The mammalian nervous system is very efficient at processing, integratingand making sense of different sensory information from the outside world.When compared to the processing speed of modern computers the mammaliannervous system is very slow but is compensated for by the dense parallel nature ofthe brain. Understanding and harnessing the computational power of such systemshas long been the goal of computational neuroscientists. However, elucidating themost basic cognitive behaviour has been difficult due to the vast complexity of sucha system. Through understanding and emulating simpler nervous systems, such asthe C. elegans nematode, it is hoped that new insights into nervous system behaviourcan be achieved. The Si elegans EU FP7 project aims to develop a HardwareNeural Network (HNN) to accurately replicate the C. elegans nervous system whichhas been widely studied in recent years and there now exists a vast wealth ofknowledge about its nervous function and connectivity. To fully replicate the C.elegans nervous system requires powerful computing technologies, based on parallelprocessing, for real-time computation and therefore will use FieldProgrammable Gate Arrays (FPGAs) to achieve this. The project will also deliveran open-access framework via a Web Portal to neuroscientists, biologists, cliniciansand engineers and will enable a global network of scientists to gain a betterunderstanding of neural function. In this paper an overview of the completehardware system required to fully realise Si elegans is presented along with an earlysmall scale implementation of the hardware system.
|Name||Biosystems & Biorobotics|
|Publisher||Springer International Publishing|
- Si elegans
- Field programmable gate array (FPGA)
- Hardware neural network (HNN)
- C. elegans
- Wireless networks