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Diverse coupling of neurons to populations in sensory cortex

Author

Listed:
  • Michael Okun

    (UCL Institute of Neurology, University College London
    Physiology and Pharmacology, University College London
    UCL Institute of Ophthalmology, University College London)

  • Nicholas A. Steinmetz

    (UCL Institute of Neurology, University College London
    Physiology and Pharmacology, University College London
    UCL Institute of Ophthalmology, University College London
    Stanford University, Stanford, California 94305-5125, USA)

  • Lee Cossell

    (Physiology and Pharmacology, University College London
    Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland)

  • M. Florencia Iacaruso

    (Physiology and Pharmacology, University College London
    Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland)

  • Ho Ko

    (Physiology and Pharmacology, University College London
    Present addresses: Lui Che Woo Institute for Innovative Medicine and Chow Yuk Ho Technology Center for Innovative Medicine, Faculty of Medicine, the Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China (H.K.); MTA-TTK NAP-B Sleep Oscillations Research Group, Research Center for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2, 1117 Budapest, Hungary (P.B.).)

  • Péter Barthó

    (Center for Molecular and Behavioral Neuroscience, Rutgers University, 197 University Avenue, Newark, New Jersey 07102, USA
    Present addresses: Lui Che Woo Institute for Innovative Medicine and Chow Yuk Ho Technology Center for Innovative Medicine, Faculty of Medicine, the Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China (H.K.); MTA-TTK NAP-B Sleep Oscillations Research Group, Research Center for Natural Sciences, Hungarian Academy of Sciences, Magyar tudósok körútja 2, 1117 Budapest, Hungary (P.B.).)

  • Tirin Moore

    (Stanford University, Stanford, California 94305-5125, USA)

  • Sonja B. Hofer

    (Physiology and Pharmacology, University College London
    Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland)

  • Thomas D. Mrsic-Flogel

    (Physiology and Pharmacology, University College London
    Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland)

  • Matteo Carandini

    (UCL Institute of Ophthalmology, University College London)

  • Kenneth D. Harris

    (UCL Institute of Neurology, University College London
    Physiology and Pharmacology, University College London
    Center for Molecular and Behavioral Neuroscience, Rutgers University, 197 University Avenue, Newark, New Jersey 07102, USA)

Abstract

Exploring the relationship between population coupling and neuronal activity reveals that neighbouring neurons can differ in their coupling to the overall firing rate of the population, the circuitry of which may potentially help to explain the complex activity patterns in cortical populations.

Suggested Citation

  • Michael Okun & Nicholas A. Steinmetz & Lee Cossell & M. Florencia Iacaruso & Ho Ko & Péter Barthó & Tirin Moore & Sonja B. Hofer & Thomas D. Mrsic-Flogel & Matteo Carandini & Kenneth D. Harris, 2015. "Diverse coupling of neurons to populations in sensory cortex," Nature, Nature, vol. 521(7553), pages 511-515, May.
    • Handle: RePEc:nat:nature:v:521:y:2015:i:7553:d:10.1038_nature14273
    DOI: 10.1038/nature14273
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    Citations

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    Cited by:

    1. Qin, Ying-Mei & Che, Yan-Qiu & Zhao, Jia, 2018. "Effects of degree distributions on signal propagation in noisy feedforward neural networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 763-774.
    2. Jan Humplik & Gašper Tkačik, 2017. "Probabilistic models for neural populations that naturally capture global coupling and criticality," PLOS Computational Biology, Public Library of Science, vol. 13(9), pages 1-26, September.
    3. Rong J. B. Zhu & Xue-Xin Wei, 2023. "Unsupervised approach to decomposing neural tuning variability," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    4. Volker Pernice & Rava Azeredo da Silveira, 2018. "Interpretation of correlated neural variability from models of feed-forward and recurrent circuits," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-26, February.
    5. Yifan Gu & Yang Qi & Pulin Gong, 2019. "Rich-club connectivity, diverse population coupling, and dynamical activity patterns emerging from local cortical circuits," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-34, April.
    6. Giovanni Diana & Thomas T J Sainsbury & Martin P Meyer, 2019. "Bayesian inference of neuronal assemblies," PLOS Computational Biology, Public Library of Science, vol. 15(10), pages 1-31, October.
    7. Guillaume Viejo & Thomas Cortier & Adrien Peyrache, 2018. "Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-25, March.
    8. Christian Donner & Klaus Obermayer & Hideaki Shimazaki, 2017. "Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-27, January.
    9. Richard F Betzel & Katherine C Wood & Christopher Angeloni & Maria Neimark Geffen & Danielle S Bassett, 2019. "Stability of spontaneous, correlated activity in mouse auditory cortex," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-25, December.
    10. Sravani Kondapavulur & Stefan M. Lemke & David Darevsky & Ling Guo & Preeya Khanna & Karunesh Ganguly, 2022. "Transition from predictable to variable motor cortex and striatal ensemble patterning during behavioral exploration," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    11. Itamar Daniel Landau & Haim Sompolinsky, 2018. "Coherent chaos in a recurrent neural network with structured connectivity," PLOS Computational Biology, Public Library of Science, vol. 14(12), pages 1-27, December.
    12. Yann Zerlaut & Alain Destexhe, 2017. "Heterogeneous firing responses predict diverse couplings to presynaptic activity in mice layer V pyramidal neurons," PLOS Computational Biology, Public Library of Science, vol. 13(4), pages 1-27, April.

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