Reliability entails input-selective contraction and regulation in excitable networks
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915804393504768 |
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| author | Bin, Michelangelo Cecconi, Alessandro Marconi, Lorenzo |
| author_facet | Bin, Michelangelo Cecconi, Alessandro Marconi, Lorenzo |
| contents | The animal nervous system offers a model of computation combining digital reliability and analog efficiency. Understanding how this sweet spot can be realized is a core question of neuromorphic engineering. To this aim, this paper explores the connection between reliability, contraction, and regulation in excitable systems. Using the FitzHugh-Nagumo model of excitable behavior as a proof-of-concept, it is shown that neuronal reliability can be formalized as an average trajectory contraction property induced by the input. In excitable networks, reliability is shown to enable regulation of the network to a robustly stable steady state. It is thus posited that regulation provides a notion of dynamical analog computation, and that stability makes such a computation model robust. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2511_02554 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Reliability entails input-selective contraction and regulation in excitable networks Bin, Michelangelo Cecconi, Alessandro Marconi, Lorenzo Systems and Control The animal nervous system offers a model of computation combining digital reliability and analog efficiency. Understanding how this sweet spot can be realized is a core question of neuromorphic engineering. To this aim, this paper explores the connection between reliability, contraction, and regulation in excitable systems. Using the FitzHugh-Nagumo model of excitable behavior as a proof-of-concept, it is shown that neuronal reliability can be formalized as an average trajectory contraction property induced by the input. In excitable networks, reliability is shown to enable regulation of the network to a robustly stable steady state. It is thus posited that regulation provides a notion of dynamical analog computation, and that stability makes such a computation model robust. |
| title | Reliability entails input-selective contraction and regulation in excitable networks |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2511.02554 |