Skip to main content

Thank you for visiting 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.


Does predictive coding have a future?

A Publisher Correction to this article was published on 22 November 2018

This article has been updated

In the 20th century we thought the brain extracted knowledge from sensations. The 21st century witnessed a ‘strange inversion’, in which the brain became an organ of inference, actively constructing explanations for what’s going on ‘out there’, beyond its sensory epithelia. One paper played a key role in this paradigm shift.

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

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it


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

Fig. 1: Hierarchical predictive coding: schematics that describe the hierarchical message passing implicit in predictive coding based on deep generative models.

Katie Vicari/Springer Nature

Change history

  • 22 November 2018

    This News & Views article should have been marked as a Historical News & Views and the supertitle was incorrect.


  1. Rao, R. P. & Ballard, D. H. Nat. Neurosci. 2, 79–87 (1999).

    Article  CAS  Google Scholar 

  2. Gregory, R. L. Philos. Trans. R. Soc. Lond. B 290, 181–197 (1980).

    Article  CAS  Google Scholar 

  3. Dayan, P., Hinton, G. E., Neal, R. M. & Zemel, R. S. Neural Comput. 7, 889–904 (1995).

    Article  CAS  Google Scholar 

  4. Mumford, D. Biol. Cybern. 66, 241–251 (1992).

    Article  CAS  Google Scholar 

  5. Hohwy, J. Noûs 50, 259–285 (2016).

    Article  Google Scholar 

  6. Friston, K. Nat. Rev. Neurosci. 11, 127–138 (2010).

    Article  CAS  Google Scholar 

  7. Knill, D. C. & Pouget, A. Trends Neurosci. 27, 712–719 (2004).

    Article  CAS  Google Scholar 

  8. Clark, A. Behav. Brain Sci. 36, 181–204 (2013).

    Article  Google Scholar 

  9. Marques, T., Nguyen, J., Fioreze, G. & Petreanu, L. Nat. Neurosci. 21, 757–764 (2018).

    Article  CAS  Google Scholar 

  10. Kanai, R., Komura, Y., Shipp, S. & Friston, K. Phil. Trans. R. Soc. Lond. B (2015).

    Article  Google Scholar 

  11. Powers, A. R., Mathys, C. & Corlett, P. R. Science 357, 596–600 (2017).

    Article  CAS  Google Scholar 

  12. Friston, K. PLoS Comput. Biol. 4, e1000211 (2008).

    Article  Google Scholar 

  13. Bastos, A. M. et al. Neuron 85, 390–401 (2015).

    Article  CAS  Google Scholar 

  14. Arnal, L. H., Wyart, V. & Giraud, A. L. Nat. Neurosci. 14, 797–801 (2011).

    Article  CAS  Google Scholar 

  15. Shipp, S. Front. Psychol. 7, 1792 (2016).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Karl Friston.

Ethics declarations

Competing interests

The author declares no competing interests.

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Friston, K. Does predictive coding have a future?. Nat Neurosci 21, 1019–1021 (2018).

Download citation

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


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