Ignatov Marina, Ziegler Martin, Hansen Mirko, Petraru Adrian, Kohlstedt Hermann
Nanoelektronik, Technische Fakultät, Christian-Albrechts-Universität zu Kiel Kiel, Germany.
Front Neurosci. 2015 Oct 20;9:376. doi: 10.3389/fnins.2015.00376. eCollection 2015.
Perception, decisions, and sensations are all encoded into trains of action potentials in the brain. The relation between stimulus strength and all-or-nothing spiking of neurons is widely believed to be the basis of this coding. This initiated the development of spiking neuron models; one of today's most powerful conceptual tool for the analysis and emulation of neural dynamics. The success of electronic circuit models and their physical realization within silicon field-effect transistor circuits lead to elegant technical approaches. Recently, the spectrum of electronic devices for neural computing has been extended by memristive devices, mainly used to emulate static synaptic functionality. Their capabilities for emulations of neural activity were recently demonstrated using a memristive neuristor circuit, while a memristive neuron circuit has so far been elusive. Here, a spiking neuron model is experimentally realized in a compact circuit comprising memristive and memcapacitive devices based on the strongly correlated electron material vanadium dioxide (VO2) and on the chemical electromigration cell Ag/TiO2-x /Al. The circuit can emulate dynamical spiking patterns in response to an external stimulus including adaptation, which is at the heart of firing rate coding as first observed by E.D. Adrian in 1926.
感知、决策和感觉都在大脑中被编码为一系列动作电位。人们普遍认为，刺激强度与神经元的全或无尖峰发放之间的关系是这种编码的基础。这引发了尖峰神经元模型的发展；尖峰神经元模型是当今用于分析和模拟神经动力学的最强大的概念工具之一。电子电路模型的成功及其在硅场效应晶体管电路中的物理实现带来了精妙的技术方法。最近，忆阻器件扩展了用于神经计算的电子设备范围，忆阻器件主要用于模拟静态突触功能。最近，利用忆阻神经晶体管电路展示了它们模拟神经活动的能力，而到目前为止，忆阻神经元电路一直难以实现。在此，基于强关联电子材料二氧化钒（VO₂）和化学电迁移电池Ag/TiO₂₋ₓ/Al，在一个包含忆阻和忆容器件的紧凑电路中通过实验实现了一个尖峰神经元模型。该电路能够响应外部刺激，包括适应，模拟动态尖峰模式，适应是1926年E.D. 阿德里安首次观察到的发放率编码的核心。
