Hardware computation of conductance-based neuron models.

Abstract : We review different applications of silicon conductance-based neuron models implemented on analog circuits. At the single-cell level, we describe a circuit in which conductances are programmed to simulate various Hodgkin-Huxley type models; integrated in a hardware/software system, they provide a simulation tool; an illustrative example is the simulation of bursting neurons of the thalamus. At the network level, we present a mixed analog-digital architecture, where the connectivity and the plasticity rules are implemented digitally and are therefore very flexible. These circuits provide valuable tools for real-time simulations, including hybrid applications where single-neuron or network models are interfaced with biological cells.
Type de document :
Article dans une revue
Neurocomputing, Elsevier, 2004, 58-60, pp.109. 〈10.1016/j.neucom.2004.01.030〉
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Contributeur : Alain Perignon <>
Soumis le : jeudi 9 février 2006 - 13:38:05
Dernière modification le : jeudi 11 janvier 2018 - 06:19:38



L. Alvado, Jean Tomas, Sylvain Saighi, Sylvie Renaud, Thierry Bal, et al.. Hardware computation of conductance-based neuron models.. Neurocomputing, Elsevier, 2004, 58-60, pp.109. 〈10.1016/j.neucom.2004.01.030〉. 〈hal-00018608〉



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