Hardware computation of conductance-based neuron models

被引:0
|
作者
Alvado, L [1 ]
Tomas, J [1 ]
Saighi, S [1 ]
Renaud, S [1 ]
Bal, T [1 ]
Destexhe, A [1 ]
Le Masson, G [1 ]
机构
[1] Univ Bordeaux 1, Lab 1XL, CNRS, UMR 5818,ENSEIRB, F-33405 Talence, France
关键词
silicon neurons; conductance-based models; simulation tool; plasticity rules;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 progammed 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. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:109 / 115
页数:7
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