Auditory Frequency and Intensity Discrimination Explained Using a Cortical Population Rate Code

Christophe Micheyl, Paul R Schrater and Andrew J Oxenham

PLOS Computational Biology, 2013, vol. 9, issue 11, 1-7

Abstract: The nature of the neural codes for pitch and loudness, two basic auditory attributes, has been a key question in neuroscience for over century. A currently widespread view is that sound intensity (subjectively, loudness) is encoded in spike rates, whereas sound frequency (subjectively, pitch) is encoded in precise spike timing. Here, using information-theoretic analyses, we show that the spike rates of a population of virtual neural units with frequency-tuning and spike-count correlation characteristics similar to those measured in the primary auditory cortex of primates, contain sufficient statistical information to account for the smallest frequency-discrimination thresholds measured in human listeners. The same population, and the same spike-rate code, can also account for the intensity-discrimination thresholds of humans. These results demonstrate the viability of a unified rate-based cortical population code for both sound frequency (pitch) and sound intensity (loudness), and thus suggest a resolution to a long-standing puzzle in auditory neuroscience.Author Summary: A widely held view among auditory scientists is that the neural code for sound intensity (or loudness) involves temporally coarse spike-rate information, whereas the code for sound frequency (or pitch) requires more fine-grained and precise spike timing information. One problem with this view is that neurons in auditory cortex do not produce precisely time-locked responses to higher frequencies within the pitch range, suggesting that a transformation to a rate code must occur. However, because cortical neurons exhibit relatively broad tuning to frequency and correlated spike counts, it is unclear whether a cortical population code based on spike rates alone can support the remarkably precise pitch-discrimination ability of humans. Here we show that a relatively small population of virtual neurons with frequency-tuning and spike-count correlation characteristics consistent with those of actual neurons in the primary auditory cortex of primates, can account for both the smallest frequency- and intensity-discrimination thresholds measured behaviorally in humans. These results suggest a resolution to a long-standing puzzle in auditory neuroscience.

Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003336 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 03336&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1003336

DOI: 10.1371/journal.pcbi.1003336

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().