New Results
Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks
View ORCID ProfileAnand Subramoney, View ORCID ProfileGuillaume Bellec, View ORCID ProfileFranz Scherr, View ORCID ProfileRobert Legenstein, View ORCID ProfileWolfgang Maass
doi: https://doi.org/10.1101/2021.01.25.428153
Anand Subramoney
1Institute for Theoretical Computer Science, Graz University of Technology, Austria
2Institute for Neural Computation, Ruhr University Bochum, Germany
Guillaume Bellec
1Institute for Theoretical Computer Science, Graz University of Technology, Austria
3Laboratory of Computational Neuroscience, Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland
Franz Scherr
1Institute for Theoretical Computer Science, Graz University of Technology, Austria
Robert Legenstein
1Institute for Theoretical Computer Science, Graz University of Technology, Austria
Wolfgang Maass
1Institute for Theoretical Computer Science, Graz University of Technology, Austria
Article usage
Posted January 27, 2021.
Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks
Anand Subramoney, Guillaume Bellec, Franz Scherr, Robert Legenstein, Wolfgang Maass
bioRxiv 2021.01.25.428153; doi: https://doi.org/10.1101/2021.01.25.428153
Subject Area
Subject Areas
- Biochemistry (11752)
- Bioengineering (8752)
- Bioinformatics (29200)
- Biophysics (14974)
- Cancer Biology (12096)
- Cell Biology (17411)
- Clinical Trials (138)
- Developmental Biology (9421)
- Ecology (14182)
- Epidemiology (2067)
- Evolutionary Biology (18308)
- Genetics (12245)
- Genomics (16803)
- Immunology (11869)
- Microbiology (28097)
- Molecular Biology (11594)
- Neuroscience (60969)
- Paleontology (451)
- Pathology (1871)
- Pharmacology and Toxicology (3238)
- Physiology (4959)
- Plant Biology (10427)
- Synthetic Biology (2886)
- Systems Biology (7340)
- Zoology (1651)