Biological neural systems are powerful, robust and highly adaptive computational entities that outperform conventional computers in almost all aspects of sensory-motor integration. Despite dramatic progress in information technology, there is a big performance discrepancy between artificial computational systems and brains in seemingly simple orientation and navigation tasks. In fact, no system exists that can faithfully reproduce the rich behavioural repertoire of the tiny worm Caenorhabditis elegans which features one of the simplest nervous systems in nature made of 302 neurons and about 8000 connections.
The Si elegans project aims at providing this missing link. We propose the development of a hardware-based computing framework that accurately mimics C. elegans in real time and enables complex and realistic behaviour to emerge through interaction with a rich, dynamic simulation of a natural or laboratory environment. We will replicate the nervous system of C. elegans on a highly parallel, modular, user-programmable, reconfigurable and scalable hardware architecture, virtually embody it for behavioural studies in a realistic virtual environment and provide the resulting computational platform through an open-access web portal to the scientific community for its peer-validation and use.
Several innovative key concepts will ensure the accurate mimicry of the C. elegans nervous system architecture and function. Each of the 302 neurons will be represented by individual field-programmable gate array (FPGA) modules, each of them being independently and dynamically programmable with a user-specific and parameterised neuronal response model through a user-friendly neuron model submission and configuration facility or through selection from a library of pre-defined and tested neuron models. Pioneering interconnection schemes will allow dense module distribution and parallel, interference-free inter-neuron communication in a 3D space. In a closed-loop feedback design, this hardware blueprint of the C. elegans nervous system will control a biophysically correct virtual representation of the nematode body in a virtual behavioural setting. Instead of limiting its function and S&T impact by imposing pre-made models only, the Si elegans framework will be made available to the worldwide scientific community through an open-access web-portal. It will feature an intuitive and user-friendly remote configuration interface to define an unlimited number of neuron models and information processing hypotheses for automatic FPGA hardware configuration. This peer-participation concept will not only warrant the independent and unbiased functional validation of Si elegans, but permit the iterative optimization of neuron models and the asymptotical approach towards a holistic reproduction and understanding of the complete set of C. elegans behaviours and their underlying nervous system mechanisms through a set of reverse-engineering tools.
While Si elegans restricts itself to the emulation of the C. elegans nervous system, the underlying design concepts have universal application. Si elegans will constitute a generalizable framework from which the universal working principles of nervous system function can be induced, and new scientific knowledge on higher brain function and behaviour can be generated. More importantly, it will lay the foundation for exploring and refining new neuromimetic computational concepts and will provide a blueprint for the design of biologically inspired, brain-like parallel processing hardware architectures that are orthogonal to current von Neumann-type machines.