Musical expertise generalizes to superior temporal scaling in a Morse code tapping task
Autoři:
Matthew A. Slayton aff001; Juan L. Romero-Sosa aff002; Katrina Shore aff001; Dean V. Buonomano aff002; Indre V. Viskontas aff001
Působiště autorů:
San Francisco Conservatory of Music, San Francisco, CA, United States of America
aff001; Department of Neurobiology, University of California Los Angeles, Los Angeles, CA, United States of America
aff002; Neuroscience Interdepartmental Program, University of California Los Angeles, Los Angeles, CA, United States of America
aff003; Department of Psychology, University of California Los Angeles, Los Angeles, CA, United States of America
aff004; Department of Psychology, University of San Francisco, San Francisco, CA, United States of America
aff005
Vyšlo v časopise:
PLoS ONE 15(1)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0221000
Souhrn
A key feature of the brain’s ability to tell time and generate complex temporal patterns is its capacity to produce similar temporal patterns at different speeds. For example, humans can tie a shoe, type, or play an instrument at different speeds or tempi—a phenomenon referred to as temporal scaling. While it is well established that training improves timing precision and accuracy, it is not known whether expertise improves temporal scaling, and if so, whether it generalizes across skill domains. We quantified temporal scaling and timing precision in musicians and non-musicians as they learned to tap a Morse code sequence. We found that non-musicians improved significantly over the course of days of training at the standard speed. In contrast, musicians exhibited a high level of temporal precision on the first day, which did not improve significantly with training. Although there was no significant difference in performance at the end of training at the standard speed, musicians were significantly better at temporal scaling—i.e., at reproducing the learned Morse code pattern at faster and slower speeds. Interestingly, both musicians and non-musicians exhibited a Weber-speed effect, where temporal precision at the same absolute time was higher when producing patterns at the faster speed. These results are the first to establish that the ability to generate the same motor patterns at different speeds improves with extensive training and generalizes to non-musical domains.
Klíčová slova:
Animal studies – Learning – Bioacoustics – Undergraduates – Linear regression analysis – Recurrent neural networks – Target detection – Music cognition
Zdroje
1. Dowling WJ, Bartlett JC, Halpern AR, Andrews MW. Melody recognition at fast and slow tempos: Effects of age, experience, and familiarity. Percept Psychophys. 2008 Apr 1;70(3):496–502. doi: 10.3758/pp.70.3.496 18459260
2. Shankar KH, Howard MW. A Scale-Invariant Internal Representation of Time. Neural Comput. 2012 Jan 29;24(1):134–93. doi: 10.1162/NECO_a_00212 21919782
3. Lerner Y, Honey CJ, Katkov M, Hasson U. Temporal scaling of neural responses to compressed and dilated natural speech. J Neurophysiol. 2014 Jun 15;111(12):2433–44. doi: 10.1152/jn.00497.2013 24647432
4. Mello GBM, Soares S, Paton JJ. A Scalable Population Code for Time in the Striatum. Curr Biol. 2015 May 4;25(9):1113–22. doi: 10.1016/j.cub.2015.02.036 25913405
5. Namboodiri VMK, Huertas MA, Monk KJ, Shouval HZ, Hussain Shuler MG. Visually Cued Action Timing in the Primary Visual Cortex. Neuron. 2015 Apr 8;86(1):319–30. doi: 10.1016/j.neuron.2015.02.043 25819611
6. Hardy NF, Goudar V, Romero-Sosa JL, Buonomano D V. A model of temporal scaling correctly predicts that motor timing improves with speed. Nat Commun. 2018 Dec 9;9(1):4732. doi: 10.1038/s41467-018-07161-6 30413692
7. Buhusi C.V., and Meck W.H. (2005). What makes us tick? Functional and neural mechanisms of interval timing. Nat Rev Neurosci 6, 755–765. doi: 10.1038/nrn1764 16163383
8. Coull JT, Cheng R-K, Meck WH. Neuroanatomical and Neurochemical Substrates of Timing. Neuropsychopharmacology. 2011 Jan 28;36(1):3–25. doi: 10.1038/npp.2010.113 20668434
9. Merchant H, Harrington DL, Meck WH. Neural Basis of the Perception and Estimation of Time. Annu Rev Neurosci. 2013 Jul 8;36(1):313–36.
10. Paton JJ, Buonomano D V. The Neural Basis of Timing: Distributed Mechanisms for Diverse Functions. Neuron. 2018 May 16;98(4):687–705. doi: 10.1016/j.neuron.2018.03.045 29772201
11. Long MA, Fee MS. Using temperature to analyse temporal dynamics in the songbird motor pathway. Nature. 2008;456(7219):189–94. doi: 10.1038/nature07448 19005546
12. Long MA, Jin DZ, Fee MS (2010) Support for a synaptic chain model of neuronal sequence generation. Nature 468:394–399. doi: 10.1038/nature09514 20972420
13. Bakhurin KI, Goudar V, Shobe JL, Claar LD, Buonomano DV, Masmanidis SC (2017) Differential Encoding of Time by Prefrontal and Striatal Network Dynamics. The Journal of Neuroscience 37:854–870. doi: 10.1523/JNEUROSCI.1789-16.2016 28123021
14. Remington ED, Narain D, Hosseini EA, Jazayeri M. Flexible Sensorimotor Computations through Rapid Reconfiguration of Cortical Dynamics. Neuron. 2018 Jun 6;98(5):1005–1019.e5. doi: 10.1016/j.neuron.2018.05.020 29879384
15. Wang J, Narain D, Hosseini EA, Jazayeri M. Flexible timing by temporal scaling of cortical responses. Nat Neurosci. 2018 Jan 4;21(1):102–10. doi: 10.1038/s41593-017-0028-6 29203897
16. Gibbon J. Scalar expectancy theory and Weber’s law in animal timing. Psychol Rev. 1977 May;84(3):279–325.
17. Killeen PR, Weiss NA. Optimal timing and the Weber function. Psychol Rev. 1987;94(4):455–68. 3317471
18. Grondin S. About the (Non)scalar Property for Time Perception. In Springer, New York, NY; 2014. p. 17–32.
19. Grondin S, Ouellet B, Roussel M-E. Benefits and Limits of Explicit Counting for Discriminating Temporal Intervals. Can J Exp Psychol Can Psychol expérimentale. 2004;58(1):1–12.
20. Hinton SC, Harrington DL, Binder JR, Durgerian S, Rao SM. Neural systems supporting timing and chronometric counting: an FMRI study. Cogn Brain Res. 2004 Oct 1;21(2):183–92.
21. Grondin S, Killeen PR. Tracking time with song and count: Different Weber functions for musicians and nonmusicians. Atten Percept Psychophys. 2009 Oct 1;71(7):1649–54. doi: 10.3758/APP.71.7.1649 19801624
22. Bueti D, Buonomano D V. Temporal perceptual learning. Timing Time Percept. 2014;2(3):261–89.
23. Wright BA, Wilson RM, Sabin AT. Generalization Lags behind Learning on an Auditory Perceptual Task. J Neurosci. 2010;30(35):11635–9. doi: 10.1523/JNEUROSCI.1441-10.2010 20810884
24. Laje R, Cheng K, Buonomano D V. Learning of Temporal Motor Patterns: An Analysis of Continuous Versus Reset Timing. Front Integr Neurosci. 2011;5 Oct:1–11.
25. Bueti D, Lasaponara S, Cercignani M, Macaluso E. Learning about Time: Plastic Changes and Interindividual Brain Differences. Neuron. 2012;75(4):725–37. doi: 10.1016/j.neuron.2012.07.019 22920262
26. Hosoda M, Furuya S. Shared somatosensory and motor functions in musicians. Sci Rep. 2016 Dec 25;6(1):37632.
27. Krause V, Schnitzler A, Pollok B. Functional network interactions during sensorimotor synchronization in musicians and non-musicians. Neuroimage. 2010 Aug 1;52(1):245–51. doi: 10.1016/j.neuroimage.2010.03.081 20363337
28. Chen JL, Penhune VB, Zatorre RJ. Moving on Time: Brain Network for Auditory-Motor Synchronization is Modulated by Rhythm Complexity and Musical Training. J Cogn Neurosci. 2008 Feb 14;20(2):226–39. doi: 10.1162/jocn.2008.20018 18275331
29. Keele SW, Pokorny RA, Corcos DM, Ivry R. Do perception and motor production share common timing mechanisms: A correlational analysis. Acta Psychol (Amst). 1985 Dec 1;60(2–3):173–91.
30. Furuya S, Soechting JF. Speed invariance of independent control of finger movements in pianists. J Neurophysiol. 2012;108(7):2060–8 doi: 10.1152/jn.00378.2012 22815403
31. Cicchini GM, Arrighi R, Cecchetti L, Giusti M, Burr DC. Optimal encoding of interval timing in expert percussionists. J Neurosci. 2012 Jan 18;32(3):1056–60. doi: 10.1523/JNEUROSCI.3411-11.2012 22262903
32. Rammsayer TH, Buttkus F, Altenmüller E. Musicians Do Better than Nonmusicians in Both Auditory and Visual Timing Tasks. Music Percept An Interdiscip J. 2012 Sep 1;30(1):85–96.
33. Kraus N, Chandrasekaran B. Music training for the development of auditory skills. Nat Rev Neurosci. 2010 Aug 1;11(8):599–605. doi: 10.1038/nrn2882 20648064
34. Chen JL, Penhune VB, Zatorre RJ. Moving on Time: Brain Network for Auditory-Motor Synchronization is Modulated by Rhythm Complexity and Musical Training. J Cogn Neurosci. 2008 Feb 14;20(2):226–39. doi: 10.1162/jocn.2008.20018 18275331
35. Stupacher J, Wood G, Witte M. Neural Entrainment to Polyrhythms: A Comparison of Musicians and Non-musicians. Front Neurosci. 2017 Apr 12;11:208. doi: 10.3389/fnins.2017.00208 28446864
36. Penhune V, Ding N, Fujioka T, Palmer C, Scheurich R, Zamm A. Tapping Into Rate Flexibility: Musical Training Facilitates Synchronization Around Spontaneous Production Rates. 2018.
37. Repp BH. Sensorimotor synchronization and perception of timing: Effects of music training and task experience. Hum Mov Sci. 2010 Apr 1;29(2):200–13. doi: 10.1016/j.humov.2009.08.002 20074825
38. Watanabe D, Savion-Lemieux T, Penhune VB. The effect of early musical training on adult motor performance: evidence for a sensitive period in motor learning. Exp Brain Res 2007 Jan 4;176(2):332–40. doi: 10.1007/s00221-006-0619-z 16896980
39. Patel AD. Musical Rhythm, Linguistic Rhythm, and Human Evolution. Music Percept. 2006 Sep 1;24(1):99–104.
40. Patel AD, Iversen JR. The evolutionary neuroscience of musical beat perception: the Action Simulation for Auditory Prediction (ASAP) hypothesis. Front Syst Neurosci. 2014 May 13;8:57. doi: 10.3389/fnsys.2014.00057 24860439
41. Karni A, Meyer G, Rey-Hipolito C, Jezzard P, Adams MM, Turner R, et al. The acquisition of skilled motor performance: fast and slow experience-driven changes in primary motor cortex. Proc Natl Acad Sci USA.1998 Feb 3;95(3):861–8. doi: 10.1073/pnas.95.3.861 9448252
42. Harris CM, Wolpert DM. Signal-dependent noise determines motor planning. Nature 1998 Aug. 394(6695):780–4 doi: 10.1038/29528 9723616
43. Buonomano DV, Karmarkar UR (2002) How do we tell time? Neuroscientist 8:42–51. doi: 10.1177/107385840200800109 11843098
44. Grondin S, Meilleur-Wells G, Lachance R. When to start explicit counting in a time-intervals discrimination task: A critical point in the timing process of humans. J Exp Psychol Hum Percept Perform. 199925(4):993–1004.
45. Ivry RB, Hazeltine RE. Perception and production of temporal intervals across a range of durations: evidence for a common timing mechanism. J Exp Psychol Hum Percept Perform. 1995 Feb;21(1):3–18. doi: 10.1037//0096-1523.21.1.3 7707031
46. Merchant H, Zarco W, Prado L. Do We Have a Common Mechanism for Measuring Time in the Hundreds of Millisecond Range? Evidence From Multiple-Interval Timing Tasks. J Neurophysiol. 2008 Feb;99(2):939–49. doi: 10.1152/jn.01225.2007 18094101
Článok vyšiel v časopise
PLOS One
2020 Číslo 1
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
- Nejasný stín na plicích – kazuistika
- Masturbační chování žen v ČR − dotazníková studie
- Těžké menstruační krvácení může značit poruchu krevní srážlivosti. Jaký management vyšetření a léčby je v takovém případě vhodný?
- Fixní kombinace paracetamol/kodein nabízí synergické analgetické účinky
Najčítanejšie v tomto čísle
- Psychometric validation of Czech version of the Sport Motivation Scale
- Comparison of Monocyte Distribution Width (MDW) and Procalcitonin for early recognition of sepsis
- Effects of supplemental creatine and guanidinoacetic acid on spatial memory and the brain of weaned Yucatan miniature pigs
- Accelerated sparsity based reconstruction of compressively sensed multichannel EEG signals