Article 926. https://doi.org/10.3389/fnhum.2013.00926

Boebinger, D., Evans, S., Rosen, S., Lima, C. F., Manly, T., & Scott, S. K. (2015). Musicians and non-musicians are equally adept at perceiving masked speech. The Journal of the Acoustical Society of America, 137(1), 378–387. https://doi.org/10.1121/1.4904537

Bregman, A. S. (1990). Auditory scene analysis: The perceptual organization of sound. The MIT Press.

Chan, A. S., Ho, Y.-C., & Cheung, M.-C. (1998). Music training improves verbal memory. Nature, 396(6707), Article 128. https://doi.org/10.1038/24075

Cohen, J. (2013). Statistical power analysis for the behavioral sciences. Routledge. https://doi.org/10.4324/9780203771587

Conway, A. R. A., Kane, M. J., Bunting, M. F., Hambrick, D. Z., Wilhelm, O., & Engle, R. W. (2005). Working memory span tasks: A methodological review and user's guide. Psychonomic Bulletin & Review, 12(5), 769–786. https://doi.org/10.3758/bf03196772

Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). "Mini-mental state": A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198. https://doi.org/10.1016/0022-3956(75)90026-6

Franklin, M. S., Sledge Moore, K., Yip, C. Y., Jonides, J., Rattray, K., & Moher, J. (2008). The effects of musical training on verbal memory. Psychology of Music, 36(3), 353–365. https://doi.org/10.1177/0305735607086044

Gaab, N., & Schlaug, G. (2003). The effect of musicianship on pitch memory in performance matched groups. NeuroReport, 14(18), 2291–2295. https://doi.org/10.1097/00001756-200312190-00001

George, E. M., & Coch, D. (2011). Music training and working memory: An ERP study. Neuropsychologia, 49(5), 1083–1094. https://doi.org/10.1016/j.neuropsychologia.2011.02.001

Gignac, G. E. (2015). The magical numbers 7 and 4 are resistant to the Flynn effect: No evidence for increases in forward or backward recall across 85 years of data. Intelligence, 48, 85–95. https://doi.org/10.1016/j.intell.2014.11.001

Gignac, G. E., & Weiss, L. G. (2015). Digit Span is (mostly) related linearly to general intelligence: Every extra bit of span counts. Psychological Assessment, 27(4), 1312–1323. https://doi.org/10.1037/pas0000105

Guo, X., Ohsawa, C., Suzuki, A., & Sekiyama, K. (2018). Improved digit span in children after a 6-week intervention of playing a musical instrument: An exploratory randomized controlled trial. Frontiers in Psychology, 8, Article 2303. https://doi.org/10.3389/fpsyg.2017.02303

Grassi, M., & Soranzo, A. (2009). MLP: A MATLAB toolbox for rapid and reliable auditory threshold estimation. Behavior Research Methods, 41(1), 20–28. https://doi.org/10.3758/BRM.41.1.20

Hansen, M., Wallentin, M., & Vuust, P. (2013). Working memory and musical competence of musicians and non-musicians. Psychology of Music, 41(6), 779–793. https://doi.org/10.1177/0305735612452186

Helmbold, N., Rammsayer, T., & Altenmüller, E. (2005). Differences in primary mental abilities between musicians and nonmusicians. Journal of Individual Differences, 26(2), 74–85. https://doi.org/10.1027/1614-0001.26.2.74

Houtgast, T., & Festen, J. M. (2008). On the auditory and cognitive functions that may explain an individual's elevation of the speech reception threshold in noise. International Journal of Audiology, 47(6), 287–295. https://doi.org/10.1080/14992020802127109

Howarth, A., & Shone, G. R. (2006). Ageing and the auditory system. Postgraduate Medical Journal, 82(965), 166–171. https://doi.org/10.1136/pgmj.2005.039388

Kraus, N., & Chandrasekaran, B. (2010). Music training for the development of auditory skills. Nature Reviews Neuroscience, 11(8), 599–605. https://doi.org/10.1038/nrn2882

Krishnaswamy, A. (2004). Inflexions and microtonality in South Indian classical music. Frontiers of Research on Speech and Music.

Kumar, A. U., & Sandeep, M. (2013). Auditory cognitive training module. ARF funded departmental project submitted to All India Institute of Speech and Hearing, Mysore.

Lee, Y.-S., Lu, M.-J., & Ko, H.-P. (2007). Effects of skill training on working memory capacity. Learning and Instruction, 17(3), 336–344. https://doi.org/10.1016/j.learninstruc.2007.02.010

Maillard, E., Joyal, M., Murray, M. M., & Tremblay, P. (2023). Are musical activities associated with enhanced speech perception in noise in adults? A systematic review and meta-analysis. Current Research in Neurobiology, 4, Article 100083. https://doi.org/10.1016/j.crneur.2023.100083

Martin, M., Zöllig, J., & Jäncke, L. (2009). The plastic human brain. Restorative Neurology and Neuroscience, 27(5), 521–538. https://doi.org/10.3233/RNN-2009-0519

Matysiak, O., Kroemeke, A., & Brzezicka, A. (2019). Working memory capacity as a predictor of cognitive training efficacy in the elderly population. Frontiers in Aging Neuroscience, 11, Article 126. https://doi.org/10.3389/fnagi.2019.00126

Mishra, S. K., Panda, M. R., & Herbert, C. (2014). Enhanced auditory temporal gap detection in listeners with musical training. The Journal of the Acoustical Society of America, 136(2), EL173–EL178. https://doi.org/10.1121/1.4890207

Muñoz-Pradas, R., Díaz-Palacios, M., Rodriguez-Martínez, E. I., & Gómez, C. M. (2021). Order of maturation of the components of the working memory from childhood to emerging adulthood. Current Research in Behavioral Sciences, 2, Article 100062. https://doi.org/10.1016/j.crbeha.2021.100062

Münte, T. F., Altenmüller, E., & Jäncke, L. (2002). The musician's brain as a model of neuroplasticity. Nature Reviews Neuroscience, 3(6), 473–478. https://doi.org/10.1038/nrn843

Owen, A. M., McMillan, K. M., Laird, A. R., & Bullmore, E. (2005). N-back working memory paradigm: A meta-analysis of normative functional neuroimaging studies. Human Brain Mapping, 25(1), 46–59. https://doi.org/10.1002/hbm.20131

Pais, R., Ruano, L., P Carvalho, O., & Barros, H. (2020). Global cognitive impairment prevalence and incidence in community dwelling older adults—A systematic review. Geriatrics (Basel, Switzerland), 5(4), Article 84. https://doi.org/10.3390/geriatrics5040084

Reynolds, M. R., Niileksela, C. R., Gignac, G. E., & Sevillano, C. N. (2022). Working memory capacity development through childhood: A longitudinal analysis. Developmental Psychology, 58(7), 1254–1263. https://doi.org/10.1037/dev0001360

Richardson, J. T. E. (2011). Eta squared and partial eta squared as measures of effect size in educational research. Educational Research Review, 6(2), 135–147. https://doi.org/10.1016/j.edurev.2010.12.001

Román-Caballero, R., Arnedo, M., Triviño, M., & Lupiáñez, J. (2018). Musical practice as an enhancer of cognitive function in healthy aging - A systematic review and meta-analysis PLoS ONE, 13(11), Article e0207957. https://doi.org/10.1371/journal.pone.0207957

Saarikivi, K. A., Huotilainen, M., Tervaniemi, M., & Putkinen, V. (2019). Selectively enhanced development of working memory in musically trained children and adolescents. Frontiers in Integrative Neuroscience, 13, Article 62. https://doi.org/10.3389/fnint.2019.00062

Sanchez, C. A., Wiley, J., Miura, T. K., Colflesh, G. J. H., Ricks, T. R., Jensen, M. S., & Conway, A. R. A. (2010). Assessing working memory capacity in a non-native language. Learning and Individual Differences, 20(5), 488–493. https://doi.org/10.1016/j.lindif.2010.04.001

Schellenberg, E. G. (2006). Long-term positive associations between music lessons and IQ. Journal of Educational Psychology, 98(2), 457–468. https://doi.org/10.1037/0022-0663.98.2.457

Schlaug, G., Jäncke, L., Huang, Y., & Steinmetz, H. (1995). In vivo evidence of structural brain asymmetry in musicians. Science (New York, N.Y.), 267(5198), 699–701. https://doi.org/10.1126/science.7839149

Sluzenski, J., Newcombe, N. S., & Kovacs, S. L. (2006). Binding, relational memory, and recall of naturalistic events: A developmental perspective. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(1), 89–100. https://doi.org/10.1037/0278-7393.32.1.89

Talamini, F., Altoè, G., Carretti, B., & Grassi, M. (2017). Musicians have better memory than nonmusicians: A meta-analysis. PLoS ONE, 12(10), Article e0186773. https://doi.org/10.1371/journal.pone.0186773

Talamini, F., Carretti, B., & Grassi, M. (2016). The working memory of musicians and nonmusicians. Music Perception: An Interdisciplinary Journal, 34(2), 183–191. https://doi.org/10.1525/MP.2016.34.2.183

Tervaniemi, M., Just, V., Koelsch, S., Widmann, A., & Schröger, E. (2005). Pitch discrimination accuracy in musicians vs nonmusicians: An event-related potential and behavioral study. Experimental Brain Research, 161(1), 1–10. https://doi.org/10.1007/s00221-004-2044-5

Vaidyanath, R., & Yathiraj, A. (2014). Screening checklist for auditory processing in adults (SCAP-A): Development and preliminary findings. Journal of Hearing Science, 4(1), 27–37. https://doi.org/10.17430/890788

Venkatesan, S., & Basavaraj, V. (2009). Ethical guidelines for bio-behavioral research involving human subjects, 1–23. Mysore, India: All India Institute of Speech & Hearing. https://www.aiishmysore.in/en/pdf/ethical_guidelines.pdf

Vuontela, V., Steenari, M.-R., Carlson, S., Koivisto, J., Fjällberg, M., & Aronen, E. T. (2003). Audiospatial and visuospatial working memory in 6-13 year old school children. Learning & Memory (Cold Spring Harbor, N.Y.), 10(1), 74–81. https://doi.org/10.1101/lm.53503

Yathiraj, A., & Vanaja, C. S. (2015). Age related changes in auditory processes in children aged 6 to 10 years. International Journal of Pediatric Otorhinolaryngology, 79(8), 1224–1234. https://doi.org/10.1016/j.ijporl.2015.05.018

Zuk, J., Benjamin, C., Kenyon, A., & Gaab, N. (2014). Behavioral and neural correlates of executive functioning in musicians and nonmusicians. PLoS ONE, 9(6), Article e99868. https://doi.org/10.1371/journal.pone.0099868

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Published

2025-03-24

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Research Papers