A New Look at Musical Expectancy: The Veridical Versus the General in the Mental Organization of Music

  • Emery SchubertEmail author
  • Marcus Pearce
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9617)


This paper takes a step back from what we label ‘problem solving’ approaches to the psychology of music memory and processing. In contrast with generalised expectation theories of music processing, a hypothesis is proposed which is based on the idea that mental representations of music are largely based on a large library of individual pieces: Case-based memory. We argue that it is the activation of these memories that forms the critical aspect of musical experience. Furthermore, a specific hypothesis is proposed that it is possible to represent any new piece of music through the chaining together of different, pre-existing veridical segments of music, in contrast with ‘problem solving by generalization’ which determines expectation based on statistical/stylistic/schematic factors. By adjusting segment length, or by forming new segments through repeated listenings, new music can be absorbed into an existing, growing mental database by chaining together existing veridical segments that match the incoming stimulus.


Music processing Veridical memory Schematic expectation Exemplars Prototypes, musical experience, problem solving, spreading activation 



This research was supported by a Fellowship from the Australian Research Council (FT120100053) held by author ES.


  1. 1.
    Bharucha, J., Curtis, M., Paroo, K.: Varieties of musical experience. Cognition 100, 131–172 (2006)CrossRefGoogle Scholar
  2. 2.
    Bharucha, J.J.: Tonality and expectation. In: Aiello, R., Sloboda, J.A. (eds.) Musical Perceptions, pp. 213–239. Oxford University Press, London (1994)Google Scholar
  3. 3.
    Bharucha, J.J., Todd, P.M.: Modeling the perception of tonal structure with neural nets. Comput. Music J. 13, 44–53 (1989)CrossRefGoogle Scholar
  4. 4.
    Bharucha, J.J.: Music cognition and perceptual facilitation: a connectionist framework. Music Percept. 5, 1–30 (1987)CrossRefGoogle Scholar
  5. 5.
    Pearce, M.T., Wiggins, G.A.: Improved methods for statistical modelling of monophonic music. J. New Music Res. 33, 367–385 (2004)CrossRefGoogle Scholar
  6. 6.
    Pearce, M.T., Wiggins, G.A.: Expectation in melody: the influence of context and learning. Music Percept. 23, 377–405 (2006)CrossRefGoogle Scholar
  7. 7.
    Wiggins, G.A., Pearce, M.T., Müllensiefen, D.: Computational modelling of music cognition and musical creativity. In: Dean, R. (ed.) Oxford Handbook of Computer Music and Digital Sound Culture, pp. 383–420. Oxford University Press, Oxford (2009)Google Scholar
  8. 8.
    Temperley, D.: The Cognition of Basic Musical Structures. MIT Press, Cambridge (2001)Google Scholar
  9. 9.
    Temperley, D.: A probabilistic model of melody perception. Cogn. Sci. 32, 418–444 (2008)CrossRefGoogle Scholar
  10. 10.
    Huron, D.: Sweet Anticipation: Music and the Psychology of Expectation. MIT Press, Cambridge (2006)Google Scholar
  11. 11.
    Folkestad, G.: Digital tools and discourse in music: the ecology of composition. In: Hargreaves, D.J., Miell, D.E., MacDonald, R.A.R. (eds.) Musical Imaginations, pp. 193–205. Oxford University Press, Oxford (2012)Google Scholar
  12. 12.
    Hargreaves, D.J.: Musical imagination: perception and production, beauty and creativity. Psychol. Music 40, 539–557 (2012)CrossRefGoogle Scholar
  13. 13.
    MacDonald, R.A., Hargreaves, D.J., Miell, D.: Musical identities. In: Hallam, S., Cross, I., Thaut, M. (eds.) The Oxford Handbook of Music Psychology, pp. 462–470. Oxford University Press, Oxford (2009)Google Scholar
  14. 14.
    Lamont, A.: Musical identities and the school environment. In: MacDonald, R.A.R., Hargreaves, D.J., Miell, D. (eds.) Musical Identities, pp. 41–59. Oxford University Press, Oxford, UK (2002)Google Scholar
  15. 15.
    Gjerdingen, R.O., Perrott, D.: Scanning the dial: the rapid recognition of music genres. J. New Music Res. 37, 93–100 (2008)CrossRefGoogle Scholar
  16. 16.
    Plazak, J., Huron, D.: The first three seconds. Musicae Sci. 15, 29–44 (2011)CrossRefGoogle Scholar
  17. 17.
    Schellenberg, E.G., Iverson, P., Mckinnon, M.C.: Name that tune: identifying popular recordings from brief excerpts. Psychon. Bull. Rev. 6, 641–646 (1999)CrossRefGoogle Scholar
  18. 18.
    Schubert, E.: Reconsidering expectancy and implication in music: the veridical chaining hypothesis. In: Ginsborg, J., Lamont, A. (eds.) Ninth Triennial Conference of the European Society for the Cognitive Sciences of Music, RNCM, Manchester, UK (2015)Google Scholar
  19. 19.
    Narmour, E.: The top-down and bottom-up systems of musical implication: building on Meyer’s theory of emotional syntax. Music Percept. 9, 1–26 (1991)CrossRefGoogle Scholar
  20. 20.
    Meyer, L.B.: Emotion and Meaning in Music. University of Chicago Press, Chicago (1956)Google Scholar
  21. 21.
    Schubert, E.: Enjoyment of negative emotions in music: an associative network explanation. Psychol. Music 24, 18–28 (1996)CrossRefGoogle Scholar
  22. 22.
    Schubert, E.: Loved music can make a listener feel negative emotions. Musicae Sci. 17, 11–26 (2013)CrossRefGoogle Scholar
  23. 23.
    Schubert, E., North, A.C., Hargreaves, D.J.: Toward a theory of music aesthetics: the affect-space framework. Psychology of Aesthetics, Creativity, and the Arts (submitted)Google Scholar
  24. 24.
    Martindale, C., Moore, K.: Priming, prototypicality, and preference. J. Exp. Psychol. Hum. Percept. Perform. 14, 661–670 (1988)CrossRefGoogle Scholar
  25. 25.
    Martindale, C.: Aesthetics, psychobiology, and cognition. In: Farley, F.H., Neperud, R.W. (eds.) The foundations of Aesthetics, Art, & Art Education, pp. 7–42 (1988)Google Scholar
  26. 26.
    Martindale, C.: The pleasures of thought: a theory of cognitive hedonics. J. Mind Behav. 5, 49–80 (1984)Google Scholar
  27. 27.
    West, A., Moore, K., Martindale, C., Rosen, K.: Prototypicality and preference. Bullet. Br. Psychol. Soc. 36, A138–A138 (1983)Google Scholar
  28. 28.
    Schubert, E., Hargreaves, D.J., North, A.C.: A dynamically minimalist cognitive explanation of musical preference: is familiarity everything? Front. Psychol. 5, 38 (2014)CrossRefGoogle Scholar
  29. 29.
    Schubert, E.: The fundamental function of music. Musicae Sci. 13, 63–81 (2009–2010)Google Scholar
  30. 30.
    Davies, S.: Musical Meaning and Expression. Cornell University Press, Ithaca (1994)Google Scholar
  31. 31.
    Hammond, K.J., Seifert, C.M.: A cognitive science approach to case-based planning. In: Chipman, S., Meyrowitz, A.L. (eds.) Foundations of Knowledge Acquisition: Cognitive Models of Complex Learning, vol. 194, pp. 245–267. Springer, Berlin (1993)CrossRefGoogle Scholar
  32. 32.
    Tomkins, S.S.: Script theory: differential magnification of affects. In: Howe, H.E., Dienstbier, R.A. (eds.) Nebraska Symposium on Motivation, vol. 26, pp. 201–236. University of Nebraska Press, Lincoln (1979)Google Scholar
  33. 33.
    Schank, R.C., Abelson, R.P.: Scripts, Plans, Goals and Understanding: An Inquiry into Human Knowledge Structures. Lawrence Erlbaum, Hillsdale (1977)zbMATHGoogle Scholar
  34. 34.
    Riesbeck, C.K., Schank, R.C.: Inside Case-Based Reasoning. Lawrence Erlbaum Associates, Hillsdale (1989)Google Scholar
  35. 35.
    Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Mateo (1993)CrossRefGoogle Scholar
  36. 36.
    Somers, H.: Translation memory systems. In: Somers, H. (ed.) Computers and Translation: A Translator’s Guide, pp. 31–48. Benjamins, Amsterdam (2003)CrossRefGoogle Scholar
  37. 37.
    Finnäs, L.: How can musical preferences be modified - a research review. Bullet. Counc. Res. Music Educ. 102, 1–58 (1989)Google Scholar
  38. 38.
    Hargreaves, D.J., Hargreaves, J.J., North, A.C.: Imagination and creativity in music listening. In: Hargreaves, D., Miell, D., MacDonald, R. (eds.) Musical Imaginations: Multidisciplinary perspectives on creativity, performance and perception, pp. 156–172. Oxford University Press, Oxford (2012)Google Scholar
  39. 39.
    Dowling, W.J., Harwood, D.L.: Music Cognition. Academic Press, London (1986)Google Scholar
  40. 40.
    Narmour, E.: The Analysis and Cognition of Basic Melodic Structures: The Implication-Realization Model. University of Chicago Press, Chicago (1990)Google Scholar
  41. 41.
    Bharucha, J.J., Stoeckig, K.: Priming of chords: spreading activation or overlapping frequency spectra? Percept. Psychophys. 41, 519–524 (1987)CrossRefGoogle Scholar
  42. 42.
    Collins, A.M., Loftus, E.F.: Spreading activation theory of semantic processing. Psychol. Rev. 82, 407–428 (1975)CrossRefGoogle Scholar
  43. 43.
    Oja, E.: Simplified neuron model as a principal component analyzer. J. Math. Biol. 15, 267–273 (1982)MathSciNetCrossRefGoogle Scholar
  44. 44.
    Zajonc, R.B.: Attitudinal effects of mere exposure. J. Pers. Soc. Psychol. 9, 1–27 (1968)CrossRefGoogle Scholar
  45. 45.
    Zajonc, R.B.: Mere exposure: a gateway to the subliminal. Curr. Dir. Psychol. Sci. 10, 224–228 (2001)CrossRefGoogle Scholar
  46. 46.
    Stewart, J.: Calculus, Concepts and Contexts. Brooks, Brooks/Cole, Belmont (2009)Google Scholar
  47. 47.
    Smith, E.R., Zarate, M.A.: Exemplar and prototype use in social categorization. Soc. Cogn. 8, 243–262 (1990)CrossRefGoogle Scholar
  48. 48.
    Griffiths, T.L., Canini, K.R., Sanborn, A.N., Navarro, D.J.: Unifying rational models of categorization via the hierarchical Dirichlet process. In: Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 323–328 (2007)Google Scholar
  49. 49.
    Pearce, M.T.: The construction and evaluation of statistical models of melodic structure in music perception and composition. Doctoral dissertation, Department of Computing, City University, London, UK (2005)Google Scholar
  50. 50.
    Bunton, S.: Semantically motivated improvements for PPM variants. Comput. J. 40(2/3), 76–93 (1997)CrossRefGoogle Scholar
  51. 51.
    Cleary, J.G., Teahan, W.J.: Unbounded length contexts for PPM. Comput. J. 40(2/3), 67–75 (1997)CrossRefGoogle Scholar
  52. 52.
    Ukkonen, E.: On-line construction of suffix trees. Algorithmica 14(3), 249–260 (1995)MathSciNetCrossRefGoogle Scholar
  53. 53.
    Justus, T.C., Bharucha, J.J.: Modularity in musical processing: the automaticity of harmonic priming. J. Exp. Psychol. Hum. Percept. Perform. 27, 1000–1011 (2001)CrossRefGoogle Scholar
  54. 54.
    Tillmann, B., Bigand, E.: Musical structure processing after repeated listening: schematic expectations resist veridical expectations. Musicae Sci. 14, 33–47 (2010)CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Empirical Musicology LaboratoryThe University of New South WalesKensingtonAustralia
  2. 2.Queen Mary, University of LondonLondonUK

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