生物学上可信的信息传播在互补金属氧化物半导体集成和发射人工神经元电路与忆阻突触

IF 2.5 4区 材料科学 Q3 MATERIALS SCIENCE, MULTIDISCIPLINARY
Lorenzo Benatti, T. Zanotti, D. Gandolfi, J. Mapelli, F. Puglisi
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引用次数: 0

摘要

基于尖峰的神经形态电路目前被设想为在特定电子实现中实现类脑计算能力的可行选择,同时由于其模拟节能生物激励机制的能力而限制了功耗。虽然已经开发了几种网络架构来将生物大脑中发现的生物启发学习规则嵌入到硬件中,例如峰值时间依赖的可塑性,但尚不清楚硬件峰值神经网络架构是否可以处理和传输类似于生物网络的信息。在这项工作中,我们从理论的角度研究了结合记忆电阻突触和基于速率的学习规则的人工神经元与生物神经元响应在信息传播方面的相似性。通过将释放的生物概率与人工突触传导联系起来,再现了生物启发实验。互信息和惊讶度被选择作为度量来证明,对于不同的突触权重值,人工神经元如何在信息传播和分析方面发展出可靠的和生物相似的神经网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Biologically plausible information propagation in a complementary metal-oxide semiconductor integrate-and-fire artificial neuron circuit with memristive synapses
Neuromorphic circuits based on spikes are currently envisioned as a viable option to achieve brain-like computation capabilities in specific electronic implementations while limiting power dissipation given their ability to mimic energy-efficient bioinspired mechanisms. While several network architectures have been developed to embed in hardware the bioinspired learning rules found in the biological brain, such as spike timing-dependent plasticity, it is still unclear if hardware spiking neural network architectures can handle and transfer information akin to biological networks. In this work, we investigate the analogies between an artificial neuron combining memristor synapses and rate-based learning rule with biological neuron response in terms of information propagation from a theoretical perspective. Bioinspired experiments have been reproduced by linking the biological probability of release with the artificial synapse conductance. Mutual information and surprise have been chosen as metrics to evidence how, for different values of synaptic weights, an artificial neuron allows to develop a reliable and biological resembling neural network in terms of information propagation and analysis.
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来源期刊
Nano Futures
Nano Futures Chemistry-General Chemistry
CiteScore
4.30
自引率
0.00%
发文量
35
期刊介绍: Nano Futures mission is to reflect the diverse and multidisciplinary field of nanoscience and nanotechnology that now brings together researchers from across physics, chemistry, biomedicine, materials science, engineering and industry.
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