一个由尖峰神经元组成的超大规模集成电路网络,具有可塑的、完全可配置的“停止学习”突触

M. Giulioni, Patrick Camilleri, V. Dante, D. Badoni, G. Indiveri, J. Braun, P. D. Giudice
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引用次数: 31

摘要

我们描述并展示了一种神经形态的模拟VLSI芯片(称为F-LANN),该芯片承载了128个具有尖波频率适应性的集成与放电(IF)神经元,以及16,384个可塑双稳态突触,实现了自我调节形式的Hebbian,尖波驱动的随机可塑性。芯片被设计为提供高度的可重构性:每个突触可以在任何时候单独配置为兴奋性或抑制性,并接收来自芯片上神经元的周期性输入或来自芯片外神经元的基于aer的输入。每个突触的初始状态可以设置为增强或抑制,每个突触的状态可以读取并存储在计算机上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A VLSI network of spiking neurons with plastic fully configurable “stop-learning” synapses
We describe and demonstrate a neuromorphic, analog VLSI chip (termed F-LANN) hosting 128 integrate-and-fire (IF) neurons with spike-frequency adaptation, and 16,384 plastic bistable synapses implementing a self-regulated form of Hebbian, spike-driven, stochastic plasticity. The chip is designed to offer a high degree of reconfigurability: each synapse may be individually configured at any time to be either excitatory or inhibitory and to receive either recurrent input from an on-chip neuron or AER-based input from an off-chip neuron. The initial state of each synapse can be set as potentiated or depressed, and the state of each synapse can be read and stored on a computer.
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