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

TL;DR

This paper surveys the emerging field of Synthetic Biological Intelligence (SBI), focusing on system-level abstractions, interaction interfaces, and the development of standardized testbeds for bio-digital systems.

Contribution

It introduces a unified protocol for SBI encompassing encoding, decoding, system engineering, and benchmarking, advancing the standardization and accessibility of SBI platforms.

Findings

Summarizes innovations leading to SBI emergence

Describes first testbed interfaces for SBI

Proposes a unified protocol for SBI systems

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.