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Efficiency and ambiguity in an adaptive neural code

Nature volume 412, pages 787–792 (2001)Cite this article

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.

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Figure 1: Variance-switching experiment.
Figure 2: Input/output relations from the switching experiment.
Figure 3: Time dependence of the information transmission.
Figure 4: A stimulus with randomly modulated variance.
Figure 5: Discrimination using the statistics of interspike intervals in a switching experiment.

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Acknowledgements

We thank B. Agüera y Arcas, T. Adelman and N. Brenner for discussions, and R. Petersen and N. Ulanovsk for comments on the manuscript.

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Authors and Affiliations

  1. NEC Research Institute, 4 Independence Way, Princeton, 08540, New Jersey, USA

    Adrienne L. Fairhall, Geoffrey D. Lewen, William Bialek & Robert R. de Ruyter van Steveninck

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  1. Adrienne L. Fairhall
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  2. Geoffrey D. Lewen
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  3. William Bialek
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  4. Robert R. de Ruyter van Steveninck
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Correspondence to Adrienne L. Fairhall.

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Fairhall, A., Lewen, G., Bialek, W. et al. Efficiency and ambiguity in an adaptive neural code. Nature 412, 787–792 (2001). https://doi.org/10.1038/35090500

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