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Efficiency and ambiguity in an adaptive neural code

Author

Listed:
  • Adrienne L. Fairhall

    (NEC Research Institute)

  • Geoffrey D. Lewen

    (NEC Research Institute)

  • William Bialek

    (NEC Research Institute)

  • Robert R. de Ruyter van Steveninck

    (NEC Research Institute)

Abstract

We examine the dynamics of a neural code in the context of stimuli whose statistical properties are themselves evolving dynamically. Adaptation to these statistics occurs over a wide range of timescales—from tens of milliseconds to minutes. Rapid components of adaptation serve to optimize the information that action potentials carry about rapid stimulus variations within the local statistical ensemble, while changes in the rate and statistics of action-potential firing encode information about the ensemble itself, thus resolving potential ambiguities. The speed with which information is optimized and ambiguities are resolved approaches the physical limit imposed by statistical sampling and noise.

Suggested Citation

  • Adrienne L. Fairhall & Geoffrey D. Lewen & William Bialek & Robert R. de Ruyter van Steveninck, 2001. "Efficiency and ambiguity in an adaptive neural code," Nature, Nature, vol. 412(6849), pages 787-792, August.
    • Handle: RePEc:nat:nature:v:412:y:2001:i:6849:d:10.1038_35090500
    DOI: 10.1038/35090500
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    Cited by:

    1. Skander Mensi & Olivier Hagens & Wulfram Gerstner & Christian Pozzorini, 2016. "Enhanced Sensitivity to Rapid Input Fluctuations by Nonlinear Threshold Dynamics in Neocortical Pyramidal Neurons," PLOS Computational Biology, Public Library of Science, vol. 12(2), pages 1-38, February.
    2. Toshiyuki Ishii & Toshihiko Hosoya, 2020. "Interspike intervals within retinal spike bursts combinatorially encode multiple stimulus features," PLOS Computational Biology, Public Library of Science, vol. 16(11), pages 1-30, November.
    3. Richard Naud & Wulfram Gerstner, 2012. "Coding and Decoding with Adapting Neurons: A Population Approach to the Peri-Stimulus Time Histogram," PLOS Computational Biology, Public Library of Science, vol. 8(10), pages 1-14, October.
    4. Christian E Stilp & Keith R Kluender, 2012. "Efficient Coding and Statistically Optimal Weighting of Covariance among Acoustic Attributes in Novel Sounds," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-13, January.
    5. Jonathan Rubin & Nachum Ulanovsky & Israel Nelken & Naftali Tishby, 2016. "The Representation of Prediction Error in Auditory Cortex," PLOS Computational Biology, Public Library of Science, vol. 12(8), pages 1-28, August.
    6. Noga Mosheiff & Haggai Agmon & Avraham Moriel & Yoram Burak, 2017. "An efficient coding theory for a dynamic trajectory predicts non-uniform allocation of entorhinal grid cells to modules," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-19, June.
    7. J. Gerard Wolff, 2019. "Information Compression as a Unifying Principle in Human Learning, Perception, and Cognition," Complexity, Hindawi, vol. 2019, pages 1-38, February.
    8. Jonathan Schaffner & Sherry Dongqi Bao & Philippe N. Tobler & Todd A. Hare & Rafael Polania, 2023. "Sensory perception relies on fitness-maximizing codes," Nature Human Behaviour, Nature, vol. 7(7), pages 1135-1151, July.
    9. Sungho Hong & Brian Nils Lundstrom & Adrienne L Fairhall, 2008. "Intrinsic Gain Modulation and Adaptive Neural Coding," PLOS Computational Biology, Public Library of Science, vol. 4(7), pages 1-11, July.
    10. David D. Woods, 2018. "The theory of graceful extensibility: basic rules that govern adaptive systems," Environment Systems and Decisions, Springer, vol. 38(4), pages 433-457, December.
    11. Braden A W Brinkman & Alison I Weber & Fred Rieke & Eric Shea-Brown, 2016. "How Do Efficient Coding Strategies Depend on Origins of Noise in Neural Circuits?," PLOS Computational Biology, Public Library of Science, vol. 12(10), pages 1-34, October.
    12. Corentin Massot & Adam D Schneider & Maurice J Chacron & Kathleen E Cullen, 2012. "The Vestibular System Implements a Linear–Nonlinear Transformation In Order to Encode Self-Motion," PLOS Biology, Public Library of Science, vol. 10(7), pages 1-20, July.
    13. Klaus Wimmer & K Jannis Hildebrandt & R Matthias Hennig & Klaus Obermayer, 2008. "Adaptation and Selective Information Transmission in the Cricket Auditory Neuron AN2," PLOS Computational Biology, Public Library of Science, vol. 4(9), pages 1-18, September.
    14. Martinez-Saito, Mario, 2022. "Discrete scaling and criticality in a chain of adaptive excitable integrators," Chaos, Solitons & Fractals, Elsevier, vol. 163(C).

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