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.


An alternative to backpropagation through time

Recurrent networks can be trained using a generalization of backpropagation, called backpropagation through time, but a gap exists between the mathematics of this learning algorithm and biological plausibility. E-prop is a biologically inspired alternative that opens up possibilities for a new generation of online training algorithms for recurrent networks.

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

Access options

Rent or buy this article

Prices vary by article type



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

Fig. 1: Recurrent neural networks are composed by loops that introduce temporal dependencies among nodes activities.


  1. Silver, D. et al. Nature 550, 354–359 (2017).

    Article  Google Scholar 

  2. Bellec, G. et al. Preprint at (2019).

  3. Werbos, P. J. Proc. IEEE 78, 1550–1560 (1990).

    Article  Google Scholar 

  4. Clopath, C., Büsing, L., Vasilaki, E. & Gerstner, W. Nat. Neurosci. 13, 344–352 (2010).

    Article  Google Scholar 

  5. Williams, R. J. & Zipser, D. Neural Comput. 1, 270–280 (1989).

    Article  Google Scholar 

  6. Sutton, R. S. & Barto, A. G. Introduction to Reinforcement Learning Vol. 2 (MIT Press, 1998).

  7. Vasilaki, E., Frémaux, N., Urbanczik, R., Senn, W. & Gerstner, W. PLOS Comput. Biol. 5, e1000586 (2009).

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Eleni Vasilaki.

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

Manneschi, L., Vasilaki, E. An alternative to backpropagation through time. Nat Mach Intell 2, 155–156 (2020).

Download citation

  • Published:

  • Issue Date:

  • DOI:


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