A UDP Packet Format Establishing Adress Event Representation Communication Between Remote Neuromorphic and Biological Setups

Abstract: In the field of brain-machine interfaces, biohybrids offer an interesting new perspective, as in them, the technological side acts like a closed-loop extension or real counterpart of biological tissue, instead of the usual open loop approaches in tranditional BMI. To achieve a credible counterpart to biological tissue, biohybrids usually employ one or several neuromorphic components as the hardware half of the biohybrid. However, advanced neuromorphic circuit such as memristor crossbars usually operate best in a dedicated lab with corresponding support equipment. The same is true for biological tissue, which makes co-locating all of the parts of a biohybrid in the same lab challenging. Here, we present as solution to this co-location issue a simple method to connect biohybrids via the internet by a custom UDP packet format. We show that the characteristics achieved with our solution (jitter, delay, packet loss, packet reordering) on a standard internet connection are compatible with various biohybrid processing paradigms, and we present a short three-ways experiment as proof-of-concept. The described UDP format has been employed to link biohybrids and neuromorphic circuits in four different EC-funded projects.

• The paper introduces a UDP packet format that efficiently translates AER spike events into 58-byte packets for remote biohybrid communication.
• It employs low-latency UDP protocols to achieve reliable real-time interfacing between neuromorphic circuits and biological tissues.
• The approach reduces physical co-location challenges, enabling cost-effective and scalable brain-machine interface research across distributed setups.

Overview of A UDP Packet Format for AER Communication in Remote Biohybrids

The paper "A UDP Packet Format Establishing Address Event Representation Communication Between Remote Neuromorphic and Biological Setups" explores a novel approach to integrating distributed components of biohybrids via the internet. Authored by CG Mayr, RM George, M Tambaro, and G Indiveri, the study is noteworthy for its contributions to the field of brain-machine interfaces (BMI), particularly in utilizing a User Datagram Protocol (UDP) format to facilitate communication between remote neuromorphic and biological setups.

Biohybrids are characterized by the integration of neurobiological and technological components. This closed-loop integration allows biohybrids to function as extended systems, blurring the boundaries between biological and technological entities. The paper addresses the complexities of co-locating various biohybrid components, such as memristors, neuromorphic circuits, and biological tissues, which are often best supported in specialized laboratories. The authors propose a novel communication protocol to connect these components via standard internet connections, resolving co-location challenges through remote interfacing.

Technical Aspects

The UDP packet format proposed is designed around the Address Event Representation (AER) protocol, commonly used in neuromorphic systems to transmit spike data asynchronously. The advantages of using UDP over other networking protocols include lower latency and reduced payload overhead, which are critical for maintaining the real-time dynamics necessary for effective biohybrid operation. The design allows for translation of AER events into UDP packets, enabling efficient routing across the internet.

The paper outlines a protocol structure that includes a 58-byte UDP packet format composed of routing information, timestamps, custom payloads, and spike source IDs. This format facilitates the transmission of events between diverse setups, including memristive devices and neuromorphic circuits, as demonstrated in the EU-funded projects.

The study details the implementation of this protocol in a distributed biohybrid setup, linking setups in different European labs using a central control unit located in Dresden. It validates the UDP-based communication through experiments that demonstrate acceptable jitter, delay, and packet loss—parameters essential for the processing demands of biohybrid interfaces.

Implications and Future Directions

The implications of this research extend across both theoretical and practical domains in neuromorphic engineering. Theoretically, it reinforces the feasibility of distributed biohybrid systems operating across geographic locations without significant degradation in real-time capabilities. The research provides insight into how complex neuromorphic and biological systems can be intricately linked, blurring the lines between biological and computational entities.

The practical implications are substantial. The use of existing internet infrastructure reduces the need for physical transport and co-location, significantly lowering costs and logistical constraints associated with biohybrid research. This approach also mitigates risks by enabling remote development and testing of biohybrid systems, which is particularly advantageous in pandemic-prone environments or regions with significant travel restrictions.

In terms of future directions, the scalability of the UDP protocol for additional biohybrid applications, such as in vivo neuroprosthetics or internet-connected neurobiological networks, opens a range of possibilities for advancing the field of distributed neuromorphic systems. Moreover, the research can contribute to the development of more sophisticated biohybrids capable of executing complex computational tasks through enhanced real-time interaction between biological and neuromorphic components.

Conclusion

The paper successfully introduces a UDP packet format tailored for remote biohybrid communication. Through its detailed methodology and experimental validation, the research lays a solid foundation for future exploration and application of distributed biohybrids. It is a significant step towards realizing the full potential of brain-machine interfaces by advancing the integration of remote biohybrid components, thereby pushing the boundaries of what is achievable in neuromorphic and biohybrid systems.