Behavioural Simulation and Synthesis of Biological Neuron Systems using VHDL
ABSTRACT 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, the models often take days to run therefore it would be advantageous to have a model which can be synthesized onto hardware. In this paper we present a synthesizable VHDL implementation of Neuron models that allow large aggregates to be simulated. The models are demonstrated using a post synthesis system level VHDL model of the C. Elegans locomotory system.
- SourceAvailable from: ncbi.nlm.nih.govThe Journal of Physiology 09/1952; 117(4):500-44. · 4.38 Impact Factor
- Comprehensive Physiology, 12/2010; , ISBN: 9780470650714
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ABSTRACT: Mathematical expressions are obtained for the response function corresponding to an instantaneous pulse of current injected to a single dendritic branch in a branched dendritic neuron model. The theoretical model assumes passive membrane properties and the equivalent cylinder constraint on branch diameters. The response function when used in a convolution formula enables one to compute the voltage transient at any specified point in the dendritic tree for an arbitrary current injection at a given input location. A particular numerical example, for a brief current injection at a branch terminal, illustrates the attenuation and delay characteristics of the depolarization peak as it spreads throughout the neuron model. In contrast to the severe attenuation of voltage transients from branch input sites to the soma, the fraction of total input charge actually delivered to the soma and other trees is calculated to be about one-half. This fraction is independent of the input time course. Other numerical examples, which compare a branch terminal input site with a soma input site, demonstrate that, for a given transient current injection, the peak depolarization is not proportional to the input resistance at the injection site and, for a given synaptic conductance transient, the effective synaptic driving potential can be significantly reduced, resulting in less synaptic current flow and charge, for a branch input site. Also, for the synaptic case, the two inputs are compared on the basis of the excitatory post-synaptic potential (EPSP) seen at the soma and the total charge delivered to the soma.Biophysical Journal 11/1974; 14(10):759-90. · 3.67 Impact Factor