Homeostatic synaptic normalization optimizes learning in network models of neural population codes
Studying and understanding the code of large neural populations hinge on accurate statistical models of population activity. A novel class of models, based on learning to weigh sparse nonlinear Random Projections (RP) of the population, has demonstrated high accuracy, efficiency, and scalability. Im...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2024-12-01
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| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/96566 |
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