Academic Bibliography

 Search 200 years of publications by Ghent University researchers.
Advanced search
1 file | 477.91 KB
Add to list
  1. Search results
  2. New insights on homeostatic activity-...

New insights on homeostatic activity-dependent structural plasticity in rate based neural networks

Tanguy Cazalets (UGent) and Joni Dambre (UGent)
(2023) 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings.
Author
Organization
Abstract
We introduce a novel rate-based homeostatic activity-dependent structural plasticity (HADSP) algorithm for echo state networks (ESNs). The algorithm employs solely homeostatic plasticity, yet enables the emergence of principles of Hebbian learning. Our analysis suggest that HADSP is able to generate networks that effectively recombine redundant inputs to improve performances and highlight the role of structural plasticity in influencing network function and organization.

Downloads

  • Download
    Guides-from-nature-neuroscience-theoretical-biology-complex-systems Tanguy-Cazalets.pdf
    • full text (Published version)
    • |
    • open access
    • |
    • PDF
    • |
    • 477.91 KB

Citation

Please use this url to cite or link to this publication:

MLA
Cazalets, Tanguy, and Joni Dambre. “New Insights on Homeostatic Activity-Dependent Structural Plasticity in Rate Based Neural Networks.” 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings, 2023.
APA
Cazalets, T., & Dambre, J. (2023). New insights on homeostatic activity-dependent structural plasticity in rate based neural networks. 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings. Presented at the 2023 International Conference on Neuromorphic, Natural and Physical Computing (NNPC), Hannover, Germany.
Chicago author-date
Cazalets, Tanguy, and Joni Dambre. 2023. “New Insights on Homeostatic Activity-Dependent Structural Plasticity in Rate Based Neural Networks.” In 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings.
Chicago author-date (all authors)
Cazalets, Tanguy, and Joni Dambre. 2023. “New Insights on Homeostatic Activity-Dependent Structural Plasticity in Rate Based Neural Networks.” In 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings.
Vancouver
1.
Cazalets T, Dambre J. New insights on homeostatic activity-dependent structural plasticity in rate based neural networks. In: 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings. 2023.
IEEE
[1]
T. Cazalets and J. Dambre, “New insights on homeostatic activity-dependent structural plasticity in rate based neural networks,” in 2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings, Hannover, Germany, 2023.
@inproceedings{01JHFZ4J4ZP2ZKD83W4XZBFMTS,
  abstract     = {{We introduce a novel rate-based homeostatic activity-dependent structural plasticity
(HADSP) algorithm for echo state networks (ESNs). The algorithm employs solely homeostatic plasticity, yet enables the emergence of principles of Hebbian learning. Our analysis suggest that HADSP
is able to generate networks that effectively recombine redundant inputs to improve performances
and highlight the role of structural plasticity in influencing network function and organization.}},
  author       = {{Cazalets, Tanguy and Dambre, Joni}},
  booktitle    = {{2023 International Conference on Neuromorphic, Natural and Physical Computing, Proceedings}},
  language     = {{eng}},
  location     = {{Hannover, Germany}},
  pages        = {{2}},
  title        = {{New insights on homeostatic activity-dependent structural plasticity in rate based neural networks}},
  url          = {{https://nnpc-conference.com/wp-content/uploads/2024/04/program-nnpc.pdf}},
  year         = {{2023}},
}