The investigation of neuron structures is an incredibly difficult and complex task that yields relatively low rewards in terms of information from biological forms (either animals or tissue). The structures and connectivity of even the simplest invertebrates are almost impossible to establish with standard laboratory techniques, and even when this is possible it is generally time consuming, complex and expensive. Recent work has shown how a simplified behavioural approach to modelling neurons can allow ?virtual? experiments to be carried out that map the behaviour of a simulated structure onto a hypothetical biological one, with correlation of behaviour rather than underlying connectivity. The problems with such approaches are numerous. The first is the difficulty of simulating realistic aggregates efficiently, the second is making sense of the results and finally, it would be helpful to have an implementation that could be synthesised to hardware for acceleration. In this paper we present a VHDL implementation of Neuron models that allow large aggregates to be simulated. The models are demonstrated using a synthesizable system level VHDL model of the C. Elegans locomotory system.
|Title of host publication||IEEE International Behavioral Modeling and Simulation Workshop (BMAS), 2008|
|Publication status||Published - 1 Sep 2008|
|Event||IEEE International Behavioral Modeling and Simulation Workshop (BMAS), 2008 - San Jose, USA United States|
Duration: 25 Sep 2008 → 26 Sep 2008
|Workshop||IEEE International Behavioral Modeling and Simulation Workshop (BMAS), 2008|
|Country||USA United States|
|Period||25/09/08 → 26/09/08|