Synthetic Biology meets Neuromorphic Computing: Towards a bio-inspired Olfactory Perception System
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866909714926796800 |
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| author | Max, Kevin Sames, Larissa Ye, Shimeng Steinkühler, Jan Corradi, Federico |
| author_facet | Max, Kevin Sames, Larissa Ye, Shimeng Steinkühler, Jan Corradi, Federico |
| contents | In this study, we explore how the combination of synthetic biology, neuroscience modeling, and neuromorphic electronic systems offers a new approach to creating an artificial system that mimics the natural sense of smell. We argue that a co-design approach offers significant advantages in replicating the complex dynamics of odor sensing and processing. We propose a hybrid system of synthetic sensory neurons that provides three key features: (a) receptor-gated ion channels, (b) interface between synthetic biology and semiconductors and (c) event-based encoding and computing based on spiking networks. Our approach is validated using simulation-based modeling of the complete sensing and processing pipeline. This research seeks to develop a platform for ultra-sensitive, specific, and energy-efficient odor detection, with potential implications for environmental monitoring, medical diagnostics, and security. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_10053 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Synthetic Biology meets Neuromorphic Computing: Towards a bio-inspired Olfactory Perception System Max, Kevin Sames, Larissa Ye, Shimeng Steinkühler, Jan Corradi, Federico Neural and Evolutionary Computing Emerging Technologies Neurons and Cognition In this study, we explore how the combination of synthetic biology, neuroscience modeling, and neuromorphic electronic systems offers a new approach to creating an artificial system that mimics the natural sense of smell. We argue that a co-design approach offers significant advantages in replicating the complex dynamics of odor sensing and processing. We propose a hybrid system of synthetic sensory neurons that provides three key features: (a) receptor-gated ion channels, (b) interface between synthetic biology and semiconductors and (c) event-based encoding and computing based on spiking networks. Our approach is validated using simulation-based modeling of the complete sensing and processing pipeline. This research seeks to develop a platform for ultra-sensitive, specific, and energy-efficient odor detection, with potential implications for environmental monitoring, medical diagnostics, and security. |
| title | Synthetic Biology meets Neuromorphic Computing: Towards a bio-inspired Olfactory Perception System |
| topic | Neural and Evolutionary Computing Emerging Technologies Neurons and Cognition |
| url | https://arxiv.org/abs/2504.10053 |