A Computational Perspective on NeuroAI and Synthetic Biological Intelligence

• URL: http://arxiv.org/abs/2509.23896v2
• Date: Thu, 09 Oct 2025 14:19:11 GMT
• Title: A Computational Perspective on NeuroAI and Synthetic Biological Intelligence
• Authors: Dhruvik Patel, Md Sayed Tanveer, Jesus Gonzalez-Ferrer, Alon Loeffler, Brett J. Kagan, Mohammed A. Mostajo-Radji, Ge Wang,
• Abstract summary: We organize the NeuroAI landscape into three interacting domains: hardware, software, and wetware.<n>We highlight advances in organoid intelligence, neuromorphic computing, and neuro-symbolic learning.<n>These developments collectively point toward a new class of systems that compute through interactions between living neural tissue and digital algorithms.
• Score: 4.364299170850049
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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