New Results

A Neuronal Least-Action Principle for Real-Time Learning in Cortical Circuits

Walter Senn, Dominik Dold, Akos F. Kungl, Benjamin Ellenberger, Jakob Jordan, Yoshua Bengio, João Sacramento, Mihai A. Petrovici
doi: https://doi.org/10.1101/2023.03.25.534198

Article Information

doi 
https://doi.org/10.1101/2023.03.25.534198
History 
  • March 25, 2023.

Article Versions

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Author Information

  1. Walter Senn*,a,#,
  2. Dominik Dold*,a,b,c,
  3. Akos F. Kungla,b,
  4. Benjamin Ellenbergera,f,
  5. Jakob Jordana,
  6. Yoshua Bengiod,
  7. João Sacramentoe and
  8. Mihai A. Petrovici*,a,b
  1. aDepartment of Physiology, University of Bern
  2. bKirchhoff-Institute for Physics, Heidelberg University
  3. cEuropean Space Research and Technology Centre, European Space Agency
  4. dMILA, University of Montreal
  5. eDepartment of Computer Science, ETH Zurich
  6. fInsel Data Science Center, University Hospital Bern
  1. ↵#Corresponding author; email: senn{at}pyl.unibe.ch

  1. ↵* Equal contribution

Back to top
Posted March 25, 2023.
Download PDF
Email
A Neuronal Least-Action Principle for Real-Time Learning in Cortical Circuits
Walter Senn, Dominik Dold, Akos F. Kungl, Benjamin Ellenberger, Jakob Jordan, Yoshua Bengio, João Sacramento, Mihai A. Petrovici
bioRxiv 2023.03.25.534198; doi: https://doi.org/10.1101/2023.03.25.534198
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools

Subject Area