Letter | Published:

Ultra-fine frequency tuning revealed in single neurons of human auditory cortex

Nature volume 451, pages 197201 (10 January 2008) | Download Citation

Subjects

Abstract

Just-noticeable differences of physical parameters are often limited by the resolution of the peripheral sensory apparatus. Thus, two-point discrimination in vision is limited by the size of individual photoreceptors. Frequency selectivity is a basic property of neurons in the mammalian auditory pathway1,2. However, just-noticeable differences of frequency are substantially smaller than the bandwidth of the peripheral sensors3. Here we report that frequency tuning in single neurons recorded from human auditory cortex in response to random-chord stimuli is far narrower than that typically described in any other mammalian species (besides bats), and substantially exceeds that attributed to the human auditory periphery. Interestingly, simple spectral filter models failed to predict the neuronal responses to natural stimuli, including speech and music. Thus, natural sounds engage additional processing mechanisms beyond the exquisite frequency tuning probed by the random-chord stimuli.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    et al. A chronic microelectrode investigation of the tonotopic organization of human auditory cortex. Brain Res. 724, 260–264 (1996)

  2. 2.

    in Integrative Functions in the Mammalian Auditory Pathway (eds Oertel, D., Popper, A. N. & Fay, R. R.) 358–416 (Springer, New York, 2002)

  3. 3.

    An Introduction to the Psychology of Hearing Ch. 3 74–114 (Academic Press, London, 1982)

  4. 4.

    in Psychophysics and Physiology of Hearing (eds Evans, E. F. & Wilson, J. P.) 185–196 (Academic Press, London, 1977)

  5. 5.

    & Frequency resolution and spectral integration (critical band analysis) in single units of the cat primary auditory cortex. J. Comp. Physiol. A 181, 635–650 (1997)

  6. 6.

    & Complex sound analysis (frequency resolution, filtering and spectral integration) by single units of the inferior colliculus of the cat. Brain Res. 472, 139–163 (1988)

  7. 7.

    , & Evaluating auditory performance limits: I. One-parameter discrimination using a computational model for the auditory nerve. Neural Comput. 13, 2273–2316 (2001)

  8. 8.

    et al. Cerebral microdialysis combined with single-neuron and electroencephalographic recording in neurosurgical patients. J. Neurosurg. 91, 697–705 (1999)

  9. 9.

    & Poor frequency discrimination probes dyslexics with particularly impaired working memory. Audiol. Neurootol. 9, 328–340 (2004)

  10. 10.

    , & Spectral-temporal receptive fields of nonlinear auditory neurons obtained using natural sounds. J. Neurosci. 20, 2315–2331 (2000)

  11. 11.

    , & Stimulus-dependent auditory tuning results in synchronous population coding of vocalizations in the songbird midbrain. J. Neurosci. 26, 2499–2512 (2006)

  12. 12.

    , & Quantifying variability in neural responses and its application for the validation of model predictions. Network 15, 91–109 (2004)

  13. 13.

    , & Modular organization of intrinsic connections associated with spectral tuning in cat auditory cortex. Proc. Natl Acad. Sci. USA 98, 8042–8047 (2001)

  14. 14.

    & Anesthesia changes frequency tuning of neurons in the rat primary auditory cortex. J. Neurophysiol. 86, 1062–1066 (2001)

  15. 15.

    , , , & Time course of tonal frequency-response-area of primary auditory cortex neurons in alert cats. Neurosci. Res. 46, 145–152 (2003)

  16. 16.

    , , , & Responses of neurons in primary auditory cortex (A1) to pure tones in the halothane-anesthetized cat. J. Neurophysiol. 95, 3756–3769 (2006)

  17. 17.

    , & Frequency and intensity response properties of single neurons in the auditory cortex of the behaving macaque monkey. J. Neurophysiol. 83, 2315–2331 (2000)

  18. 18.

    & Spectral response patterns of auditory cortex neurons to harmonic complex tones in alert monkey (Macaca mulatta). J. Neurophysiol. 64, 282–298 (1990)

  19. 19.

    , , & Spectrotemporal receptive fields in the lemniscal auditory thalamus and cortex. J. Neurophysiol. 87, 516–527 (2002)

  20. 20.

    , & Functional role of auditory cortex in frequency processing and pitch perception. J. Neurophysiol. 87, 122–139 (2002)

  21. 21.

    , , , & Invariant visual representation by single neurons in the human brain. Nature 435, 1102–1107 (2005)

  22. 22.

    & Infant discrimination of rapid auditory cues predicts later language impairment. Behav. Brain Res. 136, 31–49 (2002)

  23. 23.

    & Auditory processing deficits in dyslexia: task or stimulus related? Cereb. Cortex 16, 1718–1728 (2006)

  24. 24.

    & Speech and non-speech processing in people with specific language impairment: a behavioural and electrophysiological study. Brain Lang. 94, 260–273 (2005)

  25. 25.

    , & Optimizing sound features for cortical neurons. Science 280, 1439–1443 (1998)

  26. 26.

    , & Linear processing of spatial cues in primary auditory cortex. Nature 414, 200–204 (2001)

  27. 27.

    et al. Estimating spatio-temporal receptive fields of auditory and visual neurons from their responses to natural stimuli. Network 12, 289–316 (2001)

  28. 28.

    et al. Coupling between neuronal firing, field potentials, and FMRI in human auditory cortex. Science 309, 951–954 (2005)

  29. 29.

    , & Aim-mat: the auditory image model in MATLAB. Acta Acustica 90, 781–788 (2004)

Download references

Acknowledgements

We thank the patients for their cooperation in participating in the experiments. We thank E. Behnke, T. A. Fields, E. Ho and C. Wilson for technical assistance. This work was supported by an ISF grant (to I.N.), a NINDS grant (to I.F.), the US-Israel BSF fund (R.M. and I.F.) and a European Molecular Biology Organization and Human Frontier Science Program fellowship (R.M.).

Author information

Affiliations

  1. Department of Neurobiology, Life Science Institute,

    • Y. Bitterman
    •  & I. Nelken
  2. Interdisciplinary Center for Neural Computation, Hebrew University, Jerusalem 91904, Israel

    • Y. Bitterman
    •  & I. Nelken
  3. Ahmanson-Lovelace Brain Mapping Center, David Geffen School of Medicine,

    • R. Mukamel
  4. Division of Neurosurgery, David Geffen School of Medicine and Semel Institute for Neuroscience and Human Behaviour, University of California Los Angeles (UCLA), Los Angeles, California 90095, USA

    • R. Mukamel
    •  & I. Fried
  5. Department of Neurobiology, Weizmann Institute of Science, Rehovot 76100, Israel

    • R. Malach
  6. Functional Neurosurgery Unit, Tel Aviv Sourasky Medical Center and Sackler School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel

    • I. Fried

Authors

  1. Search for Y. Bitterman in:

  2. Search for R. Mukamel in:

  3. Search for R. Malach in:

  4. Search for I. Fried in:

  5. Search for I. Nelken in:

Corresponding authors

Correspondence to I. Fried or I. Nelken.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    The file contains Supplementary Notes and Supplementary Figure 1 with Legend, on the subjects of response reproducibility and evaluation of STRFs predictive power.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature06476

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.