Recreating neural oscillators in VLSI

S. Wolpert
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引用次数: 2

Abstract

As a prelude to a VLSI implementation of a biologically-based neuronal locomotor network, the phenomena of reciprocal inhibition and recurrent cyclic inhibition were recreated in VLSI-based artificial neurons for parametric analysis of oscillatory range and stability. The artificial neurons used in this study are behaviorally comprehensive and highly configurable, allowing for a variety of transient and steady characteristics to be precisely and continuously adjustable. Circuit tests on both oscillatory phenomena indicate that reciprocal inhibition between two neurons requires a measure of synaptic dynamics, while the recurrent cyclic inhibitory prototypes did not. In addition, the cyclic prototypes demonstrated remarkable stability, even when the frequency of self-excitation of each component neuron varied over two orders of magnitude.<>
在VLSI中重建神经振荡器
作为一个基于生物的神经元运动网络的VLSI实现的前导,在基于VLSI的人工神经元中重建了相互抑制和循环抑制现象,用于振荡范围和稳定性的参数分析。本研究中使用的人工神经元具有行为综合性和高度可配置性,允许各种瞬态和稳定特性精确连续调节。对这两种振荡现象的电路测试表明,两个神经元之间的相互抑制需要突触动力学的测量,而循环抑制原型则不需要。此外,即使每个组成神经元的自激频率变化超过两个数量级,循环原型也表现出显著的稳定性。
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