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Behavioural simulation of biological neuron systems using VHDL and VHDL-AMS

Behavioural simulation of biological neuron systems using VHDL and VHDL-AMS
Behavioural simulation of biological neuron systems using VHDL and VHDL-AMS
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 system level VHDL and VHDL-AMS model of the C. Elegans locomotory system.
Bailey, Julian
7b855f30-6803-47cd-bc2e-920aaa96c1d4
Wilson, Peter R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Brown, Andrew D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Chad, John
2b52a3e0-a9e1-4988-996b-132e95ba38bd
Bailey, Julian
7b855f30-6803-47cd-bc2e-920aaa96c1d4
Wilson, Peter R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Brown, Andrew D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Chad, John
2b52a3e0-a9e1-4988-996b-132e95ba38bd

Bailey, Julian, Wilson, Peter R., Brown, Andrew D. and Chad, John (2007) Behavioural simulation of biological neuron systems using VHDL and VHDL-AMS At IEEE Behavioural Modeling and Simulation, United States. 20 - 21 Sep 2007.

Record type: Conference or Workshop Item (Other)

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, 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 system level VHDL and VHDL-AMS model of the C. Elegans locomotory system.

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Published date: 2007
Venue - Dates: IEEE Behavioural Modeling and Simulation, United States, 2007-09-20 - 2007-09-21
Organisations: EEE

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Local EPrints ID: 264910
URI: http://eprints.soton.ac.uk/id/eprint/264910
PURE UUID: 7e564154-240f-4d82-b55a-af273f6a52b6

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Date deposited: 14 Dec 2007 10:00
Last modified: 18 Jul 2017 07:31

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Contributors

Author: Julian Bailey
Author: Peter R. Wilson
Author: Andrew D. Brown
Author: John Chad

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