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Dynamics of VLSI analog decoupled neurons

机译:VLSI模拟解耦神经元的动力学

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Electronic devices modeling the behavior of neural systems interacting with a natural environment are mainly composed of sensory devices and coupled spiking neural networks. In this context, the possibility to apply theoretical predictions on populations of analog VLSI neurons is aimed in view of their quantitative control. The purpose of this work is to state robust and scalable methods to obtain a quantitative match between experiments and theory for the spiking activity of non-interacting analog VLSI neurons. The decoupled neural dynamics is the starting point for the quantitative description of network coupled conditions. An empirical measure of the capacity, by which the VLSI neurons integrate the currents, an automatic calibration of the injected currents and few basic formulas allow the complete control of the neural dynamics.
机译:模拟与自然环境相互作用的神经系统行为的电子设备主要由感觉设备和耦合的尖峰神经网络组成。在这种情况下,鉴于其定量控制,旨在将理论预测应用于模拟VLSI神经元的种群。这项工作的目的是陈述鲁棒且可扩展的方法,以在实验和理论之间获得定量的匹配,以实现非交互模拟VLSI神经元的尖峰活动。解耦的神经动力学是定量描述网络耦合条件的起点。 VLSI神经元对电流进行积分的能力的经验度量,注入电流的自动校准以及一些基本公式允许对神经动力学进行完全控制。

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