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

Eva R M Joosten, Peter Neri

Research output: Contribution to journalArticle

6 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)465-482
Number of pages18
JournalBiological Cybernetics
Volume106
Issue number8-9
Early online date2 Aug 2012
DOIs
Publication statusPublished - Oct 2012

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Keywords

  • acoustic stimulation
  • auditory pathways
  • humans
  • models, neurological
  • neurons
  • pitch perception
  • noise image classification
  • computational modeling
  • psychophysics
  • MAX uncertainty model

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