A Computational Perspective on NeuroAI and Synthetic Biological Intelligence
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908584889024512 |
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| author | Patel, Dhruvik Tanveer, Md Sayed Gonzalez-Ferrer, Jesus Loeffler, Alon Kagan, Brett J. Mostajo-Radji, Mohammed A. Wang, Ge |
| author_facet | Patel, Dhruvik Tanveer, Md Sayed Gonzalez-Ferrer, Jesus Loeffler, Alon Kagan, Brett J. Mostajo-Radji, Mohammed A. Wang, Ge |
| contents | NeuroAI is an emerging field at the intersection of neuroscience and artificial intelligence, where insights from brain function guide the design of intelligent systems. A central area within this field is synthetic biological intelligence (SBI), which combines the adaptive learning properties of biological neural networks with engineered hardware and software. SBI systems provide a platform for modeling neural computation, developing biohybrid architectures, and enabling new forms of embodied intelligence. In this review, we organize the NeuroAI landscape into three interacting domains: hardware, software, and wetware. We outline computational frameworks that integrate biological and non-biological systems and highlight recent advances in organoid intelligence, neuromorphic computing, and neuro-symbolic learning. These developments collectively point toward a new class of systems that compute through interactions between living neural tissue and digital algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_23896 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Computational Perspective on NeuroAI and Synthetic Biological Intelligence Patel, Dhruvik Tanveer, Md Sayed Gonzalez-Ferrer, Jesus Loeffler, Alon Kagan, Brett J. Mostajo-Radji, Mohammed A. Wang, Ge Neurons and Cognition Emerging Technologies Neural and Evolutionary Computing NeuroAI is an emerging field at the intersection of neuroscience and artificial intelligence, where insights from brain function guide the design of intelligent systems. A central area within this field is synthetic biological intelligence (SBI), which combines the adaptive learning properties of biological neural networks with engineered hardware and software. SBI systems provide a platform for modeling neural computation, developing biohybrid architectures, and enabling new forms of embodied intelligence. In this review, we organize the NeuroAI landscape into three interacting domains: hardware, software, and wetware. We outline computational frameworks that integrate biological and non-biological systems and highlight recent advances in organoid intelligence, neuromorphic computing, and neuro-symbolic learning. These developments collectively point toward a new class of systems that compute through interactions between living neural tissue and digital algorithms. |
| title | A Computational Perspective on NeuroAI and Synthetic Biological Intelligence |
| topic | Neurons and Cognition Emerging Technologies Neural and Evolutionary Computing |
| url | https://arxiv.org/abs/2509.23896 |