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Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex

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  • Michael Wehr

    (Cold Spring Harbor Laboratory)

  • Anthony M. Zador

    (Cold Spring Harbor Laboratory)

Abstract

Neurons in the primary auditory cortex are tuned to the intensity and specific frequencies of sounds, but the synaptic mechanisms underlying this tuning remain uncertain. Inhibition seems to have a functional role in the formation of cortical receptive fields, because stimuli often suppress similar or neighbouring responses1,2,3, and pharmacological blockade of inhibition broadens tuning curves4,5. Here we use whole-cell recordings in vivo to disentangle the roles of excitatory and inhibitory activity in the tone-evoked responses of single neurons in the auditory cortex. The excitatory and inhibitory receptive fields cover almost exactly the same areas, in contrast to the predictions of classical lateral inhibition models. Thus, although inhibition is typically as strong as excitation, it is not necessary to establish tuning, even in the receptive field surround. However, inhibition and excitation occurred in a precise and stereotyped temporal sequence: an initial barrage of excitatory input was rapidly quenched by inhibition, truncating the spiking response within a few (1–4) milliseconds. Balanced inhibition might thus serve to increase the temporal precision6 and thereby reduce the randomness of cortical operation, rather than to increase noise as has been proposed previously7.

Suggested Citation

  • Michael Wehr & Anthony M. Zador, 2003. "Balanced inhibition underlies tuning and sharpens spike timing in auditory cortex," Nature, Nature, vol. 426(6965), pages 442-446, November.
  • Handle: RePEc:nat:nature:v:426:y:2003:i:6965:d:10.1038_nature02116
    DOI: 10.1038/nature02116
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    Citations

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    Cited by:

    1. David Pérez-González & Olga Hernández & Ellen Covey & Manuel S Malmierca, 2012. "GABAA-Mediated Inhibition Modulates Stimulus-Specific Adaptation in the Inferior Colliculus," PLOS ONE, Public Library of Science, vol. 7(3), pages 1-14, March.
    2. Panagiotis Fotiadis & Matthew Cieslak & Xiaosong He & Lorenzo Caciagli & Mathieu Ouellet & Theodore D. Satterthwaite & Russell T. Shinohara & Dani S. Bassett, 2023. "Myelination and excitation-inhibition balance synergistically shape structure-function coupling across the human cortex," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    3. Catalina Vich & Rafel Prohens & Antonio E. Teruel & Antoni Guillamon, 2020. "Estimation of Synaptic Activity during Neuronal Oscillations," Mathematics, MDPI, vol. 8(12), pages 1-22, December.
    4. Deng, Liyuan & Huo, Siyu & Chen, Aihua & Liu, Zonghua, 2024. "Coupling resonance of signal responses induced by heterogeneously mixed positive and negative couplings in cognitive subnetworks," Chaos, Solitons & Fractals, Elsevier, vol. 180(C).
    5. Sean T Kelly & Jens Kremkow & Jianzhong Jin & Yushi Wang & Qi Wang & Jose-Manuel Alonso & Garrett B Stanley, 2014. "The Role of Thalamic Population Synchrony in the Emergence of Cortical Feature Selectivity," PLOS Computational Biology, Public Library of Science, vol. 10(1), pages 1-13, January.
    6. Margot C Bjoring & C Daniel Meliza, 2019. "A low-threshold potassium current enhances sparseness and reliability in a model of avian auditory cortex," PLOS Computational Biology, Public Library of Science, vol. 15(1), pages 1-20, January.
    7. Georgios Spyropoulos & Matteo Saponati & Jarrod Robert Dowdall & Marieke Louise Schölvinck & Conrado Arturo Bosman & Bruss Lima & Alina Peter & Irene Onorato & Johanna Klon-Lipok & Rasmus Roese & Serg, 2022. "Spontaneous variability in gamma dynamics described by a damped harmonic oscillator driven by noise," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    8. Mizusaki, Beatriz E.P. & Agnes, Everton J. & Erichsen, Rubem & Brunnet, Leonardo G., 2017. "Learning and retrieval behavior in recurrent neural networks with pre-synaptic dependent homeostatic plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 279-286.
    9. Manoj Kumar & Gregory Handy & Stylianos Kouvaros & Yanjun Zhao & Lovisa Ljungqvist Brinson & Eric Wei & Brandon Bizup & Brent Doiron & Thanos Tzounopoulos, 2023. "Cell-type-specific plasticity of inhibitory interneurons in the rehabilitation of auditory cortex after peripheral damage," Nature Communications, Nature, vol. 14(1), pages 1-23, December.
    10. Daniel Bendor, 2015. "The Role of Inhibition in a Computational Model of an Auditory Cortical Neuron during the Encoding of Temporal Information," PLOS Computational Biology, Public Library of Science, vol. 11(4), pages 1-25, April.
    11. Tomáš Hromádka & Michael R DeWeese & Anthony M Zador, 2008. "Sparse Representation of Sounds in the Unanesthetized Auditory Cortex," PLOS Biology, Public Library of Science, vol. 6(1), pages 1-14, January.
    12. James M McFarland & Yuwei Cui & Daniel A Butts, 2013. "Inferring Nonlinear Neuronal Computation Based on Physiologically Plausible Inputs," PLOS Computational Biology, Public Library of Science, vol. 9(7), pages 1-18, July.
    13. Shan Shen & Xiaolong Jiang & Federico Scala & Jiakun Fu & Paul Fahey & Dmitry Kobak & Zhenghuan Tan & Na Zhou & Jacob Reimer & Fabian Sinz & Andreas S. Tolias, 2022. "Distinct organization of two cortico-cortical feedback pathways," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    14. Katie H. Long & Justin D. Lieber & Sliman J. Bensmaia, 2022. "Texture is encoded in precise temporal spiking patterns in primate somatosensory cortex," Nature Communications, Nature, vol. 13(1), pages 1-12, December.

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