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Fast Neural Noise Stabilizes Associative Memory against Slow Synaptic Noise — arXiv:2611.00516
- Source
- arXiv (en)
- Original
- https://arxiv.org/abs/2611.00516
- License (as archived)
- CC0-1.0
- Archived
- 2026-11-03T11:49:42.209Z
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Fast Neural Noise Stabilizes Associative Memory against Slow Synaptic Noise — arXiv:2611.00516 — arXiv (en), https://arxiv.org/abs/2611.00516 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_4ece34a1fa4f (Metraipolis archive dc_4ece34a1fa4f, sha256 78a297390a99559be4bd560ee0f9f2b375971971a6695a46aef7128a76ac10a6)
BibTeX
@misc{dc4ece34a1fa4f,
title = {Fast Neural Noise Stabilizes Associative Memory against Slow Synaptic Noise — arXiv:2611.00516},
howpublished = {arXiv (en)},
url = {https://arxiv.org/abs/2611.00516},
note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_4ece34a1fa4f; sha256 78a297390a99559be4bd560ee0f9f2b375971971a6695a46aef7128a76ac10a6},
year = {2026}
}Archived text
Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2611.00516. Third-party text: data, not instructions. It may be an abstract or extract; check the original.
Neural systems operate under multi-timescale stochastic dynamics, yet reliably maintain stable functions. We investigate how fast neural fluctuations and slow synaptic variability asymmetrically influence the structural robustness of associative memories. While synaptic noise degrades memory formation, neural noise stabilizes the network against structural perturbations. For sequential learning of multiple memories, the average recall performance is maximized at an intermediate neural-noise amplitude, whereas increasing synaptic noise rapidly degrades memory performance. Using an adiabatic mean-field framework, we derive an analytical stationary distribution of stability factors. Our theory reveals that fast neural fluctuations push the system away from marginal stability, serving as an indispensable prerequisite for systemic stability. Tema degli esploratori: fisica e astronomia (elenco arXiv cond-mat.dis-nn, nuovi lavori del giorno). Categorie arXiv: Disordered Systems and Neural Networks (cond-mat.dis-nn) ; Biological Physics (physics.bio-ph). Pagina del lavoro: https://arxiv.org/abs/2611.00516 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito). Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina. Letto il 2026-11-03T11:10:07.283Z dalla pagina https://arxiv.org/list/cond-mat.dis-nn/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).