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神经形态 VLSI 中的生物物理神经元动力学的同化。

Assimilation of Biophysical Neuronal Dynamics in Neuromorphic VLSI.

出版信息

IEEE Trans Biomed Circuits Syst. 2017 Dec;11(6):1258-1270. doi: 10.1109/TBCAS.2017.2776198.

Abstract

Representing the biophysics of neuronal dynamics and behavior offers a principled analysis-by-synthesis approach toward understanding mechanisms of nervous system functions. We report on a set of procedures assimilating and emulating neurobiological data on a neuromorphic very large scale integrated (VLSI) circuit. The analog VLSI chip, NeuroDyn, features 384 digitally programmable parameters specifying for 4 generalized Hodgkin-Huxley neurons coupled through 12 conductance-based chemical synapses. The parameters also describe reversal potentials, maximal conductances, and spline regressed kinetic functions for ion channel gating variables. In one set of experiments, we assimilated membrane potential recorded from one of the neurons on the chip to the model structure upon which NeuroDyn was designed using the known current input sequence. We arrived at the programmed parameters except for model errors due to analog imperfections in the chip fabrication. In a related set of experiments, we replicated songbird individual neuron dynamics on NeuroDyn by estimating and configuring parameters extracted using data assimilation from intracellular neural recordings. Faithful emulation of detailed biophysical neural dynamics will enable the use of NeuroDyn as a tool to probe electrical and molecular properties of functional neural circuits. Neuroscience applications include studying the relationship between molecular properties of neurons and the emergence of different spike patterns or different brain behaviors. Clinical applications include studying and predicting effects of neuromodulators or neurodegenerative diseases on ion channel kinetics.

摘要

对神经元动力学和行为的生物物理学进行表示,为理解神经系统功能的机制提供了一种基于分析-综合的原则性方法。我们报告了一组程序,这些程序可以在神经形态的超大规模集成电路 (VLSI) 电路上吸收和模拟神经生物学数据。该模拟 VLSI 芯片 NeuroDyn 具有 384 个可数字编程的参数,可指定通过 12 个基于电导的化学突触耦合的 4 个广义 Hodgkin-Huxley 神经元。这些参数还描述了离子通道门控变量的反转电位、最大电导和样条回归动力学函数。在一组实验中,我们将芯片上一个神经元的膜电位记录到 NeuroDyn 所基于的模型结构上,使用已知的电流输入序列对其进行建模。除了由于芯片制造中的模拟不完美而导致的模型误差之外,我们还得出了编程参数。在一组相关实验中,我们通过使用从细胞内神经记录中进行数据同化提取的参数进行估计和配置,在 NeuroDyn 上复制了鸣禽单个神经元的动力学。对详细生物物理神经动力学的忠实模拟将使 NeuroDyn 能够用作研究功能神经回路的电和分子特性的工具。神经科学应用包括研究神经元的分子特性与不同尖峰模式或不同大脑行为的出现之间的关系。临床应用包括研究和预测神经调节剂或神经退行性疾病对离子通道动力学的影响。

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