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具有生物匹配动力学的多电导硅神经元。

A multiconductance silicon neuron with biologically matched dynamics.

作者信息

Simoni Mario F, Cymbalyuk Gennady S, Sorensen Michael E, Calabrese Ronald L, DeWeerth Stephen P

机构信息

School of Electrical and Computer Engineering, Laboratory for Neuroengineering, Georgia Institute of Technology, Atlanta, GA 30332, USA.

出版信息

IEEE Trans Biomed Eng. 2004 Feb;51(2):342-54. doi: 10.1109/TBME.2003.820390.

Abstract

We have designed, fabricated, and tested an analog integrated-circuit architecture to implement the conductance-based dynamics that model the electrical activity of neurons. The dynamics of this architecture are in accordance with the Hodgkin-Huxley formalism, a widely exploited, biophysically plausible model of the dynamics of living neurons. Furthermore the architecture is modular and compact in size so that we can implement networks of silicon neurons, each of desired complexity, on a single integrated circuit. We present in this paper a six-conductance silicon-neuron implementation, and characterize it in relation to the Hodgkin-Huxley formalism. This silicon neuron incorporates both fast and slow ionic conductances, which are required to model complex oscillatory behaviors (spiking, bursting, subthreshold oscillations).

摘要

我们设计、制造并测试了一种模拟集成电路架构,以实现基于电导的动力学,该动力学可模拟神经元的电活动。此架构的动力学符合霍奇金-赫胥黎形式体系,这是一种广泛应用的、在生物物理学上合理的活神经元动力学模型。此外,该架构模块化且尺寸紧凑,因此我们能够在单个集成电路上实现具有所需复杂度的硅神经元网络。在本文中,我们展示了一种六电导硅神经元实现方式,并根据霍奇金-赫胥黎形式体系对其进行了表征。这种硅神经元包含快速和慢速离子电导,这对于模拟复杂的振荡行为(尖峰放电、爆发式放电、阈下振荡)是必需的。

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