Si elegans: Modeling the C. elegans Nematode Nervous System Using High Performance FPGAS

Abstract

The mammalian nervous system is very efficient at processing, integrating and making sense of different sensory information from the outside world. When compared to the processing speed of modern computers the mammalian nervous system is very slow but is compensated for by the dense parallel nature of the brain. Understanding and harnessing the computational power of such systems has long been the goal of computational neuroscientists. However, elucidating the most basic cognitive behaviour has been difficult due to the vast complexity of such a system. Through understanding and emulating simpler nervous systems, such as the C. elegans nematode, it is hoped that new insights into nervous system behaviour can be achieved. The Si elegans EU FP7 project aims to develop a Hardware Neural Network (HNN) to accurately replicate the C. elegans nervous system which has been widely studied in recent years and there now exists a vast wealth of knowledge about its nervous function and connectivity. To fully replicate the C. elegans nervous system requires powerful computing technologies, based on parallel processing, for real-time computation and therefore will use Field Programmable Gate Arrays (FPGAs) to achieve this. The project will also deliver an open-access framework via a Web Portal to neuroscientists, biologists, clinicians and engineers and will enable a global network of scientists to gain a better understanding of neural function. In this paper an overview of the complete hardware system required to fully realise Si elegans is presented along with an early small scale implementation of the hardware system.