Reward-optimizing learning using stochastic release plasticity
Synaptic plasticity underlies adaptive learning in neural systems, offering a biologically plausible framework for reward-driven learning. However, a question remains: how can plasticity rules achieve robustness and effectiveness comparable to error backpropagation? In this study, we introduce Rewar...
Saved in:
| Main Authors: | Yuhao Sun, Wantong Liao, Jinhao Li, Xinche Zhang, Guan Wang, Zhiyuan Ma, Sen Song |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-08-01
|
| Series: | Frontiers in Neural Circuits |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fncir.2025.1618506/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Biologically-informed excitatory and inhibitory ratio for robust spiking neural network training
by: Joseph A. Kilgore, et al.
Published: (2025-07-01) -
Research on SNN Learning Algorithms and Networks Based on Biological Plausibility
by: Bingqiang Huo, et al.
Published: (2025-01-01) -
Specific Neural Coding of Complex Neural Network Based on Time Coding Under Various Exterior Stimuli
by: Lei Guo, et al.
Published: (2025-03-01) -
A Bio-Inspired Learning Dendritic Motion Detection Framework with Direction-Selective Horizontal Cells
by: Tianqi Chen, et al.
Published: (2025-05-01) -
DS4NN: Direct training of deep spiking neural networks with single spike-based temporal coding
by: Maryam Mirsadeghi, et al.
Published: (2023-12-01)