Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

NEURAL DECODING

Good decisions require more than information

Nature Neuroscience volume 24, pages 903–904 (2021)Cite this article

Subjects

Sensory information encoding in the mouse brain is more suboptimal when mice make correct decisions than when they make incorrect ones. These suboptimal encoding structures can help information flow between different brain regions, enhancing the ability of these brain regions to work together to make decisions.

Your brain receives a near-constant stream of incoming information from your senses, which it uses to infer the state of the world and select actions. Given the importance of sensory-guided decisions, it seems intuitive that increasing sensory information must translate to better choices. This perspective underlies the long-standing ‘efficient coding’ hypothesis, which states that neural circuits should be near-optimal in terms of their ability to encode sensory information in neuronal activity patterns. First proposed in 1954 by Attneave and separately by Barlow in 1961, the efficient coding hypothesis has been instrumental in our understanding of neural circuits in the sensory periphery1,2,3,4. However, recent work in ‘higher-order’ association cortex, by Valente and colleagues in Nature Neuroscience5, has challenged this long-standing idea.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Internal consistency influences decision-making.

References

  1. Attneave, F. Psychol. Rev. 61, 183 (1954).

    Article  CAS  Google Scholar 

  2. Barlow, H. B. Sens. Commun. 1, 217–234 (1961).

    Google Scholar 

  3. Atick, J. J. & Redlich, A. N. Neural Comput. 4, 196–210 (1992).

    Article  Google Scholar 

  4. Olshausen, B. A. & Field, D. J. Nature 381, 607–609 (1996).

    Article  CAS  Google Scholar 

  5. Valente, M. et al. Nat. Neurosci. https://doi.org/10.1038/s41593-021-00845-1 (2021).

  6. Averbeck, B. B., Latham, P. E. & Pouget, A. Nat. Rev. Neurosci. 7, 358–366 (2006).

    Article  CAS  Google Scholar 

  7. Moreno-Bote, R. et al. Nat. Neurosci. 17, 1410–1417 (2014).

    Article  CAS  Google Scholar 

  8. Zylberberg, J., Pouget, A., Latham, P. E. & Shea-Brown, E. PLoS Comput. Biol. 13, e1005497 (2017).

    Article  Google Scholar 

  9. Cayco-Gajic, N. A. & Sweeney, Y. J. Neurosci. 38, 6442–6444 (2018).

    Article  CAS  Google Scholar 

  10. Parker, P. R., Brown, M. A., Smear, M. C. & Niell, C. M. Trends Neurosci. 43, 581–595 (2020).

    Article  CAS  Google Scholar 

  11. Siegle, J. H. et al. Nature 592, 86–92 (2021).

    CAS  PubMed  Google Scholar 

  12. Panzeri, S., Harvey, C. D., Piasini, E., Latham, P. E. & Fellin, T. Neuron 93, 491–507 (2017).

    Article  CAS  Google Scholar 

  13. Richards, B. A. et al. Nat. Neurosci. 22, 1761–1770 (2019).

    Article  CAS  Google Scholar 

  14. DiCarlo, J. J., Zoccolan, D. & Rust, N. C. Neuron 73, 415–434 (2012).

    Article  CAS  Google Scholar 

  15. Couzin, I. D. et al. Science 334, 1578–1580 (2011).

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Group for Neural Theory, Laboratoire de Neurosciences Cognitives et Computationnelles, Département d’Etudes Cognitives, École Normale Supérieure, Université Paris Sciences et Lettres, Paris, France

    N. Alex Cayco-Gajic

  2. Department of Physics and Astronomy, and Centre for Vision Research, York University, Toronto, Ontario, Canada

    Joel Zylberberg

  3. Learning in Machines and Brains Program, Canadian Institute for Advanced Research (CIFAR), Toronto, Ontario, Canada

    Joel Zylberberg

Authors
  1. N. Alex Cayco-Gajic
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joel Zylberberg
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joel Zylberberg.

Ethics declarations

Competing interests

The authors declare no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cayco-Gajic, N.A., Zylberberg, J. Good decisions require more than information. Nat Neurosci 24, 903–904 (2021). https://doi.org/10.1038/s41593-021-00883-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-021-00883-9

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing