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Behavioural Simulation and Synthesis of Biological Neuron Systems using VHDL

Behavioural Simulation and Synthesis of Biological Neuron Systems using VHDL
Behavioural Simulation and Synthesis of Biological Neuron Systems using VHDL
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.
978-1-4244-2896-0
Institute of Electrical and Electronics Engineers
Bailey, J.A.
8de4cc95-b53e-4f0e-84eb-25c43eff0ae1
Wilson, P.R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Brown, A.D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Chad, J.
d220e55e-3c13-4d1d-ae9a-1cfae8ccfbe1
Bailey, J.A.
8de4cc95-b53e-4f0e-84eb-25c43eff0ae1
Wilson, P.R.
8a65c092-c197-4f43-b8fc-e12977783cb3
Brown, A.D.
5c19e523-65ec-499b-9e7c-91522017d7e0
Chad, J.
d220e55e-3c13-4d1d-ae9a-1cfae8ccfbe1

Bailey, J.A., Wilson, P.R., Brown, A.D. and Chad, J. (2008) Behavioural Simulation and Synthesis of Biological Neuron Systems using VHDL In Proceedings of 2008 IEEE International Behavioral Modeling and Simulation Workshop. Institute of Electrical and Electronics Engineers. 6 pp.

Record type: Conference or Workshop Item (Paper)

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.

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More information

Published date: 2008
Venue - Dates: Behavioral Modeling and Simulation Workshop, 2008-09-25 - 2008-09-26
Organisations: Electronics & Computer Science, Centre for Biological Sciences

Identifiers

Local EPrints ID: 143339
URI: http://eprints.soton.ac.uk/id/eprint/143339
ISBN: 978-1-4244-2896-0
PURE UUID: 53cd1386-2fe6-42f2-b35e-bc03f2eee9bf
ORCID for J. Chad: ORCID iD orcid.org/0000-0001-6442-4281

Catalogue record

Date deposited: 08 Apr 2010 10:16
Last modified: 08 Nov 2017 13:35

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