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.

  • News & Views
  • Published:

Computational neuroscience

Spatially embedded neuromorphic networks

Nature Machine Intelligence volume 5, pages 1342–1343 (2023)Cite this article

Subjects

A framework for training artificial neural networks in physical space allows neuroscientists to build networks that look and function like real brains.

Access through your institution
Buy or subscribe

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

Relevant articles

Open Access articles citing this article.

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: Spatially embedded recurrent neural networks yield neuromorphic architectures.

References

  1. Bullmore, E. & Sporns, O. Nat. Rev. Neurosci. 13, 336–349 (2012).

    Article  Google Scholar 

  2. Achterberg, J., Akarca, D., Strouse, D. J., Duncan, J. & Astle, D. Nat. Mach. Intell. https://doi.org/10.1038/s42256-023-00748-9 (2023).

    Article  Google Scholar 

  3. Sporns, O. Curr. Opin. Neurobiol. 23, 162–171 (2013).

    Article  Google Scholar 

  4. Zador, A. et al. Nat. Commun. 14, 1597 (2023).

    Article  Google Scholar 

  5. Tanaka, G. et al. Neural Netw. 115, 100–123 (2019).

    Article  Google Scholar 

  6. Suárez, L. E., Markello, R. D., Betzel, R. F. & Misic, B. Trends Cogn. Sci. 24, 302–315 (2020).

    Article  Google Scholar 

  7. Betzel, R. F. & Bassett, D. S. J. Roy. Soc. Interface 14, 20170623 (2017).

    Article  Google Scholar 

  8. Loeffler, A. et al. Neuromorph. Comput. Eng. 1, 014003 (2021).

    Article  Google Scholar 

  9. Yang, G. R., Joglekar, M. R., Song, H. F., Newsome, W. T. & Wang, X.-J. J. Nat. Neurosci. 22, 297–306 (2019).

    Article  Google Scholar 

  10. Scholtens, L. H., de Lange, S. C. & van den Heuvel, M. P. Zenodo https://zenodo.org/records/5346593 (2021).

Download references

Author information

Authors and Affiliations

  1. Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada

    Filip Milisav & Bratislav Misic

Authors
  1. Filip Milisav
    View author publications

    Search author on:PubMed Google Scholar

  2. Bratislav Misic
    View author publications

    Search author on:PubMed Google Scholar

Corresponding author

Correspondence to Bratislav Misic.

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

Milisav, F., Misic, B. Spatially embedded neuromorphic networks. Nat Mach Intell 5, 1342–1343 (2023). https://doi.org/10.1038/s42256-023-00771-w

Download citation

  • Published:

  • Issue date:

  • DOI: https://doi.org/10.1038/s42256-023-00771-w

This article is cited by

Search

Advanced search

Quick links

Nature Briefing AI and Robotics

Sign up for the Nature Briefing: AI and Robotics newsletter — what matters in AI and robotics research, free to your inbox weekly.

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