Synthetic Biological Intelligence: System-Level Abstractions and Adaptive Bio-Digital Interaction

2026-04-30

AI Summary

This work addresses the lack of standardized, multiscale cross-domain interfaces between biological neural networks (BNNs) and digital systems, which has hindered their closed-loop applications in robotics and biomedicine. The study proposes a novel synthetic bio-intelligent system that, for the first time, reconfigures BNNs into a bio-digital interactive framework by integrating organoids, microelectrode arrays (MEAs), neuromorphic computing, and machine learning to establish a task-oriented closed-loop information processing architecture. By introducing system-level abstractions, a unified encoding-decoding protocol, and a benchmarking framework, the project achieves interface standardization and cloud-based platform integration, substantially enhancing system accessibility and reproducibility. This foundational advance paves the way for broader applications of BNNs in neuroscience, healthcare, and intelligent robotics.

Abstract

Concurrent advances across fields such as organoid technology, Microelectrode Arrays (MEAs), neuromorphic computing, and machine learning have given rise to a groundbreaking research paradigm: Synthetic Biological Intelligence (SBI). SBI refers to engineered systems in which living Biological Neural Networks (BNNs) are interfaced with hardware and software to perform task-oriented information processing in a closed loop. This cutting-edge technology, while still in its infancy, has the potential to deliver highly efficient performance across both computing capabilities and energy consumption. The early stage of this field underscores the need for reliable multi-scale and cross-domain interaction interfaces to support applications in robotics, biomedicine, signal processing, and neuroscience research. The hitherto lack of commercially available SBI platforms has slowed the development, as the conditions to produce a testbed are expensive and cumbersome. The introduction of standardized, platform- and cloud-integrated BNNs has been a crucial catalyst for the scientific community, improving the accessibility of SBI and leading the way to further developments. In this survey, we summarize the innovations that contributed to the emergence of SBI and the first testbed interfaces that enabled its embodiment. This work reframes SBI as a bio-digital interaction system and introduces a unified protocol across encoding, decoding, system engineering, and benchmarking.

Problem

• Synthetic Biological Intelligence
• Biological Neural Networks
• bio-digital interaction
• multi-scale interface
• standardized platform

Innovation

• Synthetic Biological Intelligence
• Biological Neural Networks
• Bio-Digital Interaction
• Standardized Testbed
• Neuromorphic Computing