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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.11374 |
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| _version_ | 1866915244116279296 |
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| author | Huo, Yongkang Forni, Fuvio Sepulchre, Rodolphe |
| author_facet | Huo, Yongkang Forni, Fuvio Sepulchre, Rodolphe |
| contents | We present a novel framework for central pattern generator design that leverages the intrinsic rebound excitability of neurons in combination with winner-takes-all computation. Our approach unifies decision-making and rhythmic pattern generation within a simple yet powerful network architecture that employs all-to-all inhibitory connections enhanced by designable excitatory interactions. This design offers significant advantages regarding ease of implementation, adaptability, and robustness. We demonstrate its efficacy through a ring oscillator model, which exhibits adaptive phase and frequency modulation, making the framework particularly promising for applications in neuromorphic systems and robotics. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_11374 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Winner-Takes-All Mechanism for Event Generation Huo, Yongkang Forni, Fuvio Sepulchre, Rodolphe Systems and Control Artificial Intelligence We present a novel framework for central pattern generator design that leverages the intrinsic rebound excitability of neurons in combination with winner-takes-all computation. Our approach unifies decision-making and rhythmic pattern generation within a simple yet powerful network architecture that employs all-to-all inhibitory connections enhanced by designable excitatory interactions. This design offers significant advantages regarding ease of implementation, adaptability, and robustness. We demonstrate its efficacy through a ring oscillator model, which exhibits adaptive phase and frequency modulation, making the framework particularly promising for applications in neuromorphic systems and robotics. |
| title | A Winner-Takes-All Mechanism for Event Generation |
| topic | Systems and Control Artificial Intelligence |
| url | https://arxiv.org/abs/2504.11374 |