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Musical Tonality, Neural Resonance and Hebbian Learning

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Mathematics and Computation in Music (MCM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6726))

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Abstract

A new theory of musical tonality is explored, which treats the central auditory pathway as a complex nonlinear dynamical system. The theory predicts that as networks of neural oscillators phase-lock to musical stimuli, stability and attraction relationships will develop among frequencies, and these dynamic forces correspond to perceptions of stability and attraction among musical tones. This paper reports on an experiment with learning in a model auditory network. Results suggest that Hebbian synaptic modification can change the dynamic responses of the network in some ways but not in others.

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Author information

Authors and Affiliations

  1. Center for Complex Systems and Brain Sciences, Florida Atlantic University, United States

    Edward W. Large

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  1. Edward W. Large
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Editors and Affiliations

  1. UMR STMS: IRCAM/CNRS/UPMC, 1, place I. Stravinsky, 75004, Paris, France

    Carlos Agon , Moreno Andreatta , Gérard Assayag  & Jean Bresson , ,  & 

  2. 1, rue du Centre, 66570, St. Nazaire, France

    Emmanuel Amiot

  3. Dipartimento di Matematica “L. Tonelli”, Università di Pisa, Largo Bruno Pontecorvo 5, 56127, Pisa, Italy

    John Mandereau

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Large, E.W. (2011). Musical Tonality, Neural Resonance and Hebbian Learning. In: Agon, C., Andreatta, M., Assayag, G., Amiot, E., Bresson, J., Mandereau, J. (eds) Mathematics and Computation in Music. MCM 2011. Lecture Notes in Computer Science(), vol 6726. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21590-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-21590-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21589-6

  • Online ISBN: 978-3-642-21590-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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