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Memristive stochastic plasticity enables mimicking of neural synchrony: Memristive circuit emulates an optical illusion

机译:忆阻随机可塑性可模仿神经同步性:忆阻电路可模拟光学错觉

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摘要

The human brain is able to integrate a myriad of information in an enormous and massively parallel network of neurons that are divided into functionally specialized regions such as the visual cortex, auditory cortex, or dorsolateral prefrontal cortex. Each of these regions participates as a context-dependent, self-organized, and transient subnetwork, which is shifted by changes in attention every 0.5 to 2 s. This leads to one of the most puzzling issues in cognitive neuroscience, well known as the “binding problem.” The concept of neural synchronization tries to explain the problem by encoding information using coherent states, which temporally patterns neural activity. We show that memristive devices, that is, a two-terminal variable resistor that changes its resistance depending on the previous charge flow, allow a new degree of freedom for this concept: a local memory that supports transient connectivity patterns in oscillator networks. On the basis of the probability distribution of the resistance switching process of Ag-doped titanium dioxide memristive devices, a local plasticity model is proposed, which causes an autonomous phase and frequency locking in an oscillator network. To illustrate the performance of the proposed computing paradigm, the temporal binding problem is investigated in a network of memristively coupled self-sustained van der Pol oscillators. We show evidence that the implemented network allows achievement of the transition from asynchronous to multiple synchronous states, which opens a new pathway toward the construction of cognitive electronics.
机译:人脑能够在庞大且大规模的神经元并行网络中整合大量信息,这些神经元网络分为功能特定的区域,例如视觉皮层,听觉皮层或背外侧前额叶皮层。这些区域中的每个区域都作为上下文相关,自组织且短暂的子网参与,每0.5到2 s注意力的变化就会移动该子网。这导致认知神经科学中最令人费解的问题之一,即众所周知的“绑定问题”。神经同步的概念试图通过使用相干状态对信息进行编码来解释问题,该相干状态在时间上会图案化神经活动。我们证明了忆阻器件,即一个可根据先前的电荷流改变其电阻的两端可变电阻器,为该概念提供了新的自由度:支持振荡器网络中瞬态连接模式的本地存储器。根据掺银二氧化钛忆阻器件电阻切换过程的概率分布,提出了局部可塑性模型,该模型在振荡器网络中引起了自发的相位和频率锁定。为了说明所提出的计算范例的性能,在忆阻耦合自保持范德波尔振荡器的网络中研究了时间约束问题。我们证明了已实现的网络可以实现从异步状态到多个同步状态的过渡,这为认知电子学的构建开辟了一条新途径。

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