Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

  • Emili Balaguer-Ballester
  • Nicholas R. Clark
  • Martin Coath
  • Katrin Krumbholz
  • Susan L. Denham
Conference paper


Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information, and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies and a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing.


Pitch perception processing Top-down modulation Temporal dynamics of pitch 



This work was supported by EmCAP (Emergent Cognition through Active Perception, 2005-2008); a research project in the field of Music Cognition funded by the European Commission (FP6-IST, contract 013123) and by the EPSRC grant EP/C010841/1 (COLAMN). EBB wants to thank Ray Meddis for his very generous support, which was critical to the completion of this study.


  1. Balaguer-Ballester E, Clark N, Coath M, Krumholz K, Denham SL (2009) Understanding pitch perception as a hierarchical generative with top-down modulation. PLoS Comput Biol 5(3):e1000301PubMedCrossRefGoogle Scholar
  2. Balaguer-Ballester E, Denham SL, Meddis R (2008) A cascade autocorrelation model of pitch perception. J Acoust Soc Am 124:2186–2195PubMedCrossRefGoogle Scholar
  3. Bregman AS, Ahad PA, Kim J, Melnerich L (1994) Resetting the pitch-analysis system: 1. Effects of rise times of tones in noise backgrounds or of harmonics in a complex tone. Percept Psychophys 56:155–162PubMedCrossRefGoogle Scholar
  4. Carlyon RP, Mahendran S, Deeks JM, Long CJ, Axon P, Baguley D, Bleeck S, Winter IM (2008) Behavioural and physiological correlates of temporal pitch perception in electric and acoustic hearing. J Acoust Soc Am 123:973–985PubMedCrossRefGoogle Scholar
  5. de Boer E (1985) Auditory time constants: a paradox? In: Michelsen A (ed) Time resolution in auditory systems. Springer, Berlin, pp 141–158CrossRefGoogle Scholar
  6. Friston K (2003) Learning and inference in the brain. Neural Netw 16:1325–1352PubMedCrossRefGoogle Scholar
  7. Gutschalk A, Patterson RD, Scherg M, Uppenkamp S, Rupp A (2007) The effect of temporal context on the sustained pitch response in human auditory cortex. Cereb Cortex 17:552–561PubMedCrossRefGoogle Scholar
  8. Hall JW, Peters RW (1981) Pitch for nonsimultaneous successive harmonics in quiet and noise. J Acoust Soc Am 69:509–513PubMedCrossRefGoogle Scholar
  9. Kiebel SJ, Daunizeau J, Friston KJ (2008) A hierarchy of time-scales and the brain. PLoS Comput Biol 4(11):e1000209PubMedCrossRefGoogle Scholar
  10. Krumbholz K, Patterson RD, Seither-Preisler A, Lammertmann C, Lutkenhoner B (2003) Neuromagnetic evidence for a pitch processing center in Heschl’s gyrus. Cereb Cortex 13:765–772PubMedCrossRefGoogle Scholar
  11. Kumar S, Stephan KE, Warren JD, Friston KJ, Griffiths TD (2007) Hierarchical processing of auditory objects in humans. PLoS Comput Biol 3(6):e100PubMedCrossRefGoogle Scholar
  12. Licklider JCR (1951) A duplex theory of pitch perception. Experientia 7:128–134PubMedCrossRefGoogle Scholar
  13. Lopez-Poveda EA, Meddis R (2001) A human nonlinear cochlear filter bank. J Acoust Soc Am 110:3107–3118PubMedCrossRefGoogle Scholar
  14. Meddis R, O’Mard L (1997) A unitary model of pitch perception. J Acoust Soc Am 102:1811–1820PubMedCrossRefGoogle Scholar
  15. Meddis R, O’Mard L (2006) Virtual pitch in a computational physiological model. J Acoust Soc Am 120:3861–3868PubMedCrossRefGoogle Scholar
  16. Plack CJ, White LJ (2000) Perceived continuity and pitch perception. J Acoust Soc Am 108:1162–1169PubMedCrossRefGoogle Scholar
  17. Sumner CJ, O’Mard LP, Lopez-Poveda EA, Meddis R (2002) A revised model of the inner-hair cell and auditory nerve complex. J Acoust Soc Am 111:2178–2189PubMedCrossRefGoogle Scholar
  18. Wiegrebe L (2001) Searching for the time constant in of neural pitch extraction. J Acoust Soc Am 107:1082–1091CrossRefGoogle Scholar
  19. Kadner A, Berrebi S (2008) Encoding of the temporal features of auditory stimuli in the medial nucleous of the trapezoid body and superior paraolivary nucleous of the rat. Neuroscience 151:868–887PubMedCrossRefGoogle Scholar
  20. von Kriegstein K, Patterson RD, Griffiths TD (2008) Task-dependent modulation of medial geniculate body is behaviourally relevant for speech recognition. Curr Biol 18(23-2):1855–1859CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Emili Balaguer-Ballester
    • 1
  • Nicholas R. Clark
  • Martin Coath
  • Katrin Krumbholz
  • Susan L. Denham
  1. 1.Computational Neuroscience group, Central Institute for Mental Health (ZI)Ruprecht-Karls University of Heidelberg, J5MannheimGermany

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