Si elegans · Emulating the C. elegans nervous system: A blueprint for brain-inspired computational architectures

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 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. Si elegans aims at providing this missing link. We propose to develop a computing framework that accurately mimics C. elegans and let complex and realistic behaviour emerge through its interaction with a rich, dynamic simulation of a natural environment. We will replicate the nervous system of C. elegans on a highly parallel, modular, arbitrarily 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. 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 brain-like hardware architectures that are orthogonal to current von Neumann-type machines. The 3-year project brings together a highly interdisciplinary, experienced and focused research team from leading European institutions with well-balanced complementary skills and will reach out to the world-wide scientific community in a peer-contribution and validation approach.