Global scaling of synaptic efficacy: Homeostasis in silicon synapses

被引：23

作者：

Bartolozzi, Chiara ^{[1
]}

Indiveri, Giacomo ^{[1
,2
]}

机构：

[1] IIT, Ist Italiono Tecnol, I-16163 Genoa, Italy

[2] UNI ETH Zurich, Inst Neuroinformat, CH-8057 Zurich, Switzerland

来源：

NEUROCOMPUTING | 2009年 / 72卷 / 4-6期

关键词：

aVLSI; Neuromorphic; Synapse; Homeostasis; Spike-based learning; Synaptic scaling; PLASTICITY; NEURONS;

D O I：

10.1016/j.neucom.2008.05.016

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Synaptic homeostasis is a mechanism present in biological neural systems that acts to maintain an homogeneous and stable computational substrate, in face of intrinsic inhomogeneities among neurons, and of their continuous changes due to learning processes and variations in the statistics of the input signals. In hardware spike-based neural networks homeostasis could be useful for solving issues such as mismatch and temperature drifts. Here we present a synaptic circuit that supports both spike-based learning and homeostatic mechanisms, and show how it can be used in conjunction with a software control algorithm to model global synaptic scaling homeostatic mechanism. (C) 2008 Elsevier B.V. All rights reserved.

引用

收藏

页码：726 / 731

页数：6

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