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Human pitch detectors are tuned on a fine scale, but are perceptually accessed on a coarse scale

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Abstract

Single neurons in auditory cortex display highly selective spectrotemporal properties: their receptive fields modulate over small fractions of an octave and integrate across temporal windows of 100–200 ms. We investigated how these characteristics impact auditory behavior. Human observers were asked to detect a specific sound frequency masked by broadband noise; we adopted an experimental design which required the engagement of frequency-selective mechanisms to perform above chance. We then applied psychophysical reverse correlation to derive spectrotemporal perceptual filters for the assigned task. We were able to expose signatures of neuronal-like spectrotemporal tuning on a scale of 1/10 octave and 50–100 ms, but detailed modeling of our results showed that observers were not able to rely on the explicit output of these channels. Instead, human observers pooled from a large bank of highly selective channels via a weighting envelope poorly tuned for frequency (on a scale of 1.5 octave) with sluggish temporal dynamics, followed by a highly nonlinear max-like operation. We conclude that human detection of specific frequencies embedded within complex sounds suffers from a high degree of intrinsic spectrotemporal uncertainty, resulting in low efficiency values (< 1 %) for this perceptual ability. Signatures of the underlying neural circuitry can be exposed, but there does not appear to be a direct line for accessing individual neural channels on a fine scale.

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References

  • Ahumada AJ (2002) Classification image weights and internal noise level estimation. J Vis 2: 121–131

    Article  PubMed  Google Scholar 

  • Ahumada AJ, Lovell J (1971) Stimulus features in signal detection. J Acoust Soc Am 49: 1751–1756

    Article  Google Scholar 

  • Ahumada AJ, Marken R, Sandusky A (1975) Time and frequency analyses of auditory signal detection. J Acoust Soc Am 57: 385–390

    Article  PubMed  Google Scholar 

  • Anantharaman JN, Krishnamurthy AK, Feth LL (1993) Intensity-weighted average of instantaneous frequency as a model for frequency discrimination. J Acoust Soc Am 94: 723–729

    Article  PubMed  CAS  Google Scholar 

  • Berg BG (2004) A molecular description of profile analysis: decision weights and internal noise. J Acoust Soc Am 115: 822–829

    Article  PubMed  Google Scholar 

  • Berg BG, Nguyen QT, Green DM (1992) Discrimination of narrow-band spectra. I: Spectral weights and pitch cues. J Acoust Soc Am 92: 1911–1918

    Article  PubMed  CAS  Google Scholar 

  • Bitterman Y, Mukamel R, Malach R, Fried I, Nelken I (2008) Ultra-fine frequency tuning revealed in single neurons of human auditory cortex. Nature 451: 197–201

    Article  PubMed  CAS  Google Scholar 

  • Burgess AE, Colborne B (1988) Visual signal detection. IV. Observer inconsistency. J Opt Soc Am A 5: 617–627

    Article  PubMed  CAS  Google Scholar 

  • Busse L, Katzner S, Tillmann C, Treue S (2008) Effects of attention on perceptual direction tuning curves in the human visual system. J Vis 8: 1–13

    Article  PubMed  Google Scholar 

  • Dai H, Nguyen Q, Green DM (1996) Decision rules of listeners in spectral-shape discrimination with or without signal-frequency uncertainty. J Acoust Soc Am 99: 2298–2306

    Article  PubMed  CAS  Google Scholar 

  • deCharms RC, Blake DT, Merzenich MM (1998) Optimizing sound features for cortical neurons. Science 280: 1439–1443

    Article  PubMed  CAS  Google Scholar 

  • Falmagne JC (1985) Elements of psychophysical theory. Oxford University Press, New York

    Google Scholar 

  • Feth LL (1974) Frequency discrimination of complex periodic tones. Percept Psychophys 15: 375–378

    Article  Google Scholar 

  • Feth LL, Stover LJ (1987) Demodulation processes in auditory perception. In: Yost A, Watson CS (eds) Auditory processing of complex sounds. Erlbaum, Hillsdale, pp 76–86

    Google Scholar 

  • Geisler WS (2003) Ideal observer analysis. In: Chalupa L, Werner J (eds) The visual neurosciences. MIT Press, Boston, pp 825–837

    Google Scholar 

  • Green DM (1988) Profile analysis: auditory intensity discrimination. Oxford University Press, New York

    Google Scholar 

  • Green DM, Swets JA (1966) Signal detection theory and psychophysics. Wiley, New York

    Google Scholar 

  • Heinz MG, Colburn HS, Carney LH (2002) Quantifying the implications of nonlinear cochlear tuning for auditory-filter estimates. J Acoust Soc Am 111: 996–1011

    Article  PubMed  Google Scholar 

  • Hunter IW, Korenberg MJ (1986) The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. Biol Cybern 55: 135–144

    PubMed  CAS  Google Scholar 

  • Kaas JH, Hackett TA, Tramo MJ (1999) Auditory processing in primate cerebral cortex. Curr Opin Neurobiol 9(2): 164–170

    Article  PubMed  CAS  Google Scholar 

  • Korenberg MJ, Hunter IW (1986) The identification of nonlinear biological systems: LNL cascade models. Biol Cybern 55: 125–134

    PubMed  CAS  Google Scholar 

  • Marmarelis PZ, Marmarelis VZ (1978) Analysis of physiological systems: the white-noise approach. Plenum Press, New York

    Google Scholar 

  • Marmarelis PZ (2004) Nonlinear dynamic modeling of physiological systems. Wiley IEEE Press, Piscataway

    Book  Google Scholar 

  • Marr D (1985) Vision. Freeman, San Francisco

    Google Scholar 

  • Moore BC (1986) Parallels between frequency selectivity measured psychophysically and in cochlear mechanics. Scand Audiol Suppl 25: 139–152

    PubMed  CAS  Google Scholar 

  • Moore BC, Glasberg BR, Roberts B (1984) Refining the measurement of psychophysical tuning curves. J Acoust Soc Am 76(4): 1057–1066

    Article  PubMed  CAS  Google Scholar 

  • Moore BCJ (2008) Psychology of hearing. Emerald, Bingley

    Google Scholar 

  • Murray RF (2011) Classification images: A review. J Vis 11.

  • Murray RF, Bennett PJ, Sekuler AB (2005) Classification images predict absolute efficiency. J Vis 5: 139–149

    Article  PubMed  Google Scholar 

  • Neri P (2009) Nonlinear characterization of a simple process in human vision. J Vis 9: 1–29

    Article  PubMed  Google Scholar 

  • Neri P (2010a) How inherently noisy is human sensory processing?. Psychon Bull Rev 17: 802–808

    Article  PubMed  Google Scholar 

  • Neri P (2010b) Visual detection under uncertainty operates via an early static, not late dynamic, non-linearity. Front Comput Neurosci 4: 151

    Article  PubMed  Google Scholar 

  • Neri P (2010c) Stochastic characterization of small-scale algorithms for human sensory processing. Chaos 20: 045118

    Article  PubMed  Google Scholar 

  • Neri P, Levi DM (2006) Receptive versus perceptive fields from the reverse-correlation viewpoint. Vision Res 46: 2465–2474

    Article  PubMed  Google Scholar 

  • Neri P, Levi DM (2008) Evidence for joint encoding of motion and disparity in human visual perception. J Neurophysiol 100: 3117–3133

    Article  PubMed  Google Scholar 

  • Oxenham AJ (2001) Forward masking: adaptation or integration?. J Acoust Soc Am 109(2): 732–741

    Article  PubMed  CAS  Google Scholar 

  • Oxenham AJ, Dau T (2001) Reconciling frequency selectivity and phase effects in masking. J Acoust Soc Am 110(3 Pt 1): 1525–1538

    Article  PubMed  CAS  Google Scholar 

  • Oxenham AJ, Plack CJ (2000) Effects of masker frequency and duration in forward masking: further evidence for the influence of peripheral nonlinearity. Hear Res 150(1–2): 258–266

    Article  PubMed  CAS  Google Scholar 

  • Paltoglou AE, Neri P (2012) Attentional control of sensory tuning in human visual perception. J Neurophysiol 107: 1260–1274

    Article  PubMed  Google Scholar 

  • Pelli DG (1985) Uncertainty explains many aspects of visual contrast detection and discrimination. J Opt Soc Am A 2: 1508–1532

    Article  PubMed  CAS  Google Scholar 

  • Phillips DP (1985) Temporal response features of cat auditory cortex neurons contributing to sensitivity to tones delivered in the presence of continuous noise. Hear Res 19(3): 253–268

    Article  PubMed  CAS  Google Scholar 

  • Priebe NJ, Ferster D (2008) Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. Neuron 57: 482–497

    Article  PubMed  CAS  Google Scholar 

  • Richards VM, Onsan ZA, Green DM (1989) Auditory profile analysis: potential pitch cues. Hear Res 39: 27–36

    Article  PubMed  CAS  Google Scholar 

  • Richards VM, Shub DE, Carreira EM (2011) The role of masker fringes for the detection of coherent tone pips. J Acoust Soc Am 130: 883–892

    Article  PubMed  Google Scholar 

  • Ringach DL (1998) Tuning of orientation detectors in human vision. Vision Res 38: 963–972

    Article  PubMed  CAS  Google Scholar 

  • Robinson K, Holdsworth J, McKeown D, Zhang C, Patterson RD, Allerhand MH (1992) Complex sounds and auditory images. In: Cazals Y, Demany L, Horner K (eds) Auditory physiology and perception. Pergamon, Oxford, pp 429–446

    Google Scholar 

  • Schetzen M (1980) The Volterra and Wiener theories of nonlinear systems. Wiley, New York

    Google Scholar 

  • Schreiner CE (1992) Functional organization of the auditory cortex: maps and mechanisms. Curr Opin Neurobiol 2(4): 516–521

    Article  PubMed  CAS  Google Scholar 

  • Sen K, Theunissen FE, Doupe AJ (2001) Feature analysis of natural sounds in the songbird auditory forebrain. J Neurophysiol 86: 1445–1458

    PubMed  CAS  Google Scholar 

  • Shera CA, Guinan JJ, Oxenham AJ (2002) Revised estimates of human cochlear tuning from otoacoustic and behavioral measurements. Proc Natl Acad Sci USA 99: 3318–3323

    Article  PubMed  CAS  Google Scholar 

  • Shub DE, Richards VM (2009) Psychophysical spectro-temporal receptive fields in an auditory task. Hear Res 251: 1–9

    Article  PubMed  Google Scholar 

  • Slaney M (1993) An efficient implementation of the Patterson–Holdsworth auditory filter bank. Apple Computer Technical Report 35

  • Solomon JA (2002) Noise reveals visual mechanisms of detection and discrimination. J Vis 2: 105–120

    Article  PubMed  Google Scholar 

  • Spiegel MF, Picardi MC, Green DM (1981) Signal and masker uncertainty in intensity discrimination. J Acoust Soc Am 70: 1015–1019

    Article  PubMed  CAS  Google Scholar 

  • Suga N (1985) Sharpening of frequency tuning by inhibition in the central auditory system: tribute to Yasuji Katsuki. Neurosci Res 21(4): 287–299

    Article  Google Scholar 

  • Theunissen FE, Sen K, Doupe AJ (2000) Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds. J Neurosci 20: 2315–2331

    PubMed  CAS  Google Scholar 

  • Tjan BS, Nandy AS (2006) Classification images with uncertainty. J Vis 6: 387–413

    Article  PubMed  Google Scholar 

  • Westwick DT, Kearney RE (2003) Identification of nonlinear physiological systems. Wiley IEEE Press, Piscataway

    Book  Google Scholar 

  • Wilcox RR (2010) Fundamentals of modern statistical methods. Springer, New York

    Book  Google Scholar 

Download references

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Correspondence to Eva R. M. Joosten.

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Joosten, E.R.M., Neri, P. Human pitch detectors are tuned on a fine scale, but are perceptually accessed on a coarse scale. Biol Cybern 106, 465–482 (2012). https://doi.org/10.1007/s00422-012-0510-x

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