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arXiv · 2509.23896

A Computational Perspective on NeuroAI and Synthetic Biological Intelligence

Dhruvik Patel·Md Sayed Tanveer·Jesus Gonzalez-Ferrer·Alon Loeffler·Brett J. Kagan·Mohammed A. Mostajo-Radji·Ge Wang
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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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Dhruvik Patel, Md Sayed Tanveer, Jesus Gonzalez-Ferrer, Alon Loeffler, Brett J. Kagan, Mohammed A. Mostajo-Radji, Ge Wang. 2025-09-28. A Computational Perspective on NeuroAI and Synthetic Biological Intelligence. https://arxiv.org/abs/2509.23896

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