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Adaptive coding of visual information in neural populations

Nature volume 452, pages 220–224 (2008)Cite this article

Abstract

Our perception of the environment relies on the capacity of neural networks to adapt rapidly to changes in incoming stimuli1,2,3,4. It is increasingly being realized that the neural code is adaptive5, that is, sensory neurons change their responses and selectivity in a dynamic manner to match the changes in input stimuli1,2,5. Understanding how rapid exposure, or adaptation, to a stimulus of fixed structure changes information processing by cortical networks is essential for understanding the relationship between sensory coding and behaviour5,6,7,8. Physiological investigations of adaptation have contributed greatly to our understanding of how individual sensory neurons change their responses to influence stimulus coding2,9,10,11,12, yet whether and how adaptation affects information coding in neural populations is unknown. Here we examine how brief adaptation (on the timescale of visual fixation)2,9,10 influences the structure of interneuronal correlations and the accuracy of population coding in the macaque (Macaca mulatta) primary visual cortex (V1). We find that brief adaptation to a stimulus of fixed structure reorganizes the distribution of correlations across the entire network by selectively reducing their mean and variability. The post-adaptation changes in neuronal correlations are associated with specific, stimulus-dependent changes in the efficiency of the population code, and are consistent with changes in perceptual performance after adaptation2,13,14. Our results have implications beyond the predictions of current theories of sensory coding, suggesting that brief adaptation improves the accuracy of population coding to optimize neuronal performance during natural viewing.

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Figure 1: Adaptation-induced response decorrelation in V1.
Figure 2: Rapid adaptation changes the structure of interneuronal correlations.
Figure 3: Rapid adaptation changes the mean and variability of correlations.
Figure 4: Rapid adaptation enhances the efficiency of population coding.

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Acknowledgements

We thank K. Josić for comments on the manuscript. This work was supported by the Pew Scholars Program, the James S. McDonnell Foundation and the National Eye Institute (V.D.).

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Authors and Affiliations

  1. Department of Neurobiology and Anatomy, University of Texas-Houston Medical School, Houston, Texas 77030, USA,

    Diego A. Gutnisky & Valentin Dragoi

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  1. Diego A. Gutnisky
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  2. Valentin Dragoi
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Correspondence to Valentin Dragoi.

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Gutnisky, D., Dragoi, V. Adaptive coding of visual information in neural populations. Nature 452, 220–224 (2008). https://doi.org/10.1038/nature06563

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